ME T H O D S
IN
MO L E C U L A R BI O L O G Y
Series Editor John M. Walker School of Life Sciences University of Hert...
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ME T H O D S
IN
MO L E C U L A R BI O L O G Y
Series Editor John M. Walker School of Life Sciences University of Hertfordshire Hatfield, Hertfordshire, AL10 9AB, UK
For other titles published in this series, go to www.springer.com/series/7651
TM
Hepatocytes Methods and Protocols
Edited by
Patrick Maurel INSERM, Université Montpellier 1, and Institut de Recherche en Biothérapie, Montpellier, France
Editor Patrick Maurel INSERM, Université Montpellier 1, and Institut de Recherche en Biothérapie INSERM U632 Physiopathologie Hépatique 1919 rte de Mende 34293 Montpellier France patrick.maurel@inserm.fr
ISSN 1064-3745 e-ISSN 1940-6029 ISBN 978-1-60761-687-0 e-ISBN 978-1-60761-688-7 DOI 10.1007/978-1-60761-688-7 Springer New York Dordrecht Heidelberg London Library of Congress Control Number: 2010921223 © Springer Science+Business Media, LLC 2010 All rights reserved. This work may not be translated or copied in whole or in part without the written permission of the publisher (Humana Press, c/o Springer Science+Business Media, LLC, 233 Spring Street, New York, NY 10013, USA), except for brief excerpts in connection with reviews or scholarly analysis. Use in connection with any form of information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed is forbidden. The use in this publication of trade names, trademarks, service marks, and similar terms, even if they are not identified as such, is not to be taken as an expression of opinion as to whether or not they are subject to proprietary rights. While the advice and information in this book are believed to be true and accurate at the date of going to press, neither the authors nor the editors nor the publisher can accept any legal responsibility for any errors or omissions that may be made. The publisher makes no warranty, express or implied, with respect to the material contained herein. Cover illustration: Expression and distribution of cytoskeletal elements and cell adhesion molecules in primary cultures of human hepatocytes maintained in a sandwich culture configuration. Immunofluorescent images showing in vivo-like distribution of actin microfilaments (upper left panel), microtubules (upper right panel), E-cadherin (lower left panel) and gap junctions (Cx-32) (lower right panel). Phenotypic expression of the cytoskeleton and cell adhesion proteins in vitro is determined, in part, by the capacity of the cells to form cell-cell contacts and intercellular communications. For more information on the isolation and culture of primary human hepatocytes see Chapter 3. Printed on acid-free paper Humana Press is part of Springer Science+Business Media (www.springer.com)
Foreword Primary human hepatocytes offer a unique model for investigating basic mechanisms of tissue differentiation, proliferation, and viability as well as a privileged tool for testing drug metabolism, efficacy, and toxicity. Thus, dissecting the extracellular and intracellular signals which drive primary hepatocyte biology has allowed, in combination with in vivo studies, a much better understanding of the interplay between cell differentiation, viability, metabolism, and proliferation. In fact, investigating primary hepatocyte biology offers a concrete case of inter- and multidisciplinary research, the results of which expand far beyond the liver and have a profound impact on the other fields of biology. In this context, what is unique in the review articles edited by Dr. Patrick Maurel in this textbook is the interdisciplinary vision which is shown and the combination of academic- and industry-driven perspectives. Thus, the authors offer a most interesting and comprehensive overview of the various assets and challenges of primary hepatocyte culture, highlighting major technical problems, such as cryopreservation, the use of primary hepatocytes for cell therapy, etc. Importantly, they also provide the most updated highlights on the fundamental biological processes which drive liver development, liver stem cell identification, etc., the comprehension of which is absolutely necessary to reinforce the potential of primary hepatocyte culture. Finally, this textbook perfectly demonstrates how primary hepatocytes can be extremely useful for industrial partners who aim to investigate the efficacy, metabolism, and toxicity of their drugs in various settings. Overall, this textbook should urge to reinforce our capacity to obtain primary human hepatocytes in the context of liver resection and transplantation. Indeed, one can only view as a paradox such clear illustration of the potential of this material and the major present difficulties to get access to it. This major issue will only be solved in the context of consortia, organized in a public–private-driven approach. Christian Bréchot Mérieux Alliance France
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Preface The liver consists of different cell types including hepatocytes, endothelial cells, stellate cells, Kupffer cells, pit cells, and bile duct cells. Hepatocytes, the parenchymal cells, account for approximately 80% of the liver mass. Although other hepatic cells play a significant role in various aspects of liver physiopathology, hepatocytes exhibit unrivaled complexity and diversity of functions. They produce the majority of circulating plasma proteins including transporters (such as albumin, ceruloplasmin, transferrin, and lipoproteins), protease inhibitors (α1 -antitrypsin, antithrombin, and α2 -macroglobulin), blood coagulation factors (fibrinogen, prothrombin, factors V, VII, IX, X, etc.), and modulators of immune complexes and inflammation (complement C3, C-reactive protein). Hepatocytes control the homeostasis of fuel molecules such as glucose/glycogen and fatty acids including triglycerides as well as other essential compounds such as cholesterol, bile acids, and vitamins A and D. They metabolize amino acids, metals such as copper and iron, and endogenous compounds such as heme and bilirubin. In addition, hepatocytes play a critical role in detoxifying xenobiotics such as diet and environmental pollutants (plant, fungal, and animal toxins, pesticides, herbicides, derivatives of domestic and industrial combustions, organic solvents, dyes, preservatives, etc.) and, more importantly, drugs. Hence, hepatocyte function strongly impacts on the pharmacokinetics, side effects, and toxicity of drugs (1, 2). As highly differentiated cells, hepatocytes rarely divide in the adult individual under normal (healthy) conditions. However, it is known since antiquity that the liver possesses a remarkable ability to regenerate after partial hepatectomy. This process of regeneration is primarily dependent on the proliferation of hepatocytes and other hepatic cell types, as documented by numerous studies in rodent models (3). Although partial hepatectomy aimed at treating some liver pathologies may be the source of serious failure (4), it is certainly not the primary cause of liver injury in mankind. Indeed, the major etiologic agents of liver diseases are xenobiotics (such as amatoxins, carbon tetrachloride, and cyanides), drugs (acetaminophen, isoniazide, halothane, estrogens, etc.) (5, 6), alcohol (7–9), hepatitis A, B, C, D, and E viruses (10–14), and immune and genetic disorders (15–17). In a variety of human liver diseases, notably in the cirrhotic stage, proliferation of senescent hepatocytes is inhibited. This results either from telomere shortening, chronic inflammation, presence of growth factors, and presence of DNA-damaging agents (reactive oxygen species and nitrogen species) or from combinations of these different agents (18). Under these conditions, the liver regeneration relies on the emergence of a heterogeneous population of small poorly differentiated bipotent progenitor cells, named oval cells in rodents (19) and liver progenitor cells (LPC) in man (20). The recruitment of LPC in the diseased liver is marked by the ductular reaction and increases with the extent of liver injury and inflammation (21–23). These progenitors, the origin of which is still a matter of debate, accumulate in the portal or periportal zones of the liver acinus (canal of Hering), invade the parenchyma generally in the form of neoductules and differentiate into mature hepatocytes and cholangiocytes.
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It is not surprising that these exceptional functional, metabolic, and proliferative properties of hepatocytes have been the object of a tremendous interest from the scientific community. Hence, numerous studies have been carried out in animal hepatocytes (mostly rodents). However, it is now evident that species specificity is an important factor (even within the rodent species), so that direct investigations on human hepatocytes are mandatory to avoid risky extrapolations from animal studies (24). In addition, the possibility of using human hepatocytes for the biotherapy of liver diseases has generated a huge interest within the last decade. The emphasis in this volume has therefore been placed on human hepatocyte models (although data on animal hepatocytes are presented in some chapters), but I believe that the information provided will be useful for those working on hepatocytes from other species. The aim of this volume is to provide the reader with methods, technical protocols, and review chapters focusing on selected areas of hepatocyte biology including isolation, culture, differentiation and stem cells, and hepatocyte use in clinical, basic, and applied research. Here is a brief survey of the content of this volume: A number of hepatocyte culture models have been designed, developed, and improved in order to maintain these cells in a high level of differentiation (see Chapters 1–3, 6, 7, and 23), while intense efforts have also been placed on the cryopreservation of these precious cells (see Chapters 4 and 5). Hence, the primary culture of adult human hepatocyte has become the gold standard model in different fields such as endogenous compound metabolism (see Chapters 19 and 22), drug/xenobiotic metabolism and transport (see Chapters 1 and 15–18), drug side effects (see Chapters 15 and 16), and drug toxicity (see Chapter 21) (25, 26). Interestingly, recent developments have led to the discovery of a human hepatoma cell line named HepaRG that, in contrast to any other existing cell lines, does differentiate in vitro to hepatocyte-like cells that exhibit a series of phenotypic markers close to those observed in normal human hepatocytes, notably in terms of detoxication (see Chapters 1, 13, and 20) (27). Further investigations point to other applications of primary hepatocytes in the field of virology (see Chapters 24 and 25) and liver biotherapy including hepatocyte transplantation and bioartificial liver devices (see Chapters 2, 10, 28, and 29) (28–30). Although isolation of hepatocytes from the human liver does not represent a challenge any more, the dramatic shortage of human liver of adequate quality for this purpose is now a real problem. It has therefore become mandatory to develop new alternative sources of human hepatocytes. The possibility to generate a wide diversity of tissue-specific cells from the differentiation of adult and embryonic stem cells, including hepatocytes, represents promising opportunities (31). Indeed, recent publications reveal that hepatocyte-like cells can be generated from the differentiation of intrahepatic progenitor cells, embryonic stem cells, adult multipotent progenitor cells, hematopoietic stem cells, mesenchymal stem cells, and induced pluripotent stem cells (see Chapters 8–12 and 14) (32). Moreover, animal studies suggest that progenitor cells could be the biotherapeutic agents for the treatment of liver disease in the near future (see Chapters 10, 26, and 27) (33). In conclusion, this volume will be useful to those who are currently using or envisaging to use human (or animal) hepatocytes to investigate any aspect of liver physiopathology or who are interested in the liver development and/or liver stem cells and liver biotherapy. Unfortunately, it has not been possible to cover all the contributions of hepatocytes to liver physiopathology nor to avoid some overlaps between chapters. I would like to express my sincere apologies to those readers who may regret such omissions or redundancies. Yet, it is also important at this stage to emphasize what has been voluntarily omitted in this volume, i.e., hepatoma cell lines such as HepG2, Huh-7, and Hep3B and derived
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cellular clones. Such cell lines are being used routinely in basic research for investigating different aspects of liver physiopathology including gene regulation, virus replication, endogenous metabolism, and cell cycle control. Although these cell lines represent very useful research tools and allow the gathering of valuable and important information, they are still too often improperly referred to as human hepatocytes. Such a confusing statement must be avoided. Indeed, these cells are not hepatocytes. They are dedifferentiated and exhibit abnormal hepatic phenotype with deregulated proliferation, defects in gene expression, perturbed signaling pathways and host anti-viral responses, deficient endogenous and xenobiotic metabolism, impaired responses to cytokines, growth factors, infectious agents, etc. Finally, I would like to express my deep gratitude to all contributors from both academics and industry who are recognized experts in the field of hepatocytes, to Christian Bréchot for writing the Foreword, and to the Series Editor, John Walker, for his help and guidance. Patrick Maurel
References 1. Schiff, L. and Schiff, E.R., eds. (1993) Diseases of the Liver, 7th ed., Philadelphia: J.B. Lippincott, vols. 1 and 2. 2. Zakim, D., Boyer, T.D., eds. (1996) Hepatology: A Textbook of Liver Disease, 3rd ed., Philadelphia: WB Saunders, vols. I and II. 3. Michalopoulos, G.K. (2007) Liver regeneration. J. Cell Physiol. 213, 286–300. 4. Garcea, G. and Maddern, G.J. (2009) Liver failure after major hepatic resection. J Hepatobiliary Pancreat. Surg. 16, 145–155. 5. Hussaini, S.H. and Farrington, E.A. (2007) Idiosyncratic drug-induced liver injury: an overview. Expert Opin. Drug Saf. 6, 673–684. 6. Papay, J.I., Clines D, Rafi R, et al. (2009) Drug-Induced Liver Injury Following Positive Drug Rechallenge. Regul. Toxicol. Pharmacol. 54, 84–90. 7. Albano, E. (2008) New concepts in the pathogenesis of alcoholic liver disease. Expert Rev. Gastroenterol. Hepatol. 2, 749–759. 8. Lieber, C.S. (2004) Alcoholic fatty liver: its pathogenesis and mechanism of progression to inflammation and fibrosis. Alcohol 34, 9–19. 9. Reuben, A. (2006) Alcohol and the liver. Curr. Opin. Gastroenterol. 22, 263–271. 10. Brundage, S.C. and Fitzpatrick, A.N., and Hepatitis, A. (2006) Am. Fam. Physician 73, 2162–2168.
11. Purcell, R.H. and Emerson, S.U. (2008) Hepatitis E: an emerging awareness of an old disease. J. Hepatol. 48, 494–503. 12. Rizzetto, M. (2009) Hepatitis D: thirty years after. J. Hepatol. 50, 1043–1050. 13. Soriano, V., Peters, M.G., and Zeuzem, S. (2009) New therapies for hepatitis C virus infection. Clin. Infect. Dis. 48, 313–320. 14. Zoulim, F., Radenne, S., and Ducerf, C. (2008) Management of patients with decompensated hepatitis B virus association cirrhosis. Liver Transpl. 14 Suppl 2, S1–S7. 15. Adams, P.C., Passmore, L., Chakrabarti, S, et al. (2006) Liver diseases in the hemochromatosis and iron overload screening study. Clin. Gastroenterol. Hepatol. 4, 918–923. 16. Bogdanos, D.P., Invernizzi, P., Mackay, I.R., and Vergani, D. (2008) Autoimmune liver serology: current diagnostic and clinical challenges. World J. Gastroenterol. 14, 3374–3387. 17. LaRusso, N.F., Shneider, B.L., Black, D., et al. (2006) Primary sclerosing cholangitis: summary of a workshop. Hepatology 44, 746–764. 18. Roskams, T. (2006) Liver stem cells and their implication in hepatocellular and cholangiocarcinoma. Oncogene 25, 3818–3822. 19. Sell, S. (2001) Heterogeneity and plasticity of hepatocyte lineage cells. Hepatology 33, 738–750.
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20. Roskams, T.A., Theise, N.D., Balabaud, C., et al. (2004) Nomenclature of the finer branches of the biliary tree: canals, ductules, and ductular reactions in human livers. Hepatology 39, 1739–1745. 21. Libbrecht, L., Desmet, V., Van Damme, B., and Roskams, T. (2000) Deep intralobular extension of human hepatic ‘progenitor cells’ correlates with parenchymal inflammation in chronic viral hepatitis: can ‘progenitor cells’ migrate? J. Pathol. 192, 373–378. 22. Libbrecht, L. and Roskams, T. (2002) Hepatic progenitor cells in human liver diseases. Semin. Cell Dev. Biol. 13, 389–396. 23. Lowes, K.N., Brennan, B.A., Yeoh, G.C., and Olynyk, J.K. (1999) Oval cell numbers in human chronic liver diseases are directly related to disease severity. Am. J. Pathol. 154, 537–541. 24. Jelnes, P., Santoni-Rugiu, E., Rasmussen, M., et al. (2007) Remarkable heterogeneity displayed by oval cells in rat and mouse models of stem cellmediated liver regeneration. Hepatology 45, 1462–1470. 25. Guillouzo, A. and Guguen-Guillouzo, C. (2008) Evolving concepts in liver tissue modeling and implications for in vitro toxicology. Expert Opin. Drug Metab. Toxicol. 4, 1279–1294. 26. Dalvie, D., Obach, R.S., Kang, P., et al. (2009) Assessment of three human in vitro systems in the generation of major
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human excretory and circulating metabolites. Chem. Res. Toxicol. 22, 357–368. Parent, R., Marion, M.J., Furio, L., Trepo, C., and Petit, M.A. (2004) Origin and characterization of a human bipotent liver progenitor cell line. Gastroenterology 126, 1147–1156. Dagher, I., Nguyen, T.H., Groyer-Picard, M.T., et al. (2009) Efficient hepatocyte engraftment and long-term transgene expression after reversible portal embolization in nonhuman primates. Hepatology 49, 950–959. Ito, M., Nagata, H., Miyakawa, S., and Fox, I.J. (2009) Review of hepatocyte transplantation. J. Hepatobiliary Pancreat. Surg. 16, 97–100. Kobayashi, N. (2009) Life support of artificial liver: development of a bioartificial liver to treat liver failure. J. Hepatobiliary Pancreat. Surg. 16, 113–117. Zaret, K.S. and Grompe, M. (2008) Generation and regeneration of cells of the liver and pancreas. Science 322, 1490–1494. Sancho-Bru, P., Najimi, M., Caruso, M., et al. (2009) Stem and progenitor cells for liver repopulation: can we standardise the process from bench to bedside? Gut 58, 594–603. Kakinuma, S., Nakauchi, H., and Watanabe, M. (2009) Hepatic stem/progenitor cells and stem-cell transplantation for the treatment of liver disease. J Gastroenterol. 44, 167–172.
Contents Foreword . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
v
Preface . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
vii
Contributors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
xv
1.
2.
3.
General Review on In Vitro Hepatocyte Models and Their Applications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Christiane Guguen-Guillouzo and Andre Guillouzo Human Foetal Hepatocytes: Isolation, Characterization, and Transplantation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Anne Weber, Thomas Touboul, Sylvie Mainot, Julie Branger, and Dominique Mahieu-Caputo Isolation and Culture of Primary Hepatocytes from Resected Human Liver Tissue . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Edward L. LeCluyse and Eliane Alexandre
1
41
57
4.
Optimisation of the Cryopreservation of Primary Hepatocytes . . . . . . . . . . Nicola J. Hewitt
5.
Cryopreservation of Human Hepatocytes for Clinical Use . . . . . . . . . . . . 107 Ragai R. Mitry, Sharon C. Lehec, and Robin D. Hughes
6.
Hepatocyte Differentiation . . . . . . . . . . . . . . . . . . . . . . . . . . . . 115 Katy M. Olsavsky Goyak, Elizabeth M. Laurenzana, and Curtis J. Omiecinski
7.
Reversible Manipulation of Apoptosis Sensitivity in Cultured Hepatocytes by Matrix-Mediated Manipulation of Signaling Activities . . . . . . 139 Patricio Godoy, Markus Schug, Alexander Bauer, and Jan G. Hengstler
8.
Markers and Signaling Factors for Stem Cell Differentiation to Hepatocytes: Lessons from Developmental Studies . . . . . . . . . . . . . . 157 Frédéric Lemaigre
9.
Hepatic Stem Cells . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 167 Robert E. Schwartz and Catherine Verfaillie
10.
Hepatic Stem Cells and Liver Development . . . . . . . . . . . . . . . . . . . . 181 Nalu Navarro-Alvarez, Alejandro Soto-Gutierrez, and Naoya Kobayashi
11.
Generation of Hepatocytes from Human Embryonic Stem Cells . . . . . . . . . 237 Neta Lavon
xi
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Contents
12.
Isolation and Culture of Adult Human Liver Progenitor Cells: In Vitro Differentiation to Hepatocyte-Like Cells . . . . . . . . . . . . . . . . . . . . . 247 Sabine Gerbal-Chaloin, Cédric Duret, Edith Raulet, Francis Navarro, Pierre Blanc, Jeanne Ramos, Patrick Maurel, and Martine Daujat-Chavanieu
13.
The HepaRG Cell Line: Biological Properties and Relevance as a Tool for Cell Biology, Drug Metabolism, and Virology Studies . . . . . . . . . . . . 261 Marie-Jeanne Marion, Olivier Hantz, and David Durantel
14.
Transdifferentiation of Pancreatic Cells to Hepatocytes . . . . . . . . . . . . . . 273 Chia-Ning Shen and David Tosh
15.
Evaluation of Drug Metabolism, Drug–Drug Interactions, and In Vitro Hepatotoxicity with Cryopreserved Human Hepatocytes . . . . . . . . . . . . . 281 Albert P. Li
16.
The Use of Human Hepatocytes to Investigate Drug Metabolism and CYP Enzyme Induction . . . . . . . . . . . . . . . . . . . . . . . . . . . 295 Sylvie Klieber, François Torreilles, François Guillou, and Gérard Fabre
17.
The Use of Hepatocytes to Investigate UDP-Glucuronosyltransferases and Sulfotransferases . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 309 Sylvie Fournel-Gigleux, Michael W.H. Coughtrie, Mohamed Ouzzine, and Jacques Magdalou
18.
The Use of Hepatocytes to Investigate Drug Uptake Transporters . . . . . . . . 327 Kazuya Maeda and Yuichi Sugiyama
19.
Metabonomic Studies on Human Hepatocyte in Primary Culture . . . . . . . . 355 Vincent Croixmarie, Thierry Umbdenstock, Olivier Cloarec, Amélie Moreau, Jean-Marc Pascussi, Yannick Parmentier, Claire Boursier-Neyret, and Bernard Walther
20.
The Application of HepRG Cells in Evaluation of Cytochrome P450 Induction Properties of Drug Compounds . . . . . . . . . . . . . . . . . . . . 375 Tommy B. Andersson
21.
The Use of Hepatocytes to Investigate Drug Toxicity . . . . . . . . . . . . . . 389 María José Gómez-Lechón, José V. Castell, and María Teresa Donato
22.
The Use of Human Hepatocytes to Investigate Bile Acid Synthesis . . . . . . . . 417 Ewa C. S. Ellis and Lisa-Mari Nilsson
23.
Use of Human Hepatocytes to Investigate Blood Coagulation Factor . . . . . . 431 Christine Biron-Andréani, Edith Raulet, Lydiane Pichard-Garcia, and Patrick Maurel
24.
Use of Human Hepatocytes to Investigate HCV Infection . . . . . . . . . . . . 447 Lydiane Pichard-Garcia, Philippe Briolotti, Dominique Larrey, Antonio Sa-Cunha, Bertrand Suc, Sylvain Laporte, and Patrick Maurel
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25.
The Use of Hepatocytes to Investigate HDV Infection: The HDV/HepaRG Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . 463 Camille Sureau
26.
Rodent Models of Liver Repopulation . . . . . . . . . . . . . . . . . . . . . . 475 Helène Gilgenkrantz
27.
Chimeric Mice with Humanized Liver: Tools for the Study of Drug Metabolism, Excretion, and Toxicity . . . . . . . . . . . . . . . . . . . 491 Stephen C. Strom, Julio Davila, and Markus Grompe
28.
Bioartificial Liver Support Systems . . . . . . . . . . . . . . . . . . . . . . . . 511 Gesine Pless
29.
Human Hepatocyte Transplantation . . . . . . . . . . . . . . . . . . . . . . . 525 Anil Dhawan, Stephen C. Strom, Etienne Sokal, and Ira J. Fox
Subject Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 535
Contributors ELIANE ALEXANDRE • Kaly-Cell, Bioparc, Illkirch, France TOMMY B. ANDERSSON • Clinical Pharmacology and DMPK, AstraZeneca R&D, Mölndal, Sweden; Department of Physiology and Pharmacology, Section of Pharmacogenetics, Karolinska Institutet, Stockholm, Sweden ALEXANDER BAUER • Leibniz Research Centre for Working Environment and Human Factors (IfADo), Dortmund, Germany CHRISTINE BIRON-ANDRÉANI • CHU Montpellier, Service d’Hématologie, Hôpital Saint Eloi, Montpellier, France PIERRE BLANC • INSERM U632, Hepatic Physiopathology, Montpellier, France; Université Montpellier 1, Montpellier, France; CHU Montpellier, Institut de Recherche en Biothérapie, Hôpital Saint Eloi, Montpellier, France; CHU Montpellier, Service Médicochirurgical des Maladies du foie et de Transplantation Hépatique, Hôpital Saint Eloi, Montpellier, France CLAIRE BOURSIER-NEYRET • Technologie Servier, Orléans, France PHILIPPE BRIOLOTTI • INSERM U632, Hepatic Physiopathology, Montpellier, France; Université Montpellier 1, Montpellier, France; CHU Montpellier, Institut de Recherche en Biothérapie, Hôpital Saint Eloi, Montpellier, France JOSÉ V. CASTELL • Unidad de Hepatología Experimental, Centro de Investigación, Hospital La Fe, Valencia, Spain; CIBERHEPAD, FIS, Spain; Departamento de Bioquímica y Biología Molecular, Facultad de Medicina, Universidad de Valencia, Valencia, Spain OLIVIER CLOAREC • School of Biological Sciences, Royal University of London, Egham, Surrey, UK MICHAEL W.H. COUGHTRIE • Division of Medical Sciences, Ninewells Hospital and Medical School, University of Dundee, Dundee, UK VINCENT CROIXMARIE • Technologie Servier, Orléans, France MARTINE DAUJAT-CHAVANIEU • INSERM U632, Hepatic Physiopathology, Montpellier, France; Université Montpellier 1, Montpellier, France; CHU Montpellier, Institut de Recherche en Biothérapie, Hôpital Saint Eloi, Montpellier, France JULIO DAVILA • Pfizer Inc, PGRD, St. Louis Laboratories, Chesterfield, MO, USA ANIL DHAWAN • King’s Cell Isolation Unit, King’s College Hospital, London, UK MARÍA TERESA DONATO • Unidad de Hepatología Experimental, Centro de Investigación, Hospital La Fe, Valencia, Spain; CIBERHEPAD, FIS, Spain; Departamento
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Contributors
de Bioquímica y Biología Molecular, Facultad de Medicina, Universidad de Valencia, Valencia, Spain DAVID DURANTEL • INSERM U871, Molecular physiopathology and new treatments of viral hepatitis, Lyon, France; Université de Lyon, and IFR62, Lyon, France; Hospices Civils de Lyon (HCL), Lyon, France CÉDRIC DURET • INSERM U632, Hepatic Physiopathology, Montpellier, France; Université Montpellier 1, Montpellier, France; CHU Montpellier, Institut de Recherche en Biothérapie, Hôpital Saint Eloi, Montpellier, France EWA C.S. ELLIS • Karolinska Institute, Department of Clinical Science, Intervention and Technology (CLINTEC), Division of Transplantation Surgery, Unit for Liver Transplantation, Karolinska University Hospital Huddinge, Stockholm, Sweden GÉRARD FABRE • Discovery Metabolism and Pharmacokinetics Safety, Sanofi-Aventis Recherche, Montpellier, France SYLVIE FOURNEL-GIGLEUX • CNRS, UMR 7561, Faculté de Médecine, CNRS-Université Henri Poincaré Nancy I, Vandoeuvre-lès-Nancy, France IRA J. FOX • Department of Surgery, University of Nebraska Medical Center, Omaha, NE, USA SABINE GERBAL-CHALOIN • INSERM U632, Hepatic Physiopathology, Montpellier, France; Université Montpellier 1, Montpellier, France; CHU Montpellier, Institut de Recherche en Biothérapie, Hôpital Saint Eloi, Montpellier, France HELÈNE GILGENKRANTZ • INSERM U567, CNRS UMR 81-04, Université Paris-Descartes Institut Cochin, Paris, France PATRICIO GODOY • Leibniz Research Centre for Working Environment and Human Factors (IfADo), Dortmund, Germany MARÍA JOSÉ GÓMEZ-LECHÓN • Unidad de Hepatología Experimental, Centro de Investigación, Hospital La Fe, Valencia, Spain; CIBERHEPAD, FIS, Spain KATY M. OLSAVSKY GOYAK • Center for Molecular Toxicology & Carcinogenesis and Department of Veterinary and Biomedical Sciences, The Pennsylvania State University, University Park, PA, USA; ExxonMobil Biomedical Sciences, Inc., Annandale, NJ, USA MARKUS GROMPE • Oregon Stem Cell Center, Department of Molecular and Medical Genetics, Oregon Health Science University, Portland, OR, USA FRANÇOIS GUILLOU • Discovery Metabolism and Pharmacokinetics Safety, Sanofi-Aventis Recherche, Montpellier, France CHRISTIANE GUGUEN-GUILLOUZO • INSERM U522, Régulation des équilibres fonctionnels du foie normal et pathologique, Hopital Pontchaillou, Rennes, France ANDRE GUILLOUZO • INSERM U620, Detoxication et Réparation Tissulaire, Faculté des Sciences Pharmaceutiques et Biologiques, Université de Rennes 1, Rennes, France OLIVIER HANTZ • INSERM U871, Molecular physiopathology and new treatments of viral hepatitis, Lyon, France; Université de Lyon, and IFR62, Lyon, France
Contributors
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JAN G. HENGSTLER • Leibniz Research Centre for Working Environment and Human Factors (IfADo), Dortmund, Germany NICOLA J. HEWITT • Scientific Writing Services, Erzhausen, Germany, nickyhewittltd@yahoo.co.uk ROBIN D. HUGHES • Institute of Liver Studies, King’s College Hospital and King’s College London School of Medicine, London, UK SYLVIE KLIEBER • Discovery Metabolism and Pharmacokinetics Safety, Sanofi-Aventis Recherche, Montpellier, France NAOYA KOBAYASHI • Department of Surgery, Okayama University Graduate School of Medicine and Dentistry, Okayama, Japan SYLVAIN LAPORTE • CHU Nîmes, Chirurgie Viscérale et Digestive, Hopital Caremau, Nîmes, France DOMINIQUE LARREY • INSERM U632, Hepatic Physiopathology, Montpellier, France; Université Montpellier 1, Montpellier, France; CHU Montpellier, Institut de Recherche en Biothérapie, Service de Gastroentérologie, Hôpital Saint Eloi, Montpellier, France ELIZABETH M. LAURENZANA • Center for Molecular Toxicology & Carcinogenesis and Department of Veterinary and Biomedical Sciences, The Pennsylvania State University, University Park, PA, USA NETA LAVON • Department of Genetics, The Hebrew University of Jerusalem, Jerusalem, Israel EDWARD L. LECLUYSE • CellzDirect | Invitrogen Corp., Durham, NC, USA SHARON C. LEHEC • Institute of Liver Studies, King’s College Hospital and King’s College London School of Medicine, London, UK FRÉDÉRIC LEMAIGRE • de Duve Institute, Université Catholique de Louvain, Brussels, Belgium ALBERT P. LI • Advanced Pharmaceutical Sciences Inc. and In Vitro ADMET Laboratories L.L.C., Columbia, MD, USA KAZUYA MAEDA • Department of Molecular Pharmacokinetics, Graduate School of Pharmaceutical Sciences, The University of Tokyo, Tokyo, Japan JACQUES MAGDALOU • CNRS, UMR 7561, Faculté de Médecine, CNRS-Université Henri Poincaré Nancy I, Vandoeuvre-lès-Nancy, France DOMINIQUE MAHIEU-CAPUTO • INSERM U972, Université Paris-Sud, Hôpital Kremlin-Bicêtre, Le Kremlin-Bicêtre, France; Hôpital Bichat - AP-HP, Université Paris VII, Paris, France SYLVIE MAINOT • INSERM U972, Université Paris-Sud, Hôpital Kremlin-Bicêtre, Le Kremlin-Bicêtre, France MARIE-JEANNE MARION • INSERM U871, Molecular physiopathology and new treatments of viral hepatitis, Lyon, France; Université de Lyon, and IFR62, Lyon, France
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PATRICK MAUREL • INSERM U632, Hepatic Physiopathology, Montpellier, France; Université Montpellier 1, Montpellier, France; CHU Montpellier, Institut de Recherche en Biothérapie, Hôpital Saint Eloi, Montpellier, France RAGAI R. MITRY • Institute of Liver Studies, King’s College Hospital and King’s College London School of Medicine, London, UK AMÉLIE MOREAU • INSERM U632, Physio-pathologie hépatique, Montpellier, France FRANCIS NAVARRO • INSERM U632, Hepatic Physiopathology, Montpellier, France; Université Montpellier 1, Montpellier, France; CHU Montpellier, Institut de Recherche en Biothérapie, Hôpital Saint Eloi, Montpellier, France; CHU Montpellier, Service Médicochirurgical des Maladies du foie et de Transplantation Hépatique, Hôpital Saint Eloi, Montpellier, France NALU NAVARRO-ALVAREZ • Department of Surgery, Okayama University Graduate School of Medicine and Dentistry, Okayama, Japan LISA-MARI NILSSON • Karolinska Institute, Department of Laboratory Medicine, Division of Clinical Chemistry, Karolinska University Hospital Huddinge, Stockholm, Sweden CURTIS J. OMIECINSKI • Center for Molecular Toxicology & Carcinogenesis and Department of Veterinary and Biomedical Sciences, The Pennsylvania State University, University Park, PA, USA MOHAMED OUZZINE • CNRS, UMR 7561, Faculté de Médecine, CNRS-Université Henri Poincaré Nancy I, Vandoeuvre-lès-Nancy, France YANNICK PARMENTIER • Technologie Servier, Orléans, France JEAN-MARC PASCUSSI • INSERM U632, Physio-pathologie hépatique, Montpellier, France L YDIANE PICHARD-GARCIA • INSERM U632, Hepatic Physiopathology, Montpellier, France; Université Montpellier 1, Montpellier, France; CHU Montpellier, Institut de Recherche en Biothérapie, Hôpital Saint Eloi, Montpellier, France GESINE PLESS • Institut für Physiologische Chemie, Universitätsklinikum Essen, Essen, Germany JEANNE RAMOS • INSERM U632, Hepatic Physiopathology, Montpellier, France; Université Montpellier 1, Montpellier, France; CHU Montpellier, Institut de Recherche en Biothérapie, Hôpital Saint Eloi, Montpellier, France; CHU Montpellier, Service d’Anatomopathologie, Hôpital Saint Eloi, Montpellier, France EDITH RAULET • INSERM U632, Hepatic Physiopathology, Montpellier, France; Université Montpellier 1, Montpellier, France; CHU Montpellier, Institut de Recherche en Biothérapie, Hôpital Saint Eloi, Montpellier, France ANTONIO SA-CUNHA • CHU Bordeaux, Service de Chirurgie Digestive, Hopital Haut-Lévèque, Pessac, France MARKUS SCHUG • Leibniz Research Centre for Working Environment and Human Factors (IfADo), Dortmund, Germany
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ROBERT E. SCHWARTZ • Department of Gastroenterology and Hepatology, Brigham and Women s Hospital, Boston, MA, USA CHIA-NING SHEN • Stem Cell Program, Genomics Research Center, Academica Sinica, Taipei, ROC, Taiwan ETIENNE SOKAL • Pediatric Department, Université Catholique de Louvain, Brussels, Belgium ALEJANDRO SOTO-GUTIERREZ • Department of Surgery, Okayama University Graduate School of Medicine and Dentistry, Okayama, Japan STEPHEN C. STROM • Department of Pathology, University of Pittsburgh, Pittsburgh, PA, USA BERTRAND SUC • CHU Toulouse, Service de Chirurgie Digestive, Hopital de Rangueil, Toulouse, France YUICHI SUGIYAMA • Department of Molecular Pharmacokinetics, Graduate School of Pharmaceutical Sciences, The University of Tokyo, Tokyo, Japan CAMILLE SUREAU • Laboratoire de Virologie Moléculaire, Institut National de la Transfusion Sanguine, Paris, France FRANÇOIS TORREILLES • Discovery Metabolism and Pharmacokinetics Safety, Sanofi-Aventis Recherche, Montpellier, France DAVID TOSH • Centre for Regenerative Medicine, Department of Biology and Biochemistry, University of Bath, Bath, UK THOMAS TOUBOUL • INSERM U972, Université Paris-Sud, Hôpital Kremlin-Bicêtre, Le Kremlin-Bicêtre, France THIERRY UMBDENSTOCK • Technologie Servier, Orléans, France CATHERINE VERFAILLIE • Interdepartementaal Stamcelinstituut, Leuven, Belgium BERNARD WALTHER • Technologie Servier, Orléans, France ANNE WEBER • INSERM U972, Université Paris-Sud, Hôpital Kremlin-Bicêtre, Le Kremlin-Bicêtre, France
Chapter 1 General Review on In Vitro Hepatocyte Models and Their Applications Christiane Guguen-Guillouzo and Andre Guillouzo Abstract In vitro hepatocyte models represent very useful systems in both fundamental research and various application areas. Primary hepatocytes appear as the closest model for the liver in vivo. However, they are phenotypically unstable, have a limited life span and in addition, exhibit large interdonor variability when of human origin. Hepatoma cell lines appear as an alternative but only the HepaRG cell line exhibits various functions, including major cytochrome P450 activities, at levels close to those found in primary hepatocytes. In vitro hepatocyte models have brought a substantial contribution to the understanding of the biochemistry, physiology, and cell biology of the normal and diseased liver and in various application domains such as xenobiotic metabolism and toxicity, virology, parasitology, and more generally cell therapies. In the future, new well-differentiated hepatocyte cell lines derived from tumors or from either embryonic or adult stem cells might be expected and although hepatocytes will continue to be used in various fields, these in vitro liver models should allow marked advances, especially in cell-based therapies and predictive and mechanistic hepatotoxicity of new drugs and other chemicals. All models will benefit from new developments in throughput screening based on cell chips coupled with high-content imaging and in toxicogenomics technologies. Key words: Hepatocytes, liver cell lines, HepaRG cells, stem cells, culture conditions, cryopreservation, differentiation, proliferation, bile metabolism, xenobiotic metabolism, transporters, hepatotoxicity, toxicotranscriptomics, high-content imaging, hepatocyte therapies, virology, parasitology.
1. Introduction The technique of high-yield preparation of isolated hepatocytes by collagenase perfusion was published in 1969 by Berry and Friend (1) and the two-step procedure that is now the usual P. Maurel (ed.), Hepatocytes, Methods in Molecular Biology 640, DOI 10.1007/978-1-60761-688-7_1, © Springer Science+Business Media, LLC 2010
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way to get hepatocyte suspensions was introduced by Seglen in 1972 (2). One year later Bissell et al. (3) described the rat hepatocyte monolayer cultures and in 1982 high-yield preparation and primary culture of adult human hepatocytes were reported by Guguen-Guillouzo et al. (4). During 40 years an extraordinary number and diversity of studies have been carried out with isolated hepatocytes from livers of humans and various animal species, dealing with both hepatocyte functions and applications in diverse fields. Many reviews and multiauthored books have already covered many of these topics, e.g. (5, 6). However, continuous progress is being made with isolated hepatocytes that deserves periodic review. In this chapter, we first summarize the main experimental conditions presently used to maintain functional hepatocytes in vitro and then attempt to analyze the more recent findings in the biology of the hepatocyte and the major application fields. Through this chapter the performance of isolated hepatocytes in suspension or in primary culture will be challenged with that of the other in vitro liver cell models, especially new established liver cell lines.
2. Culture Conditions of Hepatocytes 2.1. Primary Adult Hepatocytes
Hepatocytes can be obtained from whole liver or wedge fragments. Today human hepatocytes are marginally isolated from livers unsuitable for liver transplantation and mostly from liver fragments resected from primary or secondary tumors or some other liver diseases. Freshly isolated hepatocytes exhibit the typical structure and most of the functions of their in vivo counterparts but they have lost specialized membrane domains such as intercellular junctions and bile canaliculi and they do not survive for more than a few hours in suspension. To survive longer they must attach to a substratum. When plated in conventional culture conditions, they reaggregate and reconstitute bile canaliculuslike structures but they exhibit early phenotypic alterations and survive for only a few days. In agreement with these changes, deregulation of a large set of genes was observed by comparing suspended and attached primary human hepatocytes using the microarray approach (7). In addition to their scarce and unpredictable availability and interdonor variability, human hepatocytes behave differently upon their rodent counterparts. Indeed, at least for some functions such as cytochromes P450 (CYP), especially CYP1A2 and CYP3A4, an early and marked drop followed by a
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transient increase is frequently observed supporting the view that they are more active 2–3 days after plating. Extensive reviews have been published on conditions to improve hepatocyte survival and function in vitro (8–13). Very early it appeared that several factors were critical for survival and function of hepatocytes in primary culture, they included soluble factors (i.e., medium composition) and pericellular environmental factors (matrix proteins as well as other cell types). Addition of 2% dimethylsulfoxide (DMSO) (14) and other chromatin remodeling agents such as trichostatin A (15), the use of the sophisticated Lanford’s medium at least for monkey and human hepatocytes (16), the use of extracellular matrices that prevent cell spreading such as matrigel (17) and the sandwich configuration (18), and cocultivation with nonparenchymal cells (19, 20) are today among the most convincing culture conditions for extended survival of functional hepatocytes. Various other models have been designed, including bioreactors providing scaffolds for the cells that can be continuously oxygenated and perfused. It is also well established that entrapping in collagen or alginate gels allows hepatocytes to survive for several days instead of a few hours in suspension (21). Recently, high HCV replication was obtained in primary human hepatocytes maintained well differentiated by the use of appropriate culture conditions consisting in seeding cell suspensions (>95% viability and low-apoptotic activity) at high density (1.8 million/60 cm2 plate) in plates treated with polylysine coated with a 3-D specific rat tail collagen 1 matrix, in a medium containing 20% fetal calf serum during spreading only (22). Suspended hepatocytes can be stored for either a short period (1–3 days) in hypothermic conditions (0–5◦ C) or prolonged periods in liquid nitrogen (23, 24). Even when using well-defined freeze/thaw conditions nearly half of cryopreserved suspended hepatocytes lose their ability to attach to plastic after thawing. However, when the cells are first encapsulated or entrapped, e.g., in alginate gels, viability is well maintained after cryopreservation and CYP activities are comparable to those measured in fresh hepatocyte monolayer cultures (25, 26). A further improvement could come by vitrifying encapsulated hepatocytes. See also Chapters 2, 3, 4, 5, and 23 of the present volume. 2.2. Other Liver Cell Models
Besides primary hepatocyte cultures precision-cut tissue slices and liver cell lines are other in vitro cell models used to investigate hepatocyte functions, and hepatocyte-like cells derived from stem cells are emerging as a new potential alternative source of hepatocytes.
2.2.1. Precision-Cut Tissue Slices
Tissue slices offer the advantages of the retention of the 3-D tissue architecture organization and they can be incubated just
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after preparation. However, as in primary human hepatocyte cultures the functions rapidly decrease so that the use of liver sections is usually limited to 1–2 days. Slices must be used fresh and the cells are not all equally preserved inside a 250 μM section (around 10 cell layers). No reproducible freeze/thaw protocol has been described. Although liver sections are used for prediction of metabolic profiles, clearance, enzyme induction, and drug–drug interactions, these limitations explain why they have not acquired yet a permanent position as an in vitro tool in drug discovery and development (27). 2.2.2. Hepatocyte Cell Lines
Hepatocyte cell lines can be obtained by oncogenic immortalization or from tumors. A lot of efforts have been put on oncogenic immortalization of adult hepatocytes but the results are quite disappointing. Immortalized cells tend to be genetically unstable and lose their phenotypic characteristics. However, combination of SV40 T and TERT-mediated gene transfections to produce genetically stable cells (28) deserves further investigation. Only few immortalized liver cell lines expressing some liverspecific functions have been described. Probably the most powerful immortalized cell line is the Fa2N-4 cell line originated from human hepatocytes transfected with the SV40 large T antigen gene (29). These cells express various drug-metabolizing enzymes, including some major CYPs and transporters. However, the nuclear constitutive androstane receptor (CAR) and several transporters are >50-fold lower than in primary human hepatocyte cultures and low if any response of CYP2B6 and CYP3A4 was evidenced with CAR activators (30). The most used human hepatocyte cell lines (e.g., HepG2, Hep3B, PLC/PRFs Huh7, HBG) are derived from tumors. Since its initial establishment (31) the HepG2 cell line has lost a substantial and variable set of liverspecific functions, especially the major CYPs involved in xenobiotic metabolism. Therefore, HepG2 cells routinely used in in vitro assays should be characterized for their drug-metabolizing potential before any result can be fully interpreted (32). Subclones expressing higher drug-metabolizing activities have been established from several human hepatoma cell lines, e.g., HepG2/C3A (33), BC2 from HBG (34), or Huh-7.5 which is more appropriate for replication of HCV pseudoparticles. However, they are poorly stable at high confluence, a stage essential for reaching a high differentiation level. Only the recently obtained human hepatoma HepaRG cell line has retained the expression of liver-specific glycolytic enzymes and high expression and inducibility of the major CYPs (Table1.1). See also Chapters 13 and 20 of the present volume. These cells derive from a female suffering from liver carcinoma; they appear as an homogeneous cell population exhibiting limited
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Table 1.1 Respective advantages and limitations of primary human hepatocytes and human hepatoma HepaRG cells Advantages
Limitations
Primary human hepatocytes
Functions close to those of in vivo liver Cryopreservation Interspecies studies
Scarce and unpredictable availability Rapid phenotypic changes Short life span Large interdonor functional variability No bile collection
HepaRG cells
Major liver-specific functions expressed Functional stability at confluency Reproducible and consistent data Cell proliferation after seeding following differentiation (transdifferentiation property) Suitable for high-throughput screening Indefinite growth potential
Functional levels frequently different from those found in primary hepatocytes No bile collection Transformed cells Originated from a single donor
karyotypic alterations mainly characterized by a surnumerary and remodeled chromosome 7 and a translocation t(12;22) with a loss of the 12p fragment leading to a monosomy 12p (35) and have the property of transdifferentiation (36). When HepaRG cells are seeded at low density they rapidly recover markers of hepatic bipotent progenitors and actively divide until they reach confluence. Then they differentiate into hepatocyte-like and biliary-like cells. HepaRG cell cultures express the major CYPs, various phase II enzymes, transporters and the key nuclear factors, CAR, pregnane X receptor (PXR), and peroxisome proliferator-activated receptors (PPARs) (37–39). Maximum xenobiotic metabolism capacity is attained after a 2-week exposure to 2% DMSO that is a CYP enzyme inducer. The close resemblance to primary human hepatocytes was further evidenced by a recent study using pangenomic Agilent microarrays showing around 85% identity in genes expressed in both models (Lambert CB, unpublished data)). The mechanism(s) by which DMSO increases some liver-specific functions is not completely understood. The hepatocyte differentiation program is initiated very early at the onset of cell confluence before addition of DMSO. At a 2% concentration DMSO provokes the death of “non-hepatocyte committed” cells while it forces “committed” ones to activate their detoxifying systems in order to resist its toxic effects; these systems include increase of some phase I and phase II enzymes as well as transporters in specialized plasma membrane domains delineating functional bile canaliculi for the secretion of toxic compounds. DMSO has also been shown to act as a reactive oxygen species scavenger and an
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antiapoptotic agent (40). Noteworthy, certain CYP inducers appear ineffective in DMSO-exposed HepaRG cells, suggesting that by enhancing expression of nuclear receptors and liver transcription factors, DMSO allows these CYP genes to reach nearly maximum transcription activity (37). By contrast, the Ah receptor (AhR) and CYP1A1 that are early well expressed at the undifferentiated stage are not responsive to this agent. Similar observations have been made with primary rat hepatocytes. The process of HepaRG cell transdifferentiation mainly depends on the ability of the cells to proliferate. Indeed, when maintained at confluence they are very stably differentiated. When plated at high density, following or not selection of the hepatocyte subpopulation, cell colonies with a characteristic hepatocyte-like morphology are highly maintained and their specific functions are well preserved (36). Addition of DMSO allows to obtain maximum functional stability and cell polarity. By contrast, when the cells are plated at a lower density, leaving space for cell proliferation, a fraction of the cell population dedifferentiates within a few hours, acquires progenitor properties, and proliferates up to confluence that can be reached within a few days; both hepatocyte and biliary cell types can again undergo a complete program of transdifferentiation/differentiation toward either cell type. HepaRG cells do not develop tumors in nude mice. However, they repopulate the liver of uPA/SCID mice when injected in the spleen and form trabeculae of differentiated hepatocytes (36). 2.2.3. Hepatocyte-Like Cells Derived from Stem Cells
To overcome limited availability and interdonor variability of primary human hepatocytes stem cells obtained from either embryos (multipotent embryonic stem cells) or somatic adult tissues (pluripotent adult stem cells) have recently emerged as a potential reliable alternative source of hepatocytes. See also Chapters 8, 9, 10, 11, 12, and 14 of the present volume. Several adult tissue sources have been evaluated, including bone marrow, blood monocytes, umbilical cord (mesodermal and matrix mesenchymal stem cells), amniotic cells, and even skin fibroblasts and liver cells. It is now established that stem cells also exist in the human adult liver (41–43); they are AFP- and epithelial cell adhesion molecule (EpCAM)+ and constitute only 0.5–2.5% of the hepatocyte population of all donor ages. These stem cells are able to propagate on plastic in a defined serum-free medium (>150 population doublings) without any phenotypic changes (43). By contrast when transferred to feeder cell layers (embryonic stroma cells), they give rise to hepatoblasts that express AFP and low levels of albumin and CYP3A7. Several investigators have demonstrated the capacity of adult non-hepatic and hepatic stem cells as well as embryonic stem cells of either human or rodent origin, to generate in vitro hepatocyte-like cells, which however, at the best, express features of hepatoblasts/fetal hepatocytes by the use of
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appropriate culture protocols, consisting in the addition of cytokines, growth hormones, and some other ingredients either as a cocktail or sequentially (44). The choice and the abundance of liver markers are critical questions (45). If the levels of functional activities are compared to those measured in the liver and primary hepatocyte culture they are usually much lower and variable through the cell population. Moreover, after a few days they start to lose their characteristic morphology and markers. Even in vivo transplantation of either stem cells or hepatocyte-like cells results in only a limited improvement of the hepatic phenotype. However, a very recent study describes experimental culture conditions enabling human embryonic stem cells to differentiate in vitro into cells resembling morphologically to and expressing functions of differentiated hepatocytes. However, no more than 18–25% of the total cell population expressed adult hepatocyte markers after differentiation in culture. These cells were isolated by sorting for surface asialoglycoprotein receptor expression. Their level of conversion of testosterone into 6β-hydroxytestosterone, a specific CYP3A4-mediated reaction, was comparable to that measured in primary human hepatocyte cultures (46). This illustrates a major challenge that is to maintain a high proliferative potential at each stage of the differentiation process of a cell. Embryonic cell lines actively divide and large cell numbers can be generated. However, it must be pointed out that they exhibit frequent chromosomal abnormalities with an amplification of 2.5–4.6 Mb at 20q11.21 that has been associated with oncogenic transformation (47). Moreover, contrary to HepaRG cells, hepatocytes derived from embryonic cells have not the property of transdifferentiation and are not able to proliferate following detachment and plating. Nevertheless, from this observation and other reports marked progress may be expected in in vitro obtention of differentiated hepatocytes derived from embryonic and adult stem cells in the next future.
3. Applications to the Biology of the Hepatocyte 3.1. Hepatocyte Differentiation 3.1.1. Commitment and Stability of the Hepatocyte Phenotype
During the last 15 years, isolated hepatocytes have been extensively used for studies on the regulation of liver-specific genes. Primary cultures have been very useful for the understanding of the role of these genes on tissue function specificity as well as the role of environmental factors on their regulation. Several transcription factor families that govern tissue-restricted gene expression were clearly identified; they are characterized by their
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structurally related DNA-binding domains and include the variant homeodomain-containing proteins (HNF-1α, HNF-1β); the winged helix family proteins HNF-3α, β, and γ (also called FoxA1, 2, and 3); members of the nuclear hormone receptor family (HNF-4, COUP-TFII, LRH-1, FXRα, and PXR); the basic leucine zipper-containing factor C/EBPα; and the onecut homeodomain protein HNF-6 (48). The genes found to be targeted by HNF1 in primary human hepatocytes encode products whose functions represent a substantial cross section of hepatocyte biochemistry. HNF1 contributes to the transcriptional regulation of many of the central rate-limiting steps in gluconeogenesis and associated pathways. HNF1 also binds to genes whose products are central to normal hepatic function, including carbohydrate synthesis and storage, lipid metabolism (synthesis of cholesterol and apolipoproteins), detoxification (synthesis of cytochrome P450 monooxygenases), and synthesis of serum proteins (albumin, complements, and coagulation factors). HNF1α also regulates primarily hepatocyte polarization (49). Meanwhile, notch-2 exerts a critical role in the cell fate of hepatic bipotent progenitors (36) and HNF4α is a key regulator of morphological and functional differentiation of hepatocytes essential for the formation of a polarized hepatic epithelium (50) and cell–cell contacts (51). Cross-regulatory cascades between hepatic transcription factors have been implicated in the commitment of the hepatic phenotype. Analysis of recruitment to regulatory regions of the main hepatic regulators during liver development has revealed a gradual increase in complexity of autoregulatory and cross-regulatory circuits (52). As a consequence, none of these factors is expressed exclusively in adult hepatocytes and none of them can induce alone the hepatic program in non-hepatic cells, and transcriptional regulation of most of the liver-specific genes requires a combinatorial action of the above activators. This has been confirmed from a recent genome-wide promoter occupancy study in liver which concludes that >40% of the promoters of active genes were bound by HNF-4α, and most of the promoters bound by HNF-1α or HNF-6 were also occupied by HNF-4α (53). In addition, as in vivo, extracellular signals contribute to regulating these transcription factors during hepatic differentiation in vitro. They also coordinately contribute to stabilize their activities in differentiated hepatocytes in primary culture, as shown by Liu et al. (54) for c/EBPs. This high complexity that characterizes liver parenchymal cells explains for a part why it is difficult to preserve a high stability of liver-specific functions in hepatocytes in vitro and why attempts in restoring a transcription factor activity by gene transfection in hepatic cell lines as assayed by several investigators failed to stably restore an extinguished liver function in these permanent cell lines (55). However, transient overexpression or extinction by transfection strategy into primary hepatocytes or
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hepatoma cell lines provide very useful approaches for highlighting the role of these genes in specific living cells, which constitute a very efficient alternative to transgenic animals. Conditions mimicking environmental signals including extracellular matrix component deposition or establishment of intercellular communications between hepatocytes and other hepatic cells such as primitive biliary cells and liver endothelial cells were successfully developed in order to support stability of liver-specific functions for a prolonged period (56, 57). However, although induction of several functions is possible for 3–4 weeks under exposure to appropriate inducers and using these coculture models, the level of gene transcription activity remains less than half of that in freshly isolated hepatocytes (57). In addition, cells undergo gradual progression to aging. This contrasts with the highly differentiated hepatic HepaRG cells which can reverse to undifferentiated progenitors with restored proliferative activity at low cell density. For this reason these cells constitute a unique model for understanding the mechanisms which allow them to escape from aging and death and restore their progenitor cell properties. The major property is the commitment signal making progenitors able to undergo a complete bipotent hepatoblast differentiation program up to mature hepatocytes for one lineage and to biliary-like cells for the other. Indeed, distinct steps with sequential transcription factor expression have been reported along the hepatocyte differentiation process (36). Gene factors controlling this reprogramming are not known yet. Importent modulators could be involved, such as p53, p21 and Rb. Noteworthy, these genes and wt-β catenin are normally regulated in HepaRG cells. 3.1.2. Expression and Regulation of Liver Functions
Liver cell models have provided pertinent experimental conditions, mainly homogeneous populations supporting transient transfection, for characterizing the biological activity of multiple genes known to play a role in liver function. Most studies have gained benefits from the development of new technologies such as RNA silencing and the use of hepatocytes isolated from animals knockout for liver-specific genes and the design of in vitro liver cell models mimicking liver pathologies. Evidence was brought that groups of genes belonging to the same family, the same function, or a group of distinct functions might share common control regulations. Analysis of hepatocyte behavior in culture has allowed to elicit a strong correlation between occurrence or expression levels of highly specific proteins such as the aldolase B enzyme from the glycolysis pathway, transferrin from protein synthesis activity and CYP3A4 from the detoxication function, thus defining a genomic signature characteristic of a complete hepatic differentiation process (58). In addition, comparing four distinct steps in the differentiation process of HepaRG cells has highlighted a correlated appearance of
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the iron uptake and storage capacity in hepatocytes with several other differentiation functions including xenobiotic detoxification activities (58). Since isolated hepatocytes either in suspension or in shortterm culture retain expression of differentiated functions and responses to hormones, they have been widely used for analyzing physiological modulation of functions. Thus, they have been used for studying protein, lipid, and glucose metabolism and catabolism. Considerable literature exists on their use as well as that of other in vitro hepatocyte models; it cannot be covered in the present review. Only a few examples are given to illustrate their unique recent contribution. Recent progress mainly concerns identification of the mechanisms of regulation of metabolic pathways by hormones or endogenous compounds or by drugs or other chemicals. As an example, using primary mouse hepatocytes and RNA interference, the dual role of growth factor receptor-bound protein 14 has been demonstrated on the regulation of hepatic metabolism by insulin: this molecular adapter inhibits insulin receptor catalytic activity and acts at a distal step, i.e., on sterol regulatory element binding protein 1c (SREBP-1c) maturation (59). SREBP1c is a major mediator of insulin action on hepatic gene expression. In the presence of glucokinase (GK) it exerts a synergic action, together with the carbohydrate responsive element binding protein (ChREBP) on glycolytic and lipogenic gene expression as shown by using GK-knockout mouse hepatocytes (60). ChREBP was previously found to play a major role in the induction of pyruvate kinase L, one of the rate-limiting enzymes of glycolysis which is exclusively dependent on glucose, in rat hepatocyte cultures (61). Hepatocyte cultures, frequently together with in vivo models, have been also widely used to study regulation of hepatic lipid metabolism. Early reports concluded that they represented ideal models to investigate regulation of lipoprotein synthesis and catabolism (62). Hepatocytes form fatty acids from carbohydrates and synthesize triglycerides from fatty acids and glycerol. They are also able to perform protein glycosylation. Thus, glycosylation of apolipoproteins by cultured rat hepatocytes was demonstrated (63). Using primary human hepatocytes, we demonstrated that increased plasma human apolipoprotein-A1 levels after fenofibrate treatment was related to a direct action of the drug on apolipoprotein-A1 production as shown by an increase in both mRNA levels and apolipoprotein-A1 secretion in the culture medium (64). Participation in the understanding of the role of the major nuclear receptors initially characterized as xenosensors in the regulation of various physiological functions represents another recent major contribution of the in vitro hepatocyte
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models. These receptors, particularly AhR, PXR, and CAR (see Section 4.3), are now recognized as controlling various signaling pathways which regulate lipid metabolism, glucose homeostasis, bile acids, hormones, vitamins, and inflammation. These functions can be greatly altered following activation of these receptors by various xenobiotics and endogenous molecules. It has been well demonstrated that these receptors establish cross talk with other receptors and transcriptional factors (65). Similarly, using microarrays and HepaRG cells we have recently clarified the effects of phenobarbital on hepatic vitamin D metabolism. Phenobarbital was found to suppress mitochondrial vitamin D3 25-hydroxylation (CYP27A) and to induce 25-hydroxyvitamin D3-24-hydroxylation (CYP24) (66). Another main application of hepatic cells, mainly in primary culture, is the analysis of signaling pathways. Thus, in vitro models of sepsis created by treating hepatocytes with proinflammatory cytokines have been used to demonstrate direct cytokine effects on glycogen metabolism (67) and evaluate the effects of several catecholamines that are used to treat sepsis patients (68). Hepatocytes are particularly sensitive to Fas ligand and many aspects of this death pathway were analyzed using in vitro hepatocytes. Recently, the plasma protein transferrin was found to interfere with Fas-mediated hepatocyte death and liver failure in vivo, by decreasing pro-apoptotic and increasing antiapoptotic signals. Survival of hepatocytes stressed by Fas signals can be monitored by transferrin and iron, leading to postulate that this protein might be a target for new therapeutic applications (69). Noteworthy, the possibility that in vitro hepatic models fail to completely mimic expected hepatocyte metabolic controls may occur. Recent studies have emphasized the very high complexity of iron metabolism. The peptide hormone hepcidin was established as the principal regulator of systemic iron homeostasis, and in vivo experiments have assessed that increases in urinary hepcidin concentrations in man were proportional to the increment in transferrin saturation. Paradoxically, in previous studies on primary hepatocytes and cell lines, hepcidin response to iron or iron transferrin was not observed. However, a recent report has shown that freshly isolated murine hepatocytes responded to holotransferrin but not apotransferrin by increasing hepcidin mRNA (70). See also Chapters 6 and 7 of the present volume. 3.2. Hepatocyte Proliferation
Besides their unique contribution in dissecting the molecular mechanisms supporting the complex hepatic differentiation program, hepatocyte primary cultures have, without any doubt, allowed important breakthroughs in the understanding of the highly controlled regulation of hepatocyte proliferation occurring during the regeneration process. Because of the limited survival potential of primary hepatocytes in vitro, efforts were first mainly devoted to identifying factors which could augment their growth
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capacity. It was found that in the presence of mitogenic factors they were induced to undergo generally only one or at the best few divisions. As in vivo, EGF and TGFα appeared as the primary mitogens for hepatocytes in vitro. Different co-mitogens, including hormones such as insulin, essential amino acids, ions such as selenium, or other factors such as nicotinamide (71) all appeared to be very effective. (72–74). Evidence was provided that liver perfusion and cell isolation constitute a stress that induces hepatocytes to enter into G1 phase. Then, investigators have taken great advantage of the very long G1 phase to clarify the different steps overcome by the cells to reach the decision of the G1/S transition. In the absence of mitogenic factors we showed that rat and human adult hepatocytes are blocked at a restriction point located around the two-thirds of the G1 phase (75). At this point the cells become responsible to the mitogenic signal. This response is modulated and preceded by growth factor-dependent morphogenetic events that are characterized by changes in cell shape and spreading and in the cytoskeleton (76). The sequential control of these morphological changes and S entry involves activation of the MEK–ERK pathway, ERK1 being mainly responsible for cyclin D1 gene induction at the restriction point, while ERK2 is a key form in the decision of S-phase transition (76, 77). Other pathways are involved in reduction or delay of apoptotic signals; thus in vitro hepatocytes have allowed to eliciting involvement of PI3K/FRAP TOR pathway (78) and over all, its cross talk with the Fas/FADD/c-Flip (L) caspase 8 pathway in controlling the G1/S transition by modulating apoptosis signal through GST/AKT complex formation (40, 79). Moreover, cyclin-dependent kinase inhibitors such as P27 and particularly P21, that accumulate in G0/G1 and are known to negatively control cell cycle progression in various differentiated cell types, appear to be finely controlled in hepatocytes in order to allow them to respond to the mitogenic signal (80). Finally, by combining extracellular matrix influence, growth factor signal, and cytokine-mediated stress signaling, we succeeded in obtaining multiple cycles of DNA synthesis even in confluent rat hepatocyte cultures by performing waves of activation/repression of the ERK pathway (Fig. 1.1). This result was made possible by taking advantage of the coculture model associating rat hepatocytes with biliary cells, which restores secretion and deposition of a biomatrix network. Demonstration was provided that EGF prolongs hepatocyte progression up to late G1, whereas remodeling of the extracellular matrix was essential and required cytokines such as TGFα (81). 3.3. Bile Formation and Secretion
Bile formation plays a central role in digestion and elimination of numerous endogenous and exogenous compounds. A number of transporters work in concert to transport bile acids and xeno-
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45’
10’
50’
35’
65’
BrdU incorporation (%)
0
13
50 40 30 20 10 0 2
4 6 8 10 12 14 16 18 20 22 24 days TNFa+FGE TNFa+EGF untreated
Fig. 1.1. Multiple division cycles of mature rat hepatocytes in coculture with primitive biliary cells and stimulated with TNF/EGF. Ten day-old cocultures were stimulated for 10 days periods separated by a resting time of 4 days. Micrograph of BrdU-labeled cells at day 3 post-stimulation and phase-contrast micrographs from time-lapse microcinematography performed between 48 and 90 h of stimulation represent the chronological events of mitosis in differentiated hepatocytes at indicated times. Note that bile canaliculi remain present during mitosis. The kinetics of BrdU-labeled cells show two cycles. Bar, 20 μM.
biotics from blood to bile. In primary culture adult hepatocytes retain expression of both sinusoidal and canalicular transporters. However, in the classical 2-D conventional culture configuration they tend to exhibit a flattened morphology with less pronounced formation of bile canaliculus-like structures and this is associated with lower expression of various transporters. Like many other functions drug transporters are better preserved in human hepatocytes than in their rat counterparts. Indeed, limited changes in sinusoidal transporters have been observed after 5 days of culture in primary human hepatocytes, while a strong decrease was evidenced in rat liver parenchymal cells (82). Thus, more appropriate models have been selected for the study of bile formation and secretion, such as the isolated rat hepatocyte couplet and the sandwich configuration. The isolated rat hepatocyte couplets were first used to determine electrical driving forces across the canalicular membrane into an intact hepatocyte (83). Today, hepatocytes cultured in a collagen sandwich configuration are accepted as the most powerful in vitro tool to determine the magnitude of drug transport into the hepatocytes as well as bile secretion of drugs. Thus, this model has been used for the study of bile formation in polarized hepatocytes requiring long-term experiments where proteins involved in the bile secretory process can be specifically knocked down using adenoviral siRNA techniques (84). It has also recently been used for the analysis of hepatobiliary transport characteristics of concentrative and equilibrative nucleoside transporters; these are two families of transmembrane proteins that facilitate transport of hydrophobic nucleosides across cell membranes. The types of nucleoside transporters, their subcellular distribution, and their relative activity were studied in human hepatocytes (85). See also Chapter 22 of the present volume.
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Hepatocyte cultures have also been used to estimate the effects of xenobiotics on bile transport. It has been shown that troglitazone inhibits both basolateral uptake and canalicular excretion of taurocholate in a concentration-dependent manner in both sandwich-cultured and suspended rat and human hepatocytes (86). Antiretroviral drugs such as ritonavir, saquinavir, and efavirenz were found to inhibit taurocholate transport by inhibiting the bile salt export pump Na+ - taurocholate co-transporting polypeptide; the effects were stronger in rat than in human hepatocytes (87). Expression and activity of transporters are modulated by various xenobiotics known to regulate phase I and phase II xenobiotic-metabolizing enzymes. However, inter-interindividual variable response has been evidenced (88). An alternative is to use HepaRG cells which organize plasma membrane domains with typical and active formation of bile canaliculi, retain stable expression and specific distribution of various transporters for several weeks (89) as well as their responsiveness to xenobiotic modulators (Antherieu S, unpublished data).
4. Applications to Xenobiotic Metabolism and Toxicity
4.1. Xenobiotic Metabolism
Absorption, distribution, metabolism, excretion, and toxicity (ADMET) areas are essential for the development of new drugs. They represent an important application field of hepatocytes. Indeed, the liver is the principal organ involved in the biotransformation of xenobiotics with its capacity to convert hydrophobic compounds into water-soluble products that can be secreted readily from the body. It is also the main target for a number of drugs and other xenobiotics that are potentially hepatotoxic either directly or more frequently after bioactivation leading to the formation of chemically reactive metabolites or generation of reactive oxygen species. In vitro cell preparations have been widely used for studies on xenobiotic metabolism and cellular and genetic toxicity as well as on regulation of detoxifying enzyme pathways. See also Chapters 15, 16, 17, 18, and 19 of the present volume. Primary hepatocytes are considered as the most pertinent in vitro model. They are routinely used to analyze drug uptake and kinetics parameters, estimate hepatic clearance, generate and identify metabolites, demonstrate interspecies differences, and predict potential drug–drug interactions. In most cases these models generate metabolites identical to those formed in vivo but in vitro– in vivo quantitative variations are frequently observed. This may
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Testosterone 6β-hydroxylation (pmoles/mg/min)
result from differences in chemical concentrations used, intercellular/intracellular compartment ratios, accumulation of metabolites in the medium, absence of extrahepatic metabolism, and/or changes in the relative levels of drug-metabolizing enzymes during culture. Phase I and phase II enzymes remain inducible but the extent of induction is quite dependent on the culture conditions. Both basal levels and fold inductions greatly vary in primary human hepatocytes from different donors (90, 91). This interdonor basal variability may be related to genetic, physiopathological, and environmental factors as well as to the conditions of tissue harvesting and hepatocyte isolation (10, 92). The fold inductions are dependent not only on the inducer and its concentration and the duration of treatment but also on the substrate and the basal activity as well as polymorphisms of the test gene; the lower is the basal activity the higher is the induction level (11). Similar observations have been made in vivo (93) and with HepaRG cells (37) (Fig. 1.2). These cells are also now widely used for studying drug kinetics, metabolic profile, enzyme induction/inhibition, and prediction of drug–drug interactions (94). Although exhibiting various functional alterations, cryopreserved hepatocytes retain some metabolic activities and responsiveness to inducers. They are accepted as a model system for drug interaction studies by the FDA (www.fda.gov/ cder/guidance/6695dft.pdf). It has been reported that cryopreserved human hepatocytes retained 94% of the intrinsic clearance estimated in fresh cells on the basis of 14 drugs (95). Another study has shown that for 37 drugs there was only, on average, a 4.5-fold under-prediction of the in vivo intrinsic clearance using 1000 800
control 50 μM Rifampicin (72h)
600 400 ** 200
***
0 15 days (-DMSO)
30 days (-DMSO 72h) 30 days (+DMSO 72h)
Fig. 1.2. CYP3A4 activity in HepaRG cells. The cells were seeded at low density and after day 15 were maintained in the presence of 2% DMSO for 15 more days before treatment with the prototypical inducer rifampicin for 72 h. During treatment of 30 days cultures the cells were either maintained (+DNSO 72h) or not (–DNSO 72h) in the presence of DMSO. CYP3A4 activity was estimated by testosterone 6β-hydroxylation. In the presence of DMSO basal activity was high and only slightly increased after rifampicin treatment. Results are expressed as pmol/min/mg protein. The Student’s t-test was applied for statistical analyses between cells exposed to the vehicle only (control) and cells treated with the inducer (∗∗ p < 0.01,∗∗∗ p < 0.001).
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cryopreserved hepatocytes compared with the ninefold underprediction observed with human microsomes (96). 4.2. Xenobiotic Toxicity
A number of studies have been devoted to cellular and genetic toxicity (10, 12, 97). Although their performance has been found positive in many cases, hepatocyte models remain far to be convincing for both cellular and genetic toxicity studies. New strategies based on high-throughput screening and toxicogenomics technologies as well as the use of more powerful hepatocyte systems are starting to be extensively used and the first reported results are encouraging. See also Chapter 21 of the present volume.
4.2.1. Cellular Toxicity
Conventional in vitro cytotoxicity assays usually measure lethal events over a short period with a single endpoint and have low predictive value for the detection of human hepatotoxicity (98). Indeed, since many mechanisms can contribute to drug-induced liver injury and that in vitro cytotoxicity can occur only after several days of reiterated exposure of metabolically competent cells, the use of a panel of tests covering the different types of hepatotoxicity has been suggested. One of the most common causes of hepatotoxicity is the CYPdependent formation of reactive metabolites that are directly hepatotoxic or form adducts with hepatic proteins potentially triggering an immune response. Other mechanisms include disruption of mitochondrial functions, inhibition of xenobiotic metabolism pathways, and inhibition of bile acid transport. Hepatocyte suspensions and classical 2-D monolayers have been already widely used for toxicity testing. Obviously, no optimal experimental conditions for predictive or mechanistic toxicity of chemicals exist and the results can be greatly affected by the experimental design (culture conditions, cytotoxicity parameters, etc.). Nevertheless, based on short-term exposures to high doses, a good correlation with in vivo data has been reported for a number of hepatotoxic compounds and several studies have shown that phospholipidosis, cholestasis, or peroxisome proliferation (rat hepatocytes) can be reproduced in cultured hepatocytes (10). However, to our knowledge, steatosis with accumulation of lipid droplets induced by steatogenic chemicals has not yet been well documented in cultured hepatocytes. However, it has been obtained with an excess of free fatty acids in human liver cell lines as observed in obese patients. Thus, accumulation of characteristic cytoplasmic lipid droplets together with an increase in intracellular triglyceride content evidenced by thin-layer chromatography analysis was obtained following a 7-day treatment of an immortalized human hepatocyte cell line with 5 μM oleic acid (99). Another group has shown accumulation of lipids in primary human hepatocytes and HepG2
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cells after a 24 h treatment with a mixture of oleate and palmitate at different ratios but appearance of intracellular lipid droplets was not reported (100). Preliminary results show that extensive accumulation of lipid droplets stainable by red oil can be obtained after treatment with steatogenic drugs (Antherieu et al. unpublished data). It is well established that steatosis can progress to steatohepatitis and fibrosis/cirrhosis even in the absence of alcohol intoxication (non-alcoholic fatty liver disease). It may be expected that the use of long-term differentiated hepatocytes should allow induction of steatosis associated or not with cytotoxicity with either an excess of fatty acids, steatogenic chemicals, or both. Since stellate cells are the primary cells involved in fibrosis by production of matrix proteins, their association with hepatocytes should be more appropriate to mimic the in vivo situation. A valuable method recently proposed by Buck (22) allows to obtain primary human hepatocyte cultures composed of 95% hepatocytes and 5% sinusoidal endothelial cells and hepatic stellate cells, mimicking the hepatocyte organoid rodent cell cultures (101). Since they usually remain viable and retain differentiated functions for longer periods than in monolayer cultures, hepatocytes in 3-D constructs have potential interest in toxicity testing; however, they add a procedural complexity that is not conducive to high-throughput screening. An alternative is to use hepatic cell lines. However, many reported cell culture models for predicting hepatotoxicity that are based on liver cell lines are flawed for one or more reasons. The three main ones can be easily avoided or corrected by (i) use of the cells at postconfluence and not at subconfluence in order to test predominant post-mitotic cells as in normal liver; (ii) verification that cells do not lack important functions (e.g., cytochrome P450 activities) of mature hepatocytes; (iii) choice of realistic doses and exposure time long enough for some toxicologically relevant processes to occur. On these bases, novel statistical approaches for development of a prediction model with HepG2/C3A human hepatoma cells for acute hepatotoxicity have been recently proposed by Flynn and Ferguson (102). Hepatic cell lines have typically been the primary tool for assessment of mitochondrial toxicity. However, these lines are metabolically adapted for rapid proliferation under hypoxic and acidic conditions, and they derive almost all of their energy from glycolysis rather than via mitochondrial oxidative phosphorylation. In such cells, mitochondrial toxicants have little effect on cell growth or death. Marroquin et al. (103) have succeeded in circumventing such resistance by replacing glucose by galactose in the medium of HepG2 cells. Preliminary studies with HepaRG cells aiming at quantifying alterations of mitochondrial membrane potential by toxicants using the mitotracker JC1 have revealed a high sensitivity of these cells to the toxicants (Le Guevel, unpublished data).
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One reason why usual studies performed with primary hepatocytes have missed a number of hepatotoxic drugs in humans (104) could be the exposure time that is restricted to days while liver injury occurred typically 1–6 months after initiating therapy. In vitro chronic toxicity remains a matter of debate and only few studies have been published, using primary hepatocytes maintained in conditions that increase their survival and better preserve their functions, e.g., in culture with another cell type (105) or in a sandwich configuration (13). These studies have shown that toxicity usually occurred with lower drug concentrations after reiterated exposure. Recently, we also used functionally stable differentiated HepaRG cells for chronic toxicity evaluation of aflatoxin B1 (AFB1). The cells were exposed every 2–3 days to various concentrations of the mycotoxin for 14 days. A cumulative effect was observed; the lowest cytotoxic concentrations were 1 and 0.1 μM after 24 h and 14 days, respectively, and as expected, hepatocyte-like cells, through 8,9-epoxides generated by CYP3A4, were preferentially damaged (89). 4.2.2. Genetic Toxicology
Genotoxicity tests in mammalian cells in vitro produce a remarkably high and unacceptable occurrence of irrelevant positive results (106). As recently emphasized by Sutter (107), such disappointing findings after 30 years of routine in vitro genotoxicity testing call for a complete rethink of the field. There is agreement that cell systems that have retained a large phase I and phase II metabolism capacity and are DNA repair proficient offer the best hope of reduced false positives. Primary hepatocytes and hepatoma cell lines are widely used for mutagenesis/cancerogenesis studies. The main uses of primary hepatocytes are for measurement of unscheduled DNA synthesis, DNA damage, and hepatocyte-mediated mutagenesis. Measurement of unscheduled DNA synthesis in primary rat hepatocytes for the detection of chemical carcinogens has been developed very early (108). This cell model offers the advantage to contain both the enzymatic machinery necessary to bioactivate genotoxic chemicals and the detoxifying enzymes and to have a very low mitotic activity. However, as already emphasized the balance between bioactivation and detoxification is rapidly altered due to the fact that early and variable changes differently affect the levels of phase I and phase II enzymes. Nevertheless this assay has been widely accepted and recommendation for its use has been published. Male rat hepatocytes are preferable as well as autoradiography analysis (109). Other methodologies have been developed in hepatocytes to demonstrate induction of DNA damage; they are based on quantification of DNA strand breaks by alkaline elution and measurement of DNA adduct formation by the 32 P-postlabeling assay. The micronucleus test has also been used in primary
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hepatocyte cultures but since it requires two cell divisions addition of mitogens to the culture medium is a prerequisite (110). Hepatoma cells seem as more appropriate. HepG2 cells are more sensitive than Hep3B cells toward dietary genotoxins using the micronucleus assay (111). Different results were obtained with different HepG2 clones (112). The absence of positive result with nitrosamines is likely due to the lack of CYP2E1 since a positive effect is seen in primary human hepatocytes (113). Both the single cell gel electrophoresis (comet) assay which is a sensitive method for the detection of DNA damage and repair induced by genotoxic compounds and the micronucleus assay have been found to give positive results in HepaRG cells (Le Hegarat et al., unpublished data). Thus, AFB1 that requires bioactivation by CYP3A4 induced the formation of comets in differentiated HepaRG cells and not in their undifferentiated counterparts that do not express CYP3A4 (89).
4.2.3. New Strategies for Hepatotoxicity Testing 4.2.3.1. High-Content Imaging
To increase the specificity and the sensitivity of cytotoxicity tests and reduce the time and cost for their realization, various automated and miniaturized assays covering the different types of hepatotoxicity are receiving growing interest. The assays generally combine engineering, biological endpoints, informatics, and data mining. Thus, O’Brien et al. (114) have reported that automation of quantitative epifluorescence microscopy coupled with imaging and analysis of several biomarkers have raised sensitivity and specificity of the tests to 80 and 90%, respectively. Efforts have been made to develop cell-on-chip devices with high-content imaging analysis that allow several hundred of nanoliter drops arrayed on a patterned glass substrate and combined automated imaging analysis. Toxicants have been tested on HepG2 cells (115). When seeded in conditions of low density in such microsystems, we have observed that HepaRG cells are able to undergo a differentiation process. Using automation of quantitative epifluorescence microscopy coupled with automated imaging analysis, a set of multiparametric tests of toxicants has been devised with HepaRG cells, all based on the functional qualification of the cells using three parameters, i.e., nuclei and bile canaliculi counting and cell to cell distribution of CYP expression (Fig. 1.3.). Other systems are based on microfluidic chips allowing analysis of flows of single or complex fluids in microgeometries (116) or tend to mix hepatocytes with cells from other organs; however, they seem to be more appropriate for acute toxicity testing and not easily applicable to high-throughput screening.
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1
2
3
Fig. 1.3. Triparametric imaging analysis characterizing HepaRG hepatocyte colonies at 10 days postconfluence in the presence of DMSO. Application to high-throughput toxicity testing. Fluorescent dyes were used for (1) nuclei (Hoechst), (2) bile canaliculi (F-actin), and (3) CYP3A4 labeling. Note variation in CYP expression level from one hepatocyte to another.
4.2.3.2. Toxicogenomics Technologies
Toxicogenomics are becoming a valuable method to predict toxicity of a new compound and/or its mechanism of toxicity. Microarray technologies are the most frequently used approaches as demonstrated by several recent published studies and are more and more relevant and reproducible. Applications of proteomics and metabolomics are still limited. Several in vitro studies have been performed with primary hepatocytes and hepatic cell lines. Although primary hepatocytes are considered as the most relevant in vitro model in hepatotoxicity testing they have some major limitations, particularly due to their usual strong phenotypic instability that is amplified when cell suspensions are prepared in different sites (117). These authors came to the conclusion that a gene-by-gene comparison of gene expression profiles was very difficult (117). Moreover, currently observed extensive inter-individual variations in gene expression levels render more difficult and complex comparisons of data obtained with human hepatocytes from different donors and consequently from different laboratories (118). Data obtained with hepatic cell lines such as HepG2 and Huh7 hepatoma cells (119) as well as rat hepatic cell lines (120) are far from those observed with primary cultures. HepG2 and Huh7 cells exhibited an average of only 42.5+/−3.1% and 39.2+/−9.2% unchanged probe sets compared with the liver across the six ontology categories noted as involved in drug metabolism and identified by the PANTHER classification system while this percentage reached 83.7+/−3.7% when primary human hepatocytes were compared to the liver (119). Accordingly, after phenobarbital (PB) treatment it was found that hierarchical clustering of the human hepatocytes but not human hepatoma cell lines shifted from donor specific to treatment specific when the probe sets were filtered to focus on PB-induced genes. Comparison of various human hepatocyte populations at the whole genome level has evidenced that the magnitude of conserved gene expression changes among donors is very small with fewer than 50% of the gene responses
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altered by a chemical in more than one donor. This study was based on 10 populations of human hepatocytes exposed to aroclor 1254, di-(2-ethylhexyl)phthalate and PB. The percentage of modulated genes in all cell populations was less than 0.1% whatever the chemical tested (121). By contrast, our recent studies with HepaRG cells in combination with pangenomics microarrays showed a good consistency and reproducibility and the possible use of data obtained from different generations of microarrays and from different laboratories (122). Most toxicogenomic studies have been performed with one high concentration of chemical, resulting in the deregulation of subsets of both specific responsive genes and genes related to a nonspecific toxic insult (117, 123–125). Using HepaRG cells we recently showed that gene profiling changes induced by PB were dose- and time-dependent (66). After a 20 h exposure at low PB concentrations most modulated genes appeared to represent a specific response to the barbiturate while at concentrations of 3.2 mM or higher the number of deregulated genes rapidly increased and included an increasing percentage of genes related to oxidative stress, growth arrest, DNA repair, and apoptosis. Moreover the results resemble those obtained with human hepatocytes under similar experimental conditions (66) (Fig. 1.4). Since only low concentrations might allow to identify most of the specifically responsive genes it appears appropriate to compare at least two different concentrations of a test compound. Besides their major interest for predictive and mechanistic toxicology of chemicals in vitro toxicogenomics technologies should find a place in the predictivity of the carcinogenic potential of chemicals. The current benchmark carcinogenicity assay for such prediction in humans is the chronic 2-year bioassay of rats of both sexes. Recent studies have addressed the value of hepatic gene profiling after short-term treatment of rats with nongenotoxic and genotoxic compounds and reported an 88% accuracy (126). It may be hypothesized that primary hepatocytes and HepaRG cells could represent suitable alternatives to in vivo rodent models. 4.3. Regulation of Detoxifying Pathways
Both human and animal hepatocytes have also been widely used to investigate regulation of xenobiotic-metabolizing enzymes and transporters by both exogenous and endogenous compounds and the role of nuclear receptors such as CAR, PXR, and AhR. Thus, these models have been employed for investigating the regulation of detoxifying enzymes by chemopreventive agents. A number of dietary constituents are particularly efficient in reducing the development of chemically induced cancers in rodents. One of the most powerful compounds appears to be oltipraz, a substituted 1,2-dithiole-3-thione, that has been extensively investigated both in vivo and in vitro. Using human and rat
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Fig. 1.4. Principal component analysis (PCA) of comparative gene expression profiles from HepaRG cells and primary human hepatocytes after a 20 h treatment with various phenobarbital (PB) concentrations. Three dimensional PCA using Resolver with the Spotfire DecisionSite analysis of gene expression profiles from HepaRG cells treated with 0.5, 1, 2, 3.2, 6, and 8 mM PB and primary human hepatocytes (HH) treated with 1 and 3.2 mM PB for 20 h. HH corresponded to a pool of cultures from three different donors. Separation of concentrations occurs through PC1 and through PC2 for high concentrations. HepaRG cells and human hepatocytes treated with the same concentration are close.
hepatocytes we have shown that oltipraz induces phase II detoxication and antioxidant enzymes as well as various CYPs after a transient direct inhibitory effect of these phase I enzymes (127). Mechanisms of gene induction involve binding of transcriptional factors to specific sequences, e.g., the binding of the nuclear factor-erythroid 2-related factor 2 (Nrf2) to the antioxidant response element (ARE) and that of the AhR to the xenobiotic responsive element (XRE). The use of macroarrays has shown that several additional genes related to cell growth and oxidative stress are modulated by oltipraz and both species and interdonor differences exist (128). Understanding of decreased drug metabolism during inflammation and infection has at least partly come from studies on in vitro hepatocyte models. We have shown that inflammatory
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cytokines, such as tumor necrosis factor alpha and interleukin1beta and 6, which are overexpressed during these physiopathological situations, inhibit expression of various CYPs (129). This inhibitory effect results from activation of the nuclear factor kappa B that leads to a decreased expression of CAR, PXR, and retinoic acid X receptor (RXR) alpha and their target genes (130). Together with in vivo experiments studies on hepatocyte cultures have shown evidence of cross talks between nuclear receptors. CAR and PXR activators and inhibitors not only affect xenobiotic-metabolizing enzymes and transporters but also alter various endogenous liver functions (65).
5. Applications to Hepatocyte Therapies
5.1. Extracorporeal Bioartificial Liver Devices
Isolated hepatocytes are considered as alternatives to whole organ transplantation for liver diseases. They can be used as an extracorporeal bioartificial liver (BAL) or implanted either as suspensions or attached to a support. Many liver support devices have been designed as a bridge either to liver transplantation or liver recovery in patients with acute or chronic liver failure. They may use human hepatocytes although porcine hepatocytes are most commonly used. Their potential advantages are that hepatocytes can be stored either as suspensions or ready to use in bioreactors. In some cases human hepatoma cells have also been tested, e.g., the HepG2/C3A cell line. Various configuration bioreactors have been designed; they can be divided in four main types: hollow fiber, flat plate and monolayer, perfused beds or scaffolds, and beds of encapsulated or suspended cells (131). See also Chapter 28 of the present volume. Many non-randomized studies have suggested some biochemical and clinical benefits. However, mortality without liver transplantation remains high despite the use of liver support devices and they have not been shown to be clinically effective with regard to patient survival or other clinical outcomes in any phase III prospective, randomized trials (132). An example is given by the prospective, randomized, controlled, multicentric trial in patients with severe acute liver failure managed by Demetriou et al. (133) that enrolled 171 patients (86 control and 85 BAL). After exclusion of primary non-function patients who did not show any benefit from BAL, a higher survival in other fulminant/subfulminant hepatic failure patients was observed in the BAL compared with the control group (73 vs 59%; risk ratio = 0.56; p = 0.048). However, when survival was analyzed
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accounting for confounding factors (liver transplantation, time to transplant, disease etiology, disease severity, and treatment site) in the entire patient population, there was no difference between the two groups (risk ratio = 0.67; p = 0.13). Obviously evaluation of the results is complicated by the heterogeneity of hepatic disorders and the lack of true control groups. Consequently these devices should only be used in research or by experts proficient in their use as a bridge rather than for liver recovery. 5.2. Hepatocyte Transplantation
Hepatocyte transplantation has been proposed as an attractive alternative approach for patients with acute or chronic liver failure and liver-based metabolic disorders. Several dozens patients have already been treated (134). See also Chapter 29 of the present volume. Animal experiments were first performed to define the most appropriate transplantation conditions. Hepatocyte transplantation was shown to support liver function and hasten host liver regeneration. Thus, following intoxication with D-galactosamine all animals survived if they received hepatocytes less than 28 h after toxin administration while all animals transplanted later died (135). Similarly 40% of the rats subjected to 90% hepatectomy and transplanted with hepatocytes on microcarrier beads in the peritoneal cavity survived while no animal survival was observed in the control group (136). Different sites for hepatocyte transplantation were evaluated and it was concluded that engraftment and subsequent function are superior in the liver followed by the spleen and the peritoneal cavity. The quantity of cells needed to prevent encephalopathy was estimated to represent 1–2% of the rat liver mass (136) and 1–5% of total human liver (1.8–8.8 × 109 hepatocytes. Such a cell quantity can be safely transplanted in one time or possibly in several infusions (137). See also Chapters 26 and 27 of the present volume.
5.2.1. Chronic Liver Failure
Treatment of chronic liver failure is based on the welldocumented studies that rat hepatocytes could survive and function in the spleen for periods up to 18 months. However, hepatocytes transplanted in the spleen can migrate into the liver and form liver structures and function. Mito et al. (138) performed 10 intrasplenic hepatocyte autotransplantations in cirrhotic patients and observed clinical improvement in two cases but concluded that this was rather due to artery ligation. Although transient improvement of functions has been reported by transplanting allogenic hepatocytes in some cirrhotic patients, the role of repeated cell infusion and the volume of cells required for relevant clinical efficacy remain to be determined (134).
5.2.2. Inherited Metabolic Disorders
The first trial of intraportal hepatocyte infusion to treat an inborn metabolic disorder was conducted in patients suffering from
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familial hypocholesterolemia. Intraportal autotransplantation of hepatocytes after ex vivo low-density lipoprotein receptor gene transduction was tested in six patients but in only one was a reduction in serum cholesterol still observed after 4 months (139). Intraportal human hepatocyte transplantation of 5% of calculated liver mass with fresh or cryopreserved allogenic hepatocytes by multiple infusions was also used to treat the Crigler–Najjar syndrome type 1 of 4 children. A reproducible reduction of hyperbilirubinemia by 30–50% for more than 3 years was observed (140). Obviously, results of hepatocyte transplantation for many inherited liver diseases are encouraging (141). 5.2.3. Acute Liver Failure
Fisher and Strom (134) analyzed the effects of intraportal, splenic, and/or intraperitoneal hepatocyte transplantation in 37 adult patients with acute liver failure and multiorgan failure of different origin and conclude that improvement was evidenced in a large percentage, leading to either complete recovery or successfully bridged to orthotopic organ transplantation.
5.3. Perspectives of Hepatocyte-Based Therapies
One major limitation is the availability of human hepatocytes. The development of a reliable and large-scale available source of liver cells would probably have major impact on the introduction of hepatocyte transplantation in clinical practice. A way would be to transplant stem and precursor cells. However, right now, no evidence has been provided that these cells from either human or animal origin are able to colonize and differentiate into mature hepatocytes in the liver of experimental animals (137). Pluripotent stem cells can also be obtained by reprogramming of somatic cells (142, 143); they would offer the way to generate patient autologous cells but their further re-differentiation into specialized cells such as hepatocytes has to be demonstrated. Similarly, no in vitro complete differentiation of fetal liver progenitor cells has been succeeded (144). Obviously, many questions about safety and efficacy need to be answered before liver progenitor cells, embryonic stem cells, adult stem cells, and induced pluripotent stem cells can be applied in humans.
6. Applications to Virology and Parasitology 6.1. Virology
The liver is susceptible to several viruses, especially B (HBV) and C (HCV) viruses. Hepatocyte cultures have been extensively used for investigating viral infection and replication processes.
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HBV is a small enveloped virus whose small (3.2 kb) relaxed circular genome shows an extremely compact organization. It has a strong tropism for hepatocytes. This explains why only human hepatocytes in primary culture were first found to be susceptible to HBV infection (145) and that hepatoma cell lines required HBV transfection to support viral replication (146, 147). DMSO strongly increased the percentage of infected hepatocytes; indeed, only a few cells were infected in DMSO-free medium. The use of this model is hampered by the limited availability and the inherent variability of human liver material. In parallel, animal models have therefore been developed, mainly primary cultures of duck hepatocytes either prepared from pre-infected cells or infected in culture with DHBV particles (148). Notably, important discovery was made with the observation that primary hepatocyte cultures of the tree-shrew Tupaia belangeri were susceptible to HBV infection at a level as efficient as primary human hepatocytes and without addition of DMSO or polyethylene glycol to the medium (149). Another important progress was also made in 2002 by showing that the new human hepatoma HepaRG cell line was susceptible to HBV infection upon completion of its differentiation program. The presence of 2% DMSO or 4% polyethylene glycol during infection appeared to greatly improve the infection efficiency. At least 10% hepatocyte-like cells were infected and exhibited active production of progeny virions from day 4 following infection (35). It is interesting to note that DMSO induces the liver-specific detoxication function and strongly increases the polarity of HepaRG cells. Transcription of the pregenome and the level of HBV replication are closely related to the level of differentiation in both hepatoma cells and primary human hepatocyte cultures. This close correlation between susceptibility to HBV infection and the cellular differentiation status fits well with the recent observation made with human hepatocytes and showing that transcription factors that regulate hepatocyte differentiation control HBV replication. HNF4α is essential and acts in concerted action with HNF1α (150). HepaRG cells express these two transcription factors (36). Recently, these cells have been used to investigate unresolved issues, particularly the formation of the viral mini-chromosome believed to be responsible for the persistence of infection. A long-term persistence of infection with continuous production of viral particles having poor infection spreading was reported. Analysis of viral DNA showed formation and persistence of covalently closed circular DNA but without amplification. This contrasts with CCC DNA amplification described in duck hepatitis B model (151). See also Chapter 25 of the present volume. Since hepatoma cells replicate the virus more efficiently after transfection, the limited infection efficiency must be related to the
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initial entry phase. This has led to assays undergoing to circumvent infection. As an example, lipid-based delivery of HBV capsids into non-susceptible cells has been successfully used, allowing the production of progeny virus and subviral particles (152). These in vitro models have also been widely used for studying the mechanisms of virus attachment and entry but these remain enigmatic. A number of potential HBV membrane receptor candidates with the help of viral peptides or complete particles have been described but none of them has been confirmed to act as a receptor (153). Only carboxypeptidase has been shown to be indispensable for infection of primary duck hepatocytes with duck hepatitis B virus but its exact role remains to be clarified (153). Prevention of hepatitis B virus infection in vivo by inhibitors derived from the large envelope protein has been demonstrated by using immunodeficient urokinase-type plasminogen activator (uPA) mice repopulated with primary human or T. belangeri hepatocytes (154). Another sophisticated model has been set up consisting in establishing an in vitro cell line (HBV-Met) based on immortalized, highly differentiated hepatocytes prepared from mice transgenic for both c-Met and HBV (155). Efficient HBV replication is maintained in this model which was demonstrated very convenient for analyzing the influence of cytokines and to decipher the antiviral intracellular mechanisms they induce. These different cell models should be appropriate for dissecting the infection process, for titration and mapping of neutralizing antibodies, and for the development of entry inhibitors for future clinical applications and for improving current vaccines. 6.1.2. HCV
HCV is an enveloped positive-stranded RNA hepatotropic virus. Its life cycle is known but its relationship with its host cell is not yet completely understood. Infection and HCV RNA replication was first demonstrated in human hepatocytes in primary culture by the Maurel’s group in 1998 (156) and production of infectious viral particles was obtained by passage from infected to naive hepatocyte cultures with evidence of quasispecies selection with time of culture in 1999 (157). Although the viral cycle was completely reproduced less than 15% infected sera were infectious and the replication rate was low, representing 0.01–0.1 RNA copy per cell. This low and limited reproducibility of infection levels has hampered for a while the use of human hepatocyte primary culture as a reference model for studying the HCV replication cycle. Several groups have therefore attempted to infect hepatoma cell lines in vitro with HCV. Lohmann et al. (158) first obtained stable replication of subgenomic HCV RNAs in Huh-7 human hepatoma cells. The current Huh-7 hepatoma systems, mainly the Huh-7.5 cells which are highly permissive for HCV replication (159) used cloned synthetic HCV RNAs
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or complete viral genome to produce virions or replicons but no complete viral particles could be obtained. In addition, these cells could not be infected with naturally occurring HCV particles from infected patient sera (160, 161). These replicon systems were very useful for analyzing the viral replication process and identifying perturbations of various metabolic pathways of the host cells (162, 163) but were poorly helpful for understanding HCV entry and production of infectious viral particles. A recent major step in investigating the HCV replication cycle was the development of pseudoparticles (HCVpp), consisting of unmodified HCV envelope glycoproteins assembled onto retroviral core particles. These HCV pseudoparticles were able to infect Huh-7 and PLC/PR5 (164). However, a great advantage was obtained with the design of highly sophisticated chimeric viruses that robustly produce infectious particles in Huh-7.5 cells (VHCcc), thus making possible studies on the relationship between the virus and its host cell (165). It is clearly established today that host cell molecules are important as entry factors or receptors for internalization of HCV. They include scavenger receptor B1 (also named SR-B1) (166) tetraspanin CD81 and the tight junction protein claudin-1 (167– 169). Recently, occludin was evidenced as an essential HCV entry factor, rendering both murine and human cells infectable with HCVpp (170). This further highlights the importance of the tight junction complex in the viral entry process. Interestingly, the critical role played by CD81 has recently been evaluated on infection of primary human hepatocytes by HCV positive sera (HCVser) versus JFH1/HCVcc virion particles produced by cell lines. It was found that inhibition of JFH1/HCVcc infection was weaker than that of HCVser and in addition was weaker in primary hepatocytes compared to the Huh-7 cell system by using anti-CD81 antibodies (171). This leads to postulate important differences in affinity or kinetics of HCV interaction with Huh-7.5 versus hepatocyte membrane receptors which might suggest other membrane components not yet known as contributing to host–viral interactions. This highlights interest to pursuing efforts in developing infection models with normal human hepatocytes. Recently Buck (22) succeeded in obtaining high HCV replication in primary human hepatocyte cultures by using stringent culture conditions preserving a high differentiation stage. Hepatocytes were permissive to direct infection with naturally occurring genotypes 1, 2, 3, and 4 and infectious virions. The HCV amplification reached 7 log10 vs 1 log10 in previous studies. Moreover blockers of cell entry and inhibitors of HCV replication were effective. If these results based on only peculiar culture conditions are confirmed, this model will provide new tools for further understanding virion–host cell interactions in conditions close to liver in vivo. See also Chapter 24 of the present volume.
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6.2. Parasitology
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The liver stage of the life cycle of Plasmodium falciparum is an obligatory step in any natural malaria infection. The sporozoites form an exo-erythrocytic form that grows in size and eventually releases 20,000–30,000 merozoites into the blood. Primary hepatocytes and hepatoma cell lines represent valuable models to investigate exo-erythrocytic formation and development and to evaluate drug candidates that may interfere with these processes. Animal and human hepatocyte primary cultures were very early shown to support the exo-erythrocytic development of Plasmodia. Infection with Plasmodium vivax, P. falciparum, and animal parasites was demonstrated (172, 173). Genetic manipulation of the parasites has allowed marked progress in the understanding of hepatocyte infection. Parasites expressing the green fluorescent protein are used to determine infection efficiency and separate infected cells (174). Hepatocyte invasion by P. falciparum sporozoites deficient in expression of the P52 gene, an ortholog of the parasite gene p36p that confers long-lasting protective immunity in mice, was recently analyzed in human hepatocyte primary cultures. The invasion rate was comparable to that of wild-type sporozoites. However, development inside the hepatocyte was arrested very soon after invasion as observed in rodent malaria Plasmodium species with the equivalent gene disrupted (175).
7. Conclusions Considerable progress has been made over the last 40 years in the understanding of the biology of the hepatocyte and liver diseases caused by xenobiotics or biological agents (viruses and parasites) as well as in hepatocyte-based therapies by using suspended and cultured hepatocytes. Primary human hepatocytes remain the most pertinent in vitro liver model, being the closest to the liver in vivo; however, they have serious drawbacks, due to their low access, large donor-to-donor functional variability, and early phenotypic changes occurring in culture. Some liver cell lines are a potential alternative to circumvent such impediments; however, they have lost a large and variable subset of liver-specific functions. The human hepatoma HepaRG cell line appears as an exception since these cells express most of the liver-specific functions normally found in primary hepatocyte cultures and have the growth capacity of hepatoma cell lines (176). Indeed these cells which seem as a homogeneous cell population exhibiting limited karyotype alterations have the property of transdifferentiation into progenitor cells. Consequently, HepaRG cells can be used as
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either undifferentiated or differentiated cells. It is therefore possible to compare the response of undifferentiated (bipotent hepatic progenitors) versus differentiated liver cells and hepatocytes versus biliary cells. Stem cells from either adult or embryonic origin are expected to represent another way to get mature hepatocytes. However, right now only liver progenitors/hepatoblasts can be obtained in spite of the use of various culture conditions. Why HepaRG progenitor cells can fully differentiate together with maintenance of their proliferative capacity, while progenitors originated from stem cells do not is a challenging question. It may be hypothesized that one or some key genes are activated in the transformed HepaRG cells and not in progenitors derived from stem cells. This hypothesis is supported by recent data showing that embryonic stem cells, that are now known to exhibit karyotypic changes in vitro (47, 177), could differentiate into mature hepatocytes (46) and that pluripotent stem cells can be generated from somatic cells by transfection of some transcriptional factors (142, 143, 178). Solving these questions would open new areas for applications of isolated hepatocytes. Cells with a normal karyotype are, however, needed for transplantation in the treatment of liver diseases. One of the major areas of application of hepatocytes is toxicology. Major progress may be expected in the next future with the use of new hepatocyte models (HepaRG cells, other hepatocyte cell lines, probably hepatocytes derived from stem cells, etc.) and new technologies (xenobiotic screening with new automated and miniaturized systems and toxicogenomics technologies). Progress should be made not only on both predictive and mechanistic aspects but also on the design of new methods for genotoxicity testing based on in vitro hepatoyte models. Obviously, even after 40 years of intensive use that has led to major progress in various major areas, in vitro hepatocyte models will still remain essential model systems in most of these areas and future developments can be easily expected in the next years.
Acknowledgments We thank Dr. Anne Corlu for Fig. 1.1, Dr. Remi Le Guevel for Fig. 1.2, and Dr. Marie-Anne Robin for critical reading of the manuscript. Our recent work was supported by EEC contracts (LIINTOP-STREP-037499, COMICS-STREP 037575, PREDICT-IV-contract 202222), ANR contract (06SEST17), INCA-Cancéropôle and the Ligue 35 contre le Cancer.
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a highly differentiated model for studies of 178. Kim, J.B., Sebastiano, V., Wu, G., Arauzoliver metabolism and toxicity of xenobiotics. Bravo, M.J., Sasse, P., Gentile, L., Ko, K., Chem. Biol. Interact. 168, 66–73. Ruau, D., Ehrich, M., van den Boom, D., 177. Spits, C., Mateizel, I., Geens, M., Meyer, J., Hubner, K., Bernemann, C., OrtMertzanidou, A., Staessen, C., Vandeskelde, meier, C., Zenke, M., Fleischmann, B.K., Y., Van der Elst, J., Liebaers, I., and Sermon, Zaehres, H., and Scholer, H.R. (2009) Oct4K. (2008) Recurrent chromosomal abnorinduced pluripotency in adult neural stem malities in human embryonic stem cells. Nat. cells. Cell 136, 411–419. Biotechnol. 26, 1361–1363.
Chapter 2 Human Foetal Hepatocytes: Isolation, Characterization, and Transplantation Anne Weber, Thomas Touboul, Sylvie Mainot, Julie Branger, and Dominique Mahieu-Caputo Abstract Hepatocyte transplantation has become an alternative to orthotopic liver transplantation for the treatment of liver metabolic diseases. However, there is an increasing lack of donor organs and isolated mature hepatocytes are difficult to manipulate and cannot be expanded in vitro. It is therefore necessary to find alternative sources of hepatocytes, and different approaches to evaluate the therapeutic potential of stem cells of different origins are being developed. Hepatic progenitors (hepatoblasts) and/or foetal hepatocytes isolated from foetal livers may be one potential source to generate fully differentiated hepatocytes. We have reported that human foetal liver cells can be isolated and cultured. These cells also engraft and differentiate into mature hepatocytes in situ after transplantation into immunodeficient mice. Foetal cell populations could also be used as targets for gene therapy since efficient gene transfer is achieved with retroviral vectors. Use of such experimental approaches will help design strategies for clinical applications of liver cell therapy with hepatic progenitors. Key words: Foetal hepatocytes, lentiviral vector, transduction, transplantation.
1. Introduction Hepatocyte transplantation as an alternative to whole-organ transplantation has become a reality and to date more than 20 patients with liver metabolic diseases have been transplanted (1, 2). However, this approach is hampered not only by the shortage of organs but also by the poor engraftment efficiency of adult hepatocytes, which also do not proliferate in a quiescent liver (3). One possibility to generate hepatocytes for transplantation is the P. Maurel (ed.), Hepatocytes, Methods in Molecular Biology 640, DOI 10.1007/978-1-60761-688-7_2, © Springer Science+Business Media, LLC 2010
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use of foetal cells. Development of foetal liver begins when the ventral foregut endoderm buds off and gives rise to the early hepatic epithelium through signals from both the cardiac mesoderm and the septum transversum (4, 5). The cells within the liver arise from a multipotent stem cell that will give rise to the liver, pancreas, intestine, and stomach and are recognized as hepatoblasts. These progenitors are bipotent and give rise to hepatocytes and bile duct epithelial cells (or cholangiocytes). Foetal hepatic cells display two specific characteristics common to stem cells, a spontaneous ability to proliferate, which, however, decreases with the developmental stage, and a size half that of adult cells (10–15 vs 20–30 μm), which should allow them to migrate and engraft in the parenchymal plates after transplantation better than their adult counterparts. In vitro studies with rodent and human foetal liver tissue have shown that multipotent progenitor cells, which have features of mesenchymal– epithelial transition and retain capability to differentiate into fat, cartilage bone, and endothelial cells as well as into hepatocytes and bile duct cells, can be isolated (6, 7). Recently hepatic stem cells were also isolated from foetal and post-natal human donors and have been shown to give rise to hepatoblasts in vitro and more mature hepatocytes in vivo after transplantation into the liver of NOD/SCID mice (8). We have isolated a cell population composed mostly of bipotent progenitor cells from human livers at an early stage of development (9). In vivo studies have shown that these hepatic progenitors (hepatoblasts) after transplantation into the liver of nonconditioned immunodeficient mice were able to partially repopulate (up to 7%) transplanted liver by contrast to adult fully differentiated hepatocytes. In this chapter we described methods for isolating from human foetal liver tissues and to characterize the cells in culture. We also describe methods for cell transplantation and in situ detection after lentiviral gene marking.
2. Materials Foetal livers were obtained after the termination of pregnancy performed at 10–13 weeks of gestation and with the informed consent of mothers as recommended by the French Agency of Biomedicine and the local Ethics Committee of Paris XI University (Paris, France). 2.1. Human Foetal Hepatic Cell Isolation
1. Collagenase solution: 0.1 M HEPES (free Acid, ULTROL Grade, Merck), 0.002 M KCl (Sigma), 0.013 M fructose (Sigma), 0.12 M NaCl (Sigma), 2.8 mM Na2 HPO4
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12H2 O2 (Sigma) supplemented with 10 mM CaCl2 (Sigma) and collagenase: Worthington type 1 CLS-1 (129 U/ml). 2. Wash and plating medium: Dulbecco’s modified Eagle’s medium DMEM/HAM F12/WILLIAMS E (1:1:2) (Eurobio) supplemented with 10% heat-inactivated foetal calf serum (FCS, PAA Laboratories GmbH, Austria), 0.1% bovine serum albumin, 2 mM glutamine, and 1% antibiotics (penicillin/streptomycin, 50,000 UI, Eurobio). 2.2. Foetal Hepatic Cell Culture
1. Primaria culture dish (9.6 cm2 ) (BD Bioscience). 2. DMEM/HAM F12/WILLIAMS E supplemented with 5% foetal bovine serum and with: 0.1% linoleic acid–albumin (Sigma Chemicals Co.); store the solution at +4◦ C. 10–8 M insulin (Novo Nordisk, Denmark); store at +4◦ C. 10–6 M hydrocortisone (Merck Sharp & Dohme, Germany); dissolve 100 mg in ethanol and dilute with PBS. Store aliquots at –20◦ C. 10−7 M 3,3 ,5-triiodo-L-thyronine (Sigma). Dissolve in distilled water to a concentration of 25 mM and neutralize by NaOH 10 M. 100 μg/ml ascorbic acid (Roche). 2 mM glutamine and 1% antibiotics (Eurobio).
2.3. Reverse TranscriptionPolymerase Chain Reaction Analysis 2.4. Double Immunostaining
1. TRIzol reagent (Invitrogen). 2. Superscript II reverse transcriptase (Invitrogen). 3. GoTaq Flexi DNA polymerase (Promega). 1. Collagen I pre-coated glass coverslips (BD Biocoat Cells Environment, BD). 2. Phosphate-buffered saline (PBS) (Invitrogen) solution 1× at pH 7.4. 3. Fixation solution: Formaldehyde (Sigma): Prepare a 4% (v/v) solution fresh for each experiment. 4. Quench solution: 50 mM NH4 Cl in PBS. 5. Permeabilization solution: 0.1% (v/v) Triton X-100 in PBS. 6. Blocking solution: 1% gelatin (Sigma) in PBS (Sigma). 7. Antibody dilution buffer: 1% gelatin in PBS. 8. Primary antibody: monoclonal mouse anti-human CK19 antibody (Dako, Glostrup, Denmark). 9. Secondary antibody: Cy-3-conjugated goat anti-mouse antibodies (Amersham Biosciences, LC, England).
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10. FITC-conjugated goat anti-human albumin antibody (Bethyl Laboratories). 11. Nuclei staining: DAPI (Vector Laboratories). 2.5. Immunocytochemistry for Green Fluorescent Protein Expression
1. PBS solution 1× at pH 7.4. 2. Formaldehyde (Sigma): Prepare a 4% (v/v) solution fresh for each experiment. 3. Inhibition of endogenous peroxidase solution: 3% H2 O2 in distilled water. 4. Quench solution: 50 mM NH4 Cl in PBS. 5. Permeabilization solution: 0.1% (v/v) Triton X-100 in PBS. 6. Blocking solution: 3% (w/v) bovine serum albumin (BSA) in PBS. 7. Primary antibody: Anti-GFP antibody, BD Living Colors A.v (Clontech, BD Biosciences, CA, USA). 8. Antibody dilution: 0.1% Tween 20 + 3% BSA in PBS. 9. Secondary antibody: Biotinylated anti-mouse IgG (MOM Vector immunodetection kit; Vector Laboratories, UK). 10. Covalent conjugate between avidin and an enzyme: peroxidase-conjugated avidin (Vector Laboratories). 11. Peroxidase substrate solution: Diaminobenzidine (DAB) chromogene (Dako).
2.6. Western Blot Analysis for ERK Expression 2.6.1. Cell Lysis
1. PBS solution 1×. 2. Protease inhibitor tabs (Complete – Roche). 3. Cell lysis buffer (1X): 20 mM Tris (pH 8), 150 mM NaCl, 50 mM EDTA, 1% Triton X-100 (v/v), 2% BSA (w/v), and Complete (1X). 4. Teflon cell scrapers (Fisher).
2.6.2. SDS-Polyacrylamide Gel Electrophoresis (SDS-PAGE)
1. Mini-Protean 3 Cell (Biorad Laboratories Inc.). 2. Separating buffer (1X): 1.5 M Tris-Cl (pH 8.8), 0.4% SDS. 3. Stacking buffer (1X): 0.5 M Tris-Cl (pH 6.8), 0.4% SDS. 4. Acrylamide/bis (30% A, 2.67% bis) (Biorad Laboratories Inc.). 5. N,N,N,N -tetramethyl-ethylenediamine (Temed – Biorad Laboratories Inc.).
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6. Ammonium persulphate (APS) (Biorad Laboratories Inc.): prepare 10% solution in water and immediately freeze in single use (200 μl aliquots) at –20◦ C. 7. Running buffer (10X): 0.25 M Tris, 1.92 M Glycine, 10% SDS. 8. Sample buffer (3X): Tris-Cl 0.5 M, 10% SDS (w/v), 0.3 M DTT, 15% glycerol (v/v), and 0.5% (w/v) bromophenol blue. 9. Pre-stained molecular weight markers (kaleidoscope markers; Biorad Laboratories). 2.6.3. Western Blotting
1. PVDF transfer membrane Hybond-P (Amersham Biosciences). 2. Transblot SD Semi-dry Electrophoretic Transfer Cell (Biorad laboratories Inc.). 3. Bio-Dot SF filter paper (Biorad Laboratories Inc.). 4. Transfer buffer: 48 mM Tris (do not adjust pH), 39 mM Glycine. 5. PBS with Tween (T-PBS) (1X): 0.001% Tween 20 in PBS. 6. Blocking buffer: 5% (w/v) non-fat dry milk in T-PBS. 7. Primary antibody: rabbit anti-ERK1 (SC94) and mouse monoclonal anti-p-ERK (E4) (Santa Cruz Biotechnology, CA, USA). 8. Appropriated secondary antibodies conjugated to horseradish peroxidase (HRP) (Amersham Biosciences). 9. ECL western blotting detection system and Hyperfilm ECL (Amersham Biosciences).
2.7. Lentiviral Vectors
2.8. Transplantation
Lentiviral plasmid: the GFP gene is under regulatory sequences of apolipoprotein A-II gene (APOA-II). It has been constructed in the laboratory (10). Recombinant lentiviruses are produced by Vectalys (Toulouse, France). 1. PBS solution 1X. 2. Trypsin EDTA 0.25% (InVitrogen). 3. Hoechst 33258 (Sigma). 4. NOD/SCID mice (Charles River Laboratories). 5. Medication: ketamine, xylazine. R Micro 6. Insulin syringe with a 30-gauge needle (BD lance 3).
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2.9. Immunohistochemistry for Albumin Expression
1. PBS solution 1X at pH 7.4. 2. Formaldehyde (Sigma): Prepare a 4% (v/v) solution fresh for each experiment. 3. Inhibition of endogenous peroxidase solution: 3% H2 O2 in distilled water. 4. Quench solution: 50 mM NH4 Cl in PBS. 5. Permeabilization solution: 0.1% (v/v) Triton X-100 in PBS. 6. Blocking solution: 1% (w/v) gelatine from porcine in PBS. 7. Primary antibody: Anti-Alb antibody (Bethyl laboratories, France). 8. Antibody dilution: 0.1% Tween 20 + Antibody Diluent (Dako). 9. Secondary antibody: rabbit anti-goat Ig linked to HRP (Thermo Scientific). 10. Peroxidase substrate solution: Diaminobenzidine (DAB) chromogene (Dako).
3. Methods 3.1. Cell Isolation and Culture
1. Transfer the tissue on ice in medium. If necessary transfer into a 60 mm Petri dish and mince the residual tissue with a sterile forceps and a surgical scalpel to small pieces. 2. Transfer the tissue into a 15 ml centrifuge tube and wash it once in HEPES buffer and successive centrifugation at 50×g for 2 min. 3. Put the tissue in a sterile beaker containing the collagenase solution and a magnetic cross-barrel placed in the hood on a heating magnetic stirrer at 37◦ C (see Notes 1 and 2). 4. Incubate under slow agitation to gently mix the tissue with the collagenase solution for 1 h (usually 50 mg in 25 ml). Every 15 min dissociate mechanically by gently pipetting up and down (see Note 3). 5. Add a volume of plating medium and filter the cell suspension using a 70 μm cell strainer. 6. Transfer the cell solution into 15 ml centrifuge tubes and pellet the cells by centrifugation at 50×g for 5 min. 7. Wash the cells three times by addition of 10 ml plating medium and successive centrifugations at 50×g for 5 min.
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Fig. 2.1. Human foetal hepatocytes 2 days after isolation. Phase-contrast micrograph (magnification ×200).
8. Suspend the cells in plating medium by gently pipetting up and down several times. 9. Count the viable cells with trypan blue using a Malassez cell (see Note 4). 10. Seed the cells in plating medium at a density of 25,000/cm2 on 3-cm Primaria dishes (see Note 5). 11. Change the medium after 24 h for culture medium and then everyday. Depending on the experiments culture medium can be supplemented with 5% FCS and/or cells can be grown in the presence of various growth factors including 20 ng/ml hepatocyte growth factor (HGF) (kind gift of Genentech, San Francisco, USA) (Fig. 2.1). 3.2. Characterization 3.2.1. RT-PCR Analysis
1. Total RNA is extracted by using TRIzol reagent. 2. RNA is reverse transcribed by using the Superscript II reverse transcriptase. 3. cDNA samples are subjected to PCR amplification with DNA primers (Table 2.1). 4. RT-PCR is performed using the GoTaq Flexi DNA polymerase and the following programme conditions: first step of 5 min at 94◦ C, 30 cycles for 30 s at 94◦ C, a 30 s annealing step at 55–60◦ C and 30 s at 72◦ C, and extension for 10 min at 72◦ C (Table 2.1).
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Table 2.1 Primers and conditions used for RT-PCR and size of final products Gene name
Primers sequences
Product length (pb)
Annealing temperature (◦ C)
HNF4alpha
Sense:
370
55
449
55
395
58
675
55
354
55
558
55
247
60
312
55
220
60
CTG CTC GGA GCC ACC AAG AGA TCC ATG Antisense: ATC ATC TGC CAC GTG ATG CTC TGC A HNF6
Sense: GGG CAG ATG GAA GAG ATC AA Antisense: TGC GTT CAT GAA GAA GTT GC
CEBPalpha
Sense: CTC GAG GCT TGC CCA GAC CGT Antisense: GCG GGC TTG TCG GGA TCT CAG
AFP
Sense: AGA ACC TGT CAC AAG CTG TG Antisense: GAC AGC AAG CTG AGG ATG TC
ALB
Sense: CCT TTG GCA CAA TGA AGT GGG TAA CC Antisense: CAG CAG TCA GCC AT TCA CCA TAG G
AAT
Sense: AGA CCC TTT GAA GTC AAG CGA CC Antisense: CCA TTG CTG AAG ACC TTA GTG ATG C
ApoA-II
Sense: GGA GAA GGT CAA GAG CCC GAG Antisense: AGC AAA GAG TGG GTA GGG ACA G
Factor IX
Sense: TGT TGG TGT CCC TTT GGA TT Antisense: TCA CTC AAA GCA CCC AAT CA
Cyp3A7
Sense: AAG TCT GGG GTA TTT ATG ACT Antisense: CGC TGG TGA ATG TTG GAG AC
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3.2.2. Fluorescence Double Immunostaining
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1. Culture the cells on collagen I pre-coated glass coverslips. 2. Wash the cells with PBS twice. Fix the cells with 4% paraformaldehyde (PFA) in PBS for 15 min at 4◦ C. 3. Wash the cells with PBS three times. 4. Pretreat the cells with 1% gelatin in PBS. 5. Incubate the cells for 1 h at room temperature with monoclonal mouse anti-human CK19 antibody (1/100). 6. Wash the cells with PBS three times. 7. Incubate the cells for 1 h at room temperature with Cy-3conjugated goat anti-mouse antibodies (1:400). 8. Wash the cells three times with PBS. 9. Incubate the cells for 1 h at room temperature with FITCconjugated goat anti-human albumin antibody. 10. Counterstain nuclei with DAPI.
3.2.3. Western Blot Analysis
By contrast to adult human hepatocytes, foetal cells express the phophorylated form of ERK, which is induced after stimulation by HGF. 1. Rinse cells with PBS (4◦ C) and scrape the cells in ice cold lysis buffer (1 ml/106 cells). 2. Sonicate samples for 10 s and centrifuge 5 min at 19,000×g. 3. Collect the supernatants and quantify proteins using BCA assay. Store aliquots at –20◦ C. 4. Prepare a 1.5 mm thick, 8% gel by mixing 1.35 ml of acrylamide/bis solution, 1.25 ml separating buffer, 2.37 ml water, 25 μl APS 10%, and 5 μl Temed. Pour the gel, leaving space for a stacking gel, and overlay with isopropanol. The gel should polymerize in about 30 min. Pour off isopropanol and rinse the top of the gel twice with water. 5. Prepare the stacking gel by mixing 0.325 ml of acrylamide/bis solution, 0.625 ml stacking buffer, 1.5 ml water, 25 μl APS 10%, and 5 μl Temed. Pour the stack and insert the comb. Wash the wells with running buffer (1X). 6. Mix sample (10 μg whole lysate) with one-third of sample buffer (3X) and boil for 5 min, cool on ice for 10 min, and spin a few seconds. 7. Load samples, include one well for molecular weight prestained marker. 8. Complete the assembly of the gel unit and carry out electrophoresis at 20 mA through the stacking gel and 40 mA through the separating gel (4 h).
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9. Soak the gel in transfer buffer for 15 min. 10. Cut PVDF membrane and six pieces of filter paper to the dimension of the gel. 11. Soak the membrane briefly in 100% methanol, then in distilled water for 5 min, and in transfer buffer for 15 min. 12. Saturate filter papers and membrane in transfer buffer for 30 min. 13. Assemble the sandwich transfer onto the anode as follows: three filter papers, PVDF membrane, gel, and three filter papers. 14. Exclude all air bubbles by rolling a pipet over the surface of the paper. Transfer is accomplished within 1 h at 160 mA. 15. Incubate the membrane in blocking buffer overnight at 4◦ C on a rocking platform then wash it three times for 15 min each with T-PBS. 16. Add the primary antibody for 2 h at room temperature on a rocking platform (anti-ERK1, E4 at 1:500 or anti-p-ERK, SC-94 at 1:2,000) and wash the membrane four times for 15 min each with T-PBS. 17. Add the appropriate secondary antibody in blocking buffer (anti-rabbit 1:2,000 and anti-mouse 1:1,000) for 1 h at room temperature on a rocking platform, then wash five times for 10 min each with T-PBS. 18. Reveal immunoreactive bands by the enhanced chemiluminescence system. 19. Once a satisfactory exposure for the p-ERK has been obtained, the membrane is then stripped of that signal and then reprobed with antibody that recognizes unphosphorylated ERK. 20. The stripping is realized according to the conditions described by the manufacturer. 21. The membrane is then blocked as mentioned earlier and then ready to be reprobed anti-ERK as described above. 3.3. Cell Labelling with the Hoechst Fluorescent Dye
1. Remove the culture medium and wash the cells with Ca++ /Mg++ -free PBS. 2. Remove PBS and add 0.25% trypsin solution. Put the dish back to the incubator for a few minutes and monitor dissociation under an invert phase-contrast microscope. 3. When cells are released add several millilitres of plating medium to inhibit trypsin, centrifuge at 50×g for 5 min.
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4. Wash once in PBS and adjust hepatocyte suspension at 107 cells/ml in serum-free medium per 12 ml conical tube. 5. Add 5 μl of Hoechst 33258 at 10 mg/ml to the cell suspension and incubate for 30 min at 37◦ C with gentle agitation. 6. Stop the reaction by addition of 1 ml FCS then addition of 9 ml medium containing 10% FCS (plating medium). 7. Transfer the cells to new 12 ml conical tubes and wash the cells three times in plating medium and centrifugation at 50×g for 5 min. 8. Suspend the cells in PBS at 4 × 105 cells/10 μl for transplantation. 3.4. Retroviral Transduction
Transferring genes into foetal hepatic cells could enhance the scope of cell transplantation. Recombinant vectors derived from the onco-retroviruses (Moloney murine leukaemia virus) can be used to efficiently transduce foetal hepatic cells, by contrast to adult hepatocytes, since the cells divide extensively the first days after plating (9). However, since these vectors infect both dividing and non-dividing cells, and since the design of lentiviral vectors leads to safer recombinant lentiviruses, devoid of viral enhancer and promoter sequences, with high titre it is recommended to use lentiviral vectors rather than oncoretrovirus. These self-inactivating vectors express the gene of interest from internal promoters. An important consideration in designing vectors is promoter selection, especially if in situ gene marking of transplanted cells is to be performed. Viral promoters, including cytomegalovirus immediate-early promoter (CMV-IE), are silenced in situ and therefore ubiquitous promoter such as the eukaryotic initiation factor 1 alpha promoter (EF1α) or hepatocyte-specific promoter such as alpha 1-antitrypsin have to be used. As most of the vectors are pseudotyped with the vesicular stomatis G (VSV-G) envelope, they can be concentrated to yield high-titre viral particles.
3.4.1. Cell Transduction
Foetal cells are isolated as described above. They are suspended in plating medium without serum at a concentration of 1–10 × 106 cells/ml in cryotubes and incubated with recombinant lentivirus at MOI=30 for 2–3 h at 37◦ C. The tubes are left unscrewed to allow gas exchanges (see Notes 6 and 7). After incubation the transduced cells are plated in plating medium. After 24 h the medium is replaced by HDM supplemented with 5% FCS and after 4–5 days of culture (see Note 8).
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3.4.2. Detection of Transduced Cells
1. Wash the transduced cells three times with PBS. 2. Fix with 4% PFA for 15 min at 4◦ C then wash three times for 5 min. 3. Incubate in blocking solution for 20 min at room temperature. 4. Incubate in PBS/0.1% Triton X-100 for 10 min at room temperature. 5. Incubate in PBS/1% bovine serum albumin for 1 h at room temperature. 7. Incubate the cells with the anti-GFP antibody for 1 h at room temperature then wash three times for 5 min each in 0.1% Tween/PBS. 8. Apply the secondary biotinylated antibody according to the M.O.M kit staining procedure, then wash three times for 5 min each in 0.1% Tween/PBS. 9. Reveal by incubation with a solution of amino-ethylcarbazol for 10 min at room temperature and wash three times for 5 min each. Mount in glycergel (Fig. 2.2).
Fig. 2.2. Transduction of foetal hepatocytes using a GFP-expressing lentiviral vector. Phase-contrast micrograph (magnification ×200).
3.5. Cell Transplantation
1. 4- to 5-week-old NOD/SCID mice. 2. Anaesthetize with suitable medication (ketamine, 50 mg/kg +xylazine 20 mg/kg), place in right decubitus position, and clean the abdominal wall with iodine.
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3. Make 0.5–1 cm incision below the left subcostal abdominal wall with sharp scissors. 4. Inject 0.8–1 × 106 cells through a 1 ml insulin syringe with R Microlance 3) into the spleen. a 30-gauge needle (BD 5. Close the abdominal incision with 4-0 nylon sutures. 6. Return the animal into its cage, keep warm under heating lamp until recovery from anaesthesia, and administer analgesia. 3.6. Identification of Engrafted Hepatocytes by Albumin Histochemical Staining
1. Fix the samples in formaldehyde solution for 10 min at room temperature. 2. Wash the samples three times for 5 min each with PBS. 3. Inhibit endogenous peroxidases with 3% H2 O2 in PBS for 30 min at room temperature and wash twice with PBS. 4. Incubate in NH4 Cl for 15 min at room temperature to quench residual formaldehyde and then wash three times with PBS. 5. Incubate in PBS/0.1% Triton X-100 for 10 min at room temperature and then rinse three times with PBS. 6. Incubate in blocking buffer for 1 h at room temperature. 7. Incubate the sections with the anti-Alb antibody for 1 h at room temperature in a humid chamber and wash three times with PBS. 8. Apply the secondary antibody linked to HRP, then wash the sections twice with PBS.
Fig. 2.3. Detection of transplanted hepatocytes. Transplanted cells are visualized in recipient mouse liver using an antihuman albumin antibody (magnification ×400).
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9. Apply DAB solution on the sections and control development times under a microscope (between 2 and 10 min in the dark), then wash with distilled water three times for 2 min each. 10. Mount the samples in glycergel or glycerol (90% in PBS) if counterstaining is necessary (Fig. 2.3).
4. Notes 1. Filter HEPES solution after adjusting pH to 7.4. Prepare collagenase solution immediately before dissociation and filter it. 2. The batch of collagenase is critical for cell viability. Batches are first tested for their ability to produce high yields, maximum viability, and membrane recovery of rat hepatocytes. Currently collagenase type 3 (PAA Laboratories, France) or type 1 CLS-1 Worthington is used. 3. Agitation of the collagenase solution for liver tissue dissociation must be controlled and slow. The choice of the magnetic stirrer is therefore important. We purchased the stirrer from Fisher Bioblock Scientific. 4. The number of cells plated is difficult to estimate as the cells are isolated in clusters. 5. Unattached cells mainly haematopoietic cells wash easily from the surface of monolayer cultures during medium changes after 48 h. Additional washes can be performed. 6. We use aliquots of the virus stocks to prevent decrease of virus titre after freeze–thaw cycle. Virus can be thawed and frozen once if rapidly frozen in liquid nitrogen prior to storage in –80◦ C. 7. Polybrene is generally used at 8 μg/ml. We rather use 3 μg/ml for foetal and adult hepatocytes for retroviral transduction. 8. We wait at least 5 days after transduction, so that all virus particles are integrated but also to avoid any possible pseudotransduction, i.e. passive incorporation of GFP protein into the viral particle, or phagocytosis of plasmid DNA interfering with the results (11). As control, cells can also be pre-incubated for 1 h prior to transduction with different concentrations (from 1 to 10 μM) of 5 -azido thymidine (AZT, GlaxoSmithKline), an inhibitor of reverse transcriptase, which is also added every 24 h to the culture medium
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until cell harvest. In this sample transduction rate is expected to be close to 0%.
Acknowledgements This work was supported by “Association Française contre les Myopathies” and French Ministry of Research (Grant ANR-RIB 2005). References 1. Smets, F., Najimi, M., and Sokal, E.M. (2008) Cell transplantation in the treatment of liver diseases. Pediatr. Transplant. 12, 6–13. 2. Puppi, J. and Dhawan, A. (2009) Cell transplantation in the treatment of liver diseases. Methods Mol. Biol. 481, 1–16. 3. Azuma, H., Paulk, N., Ranade, A., Dorrell, C., Al-Dhalimy, M., Ellis, E., Strom, S., Kay, M.A., Finegold, M., and Grompe, M. (2007) Robust expansion of human hepatocytes in Fah-/-/Rag2-/-/Il2rg-/- mice. Nat. Biotechnol. 25, 903–910. 4. Lemaigre, F. and Zaret, K.S. (2004) Liver development update: new embryo models, cell lineage control, and morphogenesis. Curr. Opin. Genet. Dev. 14, 582–590. 5. Zhao, R. and Duncan, S.A. (2005) Embryonic development of the liver. Hepatology 41, 956–967. 6. Suzuki, A., Zheng, Y.W., Kaneko, S., Onodera, M., Fukao, K., Nakauchi, H., and Taniguchi, H. (2002) Clonal identification and characterization of self-renewing pluripotent stem cells in the developing liver. J. Cell Biol. 156, 173–184. 7. Dan, Y.Y., Riehle, K.J., Lazaro, C., Teoh, N., Haque, J., Campbell, J.S., and Fausto, N. (2006) Isolation of multipotent progenitor cells from human fetal liver capable of differentiating into liver and mesenchymal lineages. Proc. Natl. Acad. Sci. USA. 103, 9912–9917.
8. Schmelzer, E., Zhang, L., Bruce, A., Wauthier, E., Ludlow, J., Yao, H.L., Moss, N., Melhem, A., McClelland, R., Turner, W., Kulik, M., Sherwood, S., Tallheden, T., Cheng, N., Furth, M.E., and Reid, L.M. (2007) Human hepatic stem cells from fetal and postnatal donors. J. Exp. Med. 204, 1973–1987. 9. Mahieu-Caputo, D., Allain, J.E., Branger, J., Coulomb, A., Delgado, J.P., Andreoletti, M., Mainot, S., Frydman, R., Leboulch, P., Di Santo, J.P., Capron, F., and Weber, A. (2004) Repopulation of athymic mouse liver by cryopreserved early human fetal hepatoblasts. Hum. Gene Ther. 15, 1219–1228. 10. Parouchev, A., Nguyen, T.H., Dagher, I., Mainot, S., Groyer-Picard, M.T., Branger, J., Gonin, P., Di Santo, J., Franco, D., Gras, G., and Weber, A. (2006) Efficient ex vivo gene transfer into non-human primate hepatocytes using HIV-1 derived lentiviral vectors. J. Hepatol. 45, 99–107. 11. Negre, D., Mangeot, P.E., Duisit, G., Blanchard, S., Vidalain, P.O., Leissner, P., Winter, A.J., Rabourdin-Combe, C., Mehtali, M., Moullier, P., Darlix, J.L., and Cosset, F.L. (2000) Characterization of novel safe lentiviral vectors derived from simian immunodeficiency virus (SIVmac251) that efficiently transduce mature human dendritic cells. Gene Ther. 7, 1613–1623.
Chapter 3 Isolation and Culture of Primary Hepatocytes from Resected Human Liver Tissue Edward L. LeCluyse and Eliane Alexandre Abstract As our knowledge of the species differences in drug metabolism and drug-induced hepatotoxicity has expanded significantly, the need for human-relevant in vitro hepatic model systems has become more apparent than ever before. Human hepatocytes have become the “gold standard” for evaluating hepatic metabolism and toxicity of drugs and other xenobiotics in vitro. In addition, they are becoming utilized more extensively for many kinds of biomedical research, including a variety of biological, pharmacological, and toxicological studies. This chapter describes methods for the isolation of primary human hepatocytes from liver tissue obtained from an encapsulated end wedge removed from patients undergoing resection for removal of liver tumors or from resected segments from whole livers obtained from multi-organ donors. In addition, methods are described for culturing primary hepatocytes under various matrix compositions and geometries, which reestablish intercellular contacts and normal cellular architecture for optimal phenotypic gene expression and response to drugs and other xenobiotics in vitro. Overall, improved isolation, cultivation, and preservation methods have expanded the number of applications for primary human hepatocytes in basic research, which has allowed for exciting advances in our understanding of the biochemical and molecular mechanisms of human liver toxicity and disease. Key words: Primary human hepatocytes, in vitro hepatic model systems, cell isolation methods, sandwich culture.
1. Introduction The liver serves as the primary site of detoxification of natural and synthetic compounds in the systemic circulation. Other biological and physiological functions include the production and secretion of critical blood and bile components, such as albumin, bile salts, and cholesterol. The liver is also involved in the protein, steroid, P. Maurel (ed.), Hepatocytes, Methods in Molecular Biology 640, DOI 10.1007/978-1-60761-688-7_3, © Springer Science+Business Media, LLC 2010
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and fat metabolism, as well as vitamin, iron, and sugar storage. The parenchymal cells or hepatocytes are highly differentiated epithelial cells that perform many of the functions attributed to the liver. Much of their functional diversity is revealed in the complexity of the cytological features of the cells. Hepatocytes are highly polarized cells that are dependent on the maintenance of two distinct membrane domains. The sinusoidal and canalicular membrane domains are separated by tight junctions and exhibit striking ultrastructural, compositional, and functional differences. The maintenance of a polarized cell and membrane architecture is essential for maintaining normal biliary excretion and xenobiotic elimination. One of the most complex functions specific to the liver is its ability to metabolize an enormous range of xenobiotics. Many drugs present in the blood are taken up by hepatocytes where they can be metabolized by phase I and II biotransformation reactions. Much remains to be learned about the biochemical and molecular factors that control the expression and regulation of normal hepatocyte structure and function in humans. Because of these issues, the use of in vitro and in vivo systems to evaluate hepatic drug uptake and metabolism, cytochrome P450 (CYP450) induction, drug interactions affecting hepatic metabolism, hepatotoxicity, and cholestasis is an essential part of toxicology and pharmacology (1–9). Within the literature, one can find a number of different approaches that have been applied successfully for the isolation and cultivation of primary human hepatocytes (1, 2, 10–21). However, for the novice who is attempting to identify those methods and conditions that are most appropriate for a particular type of study, this task may appear overwhelming initially. Likewise, there are few sources available for obtaining detailed information needed to perform in vitro studies utilizing primary human hepatocytes. This chapter describes the isolation and culture of human hepatocytes from liver tissue obtained from one of two sources, an encapsulated end wedge removed from patients undergoing resection for removal of liver tumors or from resected tissue from whole livers obtained from multi-organ donors. This procedure is essentially a modification of the two-stage perfusion and digestion described by MacDonald et al. (20) and has been adopted by an interlaboratory consortium sponsored by the European Centre for the Validation of Alternative Methods (ECVAM) for the isolation and cultivation of primary human hepatocytes for testing the potential of new drugs to induce liver enzyme expression. This chapter attempts to address some of the more important issues and caveats that must be considered when utilizing primary cultures of human hepatocytes for drug evaluation, especially for long-term studies of gene expression (e.g., induction or suppression). The effects of different culture
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conditions on the restoration and maintenance of normal hepatic structure and function in vitro also are presented, especially as they relate to testing the potential of new drugs to alter liver enzyme expression (see also Chapter 23).
2. Materials 2.1. Human Liver Tissue
Adult human liver tissue suitable for the isolation of hepatocytes is either from donors undergoing surgical liver resection for the removal of metastatic tumors or from brain-dead-but-beatingheart donors, inasmuch as liver tissue is exquisitely sensitive to ischemia and deteriorates rapidly after death. Rejected livers are shunted to agencies such as the National Disease Research Interchange (NDRI) (Philadelphia, PA), International Institute for the Advancement of Medicine (IIAM) (Edison, NJ), or to NIH contract organizations that are part of the Liver Tissue Procurement and Distribution System (LTPADS) (see Note 1) to be distributed to academic and industrial researchers. These livers, ranging in weight from 1,500 to 2,500 g, are rarely sent as whole livers but rather are carved up by agency staff members to maximize the number of researchers receiving samples. Each researcher receives a piece that is usually about 100–200 g and that must be perfused through cut blood vessels exposed on the surface of the sample. The sample is shipped to the investigator as quickly as possible but often arrives late in the evening meaning that the initial work on human liver samples is often overnight. The triaging of the liver from donor to either recipient or to investigators takes about 12–24 h. The conditions prior to death and the cold ischemia of the transport conditions can result in the deterioration of the sample. Thus, the quality of the starting material is extremely variable. The samples arrive flushed with cold preservation buffer, most commonly University of Wisconsin solution (“UW” solution or R Viaspan ), bagged and on ice. For donor organs it is generally accepted that the overall organ integrity and function begins to deteriorate after 18 h of cold storage and will not be used for transplant after this time. In our experience, the quality of the cells prepared from donor organs that have been procured >18–20 h reflects this general phenomenon, and lower yields and viability of the polyploidal cell populations are observed compared with fresher organs or tissue. We also have observed that, in general, organs received >24 h after clamp time often do not yield cells of adequate quality nor are the cells able to efficiently attach to culture substrata (21). However, the time threshold after which a particular organ cannot produce cells of adequate quality is affected by several factors including
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age of the donor, proficiency of organ preservation, the quality of the tissue perfusion, and disease state of the organ (e.g., extent of cirrhosis and steatosis) (22). For the most part, organs should be a uniform tan or light brown color when received; organs that appear “bleached” or dark brown should not be used and generally yield only non-viable or CYP450-depleted cells. Medium containing phenol red with hepatocytes isolated from these organs often has a characteristic pink color, especially when mixed with R Percoll , which is believed to be reflective of the depletion of certain macromolecules from the damaged cells. Normal remnants from partial hepatectomy represent an alternative source of tissue for the isolation of primary hepatocytes, especially for many European and Asian countries due to legal and ethical considerations. In our experience fresh surgical waste tissue often yields better preparations of cells especially when prolonged warm and cold ischemia times are avoided. In a retrospective examination of the influence of human donor, surgical, and post-operative characteristics on the outcome of hepatocyte isolation obtained from liver surgical waste following hepatectomy from 149 patients, we showed that neither donor disease nor mild steatosis has a detrimental effect on the yield, viability or attachment rate of the cells (22). However, it was concluded that biopsy tissue weight (>100 g) and warm ischemia longer than 60 min affected the total yield and overall viability of the preparations. Recently, a multi-laboratory study examined the effects of liver source, pre-flushing conditions, tissue transport time, and specific hepatocyte isolation conditions and concluded that (1) surgical liver resections are preferable to tissue from rejected donor organs, (2) preflushing is only necessary if transport time from the surgical suite is greater than 1 h, (3) preflushed tissue is stable during transport for at least 5 h, and (4) ideally digestion times not longer than 20 min should be used (21). 2.2. Collection of Liver Samples
Based on the discussion above and depending on the source of the donated adult human liver specimen one of two protocols should be followed when transporting tissue directly from procurement centers: 1. For livers obtained from centers where they can be transported from source to the laboratory in less than 60 min the lobe should be placed in ice-cold medium (e.g., Dulbecco’s Modified Eagle’s Medium (DMEM)). 2. For livers obtained from remote locations, where transport will take >1h, samples should be pre-perfused with Hypothermosol-FRS (Biolife Solutions), UW solution (Viaspan), or Soltran (Baxters) and transported in this solution on melting ice. From our experience, tissues can be
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successfully preserved in these solutions for >18 h if the warm ischemia time is kept to a minimum and the tissue is flushed quickly and thoroughly with the preservation medium. 2.3. Supplies and Equipment
1. Suitable apparatus to include platform for liver undergoing perfusion and digestion, peristaltic pumps capable of flow rates between 5 and 50 ml, heating unit to maintain temperature of system at a constant 34–35◦ C, and variablesized buffer tanks to accommodate liver tissue (see Note 2). 2. Water bath for maintaining perfusion buffers at 36–37◦ C. 3. Class II biosafety cabinet. 4. Suitable surgical instruments, including knife scalpels, tissue, and hemoclip forceps. 5. Sterile gauze and cotton-tipped applicators. 6. Disposable pipettes. 7. Suitable filter apparatus for size separation (850–1,000, 400–500, and 90–100 μm) or equivalent apparatus for filtering cell suspensions. 8. Microcentrifuge tubes, 1.5 ml. 9. Polyethersulfone 0.2-μm filters. 10. Suitable refrigerated centrifuge with rotor, buckets, and adaptors to accommodate 50–250 ml centrifuge tubes for cell sedimentation. 11. Sterile screw-capped centrifuge tubes (50 and 250 ml). 12. Cannulas – 14–22 G or equivalent adapters. Flexibility in length and diameter is required to address the wide variety of vessel sizes. 13. Plastic tubing adaptors and fittings – a variety of bevel sizes and lengths can be obtained from most scientific vendors; one side of the adaptors must fit diameter of the perfusion pump tubing. R 14. Masterflex biocompatible tubing (size 14–16), joints, and suitable connectors for cannulas.
15. Suitable disinfectant for surfaces and instruments. 16. Suitable sterile containers including trays, bowls, and dishes for tissue preparation, perfusion, and dissociation steps. 17. Protective gear – safety glasses, laboratory coveralls, shoecovers, bonnets, surgical mask, and protective sleeves. 18. Set of sterile teflon or nylon mesh filters (Spectra Labs, Inc., Tacoma, WA): 850–1,000, 400–500, and 80–100 μm mesh sizes.
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2.4. Reagents
R 1. Instant medical adhesive (Loctite 4013 cyanoacrylate adhesive, Loctite Corp.).
2. Percoll (Sigma). 3. Phosphate buffered saline (PBS) 10×. 4. Trypan blue solution 0.4%, liquid, sterile filtered (Sigma). 5. Ethyleneglycol-bis(2-aminoethylether)N,N,N,Ntetraacetic acid (EGTA), tetrasodium salt (Sigma). 6. Dulbecco’s modified Eagle’s medium (DMEM) with HEPES and 4.5 g/l glucose, without phenol red (Gibco). If medium is kept longer than a period of 1 month, add R 1 ml of L-glutamine 100× (Gibco) or 1 ml of Glutamax I 100× (stable L-glutamine) (Gibco) to 100 ml DMEM. 7. Insulin: Prepare stock solution of bovine insulin (Gibco or Sigma-Aldrich) at 4 mg/ml. Store reconstituted powder at 4◦ C. 8. Collagenase (Sigma type IV or Gibco type II), preferred activity 400–600 units/mg (see Note 3). 9. Fetal bovine serum (FBS) (Gibco). 10. Penicillin–streptomycin 100× solution (Gibco). 11. Dexamethasone (Sigma, cell culture tested), dissolve 3.925 mg in 1 ml DMSO to prepare 10 mM solution and store aliquots of 100 μl at –20◦ C. Use at a final concentration of 1 μM in media for hepatocyte isolation (dilution 1/10,000) (see Note 4). 12. Dimethyl sulfoxide (DMSO) (Sigma). 13. Hanks’ balanced salt solution (HBSS): Ca++ - and Mg++ free, without phenol red (Gibco). 14. Bovine serum albumin (BSA) Fraction V (Sigma). 15. Hank’s balanced salt solution without phenol red (HBSS) (Gibco). 16. Perfusion buffer 1 (P1 medium): Prepare 0.5 mM EGTA (234.2 mg/l), 0.5% w/v BSA, and 50 μg/ml ascorbic acid in Ca++ - and Mg++ -free HBSS. Filter sterilize using a 0.2-μm polyethersulfone filter. Store at 4◦ C for up to 4 weeks. 17. Perfusion buffer 2 (P2 digestion medium): Prepare 0.03–0.05% w/v collagenase (300–500 mg/l), 0.5% (w/v) BSA in DMEM. Filter sterilize using 0.2-μm polyethersulfone filter. Store at 4◦ C for up to 4 weeks; protect from light.
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18. Suspension and Attachment Medium: Prepare 5% FBS, and penicillin–streptomycin (100 U/ml and 100 μg/ml, respectively) in DMEM. Filter sterilize and store at 4◦ C for 4 weeks. Complete medium by adding insulin (4 μg/ml, 1/1,000 of stock) and 1 μM dexamethasone (1/10,000 of stock) just before use. Completed suspension medium may be stored for up to 1 week at 4◦ C and protected from light. 19. Percoll (90% isotonic solution): Prepare fresh on each occasion. Mix 45 ml of Percoll and 5 ml 10× PBS. Mix well before use. Store at 4◦ C; warm to 37◦ C just before use. 20. Rat-tail collagen (BD Biosciences, Palo Alto, CA) at 4 mg/ml. 21. DMEM 10×: (Sigma). 22. 0.2 N NaOH. R R 23. Matrigel (BD Biosciences, Palo Alto, CA) or Geltrex (Gibco).
24. Cell harvest and homogenization buffer: 50 mM Tris–HCl, 150 mM KCl, 2 mM EDTA (Sigma), pH 7.4.
3. Methods The following procedure describes the isolation of human hepatocytes from liver tissue obtained from one of two sources: an encapsulated end wedge removed from patients undergoing liver resection for removal of metastatic tumors or resected segments from non-transplantable whole livers obtained from multi-organ donors. 3.1. Preparation for Liver Perfusion
1. Place P2 medium (100 ml/10 g liver) in water bath at 34–35◦ C. 2. Keep 100–200 ml of P1 medium at 4◦ C for initial flushing of liver segment and place the remainder in water bath. 3. Set up tissue preparation area inside of biosafety cabinet, including absorbent pads, ice tray containing shallow stainless steel or plastic tray for tissue preparation, instruments, cold P1 buffer, 30–60 ml syringe with attached cannula, medical adhesive, 2×2 in. gauze pads, and cotton swabs (see Fig. 3.1A). 4. Set up perfusion apparatus inside biosafety cabinet, including water bath or other heating apparatus, peristaltic pump(s), tubing with adaptors and bubble trap (see Fig. 3.1B). Place
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Fig. 3.1. Setup for tissue preparation area (A), perfusion apparatus (B), and cell isolation materials (C) inside a biosafety cabinet.
the appropriate size container, such as a glass bowl in the water bath or heating unit and partially fill with HBSS (enough to cover tissue when submerged). Purge perfusion lines and bubble trap of air prior to initiating perfusion; rinse perfusion lines with plenty of 70% ethanol, flush with reagent-grade water, and ensure temperature of system is slightly hypothermic at 34–35◦ C (see Note 2) (17). Ensure that all lines and bubble trap are free of trapped air bubbles prior to initiating perfusion of tissue. 5. Set up cell isolation and culture materials (e.g., in separate biosafety cabinet or adjacent to perfusion apparatus if only one cabinet is available), disinfect surfaces, prepare suspension and attachment medium and sufficient R 90% Percoll solution and place in separate water bath (see Fig. 3.1C).
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3.2. Perfusion of Resected Human Liver Tissue 3.2.1. Preparation and Cannulation of Tissue
1. Wearing proper attire and protective gear, carefully remove liver tissue from shipping container, place on balance in sterile pre-weighed container and record weight (see Note 5). 2. Using a Teflon cannula attached to a 60-ml syringe, flush the liver tissue with ice-cold P1 medium using several blood vessels on the cut surface (see Fig. 3.2A). This will clear any excess blood from the liver and help to determine the vessels that will offer optimal perfusion of the tissue. 3. Using a sterile gauze pad, dab dry the cut surface of the liver around the vessels to be cannulated.
Fig. 3.2. Resected human liver tissue (A) prior to cannulation, illustrating the flushing of a candidate vessel prior to placing the cannulae, (B) after placement of fittings and reinforcement with gauze padding, and (C) inside glass bowl attached to perfusion lines. Note that the resection is entirely submerged and floating in the perfusion buffer.
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4. Cannulate the chosen vessels (two cannulae are generally sufficient, but up to four might be required) using one of the following: a. A 200-μl pipette tip will be suitable in most cases (cut off end of pipette tip to obtain optimal size to fit snugly into each vessel opening). b. A 16–22-gauge Teflon cannula with needle removed. This is best for very small pieces. c. Beveled plastic tubing adaptors. Most useful with larger pieces and lobes; a variety of diameters and lengths can be used as required. 5. Make a collar around the periphery of the cannula with medical adhesive at the point where it will join the tissue on the cut surface; then, insert the cannula into vessel opening. Secure the cannula in place by adding more adhesive around cannula–tissue interface. 6. Once the cannulae are securely in place, seal all other open vessels on the cut surface using medical adhesive. For the larger openings it may be necessary to seal them using hemoclip forceps or a cotton-tipped applicator. The wooden dowel from the cotton-tipped applicator can be used or the cotton tip can be reduced to sufficient diameter to fit into individual vessels (cut off the protruding end of the wooden dowel so that no more than a few millimeters emerges from mouth of the vessel). Secure the cotton tip or wooden dowel in place by making a collar around the edge with medical adhesive. 7. Once all open vessels are securely sealed, dab dry the cut surface of the liver tissue, and seal entire surface with a thin layer of adhesive; apply and spread adhesive using a cottontipped applicator. 8. In some cases there may be a cut or tear on the outer capsule of the liver tissue (Glisson’s capsule) or there might be more than one cut surface. These must be sealed to ensure optimal perfusion of the tissue. In the event that a large surface area or tear must be sealed then cut appropriate-sized squares of single sheets of sterile gauze padding, soak with medical adhesive, and place like a bandage over large or damaged areas (see Fig. 3.2B). 9. Allow the medical adhesive to dry sufficiently before initiating the perfusion. Optimal perfusion results are obtained when major exit points are sealed adequately to allow for sufficient back-pressure to develop upon initiation of the perfusion process.
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1. Once the adhesive has dried adequately, place the liver into a large weigh boat and test the integrity of the sealed surface by connecting a separate perfusion line to each cannula and start the perfusion pump at a slow flow rate (do not exceed 5–10 ml/min/cannula initially; small resections may require lower flow rates). The liver tissue should slowly inflate as back-pressure begins to build and the sealed surface should remain intact (avoid over-inflating tissue). 2. If no overt leaks are observed, place several small evenly spaced pinpricks along the outer edge of the encapsulated portion of the tissue and carefully lower the tissue into the tank containing warm HBSS inside the water bath until it is completely submerged (see Fig. 3.2C) (17). 3. Slowly increase the flow rate for the P1 medium until perfusate and residual blood are observed flowing from the incisions on encapsulated surface edges. The flow rate will vary with the size of the tissue and how well it is sealed (ideally, the entire tissue specimen should be uniformly flushed with little or no residual blood or discoloration visible). On average, flow rates vary between 15 and 30 ml/min/cannula for resections weighing between 20 and 100 g. 4. Perfuse tissue with P1 medium for 10–15 min and periodically check progress of perfusion to ensure that integrity of the sealed surface and cannulae remains intact. Aspirate excess HBSS/perfusate mix from the reservoir with sterile pipette when buffer level begins to reach container capacity. 5. While P1 medium is perfusing through the liver tissue, prepare P2 medium with collagenase (see Section 2.4 for additional details). For most tissue specimens, use 50–60 mg collagenase per 100 ml of P2 medium, and for cirrhotic or steatotic (>40% fat) tissues, use 100–120 mg collagenase per 100 ml of P2 medium. Depending on the size of the tissue, the volume of P2 should be ∼100 ml/10 g liver tissue, and, therefore, the amount of collagenase will vary based on tissue mass and enzymatic activity of the individual batch of enzyme (see Note 3). After adding collagenase to P2 buffer, mix thoroughly until all residual collagenase is dissolved. Place P2 with collagenase back into water bath until needed. 6. After the initial perfusion with P1 medium is complete, stop the perfusion pump(s) and switch perfusion line to container with warmed P2 medium containing collagenase. 7. Restart perfusion pump(s) and perfuse for approx. 15–25 min at a flow rate that maintains similar tissue inflation as before. Optimal perfusion time will vary depending
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upon the activity and concentration of the collagenase, temperature, flow rate, and the size of the liver resection. 8. Watch for indications of complete digestion such as softening of the parenchyma when probed gently with a sterile wet cotton swab, visual signs of structural breakdown (e.g., loss of distinctive surface texture and development of fissures), and enlargement of the tissue. Complete digestion should be achieved within the specified time frame if a proper batch and concentration of collagenase has been chosen. However, it is important not to over-extend the perfusion time, as this might lead to excessive cell damage and a progressive loss in viability and attachment efficiency. 9. When the perfusion is complete, stop pump(s), disconnect tubing from cannulas, gently remove the liver from the perfusion chamber, and place in a sterile covered bowl or dish then proceed to the biosafety cabinet containing supplies and equipment for hepatocyte isolation. 3.3. Isolation of Hepatocytes from Digested Liver Tissue 3.3.1. Disaggregation of Liver Tissue
1. Add a sufficient volume (approx. 1–2 ml/g tissue) of warm (37◦ C) suspension medium (DMEM supplemented with 5% FBS and hormones [see Section 2.4]) to the dish containing the digested liver tissue. 2. Using tissue forceps and scissors remove the adhesive layer and cannulae from the cut face of the tissue, and with the cut surface facing down gently tear open the Glisson’s capsule (see Fig. 3.3A). With the aid of the tissue forceps, gently shake the tissue to release the hepatocytes into the medium. Further release of hepatocytes from the residual connective tissue and vascular tree can be accomplished by gently passing the tissue between the tissue forceps. This process may take several cycles of shaking and stroking the tissue to remove most of the parenchymal cells from the vascular tree and undigested material. Ideally, a successful perfusion and tissue dissociation is depicted by a near complete release of the parenchyma from the remnant connective tissue and vasculature tree (see Fig. 3.3B). 3. Add additional warm suspension medium (final volume: approx. 5 ml/g tissue) and filter the digested material through a series of Teflon, nylon, or stainless steel mesh filters using further warm medium (up to 1 l) to aid this process as appropriate: 850- to 1,000-μm mesh → 400- to 500-μm mesh → 90to 100-μm mesh
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Fig. 3.3. Resected human liver tissue (A) after digestion, demonstrating the opening of the outer membrane (Glisson’s capsule) with forceps, (B) after several minutes of shaking and stroking tissue in suspension medium to remove parenchymal material, and (C) during filtering of the resultant cell suspension. Note that the cell suspension is poured through a stacked filter system from top to bottom through the largest → smallest mesh size, respectively.
Use a large funnel and filter into sterile bottles or beakers as needed (see Fig. 3.3C). It might be necessary at the initial stage to use a syringe plunger to carefully encourage filtering. 4. The resulting cell suspension is then divided equally into sterile centrifuge bottles (ensure the suspension is not too dense [approx. 5–10 ml/g total liver]) and washed by lowspeed centrifugation (75×g for 5 min). The size of the centrifuge tubes will vary according to the amount of material (50–250 ml). 5. Discard or retain the supernatant (see Note 6) and gently resuspend each pellet in approx. 5–10 ml of suspension medium and combine into a single tube. Subject to pellet size, cells are resuspended in suspension medium using
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roughly a 1:8-fold dilution. At this stage cells should be counted and viability assessed using trypan blue. 6. Switch to 50-ml sterile centrifuge tubes if larger tubes were used for the spin in Step 4. Resuspend the pellets in warm suspension medium and warm 90% isotonic Percoll; the ratio of volumes should be approx. two parts cell suspension to one part isotonic Percoll (see Section 2.4 for details on Percoll preparation) (e.g., 34 ml of cells in DMEM + 16 ml R of 90% isotonic Percoll ). Sample tubes should be loaded 6 with approx. 200×10 cells per 50 ml tube (do not exceed a maximum of 300×106 total cells/tube). 7. Centrifuge at 150–170×g for 20 min at room temperature. 8. Carefully remove the top layer of the supernatant that contains dead cells and other debris; care should be taken not to disrupt the pellet(s) or contaminate it with the contents from the top layer of debris. Gently resuspend the pellet(s) in suspension medium, combine into one or two 50-ml tubes (≤500×106 cells/tube), and centrifuge for a final time at 100×g for 5 min. 9. Gently resuspend the final cell pellet in 10 ml of warm suspension medium per 1 ml of cell pellet. If cells are to be cultured then keep at room temperature; if cells are to be cryopreserved then place on ice. 3.4. Cell Count and Viability Assessment
1. Perform a cell count and viability assessment by trypan blue exclusion using a hemocytometer. Prepare eight parts suspension medium, one part trypan blue stock reagent, one part cell suspension (v/v/v), and invert tube gently to ensure a uniform cell suspension. 2. Add appropriate volume of cell suspension to fill the chambers of the hemocytometer and count at least four of the mm2 quadrants with an average of 80–120 cells per quadrant (approx. 400 cells total). 3. Determine total cell yield, percent viability, and cell integrity (see Fig. 3.4). 4. Remove sufficient cells for d0 biochemical assessments (see Note 7).
3.5. Monolayer Culture of Primary Human Hepatocytes 3.5.1. Plating Hepatocytes
Human hepatocytes derived from the two-step liver digestion method described in the previous sections can be cultured for a variety of biochemical, cellular, and molecular studies. This section describes the seeding, maintenance, and harvest of primary cultures of human hepatocytes.
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Fig. 3.4. Freshly isolated human hepatocytes from two separate donor tissues viewed under brightfield optics. (A) Hepatocytes exhibiting mostly normal morphology with clear cytoplasms and intact, well-delineated plasma membranes. Note that some cells possess surface blebs (B) which are caused by either physical or chemical damage and/or oxidative stress. (B) Hepatocytes isolated from a donor organ with high fat content. Note the presence of large lipid droplets (L) within the cytoplasm of most cells. Although the presence of lipid changes the morphological characteristics of the hepatocytes considerably, after several days in culture they generally exude their lipid contents and appear similar to hepatocytes from normal, healthy liver tissue.
1. Dilute the cell suspension with attachment medium (see comments in Section 2.4) to give the required final cell density (see Table 3.1 and Note 8). Dispense an aliquot of cell suspension into a test dish or multiwell plate and check the cell density under the microscope and adjust if necessary. It is important not to either underseed or overseed because both will lead to subconfluent monolayers (see Fig. 3.5). 2. Add the appropriate volume of cell suspension to each well or dish (see Table 3.1 and Note 9). Swirl the bottle of cells gently before seeding each multiwell plate or stack of dishes to ensure the suspension remains homogenous (see Note 10). 3. Place the stack of dishes or plates in a 95%/5% air/CO2 incubator at 37◦ C.
Table 3.1 Determination of seeding density for different types of tissue culturetreated vessels Type of dish or multiwell plate
Seeding density (viable cells/ml)
Volume/dish or well
Total number of viable cells
100 mm dish
1.5×106 –1.75×106
6 ml
9×106 –10.5×106
60 mm dish
1×106 –1.33×106
3 ml
3×106 –4×106
6-well plate
5×105 –7.5×105
2 ml
1×106 –1.5×106
12-well plate
5×105 –7.5×105
1 ml
5×105 –7.5×105
24-well plate
5×105 –7.5×105
0.5 ml
2.5×105 –3.75×105
96-well plate
5×105
125 μl
6.25×104
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Fig. 3.5. Graphical representation of the influence of seeding density on the percent confluence of the resulting monolayers. Optimal seeding density is typically achieved at densities between 125,000 and 150,000 cells/cm2 (∗ ). Note that subconfluent monolayers result from either under- or over-seeding cultures.
4. In order to ensure formation of uniform monolayers, gently swirl the dishes or plates in a figure-of-8 pattern when placing them in the incubator. In the case of 24- to 48-well plates, make a cross-shape (⇔, ) while shaking the plates. 5. Allow hepatocytes to attach for 4–12 h at 37◦ C in the incubator. 6. Assess attachment efficiency by gently swirling the culture vessels and counting cells in the aspirated medium from two to three dishes or wells (attachment efficiency of ≥80% is required for optimal monolayer formation). Observe cells under the microscope to confirm confluence (see Fig. 3.6). 7. After attachment, cultures should be swirled adequately to remove unattached cells and debris and the attachment
Fig. 3.6. Light micrographs of hepatocyte monolayers at optimal (A) and suboptimal (B) seeding density. Note the difference in the confluence of the monolayer and the corresponding changes in the morphology of both the cytoplasm and the nucleus of most cells. Inset: Increased signs of stress over time, such as vacuole formation, are often observed in hepatocytes at low plating densities.
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Fig. 3.7. Human hepatocytes cultured under different matrix conditions for 72 h. (A) Freshly isolated hepatocytes on a rigid collagen substratum and overlaid with medium alone. (B) Hepatocytes maintained between two layers of gelled collagen, type I. Hepatocytes maintained in the “sandwich” configuration form trabeculae or cord-like arrays throughout the monolayers. (C) Hepatocyte cultures on a rigid collagen substratum with a top layer of Matrigel. (D) Hepatocytes maintained on a substratum of Matrigel. Human hepatocytes maintained on a gelled layer of Matrigel aggregate together to form clusters or colonies of cells that become more three-dimensional over time in culture. All cultures were maintained in modified Chee’s medium supplemented with ITS+ (BD Biosciences) and dexamethasone (0.1 μM).
medium carefully aspirated and replaced with the appropriate medium, depending on the specific studies to be performed (see Note 11). In some cases, the cells can be overlaid with either Matrigel, Geltrex, or collagen hydrogels to enhance the development of a more histotypic architecture (see Sections 3.6 and Fig. 3.7). 3.5.2. Maintenance and Dosing of Hepatocyte Cultures
1. Generally, medium is replaced on a daily basis and hepatocytes are maintained for 36–48 h prior to treatment with drugs or other agents intended or expected to alter the gene expression profiles (see Note 12). Dosing with test compounds generally is started 48 or 72 h postplating. Dosing solutions containing drugs and xenobiotics that modulate liver enzymes are renewed typically every 24 h for 3–5 days depending on the purpose and end point of the studies (5). 2. Stock solutions of drugs are prepared in a compatible solvent, such as DMSO or methanol, at 1,000-fold higher concentrations as those required for experimentation.
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3. Dosing tubes are prepared prior to the first dosing day and labeled according to the dosing groups. Plates or dishes are labeled and arranged in stacks according to dosing groups. 5. At the end of the treatment period, monolayers may be harvested for biochemical assessment (see Section 3.5.3), fixed for microscopic evaluation and immunostaining (23), or treated with substrates directly to assess inherent enzyme activities (24). 3.5.3. Harvest of Hepatocyte Monolayers
1. After the dosing period, cells should be harvested into appropriate solutions depending on the biochemical or molecular tests to be conducted, such as homogenization buffer or appropriate RNA preservation reagent (e.g., TRIzol, RNAeasy) (5, 9), and stored at −80◦ C. This procedure need not be performed under sterile conditions; however, standard precautions should be observed when handling samples for isolation of RNA to minimize RNase contamination and loss of sample integrity. 2. Place homogenization buffer and HBSS on ice. Label 5- to 10-ml tubes according to the treatment groups and place on ice. 3. Gently rinse each culture dish or well twice with ice-cold HBSS, taking care not to disrupt the cell monolayer. Drain excess buffer from the culture vessel by inverting over a paper towel. 4. For isolation of cellular fractions, add 3 ml of homogenization buffer (total) to each treatment group (approx. 0.5 ml per 60-mm dish). Using a cell scraper or rubber policeman, scrape the cells into the homogenization buffer. Transfer cells in buffer to a corresponding tube, taking precautions not to leave behind any residual cellular material. This process is repeated for each sample group and tubes are kept on ice until harvest is complete. R 5. For isolation of RNA, add 1 or 2 ml of Trizol (or equivalent reagent) to each well of a 6-well plate or 60-mm dish, respectively, and scrape cells with a cell scraper. Pipette sample up and down several times until sample is dissolved completely (this step may take longer with samples overlaid with matrix). Transfer samples to the corresponding RNase-free tube, seal tube tightly, and store on ice. Repeat process for each sample until harvest is complete.
6. Store all samples at −80◦ C (in screw-cap or snap-cap tubes) or process immediately to prepare cellular fractions. 3.6. Overlay with Extracellular Matrix (Optional)
Extracellular matrix composition and configuration have been proposed to play a key role in the maintenance of hepatocyte structure and function in vitro (25–28). Many different matrix
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Fig. 3.8. Immunolabeling of primary cultures of human hepatocytes maintained for 3 days in a sandwich configuration showing the normal distribution of (A) actin microfilaments, (B) microtubules, (C) E-cadherin, and (D) gap junctions (Cx-32). BC: bile canaliculus; GP: gap junction.
conditions have been tested and found to be appropriate given that the proper cell density is maintained (see Fig. 3.7). An overlay with extracellular matrix such as Matrigel, Geltrex, or collagen is recommended in most cases to avoid variability in monolayer quality and to restore normal cell polarity and cytoskeletal distribution (see Fig. 3.8). In addition, the addition of an overlay of ECM can be more “forgiving” of misjudgments on the part of inexperienced scientists or unforeseen differences in cell attachment efficiency. 3.6.1. Overlay with Collagen
1. Prepare the required amount of gelled collagen as described in Table 3.2. All solutions must be kept on ice and must be handled with cold glass pipettes. The final concentration of gelled collagen will be approx. 1.5 mg/ml. (Note that volumes only apply if using rat-tail collagen, type I, from BD Biosciences.) 2. In the order shown on Table 3.2, add the components listed into a tube on ice and gently mix. 3. After cells have attached (from Section 3.5.1), aspirate the medium. Swirl dishes well prior to removal of medium to ensure all unattached cells and debris are removed.
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Table 3.2 Preparation of collagen solutions for overlaying hepatocyte monolayers Final volume (ml)
5
10
15
20
Collagen (ml)
2
4
6
8
Sterile water (ml)
2
4
6
8
10× DMEM (ml)
0.5
1
1.5
2
0.2 N NaOH (ml)
0.5
1
1.5
2
4. Tilt dishes at an approx. 45◦ angle against a tray and let them stand for a few seconds to allow excess medium to collect at the edge of the dish; then aspirate it. 5. Gently add 5–10 μl of diluted collagen per cm2 culture area (i.e., 200 μl per 60-mm dish) (see Note 13). Use a cold 1-ml pipette and place the drops in the center of the dish. Only handle a maximum of five dishes at any one time to prevent gelling of the collagen prematurely. 6. Gently tilt and rotate the dishes to spread the collagen evenly over the surface of the monolayers and place them back in the incubator. Leave for 45–60 min to allow the collagen to gel. Place any remaining collagen in the incubator; this provides a way of checking the gelling process. 7. Carefully add back appropriate volume of warm medium according to Table 3.1 to the center of the dish or well (see Note 14). 3.6.2. Overlay with Matrigel or Geltrex
Both dilute (5 mg/ml) and concentrated (10–13 mg/ml) Matrigel or Geltrex stocks can be used for the overlay. However, dilute stocks do provide the advantage of being easier to work with and are less likely to gel when handled. 1. Calculate the amount of stock solution required to yield a final protein concentration of 0.25 mg/ml in the desired medium (see Table 3.1 and Note 15). 2. Slowly thaw out stock solution by placing in slushy ice. It will take at least 2–3 h for the frozen stock solution to be fully thawed (see Note 16). 3. Place refrigerated culture medium on ice and using an icecold glass pipette, add the required volume of stock solution to the culture medium and mix well by swirling. 4. Rinse the pipette with the cold medium after transferring the stock solution to ensure that none is left behind in the pipette. Ensure that matrix protein is well mixed in the medium. In the event that an entire vial or tube of stock
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solution is required, rinse the vial or tube out with ice-cold medium to remove any residual matrix material from the bottom and sides of the container. 5. Aspirate medium from the cultures, ensuring all the unattached cells and debris are removed by swirling the culture vessel. 6. Add appropriate volume of overlay medium per dish or well and then return cells to the incubator (see Note 11 and Table 3.1). 7. Leave cultures undisturbed for 24 h, after which the medium should be replaced with ECM-free medium for subsequent experiments and treatments.
4. Notes 1. The Liver Tissue Procurement and Distribution System (LTPADS) is a National Institutes of Health (NIH) service contract to provide human liver from regional centers for distribution to scientific investigators throughout the United States. LTPADS provides liver tissue and isolated hepatocytes from “normal” human liver to NIH investigators. NIH investigators are always given preference for tissue requests. Supporting letters for NIH new or renewal grant requests can be provided. Direct inquires can be made to Harvey L. Sharp, M.D., Principal Investigator, Department of Pediatrics, Gastroenterology and Nutrition, University of Minnesota, Minneapolis, MN (http://www.peds.umn.edu/Centers/ltpads). 2. Instructions for materials, setup, and use of basic perfusion equipment are described by David et al. (17). RecomR mended pump system and tubing are the Masterflex L/S brushless variable speed digital drive pump (10–600 rpm) R with Masterflex L/S Easy-Load II pump head (model no. R 77200-52) and Masterflex platinum-cured silicone tubing (HV-96410-14/16) (size 14–16). A histological tissue preparation bath with accompanying Pyrex dish (Boekel analog standard model, cat. no. 145701) is a suitable heating bath system that is capable of accommodating most resected liver specimens. 3. Most liver perfusions are done with collagenase preparations that are partially purified. Different companies indicate the degree of purification with a company-specific nomenclature and one must read the company’s literature to learn the details of the nomenclature and its implications
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for the extract or purified factor(s) being sold. Generally, the liver perfusions are done with a preparation that is intermediate in purity (e.g., type IV in Sigma’s series, CLS2 in Worthington’s series, type II in Gibco’s series, or Type B or C in the Boehringer Mannheim series), because both collagenase and one or more proteases are required for optimal liver digestion. Moreover, the most successful liver digestions are often achieved with a mixture of purified collagenase and purified elastase at precise ratios (29, 30). A commercially available mixture of purified digestive enzymes for perfusion of liver tissue is Liberase Blendzymes from Roche Applied Science (Indianapolis, IN). However, its use has been limited due to its high cost. With any preparation of collagenase it is essential to pre-screen individual lots or batches to determine the optimum concentration and perfusion times. Optimal collagenase digestion conditions are a function of temperature, time, and concentration. Every batch of collagenase will inflict damage and be potentially lethal to cells; therefore, one must determine the balance between achieving optimal tissue digestion (highest yields) while minimizing cell damage and death (highest viability). In general, prolonged perfusion times (>30 min) are detrimental to hepatocyte health, especially from tissues that have been in cold storage for prolonged periods, and should be avoided. To improve tissue digestion, it is preferred to increase the collagenase concentration while minimizing the perfusion times. 4. Glucocorticoids (e.g., dexamethasone or hydrocortisone) can have significant effects on the basal expression of many genes in vitro, such as albumin and the cytochromes P450 (6, 31). 5. As with any human-derived tissue or cells, universal biohazard precautions should be taken at all times when handling liver tissue samples. For optimum protection, laboratory coveralls, surgical gloves, safety glasses or face-shield, shoe covers, and hair bonnet should be worn prior to handling and perfusing human liver specimens. 6. The supernatant contains nonparenchymal and progenitor cells, which can be isolated separately according to a number of published methods. 7. Store 9–10 million cells for d0 biochemical assessment. Centrifuge 5 min at 75×g, resuspend pellet in 3 ml of appropriate buffer, such as homogenization buffer, R R TRIzol , RNAeasy , and store at −80◦ C. 8. Of all the various factors discussed thus far regarding optimal cultivation of human hepatocytes in vitro, proper seed-
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ing density ranks first, by far, in terms of importance for restoring the normal phenotype and responsiveness to treatment with drugs and other xenobiotics. Several studies have shown that this is related to the restoration and maintenance of proper cell–cell interactions (12, 23, 32). Plating densities in the range of 125,000–150,000 cells/cm2 appear to be optimal for the formation of confluent monolayers (1, 6, 23). Notably, higher seeding densities can be used for Matrigel- or Geltrix-coated dishes and plates; however, densities that are too high on any type of substratum will interfere with cell attachment and cause less subconfluent monolayer formation (see Fig. 3.5). 9. Example calculation: Volume of cell stock required =
Volume of cell suspension needed × seeding density Stock density
Need to seed 15×60 mm dishes. Require 3 ml/dish. So total cell suspension needed = 45 ml. Make 50 ml of cell suspension: Seeding density = 1.33×106 viable cells/ml. Stock cell density = 1×107 viable cell/ml Volume of cell stock needed =
50 ml × 1.33 × 106 cells/ml = 6.65 ml 1 × 107 cells/ml
Take 6.65 ml of stock cell suspension and dilute to 50 ml in DMEM. 10. Generally do not pipette more than one stack of dishes (15 ml per five 60-mm dishes) or one plate (12 ml/plate) at a time to minimize settling of cells during plating. 11. In our experience, serum-free medium formulations, such as modified Chee’s medium (MCM), Williams’ E medium (WEM), or Hepatocyte Maintenance Medium (HMM) (Biowhittaker, CC-3197), supplemented with insulin (4–6 μg/ml), transferrin (4–6 μg), selenium (5–6 ng/ml), and BSA/linoleic acid (1 mg/ml) are adequate for performing CYP450 induction studies and maintaining monolayer integrity and hepatocyte morphology for at least 1 week. However, experiments requiring longer culture periods (>2 weeks) may require more specialized medium formulations and additives (12, 18, 19).
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12. Experimental evidence suggests that primary human hepatocytes are refractory to modulating agents until normal cell–cell contacts are restored (1, 6). 13. For example, 200 μl/60 mm dish, 100 μl/well of 6-well plate, 50 μl/well of 12-well plate, and so forth. 14. When adding medium back to the culture vessels, the medium should form droplets that “dance” across the gel. This is a good sign that the collagen has gelled sufficiently. Appropriate volumes are shown in Table 3.1. 15. Example calculation for Matrigel or Geltrex dilution: – Have 10 multiwell plates, 12 ml total medium per plate; therefore, require 120 ml of medium. – The amount of overlay protein per dish must be 0.25 mg/ml. – 0.25×120 = 30 mg of overlay protein are required in total. – Stock solution is 10 mg/ml, 30/10 = 3 – Therefore, must add 3 ml of the 10 mg/ml stock solution to 117 ml of medium. 16. Do not try to speed up the thawing process by placing Matrigel or Geltrex at room temperature or by warming in hand as this will cause it to gel prematurely. Allow enough time for the stock solution to thaw (2–3 h on ice), so that it is ready to use once the medium is ready to be changed after cell attachment.
Acknowledgments The authors would like to thank Joel LeCluyse for providing photographic images (Figs. 3.1–3.3). We also acknowledge the invaluable contributions of Drs. Benjamin Calvo, Kevin Behrns, and David Gerber (USA) and the staff of Drs. Daniel Jaeck, Georges Mantion, and Bruno Heyd (France) for assistance with the procurement of human liver tissue in support of this project. References 1. Maurel, P. (1996) The use of adult human hepatocytes in primary culture and other in vitro systems to investigate drug metabolism in man. Adv. Drug Del. Rev. 22, 105–132.
2. Guillouzo, A. (1998) Liver cell models in in vitro toxicology. Environ. Health Perspect. 106 Suppl 2, 511–532. 3. Komai, T., Shigehara, E., Tokui, T., Koga, T., Ishigami, M., Kuroiwa, C., and Horiuchi,
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LeCluyse and Alexandre outcome of isolated human hepatocytes. Cell Tissue Bank 3, 223–233. Hamilton, G.A., Jolley, S.L., Gilbert, D., Coon, D.J., Barros, S., and LeCluyse, E.L. (2001) Regulation of cell morphology and cytochrome P450 expression in human hepatocytes by extracellular matrix and cellcell interactions. Cell Tissue Res. 306(1), 85–99. Kostrubsky, V.E., Lewis, L.D., Strom, S.C., Wood, S.G., Schuetz, E.G., Schuetz, J.D., Sinclair, P.R., Wrighton, S.A., and Sinclair, J.F. (1998) Induction of cytochrome P4503A by taxol in primary cultures of human hepatocytes. Archiv. Biochem. Biophys. 355, 131–136. Bissell, D.M., Arenson, D.M., Maher, J.J., and Roll, F.J. (1987) Support of cultured hepatocytes by a laminin-rich gel. Evidence for a functionally significant subendothelial matrix in normal rat liver. J. Clin. Invest. 79(3), 801–812. Ben-Ze’ev, A., Robinson, G.S., Bucher, N.L., and Farmer, S.R. (1988) Cell-cell and cellmatrix interactions differentially regulate the expression of hepatic and cytoskeletal genes in primary cultures of rat hepatocytes. Proc. Natl. Acad. Sci. USA 85, 2161–2165. Brill, S., Zvibel, I., Halpern, Z., and Oren, R. (2002) The role of fetal and adult hepatocyte extracellular matrix in the regulation of tissue-specific gene expression in fetal and adult hepatocytes. Eur. J. Cell Biol. 81, 43–50.
28. Richert, L., Binda, D., Hamilton, G., Viollon-Abadie, C., Alexandre, E., BigotLasserre, D., Bars, R., Coassolo, P., and LeCluyse, E. (2002) Evaluation of the effect of culture configuration on morphology, survival time, antioxidant status and metabolic capacities of cultured rat hepatocytes. Toxicol. In Vitro 16, 89–99. 29. Gill, J.F., Chambers, L.L., Baurley, J.L., Ellis, B.B., Cavanaugh, T.J., Fetterhoff, T.J., and Dwulet, F.E. (1995) Safety testing of Liberase, a purified enzyme blend for human islet isolation. Transplant. Proc. 27(6), 3276–3277. 30. Olack, B.J., Swanson, C.J., Howard, T.K., and Mohanakumar, T. (1999) Improved method for the isolation and purification of human islets of Langerhans using Liberase enzyme blend. Hum. Immunol. 60(12), 1303–1309. 31. Pascussi, J.M., Drocount, L., Fabre, J.M., Maurel, P., and Vilarem, M.J. (2000). Dexamethasone induces pregnane X receptor and retinoid X receptor-alpha expression in human hepatocytes: synergistic increase of CYP3A4 induction by pregnane X receptor activators. Mol. Pharmacol. 58, 361–372. 32. Greuet, J., Pichard, L., Ourlin, J.C., Bonfils, C., Domergue, J., Le Treut, P., and Maurel, P. (1997) Effect of cell density and epidermal growth factor on the inducible expression of CYP3A and CYP1A genes in human hepatocytes in primary culture. Hepatology 25(5), 1166–1175.
Chapter 4 Optimisation of the Cryopreservation of Primary Hepatocytes Nicola J. Hewitt Abstract The use of cryopreserved hepatocytes has increased in the last decade due to the improvement of the freezing and thawing methods and has even achieved acceptance by the U.S. Food and Drug Administration for use in drug-metabolising enzyme induction studies. This chapter provides an overview of the theories behind the process of cryopreservation and some of the most important advances which have led to the ability to cryopreserve hepatocytes, which when thawed retain functions similar to fresh cells. Parameters such as cell density, cryoprotectants and freezing media should be considered as well as storage conditions and thawing techniques. Special emphasis is placed on human hepatocytes but information for the cryopreservation of animal hepatocytes is also described. Finally, a suggested method for optimising cryopreservation method is outlined. Key words: Cryopreservation, human, animal, hepatocytes, optimisation.
1. Introduction The preparation of viable human hepatocytes which attach in culture has long been the “Holy Grail” of researchers and despite strong early opinions that hepatocytes could not be frozen successfully, confidence in cryopreserved hepatocytes has never been higher. Contrary to original reports in which the recovery of hepatocytes was compromised by cryopreservation (1–3), current methods now enable the use of cryopreserved hepatocytes for assays in which previously only fresh cells could be used, for example, drug-metabolising enzyme (DME) induction studies and bile transporter function assays (4, 5). This chapter outlines the “dos P. Maurel (ed.), Hepatocytes, Methods in Molecular Biology 640, DOI 10.1007/978-1-60761-688-7_4, © Springer Science+Business Media, LLC 2010
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and don’ts” for the preparation of hepatocytes for cryopreservation and tips on how to achieve the best quality hepatocytes upon thawing. If cells are thawed using the best technique (the importance of which is often underestimated), then optimisation of the cryopreservation method can be correctly assessed, therefore a section is also dedicated to how to thaw hepatocytes. The method of cryopreservation is based on preventing cellular damage due to ice crystal formation and chemical changes in cells as they cool and eventually freeze. In order to understand cryopreservation methods, changes that occur in the cell suspension upon cooling/freezing, as well as thawing, should be considered. Early attempts to freeze hepatocytes involved the use of different freezing rates (6–8). These varied between placing the cells in a −20◦ C freezer and rapid freezing by plunging cells into liquid nitrogen. It appeared that a constant slow decline in temperature, regardless of the rate, was deleterious to the cells (6). This is because a slow rate of freezing causes the ice in the medium to freeze before intracellular ice, resulting in a higher osmolarity in the medium. Water leaves the cells by osmosis which causes them to shrink. Hepatocytes can survive a small degree of “dehydration” but if the temperature continues to decrease at a slow rate, too much water leaves the cells and they start to collapse on themselves (plasmolysis). Moreover, loss of intracellular water causes precipitation of solutes, changes in pH and denaturation of proteins – all leading to cell death (9). In contrast to slow freezing, rapid freezing does not allow intracellular water to leave the cells because the rate of freezing is too fast to allow osmosis and equilibration of intra- and extracellular solutes to occur. In this case, the water in the cells rapidly freezes and forms ice crystals which disrupt membrane structures (plasma membrane and intracellular organelle membranes). As a result of studies optimising freezing rates, it became apparent that a compromise was needed between slow freezing, allowing a small amount of water to leave the cells, and fast freezing, preventing excessive water loss but minimal mechanical damage due to ice crystals (8) (see also Chapter 5).
2. Programmable Freezing and Storage
Most freezing regimens follow the freezing profile example shown in Fig. 4.1. A programmable freezer allows for a controlled and precise rate of freezing and can take into account the increase in temperature of the cell suspension when the latent heat of fusion is released (at about −9.5◦ C when the concentration of DMSO is 10%). The fusing of ice crystals releases heat which is measureable and is reported to compromise the success of cry-
Cryopreservation Methods
85
Temperature (°C)
20 0 –20 –40 –60 "Shock-freeze"
–80 –100
0
10
20
30 40 Time (min)
50
60
Fig. 4.1. An example of a freezing profile controlled by a programmable freezer. The solid line represents the temperature of the freezing chamber. The dashed line represents the temperature of the cell suspension when frozen with a “shock-freeze” included at time at which the latent heat of fusion is released. The dotted line represents the temperature of the cell suspension when the “shock-freeze” is not included.
opreservation (10). This effect is counteracted by adding a small “shock freeze” in the freezing profile (Fig. 4.1). Initially, the cells are cooled slowly down to 0◦ C if they are pre-incubated at 37◦ C prior to freezing (see Section 3.3), maintained at this temperature for 10 min and then gradually frozen down to −30◦ C (which includes the “shock freeze” to maintain the continued gradual decrease in temperature in the cell suspension itself (Fig. 4.1)). This slow freezing step allows for loss of some intracellular water but not enough to cause changes in solute concentrations. After this, the temperature is dropped by 70◦ C to −100◦ C in 10 min, which effectively freezes all water remaining in the cells and prevents further loss of water. The vials of cells should be transferred to a storage container as quickly as possible (see Note 1). Early methods for freezing hepatocytes did not employ programmable freezers and even today, alternatives to these can still be used. A simple freezing protocol first introduced by Chesnè and Guillouzo (8) uses only −20◦ C and −80◦ C freezers and, of course, liquid nitrogen – all common to many laboratories. The cells are placed in the −20◦ C freezer for 12 min, then transferred to a −80◦ C for 1 h and then plunged into liquid nitrogen. This has shown to be successful in the cryopreservation of hepatocytes from a number of species (11–14). Others have used special cooling boxes containing isopropanol to freeze cells at a constant rate (1◦ C/min) by placing them into a −80◦ C freezer for 8–24 h (15, 16). This method of freezing human and pig hepatocytes was found to be equally effective as a programmable freezer with respect to initial cell viabilities, attachment efficiencies and some DME activities (15–17). After freezing, the vials of cells should be transferred to a storage container maintained at less than −130◦ C since some chemical reactions (proteases) are still possible at temperatures warmer than this, and they may compromise cell viability and recovery (i.e. the number of viable cells surviving cryopreservation).
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Ideally, cells can be stored at −150◦ C in a freezer (see Note 2), −160◦ C in the vapour phase of nitrogen or −196◦ C in liquid nitrogen (see Note 3). Storage at −80◦ C for longer than 2 h leads to lower initial post-thaw viabilities (18). Thus, if stored correctly, the recovery (e.g. post-thaw viability and attachment) can be maintained for years (11). There is some debate as to whether storing cells in liquid nitrogen compromises the quality of hepatocytes although this is not due to the temperature per se since no chemical reaction will occur at this temperature (19).
3. Cell Treatment Prior to Freezing The process of cryopreservation is likely to result in the recovery of only the healthiest cells, suggesting that unhealthy cells which were frozen are removed. However, the success of cryopreservation is highly dependent on the use of only the healthiest fresh cells, especially if the goal is to obtain plateable hepatocytes (15, 18). There are a number of ways to improve the quality of cells before they are cryopreserved. 3.1. Percoll Purification
It has been reported that purifying rat and dog hepatocytes using Percoll prior to cryopreservation results in higher cell recoveries after thawing (20). However, Percoll is known to cause a substantial loss of viable cells (20), unless the method is optimised (21) (see Note 4). Therefore, it is recommended that the concentrations of Percoll and/or centrifuge speed are adjusted for hepatocytes of different species (due to differences in their sizes (22)).
3.2. Pre-culture
In this method, fresh cells are allowed to recover by placing them in culture before being cryopreserved. There have been two different methods reported based on this concept: 1. Cryopreservation of cultured cells: Cells that are plated resynthesise cofactors that are lost during isolation (13), as well as cytoprotective compounds such as reduced glutathione (GSH) (23). Therefore, it may be expected that cells in culture may be more resistant to cryoinjury than cell suspensions. Indeed, there are reports of successful cryopreservation of cultures of rat (24, 25) and pig (26) hepatocytes. Likewise, Kafert-Kasting et al. (27) cultured fresh human hepatocytes at double the normal seeding density onto collagen gel and cryopreserved the entire culture plate. The cultures were cryopreserved in 10% DMSO, stored in vapour phase nitrogen and then thawed in a 37◦ C incubator. The advantage of the single gel method over a double gel sandwich configuration (26) is that it allows for any dead
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cells to detach from the plate after thawing, leaving only functional cells remaining. A second layer of collagen can be added subsequently. This method has not been adopted as a standard, possibly because of the variability in success and the practicalities of storing large culture plates. 2. Cryopreservation of cell suspensions which have been precultured: This method involves culturing of hepatocytes for 24 h before removing them using trypsin and diluting the resulting cell suspensions in cryoprotective freezing medium (15). This treatment did not affect the pre-cultured hepatocytes from reattaching to collagen-coated plates and resulted in good post-thaw viabilities, attachment efficiencies, metabolic capacities and cytochrome P450 induction responses of rat, dog and human hepatocytes. This study supports the concept that only the healthiest hepatocytes should be cryopreserved but the method itself may not be practical or economical if large numbers of hepatocytes are to be handled. 3.3. Pre-incubation with Medium Supplements
Simply incubating hepatocytes at 37◦ C for a short time prior to cryopreservation allows cells to recover from the effects of isolation and washing (16, 18). The media in which the hepatocytes are incubated can be supplemented with a number of “goodies” that may increase the success of the cryopreservation: 1. Fructose and/or alpha-lipoic acid: Attachment of rat and human cryopreserved hepatocytes may be improved by preincubating the fresh hepatocytes with fructose and/or alphalipoic acid prior to freezing (28). 2. Glucose (5 mM) and insulin (1 nM): Loven et al. (17) reported beneficial effects of pre-incubation of pig hepatocytes with optimal concentrations of glucose and insulin. These supplements increase glycogen content of hepatocytes which is broken down to glucose-6-phosphate after thawing; and thus provides an energy source which is reported to be lacking in these cells (17, 29). The opposing but connected pathway to glycogenolysis is gluconeogenesis, which requires ATP for the uptake of its precursor, glycerol (17). By contrast, glycogenolysis does not require ATP; therefore, it is more likely that hepatocytes would produce pyruvate from glucose rather than the ATP-consuming gluconeogenesis. Others have pre-incubated fresh cells in glucose-containing Krebs–Henseleit buffer for 30 min in a 5% CO2 and 95% O2 atmosphere to improve the attachment efficiency of both rat and human cryopreserved hepatocytes (30). 3. Reduced glutathione (GSH): GSH is a cytoprotective compound found in high concentrations in hepatocytes (∼5 mM
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(31)). The isolation procedure itself may cause depletion of GSH but this effect can be reduced by using a method of isolation with a shorter duration (23). In addition, cryopreservation also causes hepatocytes to lose about half their GSH ((32), Table 4.1). GSH “mops up” reactive oxygen species, decreases lipid peroxidation and prevents apoptosis (33), and clearly, depletion of such an important cytoprotective agent would compromise the cells’ ability to survive cryoinjury. This cannot be achieved by simply adding GSH to the culture medium because it will not cross the plasma membrane but is synthesised from amino acids taken up by the cell via γglutamyl transpeptidase (34). Therefore, the most effective method for increasing GSH concentrations in hepatocytes is to incubate them with N-acetyl-L-cysteine (NALC), a precursor of the amino acid L-cysteine. This amino acid is one of the three which form GSH, which is actively taken up into the cells by transpeptidase and then converted to L-cysteine in the hepatocyte. Another method is to use a medium which already has L-cysteine as a basal supplement, e.g. Williams Medium E. NALC causes a rapid increase in GSH concentrations which may initially exceed the “normal” GSH concentrations (23) but this can only be considered as a favourable effect. Addition of GSH precursors to post-thaw hepatocyte medium may also help to restore GSH lost during the cryopreservation process itself, although once cultured human hepatocytes have been shown to replete GSH back to fresh values ((16), Table 4.1). 4. Increasing ATP content: If the hepatocyte isolation or subsequent wash steps do not include oxygenation of the buffers, hepatocytes will lose ATP. Incubation of freshly isolated hepatocytes under an atmosphere of 95% oxygen/5% carbon dioxide for 30 min (at 37◦ C) increases the ATP and ADP content of hepatocytes and may increase their likelihood of survival (35) (see Note 5). The increased energy status of hepatocytes may make them more able to undergo energyconsuming processes such as urea synthesis (35) and gluconeogenesis (6).
4. Selection of Human Donors and Hepatocyte Quality
To date, there are no reports linking a specific donor demographic with plateability of cryopreserved hepatocytes. Donor age or gender appears to not influence the probability of obtaining plateable
1.2
88 ± 4
Freezing density (million/ml)
Viability
82 ± 24
109 ± 6
GSH content after 24 h
28 ± 7
44 ± 13
89 ± 10
16
1
81 ± 25
23 ± 4 (52%)
38 ± 13 (43%)
37 ± 16
82 ± 8 (88%)
CP
62 ± 14
38 ± 9
58 ± 7
90 ± 3
4
16
1
1
Fresh
Pig
ND
18 ± 0 (47%)
<10% (<17%)
16 ± 3
42 ± 13 (47%)
CP
16 ± 7
12 ± 4
87 ± 4
94 ± 4
12
10
3
0.3
Fresh
Chicken
ND
6±0 (50%)
6±6 (7%)
38 ± 34
52 ± 26 (55%)
CP
CP
ND
5±4
8±4
98 ± 1
8
16
0±0
7±3 (88%)
41 ± 21
95 ± 6 (97)
Fresh cells do not attach at RT
0.3
Fresh
Carp
The freezing medium and step-wise freezing regimen were the same for each species (12), with some exceptions in DMSO concentration and freezing densities (as shown in the table). The attachment efficiencies of hepatocytes after 24 h in culture were determined according to the LDH content of hepatocytes in culture compared to the LDH content of the cell suspension initially seeded onto culture plates. Optimal seeding densities for cultures were according to maximal confluency, assessed visually. Relative hepatocyte volumes were determined according to Swales and Caldwell (22) using light microscopy. Part of the data was generated during the Ph.D. research of Dr. Julie Spencer (58) and other data are published (12, 13). The values in parentheses indicate percent of the corresponding fresh cell ND Not determined
40 ± 25 (40%)
100 ± 13
GSH content at (nmoles/million cells)
43 ± 9 74 ± 11 (100%)
74 ± 4
Attachment efficiency (24 h)
Recovery of viable cells
93 ± 6
16
DMSO concentration (%)
85 ± 7 (97%)
4
0.3
Plating density in 35 mm plate
1
3
Fresh
Hepatocyte size (relative to rat hepatocytes)
CP
Fresh
Rat
Parameter
Mouse
Table 4.1 A comparison of optimal cryopreservation conditions and subsequent recovery of hepatocytes from different species
Cryopreservation Methods 89
90
Hewitt
cryopreserved hepatocytes, since (induction and biliary excretion) data produced from cultures of cryopreserved human hepatocytes have been produced from hepatocytes from male and female donors aged between 6 days and 97 years (4, 5, 36–38). Clearly, attachment of cryopreserved hepatocytes is more likely if the fresh cells are also of good quality. If the freshly isolated hepatocytes are of low viability and do not attach, the chances of the resulting cryopreserved hepatocytes attaching in culture are low. Attempting to improve the quality of poor cell preparations by adding supplements or pre-incubating cells will not increase the post-thaw recovery. For example, Terry et al. (28) investigated the effects of pre-incubating fresh human hepatocytes with different supplements and found the post-thaw viabilities with and without supplements to be as low as 38%. This is not surprising considering the viability of fresh cells was only 67%; furthermore, only 55% of these attached in culture (not a confluent monolayer). In consideration of the requirement of only the healthiest hepatocytes, the isolation procedure itself should be optimised. Particular attention should be paid to factors such as the transport medium used to transfer the liver to the laboratory, the time between organ procurement and the start of collagenase digestion, the condition of the liver (fatty livers require longer collagenase digestion times) and the isolation time itself (see Note 6).
5. Cryoprotectants 5.1. Cryoprotectant Properties
Glycerin was one of the first cryoprotectants used but has the disadvantage of varying permeability through cell membranes of different species. DMSO was found to have many of the properties of glycerin but permeates the membranes of cells much quicker than glycerin and is still used today to cryopreserve all types of cells. Its mechanism of action is reported to be due to a number of properties such as (a) binding to water (39) which reduces the size and number of ice crystals formed during freezing (40). The hydrogen bonds between DMSO and water are favoured at low concentrations and low temperatures (41); (b) interacting with and stabilising the plasma membrane; (c) interacting with plasma proteins, conferring protection at lower temperatures (42); and (d) easily permeating membranes (43). The properties of DMSO change according to temperature such that they cause favourable effects at low temperatures and unfavourable effects at higher temperatures. There are two main factors responsible
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for this: first, interactions in the lipid bilayers and second, effects on proteins. At lower temperatures, DMSO is more concentrated in the aqueous region of the membrane than in the lipid bilayer and, therefore, dehydrates the lipid bilayer and replaces water with DMSO – a favourable effect. However, at higher temperatures, it is predominantly concentrated in the bilayer where DMSO adopts a more hydrophobic character and causes destabilisation of phospholipid membranes (43). DMSO can act as an excluded solvent (whereby the protein is hydrated and protected from the co-solvent) or a binding solvent (whereby the denatured protein is bound by the co-solvent and this binding increases with increasing concentrations of DMSO). At room temperature and lower, DMSO acts as an excluded solvent by binding to water but at higher temperatures, it is more hydrophobic in nature and therefore binds to proteins, causing them to denature. 5.2. DMSO
The most common concentration of DMSO used to cryopreserve hepatocytes from all species is 10%. Early studies showed that human hepatocytes frozen using lower concentrations of DMSO resulted in lower initial post-thaw viabilities and attachment efficiencies than cells frozen using 10–20% DMSO (7). The recovery of hepatocytes frozen in a low concentration of DMSO (5%) was not improved by the addition of co-cryoprotectants such as dextran or polyvinylpyrrolidone (PVP)(7). The choice of concentration for cryopreserving hepatocytes from any species should be that which results in maximal post-thaw recovery at a non-cytotoxic concentration. DMSO has been shown to cause toxicity if incubated with hepatocytes at high concentrations (10–20%) for longer than 30 min prior to cryopreservation, especially if maintained at 37◦ C (8, 11) (see Note 7). The addition of DMSO should be slow (over at least 10 min) to allow for its equilibration between intracellular matrix and the medium (18). If DMSO is added too quickly, then the concentration is much higher in the medium than in the cells, causing an osmotic imbalance. Water will pass from the cells into the medium and cause the cells to shrink (similar to the changes which occur due to slow cooling) and lose viability (3). The addition of DMSO over longer period of up to 1 h does not improve the post-thaw viability or attachment efficiency of the cells compared to DMSO added over 10 min (7). The addition of DMSO is usually carried out whilst the cells are placed on ice, mainly because the cells have been washed at 4◦ C (and have not been pre-incubated at 37◦ C), a time-consuming process if there are billions of cells. Keeping cells at 4◦ C reduces the toxicity of DMSO (29) and maintains drug-metabolising enzyme activities (44). Cooling of hepatocytes leads to activation of proteolytic enzymes via alterations in the
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cellular iron homeostasis and apoptosis (45), so repetition of the warm/cool cycles should be avoided at all times. 5.3. Other Co-cryoprotectants
Other cryoprotectants have been included in freezing medium, such as PVP and polyethylene glycol (PEG), but these are used in combination with DMSO, rather than as single supplements (see Note 8). The addition of proteins such as bovine serum albumin or serum may provide additional cell protection but they are not cryoprotectants per se. Positive attributes of serum include quenching of proteolytic enzymes released from dead cells, cytoprotection from free oxygen radicals (46) and slowing down cell sedimentation during freezing (due to its viscosity). The concentration of serum used by researchers varies widely, from 10% to 90% (15, 47), although higher concentrations do not confer increased cryoprotective properties (7).
5.4. Membrane Stabilisers
More recent findings have revealed the beneficial effects of trehalose. This disaccharide protects proteins and cellular membranes from inactivation or denaturation due to different stress conditions. The basis for the idea came from the fact that lower organisms such as yeasts, bacteria, fungi and insects all survive freezing and/or drying and all have concentrated levels of disaccharides, especially trehalose (48). The recovery of humanderived haematopoietic stem cells was enhanced when trehalose was used in combination with 10% DMSO in the cryoprotectant medium, compared to 10% DMSO alone (49). Membrane stabilisation may be a result of trehalose interacting with the plasma membrane to counteract the changes in membrane fluidity. Katenz et al. (48) showed that including trehalose at a concentration of 0.2 M in the freezing medium (containing 10% DMSO) increased post-thaw viabilities of human hepatocytes from 42 to 51% and attachment efficiencies from 15 to 51%. Although only 50% of the cells attached, this is still an important finding since the increases in attachment were marked. One reason for suboptimal recovery could be due to the thawing method used (gradual dilution of DMSO using ice-cold buffer, rather than the rapid thaw method described in Section 8). An additional mechanism of cryoprotection may be due to scavenging of free radicals which may be released during oxidative stress (50). Like trehalose, taurine (an amino acid) has membrane stabilising and cryoprotectant properties and has been shown to improve recovery of cells when added to conventional freezing medium (49). Three other antioxidants have also been tested, namely, ascorbic acid, α-tocopherol acetate and catalase. Each showed beneficial effects but catalase exhibited the best cryoprotective effects (49, 51).
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Table 4.2 Different basal media used in freezing media Medium
Reference
Waymouth 752/1
(7)
Krebs–Henseleit
(3, 30, 47)
Williams Medium E
(3, 48)
Leibovitz
(11, 59, 60, 61)
Krebs–Ringer bicarbonate +MOPS+HEPES
(35)
Dulbecco’s modified Eagle’s medium
(16, 26, 53)
Minimal essential medium
(62)
Modified earle’s Medium
(63)
Ham’s F12
(64)
FCS
(15, 65)
6. Basal Freezing Medium The basal medium used for freezing cells varies between laboratories (Table 4.2) and although there are some reports of differences between media (6, 8), there is no consensus as to which is optimal for cryopreservation. Basal media with strong buffering capacities (such as phosphate-based media like Leibovitz) may offer an advantage in maintaining pH. A number of researchers use culture media, which contain essential amino acids and other cell nutrients, although even simple bicarbonate buffers have also been used, simply because of their simple and defined constituents (47).
7. Freezing Cell Density The density at which hepatocytes are frozen may affect their recovery and “vitality” (see Note 9) but this may be species dependent. The most common cell density used for human and rat hepatocytes is 10 million cells/ml and 1 ml per cryovial. This may not be optimal for hepatocytes from other species which may have different cell volumes. Mouse hepatocytes are much larger than rat or human hepatocytes (approximately threefold (22)) and this difference markedly affects the optimal density at which they can be frozen. Figure 4.2 shows the effect of different freezing densities of mouse hepatocytes on the overall recovery
Hewitt Recovery (Initial viability x viable recovery x attchment efficiency)
94
250 000 200 000 150 000 100 000 50 000 0 0,3
0,6
1,2 1,5 2 3 Freezing density (million cells/ml)
4
5
Fig. 4.2. The effect of freezing density on the recovery of mouse hepatocytes. The recovery is expressed as the product of the initial post-thaw recovery, the number of viable cells recovered and the attachment efficiency of hepatocytes after 24 h of culture (mean of three preparations).
of the cells. The method of cryopreservation was that described by Swales et al. (12). It is generally agreed that the success of cryopreservation should not be assessed by trypan blue exclusion alone since this is a poor indicator of subsequent attachment in culture (8). Therefore, recovery was expressed as the product of the initial viability, percent of viable cells recovered and attachment in culture after 24 h. The optimal freezing density of mouse hepatocytes was between 1.2 and 1.5 million cells/ml. Halving or doubling the cell density above this range resulted in marked decreases in recovery, which was mainly a result of lower attachment efficiencies (data not shown). The optimal viability, viable cell recovery and attachment of cryopreserved hepatocytes using these conditions were 85 ± 7%, 43 ± 9% and 74 ± 11%, respectively. The viability and attachment efficiency of fresh mouse hepatocytes were 88 ± 4% and 74 ± 4%, respectively (Table 4.1). Rat hepatocytes were optimally frozen at 4 million cells/ml, a density which resulted in poor viability (60%) and attachment (9%) of mouse hepatocytes.
8. Thawing and Handling of Cryopreserved Hepatocytes
It seems that most researchers are focussed on the success of cryopreservation being connected purely to the freezing process and they give little regard to the method of thawing and handling of cells. The researcher that keeps a frozen vial of hepatocytes in their pocket whilst making final preparations to thaw the cells is very likely to be wondering later on why the cells did not function (see Note 10). This is a common occurrence and many blame commercial suppliers for poor quality cells when the problem is closer to home! The method of thawing cells comes back to the
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95
simple theory of cryopreservation and the effect of changing temperature on intracellular processes. If cells are warmed slowly (for instance if the vials are removed from liquid nitrogen and placed on water ice), intracellular ice crystals will coalesce and form larger crystals, which subsequently disrupt cell membranes. Even cells placed on dry ice are warming – from −196◦ C to −80◦ C – and this may also cause membrane damage due to ice crystals growing (see Note 11). Rapid thawing in a 37◦ C water bath causes the intracellular ice crystals to instantly thaw, preventing any damage due to growing ice crystals. The dilution of DMSO after thawing is also a stage at which the overall recovery can be affected since changes in osmolarity need to be counteracted. If cells containing 10% DMSO are poured into a large volume of ice-cold medium (e.g. 1 ml cells into 50 ml medium), the DMSO does not immediately equilibrate due to the low temperature. This creates a concentration gradient between DMSO in the cells (10%) and the medium (approximately 0.2%) and therefore differences in osmolarity; water will pass from the medium into the cells by osmosis. Excessive movement of water into the cells causes them to swell and burst. Therefore, methods developed to offset this effect have involved slow dilution of DMSO by adding small amounts of medium over a prolonged period (1 ml/10 s (18)) and by addition of molar concentrations of glucose to the ice-cold medium (8, 12). The main advance in this method was the use of warmed medium (37◦ C), which allows for the immediate equilibration of DMSO between the intra- and extracellular media. The “quick-thaw” method did not necessarily improve post-thaw viabilities but it did cause hepatocytes that were non-plateable using the “cold dilution” method to attach and form confluent monolayers (52). This method of DMSO dilution is therefore highly recommended. The golden rule in using hepatocytes from any species is to handle them with care. A piece of advice that may sound obvious but is very often ignored, especially if the researcher has previously used microsomes or cell lines (the latter can withstand intensive mechanical stress and, even if many cells die, they can proliferate once placed in culture to replace the lost cells) (see Note 12).
9. Percoll Purification After Freezing
It may be considered that purifying hepatocytes after thawing may result in a substantial loss of cells, however, if the correct Percoll concentration and centrifuge speeds are employed, maximal recovery of viable cells can be achieved whilst effectively removing dead cells (Fig. 4.3). If the concentration of Percoll is too
Hewitt 160 140 120 100 80 60 40 20 0 36
29
25
18
9
Percoll concentration (%)
36
29
25
18
Percoll concentration (%)
9
C 180 160 140 120 100 80 60 40 20 0
Pre-Percoll
Pre-Percoll
0
36
20
29
40
25
60
18
80
B
9
A 100
Pre-Percoll
96
Percoll concentration (%)
Fig. 4.3. The effect of Percoll concentration on the recovery of cryopreserved dog hepatocytes after thawing. The initial viability (A), percentage of viable cells remaining (B) and the number of dead cells remaining (C) before and after centrifugation of hepatocytes at 164×g for 20 min in different concentrations of Percoll are shown. Viabilities are expressed as the percentage of cells excluding trypan blue. Recovery of viable and dead cells is expressed as a percentage of the number of cells before Percoll centrifugation. Mean of 3 ± s.d.
high, then viable cells are lost as well as dead cells (Fig. 4.3B (53)). Conversely, if the concentration is too low, the viability may even decrease because the (viable and dead) cells are rapidly sedimented into a tight pellet which is hard to resuspend (Fig. 4.3A) (For tips on Percoll, see Note 13.). The optimisation of the Percoll purification of thawed cryopreserved beagle hepatocytes (29% Percoll and 168 g for 20 min) resulted in cells having much improved phase 2 drug-metabolising enzyme activities than non-purified cell preparations (54). It is recommended that the 29% Percoll (final after mixing Percoll with cells) is used when the centrifuge speed is 168×g and the cells are centrifuged for 20 min. As already mentioned, hepatocytes from different species may have different sizes and this will also affect the method for Percoll purification (see Note 14). The cells should be carefully resuspended in suitable medium (see Note 15).
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10. Species Differences Considering the well-known differences in metabolism between different species, it would not be surprising to learn that the optimal method for cryopreservation also varies between species. The focus of this chapter is on human hepatocytes but cryopreservation of other species is also of interest, especially of valuable animal species such as the monkey (55). It is therefore important to appreciate that conditions for one species may not extrapolate to others. The main difference to note between hepatocytes of different species is the relative cell sizes: mouse hepatocytes are very large and chicken and carp hepatocytes are very small in comparison to rat hepatocytes. Table 4.1 shows the relative sizes of hepatocytes from different species and their recovery after cryopreservation (see Note 16). Of the species, mouse hepatocytes were the most robust in that the initial viability and attachment efficiency were unaltered by cryopreservation. This may be due to these cells being more able to withstand shrinkage and preserve cellular volume due to dehydration (56). Small cells, such as chicken hepatocytes, may not be able to withstand shrinkage as well as mouse hepatocytes and therefore are compromised by cryopreservation. Carp hepatocytes are also very small but fish are known to have natural cryoprotective proteins, since they are cold water animals (e.g. antifreeze protein type I (57)). Therefore fish hepatocytes have lower sensitivity to cryoinjury despite their small size. Cryopreservation caused a loss of about 50% GSH in hepatocytes from all species tested (also found by others (32)) but once placed into culture, they are likely to resynthesise this tightly controlled cytoprotective compound – as shown with mouse and rat hepatocytes (Table 4.1). The number of viable cells recovered was similar between species, with the exception of pig hepatocytes, which appeared to be more sensitive to the effects of cryopreservation. Loven et al. (17) showed that the quality of pig hepatocytes was improved by pre-incubating them with glucose and insulin, which was not carried out in these studies.
11. Conclusions In conclusion, the art of cryopreservation has improved over the past two decades such that cryopreserved hepatocytes may now be used for assays which were previously only possible using fresh cells. There are commercial sources of cryopreserved hepatocytes but the methodologies are understandably kept propri-
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Hepatocyte Isolation
Optimise isolation procedure
Are the cells healthy? Are the cells rounded, with clear cytoplasm, and a smooth plasma membrane (See Figure 5)?
No
Cells are less than 70% viable by Typan blue Cells have multiple blebbing Cytoplasm is granular Swollen organelles Fresh cells have poor attachment in culture
Yes
Option; Pre-incubate the cells with supplemented medium at 37°C for 30min (See section 3.3)
Dilute cells to optimal density: Rat, monkey, human: 10million cells/ml Mouse: 1.5million cells/ml (See Table 1)
Cryoprotectant: 10% FCS 0.2m Trehalose 2.5% PVP Williams Medium E 10% DMSO – added drop-wise over 10min (See Section 5)
Freeze cells in programmable freezer (large numbers of cells) or isopropanol freezing boxes (small number of cells) (See Section 2)
Rapidly thaw cells and dilute in 37°C medium (See Section 8). Check for recovery using a number of parameters: Post-thaw viability using Trypan blue exclusion Morphology (See Figure 4.5) Attachment efficiency Metabolic capacity Other end points are: CYP induction response Carbohydrate metabolism
Fig. 4.4. Flow diagram showing a suggested step-wise protocol for the cryopreservation of hepatocytes. The solid arrows represent a continuation of actions throughout the cryopreservation procedure. Dashed arrows represent steps which may be altered if the recovery of hepatocytes is not optimal.
etary. However, with the publications that do exist, it is possible to formulate a protocol for optimal cryopreservation of hepatocytes from different species. Figure 4.4A shows a flow diagram as to how this method can be tried, tested and then optimised if necessary. Only healthy cells should be cryopreserved and if the fresh cells do not attach in culture, the cryopreserved cells from the same preparation are less likely to attach. Once good qual-
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Quality
Morphology Highest quality:
Cells appear spherical, with clear cytoplasm, and a smooth plasma membrane. Trypan blue exclusion greater than 90%.
Good quality: Cells are spherical, have clear cytoplasm but the membrane has a small number of small blisters or “blebs”. These are reversible and are likely to disappear once the cells are allowed to recover for 30min or are placed in culture. Trypan blue exclusion greater than 70%. Poorer quality: Not all cells are spherical, some are larger and elongated. Blebs are larger and possibly non-reversible. Swollen cells may not exclude Trypan blue. Trypan blue exclusion less than 70%.
Poor quality: Few cells are spherical. Blebs join and form distended plasma pockets. Many cells do not exclude Trypan blue. Trypan blue exclusion less than 50%.
Fig. 4.5. Schematic diagrams to demonstrate differences in hepatocyte quality.
ity fresh hepatocytes are obtained (Fig. 4.5), there is an option to pre-incubate them to increase their energy status (e.g. supplementing with glucose/insulin). The cells should be frozen at the correct density, although this seems less crucial for human hepatocytes than for other species such as the mouse. The cryoprotectant is of high importance and this may need modification in order to obtain optimal recoveries. The freezing method should ideally involve the use of a programmable freezer in order to achieve a controlled and accurate rate of freezing, especially if large numbers of cells are to be frozen. Above all, the success of cryopreservation should be assessed using hepatocytes that have been correctly thawed and handled. If not, then the modifications to the freezing protocol cannot be interpreted correctly. Finally, the method of cryopreservation of hepatocytes has progressed significantly over the years and is likely to continue to do so as we strive to obtain the conditions which result in cryopreserved cells of comparable morphology and functions to fresh cells. The search goes on!
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12. Notes 1. This should be seconds rather than minutes to avoid warming of the cells (see Section 8 notes on thawing for the basis of this action). If multiple freezing runs are to be carried out, it is important to allow the programmable freezer to warm up to room temperature after each freezing run. 2. An electric freezer has the advantage of being low maintenance but make sure it is connected to emergency electricity in case of power failures. 3. One disadvantage of liquid nitrogen is that it sometimes leaks into the vials and this will create pressure in the vial when it is removed from the storage tank and warmed. The obvious consequence of this is that the tube explodes – N.B. wear eye protection! Many researchers store cryopreserved hepatocytes in vapour phase nitrogen which decreases the likelihood of exploding vials and maintains them at a temperature well below the critical threshold of −130◦ C. 4. The use of Percoll does not have to result in a significant loss of viable cells. In general, the larger the number of cells which are purified, the higher the concentration of Percoll that is needed. Although in theory, all centrifuges should spin at the same speed, this is not always true in reality. Therefore, the speed at which the cells are centrifuged may need to be adjusted according to the specific centrifuge. 5. The effect of incubating chicken and pig hepatocytes in an oxygen-rich atmosphere (95% oxygen and 5% CO2 ) in our hands was negligible but it is always worth checking to see if this treatment does make a difference. 6. We have used two methods of isolation of rat hepatocytes – the first involved a perfusion time of 40 min and a second less than 10 min. The GSH content of hepatocytes using the 40 min method was significantly lower than that of hepatocytes isolated using the 10 min method. Although hepatocytes isolated using both methods cultured well and exhibited metabolic capacities, only cells from the second method were used for cryopreservation. 7. This factor could be why cryopreservation of large quantities of cells (>300 vials) may result in poorer post-thaw viabilities – they are simply compromised because the time between addition of DMSO and the start of freezing is too long. The key is to allow the DMSO to equilibrate in the cell suspension but not to allow the DMSO to cause toxicity.
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8. One drawback of these compounds is that they may interfere with the LC-MS analysis of test compounds after the cells have been thawed and used in a metabolite profiling assay. Washing thawed cells a number of times may reduce this effect but because PEG interacts strongly with the plasma membrane, it is unlikely to be completely removed. 9. The word “vitality” is used here rather than viability because most relate viability to parameters such as the exclusion of trypan blue. However, the quality of hepatocytes cannot be based solely on the integrity of the plasma membrane, therefore, other functions should be considered. Examples of functions to test are MTT metabolism, protein synthesis, attachment efficiency, carbohydrate metabolism, DME activities, etc. 10. The most convenient transfer of vials to the water bath is when the storage tank is in the cell culture laboratory, however, this is not always possible and vials may well be kept in the basement of the building. Even if cells are stored in a different room, the method of transfer needs to be quick and safe (avoiding warming of the vials). The best way to transfer cells from the storage tank to the water bath is in a container of liquid nitrogen, with enough liquid nitrogen to ensure the vials are immersed for the entire transfer time. It is not sufficient to pour a small amount of liquid nitrogen over vials in a polystyrene box and hope that it is still there by the time they arrive at the water bath. Those who do not have good access to liquid nitrogen can opt for transferring vials in dry ice pellets. Do not use water ice and do not allow the vials to warm above −70◦ C at any time during transfer. 11. It is a mistake to assume that the cells are safe because the medium is still solid! 12. Common methods which are used for cell lines but should never be used for hepatocytes include the following: a. Strumming of the tube along the grating in a flow hood to resuspend pelleted hepatocytes. b. Vortexing of hepatocytes (e.g. for a Guava counter). c. “Cocktail shaking” (when the pellet is particularly firm). d. Mixing trypan blue sample with a pipette. 13. One drawback of Percoll is that it may form large crystals if it is repeatedly heated and cooled and these will prevent hepatocytes from attaching. If this occurs, wash the cells until no Percoll crystals are visible. Another key factor in using Percoll is that it is non-physiological (osmotically equivalent to water) and requires dilution in 10-fold concentrated buffer (such as HBSS) before use. If Percoll is diluted in water, this will result in the demise of the hep-
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atocytes due to water entering the cells through osmosis, causing them to swell and burst. 14. For mouse hepatocytes, a final concentration of 29% Percoll is suggested but considering the size of these cells, the centrifuge speed should be reduced to 60×g (for 20 min). 15. After centrifugation, pour off the supernatant and loosen the cell pellet before adding any media – if you add media first and then try to resuspend the cells, they will form clumps. Loosen the pellet by gently shaking the bottom of the tube – the gentler, the better. 16. These hepatocytes were frozen using an early method of cryopreservation and thawing (12), which had to be adjusted according to the size of cells (and the small number of cells isolated in the case of carp hepatocytes) and the sensitivity to DMSO toxicity (in the case of chicken hepatocytes). References 1. Nutt, L.H., Attenburrow, V.D., and Fuller, B.J. (1980) Investigations into repair of freeze/thaw damage in isolated rat hepatocytes. Cryo-Letters 1, 513–518. 2. Innes, G.K., Fuller, B.J., and Hobbs, K.E. (1988) Functional testing of hepatocytes following their recovery from cryopreservation. Cryobiology 25, 23–30. 3. Diener, B., Utesch, D., Beer, N., Dürk, H., and Oesch, F. (1993) A method for the cryopreservation of liver parenchymal cells for studies of xenobiotics. Cryobiology 30, 116–127. 4. Roymans, D., Annaert, P., Van Houdt, J., Weygers, A., Noukens, J., Sensenhauser, C., Silva, J., Van Looveren, C., Hendrickx, J., Mannens, G., and Meuldermans, W. (2005) Expression and induction potential of cytochromes P450 in human cryopreserved hepatocytes. Drug Metab. Dispos. 33, 1004–1016. 5. Bi, Y.A., Kazolias, D., and Duignan, D.B. (2006) Use of cryopreserved human hepatocytes in sandwich culture to measure hepatobiliary transport. Drug Metab. Dispos. 34, 1658–1665. 6. Gómez-Lechón, M.J., Lopez, P., and Castell, J.V. (1984) Biochemical functionality and recovery of hepatocytes after deep freezing storage. In Vitro 20, 826–832. 7. Loretz, L.J., Li, A.P., Flye, M.W., and Wilson, A.G. (1989) Optimization of cryopreservation procedures for rat and human hepatocytes. Xenobiotica 19, 489–498.
8. Chesné, C. and Guillouzo, A. (1988) Cryopreservation of isolated rat hepatocytes: a critical evaluation of freezing and thawing conditions. Cryobiology 25, 323–330. 9. Meryman, H.T. (1961) Freezing of living cells: biophysical considerations. Natl. Cancer Inst. Monogr. 7, 7–15. 10. Diller, K.R. (1985) The influence of controlled ice nucleation on regulating the thermal history during freezing. Cryobiology 22, 268–281. 11. Chesné, C., Guyomard, C., Fautrel, A., Poullain, M.G., Frémond, B., De Jong, H., and Guillouzo, A. (1993) Viability and function in primary culture of adult hepatocytes from various animal species and human beings after cryopreservation. Hepatology 18, 406–414. 12. Swales, N.J., Luong, C., and Caldwell, J. (1996) Cryopreservation of rat and mouse hepatocytes. I. Comparative viability studies. Drug Metab. Dispos. 24, 1218–1223. 13. Swales, N.J., Johnson, T., and Caldwell, J. (1996) Cryopreservation of rat and mouse hepatocytes. II. Assessment of metabolic capacity using testosterone metabolism. Drug Metab. Dispos. 24, 1224–1230. 14. Price, J.A., Caldwell, J., and Hewitt, N.J. (2006) The effect of EGF and the comitogen, norepinephrine, on the proliferative responses of fresh and cryopreserved
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Hewitt of human and rat hepatocytes. Drug Metab. Pharmacokinet. 21, 297–307. Nishimura, M., Koeda, A., Suganuma, Y., Suzuki, E., Shimizu, T., Nakayama, M., Satoh, T., Narimatsu, S., and Naito, S. (2007) Comparison of inducibility of CYP1A and CYP3A mRNAs by prototypical inducers in primary cultures of human, cynomolgus monkey, and rat hepatocytes. Drug Metab. Pharmacokinet. 22, 178–186. Nishimura, M., Koeda, A., Shimizu, T., Nakayama, M., Satoh, T., Narimatsu, S., and Naito, S. (2008) Comparison of inducibility of sulfotransferase and UDPglucuronosyltransferase mRNAs by prototypical microsomal enzyme inducers in primary cultures of human and cynomolgus monkey hepatocytes. Drug Metab. Pharmacokinet. 23, 45–53. Martin, D. and Hauthal, H.G. (1971) Dimethyl-Sulphoxide Van Nostrand Reinhold, New York. Anchordoguy, T.J., Cecchini, C.A., Crowe, J.H., and Crowe, L.M. (1991) Insights into the cryoprotective mechanism of dimethyl sulfoxide for phospholipid bilayers. Cryobiology 28, 467–473. Sum, A.K. and de Pablo, J.J. (2003) Molecular simulation study on the influence of dimethylsulfoxide on the structure of phospholipid bilayers. Biophys. J. 85, 3636–3645. Arakawa, T., Carpenter, J.F., Kita, Y.A., and Crowe, J.H. (1990) The basis for toxicity of certain cryoprotectants: a hypothesis. Cryobiology 27, 401–415. Anchordoguy, T.J., Carpenter, J.F., Crowe, J.H., and Crowe, L.M. (1992) Temperaturedependent perturbation of phospholipid bilayers by dimethylsulfoxide. Biochim. Biophys. Acta 1104, 117–122. Poullain, M.G., Fautrel, A., Guyomard, C., Chesné, C., Grislain, L., and Guillouzo, A. (1992) Viability and primary culture of rat hepatocytes after hypothermic preservation: the superiority of the Leibovitz medium over the University of Wisconsin solution for cold storage. Hepatology 15, 97–106. Doeppner, T.R., Grune, T., de Groot, H., and Rauen, U. (2003) Cold-induced apoptosis of rat liver endothelial cells: involvement of the proteasome. Transplantation 75, 1946–1953. Gutteridge, J.M. and Quinlan, G.J. (1993) Antioxidant protection against organic and inorganic oxygen radicals by normal human plasma: the important primary role for ironbinding and iron-oxidising proteins. Biochim. Biophys. Acta 1156, 144–150.
47. Hengstler, J.G., Ringel, M., Biefang, K., Hammel, S., Milbert, U., Gerl, M., Klebach, M., Diener, B., Platt, K.L., Böttger, T., Steinberg, P., and Oesch, F. (2000) Cultures with cryopreserved hepatocytes: applicability for studies of enzyme induction. Chem. Biol. Interact. 125, 51–73. 48. Katenz, E., Vondran, F.W., Schwartlander, R., Pless, G., Gong, X., Cheng, X., Neuhaus, P., and Sauer, I.M. (2007) Cryopreservation of primary human hepatocytes: the benefit of trehalose as an additional cryoprotective agent. Liver Transpl. 13, 38–45. 49. Limaye, L.S. and Kale, V.P. (2001) Cryopreservation of human hematopoietic cells with membrane stabilizers and bioantioxidants as additives in the conventional freezing medium. J. Hematother. Stem Cell Res. 10, 709–718. 50. Leekumjorn, S., Wu, Y., Sum, A.K., and Chan, C. (2008) Experimental and computational studies investigating trehalose protection of HepG2 cells from palmitate-induced toxicity. Biophys. J. 94, 2869–2883. 51. Sasnoor, L.M., Kale, V.P., and Limaye, L.S. (2003) Supplementation of conventional freezing medium with a combination of catalase and trehalose results in better protection of surface molecules and functionality of hematopoietic cells. J. Hematother. Stem Cell Res. 12, 553–564. 52. Hewitt, N.J., Lechón, M.J., Houston, J.B., Hallifax, D., Brown, H.S., Maurel, P., Kenna, J.G., Gustavsson, L., Lohmann, C., Skonberg, C., Guillouzo, A., Tuschl, G., Li, A.P., LeCluyse, E., Groothuis, G.M., and Hengstler, J.G. (2007) Primary hepatocytes: current understanding of the regulation of metabolic enzymes and transporter proteins, and pharmaceutical practice for the use of hepatocytes in metabolism, enzyme induction, transporter, clearance, and hepatotoxicity studies. Drug Metab. Rev. 39, 159–234. 53. Powis, G., Santone, K.S., Melder, D.C., Thomas, L., Moore, D.J., and Wilke, T.J. (1987) Cryopreservation of rat and dog hepatocytes for studies of xenobiotic metabolism and activation. Drug Metab. Dispos. 15, 826–832. 54. Hewitt, N.J. and Utesch, D. (2004) Cryopreserved rat, dog and monkey hepatocytes: measurement of drug metabolizing enzymes in suspensions and cultures. Hum. Exp. Toxicol. 23, 307–316. 55. Hewitt, N.J., Fischer, T., Zuehlke, U., Oesch, F., and Utesch, D. (2000) Metabolic activity of fresh and cryopreserved cynomolgus monkey (Macaca fascicularis) hepatocytes. Xenobiotica 30, 665–681.
Cryopreservation Methods 56. Dzuba, B.B. and Kopeika, E.F. (2002) Relationship between the changes in cellular volume of fish spermatozoa and their cryoresistance. Cryo Letters 23, 353–360. 57. Robles, V., Barbosa, V., Herráez, M., Martínez-Páramo, S., and Cancela, M. (2007) The antifreeze protein type I (AFP I) increases seabream (Sparus aurata) embryos tolerance to low temperatures. Theriogenology 68, 284–289. 58. Spencer, J.A. (1999) Cryopreservation of hepatocytes from rodents and foodproducing animals and their use for in vitro toxicology. PhD Thesis. University of London. 59. Skett, P., Roberts, P., and Khan, S. (1999) Maintenance of steroid metabolism and hormone responsiveness in cryopreserved dog, monkey and human hepatocytes. Chem. Biol. Interact. 121, 65–76. 60. Fautrel, A., Joly, B., Guyomard, C., and Guillouzo, A. (1997) Long-term maintenance of drug-metabolizing enzyme activities in rat hepatocytes after cryopreservation. Toxicol. Appl. Pharmacol. 147, 110–114.
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61. Lawrence, J.N. and Benford, D.J. (1991) Development of an optimal method for the cryopreservation of hepatocytes and their subsequent monolayer culture. Toxicol. In Vitro 5, 39–50. 62. Jackson, B.A., Davies, J.E., and Chipman, J.K. (1985) Cytochrome P-450 activity in hepatocytes following cryopreservation and monolayer culture. Biochem. Pharmacol. 34, 3389–3391. 63. Watts, P. and Grant, M.H. (1996) Cryopreservation of rat hepatocyte monolayer cultures. Hum. Exp. Toxicol. 15, 30–37. 64. De Sousa, G., Dou, M., Barbe, D., Lacarelle, B., Placidi, M., and Rahmani, R. (1991) Freshly isolated or cryopreserved human hepatocytes in primary culture: influence of drug metabolism on hepatotoxicity. Toxicol. In Vitro 5, 483–486. 65. Madan, A., DeHaan, R., Mudra, D., Carroll, K., LeCluyse, E., and Parkinson, A. (1999) Effect of cryopreservation on cytochrome P-450 enzyme induction in cultured rat hepatocytes. Drug Metab. Dispos. 27, 327–335.
Chapter 5 Cryopreservation of Human Hepatocytes for Clinical Use Ragai R. Mitry, Sharon C. Lehec, and Robin D. Hughes Abstract Cryopreservation of hepatocytes is important for use both in research and for clinical application in hepatocyte transplantation. Cryopreservation causes damage to hepatocytes with the result that cell viability and function is reduced on thawing compared to fresh cells. There are many different protocols reported for freezing human hepatocytes mainly using DMSO as cryoprotectant. In this chapter the current detailed protocols used for cryopreservation and thawing of human hepatocytes for cell transplantation at the Cell Isolation Unit at King’s College Hospital, London, are described. All procedures must be performed in a clean GMP environment using materials and reagents which are of pharmaceutical grade. The cryopreservation media is UW solution with added 300 mM glucose containing 10% DMSO and the thawing solution is EMEM containing 2% HSA. Freezing is performed in a controlled-rate freezer using a stepwise cooling programme. Key words: Cryopreservation, human hepatocyte, donor liver, cell transplantation, controlled-rate freezer.
1. Introduction Successful cryopreservation of hepatocytes is essential for their use in hepatocyte transplantation. Cryopreservation allows hepatocytes to be available for emergency treatment of acute liver failure and also for planned treatment of liver-based metabolic disorders. However, cryopreservation affects the viability and function, especially the attachment efficiency, of hepatocytes on thawing (see also Chapter 4). A large number of human hepatocyte cryopreservation protocols have been reported (see review (1)). One of the main limitations to thawed cell function is the quality of the fresh P. Maurel (ed.), Hepatocytes, Methods in Molecular Biology 640, DOI 10.1007/978-1-60761-688-7_5, © Springer Science+Business Media, LLC 2010
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hepatocytes before cryopreservation. This is related to the nature of the liver tissue from which the hepatocytes are isolated (2), including factors such as age or condition of the donor, liver steatosis and length of cold and warm ischaemia times involved in procuring the liver. There are a number of steps in the cryopreservation process that can influence the function of the thawed hepatocytes, such as the cryoprotectant used, method and media used for freezing and finally thawing of the cells. This chapter describes the optimised cryopreservation protocol for human hepatocytes used for clinical hepatocyte transplantation at King’s College Hospital. It must be emphasised that the protocol was developed so that hepatocyte cryopreservation could be carried out safely under GMP conditions using reagents and materials suitable for clinical use. There may be better experimental protocols available, but they are not currently acceptable for clinical application.
2. Materials 2.1. Human Hepatocytes
Human hepatocytes to be used for clinical cell transplantation are isolated from donor liver tissue unused/rejected for transplantation using a collagenase perfusion technique according to previously published protocols (3–5). Ethical approvals and signed consent forms must be obtained prior to processing of any tissues, and the appropriate rules and regulations for human tissue processing, cell handling and storage must be followed (see Note 1).
2.2. Chemicals and Solutions
The following is a list of the chemicals and solutions used in the cryopreservation of human hepatocytes procedure and must be of clinical grade as all work is carried out under strict GMP conditions. 1. ViaSpanTM known as University of Wisconsin solution or UW solution (Bristol-Myers Squibb AB, Sweden). This preservation solution is routinely used for cold storage of donor organs. 2. Dimethyl sulphoxide, DMSO (WAK-Chemie Medical GmbH, Steinbac, Germany). 3. 50% glucose (Hamlin Pharmaceuticals Ltd., UK). 4. Eagle’s Minimum Essential Medium containing 25 mM HEPES (EMEM), without phenol red and calcium (Lonza Wokingham Ltd., Berkshire, UK). 5. Human Serum Albumin (HSA; 20% human albumin) (Baxter AG, Berkshire, UK).
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6. Transplant Medium M199 with HEPES (Lonza Wokingham Ltd., Berkshire, UK). 7. Sterile distilled water to be used in the water bath. 2.3. Main Equipment and Other Materials
1. Baxter blood bags 250 ml (Baxter Health Care Corporation, Deerfield, IL, USA); referred to in the text as “cryo-bags”. R 2. Hematron III bag sealer (Baxter Health Care Corporation, Deerfield, IL, USA); referred to in text as “bag sealer”.
3. Controlled-Rate Freezer Planer (Model: Kryo10 CRF; Planer plc, Middlesex, UK). 4. Grant water bath SUB14 (VWR International Ltd., West Sussex, UK). R L/S Pump (Cole-Parmer 5. Peristaltic pump, e.g. Masterflex Instrument Company Ltd., UK). R silicon-rubber tubing size 16 6. Perfusion tubing: Masterflex (Cole-Parmer Instrument Company Ltd., UK). R 7. Premier Klercide 70/30 sterile denatured ethanol (Shield Medicare, Farnham, UK); referred to in text as “70% alcohol”.
3. Methods 3.1. Preparation of Cryopreservation and Thawing Solutions
1. Preparation of cryopreservation solution: add appropriate volumes of 50% glucose and DMSO to an appropriate volume of ViaSpanTM (UW) solution to give a final concentration of 5% glucose and 10% DMSO, mix well and maintain on cool pack (see Notes 2 and 3). Example: 20 ml of 50% glucose + 10 ml DMSO + 70 ml UW to give a total volume of 100 ml. 2. Preparation of thawing solution: add ice-cold 20% HSA solution to ice-cold EMEM at 1:10 dilution (example: add 100 ml of 20% HSA to 1 l EMEM and mix well). Prepare what is equivalent to 10 times the volume of cell suspension to be thawed.
3.2. Preparation of Human Hepatocyte Suspension in Cryopreservation Solution
Ensure that the CRF machine is ready for the freezing step by the time the cryo-bags are filled with the hepatocyte suspension (see Section 3.3, Step 1). 1. Resuspend hepatocytes in cryopreservation solution at a final density of 1.0–1.5×107 cells/ml. 2. Label cryo-bags, then using a 50 ml syringe introduce 50 ml of hepatocyte suspension into each 250 ml cryo-bag.
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3. Seal cryo-bag using the hermetic bag sealer and cut sealed tube about 2 mm above the mark. 4. Maintain filled cryo-bags on cool packs and immediately transfer to the controlled-rate freezer area for cryopreservation. 3.3. Freezing Hepatocytes Using CRF 3.3.1. Starting the CRF
1. Clean freezer chamber with 70% alcohol. 2. Insert the pump tube carefully into the liquid nitrogen container (check sufficient for run) and attach each securing spring one by one. 3. Press green ON button on freezer. 4. Close red valve on pump head. 5. Push flick switch ON on pump heater, so that the light comes on. The pressure gauge should stabilise between 5 and 7 lbf/in2 (takes about 10 min to set up machine). 6. When the flick switch light goes OFF, you can begin the run. 7. Run the desired saved profile. 8. The green button should flash and clicking noise will begin indicating that the CRF is allowing small amounts of liquid nitrogen through. 9. The CRF will beep when it is ready for samples (i.e. it is down to the “start” temperature). CRF can be maintained at start temperature until cells are ready for freezing (see Section 3.3.2, Step 2).
3.3.2. Starting the Cell Freezing
1. Use pre-chilled cryo-bag holders and frame which were kept at 4–8◦ C for 30–60 min prior to use. 2. Begin the freezing process within 5 min of adding the icecold cryopreservation solution. The stepwise freezing programme is shown in Table 5.1. The aim is to produce a rapid linear decrease in temperature of the sample avoiding cell damage from the latent heat of fusion released during water crystallisation. 3. Transfer one cryo-bag to each of the pre-chilled bag holders for freezing and lay the bag flat in order for the cell suspension to be evenly distributed. 4. Close bag holder(s) securely and place it/them into the frame inside the CRF. 5. Start the freezing programme immediately. 6. After the freezing run is complete (∼60 min), immediately transfer the cryo-bags in a “dry shipper” or on dry-ice, to the liquid nitrogen cell storage tank (see Note 4).
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Table 5.1 Stepwise controlled-rate freezer programme for cryopreservation of human hepatocytes based on Diener et al. (6) with modifications Start temperature (◦ C)
Rate (◦ C/min) Time
End temperature (◦ C)
8
−1.0
8 min
0
HOLD
8 min
0
0
−2.0
4 min
−8
−8
−35.0
−28
−2.5
33 s
0
−28
2 min
−33
−33
+2.5
2 min
−28
−28
−1.0
32 min
−60
−60
−10.0
4 min
−100
−100
−20.0
2 min
−140
7. Clean cryo-bag holder(s) and frame with 70% alcohol. The holder(s) and the frame could be maintained in cold room or fridge until needed. 8. The CRF must be rewarmed up to ambient temperature. Therefore, follow the CRF “shut down” steps according to the manufacturer’s manual/protocol. 9. Once the CRF has reached the ambient temperature, turn off and release the pressure from the liquid nitrogen container. Carefully remove the pump from the liquid nitrogen container when the pressure gauge is at 0 lbf/in2 , and store vertically. 10. Wipe the internal compartment of the CRF thoroughly with 70% alcohol. 3.4. Thawing Cryopreserved Hepatocytes
The following hepatocyte thawing procedure is based on that of Steinberg et al. (7) with modifications for larger scale use. 1. Carry out quick thawing of cryopreserved hepatocytes by immersing the cryo-bag(s) in a water bath containing sterile water and set to 37◦ C, with gentle shaking. Do not allow thawed cell suspension to get warm. 2. Spray cryo-bag(s) with 70% alcohol and place in the safety laminar flow cabinet or isolator. 3. Quickly transfer the content of the bag(s) into an appropriate sterile vessel that could accommodate one volume of thawed cell suspension and 10 volumes of ice-cold EMEM/HSA solution. Example: if volumes of thawed cell
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suspension = 50 ml and EMEM/HSA = 500 ml, then use a 1 l sterile bottle. 4. Using the perfusion pump and a sterile silicon-rubber tubing dispense the ice-cold EMEM/HSA at a slow rate (example: to dilute 50 ml thawed cell suspension, the rate should be 25 ml/min) with continuous but gentle agitation. 5. Pellet the cells at 50×g, 4–5◦ C for 5 min, and then aspirate the supernatant. 6. Resuspend the cell pellet in about 200 ml ice-cold EMEM/HSA and repeat Step 5 one more time. 7. Assess the hepatocyte pellet for cell number and percent viability using a standard haemocytometer/Trypan Blue exclusion technique (8) (see Note 5). 8. The hepatocyte pellet then could be used for the preparation of cell suspension for transplantation into the patient. However, a small sample (20 μl in a 0.5 ml sterile microfuge tube) of the final cell pellet must be sent for Gram stain immediately prior to transplantation (see Note 6).
4. Notes 1. Clinical grade hepatocytes must be prepared under strict sterile conditions using clinical grade materials and reagents. No animal-derived reagents can be used. The processing of the liver tissue and hepatocytes must be performed in an accredited Good Manufacturing Practice (GMP) unit which operates according to regulations set by a specialised governmental agency, e.g. in the United Kingdom, the Human Tissue Authority (HTA). 2. Glucose is added to give a concentration of 300 mM. Preincubation of hepatocytes with 300 mM glucose at 4◦ C for 2 h had beneficial effects on thawed human hepatocyte function after cryopreservation (9). This is currently not used in the clinical protocol, but could be scaled up. However, it would increase the overall processing time for hepatocyte isolation and cryopreservation. 3. Sterile ice is not available and therefore cool packs could be used instead, as they can be decontaminated with 70% alcohol spray prior to use. 4. In order to avoid any microbial contamination through the liquid nitrogen, stocks of cryopreserved cells must be stored in the vapour phase of the storage tank. Cells can be maintained frozen for at least 3 years without loss of
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function. It is also possible to use a −140◦ C ultralow temperature freezer to store cryopreserved hepatocytes. 5. Cryopreserved hepatocytes prepared according to this protocol were used for cell transplantation in three children: two with coagulation factor VII deficiency (10) and one with a severe urea cycle defect (11). A total of 16 hepatocyte preparations were infused, 8 of which were cryopreserved hepatocytes. The mean percent cell viability of the hepatocytes after thawing was 88.8% ± SD 5.8%. The high viability obtained is partly due to the centrifugation steps involved (see Section 3.4, Step 5) which tends to purify the viable cells. 6. All cell preparations used for cell transplantation must be free of microbiological contamination. When hepatocytes are isolated from donor liver, blood culture analysis is performed on samples of the fresh cells. The microbiology results will be reported a few days later and they need to be checked before deciding whether the cryopreserved hepatocytes will be available for clinical use. References 1. Terry, C., Dhawan, A., Mitry, R.R., and Hughes, R.D. (2006) Cryopreservation of isolated human hepatocytes for transplantation: state of the art. Cryobiology 53, 149–159. 2. Terry, C., Mitry, R.R., Lehec, S.C., Muiesan, P., Rela, M., Heaton, N.D., Hughes, R.D., and Dhawan, A. (2005) The effects of cryopreservation on human hepatocytes obtained from different sources of liver tissue. Cell Transplant. 14, 585–594. 3. Strom, S.C., Dorko, K., Thompson, M.T., Pisarov, L.A., and Nussler, A.K. (1982) Large scale isolation and culture of human hepatocytes, in Ilots de Langerhans et Hepatocytes (Franco, D., Boudjema, K., and Varet, B. eds.), Les Editions INSERM, Paris, pp. 195–205. 4. Mitry, R.R., Hughes, R.D., Aw, M.M., Terry, C., Mieli-Vergani, G., Girlanda, R., Muiesan, P., Rela, M., Heaton, N.D., and Dhawan, A. (2003) Human hepatocyte isolation and relationship of cell viability to early graft function. Cell Transplant. 12, 69–74. 5. Mitry, R.R. (2009) Isolation of human hepatocytes, in Hepatocyte Transplantation (Dhawan, A. and Hughes R.D., eds.), Methods Mol. Biol. 481, 3–17. 6. Diener, B., Utesch, D., Beer, N., Durk, H., and Oesch F. (1993) A method for the cryopreservation of liver parenchymal cells for studies of xenobiotics. Cryobiology 30, 116–127.
7. Steinberg, P., Fischer, T., Kiulies, S., Biefang, K., Platt, K. L., Oesch, F., Bottger, T., Bulitta, C., Kempf, P., and Hengstler, J. (1999) Drug metabolizing capacity of cryopreserved human, rat, and mouse liver parenchymal cells in suspension. Drug Metab. Dispos. 27, 1415–1422. 8. Freshney, R.I. (2000) Culture of Animal Cells, Wiley-Liss, New York, NY, pp. 309–328. 9. Terry, C., Dhawan, A., Mitry, R.R., Lehec, S.C., and Hughes, R.D. (2006) Preincubation of rat and human hepatocytes with cytoprotectants prior to cryopreservation can improve viability and function on thawing. Liver Transplant. 12, 165–177. 10. Dhawan, A., Mitry, R.R., Hughes, R.D., Lehec, C., Terry, C., Bansal, S., Arya, R., Wade, J.J., Verma, A., Heaton, N.D., Rela, M., and Mieli-Vergani, G. (2004) Hepatocyte transplantation for inherited factor VII deficiency. Transplantation 78, 1812–1814. 11. Puppi, J., Tan, N., Mitry, R.R., Hughes, R.D., Lehec, S., Mieli-Vergani, G., Karani, J., Champion, M.P., Heaton, N., Rela, M., and Dhawan, A. (2008) Hepatocyte transplantation followed by auxiliary liver transplantation – a novel treatment for ornithine transcarbamylase deficiency. Am. J. Transplant. 8, 452–457.
Chapter 6 Hepatocyte Differentiation Katy M. Olsavsky Goyak, Elizabeth M. Laurenzana, and Curtis J. Omiecinski Abstract Increasingly, research suggests that for certain systems, animal models are insufficient for human toxicology testing. The development of robust, in vitro models of human toxicity is required to decrease our dependence on potentially misleading in vivo animal studies. A critical development in human toxicology testing is the use of human primary hepatocytes to model processes that occur in the intact liver. However, in order to serve as an appropriate model, primary hepatocytes must be maintained in such a way that they persist in their differentiated state. While many hepatocyte culture methods exist, the two-dimensional collagen “sandwich” system combined with a serum-free medium, supplemented with physiological glucocorticoid concentrations, appears to robustly maintain hepatocyte character. Studies in rat and human hepatocytes have shown that when cultured under these conditions, hepatocytes maintain many markers of differentiation including morphology, expression of plasma proteins, hepatic nuclear factors, phase I and II metabolic enzymes. Functionally, these culture conditions also preserve hepatic stress response pathways, such as the SAPK and MAPK pathways, as well as prototypical xenobiotic induction responses. This chapter will briefly review culture methodologies but will primarily focus on hallmark hepatocyte structural, expression and functional markers that characterize the differentiation status of the hepatocyte. Key words: Primary hepatocytes, hepatocyte differentiation, cell culture, hepatocyte morphology, xenobiotic responsiveness, hepatic nuclear factors, cytochrome P-450, extracellular matrix, dexamethasone, phenobarbital.
1. Introduction The adult liver is the largest glandular organ in mammals and carries out critical life functions involving both endocrine and exocrine pathways. Hepatocytes comprise ∼85% of the liver P. Maurel (ed.), Hepatocytes, Methods in Molecular Biology 640, DOI 10.1007/978-1-60761-688-7_6, © Springer Science+Business Media, LLC 2010
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mass (1) and are the predominant contributors to liver physiology. Hepatocyte functions include glycogen storage, lipid and serum protein biosynthesis, biotransformation of a diverse array of dietary substances, and the detoxification of a large variety of xenobiotic compounds. Of the available in vitro hepatic models, primary hepatocytes offer substantial advantages, including conserved uptake and excretion functions, the integration of phase I and phase II metabolic pathways, and the presence of cofactors necessary for enzyme activity. Although in practice since the 1950s, early methods, involving perfusion of rodent livers under pressure, resulted in grossly damaged hepatocytes. Isolation methods were vastly improved by Berry and Friend (2) through the introduction of collagenase as a means to enzymatically disperse cells and by Seglen’s introduction of the two-step method (3). This two-step method, now considered the standard isolation method, consists of an initial perfusion with a calcium-free buffer to disrupt desmosomes that make up the tight junctions between cells followed by a second perfusion with a calcium-rich buffer containing collagenase to further digest cell junctions. Another breakthrough in hepatocyte isolation methods was the modification of the procedure to use only segments of the liver, rather than the entire organ, allowing cost-efficient scale-up of the procedure to use larger livers, such as human (4–6). Despite the improvement in methods, hepatocytes from these early isolation experiments dedifferentiated quickly in culture, within a few hours losing hallmark features of in vivo liver function, such as albumin secretion and biotransformation activity (7–9). This dedifferentiation phenomenon has sparked investigation both of the culture conditions that preserve the differentiated phenotype and of the mechanisms responsible for differentiation status. In general, an inverse relationship has been described between a well-differentiated, growth-arrested phenotype and a proliferative one, marked by a G0/G1 transition that is triggered by the isolation process itself as defined by upregulated protooncogenes such as c-fos, c-jun, and c-myc (10, 11). This proliferative state in vitro has been further characterized by activation of cell cycle-stimulating and stress-related proteins, such as AP-1 (11–13) and NFκB (12, 14), and by loss of liver-enriched nuclear factors such as C/EBPα and the hepatocyte nuclear factor (HNF) family members (11, 12, 15, 16). While the induction of a proliferative state is advantageous for investigations of liver regeneration mechanisms, studies of xenobiotic metabolism require hepatocytes that respond with the fidelity of the in vivo liver. Thus, considerable effort has been put forth to identify conditions in which hepatocytes remain well differentiated. Unfortunately, many investigators continue to use sub-optimal culture methodologies.
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2. Cell Culture 2.1. Three-Dimensional Bioreactors
Although hepatocyte culture variations are abundant, for and include the culturing of hepatocytes as spheroids (17, 18) and in various co-culture configurations (17, 19), two of the most prevalent culture methodologies, when implemented appropriately, preserve a well-differentiated hepatocyte phenotype, namely the use of three-dimensional bioreactors or two-dimensional sandwich culture configurations. The former methodology embeds hepatocytes within complex three-dimensional chambers, most
Fig. 6.1. Illustrations of two primary hepatocyte culturing methodologies that preserve a differentiated phenotype. (A) Hollow fiber membrane bioreactors generally contain the following components: a reservoir containing defined media, a pump, a carbon dioxide/oxygen exchanger, and a chamber containing a complex network of hollow fibers enabling both media perfusion and sites of hepatocyte attachment. (B) In the sandwich culture system, hepatocytes are typically embedded between a collagen substratum and a dilute Matrigel overlay. Other forms of sandwich culture include the direct attachment of cells to either tissue culture plastic or poly-lysine-coated surfaces, followed by Matrigel overlay.
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commonly hollow fiber membrane bioreactors (Fig. 6.1A). The hollow fibers, woven into a three-dimensional scaffold for hepatocyte attachment, act as capillaries through which defined culture medium is perfused, providing a continuous supply of oxygen and nutrients to the cells, efficient removal of waste products, and controlled fluid dynamics designed to mimic in vivo shear stress and interstitial flow (20–24). Under ideal bioreactor conditions, hepatocytes tend to exhibit a differentiated phenotype, over several weeks in culture, with cuboidal morphology, extensive cell–cell contacts (22, 25), and specialized structures such as bile canaliculi (26, 27). Additionally, certain functional hallmarks are preserved, as hepatocytes in bioreactors synthesize both albumin and urea (21, 22, 25–28), excrete galactose (26, 28), and demonstrate various drug biotransformation activities (22, 23, 25). Nonetheless, the continuous perfusion inherent to this model has some associated difficulties, as components derived from cells or present in the media can clog pores on the membranes, subsequently altering the flow and possibly resulting in gradients of nutrients or oxygen through the chamber (20, 26, 29). Additionally, even though the rate of perfusion is controlled, the flow of fluid may introduce excess mechanical stress that may disrupt normal hepatocyte dynamics (30–32). 2.2. Two-Dimensional Sandwich Culture
A relatively simple, but nonetheless, robust methodology is the sandwich culture system, where hepatocytes are embedded between a substratum of collagen and an overlay of either collagen or a commercially available extracellular matrix (ECM), such as Matrigel, a derivative of the Swarm-Engelbreth-Holm carcinoma (Fig. 6.1B). When adopted in the appropriate context, the sandwich culture method is capable of achieving prolonged hepatocyte viability (33, 34) and differentiated morphology, such that hepatocytes remain cuboidal in structure and form closely associated cellular networks (33, 35–37). Functional capacity is also improved, displaying appropriately polarized membrane domains (38–40), enhanced biotransformation activity (33, 41– 43), and long-term albumin secretion (34, 36, 40). This configuration mimics the in vivo microenvironment, where, as shown in Fig. 6.2, hepatocytes are anchored to two opposing surfaces, even though the precise signaling pathways that this configuration preserves have not been clearly defined. ECM components present in the space of Disse, in particular laminin and collagen, are thought to not only provide anchorage for hepatocytes in vivo, but also to promote differentiation. These matrix components participate in the preservation of normal cytoskeletal organization (35, 44) and regulate the expression of HNF family members (45–47) and albumin (48, 49), highlighting the importance of ECM in the maintenance of hepatocyte
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Fig. 6.2. Illustration of hepatocyte plate structure in the liver. The circulatory blood vessels and polarity features of the hepatocyte are indicated. Hepatocytes in vivo have polarized membranes with specialized function based on location within the liver lobule. The basolateral, or sinusoidal, domain is specialized for exchange with blood, the apical, or canalicular, domain is specialized for bile secretion, and the lateral domain is specialized for intercellular communication. The various domains are separated by tight junctions.
differentiation. Since extracellular signals are often communicated to the cytoskeleton via the integrin family of cell surface receptors, it has been suggested that integrin signaling is crucial for maintenance of differentiation (35, 50); α3β1 integrin, in particular, facilitates hepatocyte attachment to collagen (51, 52) and fibronectin (53) and overall preservation of a differentiated morphology (54). Recently, phosphatidylinositol signaling has been identified as a potential link between integrins and cytoskeletal rearrangement, as ECM/Matrigel attachment causes an increase in phosphatidylinositol 4,5-bisphosphate (PI(4,5)P2) phosphatase mRNA, with a subsequent decrease in PI(4,5)P2 levels and actin polymerization (46). Furthermore, integrin-linked kinase (ILK) has recently been shown to play a critical role in matrix-induced hepatocyte
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differentiation (55). These studies demonstrated that ILK is present in the cell-ECM adhesion sites of cultured hepatocytes. Furthermore, hepatocytes isolated from ILK knockout mice appeared less differentiated in culture than hepatocytes from wildtype mice. 2.3. Defined Media Conditions
In addition to culture configuration, defined media conditions are critical for the maintenance of differentiated hepatocyte phenotype, in particular the presence of physiological, nanomolar levels of glucocorticoids, for example, in the form of the synthetic hormone dexamethasone, when coupled with the absence of serum in the culture medium. Dexamethasone is a potent activator of the glucocorticoid receptor (GR), a member of the nuclear hormone receptor superfamily that, prior to ligand binding, is complexed in the cytosol with HSP90, p23, and one of several tetratricopeptide repeat proteins (56–59). Ligand binding causes a conformational change in GR, revealing nuclear localization signals that stimulate nuclear translocation of the receptor (60, 61). Once in the nucleus, GR binds to specific response elements, acting as an antiinflammatory and an immunosuppressant, largely through repression of the NFκB and AP-1 pathways (62–64). In primary hepatocyte culture, dexamethasone additions promote a cuboidal phenotypic architecture, facilitate the expression of liver-enriched transcription factors, such as C/EBPα, HFN4α, and RXRα (13, 36, 65, 66), and suppress the hepatocyte proliferative state otherwise stimulated by growth factors such as EGF (67). Although high doses of dexamethasone may stimulate proliferation (68), low concentrations are often included in culture media designed to induce hepatic lineage differentiation for embryonic stem cells derived from human (69, 70), monkey (71), and mouse (72). Importantly, inclusion of nanomolar concentrations in the hepatocyte culture media serves to inhibit the induction of stress signaling pathways, such as MAPK and SAPK/JNK (13). In these respects, for human hepatocyte culture, our laboratory has adopted a highly defined, serum-free, two-dimensional sandwich system that configures hepatocytes with collagen I as the substratum and a dilute overlay of ECM, combined with serum-free medium containing nanomolar levels of dexamethasone (13, 36, 73). This sandwich system is appropriate for rat and human hepatocytes, and our protocol for human hepatocytes is briefly outlined below. In our human studies, primary hepatocytes were obtained from the Liver Tissue Cell Distribution System (reference NIH Contract –#N01DK-7-0004/HHSN267200700004C). Hepatocytes are isolated according to a three-step collagenase perfusion protocol (74). Preparations enriched for hepatocytes are received plated in collagen-coated, tissue culture plastic flasks, or dishes. The culture
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media consists of William’s Media E supplemented with 1% penicillin/streptomycin, 10 mM HEPES, 20 μM glutamine, 25 nM dexamethasone, 10 nM insulin, 30 mM linoleic acid, 1 mg/ml BSA, 5 ng/ml selenious acid, and 5 μg/ml transferrin. Within 4–16 h, an ECM overlay is added. A 10 mg/ml stock solution of Matrigel (BD Biosciences, San Jose, CA) is added dropwise to the culture media and evenly distributed by gentle swirling such that the final concentration is 225 μg/ml. Matrigel is a liquid at 4◦ C temperatures and rapidly gels at room temperature or at 37◦ C; therefore the additions of Matrigel need to be made rapidly, and typically using pipette tips that are pre-chilled in the freezer. The media is subsequently changed every 48 h until cells are harvested for RNA extraction. The cells are maintained at 37◦ C under 5% CO2. Under these conditions, the hepatocytes are non-proliferative and are stable in culture for extended periods of culture, e.g., >2 weeks. See also Chapter 3 and 23 of the present volume.
3. Markers of a Differentiated Hepatocyte 3.1. Morphology
An often overlooked aspect of the differentiated hepatocyte is the status of the plasma membrane, namely that the membrane retains polarized domains, forms junctions between cells to facilitate cell–cell communication, and contains specialized structures like bile canaliculi. In vivo, hepatocytes are arranged in plate-like arrays, facing the sinusoids on one side and bile ductules on the other. The plasma membrane is functionally compartmentalized based on these interactions, such that the basolateral, or sinusoidal, membrane is specialized for exchange of metabolites with circulating blood (Fig. 6.2). Similarly, the apical, or canalicular, membrane is specialized for bile secretion, and the lateral membrane, joining adjacent hepatocytes, is specialized for intercellular communication (35, 75). Functional polarity in vitro is demonstrated by marker proteins specific for lateral domains, such as connexins 26 and 32; basolateral domains, like epidermal growth factor receptor; and apical domains, such as dipeptidyl peptidase IV (40, 76–79). Alternatively, hepatobiliary transport, shown by the appropriate accumulation and excretion of bile acids and other organic anions (38, 39, 80–82), and gap junctional intercellular communication between adjacent hepatocytes (78, 79) demonstrate the compartmentalization of these specialized functions. As dedifferentiation occurs, the cuboidal networks of cells often flatten and lose expression of specialized structures such as
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bile canaliculi, as well as distinct cell–cell contacts (35, 40, 45, 83, 84). Microscopically, in optimally cultured hepatocyte preparations, many of the morphological features of hepatocytes are visible. Figure 6.3 shows examples of primary human hepatocytes cultured in the absence and presence of Matrigel. The cells cultured in the presence of Matrigel (Fig. 6.3B, D and F) exhibited characteristic cuboidal, three-dimensional structure, and enhanced cell border definition. In contrast, cells cultured without Matrigel (Fig. 6.3A, C and E) exhibit a more flattened appearance, weakly defined borders, and evolve fibroblast-like
Fig. 6.3. Matrigel enhances cellular morphology of primary human hepatocyte cultures. Primary human hepatocytes from Donor A (A and B), Donor B (C and D), and Donor C (E and F) were cultured in the presence (B, D, F) or absence (A, C, E) of a Matrigel overlay. Photomicrographs were taken under ×20 magnification using phase-contrast imaging. Arrows indicate compromised morphology in the absence of a Matrigel overlay. Reproduced from Toxicological Sciences, 2007 (73) with permission from Oxford University Press.
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Fig. 6.4. Effect of dexamethasone concentration dependency on hepatocyte morphology and viability. Primary rat hepatocytes were cultured for 96 h under the stated dexamethasone (Dex) concentrations (nM) in the presence of a Matrigel overlay (×20 magnification). Arrows identify evidence of perturbed morphology: condensed cytoplasm and rounded-up cells, attributed to cytotoxicity. The lower right panel shows the relative level of LDH leakage associated with each Dex concentration. Reproduced from Experimental Cell Research, 2004 (13) with permission from Elsevier.
spinous processes, indicative of dedifferentiation. A further example of the morphological features is illustrated in a previous study of the effect of culture conditions on rat hepatocytes (13), as presented in Fig. 6.4. These rat hepatocyte studies serve to illustrate the importance of low concentrations of glucocorticoid additions. In Fig. 6.4, hepatocytes were cultured in the sandwich configuration as described above along with varying concentrations of dexamethasone. Omission of dexamethasone resulted in perturbation of the cuboidal networks, with cells exhibiting condensed cytoplasm, abnormal rounding of cell structure, and formation of fibroblast-like protrusions. Further, as a measure of hepatocyte toxicity associated with morphological disruption, lactate dehydrogenase (LDH) leakage from the cells was assessed. In addition to protecting morphological integrity, nanomolar additions of
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dexamethasone protected against cytotoxicity, attenuating LDH leakage (Fig. 6.4). 3.2. Immunofluorescence
Expression of cytokeratins 18 and 19 is a widely recognized feature of differentiated hepatocytes, therefore its detection in cells via immunofluorescence is a useful marker of the mature phenotype. For example, investigators assessing the progression of embryonic stem cells down the hepatic lineage often assess these markers (85–87). As indicated previously, expression and localization of connexin 32 is a hallmark feature of hepatocyte gap junctions. Our studies have shown that in the presence of Matrigel, hepatocytes exhibit enhanced gap-junctional formation, as assessed by immunofluorescence detection of connexin 32, when compared with hepatocytes cultured without Matrigel (88). ILK, a key factor in matrix-induced hepatocyte differentiation (55), is another hepatocyte marker that can be assessed using immunofluorescence. This marker is visible at the ECM adhesion sites of hepatocytes in culture.
3.3. Plasma Proteins
The most frequently assessed markers of hepatocyte differentiation include expression of plasma proteins such albumin, transferrin, transthyretin, and α-1-antitrypsin (45, 80, 84, 89–91), in that this organ is the dominant site of plasma protein synthesis (92, 93). On the other hand, hepatocyte dedifferentiated is reflected typically by the up regulation of alpha-fetoprotein (AFP) and glutathione-S-transferase P1 (GSTP1; GSTπ) (94, 95). AFP is normally silenced in adult livers and therefore an increase in its expression within primary hepatocyte cultures is indicative of a dedifferentiation process toward a fetal lineage (95). Similarly, GSTP1 is expressed selectively in fetal liver and silenced in the mature hepatocyte (94). Therefore, both of these markers are particularly useful indicators of cultured hepatocyte dedifferentiation status, largely repressed in differentiated cells but augmented in hepatocytes undergoing dedifferentiation processes. Quantitative RT-PCR (qRTPCR) analyses are convenient assays to conduct in this regard and assays for literally any human or mouse gene transcript are available commercially from sources such as Applied Biosystems (Carlsbad, CA). Figure 6.5 shows results of qRTPCR analyses for markers of differentiation and dedifferentiation on total RNA isolated from primary human hepatocytes maintained in defined culture media containing dexamethasone at physiological levels, in the absence and presence of ECM/Matrigel. When comparing expression profiles of selected markers between human liver, human hepatocytes cultured with Matrigel, and a commonly used human hepatoma cell line, hepatocytes cultured in the presence of a Matrigel overlay most closely resemble the expression profile of the human liver, while HepG2 cells, although expressing certain markers, differed from the expression levels of the liver by
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Fig. 6.5. Effects of Matrigel addition on differentiation status of primary human hepatocyte cultures. Total RNA was isolated a section of human liver # 154, from HepG2 cells, as well as three different donor samples of primary human hepatocytes that were cultured for 5 days in the presence of a Matrigel overlay. Relative mRNA transcript expression levels were assessed using TaqMan qRTPCR analyses for a panel of differentiation markers, albumin, transferrin and transthyretin, and alpha-1-antitrypin (SERPINA), and de-differentiation markers GSTP1 and alpha fetoprotein (AFP). The Ct method was used for quantification (124). The results are graphically depicted, using a log scale on the ordinate axis. Reproduced from Toxicological Sciences, 2007 (73) with permission from Oxford University Press.
at least 10-fold and as much as 200-fold (Fig. 6.5). In other studies (data not shown), further comparisons to additional human liver tissues, from six different donors, were also conducted, with similar conclusions derived as that for the representative HL#154 liver presented here. Therefore, the cumulative evidence indicated that a Matrigel overlay was a positive regulator of differentiation status of primary human hepatocytes, facilitating the up regulation of differentiation makers, down regulation of dedifferentiation markers. 3.4. Cytochromes P450 and Hepatic-Enriched Nuclear Factors
Another hallmark feature of the liver is its biotransformation activity; thus, cytochrome P450 (CYP) monooxygenase and phase II enzyme expression and activity (36, 41, 90, 91, 96) are commonly used markers of hepatocyte differentiation. In addition, a number of liver-enriched nuclear factors, including HNF family members, CAAT/enhancer binding protein α (C/EBPα), and nuclear hormone receptor superfamily members, are prominently expressed in the mature liver and are engaged in critical regulatory roles underlying the maintenance of biotransformation enzyme function as well as many other differentiated features of the hepatocyte. For example, the expression of C/EBPα has been noted to decline both as expression of protooncogenes increase and as normal morphology is altered (11–13,84), whereas the HNF4 family members play a role in liver-specific gene expression; targeted
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knockdown of this transcription factor results in decreased expression of the plasma proteins albumin and transthyretin (45, 46). Studies from our laboratory have also used whole genome expression profiling in human liver samples and in the commonly used HepG2 and Huh7 human hepatoma cell lines to determine mRNA expression levels coding for biotransformation enzymes and hepatic nuclear factors. When cultured in a two-dimensional Matrigel sandwich configuration, the transcription factors were tightly regulated in hepatocytes obtained from various human donors, as expression of the genes was maintained at levels less than 4-fold changed from liver (Fig. 6.6A). Among the two hepatoma cell lines studied, the expression profiles of the various transcription factors varied considerably compared to that of liver or primary hepatocytes, and there were notable differences in expression character even between the two cell lines. For example, mRNAs for NR1I2 (pregnane X receptor (PXR)) and NR1I3 (constitutive androstane receptor (CAR)) were undetectable in Huh7 cells and were >6- and 42-fold decreased in HepG2 cells, respectively (Fig. 6.6B). The expression levels for the retinoid X
Fig. 6.6. Gene-level expression analysis of selected liver-specific categories in human hepatocyte donors and hepatomaderived cell lines using microarray profiling. Distribution of fold change from the liver in 10 hepatocyte donors is shown for genes encoding select transcription factors (A) and drug-metabolizing enzymes (C). For comparison, the fold change for the same genes in HepG2 and Huh7 hepatoma cells are presented in panels B and D. Differential expression is defined as greater than 4-fold change from the human liver (dotted lines). ∗ indicates the measured probe set is detected as absent in at least one human hepatocyte donor (PPARA: absent in two donors; TCF1: absent two donors; CYP1A2: absent in one donor). ∗∗ indicates the probe set is detected as absent in Huh7 cells (NR1I2, NR1I3, CYP1A2, CYP2B6, CYP2C9, CYP2D6, CYP3A4). ∗∗∗ indicates the probe set is detected as absent in HepG2 (CYP1A2, CYP2B6, CYP2C9, CYP2D6, CYP2E1). Reproduced from Toxicology and Applied Pharmacology (88) 2007, with permission from Elsevier.
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receptor-α (RXRα) were reduced ∼5-fold in both of the respective cell lines, compared to liver. Generally, mRNAs for CYP450 family members were expressed in hepatocytes at levels comparable to those detected directly in liver, with the exception of CYP1A2 and CYP2E1, which were decreased (Fig. 6.6C). In contrast, in the hepatoma lines expression of CYP450 isoforms is dramatically decreased or non-existent (Fig. 6.6D). These studies demonstrated that in vitro hepatocytes, in a sandwich culture with defined medium, are reasonably representative of in vivo liver, while the HepG2 and Huh7 cells exhibited markedly deviant, dedifferentiated phenotype. When considering these comparative studies, one should also keep in mind that liver itself is comprised of ∼80% hepatocytes, with the remainder of the tissue consisting of other types of cells, such as endothelial, biliary, and stellate cells. In this regard, the measured comparisons refered to here between primary hepatocyte cultures and actual liver are likely even closer then otherwise indicated in these studies (88).
4. Stress Pathways and Hepatocyte Integrity
The importance of appropriate culture conditions on hepatocyte differentiation has been outlined above, but to further illustrate this point, previous studies from our laboratory demonstrating the interaction of culture conditions and stress pathways are presented. A compromised differentiation status is associated with the activation of stress-associated pathways in cultured hepatocytes, including the MAPK, SAPK/JNK, and c-Jun signaling pathways. For these studies, rat hepatocytes were cultured in a serum-free, highly defined medium in the absence and presence of Matrigel/ECM and with varying concentrations of dexamethasone. Cells cultured in the absence of dexamethasone exhibited a marked stimulation of p42/44 MAPK, SAPK/JNK, and c-Jun phosphorylation (Fig. 6.7). The presence of Matrigel served to attenuate the activation of these pathways, even at the 1 nM dexamethasone dose. The stress activation responses were blunted completely with 5 nM dexamethasone. In contrast, cells cultured in the absence of a Matrigel overlay exhibited stress pathway activation responses that could only be attenuated modestly, even at the highest concentrations of dexamethasone tested. Thus, there is an apparent synergy between the effects of Matrigel and dexamethasone in providing attenuation of the stress cascades. It is interesting to note that omission of dexamethasone or Matrigel only had minimal impact on the phosphorylation status of PKB, a critical and positive effector of cell survival and death (Fig. 6.7). This latter result suggests that the cell survival stimulus associated
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Fig. 6.7. Effect of ECM overlay and dexamethasone concentration on the activation of stress signaling pathways in primary rat hepatocytes. Primary rat hepatocytes were cultured for 96 h under the variable concentrations of dexamethasone (Dex), as indicated, and in the presence (+ECM) or absence (−ECM) of an ECM/Matrigel overlay. Total cell extracts were prepared and analyzed by Western blot analysis. Phospho-specific antibodies were used to discern the phosphorylation status of p42/44 MAPK (Thr202/Tyr204), SAPK/JNK (Thr183/Tyr185), c-Jun (Ser63), and Akt (Ser473). The levels of each targeted immunoreactive protein were assessed in parallel with phosphorylation-independent antibodies, as shown for αMAPK. Reproduced from Experimental Cell Research, 2004 (13), with permission from Elsevier.
with dexamethasone is independent of a PI3 kinase pathway. Consistent with the activation of the MAPK, SAPK/JNK, and c-Jun signaling pathways, limiting dexamethasone concentration also resulted in increased nuclear accumulation of the AP-1 complex ((13); data not shown). These results are consistent with a loss of control of the signaling machinery regulating cell cycle progression and mitogen-activated growth. Thus, it appears that dexamethasone and Matrigel prevent proliferative signals at the level of AP-1 activation and cell cycle progression, thus preserving the differentiated hepatocyte phenotype.
5. Functional Assessment of Hepatic Phenotype
An array of additional functional end points can offer insight into the degree of differentiation, due to the wealth of physiological functions in which the in vivo liver plays a role, including the synthesis of urea, clotting factors, and acute phase proteins (25, 26, 28, 91), synthesis of glucose and subsequent glycogen storage (26, 28, 80), excretion of bilirubin (39), and lipid and cholesterol transport (84). Use of the periodic acid Schiff’s staining technique (American Master Tech Scientific Inc., Lodi, CA) is a useful
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method for detection of intracellular glycogen (85). Hepatic glutamine metabolism in connection with urea synthesis is required for systemic ammonia detoxication and pH regulation. Due to the important role of the liver in maintaining ammonia and bicarbonate homeostasis under physiologic and pathologic conditions, ammonia metabolism is often used as a functional marker of hepatic phenotype (97, 98). 5.1. Xenobiotic/Drug Induction Responses
A primary function of the liver is to conduct the metabolism of endogenous, dietary, and xenobiotic substances. Typically, the xenobiotic biotransformation process is typified by both phase I monooxygenation reactions, followed by phase II synthetic processes. The phase I process trends toward detoxification, with the resulting metabolites being more water soluble and exhibiting increased likelihood to undergo further reactions via phase II conjugation pathways. However, a large number of procarcinogens and other environmental toxins are bioactivated by the xenobiotic metabolizing CYPs. Several classes of environmental and therapeutic substances are recognized for their capacity to markedly modulate the transcriptional status of mammalian biotransformation enzymes. There are several prototypical inducing agents, including the polyaromatic and polychlorinated hydrocarbons, ethanol and organic solvents, peroxisome proliferator compounds such as the phthalate esters, dexamethasone, and several sedative–hypnotic medications. These substances tend to regulate their corresponding biotransformation enzyme pathways via the interplay of an array of soluble and nuclear receptors (99). Therefore, based on the complex series of events leading to xenobiotic induction of hepatic gene function, the ability of cultured hepatocytes to respond to xenobiotic inducers is insightful and potentially a uniquely specific indicator of their differentiated state. Studies from our laboratory (13, 36, 73, 88) and others (83, 100–102) have shown that under proper maintenance conditions, hepatocytes will respond appropriately and robustly to a given xenobiotic-inducing agents. Several of the induction pathways are rather robust and are maintained in both established cell lines and even in hepatocytes that are maintained sub-optimally in culture. An exception is phenobarbital (PB). Although used in humans as a sedative and antiseizure agent without serious long-term adverse effects (103), PB promotes rodent tumorigenesis through mechanisms including inhibition of apoptosis (104), activation of β-catenin (105), selective promotion of cells with low TGFβ receptor expression (106), reduction in G1 checkpoint efficiency (107), and alteration of DNA methylation (108). Mechanistically, PB mediates these effects through activation of the constitutive androstane receptor (NR1I3, or CAR), a member of the nuclear hormone receptor superfamily of transcription factors (reviewed in
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(109–112)). In vivo, CAR is retained in the cytoplasm complexed with HSP90 and the tetratricopeptide repeat-containing protein cytoplasmic CAR retention protein (CCRP), until activation by xenobiotics such as PB induces nuclear translocation (113–116). Once in the nucleus, CAR forms a dimer with RXRα (117) and recruits coactivator proteins, such as steroid receptor coactivator 1 (SRC-1) (118), GR-interacting protein 1 (GRIP-1) (119), and peroxisomal proliferator-activated receptor-γ coactivator 1α (PGC1α) (120), to drive transcription of genes, notably CYP2B and CYP3A family members, containing PBresponsive enhancer modules (PBREMs) within their promoter regions (121, 122). The PB induction response is typically lost in hepatoma-derived cells or in primary hepatocytes cultured in sub-optimal conditions. An example of the PB induction response that is obtainable in primary cultures of human hepatocytes, and not apparent in most human hepatoma cell lines, is shown in Fig. 6.8. The, authors contend that assessment of the PB induction response in particular appears to serve as a uniquely sensitive and important marker of hepatocyte differentiation status (13).
Fig. 6.8. Effects of Matrigel addition on the phenobarbital induction activity primary human hepatocyte cultures. Primary human hepatocytes were cultured in the absence (control) or the presence of Matrigel (MG). Cultures of primary human hepatocytes and HepG2 hepatoma cells (indicated by arrows) were treated on day 4 with 0.5 mM phenobarbital (PB alone: PB; or PB in combination with MG, PB+MG) or DMSO (control, leftmost bars in each section of the graph) for 24 h prior to RNA isolation. Relative fold changes in transcript levels for the PB-inducible marker genes, CYP2B6 and CYP3A4, are indicated, normalized to DMSO control levels set (= 1). Reproduced from Toxicological Sciences, 2007 (73) with permission from Oxford University Press.
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Even though there are noted differences across species, the vast majority of validation studies have been carried out in hepatocytes of rodent origin due to limitations in the availability of human hepatocytes. Although further experiments with human hepatocytes may only confirm current culture methodologies, past experience has shown that there are inherent species-specific phenotypic differences in hepatocytes. For instance, early isolation studies reported significantly lower viability in rat and hamster hepatocytes vs. those from mouse and rabbit under the same conditions, as well as a steep decline in cytochrome P450 content in mouse and rat hepatocytes vs. nearly unchanged concentrations in those from rabbit (9). Time-course discrepancies have also been noted for membrane repolarization, in that co-localization of canalicular transport proteins with canalicular markers occurs faster in hepatocytes from rats compared to those from humans (76). Further, while a sandwich culture configuration was demonstrated as critical for the induction of biotransformation enzymes in rat hepatocytes (36, 83), some studies have concluded that a collagen or Matrigel overlay is not vital for enzyme induction in primary human hepatocytes, despite improved morphology and cytoarchitecture in sandwich culture (123). Considering these species-specific responses to in vitro conditions, thorough evaluation of any primary hepatocyte culture systems is warranted in order to secure confidence in its use as a model for liver biology or as predictive tool for in risk assessment.
7. Conclusion This chapter summarizes an otherwise large body of available information relating to hepatocyte function and provides the reader with an overview of appropriate experimental methodology that can be applied to assess the biological character of primary hepatocytes in culture. It is not intended to be a complete compilation of these issues; rather, this chapter strives to delineate and discuss several important considerations of hepatocyte biology that should be considered in the evaluation of a given primary culture system. Careful attention to criteria such as morphology, functional end points, and expression of appropriate differentiation/dedifferentiation markers are required in any in vitro hepatocyte model system in order to validate its use and robustness as accurate model of hepatocyte phenotype as it exists in vivo.
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Chapter 7 Reversible Manipulation of Apoptosis Sensitivity in Cultured Hepatocytes by Matrix-Mediated Manipulation of Signaling Activities Patricio Godoy, Markus Schug, Alexander Bauer, and Jan G. Hengstler Abstract Hepatocytes in culture are a valuable tool to investigate mechanisms involved in the response of the liver to cytokines. However, it is well established that hepatocytes cultured as monolayers on dried stiff collagen dedifferentiate, loosing specialized liver functions. In contrast, softer matrix systems like gelled collagen help to preserve these structural and functional features. We show that the de-differentiation process induced in conventional dry collagen is a reversible consequence of a specific signaling network constellation triggered by the extracellular matrix that results in apoptosis resistance. A dried stiff collagen activates Akt and ERK1/2 pathways that results in apoptosis resistance. In contrast to stiff collagen, a soft collagen gel does not activate these pathways keeping the hepatocytes in a state where they remain sensitive to TGF-β-induced apoptosis. Finally, we show that matrix-induced apoptosis resistance is reversible by re-plating cells from dried stiff to soft gel collagen. Practical consequences of these observations are that differentiated functions of hepatocytes, such as metabolism, endocytosis, and apoptosis, should be studied in hepatocyte sandwiches. On the other hand, proliferation and regeneration associated signaling can better be studied in hepatocytes cultured on collagen monolayers. In this chapter we focus on mechanisms that influence apoptosis sensitivity in cultured mouse hepatocytes. Key words: Transforming growth factor-β (TGF-β), apoptosis, extracellular matrix, signal transduction, de-differentiation, western blot, fluorescent microscopy.
1. Introduction Primary cultured hepatocytes are a valuable tool to investigate molecular mechanisms involved in the response of the liver to cytokines and growth factors and to study drug metabolism P. Maurel (ed.), Hepatocytes, Methods in Molecular Biology 640, DOI 10.1007/978-1-60761-688-7_7, © Springer Science+Business Media, LLC 2010
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(1–3). In vitro, hepatocytes are remarkably sensitive to the ECM in which they are cultured. Essential hepatocyte features such as polarity, bile canalicular transport, enzymatic activities, and metabolic functions are progressively lost when plated on plates coated with a stiff dried collagen. In turn, when cultured between two layers of collagen gel (referred to as collagen sandwich), most of these features are preserved for extended culture periods (1, 4–6). This indicates that biochemical and physical features of collagen strongly influence hepatocyte morphology and physiological behavior. After few days on conventional stiff collagen, hepatocytes start to spread and acquire a fibroblast-like shape, while on collagen sandwich they remain in a distinctive cuboidal shape for long periods (7). In line with this, hepatocytes on stiff collagen are responsive to growth factor induced cell cycle progression, whereas in contact to a softer collagen gel matrix cell cycle entry is blunted (8). Obviously, stiff versus soft collagen matrix induces different cell states of hepatocytes. Here, we demonstrate that matrix-induced de-differentiation results in apoptosis resistance, and that this is a reversible consequence of specific signaling network constellations, namely ERK and Akt.
2. Materials 2.1. Cell Culture
1. William’s E medium (Sigma, München, Germany). 2. Penicillin–Streptomycin (Gibco-Invitrogen, Karslruhe, Germany). Stock solution of 10,000 U/ml penicillin and 10 mg/ml streptomycin. Add 5–500 ml William’s E medium to a final concentration of 100 U/ml penicillin and 100 μg/ml streptomycin. 3.
L -Glutamine (Cambrex, Vervier, Belgium). Stock solution of 200 mM, aliquoted and stored at −20◦ C. Add 5–500 ml William’s E medium to a final concentration of 2 mM.
4. Dexamethasone (Sigma). Dissolved in ethanol 100%, at 22 μM and stored in aliquots at −20◦ C. Add 23 μl to 500 ml William’s E medium for a final concentration of 100 nM. 5. Fetal bovine serum (FCS, Invitrogen, Karlsruhe, Germany). Aliquoted in 50 ml and stored at −20◦ C. Add 50 ml to a final 500 ml with William’s E medium. 6. Phosphate buffer saline (PBS) (Sterile, without calcium and magnesium) 7. Trypsin 10X solution (PAA laboratories, Cölbe, Germany). Diluted in PBS without calcium and magnesium to 1X. Aliquoted and store at 4◦ C.
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2.2. Preparation of Rat Tail Collagen
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1. Remove skin from dissected rat tails (approx. 5) and dissect the tendon from the rat tail. 2. Wash dissected rat tail tendon three times with 400 ml of 10% NaCl solution (over 2–4 weeks). 3. Wash dissected rat tail tendon three times with equal volume of 1/15 M K2 HPO4 solution (over 2–4 weeks) 4. Lipid extraction with 400 ml of ether (over 1–2 weeks) 5. Dissolve the collagen in glacial acetic acid by stirring constantly and vigorously (over 3–4 days) 6. Filter solution to remove undissolved collagen 6. Adjust collagen concentration to 250–300 μg/ml by photo metric measurement (abs. 540 nm) by adding sirius red in acetic acid (0.5 M). As reference the former collagen solution or commercially available collagen solution can be used.
2.3. Preparation of Collagen Gel in “Sandwich” Cultures
1. Rat tail collagen-I (Roche, Mannheim, Germany). Lyophilized stocks of 10 mg dissolved in 12 ml of 0.2% sterile acetic acid to obtain a final concentration of 833 μg/ml. Store at 4◦ C. 2. 10X DMEM with phenol red (Biozol, Eching, Germany). Stored at 4◦ C. 3. 1 M NaOH. Dissolve 4 g of NaOH in 100 ml of distilled deR ionized water. Filter to sterility with Millipore Millex -GP 25 (0.22 μm pore diameter). 4. Add 1:10 volume of 10X DMEM to the dissolved collagen, keeping the solution on ice. Agitate to mix and neutralize to pH 7.3 by adding stepwise small volumes of NaOH, keeping the solution always on ice. Agitate quickly to mix. Neutralization is achieved by reaching a pink color of the indicator. The concentration of the final solution is 750 μg/ml. 5. Add 250 μl/well to a 9.6 cm2 well (6-well plates), spread evenly, and allow the solution to polymerize at 37◦ C in an incubator for 1 h. Repeat the same procedure to generate the upper layer of collagen gel.
2.4. Antibodies, Chemicals, and Cytokines
1. Recombinant human TGF-β1 (Peprotech, London, UK). 10 ng of lyophilized protein reconstituted in 500 μl of sterile BSA (2 mg/ml) in PBS. Aliquoted and stored at −20◦ C. 2. U0126 (1,4-diamino-2,3-dicyano-1,4-bis[2-aminophenylthio]butadiene) (Sigma), dissolved in DMSO to 25 mM concentration. Aliquoted and stored at −20◦ C. 3. LY294002 (2-(4-Morpholinyl)-8-phenyl-1(4H)-benzopyran-4-one hydrochloride), dissolved in DMSO to 25 mM concentration. Aliquoted and stored at −20◦ C.
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4. PP2 (4-Amino-5-(4-chlorophenyl)-7-(t-butyl)pyrazolo[3, 4-d]pyrimidine), (Merck-Calbiochem, Darmstadt, Germany), dissolved in DMSO to 25 mM concentration. Aliquoted and stored at −20◦ C. 5. Antibodies for apoptosis markers: Rabbit anti-PARP (Cell Signaling, #9542), rabbit anticleaved caspase-3 (Cell Signaling, #9664). 6. Antibodies for signal transduction pathways: mouse antiphospho-Tyr204-ERK (Santa Cruz sc-7383), mouse antiphosho-Ser473-Akt (Cell Signaling #4051), rabbit antiphospho-Ser433/435-Smad2 (Cell Signaling #3101), rabbit anti-phospho-Thr180/182-p38 (Cell Signaling #4631), rabbit anti-ERK (Santa Cruz sc-9102), rabbit anti-Akt (Cell Signaling #9272), rabbit anti-p38 (Cell Signaling #9212), rabbit anti-GAPDG (Santa Cruz sc-25778). 7. Secondary antibodies conjugated to horse radish peroxidise from Santa Cruz. 2.5. Cell Lysis and Protein Quantification
1. RIPA buffer (cell lysis buffer): 50 mM Tris-HCl (pH 7.5), 150 mM NaCl, 1% Nonidet P-40 (NP40), 0.5% sodium deoxycholate, 0.1% SDS, Proteases Inhibitor Cocktail (Roche, Mannheim, Germany, 1 tablet for 50 ml RIPA), Phosphatase Inhibitor Cocktail II (Sigma, München, Germany, 10 μl for 1 ml RIPA). 2. DC Protein Assay (Bio-Rad Laboratories) based on the Lowry assay. 3. Spectrophotometer (Wallac 1420 Victor, Wallac, Turku, Finland)
2.6. SDS Polyacrylamide Electrophoresis 2.6.1. Sample Denaturation Buffer
1. NuPage LDS Sample Buffer (4X) (Invitrogen GmbH, Karlsruhe, Germany). Stored at 4◦ C, warmed to room temperature before use. 2. 1 M DTT. 154 mg dithiothreitol (Sigma, München, Germany) dissolved in 1 ml distilled de-ionized water. Aliquoted and stored at −20◦ C.
2.6.2. SDS/PAGE (Protein Electrophoresis on Denaturating Conditions)
1. NuPAGE 4–12% Bis–Tris gels (1.0 mm×10 wells) (Invitrogen GmbH, Karlsruhe, Germany). Stored at 4◦ C. 2. NuPAGE MOPS SDS running buffer 20X (Invitrogen GmbH, Karlsruhe, Germany). Stored at 4◦ C, diluted to 1X in distilled de-ionized water before use.
Reversible Manipulation in Hepatocytes R 3. SeeBlue -Plus molecular weight GmbH, Karlsruhe, Germany).
marker
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(Invitrogen
4. XCell II Mini Cell apparatus (Invitrogen GmbH, Karlsruhe, Germany). 2.7. Western Blot
1. Nitrocellulose membranes (0.45 μm, Pierce, Rockford, IL, USA). 2. Chromatography Paper (3 MM Chr, Whatman, Maidstone, England) 3. NuPAGE transfer buffer 20X (Invitrogen GmbH, Karlsruhe, Germany). Stored at 4◦ C and diluted in distilled de-ionized water to 1X before use. Prepare 1 l of transfer buffer by mixing 750 ml of water plus 50 ml of 20X transfer buffer and 200 ml of methanol. Cool down to 4◦ C before use or place the transfer chamber in a box with ice. 4. XCell II Mini Cell apparatus (Invitrogen GmbH). 5. Enhanced chemiluminescent (ECL) reagent from Pierce (32109). 6. Immunoblot solution: 5% BSA in TBS-T. 10X TBS (Trisbuffered saline, 1.37 M sodium chloride, 0.027 M potassium chloride, 0.25 M Tris, 0.25 M Tris-HCl, pH 7.4) diluted 1:10 in distilled de-ionized water, plus 10 ml of 10% Tween-20 solution (Bio-Rad Laboratories, Hercules, CA, USA), to a final volume of 1 l with distilled de-ionized water. 7. Stripping solution: 62.5 mM Tris-HCl, pH 6.8 plus 2% (w/v) SDS. Add β-mercaptoethanol to a final concentration of 100 mM before use. 8. Wash buffer (TBS-T): 100 ml of 10X TBS (Tris-buffered saline, 1.37 M sodium chloride, 0.027 M potassium chloride, 0.25 M Tris, 0.25 M Tris-HCl, pH 7.4) and 10 ml of 10% Tween-20 solution (Bio-Rad Laboratories, Hercules, CA, USA), to a final volume of 1 l with distilled de-ionized water.
2.8. Phase-Contrast and Fluorescent Microscopy 2.8.1. Cell Fixation and Permeabilization
1. Fixing solution: 4% paraformaldehyde in PBS pH 7.4: add 50 ml hot water to 4 g paraformaldehyde, add NaOH dropwise under agitation, add 10 ml 10X PBS, adjust pH 7.4 using phosphoric acid, add water to 100 ml end volume. Used immediately after preparation or stored at −80◦ C. 2. Permeabilization solution: 0.3% (v/v) Triton X-100 (Serva, München, Germany) in PBS pH 7.4.
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3. Hoesch 33342 solution: 5 μg/ml Hoesch (Sigma, München, Germany) solution in distilled de-ionized water. Aliquoted and stored at −20◦ C. 2.8.2. Microscopy
1. Leica IPB microscope equipped with a Leica DC500 camera (Leica Microsystems, Wetzlar, Germany).
3. Methods Primary hepatocytes and several hepatoma cell lines are known to undergo apoptosis upon stimulation with transforming growth factor beta (TGF-β) (9–11). However, since primary mouse hepatocytes clearly alter their phenotype depending on the culture system, it is important to determine if their response to cytokines, in this case TGF-β, differs from one system to the other. Therefore, it is important to utilize methods that can clearly and comparably detect apoptosis between cells treated in the two culture systems. 3.1. Cell Culture and Treatment
1. Primary hepatocytes isolated from male C57B6/N mice (8–12 weeks of age) were plated on dishes coated with either an acidic solution of rat tail collagen (250 μg/ml) or a gelled collagen layer (as described in Section 2), in William’s E medium supplemented with 10% FCS, dexamethasone (100 nM final concentration). Four hours after attachment, the cells were carefully washed with PBS twice, in order not to disrupt the collagen gel matrix. For collagen monolayer cultures, the cells were immediately cultured in William’s E medium plus 100 nM dexamethasone, and for the collagen sandwich a second layer of gelled collagen was added on top of the cells and allowed to polymerize in the incubator for 30 min followed by addition of William’s E medium plus 100 nM dexamethasone over night. On the following day (day 1), the cells were washed with PBS twice and cultured from this time on in William’s E without additives. For apoptosis induction, the cells were stimulated with 5 ng/ml TGF-β in William’s E without additives. 2. For the experiments in which chemicals were used to inhibit kinase activity, the respective inhibitors were added as solutions in DMSO to the cells on day 1, 30 min prior to stimulation with TGF-β. In all experimental conditions, the medium and the additives (TGF-β and chemical inhibitors) were added fresh daily.
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Although primary mouse hepatocytes are a valuable tool to investigate molecular mechanisms in response to cytokines, in vitro culture systems hardly reflect a natural environment alike liver tissue. Conventional culture systems for primary hepatocytes rely on the presence of an extracellular matrix of collagen that is added as a single layer on culture dishes. Although this greatly enhances adhesion of the cells, they irremediably begin a de-differentiation process that is clearly appreciable under phasecontrast microscopy. The cells lose their typical honeycomb shape, spreading and adopting a fibroblast-like morphology. On the contrary, when cultured between two layers of gelled collagen, the so-called sandwich culture, hepatocytes remain in their cuboidal shape for extended periods of time, do not spread and form extensive bile canaliculi (Fig. 7.1). The cells are fairly stable in their morphology for 4 days in William’s E medium without any additives.
Fig. 7.1. Primary cultured hepatocyte morphology in collagen monolayer and collagen sandwich. Phase-contrast pictures taken at the indicated time periods after isolation. Cells were kept in basic culture media (William’s E medium, no additives). Reprinted from reference 13 with permission.
3.2. Western Blot Analysis of Apoptosis (PARP Degradation and Cleaved Caspase-3) 3.2.1. Cell Lysis and Protein Quantification
The following protocol was used in all experiments described in this chapter.
1. For Western blot analysis, the cells were cultured in 6-well plates, using 600,000 cells/well (see Note 1). The stimulation with TGF-β was performed on day 1 in medium without additives, using 2 ml/well. Forty-eight hours after stimulation, the cells were lysed in ice cold RIPA buffer. Five hundred microliters of RIPA buffer was used per well. For collagen monolayer cultured cells, the supernatant was collected into a 2 ml sterile tube and centrifuged at 3,000 rpm, 4◦ C for 5 min, in order to collect all dead cells. This is not
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necessary in sandwich-cultured cells since they are trapped in the collagen matrix. While the cells were centrifuged, ice cold RIPA buffer was added to the cells in the culture dish and placed on ice. Using a policeman all cells were harvested into a sterile 1.5 ml tube, then placed on ice. The supernatant of the centrifuged samples was discarded and the pellet was collected with the same cell lysate obtained from the dish. The cell lysate was aspirated up and down five times using a 2 ml syringe and a 20 gauge needle to achieve complete cell lysis. The samples were incubated on ice for 10 min and centrifuged at 10,000 rpm for 10 min at 4◦ C. The supernatant was collected in another sterile 1.5 ml tube and stored at –20◦ C until use. 2. Protein concentration was determined using the DC Protein Assay based on the Lowry assay following the manufacturer’s instructions, in a micro-titter plate (96-well plate). Three microliters of sample was added per well, plus 2 ml of distilled de-ionized water. For each sample, this was done in triplicate. A calibration curve of BSA (1–10 μg/μl) was included. The absorbance was read at 690 nm using a spectrophotometer. Protein concentration was calculated as the average value of three counts per sample and related to a protein standard curve of BSA and a blank value of RIPA. 3.2.2. Sample Denaturation
Twenty micrograms of protein sample was piped into a 1.5 ml tube, plus 10 μl of NuPage LDS Sample Buffer (4X) and 2.5 μl of 1 M DTT. Sample volumes were adjusted to 30 μl with sterile water. After 10 min of incubation at 95◦ C with agitation, the samples were briefly centrifuged at 14,000×g, cooled down on ice, and loaded into a SDS/PAGE gel. Five microliters of R SeeBlue -Plus standard was used on one slot as molecular weight reference.
3.2.3. SDS/PAGE (Protein Electrophoresis on Denaturating Conditions)
NuPAGE 4–12% Bis–Tris gel (1.5 mm×10 wells) and MOPS buffer were used as a standard protocol. Electrophoresis was carried out in an XCell II Mini Cell apparatus for 1 h at a constant voltage of 150 V.
3.2.4. Western Transfer and Immunoblot
1. Protein transfer was performed using an XCell II blotting apparatus with an XCell II Blot module. Chromatography paper and nitrocellulose membrane were used to prepare the gel-membrane sandwich. Blotting pads and the gelmembrane sandwich were placed in the XCell II Blot module according to the manufacturer’s instructions. Blotting was performed for 2.5 h at a constant current of 250 mA (see Note 2).
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2. Efficiency of protein transfer was determined by incubating the membranes with Ponceau Red for 2 min, followed by three washing steps with distilled de-ionized water. Multiple bands were clearly visible. 3. To simultaneously perform immunoblot of PARP, cleaved caspase-3 and β-actin, the membranes were cut with a surgical knife and a ruler, following the molecular weight pattern of the SeeBlue Plus marker (see Note 3). The upper part of the membrane was used to blot PARP, the middle part to blot pSmad2 and β-actin, the bottom part for cleaved caspase-3. 4. Ponceau Red stained membranes were washed with TBS-T for 10 min in rocking device. 5. Blotted membranes were blocked for 1 h at room temperature in 5% non-fat milk in TBS-T, in a rocking device (see Note 4) over night at 4◦ C. 6. The membranes were washed three times for 5 min in TBST in a rocking device at room temperature, followed by an incubation in appropriate secondary HRP-conjugated antibody solutions in TBS-T, diluted 1:500, for 2 h in a rocking device at room temperature. 7. The membranes were washed three times for 5 min in TBST in a rocking device at room temperature. 8. Enhanced chemiluminescent (ECL) reagent was prepared by mixing equal volumes of solutions 1 and 2, following the manufacturer’s instructions. 9. To achieve detection the membranes were incubated with ECL solution for 1 min. Chemiluminescence was detected using a Fujifilms LAS 1000 image detection system. 10. When needed, the membranes can be stripped in stripping buffer for 30 min at 70◦ C, followed by three washing steps in TBS-T for 5 min. The membranes are then blocked and incubated with new antibodies as described above (see Note 5). Although a well-documented effect of TGF-β in hepatocytes is apoptosis (9–11), hepatocytes strongly differed in their susceptibility to TGF-β-induced apoptosis depending on the culture system. In CS, TGF-β caused massive induction of cell death, evidenced by cleavage of caspase-3 and degradation of PARP (Fig. 7.2). In contrast, CM-cultured cells showed resistance to TGF-β-induced apoptosis (Fig. 7.2). 3.3. Apoptosis Detection by Chromatin Condensation
An independent method for the detection of apoptosis serves to unequivocally compare the apoptosis sensitivity of hepatocytes cultured in the two systems described. Although Western blot
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Fig. 7.2. Apoptosis detection by Western blot of PARP and caspase-3 cleavage. Primary cultured hepatocytes in monolayer or sandwich cultures were incubated with 5 ng/ml TGF-β for 48 h. Protein lysates were analyzed by immunoblot of PARP and cleaved caspase-3. β-actin was used as loading control. Reprinted from reference 13 with permission.
allows the simultaneous detection of several proteins (e.g., PARP and cleaved caspase-3), is time consuming and it generates an average readout of the whole cell population. A faster way to assess apoptosis comes from the identification of condensed chromatin, which can be visualized by staining DNA with an intercalating agent that fluoresces under UV light. The combination of Western blot and fluorescent microscopy allows a definite comparison of the apoptotic response of hepatocytes. 3.3.1. Cell Fixation, Permeabilization, and Chromatin Staining
1. Mouse hepatocytes were cultured and treated as described above. 2. 48 h after stimulation with TGF-β, the cells were washed twice with PBS pH 7.4 and fixed in 4% PFA/PBS for 10 min, followed by permeabilization with 0.3% Triton X-100 in PBS for 15 min and washed three times in PBS. 3. Chromatin (DNA) was stained with 5 μg/ml Hoechst H33342 in PBS for 10 min, followed by three washing steps with PBS. 4. Phase-contrast and conventional epi-fluorescence images were obtained in fixed and permeabilized hepatocytes. For conventional epi-fluorescent images, excitation was performed with an EQB 100 isolated fluorescent lamp. Images were acquired with a Leica IM50 software (see Note 6). Figure 7.3 shows that in both monolayer and sandwichcultured hepatocytes, chromatin is uniformly stained in clearly round nuclei, indicating normal living cells. Apoptotic nuclei are observed as small condensed nuclei, which are clearly seen in sandwich-cultured cells treated with TGF-β. This feature is prominent only in sandwich cultures, whereas in monolayer only is seen only seldom.
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Fig. 7.3. Intense chromatin condensation can be observed in collagen sandwich-cultured hepatocytes stimulated with TGF-β (white arrows), whereas in collagen monolayer there are no condensed nuclei. Normal nuclei are indicated by white arrow heads. Reprinted from reference 13 with permission.
3.4. Enhancement of Apoptosis Sensitivity in Stiff Collagen-Coated Cultures by Inhibiting MAPK and Akt Signaling
The apoptosis-resistant phenotype of mouse hepatocytes cultured in collagen monolayer reflects an active response to the culture system. This response is mediated by the activation of the survival pathways Akt and ERK. To compare the activation profile of these pathways in hepatocytes cultured in the two mentioned systems, Western blot analysis of phosphorylation of Akt and ERK can be used. 1. Hepatocytes were cultured in collagen monolayer or collagen sandwich as described. 2. Protein lysates were collected as described, on cells cultured after 24, 48, and 72 h. 3. Western blot analysis using antibodies for phosho-Ser473Akt, phospho-Tyr204-ERK, and total Akt and ERK was performed as described above. Figure 7.4 shows that in monolayer cultured hepatocytes, levels of both phosphorylated Akt and ERK increase during the culture period, while sandwich-cultured hepatocytes do not show activation of these pathways. Culturing mouse hepatocytes in collagen monolayer results in activation of ERK and Akt pathways, both known to promote cell survival (12). To determine the relevance of each pathway for apoptosis resistance, the monolayer cultured cells were stimulated with TGF-β in the presence of inhibitors for MEK1/2 (U0126, 50 μM), the kinase responsible for phosphorylating and activating ERK, and for PI-3 K (LY294006, 25 μM), which phosphorylates Akt. First, the influence of the inhibitors was tested in cells incubated for 1 h with TGF-β to determine if the concentrations used were sufficient to inhibit both basal- and TGF-β-induced
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Fig. 7.4. Comparison of ERK and Akt expression and activation of ERK and Akt in cultured hepatocytes. GAPDH was used as loading control. Reprinted from reference 13 with permission.
Fig. 7.5. Western blot analysis of Smad2, Akt, and ERK phosphorylation in hepatocytes cultured on collagen monolayer. On day 1 the hepatocytes were stimulated for 1 h with 5 ng/ml TGF-β, in the presence or absence of the indicated inhibitors. GAPDH was used as loading control. Reprinted from reference 13 with permission.
activation of the aforementioned pathways. The PI-3 K kinase inhibitor completely abrogated both endogenous and TGF-βinduced p-Akt without altering ERK phosphorylation (Fig. 7.5). The MEK1/2 inhibitor completely blunted ERK phosphorylation (Fig. 7.5); however, it had also a partial inhibitory effect on p-Akt, indicating that there is a cross talk between ERK and Akt pathways in collagen monolayer cultured hepatocytes, in which Akt activation is partially dependent on MEKERK activity. None of these inhibitors influenced TGF-β-induced Smad2 phosphorylation. To determine if these pathways inhibit TGF-β-induced apoptosis, hepatocytes were stimulated with TGF-β for 48 h in the presence of the respective inhibitors, and cleavage of PARP and
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Fig. 7.6. Effect of PI3K and MEK1/2 inhibitors on TGF-β-induced apoptosis in collagen monolayer cultured hepatocytes. Western blot analysis of apoptosis (PARP degradation, caspase-3 activation) and p38 phosphorylation. p38 was used as loading control. Reprinted from reference 13 with permission.
caspase-3 were analyzed by Western blot (see Note 7). Blocking of either ERK or Akt led to enhanced sensitivity to TGF-β-induced apoptosis, as observed by the increase in caspase-3 cleavage and PARP degradation (Fig. 7.6). Since p38 activation is required for TGF-β-induced apoptosis (9), it was tested if inhibition of the anti-apoptotic pathways influences p38 activation. Indeed, both inhibitors enhanced TGF-β-induced activation of p38 (Fig. 7.6). The strongest impact was observed under PI-3 K inhibition. Thus, activation of survival pathways Akt and ERK inhibits TGF-β-induced activation of p38. 3.5. Reversion of Hepatocyte Apoptosis Resistance by Trypsination and Re-plating in Collagen Gel Sandwich
Clearly primary mouse hepatocytes engage in a survival response in collagen monolayer cultures, which is associated to the activation of Akt and ERK pathways. This response is absent when the cells are cultured as collagen sandwich. The following experimental approach allows induction of a reversal of the dedifferentiation process induced in monolayer cultures, demonstrating that hepatocytes can exist in distinct cell states that differ in apoptosis sensitivity. 1. Mouse hepatocytes were cultured in 6-well plates as collagen monolayers for 48 h as described. 2. On day 2, a plate with monolayer of dried collagen and another with a single layer of collagen gel were prepared as described. 3. The cells were washed twice with PBS (without calcium and magnesium). 4. For de-attachment, 300 μl of 1X Trypsin were added to each well for 5 min at 37◦ C. 5. All cells were carefully aspirated with a 1 ml pipette, disrupting all cell clumps by pipetting up and down several times.
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6. The cells were re-suspended in William’s E medium with 10% FCS and dexamethasone, and plated on cell culture dishes coated with either dried collagen or gelled collagen. 7. 6–8 h after attachment, the cells were carefully washed with PBS, and in the case of collagen sandwich cultures, a second layer of collagen gel was added as described. 8. The cells were incubated over night in serum-free medium with dexamethasone. On the next day, the medium was changed to William’s E without additives. 9. The cells were then stimulated with TGF-β as described for another 48 h. 10. For signal transduction and apoptosis analysis, protein lysates were in ice-cold RIPA and analyzed by Western blot as described. The reversibility of the de-differentiation and apoptosis resistance in collagen monolayer can be observed by trypsinizing and re-plating monolayer-cultured cells into collagen sandwich. In Fig. 7.7, phase-contrast microscopy clearly shows that cells replated into collagen sandwich regain honeycomb shape and form evident bile canaliculi. This process continues for at least 48 h after re-plating. In contrast, cells plated back on monolayer further de-differentiate and form a fibroblast-like phenotype, showing extensive lamellipodia and without forming bile canaliculi (see Note 8). The reversal of the phenotype is also evidenced by the reduction in the phosphorylation of ERK (Fig. 7.7), which is only observed in cells trypsinized and re-plated into collagen sandwich. Further, these cells also re-gain sensitivity to TGF-β-induced apoptosis, as evidenced by cleavage of caspase-3 using Western blot analysis.
4. Notes 1. Primary hepatocytes in collagen monolayer spread and cover a larger area than cells in collagen sandwich. This is the reason why 600,000 cells/well on 6-well dishes are sufficient to generate a confluent culture, whereas in sandwich this number yields sub-confluent cultures. 2. The protocols described here for Western blot were done with pre-casted gels. However they can also be nicely analyzed in self casted gel systems. 3. Cutting and dividing the membranes for simultaneous Western blotting serves to speed up the analysis of multiple
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Fig. 7.7. Reversibility of de-differentiation and apoptosis resistance induced in monolayer cultures. Phase-contrast microscopy shows cells in monolayer cultures at the time of trypsination, with evident fibroblast-like phenotype. Twenty-four hours after re-plating in collagen sandwich (CS), the cells acquire honeycomb shape and visible bile canaliculi (bright refringent structures between the cells), while cells re-plated on monolayers continue the de-differentiation process. Likewise, Western blot analysis shows decreased ERK phosphorylation in sandwich re-plated cells (CS), which does not occur in monolayer culture (CM). Apoptosis sensitivity is observed by cleavage of caspase-3 (active caspase-3). Reprinted from reference 13 with permission.
protein targets. However, care must be taken when using different molecular weight markers and gel concentrations. The apparent molecular weight is also depending on the buffer composition of the electrophoresis system. Therefore, the technique should be validated with the materials available in each lab. 4. For PARP, cleaved caspase-3, β-actin, and GAPDH, the antibodies were used in 5% non-fat dried milk. All other antibodies were used in 5% BSA. Solutions are always made in TBS-T. 5. Use the anti-phospho epitope antibodies first, then use the ones for the unphosphorylated form of the proteins. Only at the very last step use the loading control antibodies.
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6. The number of apoptotic cells can be manually counted by an independent observer and generate a quantitative analysis of percentage of apoptosis. 7. Make sure to add the chemical inhibitors to the cells for 30 min before proceeding with the stimulations with TGF-β, which has to include the inhibitors as well. 8. The survival of the cells upon trypsination and re-plating is severely reduced in collagen monolayer. Therefore, we recommend using 2 wells of a 6-well plate for this particular case. In the case of collagen sandwich, the viability is very good.
Acknowledgments The figures in this chapter are part of a manuscript published in Hepatology 2009, June; 49(6):2031–2043. References 1. Hewitt, N.J., Lechon, M.J., Houston, J.B., Hallifax, D., Brown, H.S., Maurel, P., Kenna, J.G., Gustavsson, L., Lohmann, C., Skonberg, C., Guillouzo, A., Tuschl, G., Li, A.P., LeCluyse, E., Groothuis, G.M., and Hengstler, J.G. (2007) Primary hepatocytes: current understanding of the regulation of metabolic enzymes and transporter proteins, and pharmaceutical practice for the use of hepatocytes in metabolism, enzyme induction, transporter, clearance, and hepatotoxicity studies. Drug Metab. Rev. 39, 159–234. 2. Gebhardt, R., Hengstler, J.G., Muller, D., Glockner, R., Buenning, P., Laube, B., Schmelzer, E., Ullrich, M., Utesch, D., Hewitt, N., Ringel, M., Hilz, B.R., Bader, A., Langsch, A., Koose, T., Burger, H.J., Maas, J., and Oesch, F. (2003) New hepatocyte in vitro systems for drug metabolism: metabolic capacity and recommendations for application in basic research and drug development, standard operation procedures. Drug Metab. Rev. 35, 145–213. 3. Hengstler, J.G., Utesch, D., Steinberg, P., Platt, K.L., Diener, B., Ringel, M., Swales, N., Fischer, T., Biefang, K., Gerl, M., Bottger, T., and Oesch, F. (2000) Cryopreserved primary hepatocytes as a constantly available in vitro model for the evaluation
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of human and animal drug metabolism and enzyme induction. Drug Metab. Rev. 32, 81–118. Block, G.D., Locker, J., Bowen, W.C., Petersen, B.E., Katyal, S., Strom, S.C., Riley, T., Howard, T.A., and Michalopoulos, G.K. (1996) Population expansion, clonal growth, and specific differentiation patterns in primary cultures of hepatocytes induced by HGF/SF, EGF and TGF alpha in a chemically defined (HGM) medium. J. Cell Biol. 132, 1133–49. Hamilton, G.A., Jolley, S.L., Gilbert, D., Coon, D.J., Barros, S., and LeCluyse, E.L. (2001) Regulation of cell morphology and cytochrome P450 expression in human hepatocytes by extracellular matrix and cell-cell interactions. Cell Tissue Res. 306, 85–99. Michalopoulos, G. and Pitot, H.C. (1975) Primary culture of parenchymal liver cells on collagen membranes. Morphological and biochemical observations. Exp. Cell Res. 94, 70–78. Tuschl, G. and Mueller, S.O. (2006) Effects of cell culture conditions on primary rat hepatocytes-cell morphology and differential gene expression. Toxicology 218, 205–215. Hansen, L.K. and Albrecht, J.H. (1999) Regulation of the hepatocyte cell cycle by
Reversible Manipulation in Hepatocytes type I collagen matrix: role of cyclin D1. J. Cell Sci. 112 (Pt 17), 2971–2981. 9. Yoo, J., Ghiassi, M., Jirmanova, L., Balliet, A.G., Hoffman, B., Fornace, A.J., Jr., Liebermann, D.A., Bottinger, E.P., and Roberts, A.B. (2003) Transforming growth factor-beta-induced apoptosis is mediated by Smad-dependent expression of GADD45b through p38 activation. J. Biol. Chem. 278, 43001–43007. 10. Yamamura, Y., Hua, X., Bergelson, S., and Lodish, H.F. (2000) Critical role of Smads and AP-1 complex in transforming growth factor-beta -dependent apoptosis. J. Biol. Chem. 275, 36295–36302. 11. Perlman, R., Schiemann, W.P., Brooks, M.W., Lodish, H.F., and Weinberg, R.A.
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(2001) TGF-beta-induced apoptosis is mediated by the adapter protein Daxx that facilitates JNK activation. Nat. Cell Biol. 3, 708–714. 12. Coutant, A., Rescan, C., Gilot, D., Loyer, P., Guguen-Guillouzo, C., and Baffet, G. (2002) PI3K-FRAP/mTOR pathway is critical for hepatocyte proliferation whereas MEK/ERK supports both proliferation and survival. Hepatology 36, 1079–1088. 13. Godoy, P., Hengstler, J.G.C., Ilkavets, I., Meyer, C., Bachmann, A., Muller, A., Tuschl, G., Mueller, S.O., Dooley, S. (2009) Extracellular matrix modulates sensitivity of hepatocytes to fibroblastoid dedifferentiation and transforming growth factor beta-induced apoptosis. Hepatology 49, 2031–2043.
Chapter 8 Markers and Signaling Factors for Stem Cell Differentiation to Hepatocytes: Lessons from Developmental Studies Frédéric Lemaigre Abstract Liver transplantation is the preferred option to treat a number of hepatic diseases in adults and children, but the number of patients on the waiting list is exceeding the number of available livers for transplantation. Hepatocytes differentiated in vitro from stem cells are a promising and renewable source of tissue for transplantation. The principles guiding programmed differentiation of stem cells to hepatocytes are largely based on knowledge gained from studies on embryonic development of the liver. How key findings in developmental biology are translated into cell culture protocols driving stepwise differentiation of hepatocytes is illustrated in this chapter. Key words: Endoderm, hepatoblasts, hepatocytes, liver development, stem cells.
1. Introduction In the embryo the liver develops from the endoderm, a single celllayered epithelium that is formed during gastrulation and which delineates the primitive gut. Morphogenic movements give rise to the foregut lumen lined by the anterior endoderm in which genes become expressed according to a specific anteroposterior (cephalocaudal) pattern. This patterning of the foregut endoderm marks the presumptive domains of organs, such as the thyroid gland, the lungs, the stomach, the liver, and the pancreas, and is established through diffusible factor-mediated interactions between the endoderm and adjacent mesenchymal tissues. When patterning of the endoderm is completed, the liver grows out of the ventral wall of the foregut endoderm, in the vicinity of the cardiac mesoderm (Fig. 8.1). This gives rise to a tissue bud P. Maurel (ed.), Hepatocytes, Methods in Molecular Biology 640, DOI 10.1007/978-1-60761-688-7_8, © Springer Science+Business Media, LLC 2010
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Cardiac mesoderm Ventral foregut endoderm Heart
Liver Septum tranversum
Hindgut Foregut
Liver Gut
Fig. 8.1. Schematic representation of a mouse embryo at days 8.5 and 9.5 of gestation. The location of the developing liver in the vicinity of the septum transversum and heart is shown. The two embryos are not at scale.
consisting mainly of liver precursor cells called hepatoblasts. Interactions with blood vessels, mesenchymal cells, and extracellular matrix are then required to allow proliferation of the hepatoblasts, expansion of the liver bud, and invasion of the septum transversum, a mesenchymal tissue located caudally to the developing heart and which ultimately gives rise to the capsule of Glisson. Further development of the liver is associated with differentiation of the hepatoblasts into either hepatocytes or biliary cells. The hepatocytes then progressively undergo a process of maturation during which they become polygonal and line up as cords flanked by the hepatic sinusoids. In parallel, they gradually express gene networks that are characteristic of the physiological functions of hepatocytes. Maturation is initiated in fetal liver and is finalized several weeks after birth. The biliary cells differentiate around the branches of the portal vein and, following a multistep morphogenic process, give rise to the intrahepatic bile ducts. A dynamic network of transcription factors tightly controls gene expression in hepatocytes and cholangiocytes. It ensures that the cells functionally interact with the extracellular matrix and respond to diffusible factors produced by non-parenchymal cells in order to differentiate and proliferate in a coordinated way. The design of cell culture protocols in which stem cells are differentiated to hepatocytes is largely based on the identification in the embryo of sequential developmental cues, namely markers that characterize cell-specific differentiation stages and diffusible factors controlling stepwise cell fate determination. Knowledge about these markers and signaling factors has been translated into a variety of cell culture protocols which aimed at mimicking the differentiation mechanisms operating in the embryo. This chapter focuses on how developmental biology contributed to the
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identification of the mechanisms of hepatocyte differentiation. The chapter does not provide a comprehensive review on liver development, for which we refer to excellent reviews (1–3), but insists on key steps and regulators that have significant implications in programmed in vitro hepatocyte differentiation (see also Chapters 9–11).
2. Development of a Regionalized Endoderm
In vertebrates, gastrulation gives rise to the three germ layers, namely ectoderm, mesoderm, and endoderm. There is accumulating evidence that the endoderm and mesoderm derive from a common progenitor called mesendoderm, located near the node. The latter, which is characterized by the expression of Brachyury, was shown to secrete Nodal, a member of the transforming growth factor (TGF)-beta family, which in a dose-dependent manner promotes differentiation of mesendoderm to either mesoderm or endoderm. The analysis of hypomorphic alleles of Nodal in mouse embryos indicated that endoderm fate is determined by high levels of signaling while low levels promote mesoderm formation (4–6). Since Nodal protein is not available for experimental purposes, ActivinA, another member of the TGF-beta family which binds to the same receptors as Nodal, is used at high concentrations in cell culture protocols to drive differentiation of embryonic stem cells to endoderm (7, 8). Wingless-type MMTV integration site family member signal (Wnt) is also known to play a role in endoderm cell fate determination, since embryos deficient in the Wnt mediator beta-catenin showed ectopic mesoderm cells in the endoderm (9). As a result, Wnt3a is also included in cell culture protocols to generate endoderm from embryonic stem (ES) cells (10, 11). There is no unique protein whose expression defines endoderm identity and allows to make a distinction between embryonic (i.e., definitive endoderm) and extraembryonic endoderm. However, in vivo studies determined that the expression of a combination of proteins, which includes the SRY-box containing transcription factor 17 (Sox17) and the chemokine CXC receptor 4 (CXCR4), identifies definitive endoderm. Loss-of-function and gain-of-function studies validated several of these markers as functional endodermal markers. For instance, mice knockout for Sox17 are deficient in gut endoderm (12), and constitutive expression of Sox17 in ES cells induces differentiation toward definitive endoderm (13) confirming the importance of Sox17 in endoderm development. Hence, D’Amour and coworkers (10) used the expression of a set of factors that includes Sox17 and
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CXCR4 to characterize the endodermal cells obtained after treating cultured ES cells with Wnt3a and ActivinA. Importantly, beyond the gastrulation stage the expression of genes in the endoderm is characterized by an anteroposterior pattern, which results from interactions with the adjacent mesoderm. Fibroblast growth factors (FGF) and retinoic acid are key signaling factors that confer posterior identity to endoderm cells in the embryo. FGF and retinoic acid must be absent from ES cell culture medium when driving differentiation of hepatocytes, because the latter derive from foregut endoderm and not from posterior endoderm (14, 15).
3. Differentiation of Hepatoblasts from Foregut Endoderm Cells
Once foregut endoderm is generated in the embryo, several signaling factors confer hepatic identity to endoderm cells. Hepatic specification is evidenced by the expression of albumin, transthyretin, and alpha-fetoprotein, which are the earliest liver markers. This occurs in the ventral endoderm region that is adjacent to the developing heart and to the septum transversum mesenchyme, two tissues which act as a source of signaling factors that promote liver specification (Fig. 8.1). Tissue transplantation experiments and embryonic explant cultures performed by the teams of LeDouarin (16) and Zaret (17) revealed that FGF-1 and FGF-2, which are expressed by the cardiogenic mesoderm, can induce hepatoblast development in cultured endoderm. These experiments were further refined by Serls and coworkers (18) who cultured mouse endodermal explants in the presence of increasing doses of FGF. This revealed that low FGF concentrations induce liver gene expression and high concentrations induce lung-specific gene expression, thereby underscoring the need to determine the optimal dose of FGF when differentiating endoderm cells in vitro to hepatoblasts. The septum transversum, which at the time of hepatic induction is located caudally to the cardiogenic mesoderm and in the vicinity of the endoderm, is a source of bone morphogenic proteins (BMP)-2 and BMP-4. BMPs act cooperatively with FGFs in hepatic induction (19). These observations about the role of FGFs and BMPs in the embryo prompted the use of these signaling factors in cell culture protocols for stimulating differentiation of cells toward the hepatocytic lineage. The cells which are specified express albumin, transthyretin, alpha-fetoprotein and the transcription factor hepatocyte nuclear factor (HNF) 4. Detecting the expression of these genes constitutes a reliable way to identify the cells that have entered the hepatic differentiation pathway. The cells
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also express the transcription factors HNF3-alpha/Forkhead box (Fox) A1, HNF3-beta/FoxA2, and HNF1-beta/TCF2, which are not strictly liver specific, but whose expression is required for liver development as illustrated by the lack of liver in the mice with inactivation of the corresponding genes (20, 21). Developmental biology benefits from the use of several animal models such as mouse (Mus musculus), frog (Xenopus laevis), and zebrafish (Danio rerio). However, care must be taken when interspecies differences are observed about the role of signaling factors. Zebrafish deficient in Wnt2b fails to normally develop a liver from the endoderm, suggesting the need for Wnt signaling to promote hepatic specification (22). However, Wnt signaling must be repressed in Xenopus endoderm to allow hepatic induction, and mouse foregut endoderm secretes the Wnt antagonist Frizzled-related protein 5. Such discrepancies, which most likely result from evolutionary divergence (2), must be considered when implementing the use of Wnt or its inhibitors in cell culture protocols aiming at differentiating hepatoblasts from endoderm-like cells.
4. Differentiation of Bipotent Hepatoblasts Toward the Hepatocyte Lineage
When the endoderm cells have been specified to a hepatic fate, liver morphogenesis in the embryo is initiated by the outgrowth of the endoderm and the development of a liver bud. The cells, called hepatoblasts, proliferate intensively. The prospero-related homeobox factor (Prox) 1 and the transcription factor GATA6 are required at this stage in hepatoblasts since mice knockout for these transcription factors initiated liver budding from the endoderm but failed to expand their liver (23, 24). The proliferation of the hepatoblasts is tightly controlled by endothelial cells that surround the liver bud. Again, this was demonstrated by the analysis of knockout mice, and more specifically by studying mice which, due to deficiency in the Flk-1 (vascular endothelial growth receptor 2) gene, did not develop endothelial cells (25). Importantly, the signaling factors secreted by the endothelial cells have not yet been identified. Their identification and subsequent use in cell culture models is expected to allow improvement of hepatocyte differentiation protocols. The early liver is not solely constituted of hepatoblasts and endothelial cells. An important tissular compartment is formed by mesenchymal cells which progressively colonize the organ. These cells are yet another source of signaling factors. Scatter factor/hepatocyte growth factor (HGF) is commonly used in cell culture protocols, and in vivo it is produced by the mesenchymal
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cells. The functional importance of HGF and its receptor c-Met was underscored by loss-of-function studies. Mice knockout for the Hepatocyte growth factor or c-Met gene showed severe liver hypoplasia (26–28), indicating a key role of these genes in liver cell proliferation and survival. In parallel to proliferation, hepatoblasts must differentiate to either hepatocytes or cholangiocytes. Biliary cells are formed around the portal mesenchyme which acts as a source of TGFbeta. High TGF-beta signaling activity promotes biliary differentiation near the portal mesenchyme and lower TGF-beta signaling allows hepatocyte differentiation in the parenchyma, at a distance of the portal mesenchyme. Excessive TGF-beta signaling in the parenchyme is associated with the appearance of abnormal cells that co-express hepatocytic and biliary markers (29). Therefore, any in vitro culture method aiming at differentiation of hepatocytes may benefit from a tight control of TGF-beta signaling activity. Wnt3a stimulated the expression of biliary markers in liver explants, and constitutive activation of beta-catenin in embryonic livers favored biliary differentiation at the expense of hepatocyte differentiation (30, 31). These data implicate Wnt/beta-catenin signaling in hepatoblast fate decision and suggest that Wnt signaling should be downregulated when promoting hepatocyte differentiation. However, total ablation of beta-catenin in hepatoblasts is associated with impaired differentiation of hepatocytes, suggesting that some level of Wnt/beta-catenin must be maintained to allow hepatocyte differentiation (32). Once the hepatocyte lineage has been separated from the biliary lineage, the hepatocytes undergo a process of maturation during which the cells progressively acquire their metabolic properties. This process is tightly controlled by a dynamic network of transcription factors, as indicated by the in vivo analysis of gene promoter occupancy. This network contains a core of six transcription factors (HNF1-alpha, HNF1-beta, HNF3beta/FoxA2, HNF4-alpha1, HNF6, and liver receptor homolog (LRH) 1) which functionally cross-regulate each other and which regulate the expression of other downstream hepatic regulators (33). The successive steps of hepatocyte maturation are determined not only by the presence of core transcription factors but also by their abundance. Indeed, the concentration of the six core transcription factors progressively rises during hepatocyte maturation, and it was shown that a transcription factor may recruit different co-activators and stimulate the expression of different genes depending on its concentration. Therefore, the time-dependent rise in transcription factor concentration determines time-dependent maturation of hepatocytes (34). These studies illustrate that quantifying the level of key intracellular factors is required for optimization of differentiation protocols.
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Hepatocyte maturation is also controlled by cell-extrinsic cues, the most important being oncostatin M (OSM), an interleukin-6-related cytokine secreted by hematopoietic cells. Culture of fetal hepatocytes in the presence of OSM promoted morphological changes and glycogen accumulation as well as expression of hepatic differentiation markers. Moreover, the effects of OSM were amplified by glucocorticoid hormones (35). These observations form the basis for the inclusion of OSM and dexamethasone at the terminal steps of cell culture protocols for differentiation of stem cells to hepatocytes. An example is illustrated in Fig. 8.2, which is based on the results shown by Hay and coworkers (36). Human ES cells were differentiated to hepatocytes using specific signaling factors (Activin, HGF, and OSM) combined with non-specific differentiation agents (dimethyl sulfoxide and sodium butyrate), and the temporal gene expression profile was measured. This profile illustrates the sequential pattern of gene expression from undifferentiated cell stage to mature hepatocyte, and in particular the role of OSM and HGF in maturing the cells to acquire typical metabolic functions such as apolipoprotein expression.
activin
HGF + OSM
Oct4 Brachyury Sox17 FoxA2 HNF4 alpha alpha-fetoprotein Albumin Apolipoprotein F 2
5
9
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Fig. 8.2. Temporal gene expression profile during differentiation of human embryonic stem cells (ES) to hepatocytes. The sequential expression of ES cell-, endoderm-, and hepatocyte-specific genes is obtained by treating human ES cells with differentiationinducing factors that were selected to mimick key stages of liver development in the embryo. The figure is based on the results from Hay et al. (36).
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5. Hepatocyte Heterogeneity After birth, maturation of hepatocytes continues. This is associated with subspecialization of hepatocytes according to a process called liver zonation. Hepatocytes located near the central vein differ in their metabolic properties from the hepatocytes located near the portal spaces. This spatial organization of the various metabolic pathways is required to adapt liver metabolism to the different nutritional requirements in different metabolic states. Cell-intrinsic cues such as transcription factors are critical to establish the zonation pattern, as illustrated by the observation that lack of HNF4-alpha in knockout mice was associated with expression of pericentral proteins in periportal hepatocytes (37). Recent advances in the study of morphogens identified Wnt as a key modulator of liver zonation. Indeed, mice in which Wnt signaling in liver was upregulated through inactivation of the Adenomatosis polyposis coli gene, or in which Wnt signaling is repressed by overexpression of the Wnt antagonist Dickkopf-1, showed profound anomalies of liver zonation (38). These data reveal that new tools now exist to address the issue of hepatocyte heterogeneity when considering programmed differentiation of hepatocytes in culture.
6. Conclusion The extraordinary development of cellular and molecular embryology in the past two decades has allowed to define the key steps in the morphogenesis of the liver and the differentiation of hepatocytes. This now allows experts in cell replacement therapy to mimick in vitro the processes operating in the developing embryo. Significant success in the advancement of cell therapy has been booked thanks to the application of these principles, but several issues such as fine-tuning of the differentiation process, quantification of the response to differentiation-inducing agents, optimal choice of differentiation markers, or characterization of hepatocyte heterogeneity require further investigation. Continuous exchange of information between developmental biologists and experts in cell therapy remains essential for further progress.
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Chapter 9 Hepatic Stem Cells Robert E. Schwartz and Catherine Verfaillie Abstract Early studies in hepatocyte turnover and liver regeneration showed that the parenchymal cell, the hepatocyte, was the primary and only cell involved in tissue renewal. However, new studies of liver regeneration, hepatocarcinogenesis, liver transplantation, and various cell lines have shown that a variety of cell types participate in maintaining hepatocyte number and mass and question the dogma of the previous hierarchy of hepatocyte differentiation in vitro and in vivo. Key words: Hepatocytes, hepatic stem cells, development, stem cell plasticity, liver regeneration.
1. Introduction Historically organs with low cell turnover were not believed to contain stem cells. Only organs and tissues with rapid turnover such as those seen in the bone marrow, gastrointestinal epithelium, and the epidermis were believed to contain stem cells in order to maintain the tissue through continuous production of parenchymal cells. In addition, the search for liver stem cells using a variety of means only produced more questions with no identified cell that was generally accepted as the putative “hepatic stem cell” or a hierarchy of cell differentiation. However, studies of liver regeneration, carcinogenesis, and injury suggested the existence of liver stem cells. More recently it has been shown that organs with minimal turnover such as in the central nervous system (CNS) or heart or low turnover such as in the liver contain stem cells. Subsequently, stem cells have been isolated from a variety of organs and tissues and today, each organ and tissue is thought to possess cells capable of self-renewal and of giving rise P. Maurel (ed.), Hepatocytes, Methods in Molecular Biology 640, DOI 10.1007/978-1-60761-688-7_9, © Springer Science+Business Media, LLC 2010
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to a large number of differentiated descendents. However, our understanding of the role and contribution of adult stem cells and of liver stem cells in particular to hepatocyte turnover, liver pathophysiology, and in the normal function of the liver is quite limited. In addition, new concepts such as adult stem cell plasticity and cell fusion may completely alter the stem cell paradigm and with it our understanding of stem cell biology. Present research on liver stem cells comprises methods used in other fields of stem cell biology, isolation and characterization, analysis of differentiation and function, and transplantation. Recent papers in the field have led to divergent viewpoints about the nature and properties of the liver stem cell, its origin, i.e., whether the liver stem cell resides in the liver versus in the bone marrow or whether it is merely a product of fusion. In this chapter, we will review several reports on liver stem cells addressing the strengths and concerns of each report including (1) the evidence of the existence of the liver stem cell; (2) the types of stem cells in the liver; (3) the origin of liver stem cells; and (4) the isolation, culture, characterization, differentiation potential, and in vivo functional capability of liver stem cells. See also Chapters 10 and 12 of the present volume.
2. Basic Biology of Stem Cells Through the years, stem cells have been defined in many different ways. Therefore, without a consensus definition, many scientists have used similar and differing terminology to describe similar and differing cells. Therefore, the lack of common standards of what defines a “stem cell” in most fields has led the term “stem cell” to mean very different things to different researchers. Therefore, in order to begin any discussion on stem cells, we need to discuss a consensus stem cell definition, originally developed in the hematopoietic field and easily extended to the hepatology field. This consensus definition would encompass three main principles. First, a stem cell must be capable of self-renewal, i.e., undergoing symmetric or asymmetric divisions through which the stem cell population is maintained. Second, a single stem cell must be capable of multilineage differentiation. The third principle is in vivo functional reconstitution of a given tissue. Therefore, a liver stem cell (ignoring the complications of plasticity and cell fusion) would be any cell that is capable of self-renewal, able to form the different cell types composing the liver, i.e., the cholangiocyte and hepatocyte at the single-cell level, and can in vivo reconstitute both cell types and the function of the normal liver parenchyma. Stem cells are further characterized by their different capacities for self-renewal and lineage differentiation. A fertilized
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egg is capable of forming not only the cells of the ectoderm, endoderm, and mesoderm layers, and germ cells but also the supporting extraembryonic tissues required for the survival of the developing embryo. Therefore, these cells are the apex of the stem cell hierarchy and termed “totipotent.” Embryonic stem (ES) cells and embryonic germ (EG) cells, isolated from the inner cell mass of the blastocyst or from primordial germ cells of an early embryo, give rise to ectoderm, endoderm, and mesoderm layers, and germ cells but cannot form extraembryonic tissues and are therefore termed “pluripotent.” Stem cells isolated from various adult organs can self-renew and differentiate into multiple tissue-specific cell types. These stem cells are termed “multipotent stem cells.” One example, the hematopoietic stem cell (CD34+ /Sca-1+ /c-Kit+ /CD45+ /Lin− ) is limited to differentiation to hematopoietic cell lineages such as erythrocytes, lymphocytes, neutrophils, and platelets (excluding recent data on HSC plasticity), is capable of self-renewal, and has been shown through both clinical treatment and research to be capable of in vivo reconstitution of the bone marrow. Committed cells generally have limited or no self-renewal ability and differentiate into only one defined cell type and are dubbed “progenitor cells” or “precursor cells” and thus are not considered stem cells. The embryonic stem (ES) cell is the quintessential pluripotent stem cell as it fulfills all criteria. ES cells are pluripotent stem cells that can be propagated indefinitely in an undifferentiated state. ES cells differentiate to all cell lineages in vivo and also differentiate into many cell types in vitro. ES cells have been isolated from humans (1); however, their use in research as well as in clinical practice was initially hampered by ethical and technical consideration (2). With the implementation of iPS (induced pluripotent stem cells) these concerns have been replaced with concerns related to their derivation (with viral vectors), although one recent report describes their derivation without integrated viral vectors (3, 4). As embryonic stem cells readily form teratomas (pluripotent tumors), it will be critical to develop a novel method that ensures that all ES cells differentiate and none are left pluripotent (5). Stem cells exist for most tissues, including hematopoietic (6), neural (7), gastrointestinal (8), epidermal (9), hepatic (10), and mesenchymal stem cells (11). Compared with ES cells, tissuespecific stem cells have less self-renewal and proliferative capability and are not pluripotent. Only recently has it been shown that tissue-specific stem cells could not only differentiate into cells of the tissue of origin but possibly into other lineages. For example, following transplantation of donor bone marrow (BM) or enriched hematopoietic stem cells (HSC) into allogeneic recipients, skeletal myoblasts (12–14), cardiac myoblasts (15–17), endothelium (15–19), hepatic and biliary duct epithelium
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(20–22), lung, gut, and skin epithelia (23), keratinocytes (24), and neuroectodermal cells of donor origin have been detected (25–28). Although studies demonstrate that fusion may account for the unexpected results of cell lineage differentiation (28–35), other groups have reproduced such results without any evidence of fusion (24, 36–40) or a combination of both (41, 42).
3. Adult Liver as a Source of Hepatic Progenitors
Prior to our examination of adult hepatic stem cells we need to first address one of the liver’s truly unique abilities: the ability to regenerate after injury or resection while precisely controlling its growth and mass. This extraordinary feat was even known to the ancients, recounted in the myth of Prometheus. Prometheus, having given the secret of fire to humanity, was condemned to be chained to a rock in the mountains. An eagle each day would eat a portion of his liver which in turn would grow back overnight, thus providing the eagle with eternal food, and Prometheus with eternal torture. Despite the ancient’s knowledge of liver regeneration, scientific documentation was not made until the 1890s (43). Though liver regeneration is a well-known phenomenon, there are many misconceptions and unknowns. First, what is usually referred to as liver regeneration is actually a process of compensatory growth (44). In an average liver resection, approximately two-thirds of the liver is removed. The surgically resected liver does not grow back. Instead, the portions of the liver remaining after a typical hepatectomy increase in size to compensate for the loss of tissue and expand until the mass of the regenerated liver reaches approximately the original organ mass. At the end of the process (about 2 weeks in rodents and perhaps 1–2 months in humans), liver mass is restored but anatomical form is not reconstituted. This is a clear indication that compensatory growth after hepatectomy is a tightly controlled process and is in synchrony with the body. However, the liver functions independently of its anatomical form (45–48). Such rapid recovery of the liver mass in experiments in the late 1960s led many people to conclude that there were no hepatic stem cells in the liver (45). While the normal liver is a very active metabolic organ with hundreds of different functions, it is also a rather quiescent organ with only 0.0012–0.01% of hepatocytes undergoing division at any given time as shown repeatedly using BrdU and [3H]-thymidine labeling (49). Unlike other regenerating tissues (i.e., the skin, the epithelial lining of the gut, the bone marrow), liver regeneration is, in
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general, not dependent on stem cells or progenitor cells (44). Liver regeneration initiated by partial hepatectomy induces proliferation of mature hepatocytes allowing full recovery of liver mass. Often ignored and poorly understood is the required proliferation of all the other mature cell types besides hepatocytes in the liver including the biliary epithelial cells, sinusoidal endothelial cells, Kupffer cells, and stellate cells (46). The important question to ask is “What is the source of hepatocytes required to replace the missing liver mass?” This is not a simple answer as it depends on the situation and the nature of the liver injury. The next question to ask is “What is the nature of the situation that leads to different origins of hepatocytes?” Most studies demonstrate that replication of mature hepatocytes occurs in response to partial hepatectomy and centrilobular injury (44, 50). In contrast, when hepatocyte proliferation is inhibited by chemical injury induced by 2-acetylaminofluorene (2-AAF), allyl alcohol, diethoxycarbonyl1,4-dihydrocollidine (DDC), small cells called oval cells proliferate. Replication of hepatocytes seems the most likely and best documented source of hepatocytes. Other groups have shown that oval cells (a bipotential cell capable of differentiating into both biliary ductule cells and hepatocytes) can serve as a hepatocyte source. More recently, a large number of studies have shown BM contribution to hepatocytes albeit through various processes, differentiation versus fusion. Oval cells have multilineage capacity but proliferate only under special conditions (e.g., in damaged liver tissue). Oval cell progenitors are thought to be localized in biliary ductules (canals of Hering) in normal adult liver and have also been identified during hepatic embryonic development although their true origin is still unknown and is disputed (51). Work by Evarts and others have determined that oval cells are bipotential and give rise to both hepatocytes and biliary ductal epithelial cells (52, 53). Studies have identified many cell surface markers for oval cells both in rodents and in humans such as Thy1.1, CD34, Flt3-receptor, and c-kit, as well as cytoplasmic markers AFP, CK19, γ-glutamyltransferase, although no single marker or combination of markers offers complete specificity for cell identification of viable cells (54, 55). However, a new panel of surface antibodies has been produced by Dorrell et al. that may address this problem (56). It has been argued that oval cells are derived from hematopoietic stem cells, which may explain several studies suggesting a link between hematopoietic stem cells or some other cell in the bone marrow and the liver. Petersen et al. showed that following bone marrow (BM) transplantation, oval cells are derived from the donor BM (21). Kollet et al. and Hatch et al. offer a possible mechanism. Kollet et al. showed that human CD34+
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hematopoeitic progenitors expressing CXCR4 are attracted to SDF-1α production in the liver and that liver injury leads to increased SDF-1α production (57, 58). Hatch et al. showed that mouse oval cells express CXCR4 and that massive liver injury but not mild injury induces SDF-1α expression. Taken together, this suggests a possible mechanism for SDF-1α/CXCR4 in bone marrow and oval cell homing to the liver during liver injury. In contrast, Wang et al. demonstrated in the FAH–/– mice that oval cells were neither derived from mature hepatocytes or from progenitors in the bone marrow (59). Most studies look at groups of oval cells to better characterize their behavior, differentiation capability, and marker expression. This approach uses analysis of multiple cells raising the problem that multiple cell populations may be present potentially skewing the analysis. Taking a different approach Suzuki et al. demonstrated that oval cells can be isolated using CD133 to prospectively sort DDC-induced livers into clonal populations (60). Then at the clonal level they showed that these cells differentiate into both cholangiocytes and hepatocytes both in vitro and in vivo. Although previous studies have used DLK (delta-like kinase) and other markers to isolate oval cells, this represents the first study to analyze these cells at the clonal level both in in vitro and in vivo studies (61). Oval cells have also been induced in the livers of adult rats fed choline-deficient diets supplemented with the hepatocarcinogenic agent N-2-acetylaminofluorene (62), as well as under enzymatic harvesting conditions designed to destroy hepatocytes (63–66). Oval cell proliferation can be inhibited by PPAR-γ agonists (67) or enhanced by α1-adrenoceptor antagonism, chemical sympathectomy via 6-hydroxydopamine (68), or via HGF (69). Most protocols required for oval cell isolation use carcinogenic compounds to inhibit hepatocyte proliferation and often result in oval cells that have tumorigenic potential (60). This raises the question of whether oval cells represent the “transit amplifying” hepatic progenitor cell or is related to an unidentified stem cell functioning in both liver regeneration and carcinogenesis (70–72). In attempts to avoid the use of carcinogens several groups have attempted the generation and identification of hepatic progenitors generated from normal adult liver or other organs de novo. After studying common antigens on cells in fetal and adult regenerating cholestatic livers, Avital et al. showed that β2m– /Thy-1+ cells exist both in the liver and in the bone marrow and demonstrated that β2m– /Thy-1+ bone marrow cells express hepatic markers and can differentiate into cells with the phenotypic characteristics of hepatocytes both in vitro and in vivo (73). Azuma focused on the nonparenchymal liver fraction devising a complex culture methodology involving hypoxic cell culture conditions thereby largely eliminating the parenchymal fraction and promoting cellular aggregate formation. Ninety five percent of
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cellular aggregates were composed of endothelial cells, while the remaining cells consisted of rapidly proliferating, small epithelial cells that expressed AFP, E-cadherin, and albumin but not CK 19. After culture with DMSO and dexamethasone, these cells expressed mature hepatocyte markers and induced hepatocytelike morphology including the formation of bile canaliculi (74). Other work by Sahin et al. used a culture condition technique to isolate hepatic progenitors from rat liver with marker expression similar to oval cells without prior chemical induction (75). These progenitors were shown capable of both hepatocyte and biliary ductule differentiation by marker expression as well as by functional characteristics. Mitaka et al. identified what he termed the small hepatocyte (SH). SH are proliferating mononucleate cells with a less differentiated appearance possessing hepatic marker expression as shown by immunocytochemistry that form small-cell colonies surrounded by mature hepatocytes (76–78). Culture of SH with a matrigel overlay, bone marrow stromal cells, or liver nonparenchymal cells all resulted in the expression of mature hepatocyte differentiation as evidenced by reexpression and upregulation of CYP1A1/2, CYP2B1, CYP3A2, CYP4A1, connexin 32, and tryptophan 2,3 dioxygenase expression. These cells are highly similar to those described by Gordon et al. who showed that retrorsine (an alkaloid) administration in vivo which prevents hepatocyte replication secondary to retrorsine-induced injury resulted in the proliferation of small hepatocyte-like progenitors in the hepatic lobule (79–81). These cells expressed some oval cell markers such as AFP, OC.2, and OC.5 but lacked OV-6, CD34, and Thy-1 expression and after their transplantation were able to differentiate into hepatocytes. Gordon hypothesized that these cells which lack expression of the regular complement of cytochrome P450 enzymes in vivo were resistant to retrorsine and thus able to proliferate in vivo as opposed to hepatocytes which would have metabolized the toxic chemical and thereafter would be unable to proliferate.
4. Plasticity of BM, HSC, and Their Differentiation into Hepatocytes
Adult stem cells have been viewed as committed to a particular cell fate. For example, hematopoietic stem cells (HSC) were viewed to only contribute to lineages that are part of the hematopoietic system, i.e., red blood cells and white blood cells and not unrelated tissues, such as hepatocytes or oval cells as discussed earlier. Many studies have questioned this dogma by demonstrating that cells from a given tissue might differentiate into cells of
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a different tissue (12, 22, 25, 31, 82–84). To many, “stem cell plasticity” may be a new concept. However, the idea is almost a century old. In the late 19th and early 20th centuries, it was recognized that there are epithelial changes in tissues in response to different stresses (85). These changes in which one adult cell type is replaced by another cell type was termed metaplasia. An example includes the change from columnar epithelium to squamous epithelium in the respiratory tract of smokers in response to chronic irritation caused by smoking (85). Another example is the change from squamous epithelium to columnar epithelium due to gastric reflux that occurs in Barrett’s esophagus (85). Evidence that HSC or bone marrow may contribute to hepatocyte formation was initially found in experiments where the liver incurs severe damage while more recent experiments have attempted to define the subpopulation of bone marrow cells capable of generating hepatocytes both in vitro and in vivo. In livers from females who received a sex-mismatched bone marrow transplantation, 5–40% (depending on recipient) of the liver parenchyma contained the Y chromosome and this appeared to be derived from the donor bone marrow (22). When the lineage-switched hepatocytes were examined by cytogenetic analysis, they were shown to bear only one X and one Y chromosome (86). In cases of graft versus host disease, levels of engraftment were found to be even higher among cells of the liver and gastrointestinal tract. In all studies except the study by Krause et al., mixed cell populations were transplanted. Consequently, demonstration of hepatocytes of donor origin does not prove adult stem cell plasticity, as there is evidence that BM contains cells with hepatocyte markers (20, 23, 87, 88). Krause et al. demonstrated that a single “homed” CD34+ Sca1+ mouse bone marrow cell was capable of differentiation into epithelium of liver and lung along with hematopoietic cells (23). However, in a similar single-cell transplantation study, Wagers et al. found that transplantation of fresh sorted cKit+ Thy1+ Lin– Sca1+ cells gave rise to considerably less “lineage switch” (only seven hepatocytes). Whether the different phenotype of the transplanted cells plays a role in these differing results is not known. However, none of the studies suggesting bone marrow to endoderm differentiation proved that the bone marrow-derived endodermal epithelial cells were functional. One exception is the landmark study by Lagasse et al. which demonstrated that bone marrow-derived cells can successfully rescue mice lacking the enzyme fumarylacetoacetate hydrolase, a key enzyme in the tyrosine metabolism pathway (20). Mice lacking this enzyme develop acute liver failure. This results from the accumulation of the upstream metabolite, fumarylacetoacetate (FAA), which is broken down into toxic metabolites through other pathways (89). FAA production is prevented by a drug 2-(2nitro-4-trifluoromethylbenzoyl)-1,3-cyclohexanedione (NTBC),
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which acts on an enzyme upstream of FAA (90). Therefore, liver failure can be controlled through the administration of NTBC. Lagasse et al. showed that FAH mutant animals transplanted with normal BM or normal BM enriched for HSC could be taken off of NTBC (20). These animals quickly developed acute liver failure but a majority of animals recovered, and when examined more closely had evidence of donor-derived hepatocytes. Animals that received no transplant died, demonstrating functional hepatic repopulation derived from donor HSC. One criticism that can be leveled at this study is that a minimum of 50 purified HSC was necessary to get animal survival and hepatic repopulation. Therefore the possibility remains that one cell in this fraction was capable of differentiating into hepatocytes, while the other cells were capable of reconstituting the hematopoietic system. More recent studies have shown that fusion accounts for a large part of the contribution of HSC to hepatocyte engraftment in the FAH model (32, 91). Wang et al. and Vassilopoulos et al. both showed that the rescue of FAH mice with bone marrow-derived cells is the result of the fusion of HSC or HSC-derived progeny to hepatocytes. Wang et al. demonstrated that the transfer of genetic material from normal HSC or HSC-derived progeny to the FAH–/– hepatocytes resulted in hepatocytes that were able to produce the missing enzyme and consequently rescue the mice. Willenbring et al. and Camargo et al. confirmed these results demonstrating that the fusogenic cell is most likely from the myelomonocytic fraction and not directly from HSC (29, 30, 33). However, these results are confounded by reports that demonstrated that their Cre/Lox-based strategy labels both HSC and myelomonocytic cells raising the possibility again that HSC may account for some of the fusogenic events seen in their models (33). Moreover similar work by Harris et al. demonstrated the lack of a fusion requirement for hepatocyte differentiation from stem cells (36). Regardless of the mechanism, stem cell plasticity versus cell fusion, the potential clinical utility of these cells should not be ignored. Moreover, better understanding of the mechanism of cell fusion may provide a better understanding of development, cellular reprogramming, regenerative medicine, and provide a new and unique method for gene therapy. References 1. Thomson, J.A., Itskovitz-Eldor, J., Shapiro, S.S. et al. (1998) Embryonic stem cell lines derived from human blastocysts. Science 282, 1145–1147. 2. Frankel, M.S. (2000). In search of stem cell policy. Science 287, 1397. 3. Takahashi, K. and Yamanaka, S. (2006) Induction of pluripotent stem cells from
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Chapter 10 Hepatic Stem Cells and Liver Development Nalu Navarro-Alvarez, Alejandro Soto-Gutierrez, and Naoya Kobayashi Abstract The liver consists of many cell types with specialized functions. Hepatocytes are one of the main players in the organ and therefore are the most vulnerable cells to damage. Since they are not everlasting cells, they need to be replenished throughout life. Although the capacity of hepatocytes to contribute to their own maintenance has long been recognized, recent studies have indicated the presence of both intrahepatic and extrahepatic stem/progenitor cell populations that serve to maintain the normal organ and to regenerate damaged parenchyma in response to a variety of insults. The intrahepatic compartment most likely derives primarily from the biliary tree, particularly the most proximal branches, i.e. the canals of Hering and smallest ductules. The extrahepatic compartment is at least in part derived from diverse populations of cells from the bone marrow. Embryonic stem cells (ES’s) are considered as a part of the extrahepatic compartment. Due to their pluripotent capabilities, ES cell-derived cells form a potential future source of hepatocytes, to replace or restore hepatic tissues that have been damaged by disease or injury. Progressing knowledge about stem cells in the liver would allow a better understanding of the mechanisms of hepatic homeostasis and regeneration. Although a human stem cell-derived cell type equivalent to primary hepatocytes does not yet exist, the promising results obtained with extrahepatic stem cells would open the way to cell-based therapy for liver diseases. Key words: Liver stem cells, adult stem cells, embryonic stem cells, liver development, intra-hepatic stem cells, extra-hepatic stem cells, liver renewal, stem cell niche, ES derived-hepatocytes.
1. Introduction New discoveries in stem cell biology and regenerative medicine have expanded our understanding of liver biology and the pathophysiology of various liver diseases such as hepatitis, cirrhosis, and liver cancer and have created hope for the therapeutic potential of such cells in the treatment of hepatic disorders. P. Maurel (ed.), Hepatocytes, Methods in Molecular Biology 640, DOI 10.1007/978-1-60761-688-7_10, © Springer Science+Business Media, LLC 2010
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At present, liver failure is a catastrophic illness associated with the death of many patients while waiting for transplantation (1). Considering the vigorous regenerative capacity of the liver (2, 3), some forms of acute liver failure (ALF) can be managed with several bridging techniques in the waiting time. Nevertheless, still the lack of livers to use as a whole for orthotopic liver transplantation (OLT) or to isolate hepatocytes to use as a temporal support while its own liver recovers is one of the major drawbacks (4). Therefore, there has been a growing interest in liver stem cells (LSCs) as an alternative to liver treatments. The liver has enormous regenerative potential, explained by the mitotic division of hepatocytes and cholangiocytes after injury. For this reason, for decades, the role of stem or progenitor cells in liver regeneration has been controversial. Liver regeneration can be explained as a three-stage cell replacement process. The first stage is characterized by an ability of mature hepatocytes and cholangiocytes achieved after rapid cell division to repopulate the liver in response to certain types of injuries. These cells are the ones that also contribute to normal cell turnover in the liver. The second stage is characterized by the participation of an intraorgan stem cell compartment. This stem cell compartment is believed to be localized in the canals of Hering, which are the smallest, most proximal branches of the biliary tree or in the intralobular bile ducts. The best proof comes from various human analysis and animal models of extensive hepatic damage, where proliferating cells bud from the canals of Hering and further differentiate toward the biliary and the hepatocytic lineage according to the severity of the disease and the type of mature epithelial cell that is damaged (5–8) (see Fig. 10.1). The third stage is characterized by the participation of a cell source of possible extrahepatic origin, consisting of cells entering from the circulation. The cells are probably of bone marrow origin, although derivation from other sources has not been ruled out. If the cells are from bone marrow origin, it is thought that they enter the circulation through the portal vasculature and establish first next to the ducts in the portal triads when there is marked injury. Thus, the periductular location of these putative liver progenitor cells (LPCs) seems to be of external origin. A source of controversy surrounds the issue of whether plasticity events are in fact occasions of circulating cells fusing with end-organ cells, such as hepatocytes, leading to the appearance of plasticity where is present. The processes of homing circulating cells to the liver, their engraftment and differentiation into functioning liver parenchymal cells, remain unclear. It is however believed in the existence of especial factors such as g-CSF that can mobilize stem cells from the bone marrow (9). The essential role of CXC4 (SDF-1) chemotaxis, as well as the importance of hepatic MMP-9 and HGF expression in recruiting CD34+ stem cells to the liver (10), has also been confirmed.
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Fig. 10.1. Possible roles of intra and extrahepatic stem cells in the repair of hepatic tissue. After tissue injury, hepatocytes act as the first line of defense to replace necrotic cells. When the pool of hepatocytes is exhausted or their capacity is inhibited, stem cells that are intrinsic to the tissue replace necrotic cells. If the pool of endogenous stem cells is exhausted, exogenous circulating stem cells are signaled to replenish the pool and participate in tissue repair. Thus, circulating stem cells may serve as a backup rescue system.
The theory mentioned above was related to the repair process of the liver itself after injury; however, in terms of sources of hepatocytes used in cell-based therapies, there are additional sources, including stem cells from other adult populations such as bone marrow stromal cells, from fetal liver tissue, or from ex vivo differentiation of embryonic stem cells. The isolation, culture, and expansion ex vivo can generate a large quantity of cells for therapeutic use. Differentiation of mouse embryonic stem (ES) cells into mature hepatocytes has now been readily demonstrated by a number of groups (11–13). Despite uncertainty surrounding the mechanism underlying the role of stem cells in liver regeneration, there is a great hope with the use of these cells for liver-based therapies. The demonstrated potential of stem cells in other fields (14–16) has increased the enthusiasm in hepatology, because stem cells can be used for the treatment of inherited and acquired end-stage liver diseases. They can also serve as a source of cells for cell transplantation in acquired liver diseases such as acute failure due to toxic or viral injury. Since they can be expanded in vitro to a desired extent, they can be used to populate liver-assist devices or artificial livers based on bioengineered matrices. Lastly, they can be used as targets for gene therapies in primary liver diseases or diseases where extrahepatic manifestations arise from abnormal gene expression or defective protein production by the liver.
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It is very likely then that efforts to produce large numbers of transplantable hepatocytes from intra- or extrahepatic LSC will eventually prove to be successful. However, their efficient therapeutic application will demand additional scientific advances, but still has a bright future. See also Chapters 8, 9, 11, 12, and 14.
2. Defining a Stem Cell It is difficult to arrive at a universally applicable definition of a stem cell due to the fact that some of the defined properties of a stem cell can be exhibited by the stem cells in some tissues or organisms but not in others. In spite of that, a generally acceptable consensus defines a stem cell as an undifferentiated cell that has capacity to self-renew, for production of progeny in at least two lineages, for long-term tissue repopulation after transplantation, and for serial transplantability. In addition, stem cells exist in a mitotically quiescent form (17) and clonally regenerate all of the different cell types that constitute the tissue in which they exist (18). They can undergo asymmetric cell division, with production of one differentiated (progenitor) daughter and another daughter that is still a stem cell. The offspring of stem cells are referred to as progenitor cells, also named as transit amplifying cells and therefore cannot be serially transplanted, and are classified as early and late. The early progenitor or stem/progenitor cells have multilineage potential and similar characteristics to stem cells. The late progenitor cells have differentiated further and produce progeny in only a single lineage. Although they divide rapidly, they are capable of only a short-term tissue reconstitution and they do not self-renew (18). In order to maintain the pool of stem cells in the adult tissue, some of the cells need to divide without differentiating and others need to undergo asymmetric cell divisions (19). Tissue stem cells are determined, i.e., they lack the biochemical and structural markers of differentiation but are decided to differentiate into a specific cell type. While the size of the stem cell pool remains practically constant in many tissues under steady-state conditions, in some others even under normal circumstances, it responds by proliferation and differentiation to replace senescent cells. The skin epithelium is the typical example. The basal cells send daughter cells to replace senescent cells. They can also expand rapidly in response to tissue damage to restore destroyed tissues in pathological conditions (19). 2.1. Stem Cell Niche
It is believed that once postnatal tissues are formed, intraorgan stem cells can exist only in a restricted yet protective
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microenvironment (stem cell niche), which provides factors that maintain them and excludes factors that induce differentiation (20). This stem cell niche is an especial compartment of not only stem cells but also diverse gatherings of neighboring differentiated cell types (stem/progenitor cells, stromal cells), which secrete and organize a rich milieu of the extracellular matrix, basement membrane, and other factors, whose mysterious interactions modulate the stem/progenitor cell function. Nobody knows yet the precise mechanism occurring in the niche; however, studies of the Drosophila ovarian niche and the germ stem cells contained there have helped us to understand the importance of all the structures contained in the niche. For instance, we know that there are some sort of physical interactions between stem cells and their non-stem cell neighbors contained in the niche that maintain stem cells there and control their relative quiescence or activation. The evidence suggests that non-stem neighboring cells work as the “molecular glue” that anchors stem cell to their niche mediated by adherence and signaling mechanisms through Notch and WNT pathways. This “molecular glue” has been partially defined in some models, whereas in some others such as the liver, it has not been defined yet (21, 22). Additional factors participating in the retention of stem cells within their niche are integrins, which play an important role in mediating cell adhesion to a basal lamina. In fact, it has been demonstrated that stem cells have high levels of integrins. The niche can retain their stem cells by providing a unique milieu of extracellular matrix (ECM) ligands for the integrin receptors on the surface of them (21). In the case of hematopoietic stem cells (HSCs), for example, they express α4β1 and α5β1 integrins, which bind to fibronectin to promote adhesion to the bone marrow stroma. It has been demonstrated that antibodies against these integrins block hematopoiesis in longterm bone marrow cultures (23). In the liver, the same could be applied since extensive studies have identified the integrins and basement membrane components predominantly expressed in human biliary epithelium: α2, α3, α5, α6, and α9, which dimerize with β1, and laminin and type IV collagen (24). However, as for the canals of Hering, these studies have not yet been performed. Another important factor involved in the stem cell niche is the innervation. In fact, nerve niche interactions are not yet clear, though some hypothetical mechanisms have involved the possibility of direct interaction, via cell–cell junctions with the stem cells and/or stromal cells, or the secretion of factors into either the periniche milieu or the autonomic control of vascular supply to these microenvironments. Some of these factors could be stimulatory, but others could be inhibitory of niche activation (25).
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3. Liver Development The definitive endoderm is an epithelial sheet formed at the ventral side of the vertebrate embryo during gastrulation. Invagination of the endoderm at the anterior end of the embryo generates the ventral foregut, which ultimately gives rise to the liver, lung, thyroid, and the ventral pancreas (26). The development of endodermal organs occurs by a coordinated sequence of events. In mice, the liver buds from the foregut endoderm at 7.5–8.5 days post-coitus and is engrafted by hematopoietic progenitors at 9–10 days. The fetal liver is rich in hematopoietic cells and therefore is the site of proliferation and differentiation of liver cell precursors. Proliferation of undifferentiated endodermal cells of the ventral foregut is seen around embryonal day (ED) 8.5; these cells then migrate to the septum transversum, and there they come in contact with mesenchymal cells. The formation of the vertebrate liver is very important in the establishment of competence within the foregut endoderm in order to respond to organ-specific signals. This process is followed by liver specification, hepatic bud creation, growth, and differentiation (27). The specification and development of these areas seems to be controlled by cell-autonomous factors such as transcriptional regulators, as well as by inductive or inhibitory signals from surrounding tissues. Although little is known about the factors that elicit embryonic induction of the liver, extensive research using embryonic tissue explants has provided priceless information on the mechanisms involved in early mouse liver development. Tissue relations and signals from mesoderm are characteristics of endodermal patterning. A combination of positive inductive signals emanating from the cardiac mesoderm, such as fibroblast growth factors (FGFs), FGF1, FGF2, FGF8, and repressive signals from the trunk mesoderm, specifies a group of primitive pluripotent endodermal stem cells in the ventral foregut to adopt a hepatic fate (28). It has been hypothesized, however, that the endoderm must first enter a stage in which competence to respond to FGF signaling is established. This finding was based on the observation that portions of dorsal endoderm, which usually does not originate liver, were induced to express albumin (a liver marker) only when those portions were dissected between gestational days 8.5 and 11.5 and cultured with FGF. This competence was lost however when the dorsal endoderm was isolated at embryonic day (ED)13.5 or further, indicating that factors required for competence are limited to specific stages of embryonic development (29). While FGF1 and FGF2 have been shown to induce the expression of hepatic genes at multiple and distinct stages, FGF8 is thought to play a role in liver outgrowth and cell differentiation
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(28). Recently the role of FGF10 has been demonstrated to be a critical factor for liver growth during embryogenesis by enhancing hepatoblast proliferation via β-catenin activation through FGFR binding (30). FGFs bind to FGF receptors (FGFRs) in a loose manner, among them the FGFR2-IIIb (FGFR2b) isoform, which has been shown to be crucial in the postnatal liver regeneration, based on the findings that adult mice expressing a soluble, dominant negative form of FGFR2b showed markedly reduced hepatocyte proliferation after partial hepatectomy (31). The Wnt/β-catenin signaling pathway has also been implicated in the maintenance, survival, proliferation, and cell fate decisions of progenitor cell populations in several organs, including the liver during embryogenesis (32). It was demonstrated that most of the cells contained in the embryonic liver that displayed the most β-catenin activation pattern were hepatoblasts. It is speculated then that during the hepatogenesis, FGF10 seems to be secreted by the embryonic stellate cells/myofibroblasts, residing around the portal vein. Then, FGF10 is transported to hepatoblasts, which express FGFR2B through the portal vein and the developing sinusoids of the liver. FGF10 then binds to FGFR2B on hepatoblasts and induces the activation of the β-catenin signaling pathway (30). FGF10 signaling from the adjacent mesenchyme regulates differentiation of the foregut epithelial cell toward hepatic or pancreatic cell lineages in zebrafish, suggesting a significant role for FGF10 in the differentiation of liver precursor cells (33). FGF10 has also been implicated in the proliferation or the differentiation of various stem/progenitor cell populations (34, 35). Bone morphogenetic protein (BMP) signaling from the septum transversum mesenchyme coordinately works with FGFs to initiate the induction of hepatic gene expression in the endoderm and to exclude a pancreatic fate. BMP seems to affect the levels of the GATA-4 transcription factor; it is also critical for morphogenetic growth of the hepatic endoderm into a liver bud (36). Furthermore, it has been proposed that the forkhead box A (FOXA) and GATA transcription factors (37, 38) initially facilitate the ventral foregut endodermal cells to go through a stage of competence by opening compacted chromatin structures within liver-specific target genes. Therefore, cells can react to inductive mesodermal signals congregating on a common endodermal domain along the primitive gut tube (37, 39). By ED 9.0–ED 9.5 after the establishment of the competence process, the cells under the influence of all the abovementioned factors start to express α-fetoprotein (AFP) and then albumin. The hepatic-specified cells are now considered to be hepatoblasts and they have an extraordinary proliferation capacity. The septum transverse mesenchyme is also invaded by cords of hepatoblast, which will originate stellate cells, and sinusoidal
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endothelial cells that subsequently will develop into blood vessels (27). At ED 11 hepatoblast keep proliferating and they begin to express, in addition to AFP and albumin, placental alkaline phosphatase, intermediate filament proteins (CK-14, CK-8, and CK18), and γ-glutamyl transpeptidase (GGT); later on, they express α-1-antitrypsin, glutathione-S-transferase (GST)-P, and fetal isoforms of aldolase, lactic dehydrogenase, and pyruvate kinase (M2-PK) (40, 41). Immediately before ED 16, hepatoblasts selectively differentiate under the regulation of an array of liver-enriched transcription factors into either hepatocytes or bile duct epithelial cells (42–44). The Notch signaling is activated in hepatoblasts that undergo differentiation along the bile duct epithelial lineage. The expression of the Notch intracellular domain in hepatoblast inhibited hepatic differentiation by reducing the expression of albumin (45). Notch signaling pathway is antagonized by hepatocyte growth factor, which in combination with oncostatin M promotes hepatocytic differentiation (46). Recently it was proposed that a gradient of activin/TGF-β signaling is required for the differentiation of hepatoblast toward the cholangiocyte lineage. The inhibition of the activin/TGF-β signaling allows hepatoblasts to undergo normal hepatocyte differentiation (47, 48). In terms of in vitro differentiation toward hepatocyte or bile duct lineage, this point is critical to determine the fate of the desired lineage; this time period
Fig. 10.2. Signaling that induces hepatic genes in the endoderm. The figure shows factors and transcription factors influencing differentiation of the endoderm into liver. Also shown are the location of the cardiac mesoderm and prospective septum transversum mesenchyme cells (“mesenchyme”), both of which signal to the endoderm during this period to promote hepatic induction.
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is referred to as the differentiation window during the hepatic development (49). After ED 16, most of the hepatoblast are now committed to either hepatocytic or cholangiocytic lineages, thus they are no longer bipotential, although they continue to proliferate and become unipotent or late progenitor cells. It is worth mentioning that in the embryonic liver some of the LSCs do not differentiate and progressively go out of the proliferative state and after the embryonic day (ED) 16–18, they will just stay in the liver as quiescent potential LSCs (27, 43). By ED 17, intrahepatic bile ducts are formed surrounding the large portal vein branches; by this time the essential lobular arrangement of the liver is completed, but the maturation of the hepatic parenchyma will be completely mature several weeks after birth (50) (see Fig. 10.2).
4. Liver Renewal The liver is both an exocrine and an endocrine gland which performs complex functions and has a phenomenal regenerative capacity. This process enables the recovery of lost mass without endangering the viability of the entire organism (2, 3). Followed by acute injury, stem cells take part in the major role in normal tissue repair and homeostasis in quickly turning over tissues such as the skin or the bone marrow (19). In contrast, liver regeneration after loss of hepatic tissue does not depend on these kinds of cells, but on the proliferation of the existing mature hepatocytes, the parenchymal cells of the organ. In addition, the rest of the hepatic cell types, such as biliary epithelial cells, fenestrated endothelial cells, Kupffer, and Ito cells, proliferate and contribute to regenerate the lost hepatic tissue (2). In the case of liver regeneration after toxic damage, it is noteworthy mentioning that another important phenomenon aside from the hepatocyte proliferation is the capacity of the newly formed hepatocytes to adapt themselves to the distinctive threedimensional architecture of the liver lobules built around portal triads and central veins. The classical lobule is roughly hexagonal in shape, with groups of hepatocytes arranged in rows that radiate out from the central vein, and defined by loose connective tissue in which the portal canals are found. The portal triods instead or the portal canals, which is in charge of the blood transport to the liver from the intestine, the hepatic artery with highly oxygenated blood, and the bile ducts, which is in charge to carry away the bile. In order to guarantee liver function, the lobule architecture has to assure a generous blood flow from the portal vein
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through the sinusoids to the central vein within each liver lobule. The rows of hepatocytes in the lobule are one or two cell wide and are surrounded by sinusoidal capillaries. This arrangement ensures that each hepatocyte is in very close contact with blood flowing through the sinusoids, i.e., bathed in blood. Thus, liver regeneration is a complex but precisely defined process (2, 3). The hepatic acinus has three zones. Zone 1, which is high in oxygen and in which hepatocytes are the first to receive blood; Zone 2, which is lower in oxygen and in which hepatocytes are the second cells to receive blood; and Zone 3, which is the lowest in oxygen and in which hepatocytes are the last to receive blood from a branch of the hepatic artery. Thus, the cells with the highest metabolic potential are found in Zone 1 and those with the least are found in Zone 3. Importantly, the cells in Zone 3 are the most susceptible to ischemic conditions due to the already low level of oxygen that reaches them through the blood. The normal liver has been estimated to be replaced by normal tissue approximately once a year or more (51), since turnover rate of normal liver cells was calculated to be 1 in 20,000–40,000 cells at any given time (52). Conversely, this slow normal renewal rate differs from the rapid proliferative response to loss of hepatic mass. The liver’s self-healing ability was documented since the Greek mythology and exploited by Zeus to punish Prometheus, the Titan God. Zeus, the king of the Gods, ordered Prometheus to be chained to a rock in the Caucasian mountains as punishment for stealing the holy fire from Olympia – the home of the Gods – and sharing it with mankind. Zeus sent an eagle to the rock to peck at Prometheus’s liver. By night, as the eagle slept, Prometheus’s liver grew back so that it was a fresh tasty meal again for the eagle the next morning. The modern recognition of the liver’s self-healing ability is exemplified by experimental partial hepatectomy (PH) (3). The normal adult liver parenchyma is made up of mitotically quiescent hepatocytes and cholangiocytes, both of them originating from a common endodermal foregut precursor cell. Hepatocytes as fully differentiated cells normally turn over very slowly but have a remarkable ability to re-enter the cell cycle in response to mitotic stimuli. Following two-thirds partial hepatectomy (via removal of the left and median hepatic lobes), nearly all hepatocytes in the adult liver undergo cell division, starting with periportal hepatocytes, as well as those immediately adjacent to the central vein. This is followed by a second round of replication in which about half of the hepatocytes divide again to fully restore the liver of its original mass within a few days with little or almost no evidence of contribution of a liver stem cell (53, 54). This response to surgical injury is termed “regeneration,” although the term is not precisely accurate since the response involves a compensatory hyperplasia within remaining lobules,
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not a recreation of the original lobular morphology. Replication of differentiated hepatocytes and biliary epithelial cells accounts for this regeneration. Since hepatocytes are supposed to be terminally differentiated cells, it is believed that they can undergo only one or two rounds of cell proliferation. However, it was demonstrated that this is no longer true, since hepatocytes were able to regenerate the liver after 12 sequential hepatectomies, demonstrating the outstanding proliferative capacity of hepatocytes (55). Additional experiments performed on a mouse model of tyrosinemia (FAH−/− mice) demonstrated that when hepatocytes from a healthy donor were injected into FAH−/− mice, these were capable of re-establishing the liver mass, rescuing the mice. When hepatocytes isolated from this first generation of rescued mice were serially transplanted, six generations of mice were rescued, corresponding to approximately a minimal number of 69 cell doublings (56). This elegant experiment conclusively instituted the ability of mature hepatocytes to repopulate an entire organ and self-renewal. The previous findings imply that hepatocytes could essentially act as their own stem cell and regenerate the liver. Nonetheless, there is evidence that the replicative activity of hepatocytes decreases in advance cirrhosis in humans and in chronic liver injury in mice, reaching a state of “replicative senescence,” probably due to telomere shortening (57). However, the existence of a common progenitor (hepatoblast) with the ability to give rise to both bile duct epithelial cells and differentiate hepatocytes during embryonic development, and the ability to be responsible for some forms of liver regeneration later in life suggests the existence of two basic types of liver regeneration: one dependent on mature hepatocytes and one dependent on the progenitor (stem cells) which may be used when parenchymal hepatocytes are severely damaged and unable to efficiently regenerate the liver (8, 58). Nevertheless, the proliferation of the different cellular populations in the liver depends mainly on the insult that triggers the process. Mature hepatocytes for example respond immediately after chemical injury, such as in the case of carbon tetrachloride. This agent causes hepatocyte necrosis primarily in the periportal areas of the liver lobules. Because hepatocytes in the pericentral areas have much higher expression levels of cytochrome P450 2E1 that is involved in metabolic activation of CCl4 , centrilobular necrosis occurs within 36–48 h after administration, and hepatocytes are in charge of restoring this damage in a 7-day process (59). Bile duct structures are in some cases stimulated to proliferate, like those seen after bile duct ligation or bile duct necrosis induced by α-naphthyl isothiocyanate (ANIT) or 4,4 -diaminodiphenylmethane (DDPM) (60). On the other hand, when hepatocyte proliferation is inhibited such as by viral infection or by chemicals, regeneration proceeds from an alternate
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cell source (oval cells), which responds to the injury by proliferation and differentiation into hepatocytes (8). Finally, the presence of a periductular putative liver progenitor cell (LPC) has been observed in the liver. This is believed to be from a possible extrahepatic origin, the bone marrow (61). The details of each of these putative liver stem cells will be discussed in detail in the next section.
5. Liver Stem Cells 5.1. Definition
Fifty years ago, Wilson and coworkers (62) suggested the existence of hepatic stem cells in the adult liver. Nowadays researchers are doing a great effort to characterize, localize, and isolate these cells, although it has been difficult due to the lack of specific cell surface markers. According to the general definition of a stem cell, it is important first to define what liver stem cells (LSCs) are. Hence, an LSC would be one that fulfills the characteristics of being undifferentiated, with a self-renewing ability as well as the ability to produce multilineage (or at least bilineage), and is able to repopulate the liver. Those LSCs that do not fulfill all the characteristics are considered as potential LSCs. The origin, nomenclature, and function of these cells have been a long-standing area of study and debate, since these liver-related stem cell populations will fluctuate according to the liver stage of development and the diverse range of injured circumstances.
5.2. Fetal Liver
The early fetal liver at around ED 12–ED 16 contains two populations of hepatic cells: the fetal hepatic stem cells and the hepatic progenitor cells (hepatoblast). Hepatoblasts are bipotent cells derived from endodermal cells; they exhibit many properties expected for hepatic stem cells and they are also known as fetal liver stem/progenitor cells (FLSPCs) (58). During embryonic liver development of rodents, ED 14 in mice and ED 15 in rats, the hepatoblasts are located near the vascular spaces, which are going to be the site for portal spaces in later development. These hepatoblasts express dual markers of the hepatocyte and biliary lineages, and they are capable of differentiation into either of the two epithelial cell populations of the liver, hepatocytes and biliary epithelial cells. The variety of markers expressed by them has been useful for their isolation from the fetal liver. However, during the developmental process, the architecture of the mature liver becomes apparent with the differentiation of the FLSPCs into hepatocytes and sinusoid formation, and subsequently FLSPCs will express markers only of the committed lineage.
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In fact, there are several markers used for the identification, proper development, and differentiation of FLSPCs such as α-fetoprotein (AFP), (37, 63) and albumin, a marker of both hepatoblast and hepatocytes (46). C/EBPα starts to be expressed in endodermal cells at 9.5 days in the liver primordium and continues to be expressed in FLSPCs and hepatocytes throughout development (64). Cytokeratins (CK)-14 (65), CK-8 (66), and CK-18 (67) are expressed by the embryonic liver diverticulum. Dlk also known as Pref-1 is highly expressed in the ED 10.5 liver bud and is a useful marker to enrich highly proliferative FLSPCs from fetal liver (68). E-cadherin was used to isolate fetal liver progenitor cells from ED 12.5 mouse livers with high yield and purity (69). Forkhead box (Fox) m1b (Foxm1b) is critical for hepatoblast precursor cells to differentiate toward biliary epithelial cell lineage (70). GCTM-5 is a monoclonal antibody originally derived after immunization of mice with a membrane preparation from a testicular seminoma. Stamp et al. (71) recently discovered this marker to be expressed exclusively in the fetal liver of 7-week human embryos. This marker was expressed in a subpopulation of cells within the biliary epithelium (71) in the normal and diseased adult and pediatric human liver. γ-Glutamyl transpeptidase (GGT), a major enzyme of glutathione (GSH) homeostasis, is often used as a biliary marker to follow the differentiation of hepatic precursor cells (72). Hepatocyte nuclear factor-4alpha (HNF4-α), which regulates the expression of many genes preferentially in the liver (73), plays a crucial role in early embryonic development (74). Id3, a negative regulator of helix–loop–helix transcription factors, was demonstrated by Nakayam et al. to be an important regulator of hepatoblast proliferation in the developing chick liver. They demonstrated this marker to be expressed in hepatoblast at early developmental stages, but not in hepatoblasts at later stages (75). Liv2 is a hepatoblast marker (76). Prox1, a transcription factor expressed in early embryonic hepatoblasts, has been shown to be very important during the liver development. Studies using a Prox1 knockout mice demonstrated that these mice died during early embryogenesis stages, while displaying a very rudimentary liver (77). Prox1 is still expressed in the adult liver but only by hepatocytes. In addition it is considered to be one of the earliest markers of liver development together with albumin and AFP (78, 79). SEK-1 plays a crucial role in hepatoblast proliferation. Studies using mice defective in SEK-1 demonstrated embryonic lethality after embryonic day 12.5 and this was associated with abnormal liver development. The authors also demonstrated in this study that SEK1 is required for phosphorylation and activation of c-jun during the organogenesis of the liver (80). SMAD, a mediator of BMP signaling, is preferentially expressed in hepatoblast undergoing bile duct morphogenesis in the fetal liver (81). Sca-1 is a general stem cell marker that is also expressed on murine FLSPC (82).
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New cell surface markers were recently demonstrated to be expressed by murine fetal hepatic stem cells Punc E11 (Nope) and Cd24a (83). Cd24a was shown to be expressed on the surface of FLSPC but not on mature hepatocytes. Whereas Nope was expressed only in FLSPC and was not expressed by hematopoietic stem cells isolated from the adult bone marrow. Observations of the rat fetal liver by ED 14 showed the presence of three distinct populations: committed immature hepatocytes, expressing AFP and albumin, a second population expressing biliary cell markers such as cytokeratins, and a third population of cell expressing both hepatic and biliary markers. This latter small population of bipotent cells, after transplantation, engraft, proliferate, differentiate into hepatocytes and bile duct cells, and stably repopulate normal adult liver (84–86). After ED 16 the gene expression profile in the liver is remarkably evident, with a more differentiated phenotype and a decrease in the number of bipotent cells (85). This bipotent population is thought of as the fetal source of hepatic progenitor cells. The bipotential capacity of these cells for liver cell-based therapy has been widely tested in different liver-repopulating models since isolation based on a combination of different markers has been possible despite the controversy regarding this issue. The potential will vary accordingly to the liver stage in which the cells are isolated, since cells isolated in late embryological stages will lose the bipotent capacity, being able to differentiate along only one lineage. During development, the fetal liver is the main place of hematopoiesis (87), where hematopoietic cells are believed to liberate signals that direct the growth and differentiation of the liver. As the time passes, the hematopoiesis is reallocated in the bone marrow and not any more in the liver. However, during this process we may ask if any of the transient hematopoietic stem cells stay in the liver to form the hepatic stem cell compartment. This speculation led investigators to believe that if this was true, then the hepatic progenitor cells could share some cell surface markers associated with hematopoietic stem cells such as CD34 (88), CD90, Thy-1(89). Many surface markers expressed on FLSPC have been reported to be expressed by progenitor cells also in the adult liver (90). In the developing fetal liver, there is evidence of the existence of a Thy-1+ population (89, 91); these cells are believed to be located mainly in the portal tracts and express several lineage markers, including co-expression of biliary and hepatocellular proteins (91). However, not only a Thy-1+ population but also a Thy-1− population was found in the fetal liver (92). A comparison of the properties of these two populations was done in terms of tissue reconstitution, which is one of the characteristic features of stem cells. After isolation and separation of + and − population of Thy-1 cells from ED 14 fetal rat liver, it was demonstrated
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that Thy-1− cells were able to repopulate the normal host liver, whereas Thy-1+ were not. Thy-1+ cells however repopulated the liver of a retrorsine-treated rat. These observations suggested that Thy-1+ fetal liver cells at ED 14 represent a population of fetal hepatic progenitor cells that can proliferate and repopulate the liver only after extensive liver injury, whereas Thy-1− fetal liver cells are stem/progenitor cells that exhibit greater proliferation potential and can repopulate the normal adult liver. New contributions to the field of stem cells are being developed year by year, and in the future it will be easier to identify what best define a liver stem cell through a combination of several surface markers. 5.3. Adult Liver
5.3.1. Intrahepatic Stem Cells
While hepatocytes can be considered conceptually as unipotent stem cells, the presence of true stem or progenitor cells within adult livers has been largely debated. The restorative reaction of the liver to diverse injuries entails proliferation of cells at different levels in the liver lineage, which consists of stem cells, progenitor cells (transit-amplifying cells), and mature cells. Within the liver, stem cells are thought to reside in a niche composed of cells, extracellular matrix, and soluble factors released by the niche cells that help to maintain the characteristics of the stem cells. Thus, it is believed that the adult liver contains potential LSCs that are activated when the regenerative capacity of mature hepatocytes is compromised. The offspring of these potential LSCs are the liver stem progenitor cells (LSPCs) or oval cells (OCs). Stem cells in the liver are proposed to be from two origins: endogenous or intrahepatic stem cells and exogenous or extrahepatic stem cells (see Fig. 10.1). Included in the intrahepatic stem cell compartment are the LSPCs which are greater in number but with a short-term proliferation capacity. LSPCs are thought to be localized within the canals of Hering (93), interlobular bile ducts (94), or in the periductular/intraportal zone of the liver (60). These cells are called into action when hepatocytes are insufficient or unable to respond (58, 93, 95, 96). Included in the extrahepatic stem cell compartment are cells derived from bone marrow and peripheral blood cells; these cells are usually few but with long-term proliferation capacity. 1. Oval cells. During embryonic development, hepatoblast gives rise to the primitive intrahepatic bile ducts, structures that connect parenchymal hepatocytes with the larger segments of the biliary system. These primitive intrahepatic bile ducts correspond to the canals of Hering and terminal bile ductules of adult livers, which may constitute the niche for intrahepatic stem cells (50). Based on this, oval cells are thought to have originated from the cells of the canals of Hering in the adult rat liver; thus they may express AFP and
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some other markers present in both adult and fetal liver cells. However, the extent to which these markers are expressed in a population of proliferating oval cells depends on the agent that elicited oval cell proliferation. Oval cells (OCs) are thought to represent a heterogeneous population of transit-amplifying progenitor cells activated to proliferate in several models of hepatic injury when the regenerative capacity of hepatocytes is inhibited. The term oval cell was first assigned by Farber et al. (8), who observed a population of nonparenchymal cells appearing in the rat liver after treatment with various carcinogenic agents and described them as small oval cells with scanty lightly basophilic cytoplasm and pale blue-staining nuclei. Oval cells phenotypically resemble fetal hepatoblast since they behave like bipotential progenitors capable of differentiation into mature hepatocytes and biliary epithelial cells (58). Hepatic oval cells are a heterogeneous population of proliferating cells, with cells having a different capacity and stage of differentiation. Therefore, oval cells express markers associated with immature liver cells, such as a-fetoprotein; mature hepatocytes, such as albumin and γ-glutamyl transferase (GGT); and biliary epithelium, such as cytokeratin 7, 19, and oval cell 6 (OV-6), OC2 (anti-myeloperoxidase) (97). In addition, oval cells share some phenotypic characteristics with hematopoietic progenitor cells since they express the hematopoietic stem cell factor and its receptor c-kit tyrosine kinase (c-kit) (98), and the related proteins flt-3 and flt3 receptor (99). Oval cells express also CD34 (100) and a marker of early hematopoietic progenitor cells Thy-1 (101). In a mouse model of liver injury using 3,5-diethoxycarbonyl1,4-dihydrocollidine (DDC), it was shown that proliferating oval cells co-express A6 (102) and the specific marker for hematopoietic stem cells Sca-1, as well as the CD34 and CD45 surface proteins (90). The leukemia inhibitory factor (LIF) and its receptor are also highly expressed in hepatic oval cells (103). The expression of these markers suggested their stem cell-like properties. Some of these markers are shared by biliary epithelial cells (GGT, CK19, and CD34). Oval cells have been demonstrated to express the adenosine triphosphate-binding cassette transporter ABCG2/ BCRP1 (ABCG2) also, a marker for the bone marrow side population (104). The localization of these cells still remains controversial; however, they have been identified in the periductular/ intraportal zone. This and the fact that oval cells express some hematopoietic stem cell genes, including those found in the bone marrow side population, initiated the speculation of the bone marrow origin of oval cells either directly or by transdifferentiation.
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Regarding this speculation, several researchers have been working continuously in an effort to clarify this possibility. In 1999 Petersen et al. (95) used different approaches to demonstrate that bone marrow cells contribute to liver cells. Bone marrow from a male rat was transplanted into lethally irradiated female animals, followed by treatment with 2-acetylaminofluorene (2-AAF) and CCl4 , to simultaneously induce hepatic necrosis and impairment of endogenous hepatocyte proliferation. The appearance of BM-derived oval cells in the liver of these animals was observed. The same group (105) proved the same findings with a different model of liver damage and oval cell activation. Using a model F344 dipeptidyl peptidase IV-deficient [DPPIV(-)] rats treated with 2-AAF and subjected to 70% partial hepatectomy (PHx), followed by male F344 [DPPIV(+)] bone marrow transplantation, the authors concluded that under certain physiologic conditions, it is possible that a portion of hepatic stem cells arise from the bone marrow and can differentiate into hepatocytes. In addition, X/Y-chromosome analysis revealed that fusion was not contributing to differentiation of donor-derived oval cells (105). On the other hand, Wang and coworkers demonstrated that mouse liver oval cells are not originated in the bone marrow but in the liver itself by using a fumarylacetoacetate hydrolase (Fah) mice model (106). Another group reached a similar conclusion by using DPPIV− -deficient F344 rats. The authors substituted the BM of lethally irradiated female DPPIV− -deficient F344 rats with BM cells from syngeneic normal male F344 rats. Then the recipients were subjected to different models of activation and expansion of oval cells, and they demonstrated that oval cells in the injured liver do not arise through transdifferentiation from BM cells but from the endogenous liver progenitors (107). Based on the ambiguity of the existing data, the existence of hematopoietic markers in the normal adult liver and after hepatic injury with oval cell proliferation could be interpreted by two possibilities. The first possibility is that a small number of hematopoietic stem cells from the fetal livers remain in the adult liver. If this were the case, then hematopoietic stem cells may be distinct from oval cells, but a component of the oval cell compartment; therefore these cells do not acquire markers of the hepatocyte lineage but they share general stem cell markers with the origin of oval cells. The second possibility is that the hematopoietic cells contained in the adult liver may be pluripotent stem cells, working as the counterpart of embryonic stem cells, able to produce multiple lineages, including the hepatic cells. If this were the case, hematopoietic stem cells in the liver,
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thought to be located in the periductular spaces, would differentiate by the same stimuli that cause oval cell response to differentiate progressively, first into oval cells and finally into hepatocytes (60). Despite extensive studies, the hematopoietic versus hepatic origin of liver progenitor oval cells remains controversial. It is clear, however, that regardless of the origin, oval cells definitely require certain physiologic conditions and the hepatic niche to proliferate. Oval cell proliferation can be induced in a number of ways, which includes administration of a choline-deficient diet supplemented with ethionine (62, 108); treatment with other DNA-alkylating agents such as 1,4-bis[N,N’-di(ethylene)-phosphamide]piperazine (Dipin) (109); feeding 3,5-diethoxycarbonyl-1,4-dihydrocollidine (DDC) (110); phenobarbital/cocaine-induced liver injury (111); administration of D-galactosamine (112), or treatment with 2-acetylaminofluorene, to block adult hepatocyte proliferation; and then either partial hepatectomy or treatment with carbon tetrachloride to induce hepatocyte loss and a proliferation signal (95). In these settings, the failure of adult hepatocytes to respond to growth signals results in activation and rapid proliferation of oval cells (113), which initially appear near bile ductules and later migrate into the hepatic parenchyma. The use of three different models of oval cell activation in rats, 2acetylaminofluorene treatment in combination with partial hepatectomy (2-AAF/PH), retrorsine treatment followed by partial hepatectomy (Rs/PH), and D-galactosamine (D-gal)-induced liver injury, identified CD133, claudin-7, cadherin 22, mucin-1, ros-1, and Gabrp as new surface markers (114). On the other hand, in murine adult livers, 3,5-diethoxycarbonyl-1,4-dihydrocollidine (DDC) identified a population of CD133-expressing oval cells with the gene expression profile and function of primitive, bipotent liver stem cells (115). These new markers give us a big clue for the isolation of adult progenitor cells, though further research is needed using diverse species in order to confirm the standardization of these markers. Although the characterization and comparison of the oval cell reaction has been tested in several commonly used protocols for stem cell-mediated liver regeneration, it has been demonstrated that the reactions observed among different species vary in several aspects (116). However, the reasons for these differences are unknown. It could reflect differences in the microenvironment or, alternatively, inherent variations in the endogenous hepatic stem cell compartment. This suggests that extrapolation of knowledge between mammalian species must be reconsidered and that
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further studies are needed for reliable and reproducible experimental models. Nevertheless, the potential of hepatic stem/progenitor cells for use in a cell therapy basis brings great promise for the future treatment of human liver diseases. 2. Small hepatocytes. When laboratory animals are exposed to the pyrrolizidine alkaloid retrorsine, which inhibits adult hepatocytes from expanding following a proliferation signal, and undergo partial hepatectomy, liver regeneration cannot proceed normally from adult differentiated hepatocytes but is initiated by a new type of cell the small hepatocyte-like progenitor cells (SHPCs) (117–119). The activation, proliferation, and complete regeneration of normal liver structure from small hepatocyte-like progenitor cells have not been recognized in other models of liver injury characterized by impaired hepatocyte replication. Likewise, their precise origin and their defined tissue niche remain controversial. Some investigators have suggested that SHPCs may represent an intermediate or a transitional cell type between oval cells and mature hepatocytes rather than a distinct progenitor cell population (120, 121). However, the possibility of different cellular origin of SHPCs cannot be excluded. There is evidence suggesting that SHPCs may represent a distinct immature progenitor cell population (117, 118, 122). Others suggest that SHPCs represent a population of retrorsine-resistant mature hepatocytes (117, 119). While some others have proposed that SHPCs simply arise from a subpopulation of hepatocytes that lack the necessary CYP (cytochrome P450) enzymes required to metabolize the vinca alkaloid retrorsine and hence are protected from the inhibitory effects of this reagent (118–120). SHPCs have characteristics of not only mature adult hepatocytes but also fetal hepatoblasts and OC. They most closely resemble fully differentiated (but small) hepatocytes morphologically; although they express albumin and transferrin, generate bile canaliculi, and store glycogen, they also express the oval and fetal liver cell markers OC.2, OC.5, and AFP (117), and do not express cytochrome P450 (CYP) genes. During liver repopulation, SHPCs tend to form nodules with high proliferative capacity, expressing large amounts of Ki-67 and MCM-2 (119, 120). These cells also have significant capacity to proliferate in vitro, and following transplantation (123), they can repopulate the liver almost as well as freshly isolated primary hepatocytes (see Fig. 10.1). 5.3.2. Extrahepatic Stem Cells
1. Bone marrow and hematopoietic stem cells. The bone marrow (BM) compartment is largely composed of a main stem cell population, hematopoietic stem cells (HSCs), which give
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rise to all mature blood lineages and the mesenchymal stem cell (MSC), which forms stromal tissue. HSCs in the BM, functionally defined by their ability to reconstitute the BM of a myeloablated host, are contained in a population expressing CD34 (CD34+ ). In addition, HSCs express CD117 (c-kit), the receptor for stem cell factor (SCF) produced by marrow fibroblast and endothelial cells. Currently it has been suggested that bone marrow cells possess a broad differentiation potential (plasticity), being able to differentiate into mature cells of various organs (124, 125). While some groups have attributed this apparent plasticity to transdifferentiation (61, 126), some others, however, have suggested that cell fusion could explain these results (127–130). Suggestive evidence that hematopoietic stem cells may give rise to liver cells has caused considerable interest in the field of liver diseases, where new strategies to restore hepatocyte number are required. Therefore, many scientists have been trying to define the subpopulations of BM cells capable of generating liver cells, as well as the conversion mechanisms of these cells. So far, two theories have been proposed (transdifferentiation, the adoption of a different phenotype by a cell apparently committed to a tissuespecific cell type, and fusion), although it is still controversial and not well defined yet (see Fig. 10.1). 2. Stem cell plasticity. Cell fusion or transdifferentiation? The plasticity potential of stem cells has been heavily debated. Yet, experimental research has helped to demonstrate the flexibility of this process. Therefore, stem cells can be instructed by factors of the host’s microenvironment to adopt the desired fate. They can transdifferentiate, i.e., genetic reprogramming of a differentiated cell under induction of microenvironmental signaling. Alternatively, they can fuse with the recipient’s cells, thus leading to cytoplasmic mixing and reprogramming of cell fate. Although it is possible that there might be other pathways to plasticity, these have been so far well documented. The conversion of cells derived from bone marrow into hepatic cells has been suggested in vivo (95, 131–133) and in vitro (134). Although cell fusion has been proposed to be an alternative mechanism responsible for cell fate changes (127, 128), many other reports have demonstrated conversion without fusion (135, 136). In the case of humans, it has been possible to suggest the BM origin of hepatocytes by taking advantages of the very useful methods to track hepatocytes that have been developed in the last decades. Such is the case of male recipients of female orthotopic liver transplants and females who had received bone marrow transplantation (BMT) from male donors (137, 138). On the other hand, by the analysis of biopsy specimens from the liver,
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the gastrointestinal tract, and skin from female patients who had undergone transplantation of HSCs from peripheral blood or BM from male donors, engraftment of donor-derived stem cells was observed, accounting for up to 7% of the cells in histologic sections of the biopsy specimens. These results demonstrated once again the differentiation potential (plasticity) of circulating stem cells into different types of cells, including their potential to differentiate into hepatocytes (135). The conversion of cells derived from bone marrow into hepatic cells has been suggested in animals also. The transplantation of bone marrow cells CD34+ , lin− into myeloablated mice, was able to give rise to up to 2.2% of the total hepatocyte number in the recipient liver (132). In the case of animal models such as fumarylacetoacetate hydrolase (FAH)-deficient mouse, a model of fatal hereditary tyrosinemia type I, the demonstration of hepatocyte generation from bone marrow cells was also possible (131). FAH−/− mice suffer from severe liver damage as a consequence of accumulation of the hepatotoxic metabolites, fumarylacetoacetate and its precursor maleylacetoacetate. Due to the deterioration of hepatocytes, FAH-deficient mice cannot survive unless they are treated with the drug 2-(2nitro-4-trifluoromethylbenzyol)-1,3-cyclohexanedione (NTBC), which prevents production of the toxic metabolites. Due to permanent deterioration of hepatocytes, the FAH−/− mice represent an animal model with an extremely high selection pressure for wild-type (i.e., FAH+/− or FAH+/+) hepatocytes. A purified HSC population (c-kit+ Thy1low , lin− , and Sca-1+ ) was transplanted into lethally irradiated FAH−/− mice followed by liver injury by removing the drug NTBC, which is a pharmacological inhibitor of tyrosine catabolism upstream of FAH. As a result, a liver repopulation by HSC was observed, mainly due to the growth advantage that transplanted cells had over endogenous hepatocytes. These data demonstrated the feasibility of correcting a hepatic disease by bone marrow-derived liver-repopulating cells. The mechanism underlying the apparent transdifferentiation of BM-derived cells into liver phenotype in the FAH−/− mouse was years later demonstrated to be caused by cell fusion between the bone marrow-derived transplanted cells and host liver cells. This mechanism appears to be the principal source in liver repopulation models in which there is extensive liver injury and strong selection for survival of transplanted cells (129, 130). One important remaining question is: which cells fuse with the host liver cells? There is no evidence that it is the stem cells themselves. Instead, it seems more likely that differentiated progenies of the stem cells, such as blood cells known as macrophages, are responsible, because a contribution to the liver is seen only after the donor stem cells have populated the animals’ blood system (129, 130). This issue was clarified further and it was demonstrated that
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myeloid cells and myeloid progenitor cells were the major source of hepatocyte fusion partners (139, 140). On the other hand, it was proposed that HSCs could convert into functional hepatocytes without fusion (136, 141). In spite of the efforts spent until now, it is still questionable whether bone marrow-derived hepatocytes arise from stem cell “plasticity,” “fusion,” “transdifferentiation,” or another mechanism. Nevertheless, based on the available data, it seems that more than one mechanism is at play, and the liver injury itself is an important ingredient of the response. With all the research performed in the last decades, our understanding of hepatic stem cells has had an outstanding progress, although we cannot deny that there are still many unanswered questions. Nonetheless, it has been clarified now that extrahepatic cell reservoirs are capable of contributing to intrahepatic regeneration. Unfortunately, the essential mechanism of this response (i.e., “plasticity,” “transdifferentiation,” or “fusion”) remains to be fully elucidated. This uncertainty could be elucidated by the great variety of liver injury models used in the different studies. The exploitation possibility of this extrahepatic stem cell reservoir to be translated into cell-based therapies remains to be seen.
6. In vitro Hepatic Differentiation Potential of Stem Cell 6.1. Adult Stem cells
Evidence has been accumulated to indicate that certain compartments of bone marrow cells are capable of differentiating into hepatocytes in vitro. All studies performed until now have tried to demonstrate and clarify the confounding issue of cell fusion or transdifferentiation.
6.1.1. Bone Marrow and Hematopoietic Stem Cells
A high level of attention has been paid to the fusion phenomenon in order to explain the plasticity of adult stem cells; however some studies performed in vitro using bone marrow-derived cells have clearly confirmed that such phenomenon does not occur. A bone marrow-derived subpopulation enriched for HSCs co-cultured with damaged liver tissue was prevented from direct cell–cell contact by the use of transwell plates (which provide the barrier). The minced damaged liver tissue secreted substances into the culture medium that stimulated the hepatocyte differentiation from the marrow-derived cells. A truly direct differentiation potential of bone marrow cells into hepatocytes was demonstrated ruling out the possibility of cell fusion by genotypic analysis. After just 48 h, albumin and CK18 became detectable in 2–3% of the
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stem cells. Several liver transcription factors and cytoplasmic proteins expressed during the differentiation of liver (αFP, GATA-4, HNF4, HNF3β, HNF1α, and C/EBPα) and in mature hepatocytes (CK18, albumin, fibrinogen, transferrin) were analyzed in the hematopoietic stem cell-derived cell population. The expression of all markers increased over time, with the exception of αFP, which initially increased and later decreased, indicating possible maturation. The functionality of these cells was proven by transplantation of the hepatocytes into recipient mice with liver failure induced by CCl4 (141). Using a similar approach, a special population of β2microglobulin Thy1+ cells from bone marrow was co-cultured using a transwell culture system with hepatocytes isolated from cholestatic rat livers (induced by ligation of the common bile duct) in the presence of 5% “cholestatic” serum on Matrigel. The β2-microglobulin Thy1+ cells differentiated to a cell type that metabolized ammonia into urea and expressed albumin, as well as some transcription factors (142). On the other hand, the adult stem cell plasticity was also demonstrated when culture of mouse bone marrow cells in the presence and absence of several growth factors showed hepatocyte phenotype. Fibroblast growth factor (bFGF) induced albuminproducing cells as well as the expression of hepatocyte markers and transcription factors such as cytokeratin 18 and albumin HNF1a, HNF3a, HNF3b, HNF4a, GATA-4, and GATA6. Although the in vivo function of these cells was not proven, the plasticity process of bone marrow stem cells in this case was demonstrated to be through transdifferentiation (143). In a similar way, isolated CD34+ bone marrow cells were cultured on collagen-coated plates. After exposure to HGF, EGF, and insulin, these cells showed expression of albumin and CK19 after 28 days, whereas CD34− cells did not show liver-specific gene expression. The results demonstrated once again the hepatic differentiation potential of adult human bone marrow stem cells (144). 6.1.2. Peripheral Blood
Monocytes from peripheral blood have also been able to show hepatocyte differentiation potential (145, 146). Zhao and colleagues used a subset of human peripheral blood monocytes that display monocytic and hematopoietic stem cell markers including CD14, CD34, and CD45 to differentiate into liver cells by hepatocyte growth factor (145). On the other hand, Ruhnke and colleagues (146) treated monocytes with macrophage colony-stimulating factor and interleukin-3 for 6 days, followed by incubation with hepatocyte differentiation media containing FGF4. These programmable cells of monocytic origin were capable of differentiating into neohepatocytes, which closely resemble primary human hepatocytes with respect
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to morphology, expression of hepatocyte markers, and specific metabolic functions. After transplantation, neohepatocytes were able to integrate well into the liver tissue and showed a morphology and albumin expression similar to that of primary human hepatocytes. 6.1.3. Mesenchymal Cells
Mesenchymal stem cells (MSCs), widely studied over the past decade, are thought to be multipotent cells present in adult marrow and other tissues that can replicate as undifferentiated cells and that have the potential to differentiate into lineages of mesenchymal tissues, including bone, cartilage, fat, tendon, muscle, and marrow stroma (147, 148). However, the endodermal differentiation potential of bone marrow or adipose tissue MSCs has just recently been demonstrated. Mesenchymal stem cells (MSCs) were isolated from human bone marrow and umbilical cord blood. These cells were serum deprived for 2 days in the presence of EGF and bFGF prior to induction with HGF, bFGF, and nicotinamide for 7 days followed by subsequent exposure to oncostatin M, dexamethasone, and ITS (mixture of insulin, transferrin and selenium). This procedure resulted in a cell population expressing albumin, α-FP, glucose 6-phosphatase, tyrosine aminotransferase, CK18, tryptophan 2,3-dioxygenase, and CYP2B6. In addition, cells displayed albumin production, urea secretion, and uptake of low-density lipoprotein (149). Lately, using a similar approach this potential was also confirmed (150). Isolated MSCs were differentiated in the presence of human hepatocyte growth medium and transplanted in immunodeficient Pfp/Rag2 mice. The resultant cells demonstrated in vitro and in vivo morphological and functional characteristics of hepatocytes. Not only MSCs from human bone marrow but also MSCs from adipose tissue have the potential to differentiate into hepatocytes in vitro and in vivo (151). Mesenchymal stem cells obtained from adipose tissue (AT-MSCs) were incubated with several growth factors [hepatocyte growth factor (HGF), fibroblast growth factor (FGF1), FGF4]. An especial sub-fraction (CD105+ ) of these mesenchymal cells exhibited high hepatic differentiation ability in an adherent monoculture condition. The cells revealed several liver-specific markers and functions, such as albumin production, low-density lipoprotein uptake, and ammonia detoxification, and they had the ability to incorporate into the liver parenchyma (151). The ability to isolate, expand the culture, and direct the differentiation of hMSCs in vitro into particular lineages provides the opportunity to study events associated with hepatocyte commitment and differentiation. It could be used as new therapeutic approaches for the restoration of damaged or diseased liver.
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6.1.4. Multipotent Adult Progenitor Cells (MAPCs)
Bone marrow-derived stem cells with extensive in vitro expansion ability, termed multipotent adult progenitor cells (MAPCs), have been isolated from mice, rats, and humans (152). These cells have the capacity to differentiate into cells representing all three germinal layers: ectoderm, mesoderm, and endoderm. By culturing in FGF4 and HGF, MAPCs appear to differentiate into hepatocyte-like cells, which express CK19, AFP, CK18, HepPar-1, and CD26, and produce albumin, urea, and glycogen (134). Thus, MAPCs, like ES-derived cells, may have potential to develop into a wide spectrum of transplantable cells that could be used to treat a variety of degenerative and inherited diseases. Unlike ES-derived progeny, MAPCs do not develop tumors. Their potential to correct liver disease, however, has not been demonstrated in any animal model.
6.2. Embryonic Stem Cells
Embryonic stem (ES) cells have enormous potential as a source for cell replacement therapies, drug development, and as a model for early human development. In general, ES cells have been defined as cell that are self-renewing and pluripotent and that can be isolated from the inner cell mass of the blastocyst, proliferate extensively in vitro, differentiate into derivatives of all three germ layers, express a number of characteristic markers like Oct4, SSEA-4, TRA-1-60, and TRA-1-81, and show high levels of telomerase activity (153). The ability to induce specific differentiation has been demonstrated by the formation of aggregates to form spheroid clumps of cells called embryoid bodies (EBs), leading to a spontaneous differentiation and the production of cells from the three germ layers: ectoderm, mesoderm, and endoderm (154). In addition, the direct addition of various growth factors to differentiating ES cells, followed by the analysis of cell morphology and specific marker expression has been demonstrated. Specific protocols have been developed in order to enrich various cell types during the differentiation of ES cells. The production of neuronal (155), cardiac (156), hematopoietic (157), endothelial (158), pancreatic (159), and hepatic cells (11, 13, 160–170) has been documented. In general, we can divide the methods of differentiation into spontaneous and directed differentiation. In the protocol of spontaneous differentiation, the cells are grown as EBs for a few days and then usually they are plated on an adherent matrix as a monolayer, either as dissociated cells or as clumps of cells (165, 166, 169, 170). Direct differentiation has been usually induced by the addition of various kinds of growth factors, cytokines, and extracellular matrices to the culture medium to induce specific gene expression, morphology, and most importantly function in the differentiating cells to produce the desired hepatic phenotype (161, 163, 167). Recently, combinations of both methods,
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EB induction and direct application of growth factors and cocultures, have been reported (13, 160, 168). 6.2.1. Endoderm Induction from ES cells
Since ES cells are derived from and display gene expression and properties characteristic of pluripotent embryonic cells, it is generally believed that directed differentiation of ES cells into specific cell types for therapeutic purposes will necessarily begin by inducing ES cells to form germ layer intermediates. ES cells are in fact a group of undifferentiated cells localized in the epiblast. The epiblast-derived cells give rise to three principal germ layers and their terminally differentiated tissues through a process called gastrulation (26, 171). From the three germ cell layers, endoderm is the one that gives rise to hepatic, pancreatic, lung, intestinal, and other therapeutically relevant cell types, yet early endoderm development is not well understood. The initiation of gastrulation is recognized by the formation of the primitive streak (PS) at the posterior part of the epiblast. Heterotopic transplantation studies have demonstrated that by mid-to-late gastrulation, cells are determined to give rise to endoderm (172). Several early endodermal transcription factors, including Otx2, Hesx1, Hex, and Cdx2, are regionally expressed prior to the time that organ-specific genes are activated (26). Within the PS, the cells of the mesendoderm regulate the expression of several genes important for the cell fate differentiation of the definitive endoderm and mesoderm progenitors. Among them are goosecoid (GSC) forkhead box A2 (FOXA2), chemokine C–X–C motif receptor 4 (CXCR4), sexdetermining region-Y box 17 (Sox17a/b), brachyury, E-cadherin, vascular endothelial growth factor receptor-2, (VEGFR2), VEcadherin, platelet-derived growth factor receptor-a (PDGFRa), and GATA-binding protein 4 (GATA-4) (26, 173). In addition, extraembryonic endoderm arises at the blastocyst stage and eventually forms two subpopulations: the visceral endoderm, the main metabolic component of the visceral yolk sac, and parietal endoderm, which secretes Reichert’s membrane and contributes to the transient parietal yolk sac. Extraembryonic endoderm cells share the expression of many genes with definitive endoderm, including the often-analyzed transcription factors Sox17, FOXA1, and FOXA2 (160, 174). Thus, a better understanding of the genetic pathways that regulate cell fate determination of extraembryonic endoderm, as well as genes that can serve as markers to distinguish definitive and extraembryonic endoderm, is needed. Recent advances have been reported in the gene expression pattern of definitive endoderm and its following enrichment using the markers EpCAM (+), CD38 (−), and DppIV (−) (175). However, a totally pure definitive endoderm population has not yet been purified from ES cells.
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Several advances have been made in deriving endoderm from ES cells. However, a better understanding of definitive and extraembryonic endoderm is necessary for the field to progress. Recently, several groups have reported differentiation of mouse or human ES cells into definitive endoderm by the combination of activin A, a TGF-β family member that also binds the same receptors as Nodal (with the exception of the coreceptor Cripto), and a low serum concentration with relative high efficiency. Their analyses clearly indicate the possibility of modulating in vitro a direct differentiation of the ES cells into definitive endoderm derivatives (159, 173, 174, 176). The common transcriptional machinery in definitive and visceral endoderm implies a similarity in the mechanism of specification of the two tissues. Thus, it is tempting to consider that common signaling events induce Sox17 and the FOXA genes. Therefore, these signaling events confer “endoderm identity.” Moreover, selective induction of definitive endoderm from ES cells may require inhibition of visceral endoderm. Thus, factors promoting endoderm formation such as those of the Nodal family (177, 178) should be combined with factors that inhibit induction of the extraembryonic endoderm cassette to specifically induce definitive endoderm. Most of such extraembryonic endoderm-promoting factors are yet unknown, although an involvement of the FGF signaling pathway has recently been suggested (13, 179). However, a recent work suggested that two conditions are required to induce approximately 70–80% of definitive endoderm from human ES cells: signaling by activin/Nodal family members and release from inhibitory signals generated by PI3K through insulin/IGF (180). 6.2.2. Hepatic Induction
Growth factor signaling from the cardiac mesoderm and septum transversum mesenchyme specifies the underlying endoderm to adopt a hepatic fate such that by the 6–7 somite stage, hepatic gene expression can be detected in the ventral foregut endoderm (28). Concurrent with these events, the most distal region of the foregut endoderm starts to express pancreatic genes (28, 36). The growth factors identified were fibroblast growth factors (FGFs) and bone morphogenetic proteins (BMPs). Using tissue explant assay, it was demonstrated that acidic or basic FGFs could substitute for cardiac mesoderm in inducing ventral endoderm to elicit a hepatogenic response (28). Concomitantly, the same group showed that BMPs secreted from septum transversum mesenchyme are needed in concert with cardiac-derived FGFs to induce the ventral endoderm to adopt a hepatic fate. Usually, the most abundant factors that were used to induce hepatic differentiation are acid FGF, basic FGF, FGF4, BMP4, and BMP2 (12, 13, 161). Co-cultures of chick cardiac mesoderm were shown recently to induce hepatic differentiation in mouse
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ES cells, nicely illustrating how embryonic principles help control stem cell differentiation in vitro (168). Recently, some reports have proven the importance of FGFs and BMPs on mouse ES cells differentiation toward hepatic phenotype. Furthermore, interactions with endothelial cells, a mesodermal derivative in this inductive sequence, are crucial for this early budding phase in hepatic induction (181, 182). However, the relevant endothelial signaling molecule is not known. It is not clear how endothelial cells before blood vessel formation appear near the newly specified hepatic endoderm. But a recent report of our group used co-culture of ES cells and a combination of liver nonparenchymal cells including a liver endothelial cell and it was shown that the interaction of ES cells with the endothelial cell line steps up hepatic differentiation (160). Extracellular matrix plays a key role in the process of differentiation (183). Generally, collagen or Matrigel was chosen as the matrix for growing the cells since the liver bud proliferates and migrates into the septum transversum mesenchyme, which is composed of loose connective tissue containing collagen (160, 161, 163). Several transcription factors have been identified and proposed as targets of FGFs and BMPs signaling in early hepatic onset. FOXA and Gata genes have been shown by genetic analysis to regulate the competence of foregut endodermal cells to respond to hepatic inductive signals (38, 184). Gata-4 was the first Gata factor to be implicated in the development of the ventral foregut. The ability of Gata-4, in conjunction with FOXA2, to reposition nucleosomes around this enhancer has led to the hypothesis that Gata-4 potentiates hepatic gene expression (184). In the endoderm, the onset of FOXA gene expression precedes the induction of the hepatic program by FGF signals. Furthermore, FOXA proteins are able to displace nucleosomes present in the regulatory region of the albumin gene before the gene becomes activated, but other transcription factors that bind to this region are unable to do so (184, 185). FOXA2 binding can reverse chromatin-mediated repression of α-fetoprotein (Afp) gene transcription in vitro (186). In summary, FOXA1 and FOXA2 are essential for hepatic specification, FOXA proteins function as “pioneer” proteins to open compacted chromatin in regulatory regions of liver-specific genes (37). HNF4-α contributes to regulation of a large fraction of the liver and pancreatic islet transcriptomes by binding directly to almost half of the actively transcribed genes (187). Moreover, recent observations provided a refined molecular-specific hepatic fate characterization, where the transcription factor hepatocyte nuclear factor-6 (HNF6) has a critical role in the proper morphogenesis of both the intra- and the extrahepatic biliary tree. Furthermore, it would appear that the mechanism by which HNF6 regulates biliary tree development involves the related transcription
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factor hepatocyte nuclear factor-1 (HNF1) (188). There is also evidence that there is an uncovered and an unexpected relationship between extrahepatic bile duct morphogenesis and pancreas development (189). Most of the protocols of hepatic differentiation from ES cells used a constitutive expression of a hepatic transcription factor in order to direct and confirm the differentiation toward the endoderm and hepatic lineages. Some of the nuclear factors that have been used to follow up definitive endoderm and hepatic differentiation are the following. For definitive endoderm development: forkhead box (FOX) transcription factors, FOXA1, FOXA2, goosecoid (GSC), c-kit and chemokine C–X–C motif receptor 4 (CXCR4), sex-determining region-Y box 17 (Sox17a/b), brachyury, E-cadherin, vascular endothelial growth factor receptor-2, (VEGFR2), VE-cadherin, plateletderived growth factor receptor-a (PDGFRa), and GATA-binding protein 4 (GATA-4). For hepatic development: α-fetoprotein (AFP), albumin (ALB), hepatocyte nuclear factor 4 and 6 (HNF4 and HNF6), tryptophan-2,3-dioxygenase (TDO), tyrosine aminotransferase (TAT), and the cytochrome P450 (CYP) enzymes (CYP7a1, CYP3a11, CYP3a4, CYP3a1), and glucose 6-phosphatase (G6Pase) (12, 13, 174, 176) (see Fig. 10.2). 6.2.3. Hepatic Specification
Hepatocytes and bile duct cells originate from a common precursor, the hepatoblast (190). Notch signaling promotes hepatoblast differentiation into the biliary epithelial lineage, and HGF does the opposite (45). Thus, the expression of the Notch intracellular domain in hepatoblasts inhibits their differentiation into hepatocytes. Supporting the idea of HGF as a promoter for the hepatic fate decision, a study found that HGF induces the expression of C/EBPα in albumin-negative fetal liver cells (191). When C/EBPα activity is blocked through the expression of a dominant negative form of C/EBPα, there is no transition of ALBto the ALB+ stage. HGF promoted differentiation of ALB+ cells from ALB– precursors but inhibited further differentiation of the ALB+ cells into biliary cells, suggesting that HGF promotes the establishment of a bipotent state of the hepatoblasts. Wnt signaling is also involved in regulating biliary epithelial cell fate. The addition of Wnt3A in ex vivo fetal liver culture experiments supports biliary epithelial cell differentiation (192). Furthermore, the inhibition of β-catenin prevents hepatoblasts from expressing biliary markers (193). One important factor for activating this differentiation program is HNF6. HNF6 is expressed in hepatoblasts, in the gallbladder primordium, and in biliary epithelial cells of the developing intrahepatic bile ducts (188). HNF6 knockout mice developed no gallbladder, and the development of the intrahepatic and extrahepatic bile ducts was abnormal. The intrahepatic bile ducts had a similar phenotype in
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conditional HNF1β knockout mice (194). These results suggest that the effect of HNF1β is downstream of HNF6. Thus, TGF-β, HGF, C/EBPα, and HNF6, in combination with Notch pathway, integrate into a coherent network that controls bipotency and allows further biliary or hepatocytic differentiation (see Fig. 10.2). 6.2.4. Hepatic Maturation
The third important step after the induction of the hepatic fate in endoderm cells and the differentiation into hepatoblasts is the proliferation of these cells. The mesenchymal component of the liver, derived from the septum transversum mesenchyme, is essential for the proliferation of hepatoblasts (195). Other essential interactions for liver bud growth are the endothelial cells. The requirement of endothelial cells for hepatic endoderm growth could be recapitulated with embryo tissue explants, showing that the effect is independent of oxygen and factors in the bloodstream. These important interactions between endothelial and liver cells appear to persist in the adult liver (196). Hepatocyte growth factor (HGF) controls a signaling pathway that controls the proliferation of the fetal liver cells. Genetic studies in mouse embryos showed that the proliferation and the outgrowth of the liver bud cells require the interaction of HGF (197, 198) with its receptor, c-met (199). Knockout of either HGF or c-met showed similar phenotypes and failed to complete the developmental process and died in utero between embryonic days 13.5 and 16.5 with multiple abnormalities, including signs of underdeveloped liver. Interestingly, during regeneration of the adult liver, this pathway is important for the proliferation of the hepatocytes, since conditional c-met knockout mice show an inhibition in the proliferation after liver injury, where c-met primarily affects hepatocyte survival and tissue remodeling (200). This is a good example in which pathways for the development of an organism function in a similar way in the adult. Other transcription factors have been involved in hepatoblast proliferation. The transcription factors Foxm1b and Xbp1 are also required for the liver bud cell proliferation. Foxm1b knockout mice die in utero by ED18.5 and the fetal liver shows a 75% reduction in the number of hepatoblasts (70). Additionally, these animals do not develop intrahepatic bile ducts. Thus, forkhead box m1 transcription factor seems to be critical for the differentiation toward the biliary epithelial cell lineage. The Xbp1 knockout mice also show hypoplastic livers and death caused by reduced hematopoiesis, with a reduced growth rate and increased apoptosis of hepatocytes. This provides a link between hematopoiesis and liver development (201). Researchers have found that Wnt/βcatenin pathway activation plays a role in fetal liver cell proliferation and maturation, whereas inhibition of Wnt signaling results in reduced cell proliferation (193).
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Hematopoiesis plays an important role in hepatic maturation. After the liver bud emerges from the gut tube, hematopoietic cells migrate from there and propagate. The hematopoietic cells secrete oncostatin M (OSM), a growth factor belonging to the interleukin-6 (IL-6) family that includes IL-6, IL-11, leukemia inhibitory factor (LIF), ciliary neurotrophic factor, and cardiotrophin-1; these cytokines often exhibit similar functions since their receptors utilize gp130 as a common signal transducer and the surrounding liver cells express the gp130 receptor subunit OSMR (202). OSM stimulates the expression of hepatic differentiation markers and induces morphologic changes and multiple liver-specific functions such as ammonia clearance, lipid synthesis, glycogen synthesis, detoxification, and cell adhesion. However, OSM also possesses unique functions, e.g., growth stimulation of endothelial cells (203) and smooth muscle cells (204). Oncostatin M not only induces hepatic differentiation but also suppresses fetal liver hematopoiesis. Hepatic cells from ED8.5 support the expansion of hematopoietic stem cells and give rise to myeloid, lymphoid, and erythroid lineages. The addition of OSM and glucocorticoid strongly suppresses this process. In contrast, hepatic cells from ED14.5 no longer support hematopoiesis in cocultures. However, the hematopoietic cells induce further differentiation of hepatoblasts, and in consequence, the liver stops supporting local hematopoiesis and induces the hematopoietic stem cell to switch to the bone marrow (205). In addition, OSM can induce the downregulation of cyclins D1 and D2 (206). This downregulation is mediated by Stat3, which is activated through OSM and OSM receptor complex interaction. These cyclins are important for the initiation of the cell cycle and therefore for cell proliferation and they are normally downregulated during liver development. Glucocorticoids have also been involved in hepatic maturation and found to modulate proliferation and function of adult hepatocytes both in vivo and in vitro. In the fetal liver, physiological concentrations of dexamethasone (Dex), a synthetic glucocorticoid, suppress AFP production and DNA synthesis and upregulate albumin production (207). TAT mRNA, which is virtually absent in the early fetal liver, is induced by Dex in primary hepatocytes of late embryonic stage. In contrast, Dex does not regulate TAT levels at earlier stages (midgestation; ED12–14), even though these cells are able to express albumin in response to Dex (208). Recent studies have shown that embryonic stem cells can be efficiently differentiated into hepatocyte-like cells. The transcription factors previously mentioned, their receptors, and the substances related with their stimulation in either way might take part in hepatic maturation and specification from ES cells. A current work reported the co-culture of adult isolated hepatocytes with
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fetal isolated hepatocytes, resulting in the increase of liver-specific gene expression and elevated hepatic functions. Even the effects of the co-culture system were reversible for the fetal hepatocytes; adult hepatocytes provided an appropriate atmosphere for the hepatic maturation of fetal hepatocytes (209). Inspired on molecular basis of liver development and regeneration, an elegant work explored that the co-culture of liver tissue with hematopoietic stem cells induced hepatic differentiation and maturation (141). Thus, hepatocytes and liver nonparenchymal cells seem to play a role in liver maturation of stem cells. Recently, we have combined efforts to generate functional hepatocytes from mouse ES cells. The differentiation protocol is simple, uses defined reagents, and yields to date the most efficiently differentiated hepatocyte-like cells. Starting with a suspension culture system, where early endodermal development is initiated, ES cells are subsequently transferred to plates and cultured in the presence of fibroblast growth factor-2 and activin A. The predifferentiated cells are then further developed toward hepatocytes in a defined co-culture together with human nonparenchymal liver cells (endothelial cell line, cholangiocyte cell line, and stellate cell line) under the influence of hepatocyte growth factor, dimethyl sulfoxide, and dexamethasone. The improvement in hepatic maturation was observed when co-culture with liver nonparenchymal cell lines was applied. Several cytokines and growth factors were identified in the conditioned medium of the cell lines. Those substances play a key role in liver regeneration (13, 160). Yet, many questions remain to be further examined before such a protocol can be successfully applied to human ES cells. One of the most particular aspects of ES cell differentiation is whether the cells are homogeneously and specifically differentiated in the desired way. 6.2.5. Current Status of Human ES Cell Differentiation to Hepatocyte-like Cells
ES cells hold great promise as a source of new hepatocytes, but this potential has proven to be more difficult than expected. Beginning in 2000, papers began to appear (165, 167, 210–213). Progeny of mouse and human ES cells were reported to express and secrete albumin and even to have cytochrome P450 (CYP) enzyme activities. Several approaches have been used to differentiate and to obtain enriched populations. Human hepatic-like cells were isolated and characterized for their phenotype. Through gene manipulation, albumin promoter was used to select the cells, hepatic cells were labeled, and a relatively homogenous population of differentiated cell types were demonstrated (165). However, the cells expressing hepatic phenotype were isolated from EBs; thus a very small number of cells were produced and functionality of the cells was not tested. In one of the few reports on human ES cells, the combination of insulin, DEX, and collagen type I followed by sodium butyrate led to increased numbers of mature hepatic gene-expressing cells (10–15%). The
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resultant cells had morphological features similar to those of primary hepatocytes and most of the cells expressed liver-associated proteins (167). Great care must be taken in defining how closely such cells resemble normal hepatocytes, which are very well characterized in regard to their gene expression, metabolism, growth potential, and secretory functions (214). We might believe that hepatocyte-like cells derived from stem cells designated for therapeutic replacement must match the extraordinary performance of normal hepatocytes, with their ability to store glycogen, secrete albumin, metabolize drugs, and the other more than 500 different functions performed by the liver (215). However, it must be recognized that there are developmental pathways found in tissues such as fetal pancreas, fetal intestine, and other endodermal derivatives that generate cells that in certain stages of development might express similar hepatic gene pattern and that will never become a true hepatocyte. The lack of success of these early attempts at differentiating human ES cells into functional hepatocytes has focused attention on the fundamentals of normal embryonic development to better understand the early stages of definitive endoderm formation. The difficulty of this approach is the need to produce a directed homogeneous population of definitive endoderm. A recent important contribution is a protocol in which the use of activin A in combination with serum-free conditions resulted in enrichment of definitive endoderm (up to 80%) from human ES cells (176). Using a modification of this protocol, and a combination of protocols previously reported using mouse ES cells, Cai et al. reported that the addition of FGF, BMP, and HGF can induce the hepatic fate, and the later addition of OSM and Dex to the cell culture induced an even more differentiated hepatocytelike cells in a total time of 18 days. This in part is a recapitulation of the events during development. This study also showed that the transplantation of the differentiated cells into mice with drug-induced liver failure incorporated a limited quantity of cells into the liver parenchyma (161). Transplantation of the differentiated cells is a very important control to confirm that hepatocytelike cells can function as hepatocytes in vivo. However, adequate animal model of liver failure should be used to evaluate the real functional integration of the resulting hepatocyte-like cells (see Fig. 10.3). 6.2.6. Conclusions and Prospects
The hepatocyte-like cells generated from human ES cells represent an attractive source for the treatment of several hepatic diseases. However, the efficient differentiation of human ES cells into a mature hepatocyte still remains a significant challenge. The differentiation of hepatocyte-like cells from human ES cells has proven to produce a more developmentally heterogeneous population than expected. There is a need to identify reliable markers
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Fig. 10.3. Directed differentiation of hES cells to hepatocyte-like cells by mimicking embryonic development. Key stages of hepatic differentiation and stepwise differentiation of ES cells. Characteristic gene expression for each step of differentiation is shown.
for hepatocytes and yolk sac tissues. In mice, for example, it was shown that CYP7A1 is expressed in the liver and not expressed in the yolk sac tissue, and thus it can be a good marker for hepatocytes (216). Embryonic, fetal, and adult hepatocytes are different by means of their gene expression and functional activities. Fetal hepatocytes transplanted into the liver cannot completely replace the functional activities of adult hepatocyte since they represent a different developmental stage. Genes such as albumin or AFP are first expressed in early embryos and further on fetal hepatocytes. In the case of AFP, it is expressed very early in embryonic development and later on in the fetus but is turned off. A hepatocyte that had stopped to express AFP can be considered as adult hepatocyte. Thus, their expression cannot tell the state of the differentiated cell unless both markers can be scrutinized. One more hurdle that needs to be overcome is the isolation of pure hepatic cell fractions using systems with clinical significance. To solve that, membrane markers of mature hepatocytes have to be detected. One option is the asialoglycoprotein receptor (ASGPR), which is almost exclusively expressed in hepatocytes (217). This mean cell magnetic sorting would be a consistent purification system. In the future, studies of embryonic stem cells to hepatocyte differentiation can increase our understanding of the molecular basis of liver development. The exact understanding of these developmental processes that lead to a specific cell fate might help us to recapitulate the events in vitro and engineer artificial liver cells and tissues to combat liver diseases. Expectations and hopes are very high, but the difficulty of these approaches remains a challenge. However, with the extraordinary potential of modern science, one must remain hopeful that clinical advances will come sooner rather than later.
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7. Identifying a Hepatocyte To date, various ways to cause ES cells to differentiate into hepatic-like cells have been reported. The availability of a homogeneous source of human hepatocytes is considered the most precious tool for toxicity screening. In addition to hepatotoxicity, hES-derived hepatocytes would provide a renewable, cell-based assay to examine other key factors of compound attrition such as the metabolism of xenobiotics by CYP enzymes, drug–drug interactions, system for studying hepatic metabolism of xenobiotics, hepatotoxicity, and the activity of drug transporters, as well as regenerative medicine. This opens exciting new possibilities for pharmacology and toxicology, as well as for cell therapy. However, the nature of the “hepatocyte-like cells” should be analyzed very carefully under several constrictions and a clear definition of the term hepatocyte has to be implemented. The expression of hepatocyte markers, such as AFP, ALB, or CK18, as well as the induction of an epithelial phenotype and inducible cytochrome P450, has been reported in several works. Therefore, it is understandable that many scientists gave their stem cell-derived cell types terms such as hepatocyte. Properties such as epithelial morphology and expression of some hepatocyte markers are necessary but not sufficient to consider a cell as a hepatocyte. Albumin expression and cytochrome P450 (CYP) are examples of this. In fact, hepatocytes are the only cell type that secretes albumin. However, the conclusion that any albumin-secreting or albumin-expressing cell necessarily represents a hepatocyte is still premature. For example, it is possible that stem cell-derived cell types express albumin together with a limited number of hepatocyte markers, but this does not mean that they also express the necessary set of hundreds of genes that make up a true hepatocyte. Moreover, CYP enzymes are not exclusively limited to hepatocytes. Indeed, CYP induction was also reported for lung, colon and small intestine epithelial cells, white adipose tissue, and several other cell types (218–220). Therefore, it is not possible to unequivocally define whether a candidate cell is a hepatocyte or not. Thus, the definition of hepatocyte should include qualitative studies where the presence and the absence of hepatocyte markers are demonstrated together with an enzymatic activity evaluation. We have now moved from the phase of simply detecting the expression of hepatic genes in stem cells to the finding of significant measures to judge if stem cell-derived hepatocytes have truly mature hepatic function. It seems reasonable to introduce additional criteria to define if a cell is a true hepatocyte or only shares several characteristics with a hepatocyte. It is also important
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to understand what properties a hepatocyte or the substitute hepatocyte-like cell should have. We need to establish a list of mature hepatic functions, which are easily measured. The resulting hepatocyte-like cells should be compared with human fetal and mature human liver and we should define endpoints to measure the level of hepatic maturation in stem cell-derived hepatocytes. Finally, we need fast and easy tests that provide relevant and robust information on the hepatic capacities of the produced stem cell-derived hepatocytes. From a functional point of view, any candidate hepatocytelike cell type should exhibit a minimal set of hepatic functions of a true hepatocyte. Here, we present a battery of relevant studies for the analysis of enzyme activities of stem cell-derived hepatocytes: (a) analysis of expression of genes identified in mature livers; (b) metabolism of xenobiotics and endogenous substances (hormones and ammonia); (c) synthesis and secretion of albumin, clotting factors, complement, transporter proteins, bile, lipids, and lipoproteins; and (d) storage of glucose (glycogen), fatsoluble vitamins A, D, E, and K, folate, vitamin B12 , copper, and iron. Finally, a convincing in vivo experiment to prove hepatocellular differentiation is to restore liver function in animal models by means of repopulation assays. However, any repopulation experiment may only evaluate that a certain hepatic cell type has the capacity to generate hepatocytes in vivo. Thus, testing a defined battery of activities and comparing them with primary hepatocytes remains the only feasible option for evaluating the in vitro potential of stem cell-derived hepatocyte cultures as appropriate surrogates for primary human hepatocytes (see Fig. 10.4). 7.1. Hepatocyte Drug Metabolism
The entire hepatic drug-metabolizing enzyme system in an integrated form provides an in vitro model that is a very useful tool for anticipating drug metabolism and drug hepatotoxicity in man. Cytochrome P450s (CYPs) are mixed function monooxygenases and the major enzymes in phase I metabolism of xenobiotics. Depending on the nature of the xenobiotic, this oxidative metabolism results in inactivation and facilitated elimination, activation of pro-drugs, or metabolic activation (221). Evaluation of CYP for specific measurements in stem cell-derived hepatocytes classified as phase 1 metabolism may include CYP1A2, CYP2A6, CYP2B6, CYP2C8, CYP2C9, CYP2C19, CYP2D6, CYP3A4, and CYP3A7, while CYP7A1 is involved in bile acid metabolism. The enzymes of greatest importance for drug metabolism belong to the families 1–3, responsible for 70–80% of all phase I-dependent metabolism of clinically used drugs (222). Studies performed in primary human hepatocytes point to the cytochrome CYP3A4 as an important marker for hepatocytes, as this enzyme is the most abundant CYP enzyme in the human liver.
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Fig. 10.4. Distinguishing features of mature hepatocytes. Hepatocytes are the chief functional cells of the liver. These cells are involved in protein synthesis, protein storage and transformation of carbohydrates, synthesis of cholesterol, bile salts and phospholipids, and detoxification, modification, and excretion of exogenous and endogenous substances. Roughly, 80% of the mass of the liver is contributed by hepatocytes.
CYP3A4 activity can be measured using 6-β-hydroxytestosterone (223). It has been reported to be quantitative, sensitive, and specific. CYP expression and activity present large interindividual variations due to polymorphisms (224). Moreover, CYPs can be induced several fold or inhibited by specific drugs, resulting in additional, although transient, variability of metabolic activity. Inducibility of CYPs is a mature liver function that must also be observed in stem cell-derived hepatocytes. CYPs are inducible by exposure to phenobarbital, rifampicin, and, to a lesser extent, steroid hormones (225). The CYP2C family also represents a significant proportion of total P450s (2C9, 2C8, 2C19, and 2C18), representing about 20% of the total P450 (226), and metabolizes many drugs (227), thus making this enzyme subfamily important to monitor. CYP1A2 is a minor enzyme in the liver and only a small number of drugs (4%) are metabolized by this enzyme (227). However, it is involved in the bioactivation of pro-carcinogens and is therefore considered to be an important enzyme to test (228). CYP2B6 is emerging as an important enzyme in drug–drug interactions despite a previously reported low abundance in the liver (0.2% of total P450) (226). Once thought to be of minor importance and uninducible in humans (229), CYP2B6 may actually constitute at least 5% of the total P450, contribute to the metabolism of
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more than 25% of all pharmaceutical drug metabolism (230), and exhibit high inducibility (231). CYP2D6 has no known inducer and represents only 2% of the total P450 (226). However, researchers persist in testing this enzyme because of its major contribution to drug metabolism and its polymorphism (227). CYP3A7 is mainly expressed in fetal liver even at midgestation, although in rare cases, CYP3A7 mRNA has been detected in adults. CYP3A7 activity can be induced by hydroxyprogesterone caproate metabolism. The CYP3A forms have demonstrated an equal or reduced metabolic capability for CYP3A5 compared with CYP3A4 and a significantly lower capability for CYP3A7. Thus, active metabolism can be detected for both CYPs 3A7 and 3A4 (232). Cholesterol 7a-hydroxylase (CYP7A1) is found exclusively in the liver, where it catalyses the first step in the major pathway responsible for the synthesis of bile acids (233). The expression of this enzyme is subject to feedback regulation by sterols and is thought to be coordinately regulated with enzymes in the cholesterol supply pathways, including the low-density lipoprotein receptor and 3-hydroxy-3-methylglutaryl-coenzyme A reductase and synthase (233). Sensors like the aryl hydrocarbon receptor (Ahr), pregnane X receptor (PXR), and the constitutive androstane receptor (CAR) are integral to the regulation and induction of the main P450s (229) and their analysis may provide a strong evidence of the maturation state of stem cell-derived hepatocytes due to their upregulation during liver development. These receptors control the expression of CYP1A (Ahr), CYP2, and CYP3A (PXR and CAR) families. Once activated, the receptors form heterodimers with other factors, such as Arnt (Ahr nuclear translocator) and retinoid X receptor (RXR for both PXR and CAR), and then bind to the target xenobiotic response elements (XRE) located in both the proximal and the distal P450 gene promoters, resulting in the transcription of the respective CYP isoform (229). In summary, we can conclude that gene analysis of the abovementioned CYPs accompanied by induction tests could represent a robust background to follow the maturation of stem cell-derived hepatocytes. In addition, some are expressed at low levels in early development and their increased expression coincides with maturation of hepatic development/function. See also Chapters 15–17 and 19. 7.2. Hepatic Transporters
Hepatic transport proteins and mainly measurement of bile acids can serve as indicators as well. However, all hepatic functions do not mature at the same time rate and some hepatic transporters are expressed early in the development and may not be exclusive for the liver. There is evidence that they are expressed in the intestine, kidney, brain, and other organs (234). Some important hepatic transport proteins can be classified as follows:
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(a) the solute carrier SLC family, comprising among others Na+ -taurocholate cotransporting polypeptides (NTCPs), organic anion-transporting polypeptides (OATPs), organic anion transporters (OATs), and organic cation transporters (OCTs); (b) the ATP-binding cassette (ABC) transporter family, including the multidrug resistance (MDR) proteins, bile salt export pump (BSEP) (both belong to the ABCB family), breast cancer resistance protein (BCRP; belonging to the ABCG or White family); and (c) the multidrug resistance-associated proteins (MRPs), belonging to the ABCC family. MRP1 and MRP2 are involved in biliary excretion of a large variety of structurally unrelated compounds, among others bulky hydrophobic cationic compounds, but also steroid hormones. MRP2 excretes mainly anionic conjugates, among others bilirubin glucuronides, leukotriene C4, and glutathione (225). The basolateral Na+ -taurocholate cotransporting polypeptide (NTCP) transports bile acids from the space of Disse into hepatocytes, human NTCP accepts most physiological bile acids while at the canalicular membrane, and the efflux of bile acids by the bile salt export pump (BSEP) mediates concentrative excretion (235). See also Chapters 18 and 22. 7.3. Hepatic Transcription Factors, Homeostasis, and Clinically Relevant Hepatic Enzymes
The demonstration of the expression of transcription factors regulating hepatic development and maturation is useful (HNF4-α, C/EBPα, C/EBPβ), although they may not be as critical markers as the CYPs for measuring maturation because they are expressed at near adult liver levels even at midgestation. In a very elegant study, Odom et al. have demonstrated the importance of HNF4-α for gene regulation in hepatocytes. Microarray data suggest that HNF1α binds to 222 target genes in human hepatocytes corresponding to 1.6% of the genes assayed. HNF6 binds to 227 (1.7%) and HNF4-α binds to 1575 target genes (12% of the genes assayed), which means that HNF4-α binds to nearly half of the active genes in the liver that were tested. In addition, most of the genes which bind HNF1α or HNF6 were also found to bind HNF4-α, but only a few genes were found to bind both HNF1α and HNF6 (187). The differentiated state of the hepatocytes is regulated by a coordinated interplay of hepatocyte-specific transcriptional factors, including HNF4 and C/EBPα (236). HNF4 is involved in hepatocyte-specific expression of serum proteins, such as albumin and transferrin, and of cytochrome P450 proteins. In primary cultures of rat hepatocytes, the expression of C/EBPα is rapidly reduced within a few days of culture, resulting in reduced hepatic functions. Michalopoulos et al. (214) demonstrated that the maintenance of C/EBPα, HNF4, nuclear factorκB (NF-κB), and activator protein-1 (AP-1) contributed to the prolonged expression of liver-specific proteins in human hepatocyte cultures.
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Additionally, analysis of some hepatic clotting factors (II, V, VII, IX, X, and fibrinogen), albumin production, urea production or ammonia metabolism, and glycogen storage may provide additional robust evidence of an effective hepatic maturation of stem cell-derived hepatocytes. The presence of hepatic enzymes with clinical implications would be useful in the process of hepatic maturation categorization, for example, UDP-glucuronosyltransferase (UGT1A1), an enzyme of the glucuronidation pathway that transforms small lipophilic molecules, such as steroids, bilirubin, hormones, and drugs, into water-soluble, excretable metabolites (237). Other important enzyme that is present in mature hepatocytes is glucose-6phosphatase (G-6-Pase)1, which catalyzes the hydrolysis of glucose 6-phosphate to glucose, which is the terminal step of both hepatic gluconeogenesis and glycogen breakdown (237). α-1Antitrypsin (A1AT) is another example of a clinically relevant enzyme that is present in mature hepatocytes. As a member of the serpin superfamily of proteins, A1PI is a potent inhibitor of serine proteases, especially neutrophil elastase, which degrades connective tissue in the lung (238). The A1AT gene is expressed in cells of several lineages, with expression being highest in hepatocytes (239). Urea cell cycle-related enzymes might be important when hepatic function of stem cell-derived hepatocytes is to be evaluated. The ornithine transcarbamylase (OTC) gene is expressed exclusively in liver and intestinal mucosa. It is located in the mitochondria and takes part in the urea cycle as well as carbamyl phosphate synthetase I (CPS) and argininosuccinate synthetase (ASSL) (240) (see Fig. 10.4). 7.4. Conclusions
For further progress, it will be important to clearly define activities that closely resemble those of primary hepatocytes, for example, basal and rifampicin-induced activities of CYP3A4, the most abundant CYP isoform in the human liver, and even more importantly, others that are not hepatocyte-like. The above-mentioned lists of genes and functions of stem cell-derived hepatocytes must be compared to human fetal or adult liver. Mature hepatic characteristics should be demonstrated using drug metabolism detoxification at gene expression and functional levels. Additional characterization can be provided by analyzing hepatic transport proteins, mature hepatic transcription factors, and factors related to homeostasis, albumin secretion, production of bile acids, bilirubin conjugation assays, ammonia metabolism with the expression of related enzymes, and finally, the analysis of mature liver gene expression and function in animal models of liver failure after transplantation in the liver or ectopic sites. In addition, a clear definition of non-hepatocyte-like factors is important to identify mechanisms responsible for the lack of activity.
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Clarification of such mechanisms, for instance, loss of transcription factor expression or modification of signal transducers, is a requirement for further progress. It may be extremely difficult to differentiate stem cells into a cell type that resembles primary hepatocytes in all aspects of drug metabolism. However, promising results have been obtained with extrahepatic stem cells since some previously silent hepatocyte markers become expressed during differentiation and metabolic activities start appearing after new protocols have been reported (see Fig. 10.4).
8. Therapeutic Potential of Stem Cell-derived Hepatocytes
There are already insufficient donor organs to meet the demand for transplantation. With the worldwide shortage of donor organs likely to increase over the coming decades, research into alternative methods of treatment to whole organ transplantation is essential. Liver cell transplantation and cell-based therapies are evolving as viable clinical alternatives to whole organ transplantation. Cell therapies provide a better utilization of donor tissue and major surgical procedures can be avoided. See also Chapter 29. Although liver cell transplantations are safe and simple, there are not enough donor organs to spare for a procedure that is still experimental and has not been proven to be effective in the long term. It would be of great value if an alternative cell source to whole organs could be found for transplantation. Stem cells, whether adult or embryonic derived, offer such a possibility. It is clear that stem cells play a regenerative role in the liver and that different stem cell compartments in the body are activated by different types of physiological or pathological stimuli. Partial hepatectomy leads to regeneration of the mature hepatocyte compartment. The most elegant demonstration of liver regeneration was shown in a study of serial transplantation of severely immunodeficient, fumarylacetoacetate hydrolase (Fah)deficient mice. After pretreatment with a urokinase-expressing adenovirus, these animals could be highly engrafted (up to 90%) with human hepatocytes. Furthermore, human cells could be serially transplanted from primary donors and repopulate the liver for at least four sequential rounds, demonstrating the amazing ability of cells within the liver to replenish themselves (241). Moreover, it is clear that inhibition of the mature hepatocyte compartment through agents such as retrorsine and carbon tetrachloride leads to expansion of the oval cell compartment. Because of this, these cells have been felt to be central to liver repair mechanisms. See also Chapter 26 and 27.
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Recently, the demonstrations in both humans and rodents of the presence of bone marrow-derived cells in diseased livers have suggested that extrahepatic stem cells play a role in liver repair. It is hoped that this mechanism might be employed for therapeutic advantage. There are equally a number of papers that have failed to show disease correction following transplantation of extrahepatic stem cells. However, it is notable that each of the animal models employed has different liver injury or pathology. We cannot expect that the same mechanism of stem cell enrollment will be effective for a liver damaged by a metabolic disorder or a traumatic injury or chemical toxicity. It is likely that each type of liver pathology will have to be treated as a particular situation that will require an individualized stem cell approach. Several liver diseases have been identified for the purpose of cell therapeutic options. One of them is fulminant hepatic failure that is characterized by rapid onset of failure of the liver and death of the patient if whole liver replacement does not occur urgently. Cell therapeutic trials for fulminant hepatic failure in the form of liver cell transplants are underway and have shown moderate success (4). Bioartificial livers that could also theoretically employ stem cells represent an option to treat these kind of patients as an alternative to cell transplantation, to bridge them to whole organ transplantation or auto-recovery. Chronic liver disease is characterized by simultaneous liver regeneration and development of fibrosis that can finally result in cirrhosis. Patients with this form of liver disease may require treatment of portal hypertension before synthetic failure necessitates whole organ transplantation. Although extensive fibrosis could be an inhibitor of cell engraftment, it is unclear if liver cells or stem cell-derived cells could provide substantial hepatic support while adequate organ transplantation is performed. Metabolic liver diseases are characterized by an inherited defect of one hepatic enzyme, including urea cycle defects, bilirubin-metabolizing defects, and organic acidemias. In these disorders, the missing enzyme results in the buildup of toxic metabolites that are harmful to the individual but the rest of the function of the liver is normal. Metabolic liver diseases are ideal targets for development of cell therapeutic programs since only a small number of functional donor cells would effect disease correction through single enzyme replacement. Some metabolic liver diseases such as tyrosinemia type 1 are associated with severe liver injury and therefore engender selective repopulation of the recipient liver with donor cells as observed in animal models. However, most metabolic liver diseases are associated with little or no liver injury, thus cell repopulation remains an issue. However, metabolic liver diseases seem a likely option for donor stem cells to become hepatocyte competent of the native liver parenchyma.
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Before the use of stem cells can be effectively translated to clinical practice, both efficacy and safety will need to be demonstrated. At present, transplantation of stem cells from one individual to another would require the recipient to be immunosuppressed particularly for hematopoietic stem cells. However, it is not clear whether this is necessary for all cell types. Lately, several immunotolerance techniques have been suggested, for example, donor-derived leukocyte microchimerism and donor-derived dendritic cell progenitors have been implicated in liver transplant tolerance (242). This is particularly important since a benefit of transplanting hematopoietic stem cells as an adjuvant to whole organ transplantation to induce tolerance and prevent rejection has been postulated (243). Not enough is known about the immunogenicity of early lineage stem cells such as those derived from embryos, fetal liver, or liver at this time, although it is hoped that they will be more tolerogenic than adult hepatocytes, more studies need to be done in this area. Regarding the clinical use of differentiated human ES, there are concerns about their potential for tumorigenicity. Embryonic stem cells can provoke the formation of teratomas (244). Early lineage stem cells from cord blood do not and have been safely used clinically for many years. The situation with liver progenitor cells is unclear. Since long-term immunosuppression itself is carcinogenic, it remains to be seen whether these risks are clinically relevant and therefore prohibitive. The development of stem cell therapy is a work in progress. Some of the more speculative and elegant proposals, presently in the research stage, might avoid the problems outlined above. For instance, in the future, it is possible that specific human ES-equivalent cells could be obtained from patients and thus facilitate immunotolerance (245). It will be important to determine the minimum number of stem cells that can effect disease correction, as has been done for treatment of leukemias and marrow aplasias. Further work on the homing and engraftment mechanisms of extrahepatic stem cells in different forms of liver injury will add considerably to optimization of stem cell therapy. Scaled-up production of differentiated cells remains a concern as well. The ability of a stem cell population to expand to give clinically relevant numbers of cells might be truncated by terminal differentiation and loss of stem cell function. For instance, primary hepatocytes do not divide well in vitro and appear to de-differentiate and lose their hepatic potential after prolonged culturing. Growth in culture may also result in loss or change in homing and attractant capacity of stem cells. Finally, further techniques need to be developed in order to solve the inability to monitor cell function and rejection post-transplant in patients. Current experimental assessment of donor cell engraftment is unreasonable since it is usually obtained
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postmortem. Since the cell number transplanted is likely to be small, percutaneous liver biopsies may not be representative of graft function within the liver unless selective repopulation of the donor cells occurs. Furthermore, there is no morphological difference between the donor and recipient cells in liver cell transplants and it is unlikely that following successful transplantation, functioning stem cell will exhibit different morphology. Histology of the recipient liver has been unhelpful in monitoring liver cell graft rejection and this is likely to be the case for stem cell transplants. A recent work reported the pursuit of xenogeneic hepatocyte engraftment in the spleen of cynomolgus monkeys by asialoglycoprotein receptor-directed nuclear scanning. This technique may have great impact in future stem cell-derived hepatocyte clinical trials (246) (see Fig. 10.5).
Fig. 10.5. Therapeutic applications of stem cell-derived hepatocytes. (For details, see the text.)
9. Conclusions Further work is required before we can be confident that stem cells can cure liver disease. We believe that the only conclusive evidence of hepatocyte functionality for stem cells will come from demonstrating disease correction following transplantation. Although there are many promising laboratory studies, there are only a handful of disease models that have been used to test stem cell correction of liver disease and there is an urgent need to
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develop more clinically relevant models. To date based on basic studies, we have assembled the concept of stem cell-derived hepatocyte. However, this conclusion may be premature. Indeed, the question of whether the produced cells to date are true hepatocytes has not been well addressed. In this case, one should carefully evaluate crucial hepatocyte-defining enzymatic properties. Thus, there is a necessity to establish a standard criterion for defining a true human stem cell-derived hepatocyte. It is essential to understand that the definition of an authentic hepatocyte should not be limited to qualitative assays but has to include a quantitative analysis of enzymatic activities, which allows direct comparison with primary hepatocytes. Our understanding of the complex nature of liver regeneration and the role of the various stem cell compartments in liver repair has reached new levels. We are only now beginning to understand the biology of hepatic differentiation from stem cells. There are still significant clinical hurdles that will need to be overcome if stem cell therapy is to reach the full potential that basic studies have anticipated. The objective is ambitious and the journey is long, but we have to remain hopeful that stem cell-derived hepatocytes can serve in the near future as a source of cells for transplantation medicine and basic studies related to drug discovery. References 1. Lee, W.M. (1993) Acute liver failure. N. Engl. J. Med. 329, 1862–1872. 2. Michalopoulos, G.K. (2007) Liver regeneration. J. Cell Physiol. 213, 286–300. 3. Michalopoulos, G.K. and DeFrances, M.C. (1997) Liver regeneration. Science 276, 60–66. 4. Fisher, R.A. and Strom, S.C. (2006) Human hepatocyte transplantation: worldwide results. Transplantation 82, 441–449. 5. Eleazar, J.A., Memeo, L., Jhang, J.S., Mansukhani, M.M., Chin, S., Park, S.M., Lefkowitch, J.H. et al. (2004) Progenitor cell expansion: an important source of hepatocyte regeneration in chronic hepatitis. J. Hepatol. 41, 983–991. 6. Fotiadu, A., Tzioufa, V., Vrettou, E., Koufogiannis, D., Papadimitriou, C.S., and Hytiroglou, P. (2004) Progenitor cell activation in chronic viral hepatitis. Liver Int. 24, 268–274. 7. Paku, S., Schnur, J., Nagy, P., and Thorgeirsson, S.S. (2001) Origin and structural evolution of the early proliferating oval cells in rat liver. Am. J. Pathol. 158, 1313–1323. 8. Farber, E. (1956) Similarities in the sequence of early histological changes induced in
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Chapter 11 Generation of Hepatocytes from Human Embryonic Stem Cells Neta Lavon Abstract Human embryonic stem cells (HESCs) are pluripotent cells having a self-renewal capacity. These unique characteristics of HESCs allow them to be an unlimited source of cells that was shown to differentiate into many cell types, among them hepatocytes. The creation of hepatocytes in culture will allow us to further understand the mechanisms involved in the embryogenesis of hepatocytes in humans and to study pathologies related to aberrant differentiation of these cells. The resultant hepatocytes may serve as a source of cells for transplantation and as cells for toxicological studies and drug screening. In the past 10 years, since the derivation of HESCs, various protocols for the differentiation of HESCs to hepatic-like cells were published. In this chapter we detail our protocol for differentiating HESCs into hepatic-like cells through embryoid bodies. We further describe the method for the genetic labeling of the hepatic-like cells derived from the HESCs and their isolation by fluorescence-activated cell sorter. We also summarize the published protocols for differentiation of HESCs into hepatic-like cells. Key words: Hepatocytes, liver, endoderm, embryonic stem cells, genetic manipulation.
1. Introduction Human embryonic stem cells (HESCs) are pluripotent cells derived from the inner cell mass of pre-implantation embryos (1, 2). The cells have self-renewal capacity which allows them to proliferate indefinitely in culture. Upon differentiation, it was shown that HESCs may differentiate into many cell types originating from the three embryonic germ layers (3). The unique properties of HESCs make them a valuable source of cells for studying human embryogenesis, cell therapy, and as a matrix for drug and toxicological screening (5). Hepatocytes are among the many cell types derived from HESCs. The shortage in hepatocytes for clinical applications causes a vast interest in HESCs as a source for P. Maurel (ed.), Hepatocytes, Methods in Molecular Biology 640, DOI 10.1007/978-1-60761-688-7_11, © Springer Science+Business Media, LLC 2010
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human hepatocytes. See also Chapters 8, 9, 10, and 29 of the present volume. Since the first report of differentiated HESCs expressing albumin (3), many protocols aiming to derive hepatocytes from HESCs were published (4). These protocols used various methods of differentiation, induction, and selection of hepatocytes. In order to properly use HESCs as a source of hepatocytes few major issues need to be solved. The differentiation of HESCs is heterogeneous; there is a need to enrich the specific population of hepatocytes among the other cell types and to sort them out of all the cells. Since many of the genes expressed in the liver are expressed in other tissues as well, only a subpopulation of cells that expresses several hepatic genes will be characterized as hepatocytes. Moreover, to create functional hepatocytes, there is a need to cause the hepatocytes to mature and resemble adult hepatocytes. To characterize cells as hepatocytes we should state their developmental stage, since embryonic, fetal, and adult hepatocytes differ in their gene expression and functionality. We are aiming to mimic the developmental processes of embryogenesis in culture in order to efficiently differentiate HESCs into hepatocytes. These processes are mainly known from mouse studies and the in vitro differentiation of the HESCs will allow the study of the mechanisms in human embryogenesis. This research may also aid in the diagnosis and treatment of liver-associated congenital pathologies. HESCs grown in suspension culture tend to aggregate and form spheroid clumps of cells called embryoid bodies (3). It was shown that the embryoid bodies (EBs) are comprised of differentiated cells expressing markers of various cell types originating from the three embryonic germ layers. With time, the EBs mature by the process of differentiation and cavitations. Many cell types are revealed upon dissociation and plating of the EBs as a monolayer (3). In order to enrich a subset of cells within the EBs, it was shown that addition of various growth factors facilitates their differentiation into specific cell types (6). We have demonstrated that HESCs can spontaneously differentiate into hepatic-like cells (7). Using genetic manipulation, the hepatic cells were labeled and further isolated. The hepatic cells were characterized by their expression profile for their phenotype. We showed that the hepatic cells appeared to develop in a niche next to cardiac mesodermal cells and acidic fibroblast growth factor (aFGF) seemed to play a role in this interaction. Differentiation of HESCs into hepatic cells was demonstrated by other groups as well. In Table 11.1 we have summarized the published protocols for the differentiation of HESCs into hepatic cells and their characteristics (7–22). Most of the early protocols for differentiating HESCs into hepatocytes used the EBs in order to cause the HESCs to differentiate into hepatic-like cells (7, 9, 12, 13, 18–20, 22). Some of the protocols further dissociated the EBs to allow the expansion of the hepatic-like cells. To increase
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Table 11.1 Differentiation potential of HESCs into hepatic cells Protocol for differentiation
Expression by RNA
Expression by protein
Spontaneous: 20–30 days old EBs + Genetic labeling Insulin, Dex. – EBs to mono. on collagen type I
AFP, ALB, APOA4, ALB, AFP APOB, APOH, FGA, FGG, FGB, ALB, AAT ALB
Na butyrate and DMSO – EBs/mono. + HCM
ALB, AAT, AGRP, GATA4, HNF4, TTR, CEBPA, CEBPB
FGF4, HGF, 7–14 days old EBs in serum free medium to mono. on collagen type I
Further characterization R FACS of Alb-eGFP 7 cells Urea synthesis
20
ALB, AAT, CK8, CK18, CK19
CYP1A2 activity, PAS
18
AFP, ALB, CK18, CK19, GATA4, HNF3B, HNF1, CYP1A1, CYP1A2, CYP2B6, CYP3A4
ALB, HNF1, CK18, HNF3B, ASPGR1
Urea synthesis, ICG, PROD and CYP2B6
19
5 days old EBs to collagen type I 3D scaffold, aFGF, HGF, OSM, Dex. (23d)
HNF3B, AFP, TTR, AAT, CK8, CK18, CK19, ALB, CYP7A1, TDO, TAT, G6P
ALB, AFP, CK18
Urea synthesis PAS, ICG, EM
9
– 5 days old EBs to PAUcoated nonwoven PTFE fabric + bFGF, variant HGF, DMSO, Dex.
ALB
EM, urea synthe- 22 sis, lidocaine, and ammonia metabolism
Mono. on MEF ES media: two changes of media over 18–30 days
AAT, LFABP, HNF3B, GSTA1, GSTM1 CK18, AFP
Morphology, PAS, 21 GST catalytic activity
Mono. no feeders, UM ES medium + DMSO (7d), HCM, HGF, OSM (9d)
AFP, TTR, HNF4A, AAT, ALB, TDO, CEBPA
AFP, HNF4A, ALB, SOX17, SOX7, ECAD, CMET
Morphology, ICG, 16 PAS, CYP3A4 activity
Mono. Serum free medium + Act A (3d), HCM + FGF4, BMP2 (5d), HCM + HGF, OSM, DEX
AFP, ALB, CK8, CK18, G6P, AAT, HNF4A, PEPCK, TDO, TAT, CYP7A1, CYP3A4, CYP2B6
SOX17, CK7, PAS, ICG, LDL, 11 CK8, CK18, PROD, Cells CK19, AAT, ALB, infected by hepAFP atitis, ∗ Transplantation to mice
Mono. on MEF, ES media: two changes of media over 18–30 days
CYP1B1, RXR, OATPA, CYP1A2, MRP2, HNFs, CEBPs, CYP3A4/3A7 APOE
Variability of differentiation among HESC lines
Insulin, Dex. – EBs to mono. on collagen type I + Genetic labeling
AAT, ALB, TAT, CYPs, ARG, TF, G6P, early TFs (HNFs, CEBPs. . .)
13 PAS, ICG, CYP1A2, UREA synthesis ∗ Transplantation to mice
AFP, ALB, AAT, CK18
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Table 11.1 (continued) Protocol for differentiation
Expression by RNA
Expression by protein
Further characterization R
Mono. on Matrigel + aFGF, FGF4, HGF, ITS, OSM, Dex. (28d)
CKs, TTR, AFP, TDO, TAT, G6P, HNFs, CEBPs, CYP7A1
CK18, ALB, HepPar1, AFP,
Morphology, Urea synthesis, TEM, PAS, ICG, LDL
10
Act A + Na Butyrate (3–5d), DMSO (7d), HGF + OSM (7d)
Bra, GSC, SOX17, HNFs, AFP, ALB, TAT, TTR, TDO, APOF, CK7
HNFs, AFP, ALB, AAT, cMET, Bra, CXCR4, HepPar1, CKs, CD13, CPR, PXR, CYP3A
Morphology, PAS, CYP3A4 activity, Fibrinogen, and Fibronectin secretion
15
Low/mid serum + Act A (5d) on collagen + FGF4, HGF (3d) minimal medium + BSA, FGF, HGF (3d) HCM + HGF, FGF4, OSM, Dex. (9d)
AFP, ALB, AAT, CYP3A4, CYP7A1
SOX17, HNF3B, GATA4, HNF4A, AFP, CD26, ALB, AAT, CXCR4
PAS, ICG ∗ Transplantation to mice
8
Co-culture with M15 cells expressing WT1: High glucose + Act A, PI3K inhibitor (10d), Dex. HGF (40d)
AFP, ALB, CYP7A1, CK7, CK18, CK19, SOX17, CYP3A4, OATP1B1
AFP, ALB
PAS, EM
24
8 days old EBs to mono. on Gelatin + aFGF (13d) + Genetic labeling Mono. on Matrigel low serum + Act A + HGF, + Genetic labeling
Exon array analysis: 8d AFP, ALB EBs and AFP-GFP+/AFP+: EpCAM, FGFR4, HAVCR1 AFP, TAT,GATA4, ALB, AFP, ALB, ECAD, TDO SOX17
Morphology: resembling hepatocytes and bile duct units
12
17
Differentiation: EBs – embryoid bodies, Dex. – dexamethasone, Mono. – monolayer, DMSO – dimethyl sulfoxide, HCM – hepatocyte culture medium, FGF – fibroblast growth factor, HGF – hepatocyte growth factor, OSM – oncostatin M, PAU – Poly-amino-urethane, PTFE – polytetrafluoroethylene, UM – unconditioned, BMP – Bone morphogenetic, Act. A – Activin A, PI3K – phosphatidylinositol 3-kinase. Molecular markers: AFP – alpha fetoprotein, ALB – albumin, APO – apolipoprotein, FG – fibrinogen, AAT – alpha-1-antitrypsin, HNF – hepatocyte nuclear factor, TTR – transthyretin, CEBP – enhancer binding protein, CK – cytokeratin, CYP – cytochrome P450, TDO – tryptophan-2,3-dioxygenase, TAT – tyrosine aminotransferase, G6P – glucose-6-phosphatase, ASPGR1 – asialoglycoprotein receptor. LFABP – liver fatty acid binding protein, GST – glutathione transferase, SOX – SRY (sex-determining region Y) – box, CAD – cadherin, PEPCK – phosphoenolpyruvate carboxykinase, RXR – retinoid X receptor, OATPA – solute carrier organic anion transporter family, TF – transferrin, Bra – brachyury, CXCR4 – chemokine (C-X-C motif) receptor, CPR – cytochrome P450 reductase. Functional assay: FACS – fluorescence-activated cell sorting, PAS – periodic acid Schiff staining for glycogen, ICG – indocyanine green, PROD – pentoxyresorufin assay, EM – electron microscopy.
the efficiency of the differentiation of HESCs to hepatic-like cells, there is a need to develop a protocol of monolayer differentiation. The protocol will allow the process of differentiation to be repetitive, allowing equal exposure of the cells to matrices and will ease the scale up the procedure. In 2005, D’Amour et al.
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showed that adding activin A to a monolayer of HESCs yields efficient differentiation to definitive endoderm (23). This protocol was further modified by various groups in order to derive hepatic-like cells from the cells of the definitive endoderm (8, 11, 15, 17, 24). These protocols use various soluble substances in the media such as insulin, dexamethasone, sodium butyrate, and dimethyl sulfoxide (DMSO). They also use a sequential addition of growth factors such as hepatocyte growth factor (HGF), aFGF, bFGF, FGF4, and bone morphogenetic protein 2 (BMP2). Sequential media were used varying between low serum for the initial specification of the definitive endodermal cells and hepatocyte culture media for the subsequent maturation and expansion of the hepatic-like cells. Various matrices were used to plate the cells in order to mimic the extracellular interactions of the hepatocytes such as collagen type I, matrigel, and poly-aminourethane-coated fabric. The resultant cells were morphologically similar to primary hepatocytes and the cells expressed most of the fetal liver-associated proteins and some of the genes related to adult fully matured functional hepatocytes. Some protocols further characterized the cells and showed glycogen storage, albumin and urea synthesis, enzymatic activity of drug-metabolizing enzymes, and transplantation into damaged livers. In the above studies, the hepatic cells exhibit characteristics of mature hepatocytes but also retain some immature characteristics such as low levels of the drug-metabolizing enzymes and expression of the fetal liver protein, alpha fetoprotein. Further investigation is required to examine whether these hepatic-like cells derived in vitro from HESCs can be matured in culture or whether the final maturation requires an in vivo environment. In this chapter we will detail our protocol for spontaneous differentiation of HESCs into hepatic-like cells using EBs. Detailed below is our protocols for the creation of HESC lines expressing the enhanced green fluorescent protein (eGFP) reporter gene driven by hepatic promoter, their differentiation through EBs, and the further isolation of the eGFP-labeled hepatic cells using fluorescence-activated cell sorter (FACS).
2. Materials 2.1. HESCs Medium
1. 500 ml KnockoutTM DMEM-optimized Dulbecco’s modified Eagle’s medium for ES cells (Gibco BRL). 2. 75 ml KnockoutTM SR-serum free formulation (Gibco BRL) (see Note 1). 3. 6 ml non-essential amino acids ×100 (Gibco-BRL).
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4. 6 ml L-glutamine ×100 (200 mM) (Gibco-BRL) (final concentration 2 mM). 5. 3 ml insulin–transferrin–selenium (ITS) (Gibco-BRL). 6. 3 ml penicillin (10,000 U/ml) and streptomycin (10 mg/ml) (Gibco BRL). 7. 60 μl β-mercaptoethanol 1 M stock solution (final concentration 0.1 mM). 8. 1.2 ml human basic fibroblast growth factor (bFGF) stock solution (Gibco BRL) (see Note 2), (final concentration: 4 ng/ml). 9. Store the medium at 4◦ C and warm to 37◦ C before use. 10. Trypsin–EDTA (0.25% trypsin and 0.05% EDTA in Puck’s saline A (Gibco BRL). 11. Antibiotic (Greiner). 2.2. EBs Medium
1. The same as HESCs medium but without the bFGF. 2. Store the medium at 4◦ C and warm to 37◦ C before use.
2.3. Murine Embryonic Fibroblasts (MEFs) Medium
1. 500 ml Dulbecco’s modified Eagle’s medium with high glucose (4.5 g/l) and L-glutamine (Sigma) 2. 50 ml Fetal calf serum (FCS) (Biological Industries) 3. 5 ml Penicillin (10,000 U/ml) and (10 mg/ml) X100 stock (Gibco BRL).
streptomycin
4. Store the medium at 4◦ C and warm to 37◦ C before use. 2.4. Antibiotic-Resistant MEF
1. Prepared from DR4 mice containing resistance genes for neomycin puromycin, hygromycin and 6-thioguanine (Jackson Laboratories).
2.5. Transfection Medium
1. Transfection medium used is ExGen 500 (Fermentas).
3. Methods 3.1. Establishment of HESC Lines Stably Transfected by Reporter Gene Under the Control of Hepatic Promoter (e.g., Albumin-eGFP)
The plasmid DNA that is about to be transfected into the cells should be linearized in order to increase the efficiency of the plasmid DNA integration into the cells DNA and in order to avoid spontaneous breaks within the DNA sequence of our interest. The restriction enzyme should not cut within the DNA sequence of the reporter gene and its promoter (Albumin-eGFP) and should not cut within the gene that confers the antibiotic resistance
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3.1.1. Preparation of Plasmid DNA for Stable Transfection
3.1.2. Transfection of HESCs by Albumin-eGFP Using ExGen 500
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for the transfected cells. Verify that the plasmid was completely linearized and precipitate the plasmid DNA. Resuspend the linearized plasmid in sterile double distilled water to a concentration of 1 μg/μl. 1. Plate the HESCs on a gelatinized 6-well dish containing antibiotic resistant MEF. The density of the cells should be between 20 and 40% of confluence (see Note 3). 2. One hour prior to transfection, change the HESCs medium to 1 ml of fresh HESCs medium per well. 3. For each well of a 6-well tissue culture dish, prepare an Eppendorf tube containing 4 μg of DNA in 100 μl of 150 mM NaCl, vortex briefly, and spin down. 4. Add 13 μl ExGen 500 to each tube (not reverse order) and vortex immediately for 10 s. 5. Allow to stand for 10 min at room temperature. 6. Add 100 μl of ExGen/DNA mixture to each well. 7. To equally distribute the complexes on the cells, gently rock the plate to and fro. 8. Centrifuge the 6-well tissue culture dish in a swinging bucket centrifuge for 5 min at 280×g. 9. Incubate at 37◦ C, 5% CO2 for 30 min. 10. Wash twice with PBS, add HESCs medium, and return back to the incubator. 11. Two days later, selection can be initiated with the appropriate antibiotic. 12. After 2 more days, massive cell death should be visible. Every 2–3 days wash with PBS and replace with fresh HESCs medium with selection antibiotics (see Note 4). 13. After 5–10 days antibiotic-resistant colonies should appear. Using mouth pipette transfer each new colony to a separate well on a gelatinized 12-well dishes containing antibioticresistant MEFs with HESCs medium. Grow the cells in HESC medium with the selection antibiotics, to ensure that the integrated DNA is not lost during the passages of the cells (see Note 5). 14. Allow the separated colonies to expand and split the well into three wells to establish a clone from each colony. 15. Extract DNA from one well of each clone and test the clone for the presence of the exogenous DNA segment by PCR. 16. Test the cells for eGFP expression under the microscope. No eGFP signal should appear in non-differentiated HESCs. If positive for eGFP, do not use this specific clone due to leakiness of the eGFP expression.
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3.2. Differentiation of HESCs into Hepatic Cells by EBs Formation
1. Wash a confluent 10 cm plate of HESCs with PBS and harvest the cells by adding 1 ml of Trypsin–EDTA for 5 min at room temperature (see Note 6). 2. To wash, add 5 ml of MEFs medium, pipette up and down, transfer the cells to a 15 ml conical tube, and centrifuge at 600×g for 5 min. 3. Aspirate the supernatant and gently resuspend the pellet in EBs medium by pipetting up and down with a 1 ml pipette. 4. Transfer 4–5×106 cells from the cell suspension to a sterile (UV-irradiated) nonadherent 90 mm dish containing 15 ml of EBs medium with antibiotic (see Note 7). 5. Incubate the plate at 37◦ C at 5% CO2 for 20 days. 6. For the first 2 days at least, avoid moving the plate as much as possible. Then, every second day, half of the medium is carefully removed from the plate in a way that minimizes the aspiration of the EBs with the medium. To do so, tilt the plate at an angle of 45◦ . This will allow most of the EBs to sink to the bottom of the plate allowing you to aspirate the uppermost medium almost free of EBs. Then refill the plate with fresh EBs medium containing selection antibiotic.
3.3. Sorting of eGFP-Labeled Hepatic Cells Using FACS
1. Collect the EBs and the medium from a 90 mm plate of 20 days old EBs and transfer it all into 50 ml tube. Centrifuge for 5 min at 600×g. 2. Wash once with PBS. 3. Harvest the cells by adding 3 ml of Trypsin–EDTA for 5 min at 37◦ C at 5% CO2. Twice during the incubation period, take the tube out of the incubator, swirl gently, and place back in the incubator. 4. Add 10 ml of MEF medium and pipette up and down several times in order to further dissociate the EBs, then centrifuge at 600×g for 5 min. 5. Carefully aspirate the MEFs medium and add 200 μl of PBS. 6. Sort the eGFP positive cells by FACS (see Note 8).
4. Notes 1. The serum is light sensitive and should be stored in the dark, it is recommended to store the HESCs medium wrapped with aluminum foil. 2. The bFGF is crucial for the maintenance of the HESCs thus we should avoid any degradation of the bFGF. Prepare the
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stock solution (2 ng/μl) according to the data sheet and aliquot it into Eppendorf tubes of 0.3, 0.6, and 1.2 ml. To prepare a new HESCs medium, thaw the aliquot in room temperature for the shortest period needed and immediately add to the medium. If you are using less than the full amount of medium detailed above, per week, prepare half or third of the medium and use the smaller bFGF aliquots. Do not refreeze the bFGF. 3. This density is in order to allow having large number of small colonies plated uniformly over the well, on the following day. 4. Different HESC lines vary in their intrinsic resistance to antibiotic, thus for each cell line the optimal concentration of antibiotic that causes all non-transfected cells on a plate die should be empirically determined. 5. In case that the transfection does not yield enough colonies it might be related to the purity level of the plasmid. Try another cleaning step for the plasmid before or after the linearization and quantify the concentration again. 6. It is preferred to start the EBs with clusters of cells and not with single cell suspension. Thus, trypsinize the cells for the shortest time possible, once you see the cells detach from the plate add MEFs medium and collect the cells. 7. In case that the cells adhere to the plate this adversely affects the formation of the EBs. Thus, we recommend using the exact catalog numbers detailed above, and do not forget to UV sterilize them. If problems persist, use the ultra-low attachment surface dishes (Corning 3262). 8. With Albumin–eGFP ∼5% of the cells are expected to be eGFP positive while using this protocol. The sorted population of cells can be further characterized by microarray analysis or further grown if the sorting is under sterile conditions. References 1. Reubinoff, B.E., Pera, M.F., Fong, C.Y., Trounson, A., and Bongso, A. (2000) Embryonic stem cell lines from human blastocysts: somatic differentiation in vitro. Nat. Biotechnol. 18, 399–404. 2. Thomson, J.A. et al. (1998) Embryonic stem cell lines derived from human blastocysts. Science 282, 1145–1147. 3. Itskovitz-Eldor, J. et al. (2000) Differentiation of human embyronic stem cells into embryoid bodies comprising the three embryonic germ layers. Mol. Med. 6, 88–95.
4. Lavon, N. and Benvenisty, N. (2005) Study of hepatocyte differentiation using embryonic stem cells. J. Cell Biochem. 96, 1193– 1202. 5. Schleger, C., Krebsfaenger, N., Kalkuhl, A., Bader, R., and Singer, T. (2001) Innovative cell culture methods in drug development. Altex 18, 5–8. 6. Schuldiner, M., Yanuka, O., Itskovitz-Eldor, J., Melton, D.A., and Benvenisty, N. (2000) Effects of eight growth factors on the differentiation of cells derived from human
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Lavon embryonic stem cells. Proc. Natl. Acad. Sci. USA 97, 11307–11312. Lavon, N., Yanuka, O., and Benvenisty, N. (2004) Differentiation and isolation of hepatic-like cells from human embryonic stem cells. Differentiation 72, 230–238. Agarwal, S., Holton, K.L., and Lanza, R. (2008) Efficient differentiation of functional hepatocytes from human embryonic stem cells. Stem Cells 26, 1117–1127. Baharvand, H., Hashemi, S.M., Kazemi Ashtiani, S., and Farrokhi, A. (2006) Differentiation of human embryonic stem cells into hepatocytes in 2D and 3D culture systems in vitro. Int. J. Dev. Biol. 50, 645–652. Baharvand, H., Hashemi, S.M., and Shahsavani, M. (2008) Differentiation of human embryonic stem cells into functional hepatocyte-like cells in a serum-free adherent culture condition. Differentiation 76, 465–477. Cai, J. et al. (2007) Directed differentiation of human embryonic stem cells into functional hepatic cells. Hepatology 45, 1229– 1239. Chiao, E. et al. (2008) Isolation and transcriptional profiling of purified hepatic cells derived from human embryonic stem cells. Stem Cells 26, 2032–2041. Duan, Y. et al. (2007) Differentiation and enrichment of hepatocyte-like cells from human embryonic stem cells in vitro and in vivo. Stem Cells 25, 3058–3068. Ek, M. et al. (2007) Expression of drug metabolizing enzymes in hepatocyte-like cells derived from human embryonic stem cells. Biochem. Pharmacol. 74, 496–503. Hay, D.C. et al. (2008) Efficient differentiation of hepatocytes from human embryonic stem cells exhibiting markers recapitulating
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liver development in vivo. Stem Cells 26, 894–902. Hay, D.C. et al. (2007) Direct differentiation of human embryonic stem cells to hepatocyte-like cells exhibiting functional activities. Cloning Stem Cells 9, 51–62. Ishii, T. et al. (2008) Effects of extracellular matrixes and growth factors on the hepatic differentiation of human embryonic stem cells. Am. J. Physiol. Gastrointest. Liver Physiol. 295, G313–G321. Rambhatla, L., Chiu, C.P., Kundu, P., Peng, Y., and Carpenter, M.K. (2003) Generation of hepatocyte-like cells from human embryonic stem cells. Cell Transplant. 12, 1–11. Schwartz, R.E. et al. (2005) Defined conditions for development of functional hepatic cells from human embryonic stem cells. Stem Cells Dev. 14, 643–655. Shirahashi, H. et al. (2004) Differentiation of human and mouse embryonic stem cells along a hepatocyte lineage. Cell Transplant. 13, 197–211. Soderdahl, T. et al. (2007) Glutathione transferases in hepatocyte-like cells derived from human embryonic stem cells. Toxicol. In Vitro 21, 929–937. Soto-Gutierrez, A. et al. (2006) Differentiation of human embryonic stem cells to hepatocytes using deleted variant of HGF and poly-amino-urethane-coated nonwoven polytetrafluoroethylene fabric. Cell Transplant. 15, 335–341. D’Amour, K.A. et al. (2005) Efficient differentiation of human embryonic stem cells to definitive endoderm. Nat. Biotechnol. 23, 1534–1541. Shiraki, N. et al. (2008) Differentiation of mouse and human embryonic stem cells into hepatic lineages. Genes Cells 13, 731–746.
Chapter 12 Isolation and Culture of Adult Human Liver Progenitor Cells: In Vitro Differentiation to Hepatocyte-Like Cells Sabine Gerbal-Chaloin, Cédric Duret, Edith Raulet, Francis Navarro, Pierre Blanc, Jeanne Ramos, Patrick Maurel, and Martine Daujat-Chavanieu Abstract Highly differentiated normal human hepatocytes represent the gold standard cellular model for basic and applied research in liver physiopathology, pharmacology, toxicology, virology, and liver biotherapy. Nowadays, although livers from organ donors or medically required resections represent the current sources of hepatocytes, the possibility to generate hepatocytes from the differentiation of adult and embryonic stem cells represents a promising opportunity. The aim of this chapter is to describe our experience with the isolation from adult human liver and culture of non-parenchymal epithelial cells. Under appropriate conditions, these cells differentiate in vitro in hepatocyte-like cells and therefore appear to behave as liver progenitor cells. Key words: Liver, progenitor cell, differentiation, hepatocyte-like cell.
1. Introduction Obtaining highly differentiated normal human hepatocytes is critical for basic research in different areas including liver physiopathology (1, 2), pharmacology (3, 4), toxicology (5), and virology (6, 7). In addition, liver biotherapy based on hepatocyte or progenitor transplantation (8–11) and bioartificial liver systems (12–17) represents an attractive approach to correct inborn errors of metabolism and/or to bridge patients with fulminant hepatic failure or serious chronic diseases to transplantation or to spontaneous recovery. Although isolation of hepatocytes from the P. Maurel (ed.), Hepatocytes, Methods in Molecular Biology 640, DOI 10.1007/978-1-60761-688-7_12, © Springer Science+Business Media, LLC 2010
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human liver no longer represents a challenge, the availability and supply of human liver of adequate quality for this purpose has become a real problem within the last 10 years. Indeed, surgical resections are more and more restricted in size and livers from organ donors that are refuted for transplantation are generally of poor quality (high level of steatosis, for instance). It has therefore become mandatory to develop new alternative sources of human hepatocytes. The possibility to generate a wide diversity of tissuespecific cells from the differentiation of adult and embryonic stem cells, including hepatocytes, represents a promising opportunity (18, 19). See also Chapters 8–11. After partial hepatectomy or during acute or chronic failure, whatever be the etiology (toxic compounds or viruses) the liver is able to restore or maintain its homeostasis. This process is dependent on either the proliferation of hepatocytes (20, 21) or, when proliferation is impaired, the emergence of a heterogeneous population of small poorly differentiated progenitors, named oval cells in rodents (22) and liver progenitors cells (LPCs) in humans (23, 24). These bipotent progenitors, which originate from the portal or periportal zones of the liver, invade the parenchyma generally in the form of neoductules and differentiate into mature hepatocytes and cholangiocytes. Oval cells and LPCs co-express hepatic and biliary markers including, notably, albumin, cytokeratins 8/18 (CK8/18), and CK 7/19, respectively, and share some phenotypic characteristics with bipotent fetal hepatoblasts such as albumin, α-fetoprotein, CK19, and CK8/18, and hematopoietic stem cells such as c-kit and CD34 (25). In humans, the number of LPCs increases with the severity of liver diseases and correlates with the degree of inflammatory infiltrate (26, 27). Several groups isolated and characterized various subpopulations of putative LPCs from normal (28–35) or diseased (36) human liver. We recently isolated a population of nonparenchymal epithelial (NPE) cells from the liver of patients exhibiting no sign of liver failure, suggesting that such cells are present in normal human liver (37). These cells were suspected to represent LPCs because they exhibit a marked proliferative potential and, when cultured under appropriate conditions, differentiate into hepatocyte-like cells that express intermediate hepatobiliary and fetal/mature hepatic phenotype. The aim of the present chapter is to describe our experience with the isolation and characterization of NPE cells from adult human liver.
2. Materials 2.1. Human Liver Samples
1. The use of human liver samples for hepatocyte preparation for scientific purposes has to be approved by National Ethics Committees or by other regulatory authorities.
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2. Donor livers are available when considered by surgeons to be unsuitable for transplantation. In this case, several encapsulated fragments (right lobe: segments VI and VII; left lobe: segments II and III; and dome: segments I, IV, and VIII) can be used separately. 3. Lobectomies or smaller fragments resected for medical purposes are also suitable. In general, the pathologies requiring such resections include primary tumor, metastasis, adenoma, angioma, or hydatid cyst. In this case, the liver sample is first sent to the anatomopathologist who resects the tumor or lesion and the surrounding tissue for further examination. This resection must be carried out under sterile conditions. If possible, the remaining encapsulated tissue is sent to the laboratory for hepatocyte and progenitor preparation. No information on the patients is available in the laboratory, apart from sex, age, medical treatment, and the reason for surgical resection. The patients cannot be identified, directly or through identifiers. Importantly, pathological examination of the surgical specimen is in no way hindered by the procedure used to obtain hepatocytes or progenitors. 4. Written consent of donor family or patients is necessary. 2.2. Materials
1. Surgery equipments (scissors, scalpels, forceps, etc.) 2. Standard equipment for cell culture: laminar-flow microbiology safety hood, CO2 incubator, low-speed centrifuge, rotary agitator, phase-contrast optical microscope. 3. Culture dishes (Biocoat collagen I). 4. Nylon filter (250 mesh) sterilized by autoclaving. 5. Perfusion vessel (Pyrex or stainless steel), rubber tubing (hoses), Teflon terminal tip, and stoppers that can be sterilized by autoclaving. 6. Thermostated water bath for buffers and solutions. Heater for perfusion vessel. 7. Pump for tissue perfusion with flux adjustment between 10 and 500 mL/min. 8. Pump for liquid-aspiration device (for removal of liquid waste). 9. Waste collectors for tissues, liquids (blood, perfusion effluents), and other solid materials (undigested tissue, gloves, Whatman paper, aluminum foil, etc.). 10. Decontamination reservoir (50 L) for dissection instruments, perfusion vessel, tubing, and other reusable materials. 11. Forty-micrometer cell strainer (BD Biosciences).
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12. Zeiss AxioImager Z1 upright microscope (Carl Zeiss SAS, Le Pecq, France). 13. Fluorescence microscope (Leica Microsystem, Rueil Malmaison, France). 14. Metamorph software for image analysis (Universal Imaging Corporation, Downingtown, PA). 2.3. Reagents for Cell Isolation
1. Bovine serum albumin (BSA fraction V), collagenase (C5138), EGTA, ferrous sulfate, selenium acetate, glucose, Hank’s buffered saline solution (HBSS, H6648), HEPES, hydrocortisone, insulin (I1882), linoleic acid–albumin (L9530), MEM alpha, DMEM 1 g/L glucose, MCDB-201, ITS+1, nicotinamide, penicillin/streptomycin, thyrotropinreleasing hormone, acid ascorbic phosphate, dimethyl sulfoxide (DMSO) (Sigma Saint Quentin Fallavier). 2. Epidermal growth factor (EGF), hepatocyte growth factor (HGF), fibroblast growth factor 4 (FGF4) (PeproTech France, Neuilly sur Seine). 3. Fetal bovine serum, Fungizone, phosphate buffered saline, and trypsin (2.5%) (Invitrogen, Cergy-Pontoise). 4. Zinc sulfate (Fisher Scientific, Elancourt, France). 5. OptiprepTM (d = 1.12, 25% iodixanol) (Abcys, Paris). 6. Phagosurf DD (Phagogene DEC). 7. Matrigel (BD Bioscience, Le Pont-de-Claix).
2.4. Buffers and Solutions for Cell Isolation
Buffers and solutions are prepared with deionized water, sterilized by passing through 0.22-μm filters. 1. HEPES [N-(2-hydroxyethyl)piperazine-N’-(2-ethanesulfonic acid)] buffer: 10 mM HEPES, 136 mM NaCl, 5 mM KCl, 0.5% glucose, pH 7.6. 2. EGTA [ethylenebis(oxyethylenenitrilo)tetraacetic solution: 0.5 mM EGTA in HEPES buffer.
acid]
3. Antibiotic solution: 10,000 U/mL penicillin, 10 mg/mL streptomycin. Add 10 mL/L to HEPES buffer and to the EGTA solution. 4. Fungizone. Add 3 mL/L of 250 μg/mL Fungizone to HEPES buffer and EGTA solution. 5. Calcium chloride. Add 10 mL/L of 70 mM CaCl2 solution to HEPES buffer for collagenase solution. 6. BSA–HEPES solution: dissolve 5 g of BSA (fraction V)/L of HEPES buffer. Supplement with antibiotics and Fungizone as indicated above. 7. Optiprep is diluted (41.7%, v/v) with DMEM.
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8. Phagosurf DD (Phagogene DEC), 0.25% solution in tap water: this product inactivates viruses including hepatitis B virus and HIV and other pathogens, in less than 12 h. 2.5. Collagenase Solution
1. Prepare 1 L of HEPES buffer supplemented with antibiotics, Fungizone, and 10 mL of 70 mM CaCl2 and divide it into two parts of 250 and 750 mL. 2. Dissolve 500 mg collagenase in the 250 mL aliquot of this buffer and sterilize by passing through 0.45- and 0.22-μm filters if necessary (see Note 1). Because of the cost of collagenase, this solution should be prepared only when perfusion of the tissue has been shown to proceed correctly (see Section 3.1.3). 3. Add the filtered collagenase solution to the 750 mL aliquot of HEPES buffer. This solution of collagenase will be used to dissociate the liver tissue.
2.6. Cell Culture Media
1. MEM alpha supplemented with 10% fetal bovine serum, 20 ng/mL HGF, 10 ng/mL EGF, 25 mM glucose, 1 μM thyrotropin-releasing hormone, 1 μM hydrocortisone, 10μg/mL insulin, 50 μg/mL albumin–linoleic acid, 0.1 μM selenium acetate, 0.5 μg/mL ferrous sulfate, 0.75 μg/mL zinc sulfate, 10 mM nicotinamide, streptomycin, and penicillin. This medium is referred to thereafter as the expansion medium (ExpM) (36). 2. Differentiation medium (DM): 60% low-glucose DMEM, 40% MCDB-201 supplemented with ITS+1, 1 μM dexamethasone, 0.1 mM ascorbic acid 2-phosphate, 20 ng/mL HGF, 20 ng/mL FGF-4 penicillin, and streptomycin (38). 3. DM is used in the absence or the presence of 0.3 mg/mL Matrigel.
2.7. Buffers Solutions and Materials for Cell Differentiation Analysis
1. Formaldehyde (3%) and 0.05% glutaraldehyde in 60 mM PIPES, 25 mM HEPES, 10 mM EGTA, 10 mM MgCl2 , pH 6.9. 2. Triton X-100 (0.2%) in TBS. 3. Blocking solution for immunofluorescence analysis: PBS, 1% FCS. 4. Hoechst 33342. 5. Trizol reagent (Invitrogen) for RNA extraction. 6. Random hexaprimer and Moloney murine leukemia virus reverse transcriptase kit (Invitrogen) for reverse transcription of RNA. 7. LightCycler 480 SYBR Green I Master kit for quantitative PCR (Roche Applied Science, Meylan, France).
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8. LightCycler 480 real-time PCR system (Roche). 9. Primers. Whenever possible, primer pairs are designed from different exons to avoid false positives due to DNA contamination. Primer pairs used in this work are as follows: Albumin: sense 5 -TGCCTGCCTGTTGCCAAAGC; antisense 5 -TTGGCAAGGTCCGCCCTGTC α1-antitrypsin: sense 5 -CAACCTGGCTGAGTTCGCCT; anti-sense 5 -CTCGCTGAGGAACAGGCCAT Apo-H: sense 5 -GCACTGAGGAAGGAAAATGG; anti-sense 5 -GGCCATCCAGAGAATATCCA TDO: sense 5 -CCCGTAGAAGGCAGCGAAGA; anti-sense 5 -TCGGTGCATCCGAGAAACAA CPS1: sense 5 -TGTCCATTGGTCAGGCTGGA; anti-sense 5 -GCCACCCATGCCCAGAATTA G6P: sense 5 -CGTGATCGCAGACCTCAGGA; anti-sense 5 -GGCTCCCTGGTCCAGTCTCA TAT: sense 5 -AGGCCAGGTGGTCTGTGAGG; anti-sense 5 -AGGGGTGCCTCAGGACAGTG CYP3A4: sense 5 -GCCTGGTGCTCCTCTATCTA; anti-sense 5 -GGCTGTTGACCATCATAAAAG CYP2B6: sense 5 -ATGGGGCACTGAAAAAGACTGA; antisense 5 -AGAGGCGGGGACACTGAATGAC CYP1A1: sense 5 -TCCGGGACATCACAGACAGC; antisense 5 -ACCCTGGGGTTCATCACCAA PXR: sense 5 -TCCGGAAAGATCTGTGCTCT; anti-sense 5 -AGGGAGATCTGGTCCTCGAT AhR: sense 5 -TGGACAAGGAATTGAAGAAGC; anti-sense 5 -AAAGGAGAGTTTTCTGGAGGAA HNF4A1: sense 5 -ACATGGACATGGCCGACTAC; antisense 5 -CGAATGTCGCCGTTGATC. 2.8. Antibodies
1. Antibodies directed against albumin: (i) goat anti-human albumin FITC conjugated (Bethyl Laboratory, Montgomery, TX) for immunofluorescence analysis; (ii) and mouse anti-human albumin clone HSA-11 (Sigma) used at 1:1,000 dilution for immunoblotting analysis. 2. Mouse antibodies directed against CK18: clone 5D3 (Lab Vision Products Thermo Fisher Scientific, Fremont USA). 3. Rabbit antibodies directed against vimentin: clone SP20 (Lab Vision Products, Thermo Fisher Scientific). 4. Rabbit antibodies directed against human HNF4α (Santa Cruz). 5. Goat antibodies directed against human fibrinogen (Sigma).
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6. Secondary antibodies: (i) for immunofluorescence F(ab’)2 Alexa488 and 568; (ii) anti-mouse and goat horseradish peroxidase-conjugated secondary antibodies used at 1:10,000 dilution. 7. Chemiluminescent signal detection is performed with the ECL Western Blotting Detection kit (Amersham, England). 8. Virus detection tests: hepatitis C virus (ORTHO HCV 3.0 Elisa test), hepatitis B virus, and human immunodeficiency virus (VIDAS, Biomerieux).
3. Methods 3.1. Preparation of Non-parenchymal Epithelial Cells 3.1.1. Safety Conditions
1. Virological analysis (hepatitis C virus, hepatitis B virus, and human immunodeficiency virus) of the patient from whom the liver sample has been resected must be carried out before or at the time of operation. All laboratory staffs should be vaccinated against hepatitis B virus and clearly informed of the possible risk of infection. 2. Even when the virological analysis is negative, all experimentations with human tissue samples must conform to the safety policies regarding the protection of staff, the containment standard of the equipment, and the laboratory rooms in which tissue processing, isolation, and experimentation on cell cultures are to be performed (European standard containment laboratory type L2). 3. In cases where donor tissue is infected with a hepatotropic virus, isolation and culture must be performed in a containment laboratory type L3. 4. All steps of cell isolation and culture are carried out in a laminar vertical-flow microbiology safety hood to protect not only the staff but also the liver sample and cultures from contamination. Staffs must wear sterile gloves, glasses, masks, and disposable coats and boots. 5. All materials and liquid wastes must be decontaminated prior to discarding or resterilized by autoclaving (for recycled materials). Instruments and materials to be reused are decontaminated by immersion in Phagosurf DD 0.25% solution (final concentration) for 24 h. Liquid wastes are stored in an appropriate reservoir in the presence of Phagosurf DD 0.25% solution for 24 h. Other materials such as used culture dishes are decontaminated by autoclaving before being discarded.
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3.1.2. Liver Perfusion
1. Upon arrival in the laboratory, the liver sample is placed in the perfusion vessel and the edge is carefully examined in order to locate the various vein and artery entries that will be used for perfusion. The volumes indicated below for buffers and solutions are adequate for a sample of approximately 300 g; for smaller or larger samples, these should be modified accordingly. 2. All solutions and buffers are kept at 37◦ C, except for the albumin–HEPES solution used for hepatocyte washings, which is kept at room temperature. 3. The tissue is first washed with 1–2 L HEPES buffer supplemented with antibiotics and Fungizone at a rate of approximately 1 mL/min/g of tissue with no recirculation. During this and further perfusion steps, the cannula is inserted successively in all veins/arteries present on the edge for approximately 30 s each (one vein/artery at a time) (Note 2). 4. The tissue is then perfused with 1 L of EGTA solution supplemented under the same conditions as described above, with no recirculation. 5. The tissue is then perfused with 1 L supplemented HEPES buffer to remove EGTA, under the same conditions as described above. At the end of this step, the reservoir of the perfusion vessel is emptied and washed several times with sterile water. 6. The tissue is then perfused with the collagenase solution under the conditions described above, except that during this step the solution is recirculated and that the rate of perfusion is reduced to 100 mL/min. The duration of this step lasts for a maximum of 20 min.
3.1.3. Non-parenchymal Epithelial Cell Isolation
1. At the end of the collagenase perfusion, the liver sample is transferred into a new stainless steel vessel and the Glisson’s capsule is opened in several places. 2. The tissue is gently disrupted with scissors. 3. The homogenate is complemented with 1–2 L of BSA– HEPES buffer. Steps 1–3 must be carried out as quickly as possible to inactivate collagenase. 4. The homogenate is filtered through a nylon filter (250 mesh). The filter is washed twice with approximately 200 mL of BSA–HEPES solution to collect the cells that are trapped in the undissociated tissue homogenate. Then, the filtrate is distributed into 150-mL centrifuge tubes. 5. Tubes are centrifuged for 5 min at 50×g at room temperature to pellet hepatocytes. For further steps on hepatocyte preparation, see Chapter 23. See Note 3.
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6. The supernatant is centrifuged at 400×g for 10 min at room temperature. See Note 4. 7. The pellet is resuspended in 5–10 mL of DMEM, cells are counted, and the volume is adjusted so that the cell suspension is at 40 million/mL. 8. This suspension is mixed (v/v) with the diluted Optiprep solution (see Section 2.4, step 7). DMEM medium (20% of the total volume of cells plus Optiprep) is gently added at the top of the mixture and centrifugation is performed for 15 min at 500×g without brake at room temperature. 9. Cells at the interface are collected and washed twice in DMEM (200 g for 10 min at room temperature), resuspended in the complete ExpM (described in Section 2.6, step 1) and counted. 10. Cells are plated on collagen-coated dishes at a density of 125,000 cells/cm2 in the ExpM. Culture dishes are placed in an incubator, in a humid atmosphere of air and 5% CO2 at 37◦ C. ExpM is renewed (two-thirds) every 72 h. See Note 5. 3.2. Culture of Non-parenchymal Epithelial Cells
1. After 1–2 weeks, epithelial colonies are observed by phasecontrast microscopy. See Note 6. Culture medium is collected and cells are detached by trypsinization (0.25%). The cell suspension is diluted 10 times with the ExpM and centrifuged (200×g, 5 min, room temperature). 2. The cell pellet is resuspended in ExpM (one-third of which has been collected from the previous step) and cells are plated at a density of 10,000 cells/cm2 . 3. Two-third of the medium is renewed twice a week. 4. When confluent, cells are detached with 0.25% trypsin, washed, counted, plated at a density of 10,000 cells/cm2 , and cultured as described above. 5. After amplification, cells are cultured for differentiation.
3.3. Differentiation of Non-parenchymal Epithelial Cells to Hepatocyte-Like Cells
1. When cells have reached confluence in the ExpM, the medium is changed for the DM. 2. The DM is renewed twice a week and the cultures are maintained for 3–4 weeks. At this time, in our experience, a plateau of differentiation is reached. See Note 7. 3. Typical results on cell morphology and the emergence of hepatocyte phenotypic markers are reported in Figs. 12.1, 12.2, and 12.3 and Table 12.1.
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Fig. 12.1. Morphological aspect of NPE cells before and after differentiation. NPE cells were cultured in the DM for 21 days in the absence or the presence of Matrigel. Cells were examined under phase-contrast microscope. (a) Confluent NPE cells at day 0 (D0) of differentiation; (b) NPE cells after 21 days of differentiation in the absence of Matrigel; (c) NPE cells after 21 days of differentiation in the presence of Matrigel. Cells cultured in the presence of Matrigel exhibit an organization in cord-like structures.
Fig. 12.2. Immunofluorescence analysis of NPE cells after differentiation. NPE cells were cultured in the DM for 21 days in the presence of Matrigel. Cells were fixed and the expression of various markers was analysed by immunofluorescence. A: albumin (arrow head), CK18 (arrow), nucleus (star). B: albumin (arrow head), vimentin (arrow), nucleus (star). C: albumin (arrow head), nucleus (star). D: HNF4 (arrow head). E: nucleus of HNF4 positive cells (arrow head), nucleus of HNF4 negative cells (arrow). Cells exhibit an organisation in cord-like structures.
3.3.1. Indirect Immunofluorescence
1. At the end of the experiment, cells are fixed with 3% formaldehyde and 0.05% glutaraldehyde in 60 mM PIPES, 25 mM HEPES, 10 mM EGTA, 10 mM MgCl2 , pH 6.9 for 15 min at room temperature. 2. Fixed cells are permeabilized with 0.2% Triton X-100 in TBS for 2–5 min and incubated with blocking solution of PBS and 1% FCS for 10 min. 3. Antibodies directed against albumin, CK18, vimentin, or HNF4α and a goat anti-human albumin FITC conjugated are applied to the cells for 1 h at room temperature. 4. After three washes with PBS, cells are incubated with an antirabbit or an anti-mouse Fab Alexa 488 or 568 secondary
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Fig. 12.3. Immunoblotting analysis of NPE cells after differentiation. NPE cells were cultured in the DM for 21 days in the absence or the presence of Matrigel (−MAT, +MAT). At the indicated time points, the medium was collected and renewed. D1–D4 refers to medium collected at day 4 of culture (between days 1 and 4), D11–D14 refers to medium collected at day 14 (between days 11 and 14), etc. The expression of albumin and fibrinogen was assessed by immunoblotting. HHCP: expression of both proteins in the extracellular medium of human hepatocytes in primary culture (between days 1 and 4).
Table 12.1 Expression of various markers in NPE cells before and after differentiation D0
D21 -Matrigel
D21 +Matrigel
ALB
0.6
6.6
AAT
4.5
45
375
ApoH
0
0.5
11.2
Metabolism
TDO CPS1 G6P TAT
0.1 0.37 0.02 0.18
8.8 0.48 3.3 0.06
77 1.19 187.6 10.5
Detoxication
CYP3A4 CYP2B6 CYP1A1
0.2 0.01 210
0.2 0.1 10
2.3 3.5 145
Receptors and TF
PXR AhR HNF4A1
0.7 200 1.1
0.38 400 0.5
2.7 440 30.9
Secreted Proteins
135.9
(% of HHPC)
NPE cells were cultured in the DM for 21 days in the absence or the presence of Matrigel. At day 0 of differentiation (D0) and after 21 days of differentiation, RNA was extracted and analyzed by quantitative RT-PCR. Results are expressed as relative accumulation of mRNA with respect to levels observed in primary human hepatocytes after 3 days in culture, taken arbitrarily as 100.
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antibodies in PBS and 1% FCS for 45 min at room temperature. 5. Nuclei are labeled with Hoechst 33342. 6. Immunofluorescent labeling is examined under a fluorescence microscope and images are analyzed using the Metamorph software. 3.3.2. Immunoblotting
1. Three- to four-day aliquots of culture media are collected during the differentiation process. 2. Albumin and fibrinogen accumulation is analyzed by immunoblotting.
3.3.3. RT-PCR
1. One microgram of total RNA is reverse transcribed using random hexaprimer and the Moloney murine leukemia virus reverse transcriptase kit, according to the manufacturer’s instructions. 2. The following program is used: one step at 95◦ C for 10 min, 40 cycles of denaturation at 95◦ C for 30 s, annealing for 60 s at 68◦ C, elongation at 72◦ C for 30 s. Amplification specificity is evaluated by determining the product melting curve. 3. Quantification of all target mRNAs is validated by the use of calibration curves showing a linear relationship between different pools of mRNA isolated from adult hepatocytes. The expression of 18S RNA is used for relative quantification. 4. Results are expressed as relative accumulation of mRNA with respect to levels observed in primary human hepatocytes after 3 days in culture, taken arbitrarily as 100.
4. Notes 1. We use only batches of collagenase with a specific activity greater than 400 U/mg. Some batches appear to be contaminated by microorganisms. This is assessed by microscopic examination of an aliquot of culture medium supplemented with 1 mg of collagenase after 96-h incubation at 37◦ C under normal culture conditions. In such cases, the collagenase solution has to be sterilized just prior use either directly by passing through a 0.22-μm filter or to prevent the filter from becoming clogged, first through a 0.45-μm filter and then prior to a second filtration through a 0.22-μm filter. 2. The preparation of the collagenase solution should begin at this point after it is clear that perfusion proceeds normally.
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3. This low-speed centrifugation is repeated once or twice in the supernatant containing the non-parenchymal cells to remove residual hepatocytes. 4. The supernatant should be filtered on a 40-μm cell strainer if the suspension contains large debris or cell aggregates. 5. At this step, the culture may appear very heterogeneous with different cell types emerging (fibroblasts, endothelial cells, etc.). Hepatocytes and endothelial cells will not survive longer than a week in this medium. Eventually, progenitors appear as small groups of epithelioid cells after approximately 1–2 weeks. 6. At this step, if epithelioid cells are still contaminated by fibroblasts, progenitors can be picked up with a clone disk. 7. During this step, both medium and cells can be collected at different time points for analysis of hepatocyte phenotypic markers.
Acknowledgments Part of the work described here has been supported by the European Community (PREDICTOMICS), the Fondation de l’Avenir and Sanofi-Aventis. References 1. Biron-Andreani, C., Bezat-Bouchahda, C., Raulet, E. et al. (2004) Secretion of functional plasma haemostasis proteins in longterm primary cultures of human hepatocytes. Br. J. Haematol. 125, 638–646. 2. Pascussi, J.M., Robert, A., Moreau, A. et al. (2007) Differential regulation of constitutive androstane receptor expression by hepatocyte nuclear factor4alpha isoforms. Hepatology 45, 1146–1153. 3. Maurel, P. (1996) The use of adult human hepatocytes in primary culture and other in vitro systems to investigate drug metabolism in man. Adv. Drug Del. Rev. 22, 105–132. 4. Gomez-Lechon, M.J., Castell, J.V., and Donato, M.T. (2008) An update on metabolism studies using human hepatocytes in primary culture. Expert. Opin. Drug Metab. Toxicol. 4, 837–854. 5. Guillouzo, A. and Guguen-Guillouzo, C. (2008) Evolving concepts in liver tissue mod-
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eling and implications for in vitro toxicology. Expert. Opin. Drug Metab. Toxicol. 4, 1279–1294. Farquhar, M.J. and McKeating, J.A. (2008) Primary hepatocytes as targets for hepatitis C virus replication. J. Viral Hepat. 15, 849–854. Molina, S., Castet, V., Pichard-Garcia, L. et al. (2008) Serum-derived hepatitis C virus infection of primary human hepatocytes is tetraspanin CD81 dependent. J. Virol. 82, 569–574. Dhawan, A., Mitry, R.R., and Hughes, R.D. (2006) Hepatocyte transplantation for liverbased metabolic disorders. J. Inherit. Metab. Dis. 29, 431–435. Fisher, R.A. and Strom, S.C. (2006) Human hepatocyte transplantation: worldwide results. Transplantation 82, 441–449. Strom, S.C., Bruzzone, P., Cai, H. et al. (2006) Hepatocyte transplantation: clinical
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Gerbal-Chaloin et al. experience and potential for future use. Cell Transplant. 15, S105–S110. Kakinuma, S., Nakauchi, H., and Watanabe, M. (2009) Hepatic stem/progenitor cells and stem-cell transplantation for the treatment of liver disease. J. Gastroenterol. 44, 167–172. Ambrosino, G. and D’Amico, D.F. (2003) Bioartificial liver support. Review and personal experience. Minerva Chir. 58, 649–656. Chamuleau, R.A., Poyck, P.P., and van de Kerkhove, M.P. (2006) Bioartificial liver: its pros and cons. Ther. Apher. Dial. 10, 168–174. Court, F.G., Wemyss-Holden, S.A., Dennison, A.R., and Maddern, G.J. (2003) Bioartificial liver support devices: historical perspectives. ANZ J. Surg. 73, 739–748. Nussler, A., Konig, S., Ott, M. et al. (2006) Present status and perspectives of cell-based therapies for liver diseases. J. Hepatol. 45, 144–159. Park, J.K. and Lee, D.H. (2005) Bioartificial liver systems: current status and future perspective. J. Biosci. Bioeng. 99, 311–319. Kobayashi, N. (2009) Life support of artificial liver: development of a bioartificial liver to treat liver failure. J. Hepatobiliary Pancreat. Surg. 16, 113–117. Reubinoff, B.E., Pera, M.F., Fong, C.Y., Trounson, A., and Bongso, A. (2000) Embryonic stem cell lines from human blastocysts: somatic differentiation in vitro. Nat. Biotechnol. 18, 399–404. Thomson, J.A., Itskovitz-Eldor, J., Shapiro, S.S. et al. (1998) Embryonic stem cell lines derived from human blastocysts. Science 282, 1145–1147. Overturf, K., al-Dhalimy, M., Ou, C.N., Finegold, M., and Grompe, M. (1997) Serial transplantation reveals the stem-celllike regenerative potential of adult mouse hepatocytes. Am. J. Pathol. 151, 1273–1280. Michalopoulos, G.K. (2007) Liver regeneration. J. Cell Physiol. 213, 286–300. Sell, S. (2001) Heterogeneity and plasticity of hepatocyte lineage cells. Hepatology 33, 738–750. Roskams, T. (2006) Liver stem cells and their implication in hepatocellular and cholangiocarcinoma. Oncogene 25, 3818–3822. Roskams, T.A., Theise, N.D., Balabaud, C. et al. (2004) Nomenclature of the finer branches of the biliary tree: canals, ductules, and ductular reactions in human livers. Hepatology 39, 1739–1745. Newsome, P.N., Hussain, M.A., and Theise, N.D. (2004) Hepatic oval cells: helping redefine a paradigm in stem cell biology. Curr. Top. Dev. Biol. 61, 1–28.
26. Libbrecht, L., Desmet, V., Van Damme, B., and Roskams, T. (2000) Deep intralobular extension of human hepatic ‘progenitor cells’ correlates with parenchymal inflammation in chronic viral hepatitis: can ‘progenitor cells’ migrate? J. Pathol. 192, 373–378. 27. Libbrecht, L. and Roskams, T. (2002) Hepatic progenitor cells in human liver diseases. Semin. Cell Dev. Biol. 13, 389–396. 28. Crosby, H.A., Kelly, D.A., and Strain, A.J. (2001) Human hepatic stem-like cells isolated using c-kit or CD34 can differentiate into biliary epithelium. Gastroenterology 120, 534–544. 29. Herrera, M.B., Bruno, S., Buttiglieri, S. et al. (2006) Isolation and characterization of a stem cell population from adult human liver. Stem Cells 24, 2840–2850. 30. Laurson, J., Selden, C., Clements, M. et al. (2007) Putative human liver progenitor cells in explanted liver. Cells Tissues Organs 186, 180–191. 31. McClelland, R., Wauthier, E., Zhang, L. et al. (2008) Ex vivo conditions for selfreplication of human hepatic stem cells. Tissue Eng. Part C Methods 14, 341–351. 32. Najimi, M., Khuu, D.N., Lysy, P.A. et al. (2007) Adult-derived human liver mesenchymal-like cells as a potential progenitor reservoir of hepatocytes? Cell Transplant. 16, 717–728. 33. Sasaki, K., Kon, J., Mizuguchi, T. et al. (2008) Proliferation of hepatocyte progenitor cells isolated from adult human livers in serum-free medium. Cell Transplant. 17, 1221–1230. 34. Schmelzer, E., Wauthier, E., and Reid, L.M. (2006) The phenotypes of pluripotent human hepatic progenitors. Stem Cells 24, 1852–1858. 35. Yamasaki, C., Tateno, C., Aratani, A. et al. (2006) Growth and differentiation of colonyforming human hepatocytes in vitro. J. Hepatol. 44, 749–757. 36. Selden, C., Chalmers, S.A., Jones, C. et al. (2003) Epithelial colonies cultured from human explanted liver in subacute hepatic failure exhibit hepatocyte, biliary epithelial, and stem cell phenotypic markers. Stem Cells 21, 624–631. 37. Duret, C., Gerbal-Chaloin, S., Ramos, J. et al. (2007) Isolation, characterization, and differentiation to hepatocyte-like cells of nonparenchymal epithelial cells from adult human liver. Stem Cells 25, 1779–1790. 38. Schwartz, R.E., Reyes, M., Koodie, L. et al. (2002) Multipotent adult progenitor cells from bone marrow differentiate into functional hepatocyte-like cells. J. Clin. Invest. 109, 1291–1302.
Chapter 13 The HepaRG Cell Line: Biological Properties and Relevance as a Tool for Cell Biology, Drug Metabolism, and Virology Studies Marie-Jeanne Marion, Olivier Hantz, and David Durantel Abstract Liver progenitor cells may play an important role in carcinogenesis in vivo and represent therefore useful cellular materials for in vitro studies. The HepaRG cell line, which is a human bipotent progenitor cell line capable to differentiate toward two different cell phenotypes (i.e., biliary-like and hepatocyte-like cells), has been established from a liver tumor associated with chronic hepatitis C. This cell line represents a valuable alternative to ex vivo cultivated primary human hepatocytes (PHH), as HepaRG cells share some features and properties with adult hepatocytes. The cell line is particularly useful to evaluate drugs and perform drug metabolism studies, as many detoxifying enzymes are expressed and functional. It is also an interesting tool to study some aspect of progenitor biology (e.g., differentiation process), carcinogenesis, and the infection by some pathogens for which the cell line is permissive (e.g., HBV infection). Overall, this chapter gives a concise overview of the biological properties and potential applications of this cell line. Key words: Liver progenitor, carcinogenesis, differentiation, drug metabolism, HBV, cellular innate antiviral response.
1. Introduction The HepaRG cell line has been recently established from an Edmonson grade I well-differentiated liver tumor of a female patient suffering from chronic hepatitis C infection and macronodular cirrhosis. The first scientific paper describing the establishment of the cell line also reported that HepaRG cells, as human primary hepatocytes (HPH), were permissive to hepatitis P. Maurel (ed.), Hepatocytes, Methods in Molecular Biology 640, DOI 10.1007/978-1-60761-688-7_13, © Springer Science+Business Media, LLC 2010
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B virus infection (1), thus emphasizing one of the main interesting properties of this cell line. To date HepaRG remains the only cell line capable to support a complete HBV cycle. Since this first publication, 37 other papers or reviews (i.e., PubMed list with “HepaRG” entry) have been published and concerned the characterization and properties of the cell line, as well as its main uses in various fields of research, including viral hepatitis, toxicology, drug evaluation and metabolism (see also Chapter 20), iron homeostasis, and cancer research. This chapter will describe the cell line to some extent, coming back on its establishment and main properties, and will summarize its main use in fields of research requiring cells sharing properties with functional and mature hepatocytes. See also Chapters 1, 20, and 25 of the present volume.
2. Establishment of the HepaRG Cell Line
A small fragment of tumor tissue was minced in small pieces, rinsed in Hepes buffer, and incubated in the presence of collagenase and CaCl2 with gentle stirring. Isolated cells were washed and plated on several uncoated dishes. After several weeks, hepatocyte-like cells filled the culture dishes. Cells from dishes that appeared the most homogeneous were harvested by trypsinization, passaged three times, and frozen. After thawing, cells from one single dish were further selected as cell aggregates by brief trypsinization of these cultures treated with 2% DMSO and 5 × 10−5 M hydrocortisone for 4 weeks. Indeed, after several passages, the cells acquired an undifferentiated morphology. In the presence of hydrocortisone and DMSO, most of the cells died but the surviving cells grew as small clusters exhibiting a typical hepatocyte-like morphology. These clusters were harvested selectively by gentle trypsinization and the resulting cell line was called HepaRG (1). HepaRG cells are routinely grown in William’s E medium supplemented with 10% fetal calf serum, 5 μg/ml insulin, 5 × 10−5 M hydrocortisone hemisuccinate, 100 units/ml penicillin, and 100 mg/ml streptomycin. After 2 weeks in this medium, they are further differentiated by culture in the same medium supplemented with DMSO (2%) (1).
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3. Characterization of HepaRG Cells 3.1. Morphologic Aspects
Just after plating, in the proliferation phase, HepaRG cells exhibit homogeneously a typical epithelial morphology. They proliferate for approximately 7 days (when seeded at 5 × 104 cells/cm2 ) when they become confluent. From days 7 to 14, in the stationary phase, two morphologically distinct cell populations emerge: the so-called epithelium-like cells (1) or biliary-like cells (2) which are large and flat cells with a clear cytosol, a regular polygonal shape and highly refringent edges, and the so-called hepatocyte-like cells that are smaller cells with a granular and dark cytosol, prominent nuclei and visible nucleoli, and resembling hepatocytes. From day 14, when the culture is continued in the presence of DMSO (differentiated phase), the clusters of hepatocyte-like cells reinforce and tend to organize in trabeculae with functional bile canaliculilike structures as shown by fluorescein excretion (3), surrounded by some biliary-like cells. Differentiation of HepaRG cells toward a more hepatocytic phenotype can also be achieved by treating cells with 20 ng/ml of EGF (2).
3.2. Hepato-specific Markers
The expression of liver-specific mRNAs and proteins by HepaRG cells was determined by Northern blot, Western blot (WB), indirect immunofluorescence (IF), and/or flow cytometry analyses, either in their proliferative state, at confluence, or in DMSO-induced differentiated state. An increase of the expression of liver-specific markers is observed as the differentiation progresses toward an hepatocyte-like phenotype. Albumin and GSTα mRNAs were shown to be slightly expressed by Northern blot in proliferating cells and their levels increased clearly when the cells reached confluence. Aldolase B mRNA is detected in confluent and differentiated cells but not in proliferative cells. CYP2E1 and CYP3A4 mRNAs levels are low or undetectable in proliferative and confluent cells and drastically increase when the cells are differentiated in the presence of DMSO (1). It was also shown by IF that only hepatocyte-like cells (i.e., 54.5% of the whole cellular population) were positive for CYP3A4 (3). Later, they were also shown to express other CYPs, various nuclear receptors, and phase II enzymes (4). Albumin and hepatocyte-specific antigen (HP-1) were also detected by WB analysis and IF. As expected, the expression of these markers is restricted to the hepatocyte-like cells in differentiated HepaRG. A strong staining for cytokeratin (CK)18, another hepatocytic marker, is observed all along the culture, although
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CK18 expression seems to be more intense in the hepatocytic areas of differentiated HepaRG. However, flow cytometry analysis shows that all the cells are positive for CK18 whatever the state of differentiation (2, 3). Moreover, as seen in human liver, HepaRG hepatocyte-like cells are positive for CD49a (α-1 integrin), whereas biliary-like cells are positive for CD49f (α-6 integrin) (3). Of importance, α-fetoprotein mRNA and protein were never detected. 3.3. Genotype and Phenotype of HepaRG Cells
HepaRG cells display a pseudodiploid karyotype with a t(12;22) translocation with loss of the small arm of chromosome 12 and an additional remodeled chromosome 7. This karyotype seems rather stable over time. HepaRG cells are not able to grow in serum-deprived medium and give only colonies of moderate size in soft agar. They do not give tumor after transplantation in nude mice, thus showing that they are not tumorigenic although they are partially transformed. In this respect, no deregulation of expression or mutations in genes such as p53, pRb, β-catenin were found in HepaRG cells ((3) and unpublished observations).
4. Progenitor Features HepaRG cells display a great plasticity as shown by their ability to develop from an epithelial phenotype, in the early stages of culture (progenitor stage), to a dual phenotype at confluence (differentiated stage). Indeed, a single-cell cloning experiment confirmed the ability of isolated HepaRG cells to give rise to both phenotypes (2). Also, purified hepatocyte-like cells seeded at low density (0.1×104 cells/cm2 ) revert to a more undifferentiated phenotype to give rise again, at confluence, to both hepatocyte-like cells and biliary-like cells. Reciprocally, biliary-like cells after the removal of hepatocyte-like cells also give rise to both cell populations. These observations suggested that HepaRG cells could be progenitor cells. Therefore, the expression of known liver progenitor markers was studied in HepaRG cells to confirm this assumption. Hence, it has been initially reported that in addition to CK18, HepaRG cells expressed also CK19, M2-PK, OV1, OV6, and CD34, which are markers of oval cells. M2-PK was strongly detected, either by IF or by WB, in the proliferative and confluent states. CK19 is strongly expressed at all stages of cell growth. Whether its expression is restricted to biliary-like cells is still in debate. For Parent et al. (2), CK19 expression is predominant in biliary-like cells, but a positive staining, albeit weaker, is also observed in the hepatocyte-like cells. On the contrary, it was reported by Cerec et al. (3) that only biliary-like cells are able
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to express CK19. It was also reported that HepaRG cells also display expression of NCAM, ABCG2, CD34, Thy1, Flt-3, c-Kit, IL-3Rα, LIF-R, CD71, gp130, G-CSF-R, VGEF-R2, ICAM-1, CD29, CD44, CD49a, CD49b, CD49f, CD138, CD13, CD33, CD10, which are considered as progenitor markers. Many of these markers decreased during the differentiation process.
5. In Vitro and In Vivo Differentiation of HepaRG Cell
As already mentioned above, HepaRG cells have the property to differentiate over time when cultured in vitro in adapted conditions. The acquisition of a polarized hepatic phenotype was demonstrated by the expression of CD26 (DDPIV) and E-cadherin, respectively, markers of apical and lateral poles, as well as ZO1, a marker of tight junctions (2). The acquisition of this differentiated phenotype is the result of the modulation of the expression of hepato-specific genes.
5.1. Transcriptional Control and Hepatocyte Differentiation
Hepatic nuclear factors are important transcriptional factors involved in hepato-specific genes expression. The expression of the different HNFs varies as function of the differentiation status of hepatocytes. HepaRG cells express HNF-3β only at the progenitor stage, whereas the expression of HNF4α, low at the beginning of the culture, gradually increases as the differentiation takes place. HNF1α is expressed at all stages of the culture. The expression of Notch genes, involved in cell proliferation homeostasis, has also been studied. Notch 1, 2, 3 (but not Notch 4) are also expressed at the progenitor state, with a decrease in Notch 1 and 2 expressions during the differentiation. In parallel, changes in β-catenin localization are observed with a nuclear localization just after plating which becomes cytoplasmic and membranous in progenitors and restricted to membranes in differentiated cells (3).
5.2. Translational Control and Hepatocyte Differentiation
Parent and Beretta (5) showed that translational control plays a prominent role in differentiation of HepaRG cells and is associated with the downregulation of the Akt–mTOR pathway (6). Hence, HepaRG clones expressing a constitutively activated mTOR mutant have impaired ability to differentiate. Remarkably, increased mTOR activity results in cell resistance to the antiproliferative effect of TGF-β. These authors compared the polysome-bound mRNA profiles of HepaRG expressing mTOR and of control HepaRG. They demonstrated that mTOR specifically targets genes posttranscriptionally regulated in HepaRG differentiation including members of the TNF/caspase transduction
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pathway suppress, transcription factors associated with lipid homeostasis (PPARα, PPARδ, and RXBβ), and C/EPBα, a transcription factor involved in hepatic differentiation. 5.3. In Vivo Differentiation
6. HepaRG Cell Line: An Interesting Tool for Studying Liver Cell Biology and Hepatitis Viruses
When injected in the spleen of partially hepatectomized uPA/SCID mice, either as progenitors or differentiated cells, HepaRG cells are able to repopulate the liver. However, contrary to the in vitro HepaRG differentiation process, which always leads to a mixture of biliary-like and hepatocyte-like cells, HepaRG cells preferentially differentiate toward the hepatocyte lineage in vivo (3).
The progenitor nature of HepaRG cells and their ability to undergo differentiation toward biliary and hepatocyte phenotypes make them a very interesting tool for studying differentiation, liver metabolism, drug effect/metabolism/toxicity, hepatotropic viruses, and some aspect of carcinogenesis.
6.1. Liver Metabolism and Iron Storage
Hepatic iron overload occurs in genetic hemochromatosis and leads to the development of cirrhosis and hepatocellular carcinoma (HCC). Iron overload is also observed in chronic liver diseases such as viral or alcoholic hepatitis. On the other hand, hepatocarcinoma cells seem to lose their ability to store iron. Troadec et al. (7) using a cDNA microarray analyzed the differentiation of HepaRG cells from the progenitor to differentiated stages in relation with iron metabolism. They showed that iron loading capacity is associated with a differentiation toward the hepatocytic phenotype including xenobiotic metabolism and a decrease in cell motility. Indeed, some genes involved in cell motility (RAC1, MSN, TMP3, FN1) are repressed during the differentiation process, whereas genes involved in lipid metabolism (FABP1, CYP4F2, UGT2B7, PLCG2) are upregulated. In parallel, ferritin H and NFE2L2, a transcription factor known to regulate the expression of some genes involved in iron metabolism, are downregulated as well as cytochrome c genes or other ironbinding proteins. On the other hand, genes of cytochrome P450 family and plasmatic iron transporters are upregulated. These authors also proposed new genes associated with hepatocyte differentiation and carcinogenesis.
6.2. Drug Metabolism and Toxicity Studies
Unlike freshly prepared human primary hepatocytes, most human hepatic cell lines lack important liver-specific functions, therefore they are not totally suitable to perform drug metabolism and toxicity studies. The ability of HepaRG cells to express
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cytochrome P450 enzymes (e.g. CYP1A1, 1A2, 2A2, 3A4, CYP4A11, 7A1, 2B6, 2C8, 2C9, 2C19, 2E1, 4F3), as well as nuclear receptors (e.g. PXR, CAR, PPARα, AhR), the major hepatic membrane transporters (e.g. bile salt export pump), phase II enzymes (e.g. UGT1A1, GSTA1, GSTA4, GSTM1), and antioxidant enzymes, particularly in their differentiated state, makes them a valuable in vitro model to perform drug metabolism and toxicity studies (8–14). The expression of P450 in HepaRG is in general close to or lower than that observed for HPH, with the exception of CYP3A4 and CYP7A1 that are overexpressed. The level of activities of CYP3A4, CYP1A2, and UDPglucuronosyltransferase enzymes is similar to that found in HPH, as shown by equivalent metabolism of midazolam, naloxone, and clozapine, whereas the function of CYP2A2 and CYP2D6 is weaker. The suitability of HepaRG in toxicology studies was further demonstrated by the similarity of metabolic profiles obtained for carcinogens (e.g., aflatoxin B1, acetaminophen) with HepaRG cells and HEH or their response to reference hepatotoxicants (15, 16). Comparison of gene expression profiles induced by phenolbarbital, and analyzed by cDNA microarrays in both HepaRG and HPH, also emphasizes that HepaRG cells closely resemble primary human hepatocytes (17). It was shown in particular that many genes involved in lipid metabolism (FABP4, AKR1B1, AKR1C1, etc.) and inflammation (i.e. IL1B, IL6) could be modulated by phenolbarbital, including again several CYPs (i.e. CYP4A11, CYP4F3). 6.3. HepaRG and Hepatitis B Virus Infection
In the original paper describing the cell line (1), it was reported that HepaRG cells were susceptible to a proper hepatitis B infection (from entry to virion production). Several human and rat hepatoma cell lines (18, 19) are able to support HBV replication after artificial introduction of the full HBV genome by transfection but, currently, beside primary human (20) and Tupaia (21) hepatocytes, HepaRG is the sole cell line that can be efficiently infected and supports a complete cycle of viral replication. Susceptibility of HepaRG cells to HBV is strongly dependent on the differentiation state induced by DMSO treatment as described by Gripon et al. (1), and well-defined culture conditions are required to achieve successful infection (22): a long (12–16 h) incubation phase of HBV virions with highly differentiated HepaRG cells is requested for a productive infection. In our experience, low temperature (32◦ C) and addition of polyethylene glycol (4% of PEG 8000), as described for primary human hepatocytes (23), increase efficiently the number of infected cells. The replication of HBV is a rather suppress slow process, with an appearance of viral RNA (pregenomic RNA and viral mRNAs) few days (between days 5 and 8) postinoculation (p.i.). The level of virion-associated
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DNA, which results from the reverse transcription of encapsidated pgRNA, peaks between days 10 and 15 p.i., although viral DNA remains detectable for many weeks (up to 100 days tested). The production of virions is rather low, but neo-produced virions are infectious (22). The status of differentiation, induced by DMSO and glucocorticoid, is crucial for HBV replication, HNF4α being a major transcription factor involved in the transcription of HBV promoters (24, 25). However, transcriptional activation by liver-specific factors cannot explain why susceptibility to HBV is restricted to differentiated hepatocytes. Clearly, early steps of HBV infection require some, yet unknown, host entry molecules that are likely express after the differentiation process in HepaRG cells and are retained only in freshly human primary hepatocytes (for review see (26)). It is worth noting that a maximum of 20% of HepaRG cells are infected, as shown by IF staining with anti-HBs antibodies, thus suggesting a limited permissivity of cells. In addition, it seems there is no spreading of the infection (22). The reasons why only up to 20% of cells are infected are unclear. It might be due to the polarization of hepatocyte-like cells that form islets surrounded by biliary-like cells, and only cells at the periphery of the islet would be infected. But it cannot be excluded at present that a cellular antiviral response in some cells would restrict infection to a moderate number of cells. During the last years, the HepaRG model for HBV infection has been very useful to get new insight on several aspects of HBV life cycle. HepaRG cells have been used to characterize the HBV receptor binding site (27) and viral determinants (28–30) involved in virus entry, leading to the development of efficient entry inhibitors (31, 32). Difficulties linked to the detection of actively replicating HBV DNA in only a low percentage of infected cells can be overcome by the use of HDV, a satellite virus that uses HBV envelopes for entry and synthesizes high level of HDV RNA following infection (28). Following entry, HBV infection, is characterized by the formation of the viral mini chromosome, the covalently closed circular DNA (cccDNA), in the nucleus of infected cells. Since it plays a key role in persistence of infection, cccDNA formation and regulation have been extensively studied for the avian hepadnavirus (duck hepatitis B virus) in duck primary hepatocytes culture (33–36). However, HBV and DHBV may differ in several aspects and HepaRG cell system, as an alternative to primary culture of human hepatocyte, may help our understanding of this crucial step of HBV life cycle. As suggested recently (22), cccDNA synthesis of HBV in HepaRG cells differs from that of DHBV in duck primary hepatocyte, an important finding that needs to be confirmed in human hepatocyte primary culture. Antiviral therapy of chronic hepatitis B may be associated with the emergence of complex HBV mutants, harboring mutations in
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both the reverse transcriptase and envelope proteins (for review see (37)). It is of crucial importance to study the fitness of these escape mutants to better adapt treatment in patient. HepaRG cell culture system has recently proven to be very useful to analyze the infectivity of such viruses and to explain the emergence of a particular HBV variant (38). Antiviral innate response during HBV infection remains an open question. As described below, HepaRG cells are able to mount a strong antiviral response following dsRNA stimulation. Whether HBV infection also leads to a specific innate response is still unknown. 6.4. HepaRG, Viral Infection, and Antiviral Innate Response
Following the report that HepaRG cells could be infected by HBV, the question of the permissivity of these cells to HCV replication was raised. Different approaches were used to determine whether HepaRG could be infected by and/or could replicate HCV. First, several attempts to install different HCV subgenomic replicons in HepaRG have been unsuccessful (Parent, unpublished results). Second, with the recent identification of a particularly replication-competent HCV strain (i.e., JFH1 strain), proper inoculations at a high multiplicity of infection (m.o.i.) of either proliferative or differentiated HepaRG cells with well defined (i.e., genetically) and in vitro produced recombinant HCV virions (i.e., HCVcc) were performed. No strong and lasting replication was observed in HepaRG cells as determined by the negativity of IF stainings with an anti-core antibody. This absence of (or weak) replication correlated with the production of type-I interferons in the culture medium, which likely inhibits HCV replication and spreading (Durantel et al., unpublished results). These results shed light on the potential role of cellular antiviral response in HepaRG cells to restrict viral infection. As HCV replication is mainly detected by sensors of cellular innate immunity (i.e., RIG, MDA5) recognizing double-stranded RNA, the dsRNA response was analyzed in HepaRG cells. It was found that a dsRNA (i.e., poly-IC) stimulation induces an antiviral and proinflamatory response in HepaRG cells, with the production of IFN-β, CXCL10, IL8, and others CK ligands (39). Moreover, dsRNA-conditioned medium from HepaRG cells exerted a drastic antiviral effect in Huh7 either harboring subgenomic replicons or infected with JFH1 strains. The blockade of the production of IFN-β by RNA silencing reverted this effect, thus suggesting that type-I IFN response is at least partially responsible for the observed antiviral effect in trans (39). Therefore the ability of HepaRG cells to mount a strong type-I IFN response may explain why the cell line is not permissive to a strong HCV replication. With respect to HBV replication, it was indicated earlier that the number of infected cells is rather low (up to 20% of cells). One possible explanation is that an antiviral response in HepaRG, as clearly evidenced for HCV, could be
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responsible for this restriction. In the case of HBV infection of HepaRG, it is difficult to quantify a potential IFN-β response, as this response is likely stochastic (40), meaning that the expression of IFN-β may be weak (i.e., monoallelic) and restricted to few cells, and that the overall response does not need to be intense to be efficient. Together with the fact that only few cells are exposed to the virus, due to the islet structure of hepatocyte-like cells, it explains why this response in the case of a virus-like HBV, which is not a strong inducer of innate response and is very efficient to inhibit IFN signaling, has not yet been evidenced. When the replication of HBV is artificially augmented by using recombinant baculoviruses carrying HBV genome to launch infection (41), we have demonstrated recently that an IFN-β response specific of HBV can be mounted in HepaRG cells and can induce in a non-cytopathic fashion the clearance of HBV (42). The invalidation of this innate antiviral response in HepaRG cells may be a prerequisite to achieve higher level of HBV and HCV replications. It remains also to understand why the innate antiviral response is so strong in HepaRG cells and the significance of this with respect to the biology of these cells.
7. Conclusions Ex vivo cultivated HPH represents the more physiologic in vitro model to perform hepatocyte cellular biology and virology studies, but its use is limited by the scarcity of human liver cells and the inherent variability of cells from different donors. The HepaRG cell line represents a valuable alternative tool, as HepaRG cells share some features and properties with adult hepatocytes. In this chapter, we have described to some extent the features and properties of HepaRG cells and have presented different scientific results obtained with this cell line, illustrating its interest in various fields of research. To summarize, this cell line represent a very useful tool, and a good alternative to HPH, to evaluate drugs and perform drug metabolism studies. It is also an interesting model to study many aspect of hepatocytes cellular biology and to study pathogens infecting these cells. References 1. Gripon, P., Rumin, S., Urban, S., Le Seyec, J., Glaise, D., Cannie, I. et al. (2002) Infection of a human hepatoma cell line by hepatitis B virus. Proc. Natl. Acad. Sci. USA 99, 15655–15660.
2. Parent, R., Marion, M.-J., Furio, L., Trepo, C., and Petit, M.A. (2004) Origin and characterization of a human bipotent liver progenitor cell line. Gastroenterology 126, 1147–1156.
The HepaRG Cell Line 3. Cerec, V., Glaise, D., Garnier, D., Morosan, S., Turlin, B., Drenou, B. et al. (2007) Transdifferentiation of hepatocyte-like cells from the human hepatoma HepaRG cell line through bipotent progenitor. Hepatology 45, 957–967. 4. Aninat, C., Piton, A., Glaise, D., Le Charpentier, T., Langouet, S., Morel, F. et al. (2006) Expression of cytochromes P450, conjugating enzymes and nuclear receptors in human hepatoma HepaRG cells. Drug Metab. Dispos. 34, 75–83. 5. Parent, R. and Beretta, L. (2008) Translational control plays a prominent role in the hepatocytic differentiation of HepaRG liver progenitor cells. Genome Biol. 9, R19. 6. Parent, R., Kolippakkam, D., Booth, G., and Beretta, L. (2007) Mammalian target of rapamycin activation impairs hepatocytic differentiation and targets genes moderating lipid homeostasis and hepatocellular growth. Cancer Res. 67, 4337–4345. 7. Troadec, M.B., Glaise, D., Lamirault, G., Le Cunff, M., Guerin, E., Le Meur, N. et al. (2006) Hepatocyte iron loading capacity is associated with differentiation and repression of motility in the HepaRG cell line. Genomics 87, 93–103. 8. Aninat, C., Seguin, P., Descheemaeker, P.N., Morel, F., Malledant, Y., and Guillouzo, A. (2008) Catecholamines induce an inflammatory response in human hepatocytes. Crit. Care Med. 36, 848–854. 9. Antoun, J., Amet, Y., Simon, B., Dreano, Y., Corlu, A., Corcos, L. et al. (2006) CYP4A11 is repressed by retinoic acid in human liver cells. FEBS Lett. 580, 3361–3367. 10. Antoun, J., Goulitquer, S., Amet, Y., Dreano, Y., Salaun, J.-P., Corcos, L. et al. (2008) CYP4F3B is induced by PGA1 in human liver cells: a regulation of the 20-HETE synthesis. J. Lipid Res. 49, 2135–2141. 11. Josse, R., Aninat, C., Glaise, D., Dumont, J., Fessard, V., Morel, F. et al. (2008) Longterm functional stability of human HepaRG hepatocytes and use for chronic toxicity and genotoxicity studies. Drug Metab. Dispos. 36, 1111–1118. 12. Kanebratt, K.P. and Andersson, T.B. (2008) Evaluation of HepaRG cells as an in vitro model for human drug metabolism studies. Drug Metab. Dispos. 36, 1444–1452. 13. Kanebratt, K.P. and Andersson, T.B. (2008) HepaRG cells as an in vitro model for evaluation of cytochrome P450 induction in humans. Drug Metab. Dispos. 36, 137–145. 14. Le Vee, M., Jigorel, E., Glaise, D., Gripon, P., Guguen-Guillouzo, C., and Fardel, O. (2006) Functional expression of sinusoidal
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Marion, Hantz, and Durantel nuclear hormone receptors is a critical determinant of viral tropism. Proc. Natl. Acad. Sci. USA 98, 1841–1846. Glebe, D. and Urban, S. (2007) Viral and cellular determinants involved in hepadnaviral entry. World J. Gastroenterol. 13, 22–38. Engelke, M., Mills, K., Seitz, S., Simon, P., Gripon, P., Schnolzer, M. et al. (2006) Characterization of a hepatitis B and hepatitis delta virus receptor binding site. Hepatology 43, 750–760. Jaoude, G.A. and Sureau, C. (2005) Role of the antigenic loop of the hepatitis B virus envelope proteins in infectivity of hepatitis delta virus. J. Virol. 79, 10460–10466. Blanchet, M. and Sureau, C. (2006) Analysis of the cytosolic domains of the hepatitis B virus envelope proteins for their function in viral particle assembly and infectivity. J. Virol. 80, 11935–11945. Abou-Jaoude, G. and Sureau, C. (2007) Entry of hepatitis delta virus requires the conserved cysteine residues of the hepatitis B virus envelope protein antigenic loop and is blocked by inhibitors of thiol-disulfide exchange. J. Virol. 81, 13057–13066. Gripon, P., Cannie, I., and Urban, S. (2005) Efficient inhibition of hepatitis B virus infection by acylated peptides derived from the large viral surface protein. J. Virol. 79, 1613–1622. Petersen, J., Dandri, M., Mier, W., Lutgehetmann, M., Volz, T., von Weizsacker, F. et al. (2008) Prevention of hepatitis B virus infection in vivo by entry inhibitors derived from the large envelope protein. Nat. Biotechnol. 26, 335–341. Tuttleman, J.S., Pourcel, C., and Summers, J.W. (1990) Formation of the pool of covalently closed circular viral DNA in hepadnavirus-infected cells. Cell 47, 451–460. Summers, J.W., Smith, P.M., and Horwich, A.L. (1990) Hepadnavirus envelope
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Chapter 14 Transdifferentiation of Pancreatic Cells to Hepatocytes Chia-Ning Shen and David Tosh Abstract Hepatocytes maintained in culture provide an attractive model system for the study of liver function. Furthermore, hepatocyte transplantation offers an alternative cellular therapy to orthotopic liver transplantation for the treatment of hepatic failure and hereditary liver disease. To overcome the problem of organ shortage, additional source of hepatocytes must be found. Here, we present a strategy and protocol to transdifferentiate (or convert) developmentally related pancreatic cells into hepatocytes based on the addition of the synthetic glucocorticoid dexamethasone. Key words: Transdifferentiation, hepatocytes, pancreatic cells, glucocorticoid.
1. Introduction Transdifferentiation can be defined simply as the conversion (or reprogramming) of one cell type into another cell type. Transdifferentiation belongs to the wider class of cell-type conversions known as metaplasias which also includes cases in which stem cells of one tissue type switch to become those of another (1). Metaplasia is frequently associated with an increased risk of developing neoplasia. The phenotypic conversion may result from a variety of cellular mechanisms such as (i) reprogramming of tissue-specific stem cells, (ii) selective expansion of differentiated cell types ordinarily present in low abundance, or (iii) direct transdifferentiation of one mature cell type to another. In adult tissues, the mechanisms underlying metaplastic conversion have rarely been studied in detail, reflecting the challenges associated with confirming precursor–progeny relationships in a multilineage context. P. Maurel (ed.), Hepatocytes, Methods in Molecular Biology 640, DOI 10.1007/978-1-60761-688-7_14, © Springer Science+Business Media, LLC 2010
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The appearance of hepatic foci in the pancreas has been documented in rats, hamsters, mice, monkeys, and humans under experimental and pathological conditions. For example, hepatocytes can be induced in the pancreas in copper depletion of the diet (2, 3), following transplantation of pancreatic epithelial cells (4), and in transgenic mice overexpressing keratinocyte growth factor in the pancreas (5). It has also been observed naturally in a human pancreatic cancer patient (6). The conversion between pancreas and liver may reflect the close developmental relationship between the two tissues. Indeed, liver and pancreas originate from neighboring regions of the foregut endoderm, so it is possible that they are initially distinguished by the activity of one or a few transcription factors (so-called master switch genes) (7). In order to investigate the mechanism of pancreas-to-liver transdifferentiation, we have developed in vitro models to induce pancreatic exocrine cells to transdifferentiate into hepatocytes by using a combination of the synthetic glucocorticoid dexamethasone (DEX) and oncostatin M (OSM) treatment (8). For example, in the pancreatic AR42J-B13 cell model, we found that addition of 1 μM of dexamethasone is sufficient to induce the conversion of pancreatic exocrine cells to hepatocytes. The number of hepatocytes can be further increased by co-culture with dexamethasone and OSM. The underlying molecular mechanism involves activation of the transcription factors CCAAT/enhancer binding protein, C/EBPα and C/EBPβ (8–10). The “transdifferentiated hepatocytes” express a range of proteins normally present in mature hepatocytes such as albumin, transferrin, glucose-6phosphatase, acute phase proteins, a liver-specific calcium channel, and cytochrome P450s (8–13). Moreover, transdifferentiated hepatocytes support the replication of hepatitis B virus suggesting the cells function as bona fide hepatocytes (14). Here we present two models for the conversion of pancreatic cells to hepatocytes. The first is based on the rat pancreatic cell line AR42JB13 and the second is based on primary cultures of mouse pancreatic acinar cells.
2. Materials 2.1. Culture and Transdifferentiation of AR42J Pancreatic Acinar Cell Lines
1. AR42J is a rat pancreatic exocrine cell line which can be purchased from ECACC (European Collection of Cell Cultures). AR42J-B13 cell (kindly provided by Dr. I. Kojima, Tokyo, Japan) is a subclone of the parent line AR42J. 2. Culture medium: Dulbecco’s modified Eagle’s medium (Sigma) containing 2 mM L-glutamine, 0.5 u/ml
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penicillin, 500 ng/ml streptomycin, and 10% fetal bovine serum (Invitrogen). 3. Freezing medium: Fetal bovine serum containing 10% (v/v) dimethyl sulfoxide (DMSO). 4. 70% (v/v) ethanol. 5. CO2 incubator. 6. Centrifuge. 7. Water bath. 8. Inverted light microscope. 9. Dexamethasone (Sigma Chemical Co.) is dissolved in ethanol at the stock concentration of 1 mM. 10. Recombinant human oncostatin M is obtained from R&D System Inc. and dissolved in phosphate-buffered saline containing 0.1% bovine serum albumin at the stock concentration of 10 μg/ml. 11. Tissue culture plastic: sterile pipettes, culture flasks, Petri dishes. 2.2. Culture and Transdifferentiation of Primary Mouse Pancreatic Cells
1. Wash solution: phosphate-buffered saline (pH 7.2) containing 0.01% soybean trypsin inhibitor (Sigma). 2. Digestion solution I: phosphate-buffered saline (pH 7.2) containing 0.02% trypsin and 0.25% EDTA. 3. Neutralization medium: Waymouth’s MB 752/1 medium (Sigma) containing 0.1 mg/ml soybean trypsin inhibitor, 5 mg/ml bovine serum albumin fraction V (Sigma), and 20% fetal bovine serum. 4. Digestion solution II: Hanks Balanced Salt Solution (GIBCO) containing 1 mg/ml collagenase P (Roche Diagnostics) and 0.2 mg/ml bovine serum albumin fraction V. 5. Culture medium: Waymouth’s MB 752/1 medium containing penicillin, streptomycin, 0.1 mg/ml soybean trypsin inhibitor, 20 ng/ml EGF (R & D Systems), 10 mM nicotinamide (Stem Cell Technologies), and 10% fetal bovine serum. 6. Gelvatol medium: prepared by dissolving 20 g of polyvinyl alcohol in 80 ml of 10 mM Tris [pH 8.6], and 3 g of n-propyl gallate in 50 ml glycerol followed by mixing and centrifugation at 7,000×g to remove any undissolved particles. 7. 70% (v/v) ethanol. 8. CO2 incubator. 9. Centrifuge. 10. Shaking water bath.
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11. Inverted light microscope. 12. Sterile scalpels. 13. Nylon mesh (100 μm mesh (BD Biosciences)) 14. Hemocytometer. 15. Tissue culture plastic: sterile pipettes, culture flasks, Petri dishes.
3. Methods 3.1. Transdifferentiation of Pancreatic AR42J or AR42J-B13 Cells to Hepatocytes
1. Both AR42J and AR42J-B13 cells are maintained in Dulbecco’s modified Eagle’s medium containing penicillin, streptomycin, and 10% fetal bovine serum. 2. The medium is changed every 2–3 days, and subculture is performed every 4–6 days at a ratio of 1:5 (AR42J) or 1:7(AR42J-B13). 3. For induction of transdifferentiation, dexamethasone is added as a solution in ethanol at a final concentration of 1 μM together with 10 ng/ml oncostatin M. The medium is changed every 2–3 days. Addition of 1 μM of dexamethasone and 10 ng/ml oncostatin M (OSM) is sufficient to induce 80–90% of AR42J-B13 cells to hepatocytes in 5–7 days. See Notes 1–4.
3.2. Isolation and Transdifferentiation of Pancreatic Exocrine Cells to Hepatocytes
1. Isolation of mouse exocrine cells is performed as described previously (15, 16) with some modifications. Briefly, male C57BL/6 mice at 6–8 weeks of age were killed by cervical dislocation and the pancreata removed and minced in a Petri dish and washed for 2× with Wash solution. 2. The contents of the Petri dish is then transferred to a 50 ml centrifuge tubes containing 10 ml of Digestion solution I. 3. The tubes are incubated at 37◦ C for 5 min in a shaking water bath. The tubes are then centrifuged at 500×g for 2 min. 4. After centrifugation, the supernatant is aspirated and then the tissue pellet is rinsed with 10 ml of Neutralization medium and centrifuged at 500×g for 2 min. 5. After centrifugation, the pellet is resuspended in 10 ml of Digestion solution II, incubated for 15 min at 37◦ C in a shaking water bath and centrifuged at 500×g for 2 min. 6. After centrifugation, the supernatant is aspirated off and then the cell pellet is resuspended in 5 ml of Waymouth’s MB 752/1 medium containing 10% FBS.
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7. In order to remove any undigested and partially digested tissue, the resuspended material is filtered through 100 μm mesh. 8. For removal of fibroblasts, harvested cells are pre-seeded on culture dishes for 8 h. 9. Floating cells are collected, pelleted by centrifugation at 500×g for 2 min, and replated on culture dishes pre-coated with 10 μg/ml fibronectin 10. For induction of hepatic transdifferentiation, 1 μM dexamethasone and 10 ng/ml oncostatin M (OSM) are added to the culture medium for 5–7 days (Fig. 14.1).
Fig. 14.1. Time course of expression of TFN, CYP3A1, C/EBPbeta, and HNF-4 in hepatic transdifferentiation. (A–D) Immunofluorescent staining of TFN, CYP3A1, C/EBPbeta, and HNF-4 in control AR42J-13 cells (A), in AR42J-B13 cells treated with DEX+OSM for 2 days (B), 3 days (C), and 5 days (D). Mouse primary pancreatic cells were treated with DEX+OSM for 5 days (E). Immunofluorescent staining was performed for TFN and C/EBPbeta. (F) AR42J or AR42J-B13 was treated for 1, 3, 5, 7 days with DEX+OSM. RT-PCR was performed to determine the expression of TFN, TAT, ALB, CYP3A1, and CYP7A1. Expression of GAPDH was performed as a loading control.
3.3. Immunofluorescence Analysis of Transdifferentiated Hepatocytes
1. For immunofluorescence analysis, cells are cultured on noncoated glass coverslips, rinsed with PBS, fixed with 4% paraformaldehyde (PFA) in PBS for 30 min. 2. For PFA fixed samples, cells are permeabilized with 0.1% (vol/vol) Triton X-100 in PBS for 30 min, and incubated in 2% blocking buffer (Roche, East Sussex, UK) which contains 0.1% Triton X-100. 3. Cells are incubated overnight with primary antibodies at 4◦ C. Examples of antibodies used for characterizing the liver phenotype are listed in Table 14.1. 4. Cells are washed three times with PBS buffer and then incubated in secondary antibodies for 3 h at room temperature.
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Table 14.1 List of antibodies using in immunocytochemical analysis of the hepatic phenotype Antibody
Clone
Cytochrome P450 3A1
Species
Isotype
Rabbit
Transferrin
Supplier
Dilution
Chemicon 1/400
Dako
1/450
HNF4α
C19
Rabbit Goat
IgG
Santa Cruz
1/400
C/EBP β
H-7
Mouse
IgG2a
Santa Cruz
1/300
5. After incubation of secondary antibodies, cells are washed three times with PBS buffer, and then mounted in Gelvatol medium.
3.4. RT-PCR Analysis of Transdifferentiated Hepatocytes
1. RNA is extracted from the control pancreatic cells and transdifferentiated hepatocytes using TRI REAGENTTM according to the manufacturer’s instructions. The RNA is then digested with RQ-1 DNase (Promega, Southampton, UK) to remove any contaminating genomic DNA. 2. First strand complementary DNA is synthesized using SuperScript III reverse transcriptase (Invitrogen). 3. Examples of rat PCR primers used are listed in Table 14.2. PCR reactions are processed in a DNA thermal cycler under the following conditions: denaturation at 94◦ C for 1 min, annealing at 55–58◦ C for 1 min, and extension at 72◦ C for 1 min. The number of cycles is 28–32.
Table 14.2 List of primers used in RT-PCR analysis of hepatic phenotype Gene
Sense
Antisense
Albumin (ALB)
gtcagaacctcattgtatttc
attcacactctcttcggagac
Transferrin (TFN)
gagacgtagcctttgtgaag
gtactctgctcctaagtactc
CYP3A1
ggaaattcgatgtggagtgc
aggtttgcctttctcttggc
CYP7A1
cctcctggccttcctaaatc
gtcaaaggtggagagcgtgt
GAPDH
aaggtcggtgtgaacggatt
tggtggtgcaggatgcattg
Tyrosine aminotransferase (TAT)
cacgacacgttaagcttcct
ctgccttcatcacagtggta
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4. Notes 1. Transdifferentiation of pancreatic AR42J cells can be seen by morphological changes following addition of dexamethasone. Hepatic transdifferentiation is associated with discrete changes in the cellular morphology of pancreatic exocrine cells. During the early phase of transdifferentiation, the cells flatten, enlarge, and form epithelial tight/adherin junctions which are associated with the formation of hepatocytes. 2. The time course of the transdifferentiation process can either be characterized by immunofluorescent staining (Fig. 14.1A–E) or RT-PCR (Fig. 14.1E). Liver markers appear in sequence (Fig. 14.1). Some of the cells that become flattened by 2 days began to express C/EBPβ and nuclear HNF-4α. Transferrin starts to appear from 2 to 3 days, and then mature liver markers can be detected between 5 and 7 days. 3. High cell density reduces the transdifferentiation efficiency. 4. For long-term maintenance of “transdifferentiated hepatocytes.” AR42J-B13 cells can be maintained in culture medium containing 1 μM Dex for 2 weeks without the need for splitting. Cells can also be maintained for longer periods of time. The cells can be split and cultured with 1 μM Dex and 10 ng/ml OSM. Three to five days should be allowed for the split cells to reach maturation.
Acknowledgments The authors wish to thank the Wellcome Trust, Medical Research Council and the National Science Council for financial support References 1. Slack, J.M. (2007) Metaplasia and transdifferentiation: from pure biology to the clinic. Nat. Rev. Mol. Cell Biol. 8, 369–378. 2. Rao, M.S., Dwivedi, R.S., Subbarao, V., Usman, M.I., Scarpelli, D.G., Nemali, M.R., Yeldandi, A., Thangada, S., Kumar, S., and Reddy, J.K. (1988). Almost total conversion of pancreas to liver in the adult rat: a reliable model to study transdifferentiation. Biochem. Biophys. Res. Commun. 156, 131–136.
3. Tosh. D., Shen, C.N., Alison, M.R., Sarraf, C.E., and Slack, J.M.W. (2007) Copper deprivation in rats induces islet hyperplasia and hepatic metaplasia in the pancreas. Biol. Cell 99, 37–44. 4. Wang, X., Al-Dhalimy, M., Lagasse, E., Finegold, M., and Grompe, M. (2001). Liver repopulation and correction of metabolic liver disease by transplanted adult mouse pancreatic cells. Am. J. Pathol. 158, 571–579.
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5. Krakowski, M.L., Kritzik, M.R., Jones, E.M., Krahl, T., Lee, J., Arnush, M., Gu, D., and Sarvetnick, N. (1999) Pancreatic expression of keratinocyte growth factor leads to differentiation of islet hepatocytes and proliferation of duct cells. Am. J. Pathol. 154, 683–691. 6. Paner, G.P., Thompson, K.S., and Reyes, C.V. (2000) Hepatoid carcinoma of the pancreas. Cancer 88, 1582–1589. 7. Shen, C.N., Horb, M.E., Slack, J.M.W., and Tosh, D. (2003) Transdifferentiation of pancreas to liver. Mech. Dev. 120, 107–116. 8. Shen, C.N., Slack, J.M.W., and Tosh, D. (2000) Molecular basis of transdifferentiation of pancreas to liver. Nat. Cell Biol. 2, 879–887. 9. Shen, C.N., Seckl, J.R., Slack, J.M.W., and Tosh, D. (2003) Glucocorticoids suppress beta cell development and induces hepatic metaplasia in embryonic pancreas. Biochem. J. 375, 41–50. 10. Burke, Z.D., Shen, C.N., Ralphs, K.L., and Tosh, T. (2006) Characterization of liver function in TD hepatocytes. J. Cell Physiol. 206, 147–159. 11. Tosh, D., Shen, C.N., and Slack, J.M.W. (2002) Differentiated properties of
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hepatocyte-like cells induced from the pancreatic cell. Hepatology 36, 534–543. Kurash, J.K., Shen, C.N., and Tosh, D. (2004) Induction and expression of acute phase proteins in transdifferentiated hepatocyte. Exp. Cell Res. 292, 342–358. Marek, C.J., Cameron, G.A., Elrick, L.J., Hawksworth, G.M., and Wright, M.C. (2003) Generation of hepatocytes expressing functional cytochromes P450 from a pancreatic progenitor cell line in vitro. Biochem. J. 370, 763–769. Wang, R.Y.L., Shen, C.N., Lin, M.H., Tosh, D., and Shih, C.H. (2005) Hepatocyte-like cells transdifferentiated from pancreatic origin can support hepatitis B virus. J. Virol. 79, 13116–13128. Lardon, J., De Breuck, S., Rooman, I., Van Lommel, L., Kruhoffer, M., Orntoft, T., Schuit, F., and Bouwens, L. (2004) Plasticity in the adult rat pancreas: transdifferentiation of exocrine to hepatocyte-like cells in primary culture. Hepatology 39, 1499–1507. Kurup, S. and Bhonde, R.R. (2002) Analysis and optimization of nutritional set-up for murine pancreatic acinar cells. JOP 3, 8–15.
Chapter 15 Evaluation of Drug Metabolism, Drug–Drug Interactions, and In Vitro Hepatotoxicity with Cryopreserved Human Hepatocytes Albert P. Li Abstract Human-based in vitro hepatic experimental systems are now used routinely in drug development. The initial concept of the use of human-based in vitro systems is based on the known species–species differences in drug properties. Human-specific drug properties, by definition, cannot be defined using nonhuman experimental animals and therefore can be only assessed in the preclinical phase of drug development using in vitro human-based experimental systems such as human hepatocytes. Successful cryopreservation of human hepatocytes greatly enhances the utility of this valuable in vitro experimental system, allowing storage, transport, convenient scheduling of experimentation, and repeat experimentation using hepatocytes isolated from the same donors. Assay procedures with cryopreserved human hepatocytes using multiwell plates for the evaluation of critical drug properties including metabolic stability, drug–drug interaction potential, and drug toxicity during drug development are described. Key words: Human hepatocytes, drug metabolism, metabolic stability, metabolite profiling drug–drug interactions, hepatotoxicity.
1. Introduction One major challenge in the selection of drug candidates for clinical trials is that, due to species–species differences in drug properties, human-specific drug effects cannot be detected using nonhuman animal experimental systems. This species–species difference has been attributed to the high (>25%) incidence of clinical trial failures (1). One of the probable reasons for species–species differences in drug properties is the occurrence of species–specific P. Maurel (ed.), Hepatocytes, Methods in Molecular Biology 640, DOI 10.1007/978-1-60761-688-7_15, © Springer Science+Business Media, LLC 2010
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xenobiotic metabolism pathways. Species differences in P450dependent monooxygenases, a major group of enzymes responsible for drug metabolism, are well established (2). In vitro experimental systems with human-specific properties represent attractive tools for the assessment of human-specific drug properties. In vitro experimental systems derived from the human liver, namely human hepatocytes and human liver tissue fractions, are now used routinely for the evaluation of human drug metabolism. The combined use of human in vitro hepatic systems and relevant nonhuman animal models led to the reduction in the contribution of pharmacokinetics as a major factor of human clinical trial failures from approximately 40% in 1991 to approximately 10% in 2000 (3). The parenchymal cells of the liver, commonly known as hepatocytes, contain the majority, if not all, of hepatic xenobiotic biotransformation enzymes. The drug metabolic activities of the hepatocytes therefore are representative of the liver as an organ. Furthermore, the hepatocytes are often the cells damaged by hepatotoxic drugs, leading in some cases to severe liver damage, including organ failures. For these reasons, hepatocytes represent a relevant experimental system for the evaluation of drug properties since the beginning of the establishment of their isolation and culturing procedures (4). This view continues to be held by the current scientific community (5, 6). The use of hepatocytes in the evaluation of drug metabolism, drug–drug interaction potential, and drug toxicity is now a routine practice in both academic and industrial laboratories (7). There are many reviews, including those by this author, on the general concepts of the use of human hepatocytes in drug metabolism and toxicology research (5–9). Human hepatocyte cryopreservation is an enabling technology for the use of human hepatocytes. The advantages of cryopreserved hepatocytes over freshly isolated cells include long-term storage, ease of experimental scheduling, choice of precharacterized lots for experimentation, and repeat experimentations with hepatocytes from the same donors. Our laboratory was one of the first to report successful cryopreservation of human hepatocytes (10) and to show similar drugmetabolizing enzymes between cryopreserved and freshly isolated human hepatocytes (11) as well as the development of practical approaches for the evaluation of metabolic stability, drug–drug interactions, and cytotoxicity using cryopreserved human hepatocytes (5, 7, 8, 11, 12). Until recently, cryopreserved hepatocytes generally would lose their ability to be cultured as attached, monolayer cultures, presumably due to the unavoidable membrane damage during the cryopreservation and subsequent thawing processes. It has been projected in the past that 1 out of 20 human hepatocyte isolations would lead to “plateable” cryopreserved hepatocytes.
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A focused research effort was initiated in our laboratory in 2005 to overcome this deficiency in hepatocyte cryopreservation. Our research resulted in the development of highly optimized hepatocyte isolation, cryopreservation, and recovery procedures (5). One practical achievement of our research with hepatocyte cryopreservation is the development of a cryopreserved hepatocyte recovery medium (CHRM) which greatly enhances the quality of the human hepatocytes when thawed from cryopreservation. The similarity between freshly isolated and cryopreserved human hepatocytes in drug-metabolizing enzyme activities is now generally accepted by the scientific community (9, 11–13). Besides the retention of high viability and plateability, human hepatocytes after cryopreservation have been shown to retain human drug-metabolizing enzyme activities including the activities of P450 isoforms, UDP-dependent glucuronosyltransferase (UGT) activity, and sulfotransferase activity (ST) (11, 12). The original proposed applications of cryopreserved hepatocytes in drug metabolism studies (11, 12) have been generally accepted by the scientific community at large (13, 14). The plateable cryopreserved human hepatocytes can be used for enzyme induction studies (15). One of the latest findings with plateable cryopreserved human hepatocytes is that they form functional bile canaliculi and therefore can be applied toward the evaluation of hepatobiliary excretion (16). The procedures for the use of human hepatocytes in the evaluation of drug properties during drug development are described here. Key reagents used in our laboratory for the thawing, recovery, and application of cryopreserved human hepatocytes described in this paper are listed in Table 15.1. See also Chapters 4, 5, 16–19, and 21.
2. Materials Key reagents used in our laboratory for the thawing, recovery, and application of cryopreserved human hepatocytes described in this paper are listed in Table 15.1. P450 substrates and metabolite standards are listed in Table 15.2. Positive controls for P450 inhibition studies are listed in Table 15.3. Organic solvents used for the test articles include acetonitrile (ACN), DMSO, methanol, and ethanol. The other materials include collagencoated 24- and 96-well culture plates, serological pipettes, and micropipettes. Equipments needed include cell culture hoods, cell culture incubators, and analytical chemistry instruments such as HPLC, LC/MS, and LC/MS/MS.
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Table 15.1 Reagents used with the application of cryopreserved human hepatocytes in drug metabolism, drug–drug interactions, and cytotoxicity studies Catalog number
Reagent
Application
Manufacturer
Trypan blue solution (0.4%) Cryopreserved hepatocyte recovery medium (CHRM)
Viability determination
Sigma-Aldrich T8154 (www.sigmaaldrich.com) APSciences Inc. 70001 (www.apsciences.com)
Hepatocyte suspension medium (HSM)
Medium for the resuspension of thawed, cryopreserved hepatocytes for viability and yield determination
APSciences Inc. (www.apsciences.com)
70026
Hepatocyte metabolism medium (HMM)
Medium for metabolism studies such as metabolic stability, metabolite profiling. The medium is also used for the evaluation of P450 substrate metabolism for P450 inhibition and induction studies
APSciences Inc. (www.apsciences.com)
70005
Hepatocyte plating medium (HPM)
Medium for the plating of hepatocytes for culturing as attached monolayer cultures
APSciences Inc. (www.apsciences.com)
70002
Hepatocyte induction medium (HIM)
Medium for enzyme induction studies
APSciences Inc. (www.apsciences.com)
70011
Collagen-coated cell culture plates
Plates for the culturing of hepatocytes as monolayer cultures
APSciences Inc. (www.apsciences.com)
ATP reagent
Quantification of cellular ATP content for cytotoxicity studies
PerkinElmer (www.perkinelmer.com)
71006 (24well plates) and 71011 (96-well plates) 6016736
Recovery of hepatocytes after thawing
These are the reagents used in the author’s laboratories and may be replaced with similar reagents from other manufacturers.
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Table 15.2 Substrates and corresponding metabolites for the evaluation of drug-metabolizing enzyme activities for the evaluation of enzyme inhibition and enzyme induction potential Drug-metabolizing enzyme
Substrate conc. (μM)
Substrates
Metabolites
CYP1A2
50
Phenacetin
Acetaminophen
CYP2A6
50
Coumarin
7-OH Coumarin
CYP2B6
50
Bupropion
Hydroxybupropion
CYP2C8
50
Taxol
6-OH Taxol
CYP2C9
75
Tolbutamide
4-OH Tolbutamide
CYP2C19
50
S-Mephenytoin
4 -OH Mephenytoin
CYP2E1
50
Chlorzoxazone
6-OH Chlorzoxazone
CYP3A4
125
Testosterone
6β-OH Testosterone
UGT
12.5
7-OH Coumarin
Coumarin-7glucuronide
ST
12.5
7-OH Coumarin
Coumarin-7-sulfate
The drug-metabolizing enzymes are the various P450 isoforms (CYP), UDP-dependent glucuronosyltransferase (UGT), and sulfotransferase (ST). The substrates and metabolites can be obtained commercially from Sigma-Aldrich, Inc. (www.sigmaaldrich.com) and BD Biosciences, Inc. (www.bdbiosciences.com).
Table 15.3 Positive control for P450 inhibition studies P450 isoforms
Inhibitors
CYP1A2
Furafylline
CYP2A6
Methoxypsoralen
CYP2C9
Sulfaphenazole
CYP2C19
Ticlopidine
CYP2D6
Quinidine
CYP2E1
Diethyldithiocarbamate
CYP2B6
Triethylenethiophosphoramide (Thiotepa)
CYP2C8
Quercetin
CYP3A4
Ketoconazole
The chemicals can be obtained commercially from Sigma-Aldrich, Inc. (www.sigmaaldrich.com).
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3. Methods 3.1. Cryopreserved Human Hepatocyte Thawing and Viability Determination 3.1.1. Thawing and Recovery of Cryopreserved Hepatocytes
1. Place a 50-mL tube of CHRM in a water bath at 37◦ C and allow approximately 2 h for the CHRM to reach 37◦ C (see Note 1). 2. Remove a vial of cryopreserved human hepatocytes from the liquid nitrogen freezer and immediately immerse the vial in a 37◦ C water bath for thawing. 3. Continuously shake the vial gently in the water bath until the ice crystal totally disappears. Place the vial on ice immediately to prevent rise in temperature above 4◦ C. 4. Quickly pour the thawed hepatocytes into the pre-warmed 50-mL tube of CHRM. 5. Add 1 mL of CHRM (from the tube with the hepatocytes) into the vial to recover cells left in the vial after pouring. Pour into the 50-mL tube of CHRM (avoid pipetting the cells at this stage as they are extremely fragile). 6. Gently invert the CHRM to allow even distribution of the hepatocytes in the medium. 7. Centrifuge at 100×g for 10 min to pellet the hepatocytes. 8. Discard the supernatant and resuspend the hepatocytes in 2 mL of hepatocyte suspension medium (HSM) for cell concentration and viability evaluation.
3.1.2. Viability Determination
1. Add 100 μL of the hepatocyte suspension into 700 μL of culture medium. 2. Add 200 μL of trypan blue solution. Invert to mix. Wait approximately 5 min at room temperature to allow dye penetration into damaged hepatocytes. 3. Load the mixture into a hemocytometer for counting. Hepatocyte viability is expressed as the percent of trypan blue-excluding cells: Viability(%) =Number of (trypan blue - excluding cells/total number of cells) × 100% Cell concentration is determined from the hemocytometer counts using the following equation: Cells/mL =number of viable cells per square × 10,000 × dilution factor
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The initial 10,000 factor is a correction for the liquid volume of each square of the hemocytometer (10−4 mL). The dilution factor using the above dilution scheme is 10. (A cell count of 25 trypan blue-excluding hepatocytes per square, for instance, would result in a cell concentration of 2.5 million hepatocytes per milliliter or 5.0 million viable hepatocytes per vial.) 3.2. Applications of Human Hepatocytes in Drug Development
The following are the procedures for the current routine applications of human hepatocytes in drug development. Cryopreserved human hepatocytes are routinely used for these assays. While the general scientific principles of in vitro screening methodologies have been previously reviewed (7, 8), specific procedure for each assay is described here.
3.2.1. Metabolic Stability Screening
A major drug-like property for new chemical entities (NCEs) is an appropriate metabolic stability to allow a practical frequency of drug administration (see Note 2). In the past, liver microsomes were used routinely for metabolic stability screening. However, as liver microsomes contain mainly enzymes such as the P450 isoforms for phase I oxidation, the assay would yield only metabolic stability toward microsomal oxidative enzyme metabolism, while in humans in vivo, the chemicals studied may be cleared via nonmicrosomal enzyme pathways such as conjugating enzyme pathways. Intact hepatocytes therefore represent a more relevant experimental system for metabolic stability evaluation than do liver microsomes (7, 8, 13, 17). We have developed a simple procedure for a relatively high-throughput screening for metabolic stability. The procedure for the hepatocyte metabolite stability assay is as follows: 1. Plating of human hepatocytes (35,000 cells in 50 μL per well) in 96-well plates in hepatocyte metabolism medium (HMM). 2. Addition of 50 μL per well of HMM containing two times the concentration of the test article to be evaluated. A concentration that is routinely used for metabolic stability evaluation is 1 μM. 3. Incubation at 37◦ C for multiple time points (for the determination of T1/2 , the time period leading to the disappearance of 50% of the parent test article) or, for screening purpose, one single time point (e.g. 30 min). 4. Addition of 100 μL acetonitrile (ACN) to terminate metabolism. 5. Centrifugation to remove hepatocytes and cellular macromolecules from the supernatant containing the remaining test article.
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6. LC/MS/MS quantification of the parent test article concentration after incubation. Results are in general expressed as % of the parent test article remaining after incubation: %Remaining = [(Concentration after incubation)/(Concentration before incubation)] × 100% In vivo hepatic intrinsic clearance can be further calculated from the T1/2 values as an initial estimation of the rate of human in vivo hepatic clearance of the NCE in question (5, 13). The laboratory of Lu et al. (18) has shown that the correlation between in vitro human hepatocytes and human in vivo results can be improved by considering not only the rate of metabolism, but also protein binding and intracellular uptake. 3.2.2. Metabolite Profiling and Species Comparison
The identification of metabolites formed from the parent drug (metabolite profiling) is important to drug development, as it allows the design of chemical structure to improve metabolic stability or to decrease cytotoxicity (see below). Metabolite identification is also important for the determination of the key drugmetabolizing enzyme pathways (e.g., oxidation or conjugation) as part of the program to understand drug–drug interaction potential. Lastly, metabolite profiling allows the selection of laboratory animal species most relevant to human for in vivo experimentation. An animal species which forms metabolites found in humans would be more relevant to one with metabolites different from those formed in humans. This species comparison is routinely performed using in vitro systems such as hepatocytes (e.g., from human, rat, mouse, guinea pig, dog, monkey). The procedure for the hepatocyte metabolite profiling assay is as follows (see Note 2): 1. Plating of human or animal hepatocytes (250,000 cells in 0.25 mL of HMM per well) in 24-well plates. 2. Addition of 0.25 mL of HMM containing two times the concentration of the drug to be evaluated. 3. Incubation at 37◦ C for 2 h. 4. Addition of 1 mL ACN to terminate reaction. 5. Centrifugation to remove cellular macromolecules. 6. LC/MS/MS quantification and identification of metabolites. The metabolites are in general identified based on mass-tocharge (m/z) ratio and with the identity ascertained based on differences in m/z ratio to the parent. For instance, a +16 change in m/z would indicate an addition of oxygen, suggesting the
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formation of a hydroxylated metabolites. The recent advancements of mass spectrometry including machines with accurate mass measurement and software for metabolite identification have greatly facilitated the metabolite profiling process. Our laboratory was one of the first to apply the hepatocyte metabolite profiling assay in drug development. We have shown that minor structural modifications can have profound effects on species differences in metabolite profiles (19). There are now plentiful reports on the use of isolated hepatocytes from multiple animal species and humans for the selection of the most appropriate animal species as an in vivo experimental model to predict human metabolism and pharmacokinetic properties (20). This assay is now an FDA requirement for Investigative Drug Application (21). 3.2.3. Drug–Drug Interaction Evaluation
3.2.3.1. Hepatocyte P450 Inhibition Assay (Evaluation of Inhibitory Drug–Drug Interaction
Drug–drug interactions represent an adverse drug property that has led to fatality, resulting in the withdrawal of marketed drugs. A drug may inhibit the metabolic clearance of a co-administered drug, leading to toxicity due to high systemic exposure of the affected drug (inhibitory drug–drug interactions). Conversely, a drug may enhance the metabolic clearance of a co-administered drug, leading to inefficacy due to lower than optimal systemic exposure (inductive drug–drug interactions). Inhibitory drug–drug interactions are caused by the inhibition of drugmetabolizing enzyme activities. Inductive drug–drug interactions are caused by the induction of drug-metabolizing enzyme activities. Both types of drug–drug interactions can be evaluated with human hepatocytes. In general, cytochrome P450-dependent monooxygenases (P450) are evaluated for drug–drug interaction potential. The procedures for the hepatocyte 450 inhibition and induction assays are as follows (see Note 3). 1. Add 490 μL of HMM containing 250,000 human hepatocytes in 24-well plates. 2. Add 5 μL of HMM containing one hundred times the concentration of the test article to be evaluated. 3. Pre-incubate for 15 min to allow interaction of the test article with the hepatocytes. 4. Add 5 μL of HMM containing one hundred times the concentration of the drug-metabolizing enzyme substrate (Table 15.2) into the same well. 5. Incubate for 30 min at 37◦ C. 6. Add 1 mL of ACN to terminate the reaction. 7. Centrifuge to remove cellular macromolecules. 8. LC/MS or HPLC quantification of drug-metabolizing enzyme metabolism of the substrate.
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9. The P450 isoform-specific substrates used routinely for the inhibitory drug–drug interaction assay and isoform-specific inhibitors which can be used as positive controls for the assay are shown in Tables 15.2 and 15.3. Results of inhibition assays are usually presented as relative activity: Relative activity (% ) = [activity (treatment)/activity (negative control)] × 100 Based on the relativity, EC50 values and K calculated (5). 3.2.3.2. Hepatocyte P450 Induction Assay (Evaluation of Inductive Drug–Drug Interaction Potential)
i
values can be
1. Add 500 μL of hepatocyte plating medium (HPM) containing 0.35–0.40 million plateable, cryopreserved human hepatocytes or freshly isolated human hepatocytes into each well of a collagen-coated 24-well plate(see Note 3). It is critical that the resulting monolayer culture is nearly 100% confluent. The day of hepatocyte plating is day 0 . 2. After 4 h of culturing, replace medium with that containing 0.25 mg/mL MatrigelTM . 3. After overnight incubation (day 1), remove medium and replace with hepatocyte induction medium (HIM). Culture the hepatocyte for another day. 4. On day 2, change medium to HIM containing the desired concentration of the drug to be evaluated for enzyme induction potential. 5. On days 3, 4, and 5, change medium daily to HIM containing the drugs to be evaluated to allow a total of 72 h of treatment. 6. On day 6, remove treatment medium and replace with 0.5 mL of HMM containing specific drug-metabolizing enzyme substrates (Table 15.2) and incubate for an additional 30 min. 7. Add 1 mL of ACN to terminate the reaction. 8. LC/MS or HPLC quantification of drug-metabolizing enzyme metabolism of the substrate. Induction results are usually expressed as percentage of negative (solvent) control: Induction (% ) = activity (treatment)/activity (solvent control) × 100% US FDA recommends the evaluation of CYP1A2 and CYP3A4 for induction studies, using substrates as specified in Table 15.2. The argument is that CYP2B6, CYP2C9, and
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CYP2C19 inducers are also CYP3A4 inducers. US FDA also requires enzyme induction studies with human hepatocytes from three individual donors and accepts results from either plateable cryopreserved human hepatocytes or freshly isolated human hepatocytes. Results are compared to those from positive controls, omeprazole (10 μM; for CYP1A2 induction) and rifampin (10 μM; for CYP3A4 induction). FDA considers responses that are equal to or higher than 40% of positive controls to be positive findings (21). Induction potential can also be presented as EC50 (concentration yielding 50% induction) values. 3.3. Hepatotoxicity Screening
Hepatotoxicity is a major manifestation of drug toxicity, the reasons being that the liver usually would receive the highest bolus concentration of an ingested drug. Further, the hepatocytes, the cells being responsible for drug metabolism, are the first cells to be affected by reactive or toxic metabolites. Isolated hepatocytes therefore represent a physiologically relevant experimental model for the evaluation of hepatotoxicity. In vitro hepatocyte cytotoxicity measurements have been found to be effective in the delineation of hepatotoxic and less hepatotoxic structures (5). Hepatocyte cytotoxicity assays can be performed using cryopreserved human hepatocytes in suspension or as plated cells. We recommend the use of plated cells to allow a prolonged treatment period (at least 24 h). The procedure is as follows (see Note 4): 1. Add 100 μL of hepatocyte plating medium containing 35,000 hepatocytes into each well of a collagen-coated 96-well plate. 2. Incubate for 24 h to allow attachment and the formation of a monolayer culture. 3. Change medium to hepatocyte incubation medium containing the desired concentration of the drugs to be evaluated for hepatotoxic potential. 4. Incubate for 24 h (longer or shorter treatment can be used with 72 h as the longest treatment time if media are not replaced) at 37◦ C. 5. Assay for cytotoxicity using a desired cytotoxicity endpoint (e.g., for the quantification of cellular ATP content, add 50 μL of lysis buffer followed by 50 μL of luciferin–luciferase reagent followed by quantification of luminescence using a multiwell plate reader). Besides cellular ATP content, hepatocyte viability can also be determined using MTT metabolism and cytoplasmic enzyme leakage. ATP, however, represents the most quantitative and convenient endpoint. One caution is to ensure that the chemicals
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evaluated would not interfere with luciferase activity, which is key to ATP quantification by luminescence. In our laboratory, tamoxifen (highest concentration used of 200 μM) is used routinely as a positive control to demonstrate that the experimental conditions employed are adequate for the detection of cytotoxic effects. 3.4. Conclusion
An ideal drug candidate is one that is readily absorbed, has an acceptable plasma half-life to accommodate a convenient drug administration schedule, high efficacy, minimum toxicity, and minimum drug–drug interaction potential. Successful selection of drug candidates with these desired drug-like properties would greatly enhance the efficiency of drug development. The procedures described here with human hepatocytes can be used to aid the selection of the appropriate drug candidates with acceptable drug properties.
4. Notes Primary hepatocytes represent the “gold standard” for drug metabolism, drug–drug interactions, and in vitro hepatotoxicity studies. The quality of the data, however, is dependent on the quality of the hepatocytes. The following are important aspects of using hepatocytes in various studies. 1. Cryopreserved human hepatocytes should be stored in liquid nitrogen, preferably in the vapor phase. For best results, the vial of cryopreserved hepatocytes should be transferred from liquid nitrogen storage to the 37◦ C water bath with minimum transit time. In most laboratories, the liquid nitrogen storage vessels are situated in a different location from the laboratory where the experiments are to be performed. The best procedure is to place the vial in a liquid nitrogencontaining transport vessel (e.g., foam box or liquid nitrogen shipping Dewar) for transport to the laboratory where thawing of the hepatocytes is performed. Avoid pipetting of the hepatocytes immediately after thawing as the cells are most fragile at that stage. Pour the thawed contents into the 50-mL tube with the pre-warmed CHRM. Rinse the vial by pipetting 1 mL of the CHRM into the vial, then pour the rinse into the CHRM tube. 2. For metabolic stability and metabolite profiling studies, cryopreserved human hepatocytes pooled from multiple donors allow results representing the “average” human population. This use of pooled hepatocytes is akin to the use
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of liver microsomes that are routinely prepared from multiple human livers. In cases where the test article being studied is very slowly metabolized, it may be necessary to use “plateable” cryopreserved human hepatocytes and prolonged incubation periods (e.g., 6–24 h). Hepatocytes in suspension would lose viability with time (approximately 5–10% per hour) and therefore cannot be used for these prolonged incubations. 3. For P450 inhibition and induction studies, it is important to make sure that the results are not compromised by cytotoxicity of the substance studied. It may be prudent to first evaluate cytotoxicity for dose-selection purpose. Concurrent cytotoxicity evaluation, especially for induction studies, is recommended. Cytotoxicity can be evaluated using the in vitro hepatotoxicity assays described in this chapter. 4. As hepatocytes are the site of metabolism, cytotoxicity studies with primary hepatocytes can provide valuable information on the role of metabolism in the cytotoxicity of the chemical being studied. In our laboratory, we have developed an assay (cytotoxic metabolic pathway identification assay (CMPIA) using P450 inhibitors to evaluate the role of specific P450 isoforms in the cytotoxicity observed (22). We have also developed a novel co-culture system the integrated discrete multiple organ co-culture (IdMOC) (23, 24), with which hepatocytes are co-cultured with cells from nonhepatic organs such as lung, kidney, neurons for the evaluation of multiple organ cytotoxicity in the presence of hepatic metabolism. References 1. DiMasi, J.A., Hansen, R.W., and Grabowski, H.G. (2003) The price of innovation: new estimates of drug development costs. J. Health Econ. 22, 151–185. 2. Guengerich, F.P. (2006) Cytochrome P450 s and other enzymes in drug metabolism and toxicity. AAPS J. 8, E101–E111. 3. Kola, I. and Landis, J. (2004) Can the pharmaceutical industry reduce attrition rates? Nat. Rev. Drug Discov. 3, 711–715. 4. Fry, J.R. (1982) The metabolism of drugs by isolated hepatocytes. Q. Rev. Drug Metab. Drug Interact. 4, 99–122. 5. Li, A.P. (2007) Human hepatocytes: isolation, cryopreservation and applications in drug development. Chem. Biol. Interact. 168, 16–29.
6. Gomez-Lechon, M.J., Castell, J.V., and Donato, M.T. (2007) Hepatocytes – the choice to investigate drug metabolism and toxicity in man: in vitro variability as a reflection of in vivo. Chem. Biol. Interact. 168, 30–50. 7. Li, A.P. (2004) In vitro approaches to evaluate ADMET drug properties. Curr. Top. Med. Chem. 4, 701–706. 8. Li, A.P. (2001) Screening for human ADME/Tox drug properties in drug discovery. Drug Discov. Today 6, 357–366. 9. Hewitt, N.J., Lechon, M.J., Houston, J.B., Hallifax, D., Brown, H.S., Maurel, P., Kenna, J.G., Gustavsson, L., Lohmann, C., Skonberg, C., Guillouzo, A., Tuschl, G., Li, A.P., LeCluyse, E., Groothuis, G.M., and Hengstler, J.G. (2007) Primary hepatocytes:
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Chapter 16 The Use of Human Hepatocytes to Investigate Drug Metabolism and CYP Enzyme Induction Sylvie Klieber, François Torreilles, François Guillou, and Gérard Fabre Abstract Over the past two decades, attrition of new drug candidates which entered into development increased strongly mainly due to sub-optimal ADME profiles. Major problems were linked to poor metabolic stability and drug–drug interactions linked to inhibition or induction of metabolism. Since most small molecule (MW below 1000) drugs are cleared from the body by the liver, primary cultures of human hepatocytes became the most predictive and widely used in vitro model for drug metabolism studies as well as enzyme induction. For this purpose, well-established and robust in vitro assays for the measurement of cell viability, metabolic activity, and cytochrome P450 (CYP) mRNA expression levels are needed to characterize the quality of the isolated and/or cryopreserved hepatocytes used to perform such studies. Key words: Fresh and cryopreserved human hepatocytes, phenotyping, CYP, enzyme activities, enzyme induction, RT-PCR.
1. Introduction Primary cultures of human hepatocytes are a powerful and predictive in vitro model for performing drug metabolism studies (determination of in vitro intrinsic clearance and enzyme mapping) and/or enzyme induction studies. Since they are whole cells isolated directly from liver biopsies, the hepatocytes in culture retain a very physiologically relevant environment and express the full panel of drug-metabolizing enzymes, therefore combining phase I and phase II metabolic reactions. They also allow for intracellular distribution and potentially any concentration gradients driven by plasma membrane or intra-cellular transporters, which may govern the access of substrate/inhibitors to the enzyme P. Maurel (ed.), Hepatocytes, Methods in Molecular Biology 640, DOI 10.1007/978-1-60761-688-7_16, © Springer Science+Business Media, LLC 2010
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active sites (1). Indeed, it is now well recognized that hepatocytes retain high enough levels of their CYP activities and protein contents after 24 h of culture (2, 3), thus allowing early evaluation of human drug metabolism. However, the scarcity of availability of fresh human hepatocytes makes those studies difficult and expensive, limiting the number of molecules which can be tested. Over the last decade, the improvement of cellular cryopreservation and the commercial availability of highly viable, plateable, and functional cells made human hepatocytes a more readily available in vitro tool, thus decreasing the need for fresh human tissue and allowing routine screening of new chemical entities (NECs) on this model, provided the cells have priorly been carefully selected and cultured. The aim of this chapter is to document the authors’ experience in the characterization and validation of reliable fresh and cryopreserved human hepatocyte batches for in vitro drug metabolism as well as CYP gene induction studies. Indeed, a good viability and an efficient plating of the cells (see Note 1) represent critical elements for the successful selection of human hepatocytes but also, and above all, it is fundamental to obtain satisfactory and well-characterized functionalities such as drug-metabolizing activities and CYP gene inducibility. See also Chapter 15 and 17 – 19.
2. Materials 2.1. Human Tissue
1. Cryopreserved human hepatocytes (BD Gentest, Bedford, MA; Celsis-IVT, Chicago, USA; CellzDirect, Carlsbad, CA; Biopredic, Rennes, France; Cambrex, Charles City, USA) are stored in liquid nitrogen until required. 2. Fresh human liver tissue was obtained either from donors undergoing partial hepatectomy or from unused liver portions from patients undergoing liver transplantation (see Note 2).
2.2. Cell Culture
1. Plating medium: Ham’s F12/William’s E medium 50/50 (v/v) (Gibco/BRL, Bethesda, MD) supplemented with 10% decomplemented fetal calf serum (FCS; Gibco), 10 mg/L insulin, 0.8 mg/L glucagon (Sigma, St. Louis, MO), 100 IU penicillin G, and 100 μg/mL streptomycin (Gibco). 2. Culture medium: Ham’s F12/William’s E medium 50/50 (v/v) supplemented with 3.6 g/L HEPES, 4 mg/L ethanolamine, 10 mg/L transferrin, 1.4 mg/L linoleic acid– albumin, 252 mg/L glucose, 44 mg/L sodium pyruvate, 50 mg/L ascorbic acid, 104 mg/L arginine, and 0.7 g/L L-glutamine (4) (all from Sigma).
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3. Forty-eight-well and 96-well collagen I-coated plates (BD Biosciences, Bedford, MA). 2.3. Chemicals
1. Phenacetin, 4-acetamidophenol, tolbutamide, 4methylhydroxytolbutamide, dextromethorphan, dextrorphan, midazolam, 1 -hydroxymidazolam, DMSO, dexamethasone, diclofenac, 4-hydroxytamoxifen, and menadione (Sigma). 2. 1 -Hydroxymidazolam glucuronide (synthesized by the Isotope Chemistry and Metabolites Department of SanofiAventis Recherche located in Chilly-Mazarin, France) solubilized in distilled water. 3. Reference inducers: Omeprazole for CYP1A1 and CYP1A2 and rifampicin for CYP3A4 (Sigma). 4. All other chemicals and reagents used were obtained from usual commercial sources and were of the highest commercially available grade.
2.4. Analytical Materials and Equipments
R 1. C18 Hypersil BDS column, 125 mm ×3.0 mm i.d., 3 μm particle size (Agilent).
2. BioRobot 8000, RNeasy 96 BioRobot 8000 Kit, RNase-free water and RNase-free DNase Set and buffer RLT (Qiagen, Valencia CA). 3. High-capacity cDNA archive kit, Taqman Fast Universal PCR Master Mix, Fast 96-Well Optical Reaction Plate with barcode, 96-Well Optical Reaction Plate with barcode (PE Applied Biosystems, UK). 4. Probes and primers (Applied Biosystems, UK). R 5. TaqMan Fast Universal PCR Master Mix and 7500 Fast Real-Time PCR System (PE Applied Biosystems, UK). R HS Kit (Lonza Rockland, ME, USA). 6. ATP ViaLight
7. Bio-Tek Synergy HT Microplate Reader (Bio-Tek Instruments, Inc., Winooski, USA). 8. BIOST@T-SPEED software developed at Sanofi-Aventis R & D.
3. Methods 3.1. Evaluation of Drug-Metabolizing Capacities
The difficulty here is that the variability observed in human hepatocytes reflects the existing phenotypic heterogeneity of cytochrome P450 expression in human liver within the population (3). Indeed, in order to be as predictive as possible
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of the in vivo situation in terms of variability, numerous studies on human hepatocyte preparations obtained from different donors would be required. In order to limit the number of studies, the characterization by the authors of numerous fresh human hepatocytes over the past years has allowed them to establish the drug-metabolizing phenotype of an average “generic” human, taking into account both inter-individual and/or interpreparation variability, and this average phenotype now serves as a basis for the selection of reliable human hepatocyte batches. Thus, human hepatocyte preparations are systematically characterized with regard to their capacity to metabolize four CYP isoform-selective substrates used as phenotypic markers for the four main human CYP isoforms involved in drug metabolism, i.e., phenacetin for CYP1A2, tolbutamide for CYP2C9, dextromethorphan for CYP2D6, and midazolam for CYP3A4 activity (Table 16.1).
Table 16.1 Reference substrates and specific enzymatic reactions catalyzed by the four main human CYP isoforms CYP
Marker substrate
Enzymatic reaction
Specific metabolite quantified
CYP1A2
Phenacetin
O-Deethylation
4-Acetamidophenol
CYP2C9
Tolbutamide
Methylhydroxylation
4-Methylhydroxytolbutamide
CYP2D6
Dextromethorphan
O-Demethylation
Dextrorphan
CYP3A4
Midazolam
1 -Hydroxylation followed conjugation
1 -Hydroxymidazolam followed (1 -OH-MDZ) by 1 -OH-MDZ glucuronidation (1 -OH-MDZ-Glu)
by
1. Thawing procedures of cryopreserved human hepatocytes. Cryopreserved human hepatocyte batches were thawed strictly according to each supplier’s protocol (BD, Celsis-IVT, CellzDirect, etc.). Briefly, the vials containing the cryopreserved hepatocytes were removed from liquid nitrogen storage. Vials were thawed in a 37◦ C water bath (75–90 s) and quickly poured in pre-warmed seeding medium (see Note 3). An additional washing step by centrifugation at 50 or 100×g for 5 min was performed depending on the origin of the cells. The cell pellet was then resuspended in 2 mL per vial of seeding medium before assessing cellular viability. 2. Fresh hepatocytes isolation. Liver tissue biopsies were rapidly transported from the operating room in ice-cold University of Wisconsin solution at 4◦ C. Hepatocytes were obtained according to the two-step collagenase perfusion technique first described by Berry and Friend (5) and adapted by Fabre et al. (6). This perfusion technique allows several billions of
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cells to be obtained, up to 4×109 hepatocytes depending on the size of the hepatic sample, with cell viability typically higher than 85%. Following different washing steps (filtration through 150- and 250-μm nylon mesh, and low-speed centrifugation at 50×g for 5 min, threefold), a concentrated cellular suspension is obtained. 3. Cell viability. Cell viability was assessed using the trypan blue exclusion test (see Note 4). 4. Cell culture. After isolation and/or thawing, cells were diluted to a 0.84 million cells/mL suspension in seeding medium, and 200 μL of this cell suspension was added to each well of collagen I-coated 48-well plates. This cell density corresponds to a confluent monolayer. Cells are evenly distributed by gentle agitation and placed in an incubator at 37◦ C under 5% CO2 and 100% humidified atmosphere. After 4–6 h of incubation at 37◦ C, period during which hepatocytes attach to the collagen matrix, the seeding medium is removed and replaced by 100 μL of culture medium devoid of FCS. Cells are kept overnight in order to recover from isolation or thawing procedure. 5. Characterization of drug metabolism capacity. The day after plating, the medium is renewed with 90 μL of fresh culture medium. CYP isoform probes are added directly. Prepare a 20 mM stock solution of dextromethorphan and 5 mM stock solutions of midazolam, tolbutamide, and phenacetin in DMSO (i.e., 1,000× stock solutions, see Note 5). Dilute those solutions 100-fold in culture medium containing 1% (w/v) BSA in order to obtain 10× working solutions. Add 10 μL of each working solution of each CYP isoform probe to 90 μL of medium already present in the wells in order to achieve a 5 μM final concentration for midazolam, tolbutamide, and phenacetin, 20 μM for dextromethorphan, and a 0.1% (v or w/v) final concentration for solvent and BSA (see Note 6). For the determination of the metabolism of the different probes, kinetic studies are performed for over either 6 h for dextromethorphan and midazolam (sampling times: 0.5, 1, 2, 3, 4, and 6 h) or 24 h for phenacetin and tolbutamide (sampling times: 0.5, 1, 2, 3, 4, 6, 8, and 24 h). These differences in the experimental conditions were based on primary determinations of the rate of biotransformation of the different CYP probes (see Note 7). At each selected time point, add 700 μL of an acetonitrile/water mixture (40/30, v/v) to each specific well, and both extracellular medium and cell compartment are scraped and mixed together (see Note 8). Transfer the cell homogenate to a glass test tube and store frozen at −20◦ C until further analysis.
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6. Bioanalysis. Prior to analysis, cell homogenates were sonicated for a few seconds, homogenized, and centrifuged at 3,000 rpm for 20 min. After sample transfer to a 96-well plate and threefold dilution, supernatants were then analyzed for unchanged drug and specific metabolites by LC/MS–MS (Table 16.2): midazolam, 1 hydroxymidazolam and its glucuronide, dextromethorphan and dextrorphan, tolbutamide and 4-hydroxytolbutamide, phenacetin, and 4-acetamidophenol. The data were collected and processed using MassLynx 4.0 Software (WatersMicromass). The chromatograph was fitted with a C18 R Hypersil BDS column (125×3.0 mm i.d., 3 μm particle size). The mobile phase was a mixture of 1.5 g/L ammonium acetate–2 mL/L formic acid (solvent A) and 80% acetonitrile −20% methanol −0.15 g/L ammonium acetate–2 mL/L formic acid(solvent B). Solvent programmer was set to deliver a flow rate of 0.25 mL/min. Compounds were eluted with a linear gradient from 10% to 90% solvent B for over 1.5 min, followed by an isocratic step at 90% for 3 min. 7. Expression of the results. Results are expressed as initial velocity of metabolite formation respective to each isoform in nmol/h/106 hepatocytes (Table 16.3, see Notes 9–11).
3.2. Evaluation of CYP Gene Inducibility
The cytochrome P450 (CYP) is a family of heme containing monooxygenases that catalyzes the oxidative metabolism of a large number of endogenous and exogenous compounds, including pharmaceuticals (7). The majority of drug-metabolizing isoforms belong to the CYP families 1–3 and are responsible for biotransformation of approximately 75% of all marketed drugs (8). Several of the CYP gene expression can be regulated by a wide range of chemicals (9). Some of these CYPs may be induced several fold by specific drugs. Because of the prevalence of multidrug therapy, the large number of drug-metabolizing enzymes, and the potential for drug–drug interactions (DDIs), early evaluation of the potency of new chemical entities (NCEs) to induce CYP is paramount to allow developing new drugs devoid of these potentially negative traits (10). Determination of the mRNA content of each CYP allows to measure CYP expression in biological tissue samples. In this chapter we describe an in vitro procedure to study induction of three major human CYPs, namely CYP1A1, CYP1A2, and CYP3A4. RT-PCR is a highly sensitive and specific method which allows the measurement of high- and low-abundant mRNA CYPs in cultured cells. With cytotoxic compounds a decrease in cell number may be observed. These losses in viability have large consequences on
20
5
5
MDZ
Tolbutamide
24
6
6
Tolbutamide, C12 H18 N2 O3 S 4-OH-Tolbutamide, C12 H18 N2 O4 S
MDZ, C18 H13 ClFN3 1 -OH-MDZ, C18 H13 ClFN3 O 1 -OH-MDZ-Glu, C24 H22 ClFN3 O7
Dextromethorphan, C18 H25 NO Dextrorphan, C17 H23 NO
285.1 > 186.1
269.2 > 170.1
326.1 > 291.2 342.2 > 324.2 518.1 > 324.1
258.2 > 157.2
272.2 > 147.2
152.2 > 110.1
180.2 > 110.1
Dextromethorphan
Phenacetin, C10 H13 NO2 4-Acetamidophenol, C8 H9 NO2
5
Phenacetin
24
Formula and mass transitions
Substrate concentration (μM)
Compound
Incubation time (hours)
LC-MS/MS conditions
In vitro conditions
30
30
30
30
Cone voltage (V)
16
28 22 25
ES−
ES+
ES+
ES+ 18 15
32
Ionization mode
Collision energy (eV)
Table 16.2 Incubation and analytical conditions for substrates and metabolites used for the phenotyping of fresh and cryopreserved human hepatocytes
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Table 16.3 Drug-metabolizing activities in primary culture of fresh and cryopreserved human hepatocytes
Enzyme CYP1A2
CYP2C9
CYP2D6
CYP3A4
Enzymatic reaction O-Deethylation
Methylhydroxylation
O-Demethylation
1’-Hydroxylation + conjugation
Activity∗
Number of donors n
Ratio#
Fresh
1.101 ± 0.933 (0.034–4.004)
69
117
Cryopreserved
0.278 ± 0.549 (0.006–3.135)
44
522
Fresh
0.056 ± 0.036 (0.003–0.162)
59
54
Cryopreserved
0.045 ± 0.041 (0.004–0.189)
44
47
Fresh
0.933 ± 0.639 (0.017–3.744)
87
220
Cryopreserved
0.676 ± 0.587 (0.006–2.566)
44
428
Fresh
0.790 ± 0.640 (0.083–3.900)
89
47
Cryopreserved
0.481 ± 0.506 (0.016–1.830)
44
114
∗Mean ± SD activity measured in 6- or 24-h cultured human hepatocytes (preparations for which no CYP activity was detected were excluded). Range values are given in parentheses. Values are expressed as nmol/h/106 hepatocytes. # Ratio between the highest and the lowest activity values.
the regulation of the expression of numerous genes, with aberrant fold increases of the target genes. These also correlate with a poor yield in total mRNA recovered per well, confirmed by the increased Ct values of the housekeeping gene. Using cellular adenosine triphosphate (ATP) content as an endpoint, the cytotoxicity of the test compounds was evaluated in parallel with CYP induction to avoid working at toxic concentrations. 1. Cell culture and treatment. Fresh human hepatocytes were obtained according to the two-step collagenase perfusion technique or cryopreserved human hepatocytes were used in these experiments (see Note 12). Cells were counted, diluted to 0.84×106 cells/mL in pre-warmed plating medium (37◦ C), and plated at 85 μL per well in 96-well collagen I-coated plates. Plates were incubated for 4 h at 37◦ C under 5% CO2 and 100% humidified atmosphere. Following this cell attachment period, plating medium was removed and hepatocytes were treated daily, for 2 days (48 h), with 60 μL per well of incubation medium containing either vehicle (DMSO at a final concentration of 0.6%, v/v) or reference inducers (30 μM omeprazole, 10 μM β-naphthoflavone,
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or 10 μM rifampicin) or test compounds at 1, 3, 10, and 30 μM. For each lot of hepatocytes, two separate wells per treatment condition were used. 2. Isolation and purification of total RNA from cell cultures. After 48 h of incubation with tested compounds, cell culture medium was removed and cells were lysed with 160 μL of buffer RLT. Then extraction and purification of total cellular RNA were performed on the BioRobot 8000. The RNeasy method was used following the instructions supplied with the RNeasy 96 BioRobot 8000 Kit and included an oncolumn DNase I digestion to minimize genomic DNA contamination. At the end of the process, purified mRNA was eluted under 100 μL of RNase-free water. 3. Reverse transcription. Reverse transcription was carried out in the 96-Well Optical Reaction Plate with barcode. The cDNA was synthesized from 50 μL of total RNA using the high-capacity cDNA archive kit as per the manufacturer’s instructions in a final volume of 100 μL. The thermal cycling conditions were 25◦ C for 10 min, 37◦ C for 120 min, and 85◦ C for 5 s. 4. Real-time PCR plate preparation. A process was created on the BioRobot 8000 to distribute four times 8 μL of cDNA from 100 μL in the 96-Well Optical Reaction Plate with barcode in four Fast 96-Well Optical Reaction Plate with barcode. Each Fast 96-Well Optical Reaction Plate with barcode will be used to measure the expression of one of the four analyzed human genes (CYP1A1, CYP1A2, CYP3A4, or β-2-microblogulin). 5. Measurement of human CYP mRNAs by RT-PCR. Applied Biosystems 60× gene expression kits were used for CYP1A1 (Hs00167927_m1), CYP1A2 (Hs00153120_m1), CYP3A4 (Hs00604506_m1) and the house keeping gene β-2-microblogulin (Hs99999907_m1). Real-Time polymerase chain reaction (RT-PCR) was performed using R TaqMan Fast Universal PCR Master Mix according to the manufacturer’s instructions. Amplification and detection were performed on 8 μL of cDNA in a final volume of 20 μL and contained 300 nM forward primer, 300 nM reverse primer, and 200 nM TaqMan probe labeled with the FAM and TAMRA reporter dyes. These reactions were performed on a 7500 Fast Real-Time PCR System. Typical profile times for these studies were 95◦ C for 20 s, 40 cycles at 95◦ C for 3 s, and 60◦ C for 30 s. Semi-quantitation of the target to β-2-microblogulin cDNAs in all samples was normalized Ct = Ctgeneofinterest − Ctβ2 M , and the effect of each compound on the target cDNA was expressed compared
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to the amount in the DMSO control sample, i.e., the calibrator (Ct = Cttreatedcells − Ctcalibrator ). For each replicate of the sample, fold changes in target gene expression were by taking 2 to the power of the determined value Ct 2−Ct . Then an average of the two values was determined (mean). For each CYP isoform, results were also expressed as percentage of Emax , Emax being the effect observed with the corresponding reference inducer, i.e., omeprazole for CYP1A1 and CYP1A2, and rifampicin for CYP3A4, for which the expression level value has been arbitrarily fixed to 100% (see Note 13). 6. Cell viability analysis. To detect possible cytotoxic effects of the tested compound under investigation, a cytotoxicity assessment was performed in parallel with the CYP induction study. Cytotoxic assays were carried out in the same culture conditions as induction assays, except that prototypic inducers were replaced by cytotoxic reference compounds including vehicle as negative control, i.e., 0.6% DMSO, which corresponds to a 100% cell viability, 100 μM menadione as 100% positive control (this molecule totally disrupts the plasma membrane of hepatocytes corresponding to a 0% cell viability), and diclofenac, 4-hydroxytamoxifen, and menadione as cytotoxic references, over a concentration range of 1–300 μM. ATP content analysis was performed using R the ATP ViaLight HS Kit. Briefly, the hepatocytes were lysed after 48-h incubation by the addition of 100 μL of nucleotide-releasing reagent (NRR) in each well followed 5 min later by the addition of 20 μL of ATP monitoring reagent. Luminescence was quantified immediately using a Bio-Tek Synergy HT Microplate Reader. All results are expressed as the percentage of viable cells in treated hepatocytes, relative to control conditions. The TC50 values (toxic concentration corresponding to 50% of cell lysis) are determined using the BIOST@T-SPEED software developed at Sanofi-Aventis R & D.
4. Notes 1. Cryopreserved hepatocytes in suspension were successfully used in short-term metabolism studies. Nevertheless, hepatocytes in suspension only allow investigating drug exhibiting an extensive metabolism since cells cannot be cultured for longer than 4–6 h. Indeed, a prolonged culture in suspension will induce hepatocytes to apoptosis, leading to
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the release of cellular organites and intra-cellular content (enzymes, etc.), which can affect the metabolism of the drug. Cultures of plateable cryopreserved human hepatocytes are, therefore, an excellent model to obtain data for metabolically low turnover compounds. Moreover, enzyme induction studies, for mRNA expression as well as for enzyme activity, require prolonged time in culture, which renders the use of plateable human hepatocytes mandatory. In general, only a small percentage of cryopreserved cells can attach onto collagen I-coated plates (less than 50%). Among the 44 “plateable” batches we have characterized, only one batch was not able to attach on collagen-coated plates. 2. Olinga et al. (11) reported that in terms of metabolic capacity, hepatocytes obtained following perfusions of liver lobes obtained from partial hepatectomy or from transplantation can be used in the same study without consideration of the procurement of the tissue. 3. Viability, plating efficiency and morphology. The thawing procedure should be as quick as possible and keeping hepatocyte vials too long a time on ice should be avoided because of deleterious effects on cell viability. The efficiency of plating of the hepatocytes is the first sign of a good hepatocyte preparation. A monolayer with confluence higher than 80% should always be achieved in order to guarantee the maintenance of the highly differentiated phenotype of the hepatocytes, which is ensured by a tight cell–cell contact (polyhedral form of the cells with refringent nuclei). 4. Cell counting was performed immediately after the cells have been added; incubation at 37◦ C for few minutes was not performed like some authors can advocate since this would result in over-estimated cell death rate. Indeed, especially for cryopreserved human hepatocytes, the cell membrane of which is rendered more permeable due to the freezing/thawing procedure, some cells can exhibit a blueshaped membrane without being apoptotic or necrotic. Care should be taken to count cells only with a bluecolored cytoplasm. 5. Substrates and metabolite stock solutions can be stored at −20◦ C for up to 2 years. 6. A too high DMSO concentration would result in either induction of the CYP2E1 isoform or reduction of CYP2C9/19 and CYP3A4 activities (12). At 0.1% (v/v), effect of DMSO on drug-metabolizing enzymes is negligible.
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7. In order to strictly characterize each CYP isoform it is mandatory to evaluate the activity in the linear part of the metabolite formation curve, i.e., initial rate. 8. The qualitative and quantitative analysis of drug (and possibly metabolite) distribution between intra- and extracellular compartments can be of great interest for a better understanding of transport, accumulation, and metabolic processes. By analyzing both compartments, highly and slowly metabolized drugs can be differentiated since it allows differentiating between non-metabolized/ intensively distributed drugs and highly metabolized drugs. 9. Analysis of the activity level of the major CYPs in fresh human hepatocytes revealed considerable variations which make it difficult to define a “normal liver.” Phenotypic differences observed in vitro for drug-metabolizing enzymes are representative of the phenotypic variability observed in vivo. CYP1A2 and CYP2D6 showed the greatest interindividual and/or inter-preparation variability followed equally by CYP2C9 and CYP3A4. CYP1A2 variability, as opposed to CYP2D6, is unlikely attributable to genetic polymorphism but is probably directly linked to gene expression modulation as this enzyme is highly inducible by environmental factors like xenobiotics or food habits. Nevertheless, it has to be noted that a part of the variability observed here is also linked, in addition to the phenotype/genotype or medical/nutritional status, to artifactual factors like the quality of the tissue (depending on the conservation and the transport following surgical resection) or the actual proceeding of the hepatocyte isolation procedure. In order to minimize this variability not directly due to the donor solely, only human hepatocyte preparations exhibiting acceptable morphological characteristics and satisfactory viabilities (>85%) were included in this set of data. Moreover, a human hepatocyte preparation was rejected for metabolic capacity if all four CYP activities tested were low. 10. Among the different cryopreserved batches tested, cells chosen for our metabolism studies showed a good cell viability (above 90%) with at least 80% confluence and were metabolically active for at least one out of the four CYP activities tested compared to the mean CYP activities obtained on fresh hepatocytes, privileging the CYP3A4 activity, regarding the importance of this CYP isoform for drug metabolism. 11. Moreover, given the great inter-individual variability of P450 patterns in humans, the prediction of in vitro intrinsic metabolic clearance should be carried out, at
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least, on three different donors exhibiting different drugmetabolizing profile, i.e., low/high CYP2D6 activity, induced CYP1A2/CYP3A4 status. In this perspective, the creation of cell banks with various phenotypes has become of great importance. 12. Due to the large inter-preparation and/or inter-subject variability in the basal expression of the various genes and in the inducing effect of CYPs following treatment of cells with reference inducers, each hepatocyte preparation is analyzed individually and the potency of induction is compared to that of reference inducers. This required testing multiple concentrations using several lots of either fresh or cryopreserved human hepatocytes taking into account cell viability data to interpret the results. 13. Quantitative measurements by PCR technique are not easy due to the fact that minor variations in the different steps of the assay can be greatly magnified during the amplification step. A normalized quantification using a housekeeping gene allows minimizing such variations. Then, all results are expressed as the ratio of the expression levels of the investigated gene and that of the housekeeping gene in treated hepatocytes, normalized to control conditions (calibrator). Final expression levels are then expressed as a percentage of the Emax (Emax being the effect observed with the corresponding reference inducer, i.e., omeprazole for CYP1A1 and CYP1A2, and rifampicin for CYP3A4). The calibrator used is “untreated hepatocytes” (i.e., hepatocytes treated over the same period of time with 0.6% DMSO alone), for which the expression level value has been arbitrarily fixed to 1.
References 1. Hewitt, N.J., Lechon, M.J., Houston, J.B., Hallifax, D., Brown, H.S., Maurel, P. et al. (2007) Primary hepatocytes: current understanding of the regulation of metabolic enzymes and transporter proteins, and pharmaceutical practice for the use of hepatocytes in metabolism, enzyme induction, transporter, clearance, and hepatotoxicity studies. Drug Metab. Rev. 39, 159–234. 2. Rodriguez-Antona, C., Donato, M.T., Boobis, A., Edwards, R.J., Watts, P.S., Castell, J.V. et al. (2002) Cytochrome P450 expression in human hepatocytes and hepatoma cell lines: Molecular mechanisms that determine lower expression in cultured cells. Xenobiotica 32, 505–520.
3. Gomez-Lechon, M.J., Castell, J.V., and Donato M.T. (2007) Hepatocytes – the choice to investigate drug metabolism and toxicity in man: In vitro variability as a reflection of in vivo. Chem. Biol. Interact. 168, 30–50. 4. Isom, H.C. and Georgoff, I. (1984) Quantitative assay for albumin-producing liver cells after simian virus 40 transformation of rat hepatocytes maintained in chemically defined medium. Proc. Natl. Acad. Sci. USA 81, 6378–6382. 5. Berry, M.N. and Friend, D.S. (1969) High-yield preparation of isolated rat liver parenchymal cells: A biochemical and fine structural study. J. Cell. Biol. 43, 506–520.
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6. Fabre, G., Rahmani, R., Placidi, M., Combalbert, J., Covo, J., Cano, J.P. et al. (1988) Characterization of midazolam metabolism using human hepatic microsomal fractions and hepatocytes in suspension obtained by perfusing whole human livers. Biochem. Pharmacol. 37, 4389–4397. 7. Guengerich, F.P. (1990) Enzymatic oxidation of xenobiotic chemicals. Crit. Rev. Biochem. Mol. Biol. 25, 97–153. 8. Burke, M.D., Thompson, S., Elcombe, C.R., Halpert, J., Haaparanta, T., and Mayer, R.T. (1985) Ethoxy-, pentoxy- and benzyloxyphenoxazones and homologues: a series of substrates to distinguish between different induced cytochromes P-450. Biochem. Pharmacol. 34, 3337–3345. 9. LeCluyse, E.L. (2001) Human hepatocyte culture systems for the in vitro eval-
uation of cytochrome P450 expression and regulation. Eur. J. Pharm. Sci. 13, 343–368. 10. Silva, J.M., Morin, P.E., Day, S.H., Kennedy, B.P., Payette, P., Rushmore, T. et al. (1998) Refinement of an in vitro cell model for cytochrome P450 induction. Drug Metab. Dispos. 26, 490–496. 11. Olinga, P., Merema, M., Hof, I.H., de Jong, K.P., Slooff, M.J., Meijer, D.K. et al. (1998) Effect of human liver source on the functionality of isolated hepatocytes and liver slices. Drug Metab. Dispos. 26, 5–11. 12. Nicolas, J.M., Whomsley, R., Collard, P., and Roba, J. (1999) In vitro inhibition of human liver drug metabolizing enzymes by second generation antihistamines. Chem. Biol. Interact. 123, 63–79.
Chapter 17 The Use of Hepatocytes to Investigate UDP-Glucuronosyltransferases and Sulfotransferases Sylvie Fournel-Gigleux, Michael W.H. Coughtrie, Mohamed Ouzzine, and Jacques Magdalou Abstract Since phase II reactions quantitatively represent the most important pathways involved in drug biotransformation, the development and the use of in vitro approaches to predict glucuronidation and sulfation are currently attracting intense interest to assist in the selection of new drug candidates and for the optimization of dosage regimens for established drugs. At present, primary cultures of human hepatocytes represent the most suitable in vitro model for drug metabolism studies. This system theoretically expresses the full complement of drug-metabolizing enzymes associated with the endoplasmic reticulum (CYP and UDP-glucuronosyltransferases) or located in the cytosolic compartment (sulfotransferases), and relevant accessory proteins required for drug transport and excretion. Primary hepatocytes also represent a unique in vitro model for global examination of inductive potential of drugs on conjugation reactions (monitored as increases in mRNA content or activity). The progress in cryopreservation over the last decade has made available preserved hepatocytes to address key issues such as the (i) establishment of phase II metabolic profile and rate, (ii) identification of conjugation enzymes involved, and (iii) evaluation of drug–drug interactions. These advances allow a better assessment of phase II reactions during drug discovery and development. Key words: Phase II enzymes, UDP-glucuronosyltransferases, sulfotransferases, conjugation reaction, drug metabolism, human hepatocytes.
1. Introduction UDP-glucuronosyltransferases (UGTs, EC 2.4.1.17) and sulfotransferases (SULTs, EC 2.8.2) represent the major phase II drug-metabolizing enzymes. These multiple enzyme systems display extremely broad substrate specificity, catalyzing the biotransformation of a variety of drugs with diverse chemical structures belonging to multiple therapeutic classes. UGTs and SULTs often share similar substrates, especially among phenols P. Maurel (ed.), Hepatocytes, Methods in Molecular Biology 640, DOI 10.1007/978-1-60761-688-7_17, © Springer Science+Business Media, LLC 2010
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and amine-type compounds. Competition between the two conjugation pathways is governed by several factors, including kinetic properties of the enzymes (Km , Vmax ), differential induction of the individual isoforms, availability of the donor substrate, UDP-glucuronic acid (UDP-GlcA) and 3’-phosphoadenosine 5’-phosphosulfate (PAPS), respectively, and the physicochemical properties of the acceptor substrate. Glucurono- and sulfoconjugation processes generally lead to an increased polarity of hydrophobic compounds and also result, in many cases, in a loss of their biological activity. UGTs and SULTs also play a critical role in the generation of bioactive or even toxic compounds. Specifically, morphine, steroids, retinoids are all glucuronidated to more active or in some instances toxic compounds. Similar effects are observed in the case of sulfoconjugates, where certain drugs (e.g., minoxidil) and many dietary and environmental promutagens are activated following sulfation. Although drug–drug interactions between conjugated compounds occur with lower incidence than for oxidized metabolites, several studies emphasize the requirement of careful assessment of drug metabolism mediated by conjugation enzymes. Indeed, significant drug–drug interactions related to glucuronidation have been reported, such as those between atovaquone and zidovudine (1) or between the anti-epileptic drugs valproic acid and lamotrigine (2). For sulfation, drug–drug interactions are known for paracetamol and ethinylestradiol (3), although interactions with endogenous substrates for sulfation (e.g., thyroid hormones, steroids, catecholamines) may be much more important. The development of in vitro models for the characterization of conjugation reactions has taken benefits from the molecular characterization of the UGT and SULT superfamilies. Recent advances in the characterization of UGT isoforms in terms of substrate specificity and tissue expression suggest that UGT1A1, 1A3, 1A4, 1A6, 1A9, 2B7, and 2B15 are the main isoforms responsible for drug glucuronidation in liver and thus should be considered primarily during drug development process. For the sulfotransferases, the major forms involved in drug sulfation are SULTs 1A1, 1A3, 1B1, 1E1, and 2A1, although SULT1A3 is not expressed in the adult human liver, being a major form in the gastrointestinal tract. Although the use of in vitro systems such as human hepatocytes is suitable for studying the glucuronidation and sulfation pathways, the identification of the major isoforms involved in the conjugation of a particular drug is hampered by the broad and overlapping substrate specificity of the UGT and SULT enzymes. In contrast to CYP enzymes, only a limited number of isoform-selective UGT and SULT substrates have been identified to date (Table 17.1). 1-Naphthol and bilirubin/estradiol are commonly used to estimate the conjugation capacity of
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Table 17.1 Probe substrates for major human UGTs and SULTs involved in drug metabolism UGT enzyme
Substrate
SULT enzyme
Substrate
UGT1A1
Bilirubin/estradiol-3glucuronidation
SULT1A1
2-Aminophenol 4-Nitrophenol (2 μM)
Irinotecan UGT1A3
Hexafluoro-1α,25dihydroxyvitamin D3
SULT1A3
Dopamine
UGT1A6
Serotonin
SULT1B1
4-Nitrophenol (100 μM)
1-Naphthol UGT1A9
Propofol
SULT1E1
17β-Estradiol
UGT2B7
Morphine
SULT2A1
Dehydroepiandrosterone
UGT2B15
5-Oxazepam
Zidovudine
UGT1A6 and UGT1A1 isoenzymes, respectively. Propofol and morphine have been used as “probe” substrates for UGT1A9 and UGT2B7, respectively. For the SULTs, 2-aminophenol is a probe for SULT1A1 and dopamine for SULT1A3. For SULT1B1, no clear selective substrate has been found, although higher concentrations (100 μM) of 4-nitrophenol could be used (4). SULTs 1E1 and 2A1 can be followed using 17β-estradiol and dehydroepiandrosterone, respectively. Similarly, few selective inhibitors have been characterized. Triphenylcarboxylic acid derivatives have proven to be useful inhibitors of UGT1A1 responsible for bilirubin conjugation (5). Hecogenin and fluconazole have been shown to inhibit UGT1A4 and UG2B7, respectively (6). For SULTs, inhibition of SULT1A1 can be achieved with 2,6-dichloro-4-nitrophenol or pentachlorophenol, and mefenamic acid is a broad-spectrum SULT inhibitor. Phenotyping of these conjugation reactions with hepatocytes as enzyme source will undoubtedly improve as increasing numbers of isoform-selective substrates and inhibitors become available from the screening of compounds of greater structural complexity and diversity. In the meantime, prototypical drugmetabolizing enzyme inducers can be used to help identify isoforms responsible for the glucuronidation and/or the sulfation of a specific compound. Indeed, several studies have shown that phase II enzymes are mainly regulated by the aryl hydrocarbon receptor (AhR), the constitutive androstane receptor (CAR), and the pregnane X receptor (PXR) (7, 8). Differential induction of UGTs in primary hepatocytes is achieved by exposure of cells to AhR, CAR, and PXR agonists such as 3-methylcholanthrene, phenobarbital, dexamethazone, and rifampicin (9, 10), providing a
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useful tool to identify the UGT isoforms involved in the glucuronidation of new drugs. Finally, the use of primary hepatocytes remains the most accepted method to assess the potential of a therapeutic agent to cause phase II enzyme induction that may result in drug–drug interactions.
2. Materials 2.1. Assessment of Drug Conjugation by Human Hepatocytes 2.1.1. Hepatocyte Culture and Ex Vivo Drug Glucuronidation and Sulfation
1. Human hepatocytes are isolated from samples of liver tissue following ethical rules used in the collagenase method, as previously established by Pichard et al. (11). Human hepatocytes are also commercially available (Biopredic International, Rennes, France; BD Gentest, Bedford, MA, USA) as plated cells or cryopreserved hepatocytes. 2. Primary human hepatocyte culture medium: Ham’s F12/William’s medium E (GIBCO–Invitrogen CergyPontoise, France) is supplemented with 5% fetal calf serum, 2 mM glutamine, 1% (v/v) nonessential amino acids, 0.1 μM dexamethazone, 5 μg/mL insulin, 5 μg/mL transferrin, 5 ng/mL selenium, 100 U/mL penicillin, 100 μg/mL streptomycin, 0.25 μg/mL Fungizone, and 50 μg/mL vitamin C, as described in detail by Pichard et al. (11). 3. Trypan blue (0.4%; GIBCO–Invitrogen; store in dark bottle and filter after prolonged storage). 4. The drugs to be tested for can be dissolved in dimethyl sulfoxide (DMSO) [final concentration of solvent in the culture medium less than 0.5% (v/v)] or, where water soluble, in phosphate buffered saline (PBS). 5. Heating incubator set at 37◦ C in 95% air, 5% CO2 humidified atmosphere. 6. Trypan blue exclusion test CountessTM automated cell counter (Thermo Fisher–Invitrogen).
2.1.2. Preparation of Microsomes and Cytosol from Hepatocytes
1. Homogenization buffer: 10 mM Tris–HCl (pH 7.4), 250 mM sucrose, 0.1 mM phenylmethylsulfonyl fluoride, 5% (v/v) glycerol. 2. Dounce homogenizer (motor- or hand-driven) (Fisher Bioblock Scientific, Illkirch, France). 3. Micro-ultracentrifuge (Sorvall RC-M120GX; ThermoScientific, Courtabœuf, France).
2.1.3. In Vitro Measurement of UGT Activity Toward Drugs
1. UDP-GlcA, sodium salt (Roche–Boehringer, Mannheim, Germany).
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2. UDP-[U-14 C]-GlcA [>180 mCi (6.66 GBq)/mmol] (NEN PerkinElmer, Courtabœuf, France) in ethanol– water (7:3, v/v). 3. Incubation buffer: 100 mM Tris–HCl (pH 7.4), 10 mM MgCl2 . 4. Acceptor substrate (see below) stock solution: 20 mM in DMSO. R 5. Thin layer chromatography (TLC) plates Partisil LK6DF silica gel with fluorescent indicator, thickness 250 μm (Whatman, Versailles, France).
6. Mobile phase composed of n-butanol, acetone, acetic acid, aqueous ammonia (28%), water (70:50:18:1.5:60, v/v). 7. X-Omat Kodak films for autoradiography. 8. Fluoran-Safe Ultima Gold scintillation cocktail (Packard, Rungis, France). 9. Alliance 2795 chromatograph (Waters) consisting of a solvent delivery pump, an injection valve fitted with a 50-μL loop, a radial pack C-18 reverse-phase column (100 mm ×10 mm) enclosed in a Waters RCM 100 radial compression module. 10. Microfilter (0.45 μm; Sartorius, Gottingen, Germany). 11. Radio HPLC detector (FlowStar; Berthold, Thoiry, France). 12. Phosphor Imager Typhoon 9410 (Thermo Fisher Instrument). 13. TLC plates. 2.1.4. In Vitro Measurement of SULT Activity Toward Drugs
1. 3’-Phosphoadenosine 5’-phosphosulfate (PAPS) (German Institute of Human Nutrition, Prof. HR Glatt or SigmaAldrich, St. Louis, MO). 2. [35 S]-3’-Phosphoadenosine GBq/mmol; PerkinElmer).
5’-phosphosulfate
(37–111
3. Incubation buffer: 100 mM phosphate (pH 7.4). 4. Acceptor substrate in aqueous ethanol or water if possible (DMSO is inhibitory in vitro). 5. Barium acetate (100 mM), barium hydroxide (100 mM), and zinc sulfate (100 mM) for precipitation of unreacted PAPS. 6. Emulsifier-SafeTM scintillation cocktail (PerkinElmer). 2.2. Induction Studies
1. Inducers: Dexamethasone, 3-methylcholanthrene, phenobarbital, and rifampicin (Sigma). These compounds are dissolved in DMSO at 10, 5, 100, and 10 mM, respectively, as
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a stock solution and are added to culture dishes at 10 μM, 4 μM, 2 mM, and 10 μM, respectively (final concentration). 2. UGT substrates: β-Estradiol, 1-naphthol, propofol (Sigma) are dissolved in DMSO, and morphine (Sigma) is dissolved in water at 30 mM and stored in aliquots at −80◦ C. They are added to tissue culture plates at a concentration of 30 μM. SULT substrates are dissolved in either ethanol, PBS, or DMSO and added to tissue culture plates at a concentration between 1 and 50 μM. 2.3. Evaluation of UGT and SULT Expression in Hepatocytes 2.3.1. Total mRNA Preparation
1. The SV Total RNA Isolation System (Promega Madison, WI, USA) is used for RNA extraction from primary hepatocytes or cryopreserved hepatocytes. 2. RNA lysis buffer: 4 M guanidine isothiocyanate, 0.01 M Tris–HCl (pH 7.5), 0.97% β-mercaptoethanol. 3. DNase stop solution: 5 M guanidine isothiocyanate, 10 mM Tris–HCl (pH 7.5). After dilution with ethanol, the final concentration is 2 M guanidine isothiocyanate, 4 mM Tris– HCl (pH 7.5), and 57% (v/v) ethanol. 4. RNA wash solution: 162.8 mM potassium acetate, 27.1 mM Tris–HCl (pH 7.5). Add 100 mL of 95% (v/v) ethanol to a bottle containing 58.8 mL concentrated solution. 5. RNA concentration and purity are estimated by UV spectrophotometry using a Nanodrop instrument (Fisher Bioblock Scientific, Illkirch, France).
2.3.2. cDNA Synthesis and Real-Time PCR Quantification
1. PrimeScript reverse transcriptase (Takara Bio Saint Germainen-Laye, France) and 5× PrimeScript buffer [250 mM Tris– HCl (pH 8.3), 375 mM KCl, 15 mM MgCl2 ] are used for cDNA synthesis. 2. Oligo(dT)12−18 primer and dNTP (100 mM dNTP set) (Invitrogen Paisley, UK). 3. QIAGEN QuantiTect SYBR Green PCR Kit (QIAGEN GmbH Hilden, Germany). 4. LightCycler 2.0 (Roche, Meylan, France).
3. Methods 3.1. Assessment of Drug Conjugation by Human Hepatocytes Ex Vivo 3.1.1. Glucuronide and Sulfate Formation from Various Drugs
1. Primary hepatocytes are seeded on 100-mm culture dishes at a density of 80×103 viable cells/cm2 in culture medium. The culture is maintained at 37◦ C in a humidified atmosphere containing 5% CO2 , and the medium is renewed every 24 h (10).
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2. The number of viable cells is determined by the trypan blue exclusion test (see Note 1). 3. Hepatocytes are incubated in the presence of the drug (5–500 μM) for various time periods (typically 0–24 h) (see Note 2). 4. At each incubation time, 0.5 mL volume is withdrawn and mixed with an equal volume of acetonitrile. Separation, structure identification, and quantification of the glucuronide and sulfate can be performed by HPLC/MS/MS (see Section 3.1.2). Alternatively, when the radiolabeled drug substrate (e.g., with [3 H] or [14 C]) is available, detection and quantification of metabolites can be performed by HPLC with radioactivity detection – for example, paracetamol (acetaminophen). 3.1.2. Separation, Structure Identification, and Quantification of Drug Conjugates
The main analytical method for this purpose is a highperformance liquid chromatography/tandem mass spectrometry (HPLC/MS/MS). Multiple variations of the separation protocols of the conjugates from the parent compounds exist in the literature, depending on their physicochemical properties, and concern the choice of the stationary and mobile phases, the detection methods, and the mode of ionization (12, 13). Here, a standard separation and identification procedure using reverse-phase chromatography, UV detection, and electrospray ionization (ESI) mass spectrometry is given. 1. An Alliance 2795 chromatograph (see Section 2.1.3) consisting of a solvent delivery pump, an injection valve fitted with a 50-μL loop, a radial pack C-18 reverse-phase column (100 × 10 mm) enclosed in a Waters RCM 100 radial compression module is used. 2. Injection of the sample into the injection valve (10–50 μL). 3. Elution of the compounds by a mobile phase composed of 25–60% (v/v) acetonitrile in water containing 0.05% (v/v) trifluoroacetic acid (see Note 3). The mobile phase has to be filtered through a 0.45-μm microfilter. Flow rate: 1.0 mL/min. Elution run can be performed at room temperature or with a column in a thermo-stated oven at 35◦ C. Acetonitrile gradient could also be used (0–90% in 6 min) using shorter columns (50 mm × 2.1 mm) and reduced flow rate (0.4 mL/min). Formic acid could replace trifluoroacetic acid. Re-equilibration of the column at initial acetonitrile concentration is needed prior to the next injection (14). 4. Detection of the glucuronide/sulfate and of the parent compounds by a UV detector set at 210 nm. Specific detection of the glucuronide/sulfate by UV detector set at max-
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imum absorption wavelength (λmax ). Diode-array detectors are useful for determination of λmax . 5. Identification and quantification of the conjugates are performed by mass spectrometry which is operated in the selected multiple reaction monitoring (MRM) mode, from the column eluant directed to an atmospheric pressure ionization interface of the spectrometer. 6. Detection and quantification can also be achieved by radio HPLC detection (see Section 2.1.3) when radiolabeled glucuronides are formed using UDP-[U-14 C]-GlcA or sulfates are formed with PAP[35 S] as donor substrates in in vitro assays (see Section 3.2.2). 7. Classical quantification method of the amount of conjugate is performed from the linear portion of a standard curve, using increasing amounts of pure glucuronide processed in similar analytical conditions, or from measurement of the radioactivity associated with the glucuronide/sulfate. 3.2. Assessment of Drug Glucuronidation by Human Hepatocytes In Vitro 3.2.1. Preparation of Microsomes and Cytosol from Hepatocytes
Microsomes correspond to the subcellular fraction (mainly membranes from the endoplasmic reticulum), which contains all the UGT isoforms expressed. This fraction is suitable to determine the overall glucuronidation potency of hepatocytes for a given drug and assess apparent kinetic constants toward that drug. SULTs are found in the cytoplasmic compartment (cytosol) of the cell. 1. Hepatocytes are harvested with a scraper, homogenized in Eppendorf tubes in 5 mL homogenization buffer, submitted to five thaw–freeze cycles, and finally homogenized by 20 up-and-down strokes (10 s each) in a motor-driven Dounce homogenizer in ice (see Note 4). 2. The homogenate is centrifuged for 15 min at 5,000×g to remove nuclear and cell debris followed by a subsequent centrifugation step of the supernatant for 20 min at 12,000×g to remove mitochondria. The microsomal fraction is obtained from the supernatant by centrifugation for 1 h at 100,000×g in a micro-ultracentrifuge at 4◦ C (see Section 2.1.2). 3. The membrane fraction is resuspended in buffer by Dounce homogenization and frozen at −80◦ C until use. The cytosolic fraction is aliquoted and frozen at −80◦ C.
3.2.2. Measurement of the In Vitro UGT Activity Toward Acceptor Substrates
There are several methods allowing the determination of UGT activity in microsomes, which can be classified into two categories:
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– Specific methods for a given acceptor substrate, based on the intrinsic chromophoric properties, allowing determination of rate of reaction by spectrophotometric or fluorescence quantification of the glucuronide after liquid–liquid extraction or separation on reverse-phase HPLC of the polar metabolite. – General methods, based on the measurement of the incorporation of the 14 C-radiolabeled donor substrate glucuronic acid into the glucuronide separated by HPLC or thin layer chromatography (TLC). 1. The incubation mixture in Eppendorf tubes, final volume 40 μL, contains the following: microsomal fraction (50– 100 μg protein), 4 μL of 1.0 mM UDP-GlcA (0.1 mM final) and UDP-[U-14 C]-GlcA (∼250,000 cpm) in 100 mM Tris–HCl (pH 7.4), and 10 mM MgCl2 . 2. Start the reaction by addition of 2 μL stock solution of acceptor substrate (20 mM in DMSO). Incubation is carried out for 60 min at 37◦ C. A control sample is run simultaneously in the presence of 2 μL DMSO only. 3. Stop the reaction by addition of 40 μL ethanol in ice. The precipitated proteins are removed by centrifugation for 10 min at 4,000×g in a table-top centrifuge (4◦ C). 4. The glucuronides are separated by TLC as follows: 60 μL of supernatant is loaded onto TLC plates and developed with mobile phase for 3–4 h (see Notes 5 and 6). 5. Plates are dried and sprayed with 1% (v/v) 2-(4-tbutylphenyl)-5(-4-biphenyl)-1,3,4-oxadiazole in toluene. Glucuronides are detected by autoradiography for 3 days at −20◦ C or by a Phosphor Imager Typhoon 9410 (see Section 2.1.3). 6. The silica gel area corresponding to the radioactive spots is scrapped out from the TLC plate, and the radioactivity associated is quantified on a scintillation counting spectrometer in vials containing 5 mL scintillation cocktail (see Note 7). 7. Calculation of the activity:
dpm assay − dpm control assay 4 80 A= × × total dpm 60 × mg protein 60 A, Activity in nmol/min/mg protein; dpm assay, number of dpm associated with radiolabeled glucuronide; dpm control assay, number of dpm corresponding to the control assay containing no acceptor; total dpm, number of dpm corresponding to radiolabeled UDP-GlcA; 4, nanomoles of UDP-GlcA in the assay; 80:60, dilution factor (total volume of incubation)/(volume of incubation analyzed by TLC).
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8. Determination of kinetic parameters Apparent kinetic constants (Km , Vmax values) toward drug are determined by incubating hepatocyte microsomes with increasing concentrations of substrate (in the range of 0.01–2.0 mM) in the presence of a fixed concentration of UDP-GlcA (5.0 mM). Km and Vmax values are determined using nonlinear least squares analysis of the data fitted to Michaelis–Menten rate equation (v = Vmax × S/Km + S using the curve-fitter program Sigmaplot 9.0) (see Notes 8 and 9). 3.2.3. Measurement of the In Vitro SULT Activity Toward Acceptor Substrates
There are a number of methods that can be used to determine SULT activity in cell homogenates or cytosols, which can be classified into two categories: – Specific methods for a given acceptor substrate, based on (a) the availability of radioactively labeled substrate – for example, steroids – where the unreacted substrate can be separated from the sulfate conjugate by solvent extraction, (b) intrinsic chromophoric properties, allowing determination of rate of reaction by spectrophotometric or fluorescence quantification followed by separation on reverse-phase HPLC of the polar metabolite, or (c) using HPLC-mass spectrometry as described above. – General methods, based on the measurement of the incorporation of 35 S-radiolabeled sulfate from the universal sulfuryl donor PAPS into the conjugate. 1. Reaction mixtures are established in Eppendorf tubes in a total volume of 160 μL. 2. The mixture contains 0.1 M phosphate buffer (pH 7.4), cytosol (10–50 μg), substrate (0.01–600 μM depending on protein sample), and PAPS (20 μM, in water) containing 0.09 μCi PAP[35 S] (see Note 10). 3. Substrate stock solutions are prepared fresh each day in 50% (v/v) aqueous ethanol or water and diluted in assay buffer prior to use. 4. Reaction mixtures are incubated for 15–30 min in a circulating water bath at 37◦ C and stopped by placing the samples on ice and adding 200 μL barium acetate (0.1 M). 5. To remove unutilized PAPS, 200 μL barium hydroxide (100 mM) and 200 μL zinc sulfate (100 mM) are added, the samples mixed, and then centrifuged at 16,000×g for 4 min. 6. A sample (500 μL) of the resulting supernatant is removed and mixed with 4 mL scintillation fluid (Emulsifier-Safe). The mixture should then be subject to liquid scintillation counting (for 1 min per vial) using a scintillation counter (Beckman Coulter, High Wycombe, UK) (see Note 6).
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The potential of drug candidates to induce drug-metabolizing enzyme expression is a concern during the drug development process, although this is mainly the case for CYPs and UGTs – the consequences of induction of SULT expression are not clear and with the exception of SULT1E1 and SULT2A1, the capacity for induction appears to be limited. Primary human hepatocytes can be used in phase II induction studies toward two major goals: (1) to investigate the potential of a new chemical entity to induce UGT and/or SULT expression (see Note 11) and (2) to help identify which UGT/SULT isoform is responsible for the glucuronidation of a new drug, based on the alteration of its expression and activity by prototypic inducers. Indeed, emerging evidence indicates that similar mechanisms identified in the regulation of CYP enzymes are also involved in the regulation of the UGTs, i.e., AhR, CAR, and PXR mediate induction of UGT1A6, UGT1A1, and UGT2B7, respectively. Thus, agonists of these nuclear receptors, i.e. 3-methylcholanthrene, phenobarbital, and rifampicin, are used as inducers of the major UGT isoforms involved in drug metabolism (see Table 17.2).
Table 17.2 Transcription factors and typical agonist-inducing UGTs Receptor
Inducer
Enzyme
AhR/XRE
3-Methylcholanthrene/TCDD
UGT1A6/UGT1A1
CAR
Phenobarbital
UGT1A1/UGT2B7
PXR
Rifampicin/dexamethasone
UGT1A1/UGT1A6
PPARα
Clofibrate
UGT1A1/UGT1A9
Since induction of UGTs or SULTs occurs at the transcription level, this event can be evaluated by quantitative PCR analysis of mRNA transcripts (see Section 3.3.2). This analysis should be complemented by the measurement of protein expression and/or enzyme activity. However, the lack of widely available specific antibodies directed against individual UGTs has hindered accurate evaluation of protein expression (see Note 12). Antibodies against a number of human SULTs are available. It is equally important to determine the effect of inducers on UGT or SULT enzyme activities by analyzing the glucuronidation rate of a set of compounds considered as “probe” substrates for individual human isoforms (see Note 13). These are described above. 3.3.1. Hepatocyte Culture, Inducer Treatment, and UGT/SULT Activity
1. Hepatocytes (2×106 cells/well) are seeded in 6-well culture plates in appropriate medium and maintained at 37◦ C in a humidified 5% CO2 atmosphere.
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2. After an overnight equilibration period, the medium is replaced with serum-free medium containing either vehicle (0.1% DMSO, control medium) or inducer at the concentration indicated in Section 2.1.4 and changed at 24 h intervals. 3. After 72 h of induction, cells are washed with PBS and incubated in 1.0 mL of serum-free medium containing UGT or SULT “probe” substrate for 30 min at 37◦ C. 4. An aliquot of each sample is then analyzed by HPLC or LC/MS/MS (see Section 3.1.2) for quantification of the glucuronide and/or the sulfate conjugate formed upon incubation with the probe substrate. 5. Alternatively, following treatment with the inducer, cells can be collected for mRNA extraction or for microsome/cytosol preparation, and used for the determination of UGT and SULT activity and for Western blot analysis. 3.3.2. Analysis of Expression of UGT and SULT in Hepatocytes by Quantitative PCR 3.3.2.1. Total mRNA Preparation
1. The number of cells required for mRNA expression analysis should be in the range of 1.5×103 to a maximum of 5×106 cells per purification. 2. Collect the cells in a sterile 50-mL conical centrifuge tube by centrifugation at 300×g for 5 min. Wash the cell pellet with ice-cold sterile PBS. 3. Add 175 μL of RNA lysis buffer to the washed cells and mix well by pipetting. 4. Expel the lysate into a 1.5-mL tube. 5. Add 350 μl of RNA dilution buffer to 175 μL of lysate. Mix by inverting the tube three to four times. Place in a water bath or heating block at 70◦ C for 3 min exactly. 6. Centrifuge at 12,000–14,000×g for 10 min at 20–25◦ C and transfer the cleared lysate to a fresh tube. 7. Add 200 μL of 95% ethanol to cleared lysate and mix well by pipetting. 8. Transfer to Spin Basket Assembly, centrifuge for 1 min, and discard the eluate. 9. Add 600 μL of RNA wash solution, centrifuge for 1 min, and discard the eluate. 10. Apply 50 μL of DNase mix (containing 40 μL buffer 22.5 mM Tris (pH 7.5), 1.125 M NaCl, 0.0025% yellow dye, 5 μL of 0.09 M MnCl2 , 5 μL DNase I) to the membrane and incubate at room temperature for 15 min. 11. Add 600 μL RNA wash solution, centrifuge for 1 min, and empty.
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12. Add 250 μL RNA wash solution, centrifuge for 2 min, and transfer Spin Basket to elution tube. 13. Add 100 μL nuclease-free water to membrane. Centrifuge for 1 min to elute the RNA and store at −70◦ C. 14. RNA concentration and purity are estimated by UV spectrophotometry according to the following criteria: (i) concentration evaluated by A260 value should be greater than 4 μg/mL total RNA and (ii) A260 /A280 ratio should be greater than 2.0. Electrophoresis of a fraction of each RNA sample on a denaturing agarose gel is performed and shows a sharp distinction between 18S and 28S ribosomal RNA bands. 3.3.2.2. cDNA Synthesis
1. Prepare template RNA/primer mixture: 50 pmol Oligo(dT)12−18 primer, 1 μl dNTP mixture (10 mM), 2 μg RNA, qsp 10 μl RNase-free H2 O. 2. Heat at 65◦ C for 5 min and cool immediately on ice. 3. Prepare the reaction mixture in a total volume of 20 μl: 10 μl RNA/primer mixture, 2 μl of 5× PrimeScript buffer, 20 U RNase inhibitor, 100 U PrimeScript reverse transcriptase, qsp 20 μl RNase-free H2 O. 4. Perform the reaction under the following conditions: 30◦ C for 10 min, 42◦ C for 30–60 min, 70◦ C for 15 min. Cool on ice.
3.3.2.3. Real-Time PCR Quantification
1. Real-time quantification of human UGT mRNA (NCBI Accession N◦ in parentheses) for UGT1A1 (NM_000463), 1A3 (NM_000463), 1A4 (NM_007120), 1A6 (AY435141), 1A9 (NM_001075), 2B7 (NM_001074), and 2B15 (NM_001076) and GAPDH (NM_002046) is performed using the QIAGEN QuantiTect SYBR Green PCR Kit. 2. Incubation mixture contains 10 μl of 2× QuantiTect SYBR Green PCR Master mix, 0.25 μM primer A, 0.25 μM primer B, 2 μl template cDNA (RT product 10-fold dilution), qsp 20 μl H2 O. 3. PCR amplification consists of an initial 10-min denaturation step at 95◦ C, followed by 40 cycles of denaturation at 95◦ C for 10 s, annealing at 60◦ C for 12 s, and extension at 72◦ C for 1 min/1-kbp amplification. Specificity of the amplified PCR product is assessed by performing a melting curve analysis on the LightCycler 2.0 (Roche, Meylan, France). Primers used for major UGT isoforms involved in drug metabolism are listed in Table 17.3.
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Table 17.3 Primer sequence for real-time PCR mRNA quantification of UGT and SULT expression Isoform
Forward primer
Reverse primer
Size (bp)
UGT1A1
5’-AATAAAAAAGGACTCTGC TATGCT-3’
5’-ACATCAAAGCTGCTT TCTGC-3’
96
UGT1A3
5’-TGTTGAACAATATGTCT TTGGTCTA-3’
5’-ACCACATCAAAGGAA GTAGCA-3’
100
UGT1A6
5’-CATGATTGTTATTGGC CTGTAC-3’
5’-TCTGTGAAAAGAGCATC AAACT-3’
105
UGT1A9
5’-TGGAAAGCACAAGTA CGAAGTATATA-3’
5’-GGGAGGGAGAAATA TTTGGC-3’
200
UGT2B7
5’-GGAGAATTTCATCATGC AACAGA-3’
5’-CAGAACTTTCTAGTT ATGTCAACCAAATATTG-3’
123
UGT2B15
5’-CTTCTGAAAATTCTCGAT AGATGGAT-3’
5’-CATCTTCACAGAGC TTTATATTATAGTCAG-3’
124
SULT1A1
5’-GCAACGCAAAGGATG TGGCA-3’
5’-TCCGTAGGACACTTC TCCGA-3’
122
SULT1A3
5’-TGAGGTCAATGATCCA GGGGAA-3’
5’-CGCCTTTTCCATACGG TGGAAA-3’
199
SULT1B1
5’-CAGTTCCATAGCAGAC CAGATG-3’
5’-AATCCAGGGAGAGTCA TTTCCAAC-3’
170
SULT1C1
5’-GGTTTGGGGTTCCTGG TTTGAC-3’
5’-GGCTGGGACTGAAGGA TTGAAG-3’
460
SULT1E1
5’-TTGCCACCTGAACTTCTTC CTGCC-3’
5’-TTGGATGACCAGCCACCA TTAGAA-3’
127
SULT2A1
5’-TGGTTTGAAGGCATAGC TTTCC-3’
5’-GGAGTGCATCAGGCAGA GAATC-3’
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Primer sequences applicable to PCR amplification of the major human SULTs are provided in Table 17.3 (15) and the associated annealing temperatures are listed in Ref. (16). Changes in mRNA expression level are determined by the Ct data analysis method, where Ct represents the threshold cycle corresponding to the expression level of the gene of interest and of the housekeeping gene.
4. Notes 1. The trypan blue exclusion test is based on the principle that live cells possess intact cell membranes that exclude certain dyes, such as trypan blue, whereas dead cells do not. 2. Drug–drug interactions can be evaluated by the addition of a potential competing molecule with the drug to be tested.
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3. Trifluoroacetic acid is a strong acid, which should be handled with special care. 4. Alternately, sonication of hepatocyte suspension is also being used to prepare cell homogenates. Although this technique provides better yields in terms of membrane recovery, it has to be highlighted that this cell disruption method is not appropriate for microsome preparation. 5. The TLC method using radiolabeled UDP-GlcA permits to test most molecules as potential substrates for UGTs, provided the compound tested is not hydrophilic. For example, morphine glucuronide cannot be separated from parent compound by this method. 6. The method has to be performed in strict conditions and in a controlled area. The laboratory should have all authorizations to handle radiolabeled chemicals. 7. A drop of water should be laid on the radioactive area of the TLC plate corresponding to the glucuronide, before removing the silica gel for counting. This avoids projections of radioactive hazardous silica gel dusts and loss of radiolabeled glucuronide. 8. The TLC method is generally not appropriate to determine kinetic parameters, since the low concentration of UDPGlcA used to improve detection level does not allow to reach V max value. 9. Some limitations in the extrapolation of in vitro–in vivo clearance have been highlighted as far as the glucuronidation reaction is concerned (6). Intrinsic clearance values generated using liver microsomes (from Km /Vmax values) underpredict in vivo hepatic clearance, typically by an order of magnitude due to various factors inherent in the enzymatic system (UGT topology, latency, non-Michaelis– Menten kinetics, etc.). In vivo clearance of glucuronidated drugs is also generally underpredicted by intrinsic clearance values from human hepatocytes, but to a lesser extent than observed with the microsome model. 10. The method using radiolabeled PAPS allows the testing of most molecules as potential substrates for SULTs. It is generally not suitable for steroid substrates. 11. The majority of the investigations on induction have so far been focused on the regulation of CYP enzymes. However, recent studies emphasize the need to investigate the induction of UGTs and SULTs in humans. Of particular interest are the drug–drug interactions initially believed to be the result of inductions of CYP enzymes, which upon further investigation were found
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to be the result of the induction of phase II enzymes. For example, rifampicin coadministration was thought to increase ethinylestradiol clearance as a result of induction of CYP3A4, leading to unwanted pregnancies. However, Li et al. (17) demonstrated that induction of the phase II enzymes was actually the cause of the increased clearance of ethinylestradiol. 12. Several attempts have been made to develop specific antibodies directed against a single UGT isoform. Two antibodies denominated RAL and RAK have been extensively characterized (18) and RAL is now commercially available (Cypex, Dundee, UK). Specific antibodies to human UGT1A6 and UGT2B4 isoforms directed against the N-terminal part of the recombinant human protein have been developed in our group (19). An antipeptide anti-UGT2B7 antibody is commercially available (BDBiosciences, San Jose, CA, USA). However, this antibody also recognizes UGT2B4 and UGT2B10. A series of antibodies directed against the major human SULTs have been developed and validated in the Coughtrie laboratory (16). 13. The large degree of redundancy exhibited in the human UGT family with respect to overlapping substrate specificity has hindered the identification of form-selective substrates. The availability of recombinant UGT cell lines allowed to conclude that majority of estradiol-3-position is catalyzed by UGT1A1, although several human UGTs including UGT1A8, 1A10, 1A3 have significant activity toward this substrate. Irinotecan used as anticancer drug is specifically glucuronidated by UGT1A1. Thus, this compound can also be considered as a probe substrate for UGT1A1. 1-Naphthol glucuronidation has been historically used as a selective substrate for UGT1A6 (20). This view has been supported by further studies, indicating that 1-naphthol glucuronidation mediated by UGT1A6 was found over 20-fold greater than any other UGT form known to be expressed in the liver and that UGT1A6 exhibited the highest affinity compared to other isoforms.
Acknowledgments This work was supported in part by the following: an INSERMUniversity of Dundee Collaboration Contract (C2I), a Royal Society International Joint Project award, ANR-08-PCVI-002301 GAGNetwork and Région Lorraine.
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References 1. Lee, B.L., Tauber, M.G., Sadler, B., Goldstein, D., and Chambers, H.F. (1996) Atovaquone inhibits the glucuronidation and increases the plasma concentrations of zidovudine. Clin. Pharmacol. Ther. 59, 14–21. 2. Patsalos, P.N. and Perucca, E. (2003) Clinically important drug interactions in epilepsy: interactions between antiepileptic drugs and other drugs. Lancet Neurol. 2, 473–481. 3. Rogers, S.M., Back, D.J., Stevenson, P.J., Grimmer, S.F., and Orme, M.L. (1987) Paracetamol interaction with oral contraceptive steroids: increased plasma concentrations of ethinyloestradiol. Br. J. Clin. Pharmacol. 23, 721–725. 4. Riches, Z., Bloomer, J.C., and Coughtrie, M.W. (2007) Comparison of 2-aminophenol and 4-nitrophenol as in vitro probe substrates for the major human hepatic sulfotransferase, SULT1A1, demonstrates improved selectivity with 2-aminophenol. Biochem. Pharmacol. 74, 352–358. 5. Fournel-Gigleux, S., Shepherd, S.R.P., Carre, M.C., Burchell, B., Siest, G., and Caubere, P. (1989) Novel inhibitors and substrates of bilirubin UDP-glucuronosyltransferase: arylalkylcarboxylic acids. Eur. J. Biochem. 183, 653–659. 6. Miners, J.O., Knights, K.M., Houston, J.B., and Mackenzie, P.I. (2006) In vitro–in vivo correlation for drugs and other compounds eliminated by glucuronidation in humans: pitfalls and promises. Biochem. Pharmacol. 71, 1531–1539. 7. Maglich, J.M., Stoltz, C.M., Goodwin, B., Hawkins-Brown, D., Moore, J.T., and Kliewer, S.A. (2002) Nuclear pregnane x receptor and constitutive androstane receptor regulate overlapping but distinct sets of genes involved in xenobiotic detoxification. Mol. Pharmacol. 62, 638–646. 8. Mankowski, D.C. and Ekins, S. (2003) Prediction of human drug metabolizing enzyme induction. Curr. Drug Metab. 4, 381–391. 9. Bock, K.W. and Kohle, C. (2004) Coordinate regulation of drug metabolism by xenobiotic nuclear receptors: UGTs acting together with CYPs and glucuronide transporters. Drug Metab. Rev. 36, 595–615. 10. Abid, A., Sabolovic, N., and Magdalou, J. (1997) Expression and inducibility of UDP-glucuronosyltransferases 1-naphthol in human cultured hepatocytes and hepatocarcinoma cell lines. Life Sci. 60, 1943–1951. 11. Pichard, L., Paulet, E., Fabre, G., Ferrini, J.-B., Ourlin, J.-C., and Maurel, P. (1996)
12.
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Human hepatocyte culture. Methods Mol. Biol. 320, 283–293. Keski-Hynnila, H., Kurkela, M., Elovaara, E., Antonio, L., Magdalou, J., Luukkanen, L., Taskinen, J., and Kostiainen, R. (2002) Comparison of electrospray, atmospheric pressure chemical ionization, and atmospheric pressure photoionization in the identification of apomorphine, dobutamine, and entacapone phase II metabolites in biological samples. Anal. Chem. 74, 3449–3457. Sabolovic, N., Heydel, J.M., Li, X., Little, J.M., Humbert, A.C., Radominska-Pandya, A., and Magdalou, J. (2004) Carboxyl nonsteroidal anti-inflammatory drugs are efficiently glucuronidated by microsomes of the human gastrointestinal tract. Biochim. Biophys. Acta 1675, 120–129. Lahoz, A., Donato, M.T., Montero, S., Castell, J.V., and Gomez-Lechon, M.J. (2008) A new in vitro approach for the simultaneous determination of phase I and phase II enzymatic activities of human hepatocyte preparations. Rapid Commun. Mass Spectrom. 22, 240–244. Dooley, T.P., Haldeman-Cahill, R., Joiner, J., and Wilborn, T.W. (2000) Expression profiling of human sulfotransferase and sulfatase gene superfamilies in epithelial tissues and cultured cells. Biochem. Biophys. Res. Commun. 277, 236–245. Stanley, E.L., Hume, R., and Coughtrie, M.W. (2005) Expression profiling of human fetal cytosolic sulfotransferases involved in steroid and thyroid hormone metabolism and in detoxification. Mol. Cell. Endocrinol. 240, 32–42. Li, A.P., Hartman, N.R., Lu, C., Collins, J.M., and Strong, J.M. (1999) Effects of cytochrome P450 inducers on 17alphaethinyloestradiol (EE2) conjugation by primary human hepatocytes. Br. J. Clin. Pharmacol. 48, 733–742. Coughtrie, W.H., Burchell, B., Leakey, J.E.A., and Hume, R. (1988) The inadequacy of perinatal glucuronidation: Immunoblot analysis of the developmental expression of individual UDP-glucuronosyltransferase isoenzymes in rat and human liver microsomes. Mol. Pharmacol. 34, 729–735. Pillot, T., Ouzzine, M., Fournel-Gigleux, S., Lafaurie, C., Radominska, A., Burchell, B., Siest, G., and Magdalou, J. (1993) Glucuronidation of hyodeoxycholic acid in human liver: evidence for a selective role
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of UDP-glucuronosyltransferase 2B4. J. Biol. Chem. 268, 25636–25642. 20. Fournel-Gigleux, S., Sutherland, L., Sabolovic, N., Burchell, B., and Siest, G.
(1991) Stable expression of two human UDP-glucuronosyltransferases cDNAs in V79 cell cultures. Mol. Pharmacol. 39, 177–183.
Chapter 18 The Use of Hepatocytes to Investigate Drug Uptake Transporters Kazuya Maeda and Yuichi Sugiyama Abstract The liver plays an important role in the clearance of endogenous and exogenous compounds, including drugs. As hepatic uptake is the first step in hepatic clearance, any change in the former process directly affects the overall intrinsic hepatic clearance. Several uptake transporters are expressed on the basolateral membranes of hepatocytes and mediate the hepatic uptake of hydrophilic charged compounds that cannot easily penetrate the plasma membrane. As the substrate specificities of these individual drug transporters are broad and overlap, compounds are often recognized by multiple uptake transporters. Thus, knowledge of the contribution that each transporter makes to the hepatic uptake of a compound is important for predicting the extent to which hepatic uptake clearance will change if the activity of a specific transporter is altered by a genetic polymorphism or a drug–drug interaction. Human cryopreserved hepatocytes are now commercially available and can be used for studying hepatic uptake clearance. In this chapter, we describe a method for using isolated hepatocytes to estimate the in vivo uptake clearance of compounds and the quantitative contribution of each uptake transporter to the overall hepatic uptake of anionic compounds. Key words: human cryopreserved hepatocytes, hepatic uptake, transporter.
1. Introduction The liver and kidney are the main organs responsible for the detoxification of toxic compounds. In the liver, drug clearance involves uptake by hepatocytes, intracellular metabolism, transfer to the circulation, and efflux from hepatocytes to bile. Various types of transporters and enzymes are involved in these processes. The major drug transporters in the human liver are depicted in Fig. 18.1. The organic anion transporting polypeptides (OATPs) P. Maurel (ed.), Hepatocytes, Methods in Molecular Biology 640, DOI 10.1007/978-1-60761-688-7_18, © Springer Science+Business Media, LLC 2010
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OCT1
NTCP
OATP1B3 (OATP8)
OATP1B1 (OATP2)
OATP2B1 (OATP-B)
OAT2
MRP3
ATP
Phase I Metabolism
MRP4
ADP ATP
ADP
–OH Phase II Metabolism –OX ATP
ATP
ADP
ATP ADP
ADP
MDR1
MRP6
ATP ADP
BCRP
ATP
ADP
MRP2
BSEP Phase III Detoxification
Fig. 18.1. Uptake and efflux transporters in human liver.
1B1 and 1B3 are thought to be responsible for the hepatic uptake of several organic anions. Several efflux transporters driven by ATP hydrolysis are expressed on the bile canalicular membrane (multidrug resistance 1 [MDR1], multidrug resistance-associated protein 2 [MRP2], and breast cancer resistance protein [BCRP]). For organic anions, the substrate specificities of the uptake transporters (OATPs) are very similar to those of the efflux transporter (MRP2), even though their protein sequences are very different. Consequently, coordination of uptake and efflux transporters efficiently facilitates biliary excretion of anionic drugs from blood to bile (1). According to pharmacokinetic theory (2), overall intrinsic hepatic clearance (CLint, all ) can be described in terms of the intrinsic clearance of several independent processes: CL int, all = PSuptake ×
PSeff + CLmet , (PSeff + CLmet ) + PSback
[1]
where PSuptake , PSeff , CLmet , and PSback represent the intrinsic clearance of uptake from blood to hepatocytes, efflux from hepatocytes to bile, metabolism and backflux from hepatocytes to blood, respectively. According to this equation, uptake intrinsic clearance (PSuptake ) always dominates the overall intrinsic clearance (CLint, all ). If the intrinsic clearance of backflux (PSback ) is much smaller than the sum of the clearances of biliary excretion
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and metabolism (PSeff + CLmet ), uptake clearance approxi mates the overall intrinsic hepatic clearance CLint,all ∼ PSuptake . Recently, several clinical reports have demonstrated that the pharmacokinetics of some transporter substrates that are eliminated from liver by extensive metabolism may be affected by hepatic uptake (2). For example, coadministration of cyclosporin A, a potent OATP1B1 inhibitor and a mild CYP3A4 inhibitor, decreased the hepatic clearance of pravastatin, atorvastatin, and simvastatin, but coadministration of itraconazole, a potent CYP3A4 inhibitor, greatly affected the area under the plasma concentration time curve (AUC) of simvastatin (lactone form) and modestly changed that of atorvastatin, although both simvastatin and atorvastatin are substrates of CYP3A4 (Fig. 18.2) (3–7). Pravastatin is a substrate of OATP1B1, but is not metabolized, whereas simvastatin lactone is thought to be taken up without any aid from transporters because of the high lipophilicity of the simvastatin lactone. On the other hand, atorvastatin is taken up into liver by OATP1B1 and subsequently metabolized by CYP3A4. This apparent discrepancy can be explained by the rate-limiting step in the clearance of these two statins. OATP1B1 mediates the hepatic uptake of the hydrophilic agent, atorvastatin, the overall intrinsic clearance of which is solely determined by uptake clearance. Thus, the decrease in hepatic clearance of atorvastatin was almost the same as that of pravastatin. On the other hand, because the hydrophobic agent, simvastatin, permeates membranes passively, its overall intrinsic clearance approximates its metabolic intrinsic clearance. Consequently, inhibition of CYP3A4 greatly decreases the hepatic clearance of simvastatin. Thus, the importance of transporters for
AUC fold increase
20 +cyclosporin A + itraconazole 10
0 pravastatin simvastatin atorvastatin OATP1B1 No Yes Yes Yes Yes CYP3A4 No BA Fh Fa*Fg
0.18 0.29 0.62
<0.05(acid)
0.13 0.42 0.31
Fig. 18.2. Effects of itraconazole and cyclosporin A on the plasma AUC for pravastatin, simvastatin, and atorvastatin. The fold increases in the plasma AUCs of statins were determined after coadministration of cyclosporin A or itraconazole. The data were obtained from the literature (5, 7). BA: bioavailability, Fh: hepatic availability, Fa∗ Fg: intestinal availability.
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the hepatic uptake of transporter substrates that undergo extensive metabolism has also been recognized. Moreover, two frequently observed SNPs (A388G [N130D] and T521C [V174A]) in OATP1B1 alter the pharmacokinetics of several drugs (8). Subjects with the T521C allele exhibit decreased hepatic clearance of many OATP1B1 substrate drugs, whereas those with the A388G allele exhibit increased hepatic clearance of some OATP1B1 substrate drugs. A recent report indicated that an intronic SNP in OATP1B3 (rs11045585) is associated with severe docetaxel-induced neutropenia (9). Regarding simvastatin mentioned above, an active form of simvastatin, simvastatin acid, was reported to be a substrate of OATP1B1 (10), while simvastatin lactone is not thought to be a substrate of OATP1B1. Recent genome-wide association study (GWAS) indicated that T521C mutation in OATP1B1 is an only factor to observe significant relationship between this mutation and the increase in the prevalence of statin-induced severe myopathy (11). This can be explained by the fact that decrease in the OATP1B1 function leads to the reduction of the hepatic clearance of simvastatin acid and subsequent increase in the exposure of simvastatin to muscle. Because OATP1B1 and OATP1B3 accept a wide variety of structurally unrelated compounds as substrates and because their substrate specificities overlap, many compounds are recognized as bisubstrates of these transporters by transporter-expressing cell lines. However, the relative importance of transporters for hepatic uptake cannot be determined only from the rank order of their uptake clearances in transporter-expression systems because transporters differ in the extent to which they are expressed in hepatocytes vs expression systems. Therefore, a method for estimating the quantitative contribution of transporters to the hepatic uptake of organic anions is needed to predict changes in overall hepatic clearance resulting from alteration of the function of a specific transporter. There are three strategies for estimating the contribution of uptake transporters to the uptake of anionic compounds into human hepatocytes (Fig. 18.3) (12, 13). The first method involves determining the uptake clearance of reference and test compounds by human cryopreserved hepatocytes and transporter-expression systems (Fig. 18.3A) (12). Specific substrates for the target transporters are required for this analysis. This concept was originally developed to study metabolic enzymes by Crespi and Penman (14), who named it the relative activity factor (RAF) method. Kouzuki et al. used this theory to estimate the contribution of Oatp1a1 and Ntcp to the hepatic uptake of bile acids and organic anions, although their selection of transporter-specific compounds is currently no longer appropriate because of the discovery of new uptake transporters in hepatocytes (15, 16). In our method, estrone-3-sulfate (E-sul)
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and cholecystokinin octapeptide (CCK-8) are used as reference compounds for OATP1B1 and OATP1B3, respectively. First, the uptake clearance of the reference and test compounds is measured in cell lines that express each target transporter and in human cryopreserved hepatocytes. The ratio of the uptake clearance of the reference compound in human hepatocytes to that in each expression system is defined as “Ract ” for OATP1B1 and OATP1B3. The product of the Ract value and the uptake clearance of the test compound (CLtest ) in each transporter-expression system is used to estimate the uptake clearance of the test compound mediated by a specific transporter in human hepatocytes. The following equation describes uptake clearance in human hepatocytes (CLhep ) as a function of OATP1B1- and OATP1B3-mediated transport: CLhep = Ract,OATP1B1 × CLtest,OATP1B1 + Ract,OATP1B3 × CLtest,OATP1B3 .
[2]
Hirano et al. demonstrated that pitavastatin and E2 17βG were mainly taken up by OATP1B1 in three independent batches of human hepatocytes and that the observed uptake clearance in human hepatocytes was similar to the sum of the estimated clearance mediated by OATP1B1 and OATP1B3 (12). The second approach is to directly estimate the ratio of expression of OATP1B1, OATP1B3, and OATP2B1 in human hepatocytes to that in expression systems from band densities of Western blots and to use this ratio instead of the Ract value to estimate their contributions (Fig. 18.3B) (12, 13). The third approach is to estimate the inhibitable portion of the uptake of test compounds in human hepatocytes in the presence of a specific inhibitor of each transporter (Fig. 18.3C) (13). E-sul can be used as a specific inhibitor as well as a specific substrate for OATP1B1. As CCK-8 inhibits OATP1B1 and OATP1B3 to the same extent, it should not be used as a specific inhibitor, even though it is a specific substrate for OATP1B3. As each approach has advantages and disadvantages, results should be obtained using different methods before they are regarded as definitive. Regarding the prediction of the absolute value of drug uptake into human hepatocytes, assuming that hepatic uptake is the rate-limiting step for hepatic clearance of transporter sub strates CLint, all ∼ PSuptake , it is theoretically possible to estimate in vivo hepatic intrinsic clearance by extrapolation from in vitro uptake clearance in hepatocytes simply by multiplying the uptake clearance per cell by the number of cells per gram of liver (1.2–1.25×108 cells/g liver) and the liver weight per kilogram body weight (38.3 g liver/kg BW for rats, 24.3 g liver/kg BW for humans). Miyauchi et al. demonstrated that the uptake
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(C)
(B)
Fig. 18.3. Schematic diagram of the method for estimating the contribution of each transporter to the overall hepatic uptake (A) using reference compounds, (B) using relative expression levels estimated from Western blot analysis, and (C) using transporter-specific inhibitors.
clearances of 15 drugs estimated using isolated hepatocytes were well correlated with those estimated using the in situ multiple indicator dilution (MID) method; however, the in situ clearance estimates appeared to reach an upper limit, possibly because diffusion of compounds in the unstirred water layer became rate limiting (17). Kato et al. showed that the uptake clearances of four types of endothelin antagonists estimated using integration plot analysis after i.v. administration of compounds to rats were similar to estimates derived using isolated rat hepatocytes (18). Watanabe et al. recently reported that in vivo uptake clearances of 12 drugs (substrates of OATPs) estimated using integration plot analysis in rats could be predicted from the in vitro uptake clearance of isolated rat hepatocytes (19). These reports indicate that the isolated hepatocyte is a good model for predicting hepatic uptake clearance. Watanabe et al. also demonstrated that the in vivo biliary clearance of 12 drugs could be predicted from in vitro uptake data, suggesting that the rate-limiting step for the hepatic clearance of these substrate drugs is hepatic uptake (19). In this chapter, we describe experimental methods and calculations for quantitative prediction of in vivo hepatic clearance of transporter substrates and for determining the contribution of each transporter to the overall hepatic uptake of substrates using isolated animal and human hepatocytes.
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2. Materials 2.1. Isolation of Rat Hepatocytes by Collagenase Perfusion
1. Urethane solution: 250 mg/mL urethane (Sigma-Aldrich, St. Louis, MO) in distilled water. 2. Heparin solution: Heparin Sodium Injection-Wf (Mitsubishi Tanabe Pharma Co., Osaka, Japan). 3. Antiseptic solution: 5% chlorhexidine gluconate solution (Dainippon Sumitomo Pharma Co., Ltd., Osaka, Japan) diluted in 50 volumes of warm water for use (final concentration, 0.1%) (see Note 1). 4. Stock solution of perfusion buffer (×10): 80 g NaCl, 4 g KCl, 0.78 g NaH2 PO4 2H2 O, 1.5 g NaHPO4 12H2 O, 23.8 g HEPES, and 0.06 g phenol red. Store at 4◦ C. 5. Solution A: 50 mL stock solution of perfusion buffer (×10) (450 mL Milli-Q reagent, 0.095 g EGTA, 0.49 g glucose, and 0.175 g NaHCO3 , adjusted to pH 7.2 using NaOH). Sterilize using an autoclave and store at 4◦ C. 6. Solution B: 50 mL stock solution of perfusion buffer (×10) (450 mL Milli-Q reagent, 0.28 g CaCl2 2H2 O, 0.175 g NaHCO3 , adjusted to pH 7.5 using NaOH). Sterilized using a bottle-top filter (0.22 μm, cellulose acetate; Corning Coster, Bodenheim, Germany) attached to an autoclaved bottle. On the day of the isolation of hepatocytes, 10 mL of solution is collected into a 15 mL centrifuge tube and gently mixed with 0.025 g of trypsin inhibitor (SigmaAldrich) and 0.25 g of collagenase (Wako, Osaka, Japan). The mixture is then dispensed back into the bottle using a syringe filter (Acrodisc 25 mm syringe filter [0.45 μm]; Pall, Ann Arbor, MI) (see Note 2). 7. Peristaltic pump (Peri-Star) from World Precision Instruments (Sarasota, FL). 8. Indwelling needle (18G × 1 1/4 ) from Terumo Co. (Tokyo, Japan). 9. Stock solution of Krebs–Henseleit buffer (×5): 1.8 g KCl, 0.65 g KH2 PO4 , 1.475 g MgSO4 7H2 O, 14.875 g HEPES, 1.122 g CaCl2 2H2 O in 1 L of Milli-Q reagent. Store at 4◦ C. 10. Krebs–Henseleit buffer: 100 mL stock solution (×5), 400 mL Milli-Q reagent, 0.45 g glucose, 3.45 g NaCl, 1 g NaHCO3 , adjusted to pH 7.4 using NaOH. 11. Nylon cell strainers (mesh sizes: 100, 70, and 40 μm; BD Biosciences, Bedford, MA).
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12. Trypan blue solution: Trypan Blue Stain 0.4% (Invitrogen, Carlsbad, CA). 13. Hemocytometer from Erma Inc. (Tokyo, Japan). 2.2. Thawing Procedure for Human Cryopreserved Hepatocytes
1. Human cryopreserved hepatocytes can be purchased from some distributors such as Celsis International (Chicago, IL), XenoTech, LLC (Lenexa, KS), and BD Biosciences (San Jose, CA). These cells should be stored in liquid N2 to preserve cell function (see Note 3).
2.3. Uptake Experiments Using Isolated Hepatocytes
1. Glass round-bottom centrifuge tubes (internal diameter, 14 mm) are used to ensure efficient mixing of hepatocytes during the uptake assay. 2. Substrate solution: Typically, [3 H]- or [14 C]-labeled compounds are used for the assay. The substrate solution usually contains 0.1 μCi/mL of radioactive tracer compound and unlabeled compound is added to adjust the final concentration of the compound in the incubation buffer (see Note 4). 3. Oil mixture: 46.8 g silicon oil (Sigma-Aldrich) and 8.6 g mineral oil (Sigma); final density, 1.015. The oils are mixed overnight using a magnetic stirrer. 4. Sampling tube: Before conducting the uptake assay, it is necessary to prepare the same number of tubes as samples. Fifty microliters of 2 N NaOH is deposited in a 0.25 mL polypropylene sampling tube (Assist Co., Ltd., Tokyo, Japan) using a pipette and 100 μL of oil mixture is then layered over the aqueous NaOH solution. The tubes are then centrifuged for 10 s and stored at room temperature. 5. Benchtop centrifuge (Beckman Microfuge E) from Beckman Coulter (Fullerton, CA). 6. Scintillation cocktail: Clear-Sol II (Nacalai Tesque, Kyoto, Japan).
2.4. Construction of Cell Lines Stably Transfected with cDNA for OATPs
1. Human liver cDNA can be purchased from BD Biosciences Clontech (Palo Alto, CA) and Takara Bio Inc. (Shiga, Japan). 2. Mammalian expression vector: pcDNA3.1(+)/Neo vector from Invitrogen. 3. Kit for Midi-Prep: Several distributors sell kits for Midi-Prep. We routinely use the GenElute HP Plasmid Midiprep Kit from Sigma, but any kit can be used for this purpose. 4. Dulbecco’s modified Eagle’s medium (DMEM): low glucose (Invitrogen) supplemented with 10% fetal bovine serum
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(Sigma) and 1% antibiotic–antimycotic solution (×100) (100 U/mL penicillin, 100 μg/mL streptomycin, and 0.25 μg/mL amphotericin B; Invitrogen). 5. Trypsin/EDTA: Trypsin–EDTA (0.25% Trypsin, 1 mM EDTA 4Na) from Invitrogen. 6. Transfection reagent: FuGENE6 reagent from Roche Diagnostics (Indianapolis, IN). 7. Antibiotics for clone selection: Antibiotic G418 sulfate from Promega (Madison, WI). 2.5. Uptake Experiments Using TransporterExpressing Cell Lines
1. Coat solution: 50 mg/L poly-L-lysine (Sigma) and 50 mg/L poly-L-ornithine (Sigma) are dissolved in MilliQ reagent and sterilized using a bottle-top filter (0.22 μm). Store at 4◦ C. 2. PBS(−): 137 mM NaCl, 2.7 mM KCl, 10 mM Na2 HPO4 , and 1.8 mM KH2 PO4 in Milli-Q reagent, adjusted to pH 7.4 with HCl. The solution should be autoclaved before cell culture. Store at 4◦ C. 3. Sodium butyrate powder (Wako). 4. Substrate solution: Typically, [3 H]- or [14 C]-labeled compounds are used for the assay. The substrate solution usually contains 0.1 μCi/mL of tracer radioactive compound and unlabeled compound is added to achieve the desired concentration in the incubation buffer (see Note 4). 5. Scintillation cocktail: Clear-Sol I (Nacalai Tesque). 6. Bovine serum albumin from Thermo Fisher Scientific Inc. (Rockford, IL).
2.6. SDS-Polyacrylamide Gel Electrophoresis and Western Blot Analysis of OATPs in Expression Systems and Hepatocytes
1. Cell scraper from AGC Techno Glass (Chiba, Japan) 2. 0.1 M Tris–HCl buffer (pH 7.4) containing protease inhibitors: 12.1 g Tris made up to 1 L with Milli-Q reagent and adjusted to pH 7.4 with HCl. Store at 4◦ C. Just before the experiment, leupeptin, pepstatin A, and phenylmethylsulfonyl fluoride (PMSF) (Sigma) are added to the Tris– HCl buffer. 3. Reagents for making the SDS-PAGE gel: (1) Acrylamide/bis solution: 30 g acrylamide and 0.8 g N,N -methylene-bis-acrylamide made up to 100 mL with Milli-Q reagent (this solution is a neurotoxin when unpolymerized). Store at 4◦ C and protect from light. (2) 3 M Tris–HCl buffer (pH 8.8): 36.342 g Tris made up to 100 mL with Milli-Q reagent, adjusted to pH 8.8 with HCl. Store at 4◦ C.
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(3) 10% SDS: 10 g sodium dodecyl sulfate (SDS) made up to 100 mL with Milli-Q reagent. Store at room temperature. (4) Ammonium persulfate solution: 0.15 g ammonium persulfate dissolved in 10 mL of Milli-Q reagent. Freeze immediately in single-use aliquots (∼500 μL) at −20◦ C. (5) 0.5 M Tris–HCl buffer (pH 6.8): 6.057 g Tris made up to 100 mL with Milli-Q reagent, adjusted to pH 6.8 with HCl. Store at 4◦ C. (6) TEMED: from Bio-Rad Laboratories (Hercules, CA). 4. Running buffer: 9.09 g Tris, 43.2 g glycine, and 3.0 g SDS made up to 3 L with Milli-Q reagent. Store at 4◦ C. 5. Loading buffer: 3× Red Loading Buffer from New England Biolabs (Beverly, NA). 6. Protein Marker: Prestained Protein Marker, Broad Range (6–175 kDa) from New England Biolabs. 7. Polyvinylidene diflouride (PVDF) membrane: Fluorotrans W membrane from Pall. 8. Blotting paper: Protean paper from Bio-Rad Laboratories. 9. Blotter: Trans-blot from Bio-Rad Laboratories 10. Transcription buffer: 17.46 g Tris, 8.79 g glycine, and 600 mL MeOH made up to 3 L with Milli-Q reagent. Store at 4◦ C. 11. TBS-T: 3.63 g Tris, 26.3 g NaCl, and 1.5 mL Tween 20 made up to 3 L with Milli-Q reagent and adjusted to pH 8.0 with HCl. Store at 4◦ C. To avoid nonspecific binding of the antibody, 2.5 g of skimmed milk powder (Wako) is added to 50 mL of TBS-T. 12. Primary antibodies: rabbit antisera for OATP1B1, OATP1B3, and OATP2B1 were created in-house (12, 13). Anti-OATP1B1, anti-OATP1B3, and anti-OATP2B1 were raised in rabbits against synthetic peptides consisting of the 21, 15, and 15 carboxyl-terminal amino acids of OATP1B1, OATP1B3, and OATP2B1, respectively, coupled to keyhole limpet hemocyanine at its N terminus via an additional cysteine moiety (see Note 5). 13. Secondary antibody: horseradish peroxidase-linked antirabbit F(ab’)2 fragment from GE Healthcare (Dedham, MA). 14. Band detection: ECL Plus Western blotting detection system from GE Healthcare. 15. Image analyzer: LAS-1000 from Fuji Film (Tokyo, Japan).
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3. Methods 3.1. Isolation of Rat Hepatocytes by Collagenase Perfusion
1. A urethane solution is administered to the rat at a dose of 1 g/kg body weight to induce anesthesia. 2. To avoid rapid coagulation of blood during this procedure, 0.1 mL of a heparin solution is administered via the tail vein. 3. The anesthetized rat is rinsed in antiseptic solution to prevent contamination with microorganisms present on the surface of the rat (see Note 1). 4. All of the following procedures should be performed on a clean, disinfected bench. All materials, including the peristaltic pump, water bath, surgical table, and all bottles containing solutions, should be sterilized by spraying them with an ethanol solution before they are put onto the bench. Solution A and solution B should be prewarmed at 37◦ C in a water bath before the operation. 5. A rat is placed on a surgical table on the clean bench and the abdomen is opened using scissors. The organs are then pushed aside and portal vein is exposed for cannulation. 6. A silicone tube is attached to a peristaltic pump and an 18gauge indwelling needle is connected to the tip of the silicone tube. Before cannulation, a small volume of solution A is passed through the perfusion tube via the peristaltic pump to remove air bubbles from the tube. Maintaining a continuous flow of a small amount of solution A through the tube, the indwelling needle is inserted into the portal vein and fixed using small clamps. 7. Immediately after cannulation, the inferior vena cava is cut several times with scissors to make an outlet for the perfusate and the flow rate of solution A is increased to 40 mL/min. Then, solution A is perfused continuously for about 5 min (see Note 6). 8. The peristaltic pump is switched off and the perfusate is changed from solution A to solution B. Solution B is then perfused continuously for about 5 min at a rate of 15 mL/min (see Note 7). 9. After perfusion of solution B, liver is excised using scissors and placed into 10 mL of ice-cold Krebs–Henseleit buffer in a 10 cm diameter dish. The surface of the liver is washed by shaking it gently using tweezers and placed into another 10 cm dish filled with 10 mL of ice-cold Krebs–Henseleit buffer.
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10. The liver is cut several times in a random pattern with a surgical knife while immersed in the ice-cold Krebs–Henseleit buffer. If the perfusion has been successful, the liver is easily crumbled and hepatocytes flow out of the lobes during gentle shaking. 11. To remove the debris from hepatocytes, the hepatocyte suspension is filtered through two sheets of sterilized gauze and the filtrate is collected in a prechilled 50 mL centrifuge tube. The dish is washed several times with icecold Krebs–Henseleit buffer and the wash fluid is filtered with gauzes and collected to collect the remaining hepatocytes. The hepatocyte suspension is then filtered using a cell strainer with a mesh size of 100 μm and the filtrate is collected in a prechilled 50 mL centrifuge tube. The hepatocyte suspension is then centrifuged at 80×g for 1 min at 4◦ C, the supernatant is removed, and the hepatocytes are gently resuspended in 40 mL of ice-cold Krebs–Henseleit buffer. 12. The hepatocyte suspension is filtered using a cell strainer with a mesh size of 70 μm and the filtrate is centrifuged at 80×g for 1 min at 4◦ C. The supernatant is removed and hepatocytes are again gently resuspended in 40 mL of icecold Krebs–Henseleit buffer. 13. The hepatocyte suspension is filtered using a cell strainer with a mesh size of 40 μm and the filtrate is centrifuged at 80×g for 1 min at 4◦ C. The supernatant is removed and hepatocytes are again gently resuspended in 10 mL of icecold Krebs–Henseleit buffer. 14. To check the viability and the number of hepatocytes, 50 μL of trypan blue solution is mixed with 50 μL of cell suspension by gentle pipetting. The number of viable (white) and dead (blue) cells is counted using a hemocytometer (see Note 8). For the regular uptake assay, hepatocytes are diluted with ice-cold Krebs–Henseleit buffer at a concentration of 2×106 viable cells/mL. 3.2. Thawing Procedure for Human Cryopreserved Hepatocytes
1. A tube of human hepatocytes is removed from liquid N2 , the cap on the vial is loosened, and the vial is placed on ice for 5 min to release any liquid N2 that may have seeped into the vial. After closing the cap firmly, the vial is immersed in a 37◦ C water bath with gentle shaking for 75–90 s until the ice in the tube has almost entirely melted. 2. The contents of the vial are decanted into an ice-cold 15 mL centrifuge tube and the vial is washed with 200 μL of ice-cold Krebs–Henseleit buffer. The wash fluid is also transferred to the centrifuge tube.
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3. Ten milliliters of ice-cold Krebs–Henseleit buffer is added very slowly to the cell suspension. The cells are suspended gently and the cell suspension is centrifuged at 50×g for 2 min at 4◦ C. The supernatant is then removed. This procedure is repeated once more to remove the cryopreservation buffer, and the cells are resuspended in 5 mL of ice-cold Krebs–Henseleit buffer. 4. Trypan blue staining is performed to check the viability and number of hepatocytes. Trypan blue solution is added to nine volumes of ice-cold Krebs–Henseleit buffer and 90 μL of this solution is then mixed with the 10 μL of the cell suspension by gentle pipetting. The number of viable (white) and dead (blue) cells is counted using a hemocytometer (see Note 8). For the regular uptake assay, hepatocytes are diluted with ice-cold Krebs–Henseleit buffer at a concentration of 1–2×106 viable cells/mL. 3.3. Uptake Experiments Using Isolated Hepatocytes
The same uptake assay protocol is used for isolated human and rat hepatocytes. This protocol is typical of that used for human cryopreserved hepatocytes when radioactive compound is used as substrate. As the number of hepatocytes and the total volume required for each time point depend on the uptake clearance and detection limit of the test compound, conditions should be modified for each case. 1. Glass round-bottom centrifuge tubes are prechilled at 4◦ C and 160 μL of cell suspension is added to each tube. The cell suspension is then warmed in a water bath at 37◦ C for 3 min. 2. To initiate cellular uptake, 160 μL of substrate solution (warmed to 37◦ C) is added to the cell suspension. The tube is shaken gently in a water bath and the timer is switched on. 3. When cells are sampled at 30 s, 2 min, and 5 min (three time points), an aliquot of 80 μL of the hepatocyte suspension is obtained at each time point and loaded into a sampling tube containing the oil mixture and 2 N NaOH to separate the hepatocytes from the incubation medium. The sampling tube is then centrifuged at 10,000×g for 10 s using a benchtop centrifuge. During this process, hepatocytes pass through the oil layer into the alkaline solution and the incubation medium remains above the oil layer. 4. After centrifugation, the sample tube is incubated overnight at room temperature to enable complete lysis of the cells in the NaOH phase. The sampling tube is cut at the middle of the oil layer and the upper and lower phases are transferred to separate scintillation vials. The lower phase containing the lysed cells is neutralized with 50 μL of 2 N HCl. Scintillation cocktail (Clear-Sol II) is then added to the scintillation
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vial and radioactivity is measured using a liquid scintillation counter (see Note 9). 3.4. Construction of Cell Lines Stably Transfected with cDNA for OATPs
1. cDNA for each isoform of OATP is amplified by PCR using human liver cDNA as a template and inserted into the mammalian expression vector, pcDNA3.1(+)/Neo. For transfection, Escherichia coli carrying the expression vector is amplified overnight and the vector is isolated using a Midi-prep kit. The pcDNA3.1(+)/Neo vector is also needed to construct control cells. 2. HEK293 cells are grown in low-glucose Dulbecco’s modified Eagle’s medium (DMEM) supplemented with 10% fetal bovine serum and 1% antibiotic–antimycotic solution (×100) at 37◦ C in an atmosphere of 5% CO2 and 95% humidity. When they approach confluence, the cells are routinely passaged with Trypsin/EDTA. One day before transfection, 1–3×105 cells are seeded into each well of a six-well plate. 3. The culture medium is replaced with 2 mL of serum- and antibiotic-free medium. 4. For each well, 100 μL of serum- and antibiotic-free medium is mixed with 3 μL of FuGENE6 reagent by tapping the tube. Then, 2 μg of the expression vector is mixed by gentle tapping of the tube and left at room temperature at least for 15 min. 5. The mixture is added to each well of the plate and the cells are incubated in a CO2 incubator. The medium is replaced with serum-containing regular culture medium 6 h after transfection. 6. For selection of transfected cells, the medium is replaced with culture medium containing 800 μg/mL antibiotic G418 sulfate 1 day after transfection. G418-resistant colonies that express the OATP gene are usually obtained 3 weeks after transfection.
3.5. Uptake Experiments Using TransporterExpressing Cell Lines
1. Each well of a 12-well plate is precoated with poly-L-lysine and poly-L-ornithine by incubating 0.5 mL of the coat solution per well for 5 min at room temperature. Each well is then washed with 1 mL of PBS(−). 2. Three days before the uptake experiments, cells are seeded into each well of a precoated 12-well plate at a density of 1.5×105 cells/well. 3. One day before the experiments, the culture medium is replaced with medium supplemented with 5 mM sodium butyrate to induce gene expression (see Note 10).
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4. Before uptake experiments, cells are washed twice with prewarmed (37◦ C) Krebs–Henseleit buffer and preincubated in 1 mL of Krebs–Henseleit buffer at 37◦ C for 15 min to remove the culture medium. The cells are placed on a slide warmer at 37◦ C (PS-53; Sakura Finetek Japan Co., Ltd., Tokyo, Japan) to maintain a constant temperature. 5. To initiate cellular uptake, 1 mL of substrate solution (prewarmed to 37◦ C) is added to each well and timer is switched on. 6. To terminate cellular uptake at the designated time, the substrate solution is aspirated and the cells are washed twice with 1 mL of ice-cold Krebs–Henseleit buffer. The cells are solubilized in 500 μL of 0.2 N NaOH and kept overnight at 4◦ C (see Note 11). 7. Two hundred and fifty microliters of 0.4 N HCl is added to the cell lysate and a 500 μL aliquot is transferred to a scintillation vial. Two milliliters of scintillation fluid (ClearSol I) is added to the scintillation vial and the radioactivity associated with the cells and incubation buffer is measured using a liquid scintillation counter. 8. The remaining 50 μL of cell lysate is used to determine protein concentration using the method of Lowry and bovine serum albumin as a standard. 3.6. SDS-Polyacrylamide Gel Electrophoresis and Western Blot Analysis of OATPs in Expression Systems and Hepatocytes
1. Transporter-expressing HEK293 cells are detached from the culture dish using a cell scraper and homogenized with 20 strokes of a Dounce homogenizer in five volumes of 0.1 M Tris–HCl buffer (pH 7.4) containing 1 μg/mL leupeptin and pepstatin A and 50 μg/mL phenylmethylsulfonyl fluoride. 2. The cell homogenate is centrifuged at 1,500×g for 10 min at 4◦ C and the supernatant is recentrifuged at 100,000×g for 30 min at 4◦ C. Then, the precipitate is suspended in Tris–HCl buffer and recentrifuged at 100,000×g for 30 min at 4◦ C. The crude membrane fraction is resuspended in a Tris–HCl buffer containing protease inhibitors with five strokes of a Dounce homogenizer and stored at –80◦ C before Western blot analysis. 3. To make the 7% SDS-PAGE separation gel in a minigel format, 3.49 mL of Milli-Q reagent is mixed with 1.7 mL of acrylamide/bis solution, 0.75 mL of 3 M Tris–HCl buffer (pH 8.8), 0.06 mL of 10% SDS, 0.3 mL of 1.5% ammonium persulfate solution, and 3 μL TEMED. The mixture is poured into the space between the glass plates, leaving the space for a stacking gel, and gently overlaid with
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Milli-Q reagent. The gel should polymerize in about 30 min. The Milli-Q reagent is decanted after the gel has formed. 4. To overlay a 3.75% stacking gel onto the separation gel, 2.26 mL of Milli-Q reagent is mixed with 0.5 mL of acrylamide/bis solution, 1.0 mL of 0.5 M Tris–HCl buffer (pH 6.8), 0.04 mL of 10% SDS, 0.2 mL of 1.5% ammonium persulfate solution, and 3 μL TEMED. The mixture is poured into the space between the glass plates and a comb is inserted. The stacking gel should polymerize within 30 min. 5. After the stacking gel has formed, the gel is attached to the electrophoresis chamber and running buffer is added to the upper and lower chambers. The comb is carefully removed and each well is washed with running buffer using a 2.5 mL syringe fitted with a 20-gauge needle. 6. The crude membrane fraction is diluted with 3× red loading buffer and loaded onto the SDS-PAGE gel (see Note 12). A prestained protein marker is also loaded as a molecular weight reference. The gel is electrophoresed for 2 h at 20 mA. 7. The polyvinylidene diflouride (PVDF) membrane is preincubated with methanol for 1 min and with transcription buffer for more than 15 min before electroblotting. The blotting paper is also preincubated with transcription buffer for 5 min. After electrophoresis, the running gel is incubated with transcription buffer for 5 min. The blotting paper, PVDF membrane, and running gel are stacked and the proteins are electroblotted onto a PVDF membrane using a blotter set at 15 V over a period of 1 h. 8. The PVDF membrane is blocked with 5 mL of TBS-T containing 5% skimmed milk for 1 h at room temperature and washed several times with 10 mL TBS-T. 9. After washing with TBS-T, the membrane is incubated with 5 mL TBS-T containing 5% skimmed milk and rabbit antiserum (dilution, 1:500–1:1,000) for 1 h at room temperature and washed several times with 10 mL of TBS-T. 10. The membrane is incubated with a horseradish peroxidaselabeled anti-rabbit IgG antibody diluted 1:2,000 in 5 mL of TBS-T containing 5% skimmed milk for 1 h at room temperature and washed several times with 10 mL of TBS-T. 11. The ECL Plus Western blotting detection system is used for detection of bands. Under dark conditions, 2 mL of
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solution A is mixed with 50 μL of solution B and the membrane is immersed in the solution and incubated for 5 min at room temperature. The band is detected and its intensity quantified using an image analyzer. 12. Several amounts of protein (at least three points) from samples of human hepatocytes and expression systems are separated by SDS-PAGE and their band densities are quantified. The band density of each sample is plotted against its protein content and if a linear correlation is observed, the slope corresponds to the expression level of each sample. Thus, the ratio of the slope for human hepatocytes to that for the expression system represents the relative expression level of each transporter (see 3.8.2). 3.7. Calculation of Uptake Clearance of Compounds in Hepatocytes and Expression Systems
Ligand uptake is expressed as the uptake volume (μL/mg protein), which is defined as the amount of radioactivity associated with the cells (dpm/mg protein) divided by the amount of radioactivity in the incubation medium (dpm/μL). Transportermediated uptake is estimated by subtracting the uptake into vector-transfected cells from the uptake into cDNA-transfected cells. The uptake clearance is the slope of the time-dependent uptake volume within the period in which time-dependent linear uptake is maintained. Thus, we first check the uptake of ligands at several time points and draw a graph to visualize the time course of the uptake volumes and to determine how long ligand uptake increases in a linear manner. To calculate the uptake clearance of human cryopreserved hepatocytes, we determined the hepatic uptake clearance (CL(2−0.5 min) ; μL/min/106 cells) from the slope of the uptake volume (V d ; μL/106 cells) between 0.5 and 2 min (equation [3]) because the cost of human hepatocytes limits the number of cells that can be used. The saturable component of hepatic uptake clearance (CLhep ) was determined by subtracting CL(2−0.5 min) in the presence of an excess amount of substrate (100 or 1,000 μM) from that in the presence of a tracer amount of substrate (0.1 or 1 μM) (equation [4]):
CL(2−0.5 min ) =
Vd, 2 min − Vd, 0.5 min , 2 − 0.5
CLhep = CL(2−0.5 min ), tracer − CL(2−0.5
min ), excess ,
[3]
[4]
where CL(2−0.5 min), tracer and CL(2−0.5 min), excess represent CL(2−0.5 min) estimated in the presence of tracer and excess concentrations of substrate, respectively.
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3.8. Calculation of the Quantitative Contribution of OATPs to the Overall Hepatic Uptake of Compounds 3.8.1. RAF Method for Estimating the Uptake Clearance of Reference Compounds for Each Transporter
This method is based on the ratio of the uptake clearance of reference compounds that are recognized by a specific transporter in human hepatocytes to that in expression systems. The uptake clearance of test compounds mediated by specific transporters in human hepatocytes can be predicted from this ratio and the uptake clearance of test compounds in expression systems. Regarding the uptake transporter for anions, estrone-3-sulfate (Esul) and cholecystokinin octapeptide (CCK-8) are selective substrates for OATP1B1 and OATP1B3, respectively, and are used as reference compounds for OATP1B1- and OATP1B3-mediated uptake. The ratio of the uptake clearance of reference compounds in human hepatocytes to that in the expression system is calculated and defined as Ract, OATP1B1 and Ract, OATP1B3 . The uptake clearances for OATP1B1 and OATP1B3 are calculated separately by multiplying the uptake clearance of test compounds in transporter-expressing cells (CLOATP1B1, test and CLOATP1B3, test ) by Ract, OATP1B1 and Ract, OATP1B3 , respectively, as described in the following equations: CLHep, E−sul , CLOATP1B1,E−sul CLHep, CCK−8 = , CLOATP1B3, CCK−8
Ract, OATP1B1 = Ract, OATP1B3
[5] [6]
CLhep, test, OATP1B1 = CLOATP1B1, test · Ract, OATP1B1 ,
[7]
CLhep, test, OATP1B3 = CLOATP1B3, test · Ract, OATP1B3 .
[8]
If the uptake of test compounds in human hepatocytes can be explained only by OATP1B1 and OATP1B3, the following equation should be used: CLhep, test = CLhep, test, OATP1B1 + CLhep, test, OATP1B3 .
[9]
For example, Kitamura et al. reported the contribution of OATP1B1 and OATP1B3 to the overall hepatic uptake of rosuvastatin in three independent batches of human hepatocytes (20). As is evident from Table 18.1, although inter-batch differences in the contributions of OATP1B1 and OATP1B3 were observed, the hepatic uptake of rosuvastatin is mainly mediated by OATP1B1. 3.8.2. Comparison of the Expression Level of Each Transporter Using Western Blot Analysis
This method is very similar to the RAF method, except that the ratio between expression levels is estimated using Western blot analysis instead of the uptake clearance of reference compounds. The ratio of the expression levels of OATP1B1, OATP1B3, and OATP2B1 in human hepatocytes (per 106 cells) to those in transporter-expressing cells (per milligram of protein)
110
7.89
134
3.50
57.7
2.02
Transporter
OATP1B1
OATP1B3
OATP1B1
OATP1B3
OATP1B1
OATP1B3
41.9
96.0
41.9
96.0
41.9
96.0
(2) Expression system (μL/min/mg protein)
0.0482
0.601
0.0835
1.40
0.188
1.15
(3)R value (1)/(2)
14.8
4.79
14.8
4.79
14.8
4.79
(4) Expression system (μL/min/mg protein)
Rosuvastatin
0.713
2.88
1.24
6.69
2.79
5.49
CLhepatocyte (μL/min/106 cells) (3)×(4)
19.8
80.2
15.6
84.4
33.7
66.3
Contribution (%)
In experiments with transporter-expression systems, uptake of E1 S (reference compound for OATP1B1), CCK-8 (reference compound for OATP1B3), and rosuvastatin were determined simultaneously for 0.5, 5, and 1 min, respectively. OATP1B1- and OATP1B3-mediated transport was calculated by subtracting uptake in vector-transfected control cells from that in OATP1B1- and OATP1B3-expressing cells. ∗ Data were derived from a previous report (12).
ETR
094
OCF
Lot No.
(1) Human hepatocytes∗ (μL/min/106 cells)
Reference compounds
Table 18.1 Uptake clearance of reference compounds (E1 S and CCK-8) and rosuvastatin in OATP1B1- and OATP1B3-expressing HEK293 cells (our results) and human hepatocytes (reported values), and the relative contribution of OATP1B1 and OATP1B3 to the overall hepatic uptake of rosuvastatin in human hepatocytes (20)
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(R exp, OATP1B1 , R exp, OATP1B3 , R exp, OATP2B1 ) can be calculated from the intensity of specific bands in Western blot analysis and the amount of crude membrane prepared from each cell type as follows. The relative expression level per 106 hepatocytes or per milligram of protein in whole HEK293 cells is calculated by multiplying the band density per unit protein in the crude membrane fraction of each batch of hepatocytes or transporter-expressing HEK293 cells by the amount of protein in the crude membrane fraction obtained from 106 hepatocytes or 1 mg whole cell protein from HEK293 transfectants. The R exp value is calculated as the relative expression level per 106 hepatocytes divided by the relative expression per milligram protein in HEK293 cells. The OATP1B1-, OATP1B3-, and OATP2B1-mediated hepatic uptake of test compounds is calculated using the following equation if the uptake of test compounds in human hepatocytes can be explained only by OATP1B1, OATP1B3, and OATP2B1: CLhep, test = CLOATP1B1, test · Rexp, OATP1B1 + CLOATP1B3, test · Rexp, OATP1B3 + CLOATP2B1, test · Rexp, OATP2B1 [10] For example, Hirano et al. reported the contribution of OATP1B1, OATP1B3, and OATP2B1 to the overall hepatic uptake of estradiol-17β-glucuronide (E2 17βG) and pitavastatin in three independent batches of human hepatocytes. As is evident from Table 18.2, the ratio of the expression level of OATP2B1 in human hepatocytes to that in the expression system is very low compared with that of OATP1B1 and OATP1B3 (13). The hepatic uptake of these two test compounds is predominantly mediated by OATP1B1. 3.8.3. Inhibitable Portion of Uptake in Human Hepatocytes in the Presence of a Specific Inhibitor for Each Transporter
It has been reported that estrone-3-sulfate (E-sul) potently inhibits OATP1B1-mediated uptake, but not OATP1B3mediated uptake. Thus, assuming that the hepatic uptake of organic anions is mediated by OATP1B1 and OATP1B3, the ratio of the uptake of test compounds in the presence of E-sul to their uptake in the absence of E-sul represents the contribution of OATP1B1-mediated uptake. It would be desirable to observe the inhibitory effects of specific inhibitors on transporters such as OATP1B3 and OATP2B1 but specific inhibitors have not been identified yet. Therefore, we never estimate the contribution of OATP1B1 to the overall hepatic uptake of test compounds using this method only, but consider results obtained using this method in conjunction with results obtained using the other two methods before making conclusions. For example, Ishiguro et al. demonstrated that OATP1B1 makes a minor contribution to the hepatic uptake of telmisartan using this method (21). An in vitro study indicated that telmisartan is transported in OATP1B3-expressing HEK293 cells, but
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Table 18.2 Contribution of OATP1B1, OATP1B3, and OATP2B1 to the hepatic uptake of pitavastatin according to relative expression level (13) Ratio of expression levela hepatocyte/transporter
Estimated clearanceb of pitavastatin
OATP1B1 OATP1B3 OATP2B1 Hepatocyte (microL/ (microL/ (microL/ Rexp, OATP1B1 Rexp, OATP1B3 Rexp, OATP2B1 min/106 cells) min/106 cells) min/106 cells) lot OCF
2.90c
1.21c
0.200
094
1.58c
0.930c
0.152
ETR
0.890c
0.737c
0.112
222
37.0
0.658
85.5%
14.3%
0.253%
121
28.5
0.500
80.7%
19.0%
0.333%
68.2
22.6
0.368
74.8%
24.8%
0.405%
a The ratio of the expression level was determined as the intensity of the specific band in the crude membrane fraction prepared from human hepatocytes (per 106 cells) divided by that in the crude membrane fraction prepared from transporter-expressing cells (per milligram). b The values in every second row in the estimated clearance columns indicate the percentage of OATP1B1-, OATP1B3-, or OATP2B1-mediated uptake clearance relative to the sum of the estimated clearance mediated by OATP1B1, OATP1B3, and OATP2B1. c Hirano et al. (2004) J. Pharmacol. Exp. Ther. 311, 139–146.
not in OATP1B1-expressing cells. To validate the minor role of OATP1B1, the effect of 30 μM E-sul on the uptake of telmisartan and E2 17βG, which was previously reported to be mediated mainly by OATP1B1 according to the RAF method, was investigated using human cryopreserved hepatocytes. As Table 18.3 shows, E2 17βG uptake was inhibited by 30 μM E-sul, but telmisartan uptake was not affected by E-sul, indicating that OATP1B1 does not make a major contribution to the hepatic uptake of telmisartan. 3.9. Prediction of In Vivo Hepatic Clearance of Transporter Substrates
The in vitro intrinsic uptake clearance of rat isolated hepatocytes is calculated by dividing the initial uptake velocity by the drug concentration in the incubation buffer. To extrapolate in vitro results to in vivo conditions, we assume 1.25×108 cells/g liver and 38.3 g liver/kg body weight for rats, although these values vary a little according to other reports. For example, the uptake clearance of valsartan in rat hepatocytes was reported to be 0.112 mL/min/106 cells (19). Thus, the in vivo intrinsic hepatic uptake clearance of valsartan can be estimated using the following equation: CLint, h = 0.112(mL/min/106 cells) × 1.25 × 108 (cells/g liver)/ 106 × 38.3(g liver/kg body weight) = 536(mL/min/kg). [11]
1.50 ± 0.75 (26.6%)
63.9 ± 11 (131%)
30
1.03 ± 0.76 (55.8%)
1.85 ± 0.72
E2 17βG
18.1 ± 3.7 (108%)
16.8 ± 5.3
μl/min/106 cells
Telmisartan
HH-MYO
0.38 ± 0.45 (19.0%)
2.01 ± 0.62
E2 17βG
The substrate concentrations used were 0.1 and 1 μM for telmisartan and E2 17βG, respectively. The saturable uptake of telmisartan and E2 17βG into cryopreserved human hepatocytes was determined after subtraction of the nonsaturable uptake (evaluated as the uptake clearance of the respective compounds in the presence of 40 μM telmisartan and 200 μM E2 17βG). Values in parentheses indicate the percentage of the saturable uptake of telmisartan and E2 17βG in the absence of inhibitor.
42.2 ± 0.41 (100%)
42.0 ± 1.7
5.66 ± 1.1
48.5 ± 3.6
Telmisartan
0
E2 17βG
HH-094
μl/min/106 cells
Telmisartan
HH-OCF
μl/min/106 cells
E-sul (μM)
Table 18.3 Effect of E-sul on the uptake of telmisartan and E2 17βG by cryopreserved human hepatocytes in the presence of 0.3% human serum albumin (21)
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The predicted organ clearance of valsartan can be using a simple well-stirred model (equation [12]) or a dispersion model (dispersion number (DN ) = 0.17) (equations [13]–[16]), assuming that intrinsic hepatic uptake clearance is equal to intrinsic overall hepatic clearance (CLint, h ) (uptake-limited clearance). In the well-stirred model, hepatic clearance (CLh ) is expressed as a function of intrinsic hepatic clearance (CLint, h ), hepatic blood flow rate (Qh ), and the protein unbound fraction in blood (fB ):
CLh =
Q h × fB CLint, h . Q h + fB CLint, h
[12]
In the dispersion model, hepatic clearance (CLh ) is expressed as a function of CLint, h , Qh , fB , and dispersion number (DN ):
CLh = Qh × (1 − F ),
[13]
In vivo CLbile,B(mL/min/kg)
1000
3
1
100 7 12
9 2 4
10 5
10
6 8 11
1
1
10
100
1000
In vitro CLh,predicted(mL/min/kg) Fig. 18.4. Comparison between observed and predicted hepatic clearances of 12 transporter substrates in rats (19). The predicted organ clearances were calculated using equations [13]–[16], assuming that uptake clearance obtained from rat isolated hepatocytes was equal to the intrinsic hepatic clearance (CLint ). The observed and predicted hepatic clearances of 12 transporter substrates are shown (1, pravastatin; 2, pitavastatin; 3, rosuvastatin; 4, valsartan; 5, olmesartan; 6, candesartan; 7, temocaprilat; 8, enalaprilat; 9, benazeprilat; 10, PCG; 11, ceftizoxime; and 12, cefmetazole). The solid and dashed lines represent unity and correlations of 1:2 and 2:1, respectively.
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where F=
4a , (1+a)2 · exp{(a − 1)/2DN }−(1 − a)2 · exp{−(a + 1)/2DN } [14] a = (1 + 4RN · DN )1/2 , R N = fB ·
CLint, h . Qh
[15] [16]
In these calculations, we assume a hepatic blood flow rate of 60 mL/min/kg and a measured protein unbound fraction of valsartan in blood of 0.014. Thus, the hepatic clearance of valsartan is predicted to be 6.67 mL/min/kg according to the well-stirred model and 7.05 mL/min/kg according to the dispersion model (see Note 13). The hepatic clearances of 12 transporter substrates estimated using the in vitro rat-isolated hepatocyte uptake assay correlates well with observed in vivo hepatic clearances in rats (Fig. 18.4) (19).
4. Notes 1. Warm water should be used to dilute the chlorhexidine gluconate solution because urethane decreases the body temperature of rats. 2. Because the specific activity of collagenase per unit weight varies among batches, another batch of collagenase should be used if the hepatocytes do not disperse well after successful perfusion. 3. The transport activity of human cryopreserved hepatocytes varies among batches and in our experience, only 30–40% of commercially available batches of human hepatocytes exhibit adequate uptake of typical organic anions such as estradiol-17β-glucuronide (E2 17βG) and taurocholate. Our in-house data show that the uptake activity of typical transporter substrates is not correlated with metabolic activities mediated by CYP enzymes, which is often claimed to be the case in the product sheets that accompany batches of human hepatocytes. Thus, for the transport assay, it is very important to select good batches of human hepatocytes. We screen batches for the uptake activities of E2 17βG and taurocholate, which are typical ligands for OATPs and NTCP, respectively, and only use
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batches in which the transport of both compounds is adequate (more than 5 μL/min/106 cells) for future experiments. Even when only good batches are used, the interbatch difference in the uptake activity of typical ligands is large. This difference is thought to be caused by intrinsic inter-individual differences in transporter function and differences in methods used for isolation and cryopreservation of hepatocytes. We recommend the use of at least three independent batches of human hepatocytes to determine the transport activities of compounds and the contribution of each transporter to their uptake. 4. Unlabeled compound is usually stocked as a concentrated solution of DMSO (e.g., ×1,000) and stored at −20 or −80◦ C. When making the substrate solution, unlabeled compound is added as the DMSO solution. However, the concentration of DMSO in the substrate solution should not exceed 0.1–0.5% because DMSO influences the cell metabolism and uptake activity. If a higher concentration of DMSO is used in the substrate solution, tests should be conducted to determine that there is no significant difference in the uptake activity of the tracer dose of test compounds or typical ligand (e.g., E2 17βG) in the presence and absence of DMSO. Tests should also be conducted to determine whether all of the ligands are dissolved in the substrate solution because it is often very difficult to see insoluble compounds with the naked eye. 5. Because the reactivity of antiserum varies between individual rabbits, three rabbits are simultaneously immunized with synthetic peptides and the antiserum with the best reactivity is used for future experiments. 6. If liver perfusion with solution A is successful, the blood in the whole liver washes out immediately and the liver becomes a uniform khaki color. 7. If the liver perfusion with solution B is successful, the edge of each lobe becomes rounded, the whole liver becomes inelastic and small clots with dispersed hepatocytes can be seen in parts of the lobes. 8. Further purification with percoll improves the viability of hepatocytes. In our hands, the viability of rat isolated hepatocytes is greater than 85% without further purification with percoll and we have not experienced problems with analyses. The viability of human cryopreserved hepatocytes is low. Purification with percoll greatly improves their viability, but if the number of viable cells is low, a greater number of cells than were used in our uptake experiments may be required.
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9. If a test compound is not radiolabeled, its concentration may be estimated using LC/UV or LC/MS. Because NaOH sometimes degrades the chemical structure of test compounds, 100 μL of 5 M sodium acetate can be used instead of 50 μL of 2 N NaOH in the sampling tube (19). After the lower phase is sampled, cells in 5 M sodium acetate are sonicated in a new tube to break them down, precipitated with three volumes of methanol and centrifuged at 15,000×g at 4◦ C for 10 min. The supernatants are subjected to liquid chromatography. 10. The effect of sodium butyrate on the expression level of transporters depends on the clone and some clones do not show any enhanced expression of transfected transporter. 11. If a test compound is not radiolabeled, its concentration may be estimated using LC/UV or LC/MS. In that case, some compounds may be degraded by strong alkaline condition. If so, NaOH should not be used for solubilization of cells and extraction of intracellular compound by organic solvents such as methanol or acetonitrile is sometimes effective. Extracted solution is then centrifuged at 15,000×g at 4◦ C for 10 min. The supernatants are subjected to LC/MS. 12. Because OATPs have multiple membrane spanning domains, the boiling of samples may enhance the aggregation of membrane proteins with the result that the band becomes broad and fuzzy. Consequently, we do not boil the samples before loading them onto the gel. 13. The previous report indicated that the difference in calculated hepatic availability estimated using the well-stirred model or the dispersion model is large if intrinsic hepatic clearance is large relative to the hepatic blood flow rate. Thus, if the hepatic clearance is limited by blood flow, it is strongly recommended that the dispersion model is used for the prediction of hepatic clearance from in vitro data.
References 1. Giacomini, K.M. and Sugiyama, Y. (2005) Membrane transporters and drug response, in Goodman & Gilman’s the Pharmacological Basis of Therapeutics, 11th ed. (Brunton, L.L., Lazo, J.S., and Parker, K.L., eds.), McGraw-Hill, New York, pp. 41–70. 2. Shitara, Y., Horie, T., and Sugiyama, Y. (2006) Transporters as a determinant of drug clearance and tissue distribution. Eur. J. Pharm. Sci. 27, 425–446.
3. Regazzi, M.B., Iacona, I., Campana, C., Raddato, V., Lesi, C., Perani, G., Gavazzi, A., and Vigano, M. (1993) Altered disposition of pravastatin following concomitant drug therapy with cyclosporin A in transplant recipients. Transplant. Proc. 25, 2732–2734. 4. Asberg, A., Hartmann, A., Fjeldsa, E., Bergan, S., and Holdaas, H. (2001) Bilateral pharmacokinetic interaction between cyclosporine A and atorvastatin in renal
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transplant recipients. Am. J. Transplant. 1, 382–386. Ichimaru, N., Takahara, S., Kokado, Y., Wang, J.D., Hatori, M., Kameoka, H., Inoue, T., and Okuyama, A. (2001) Changes in lipid metabolism and effect of simvastatin in renal transplant recipients induced by cyclosporine or tacrolimus. Atherosclerosis 158, 417–423. Mazzu, A.L., Lasseter, K.C., Shamblen, E.C., Agarwal, V., Lettieri, J., and Sundaresen, P. (2000) Itraconazole alters the pharmacokinetics of atorvastatin to a greater extent than either cerivastatin or pravastatin. Clin. Pharmacol. Ther. 68, 391–400. Neuvonen, P.J., Kantola, T., and Kivisto, K.T. (1998) Simvastatin but not pravastatin is very susceptible to interaction with the CYP3A4 inhibitor itraconazole. Clin. Pharmacol. Ther. 63, 332–341. Maeda, K. and Sugiyama, Y. (2008) Impact of genetic polymorphisms of transporters on the pharmacokinetic, pharmacodynamic and toxicological properties of anionic drugs. Drug Metab. Pharmacokinet. 23, 223–235. Kiyotani, K., Mushiroda, T., Kubo, M., Zembutsu, H., Sugiyama, Y., and Nakamura, Y. (2008) Association of genetic polymorphisms in SLCO1B3 and ABCC2 with docetaxel-induced leukopenia. Cancer Sci. 99, 967–972. Noe, J., Portmann, R., Brun, M.E., and Funk, C. (2007) Substrate-dependent drugdrug interactions between gemfibrozil, fluvastatin and other organic anion-transporting peptide (OATP) substrates on OATP1B1, OATP2B1, and OATP1B3. Drug Metab. Dispos. 35, 1308–1314. Link, E., Parish, S., Armitage, J., Bowman, L., Heath, S., Matsuda, F., Gut, I., Lathrop, M., and Collins, R. (2008) SLCO1B1 variants and statin-induced myopathy – a genomewide study. N. Engl. J. Med. 359, 789–799. Hirano, M., Maeda, K., Shitara, Y., and Sugiyama, Y. (2004) Contribution of OATP2 (OATP1B1) and OATP8 (OATP1B3) to the hepatic uptake of pitavastatin in humans. J. Pharmacol. Exp. Ther. 311, 139–146.
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13. Hirano, M., Maeda, K., Shitara, Y., and Sugiyama, Y. (2006) Drug-drug interaction between pitavastatin and various drugs via OATP1B1. Drug Metab. Dispos. 34, 1229–1236. 14. Crespi, C.L. and Penman, B.W. (1997) Use of cDNA-expressed human cytochrome P450 enzymes to study potential drug-drug interactions. Adv. Pharmacol. 43, 171–188. 15. Kouzuki, H., Suzuki, H., Ito, K., Ohashi, R., and Sugiyama, Y. (1998) Contribution of sodium taurocholate co-transporting polypeptide to the uptake of its possible substrates into rat hepatocytes. J. Pharmacol. Exp. Ther. 286, 1043–1050. 16. Kouzuki, H., Suzuki, H., Ito, K., Ohashi, R., and Sugiyama, Y. (1999) Contribution of organic anion transporting polypeptide to uptake of its possible substrates into rat hepatocytes. J. Pharmacol. Exp. Ther. 288, 627–634. 17. Miyauchi, S., Sawada, Y., Iga, T., Hanano, M., and Sugiyama, Y. (1993) Comparison of the hepatic uptake clearances of fifteen drugs with a wide range of membrane permeabilities in isolated rat hepatocytes and perfused rat livers. Pharm. Res. 10, 434–440. 18. Kato, Y., Akhteruzzaman, S., Hisaka, A., and Sugiyama, Y. (1999) Hepatobiliary transport governs overall elimination of peptidic endothelin antagonists in rats. J. Pharmacol. Exp. Ther. 288, 568–574. 19. Watanabe, T., Maeda, K., Kondo, T., Nakayama, H., Horita, S., Kusuhara, H., and Sugiyama, Y. (2009) Prediction of the hepatic and renal clearance of transporter substrates in rats using in vitro uptake experiments. Drug Metab. Dispos. 37, 1471–1479. 20. Kitamura, S., Maeda, K., Wang, Y., and Sugiyama, Y. (2008) Involvement of multiple transporters in the hepatobiliary transport of rosuvastatin. Drug Metab. Dispos. 36, 2014–2023. 21. Ishiguro, N., Maeda, K., Kishimoto, W., Saito, A., Harada, A., Ebner, T., Roth, W., Igarashi, T., and Sugiyama, Y. (2006) Predominant contribution of OATP1B3 to the hepatic uptake of telmisartan, an angiotensin II receptor antagonist, in humans. Drug Metab. Dispos. 34, 1109–1115.
Chapter 19 Metabonomic Studies on Human Hepatocyte in Primary Culture Vincent Croixmarie, Thierry Umbdenstock, Olivier Cloarec, Amélie Moreau, Jean-Marc Pascussi, Yannick Parmentier, Claire Boursier-Neyret, and Bernard Walther Abstract Mechanisms involved in induction processes have been investigated using fresh human hepatocytes in culture as a cellular model and using mass spectrometry-based metabonomics as a global investigation tool. Sample preparation to data analysis have been detailed in an approach enabling to separate druginduced (endogenous metabolites) and drug-related (drug metabolites) biomarkers for reference inducers. Rifampicin, a nuclear pregnane X receptor (PXR) ligand; CITCO, a nuclear constitutive androstane receptor (CAR) ligand; and phenobarbital, which activates both CAR and PXR, have been used. Specific intra-cellular metabolites have been isolated for rifampicin and CITCO as potential endogenous biomarkers of their respective induction mechanism. A mixture of these two types of biomarkers modified in the same way after treatment with either rifampicin or CITCO on the one hand and with phenobarbital on the other hand has been found. Key words: Hepatocytes, induction, UPLC–ToF-MS, metabonomics, phenobarbital, CITCO, rifampicin, data analysis, CAR, PXR.
1. Introduction In vitro cellular models such as hepatocytes have demonstrated their impact in the early evaluation of safety and efficacy profile of drugs as well as in the optimization of drug–drug interaction studies, because they express absorption, distribution, metabolism, and excretion (ADME) proteins such as enzymes, transporters but also regulation factors of cellular pathways P. Maurel (ed.), Hepatocytes, Methods in Molecular Biology 640, DOI 10.1007/978-1-60761-688-7_19, © Springer Science+Business Media, LLC 2010
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allowing to better understand the positive (efficacy) and negative (safety) aspects of a drug (1), as well as enzyme induction potential of a drug. This latter point is of particular interest because enzyme induction is a physiological process related to the exposure to exogenous chemicals able to trigger major changes in the regulation pathways of a cell (2–4). Hepatocytes can be considered as a reference model for induction because transcription factors belonging to nuclear receptor superfamilies as well as regulation processes of hepatic genes encoding drug metabolism enzymes and transporters are present and functional in this model (5). This is especially true for the nuclear receptors constitutive androstane receptor (CAR) (5, 6) and pregnane X receptor (PXR) (5, 7, 8), which play a critical role in modulating the human P450 2B and 3A enzymes, respectively. During the process of hepatic induction, these receptors which heterodimerize with retinoid X receptor (RXR) are activated and establish cross talks with other nuclear receptors regulating homeostasis of endogenous biomarkers, such as bile acids, steroid hormones, lipids, and vitamins (9, 10). We investigated the biochemical variations induced in primary culture of human hepatocytes by reference inducers. Those inducers have been chosen because two of them are specific ligands for one of the studied nuclear receptors – CITCO with CAR (2, 6) and rifampicin with PXR (2–4, 8) – when the third one (phenobarbital) activates both of them (2). A global tool such as metabonomics was used for this purpose. Today, this global approach is defined as a quantitative measurement of the dynamic multiparametric metabolic responses of living systems to pathophysiological stimuli or genetic modifications to capture large ranges of metabolic changes due to a treatment and to follow simultaneously in a cellular model such as hepatocytes and drug-related (drug metabolites) and druginduced (endogenous metabolites) biotransformation products (11). Monitoring metabolism and biomarker changes can then be considered as an analytical chemistry approach with the aim of exhaustively tracking the availability and concentration of small molecules – everything from electrolytes to metabolic intermediates and enzyme cofactors – in biological systems. Food and Drug Administration and pharmaceutical companies show a great interest in this field (12, 13). Although the application domains of metabonomics are quite large (agriculture, industrial biotechnology, xenobiochemistry, medical applications), its use in the cell culture area is not very developed yet (14). This methodology coupling new analytical technologies and approaches with chemometric tools will allow to propose new strategies enabling to monitor the biomarkers linked to a biological stress (treatment, pathology, etc.).
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Here we present a framework to perform a metabonomic study on hepatocyte cultures treated with several drugs. The different aspects of data processing and pattern recognition have been especially developed, illustrating the importance of a global experimental design considering every single step of the study, from the sample preparation to data analysis.
2. Materials 2.1. Cell Origin and Culture
1. Discarded human hepatic tissue fragments, lobectomy (latter called FT 290, 291, 292, 293, and 294) from patients with secondary hepatic tumors, were obtained at the Saint Eloi Hospital, Montpellier, France. See Chapters 12 and 23 for hepatocyte culture preparation. 2. Collagenase was used to prepare hepatocytes by conventional perfusion. 3. Culture media, dimethyl sulfoxide (DMSO), rifampicin, CITCO and phenobarbital, and culture medium additives were purchased from Sigma (Saint Louis, MO). 4. Eurocollins: 2.05 g/L NaHCO3 , 35 g/L glucose (pH 7.33), used for extensive washing of the tissue. 5. The chemically defined medium (designated HCD medium) consisted of a 1:1 ratio of William’s medium E and Ham’s F12 medium supplemented with 0.25% bicarbonate, 15 mM HEPES, 500 units/mL penicillin, 500 μg/mL streptomycin, 65.5 μM ethanolamine, 100 μg/mL transferrin, 0.6 μg/mL insulin, 1 μM dexamethasone, 10 nM glucagon, 7.18 μM linoleic acid linked to 0.08% fatty acid-free bovine serum albumin, 7.0 mM glucose, 0.4 mM sodium pyruvate, and 0.1 mM ascorbic acid (15) and containing 10% fetal calf serum. 6. BioCoatTM collagen I six-well cell culture plates from BD Biosciences. 7. Phosphate buffered saline (PBS) solution.
2.2. Samples Analysis
R 1. A Precellys system for intra-cellular medium collection by orbital centrifugation leading to cell disruption.
2. A Waters ACQUITY Ultra-Performance Liquid Chromatography (UPLC) system (Waters Corporation, Milford, MA, USA) was utilized for the chromatographic separations. 3. A Waters ACQUITY BEH C18 column (100 mm × 2.1 mm × 1.7 μm).
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4. A Micromass LCT Premier time-of-flight mass spectrometer (ToF-MS) from Waters equipped with an electrospray source coupled to the chromatographic system. 5. Test mix solution: 12 μg/mL theophylline, 12 μg/mL caffeine, 12 μg/mL hippuric acid, 4.5 μg/mL nortriptyline, and 4.5 μg/mL 4-nitrobenzoic acid, purchased from Waters. 6. Leucine enkephalin solution: 50 pg/μL, used as lock mass compound in MS experiments, purchased from Sigma (Saint Louis, MO). 2.3. Data Analysis
1. File conversion from MassLynx “.raw” into NetCDF format has been performed with Databridge program, which is in the MassLynx package. 2. Peak detection and integration used the in-house MassExplorer (see Note 1) package implemented in Matlab software (R2007a; Mathworks). 3. The resulting output was loaded in Excel (Microsoft). 4. The multivariate statistical analysis was done with SIMCAP software (v. 12; Umetrics). The – nonsupervised – principal component analysis (PCA) procedure was applied to inspect data. The supervised partial least squares projections to latent structure discriminant analysis (PLS-DA) and orthogonal PLS (O-PLS) methods were carried out to build the shared and unique structure (SUS) plot.
3. Methods Traditionally, in metabonomics, nuclear magnetic resonance (NMR) spectroscopy has been the technique of choice due to its ability to measure intact biomaterial non-destructively as well as the rich structural information that can be obtained (16–18). However, the sensitivity of NMR spectroscopy is relatively poor compared with mass spectrometry (MS) methods, and concentrations of potential biomarkers may be below the detection limit. Gas chromatography (GC) in tandem with MS is also widely used for metabonomic studies (19–21) and provides efficient and reproducible analysis. However, GC/MS requires sample derivatization to generate volatile compounds that can be separated on the GC column. Non-volatile compounds that cannot be derivatized and large or thermolabile ones will not be observed in GC/MS analysis.
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With high-performance liquid chromatography (HPLC) coupled to MS (22) (LC/MS), there is no need to derivatize compounds prior to analysis. LC/MS is also capable of analyzing a large number of compounds that cannot be analyzed by GC/MS. Unfortunately, compared with GC, LC/MS has some drawbacks in chromatographic performance such as resolution. However, the recent introduction of UPLC, which uses columns with smaller particle size and high-pressure separation, has improved chromatographic resolution (23). Therefore, the recently developed analytical technique called ultra-performance liquid chromatography coupled with a time-of-flight mass spectroscopy (24) (UPLC–ToF-MS) is gaining interest in metabonomic analysis of complex samples such as biofluids or tissue extracts. MS data post-processing, visualization, and statistical methods are also of great importance in order to sort and select potential biomarkers according to the biological questions explored by the study design. Shared and unique structure (SUS) plot (25) is one of such powerful methods that has been implemented here. 3.1. Primary Culture of Human Hepatocytes (HHPCs) and Sample Preparation
1. Hepatic tissue fragments from different patients are used to prepare hepatocytes by conventional collagenase perfusion after an extensive washing of the tissue with Eurocollins (26) (see Note 2). See Chapters 12 and 23 for hepatocyte culture preparation. 2. Hepatocytes (12 millions) are suspended in 6 mL of the HCD supplement containing 10% fetal calf serum. 3. One milliliter is distributed in BioCoatTM collagen I sixwell plates to obtain 2 million cells/well. 4. Cultures are maintained at 37◦ C in humid atmosphere containing 5% CO2 . 5. HCD medium is renewed after 10 h and thereafter every 48 h in the absence of serum. Treatment of the cells can start 36 h after plating. 6. Drugs are diluted in dimethyl sulfoxide (DMSO) at appropriate concentrations: 10 mM rifampicin, 500 mM phenobarbital, and 1 mM CITCO. About 1.5 μL of these solutions is added to 1.5 mL of HCD medium to reach the final concentration. Untreated cultures receive the same amount of DMSO. 7. HHPCs are maintained in the absence (0.1% DMSO) or the presence of treatment for 96 h. After 48 h of incubation, the medium is renewed with 1.5 μL of the drug solution. After 24 and 72 h of incubation, some medium is added (500 μL containing 2 μL of the drug solution).
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8. Six biological replicates are performed for each different condition. 9. After 96 h of incubation, supernatants are collected in 2-mL Eppendorf tubes and frozen at −80◦ C, whereas the hepatocyte cells are washed with PBS at 4◦ C, scraped in 1 mL of PBS solution at 4◦ C, and centrifuged at 2,000×g for 10 min at 4◦ C or at 10,000×g for 5 min at 4◦ C. Then, PBS is removed and tubes are frozen at −80◦ C. 10. Cell pellets and supernatants are used for metabolic profiling. 11. Supernatants are analyzed directly by UPLC–ToF-MS after a dilution step (1:3 dilution with H2 O), whereas the cells are extracted with the following procedure: after storage at −80◦ C, the cell pellet is resuspended with 200 μL of a mixture of water/acetonitrile (1:1). 12. Cells are disrupted by orbital centrifugation using a R Precellys system: two centrifugation steps at 6,000 rpm for 30 s at room temperature. The resulting homogenate is then centrifuged at 13,000×g for 2 min before injection. 3.2. Sample Analysis by UPLC–TOF-MS
1. Samples are injected on a Waters ACQUITY UPLC system. Cell extracts and supernatants are injected in two separate batches. 2. Chromatographic separations are performed on the BEH C18 column maintained at 40◦ C. The chromatographic flow rate is 500 μL/min and the run length is 12 min. 3. The mobile phases used are 0.1% formic acid in water (solvent A) and 0.1% formic acid in acetonitrile (solvent B). The starting conditions are 100% solvent A and a gradual increase of solvent B from 0 to 20% over the first 4 min, from 20 to 80% between 4.0 and 9.0 min, from 80% to 95% between 9.0 and 9.1 min. Then isocratic conditions with 95% of solvent B are used from 9.1 to 10 min. Finally the starting conditions with 100% solvent A are used from 10 to 12 min. 4. The UPLC–ToF-MS system equipped with an electrospray source is operated successively in positive and negative ion modes with a lockspray interface for accurate mass measurements. 5. The source temperature is set at 150◦ C with a cone gas flow of 50 L/h at 400◦ C and a nebulization gas flow of 700 L/h. 6. The capillary voltage is set at 3 and 2.7 kV for positive and negative ion modes, respectively, with a cone voltage of 50 V.
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7. The data acquisition rate is set at 0.1 s−1 and the interscan delay is set at 0.01 s, with the dynamic range enhancement (DRE) mode activated. 8. The LCT Premier Mass Spectrometer operates in W mode with 14,000 of resolving power. 9. Leucine enkephalin, used as lock mass compound, is infused at a concentration of 50 pg/μL and with an infusion flow rate of 50 μL/min. 10. In positive mode, isotopic [M+H]+ ions of leucine enkephalin at 556.2771 and 558.2829 Da are used as the attenuated lock mass and lock mass, respectively. 11. In negative mode, isotopic [M−H]− ions at 554.2615 and 555.2645 Da are used. 12. All mass spectral data are acquired in centroid mode (fivescan average with the lockspray interval of 15 s) over the mass range m/z 50–1,000 Da. The instrument is calibrated using phosphoric acid solution. 13. Cell extracts and supernatants are pooled separately (each containing all samples of their respective set), and a set of concentrated and diluted pooled samples is prepared and ordered in an orthogonalized way against injection order, for instance [0; 1/3; 1/1; 3/1; 3/1; 1/1; 1/3; 0; 0; 1/3; 1/1; 3/1; 3/1; 1/1; 1/3; 0], “0” being a blank sample. 14. In the sample list, the liver number and the kind of treatment are orthogonalized to the injection order to avoid known bias linked to the systematic analytical gain variations. 15. The sample list is completed in inserting the “dilution variable” containing the concentrated and diluted pooled samples regularly throughout the list. 16. Some blank and reference (containing the test mix solution) samples are also regularly inserted throughout the list, with the first “true sample” being in a fourth or a fifth position (see Note 3). 17. Samples (cell extracts and supernatants) are distributed over 96-well plates. 3.3. Data Analysis (Data Treatment and Chemometric Analysis)
1. Files are converted from MassLynx “.raw” into NetCDF format using the Databridge program. 2. Secondary experiment names are retrieved from the sample list and are kept during the whole process for annotation and further supervised for analysis purpose. The following seven points (3–9) are specific parts of the in-house MassExplorer software.
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3. The NetCDF files correspond essentially to a list of detected impacts. This list has three columns: the time, which corresponds to the UPLC elution time, the mass detected during the MS scan, and the intensity of the corresponding ion current. The raw data – a vector of [Time; Mass; Intensity] data – obtained from UPLC-MS cannot be directly used for further pattern recognition; they are loaded into memory with an intensity threshold of 20. 4. A chromatographic peak is around 5 s long while a scan is acquired roughly three times per second, so the amount of data (lines) is huge and still meaningless. The goal here is to reduce the data into well-shaped peaks, but the impacts are not connected at this stage. A continuous representation of the [Time; Mass; Intensity] triplet will allow our feature detection (see Note 4). With each triplet, a twodimensional Gaussian curve is calculated with a doublet sigma (the time and mass component values are chosen heuristically depending on the chemical analysis settings). The intensity provides the height parameter, while the time and the mass give the curve location. The density map is the sum of the entire set of Gaussian curves. This step is done on a 1-Da-width map and it is repeated sequentially on the entire m/z range. 5. After a UPLC–ToF-MS analysis, data with low mass and time shift are provided, together with a mass accuracy around (at least) 5–10 ppm. Therefore, with appropriate parameters, the resulting surface is made of isolated peaks (see Fig. 19.1, upper panel), which have to be located. 6. The subsequent algorithm is repeated until an intensity threshold is reached: (i) the global maximum of the 1-Da-width density map is gathered, Imax ; (ii) a projection of the map along mass and time dimension is done; (iii) intervals along each dimension where the intensity is above the a∗Imax (a belonging to the interval [0.1; 0.9]) are selected; (iv) the entire set of intersections of those intervals is tested with the same a∗Imax threshold and cleaned in order to pick the area of the underlying peak; (v) the areas and their surroundings are put to zero intensity; and the loop is redone. See Fig. 19.1, lower panel for the resulting map after three loops. 7. Local maxima [Ret. Time; m/z] coordinates which are localized on a 1-Da-width map are stored. This procedure is repeated until the entire m/z range has been covered. 8. The previous local maxima list (i.e., variable list) is used for the integration step. The non-modified impacts (from the raw data) lying under a rectangular area centered on the
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Fig. 19.1. Peak picking activity result on a typical “density map.” The upper panel shows the density map in a typical mass default range from 332 to 332.4 Da. The spots are made of the Gaussian-transformed impacts. The lower panel shows the rectangular frames where the spots are identified as chromatographic peaks.
variable coordinates are summed file by file. The result is a line of intensity values for one particular variable, each row being a file (a sample). The whole table is finished when the list has been covered. 9. The “dilution variable” is the vector containing the concentration and dilution levels and their injection order: here [0; 1/3; 1/1; 3/1; 3/1; 1/1; 1/3; 0; 0; 1/3; 1/1; 3/1; 3/1; 1/1; 1/3; 0]. The files corresponding to the pooled samples have been processed together with the other samples. They contain the whole set of molecules and so the integration has provided a “dilution table”, as four replicates of four different concentrated levels have been introduced. 10. For each variable a correlation is calculated between the integrated intensity found in the “dilution table” and the so-called dilution variable. See Fig. 19.2 for the distribution of the calculated correlations. 11. A data filtration is made by selection of the variables for which the correlation is above a threshold, usually put at 0.8 (vertical line in Fig. 19.2 with cutoff annotation) (see Note 5).
3.4. Metabolic Profile Interpretation
1. PCA has been performed on the data before and after the removal of the variables non-positively correlated with the pooled sample concentration. Fig. 19.3 shows the difference between the PCA score distribution obtained
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Fig. 19.2. The histogram highlights the correlation distribution between the concentration of the pooled samples (0, 1/3, 1, and 3/1) and the extracted feature signal intensity for those samples. (a–c) Examples of correlation between UPLC-MS signal intensities and concentrations of the pooled sample.
Fig. 19.3. PCA scores of the two first principal components (a) before data filtration and (b) after data filtration based on the dilution series and colored according to the hepatic tissue number. The samples are clustering more tightly after data filtration (b) and the fraction of variation explained by the first two components increases from 24% (a) to 46% (b).
from the filtered and non-filtered data; the clusters corresponding to the different livers are much tighter and separated from each other for the filtered data (Fig. 19.3b) than for the unfiltered data (Fig. 19.3a). Moreover, the amount of variation explained by the two first principal components is much more important with filtered data (explained variation of both first components 27% and 19% = 46%) than with the unfiltered data (explained variation 14% and 10% = 24%). This shows the benefit of applying such data filtration before pattern recognition, as
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it provides much more robust data analysis leading to a more reliable interpretation. 2. The PCA score plot corresponding to the two first principal components (Fig. 19.3b) shows that the first source of variation in the metabolic profile is related to the hepatocytes origin. The samples corresponding to one liver are clustered together whether they received a treatment (whatever its nature) or not. The inter-liver variations explain 46% of the whole variation (two first components), whereas the treatment (the second source of variation) explains only 13% of the variation (third component, Table 19.1) (see Note 6).
Table 19.1 Explained variance in the UPLC-MS data after univariance scaling Factor
Explained variance (%)
Liver
46
Treatment
13
Run order
11
Remaining
28
3. Supervised pattern recognition has then been performed in order to more directly explore the data. PLS-DA was used to test the potential differences between treatments and whether the model characteristics were satisfactory. The between the explained sum small difference of square R2Y = 0.53 and the predictive sum of square 2 Q Y = 0.47 – predictive power – allows a confident interpretation of the scores, presented in Fig. 19.4. It can be observed with the separation of treatments on the two first principal components (Fig. 19.4a), that rifampicin generates a different metabolic profile from the two other treatments. The separation with second and third components (Fig. 19.4b) illustrates the specificity of phenobarbital profile when compared to DMSO and CITCO on the one hand and to rifampicin on the other hand (see Note 7). 4. A pair-wise comparison with DMSO (the control group) has been carried out for each treatment (CITCO, phenobarbital, and rifampicin) using O-PLS. Table 19.2 shows a summary of the different pair-wise comparisons. This O-PLS statistical approach is forcing the separation of each treated group against the control one, using the first principal component’s dimension. However, each treatment can
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Fig. 19.4. PLS-DA scores with the classes RIF for rifampicin). The set according to the treatment (PB for phenobarbital, explained sum of square R2Y = 0.53 and the predictive sum of square Q 2Y = 0.47 – predictive power – allows a confident interpretation of the scores. It can be observed that rifampicin generates a different metabolic profile from the two other treatments when the first and the second components are displayed (a), while the separation with the second and the third components (b) illustrates the specificity of phenobarbital profile when compared to the other groups.
Table 19.2 O-PLS pair-wise comparisons between DMSO (control) and treatments Treatment
n. comp.
R2
Rifampicin vs. DMSO
1+1
85
Y
(%)
Q2 Y (%)
Max Q2 Y perm (%)
R2 Xp (%)
80
10
6.7
CITCO vs. DMSO
1+2
85
61
25
2.5
Phenobarbital vs. DMSO
1+1
90
82
15
3.3
RIF, rifampicin; PB, phenobarbital. R2 Y accounts for the explained variance of the Y component. Q2 Y accounts for the cumulative fraction of the total variation of Y that can be predicted by the model. Max Q2 Y perm is the maximum Q2 Y value reached after a random permutation of the Y vector; the differences between Max Q2 Y perm and Q2 Y is a validation criterion (reached here in every model). R2 Xp represents the fraction of the total variation of X explained by the sole predictive component.
still produce a bias in the discrimination due to exogenous (drug) metabolites. Every treatment demonstrates a significant difference from the control livers, thus it is possible to interpret and compare the loadings of the O-PLS models (see Note 8). 5. In order to avoid a bias due to the potential presence of exogenous drug metabolites in the interpretation of endogenous biomarkers of PXR and CAR activation processes, a complementary statistical approach, the SUS plot technique (25), has been used. This type of representation allows the comparison between two different models which share the same control group. Fig. 19.5 shows two SUS plots. Each SUS plot component comes from the O-PLS
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Fig. 19.5. Shared and unique structure (SUS) plot for the comparison of the metabolic profile induced by phenobarbital and the profiles induced either by rifampicin (a) or CITCO (b). A SUS plot uses the combination of two predictive loadings obtained from two different O-PLS models (see Table 19.2), both sharing a common control group (DMSO). Each variable has then one coordinate from each model. This approach allows in particular the discrimination between endogenous potential biomarkers and drug metabolites, the latter being exactly packed on one axis in the upregulated direction (rectangles on both plots). The potential biomarkers of a common effect to both treatments are located along the first bisecting line of the plots (dotted line squares). When some variables have an opposite regulation (but still discriminative), they are positioned on the second bisecting line (hexagon, b).
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predictive loading component of one model. Each variable has then a coordinate from two models, and its position in the plot defines into which “group” of variables it may be classified. It can now be envisaged to separate drug metabolism in one group and endogenous biomarkers in the other group at the same time in a single data analysis step. 6. A first group of variables is made of simultaneously discriminative variables in two treatments, phenobarbital and rifampicin on the one hand (see dotted line red squares in Fig. 19.5a) and phenobarbital and CITCO (see dotted line red squares in Fig. 19.5b) on the other hand. Some of the variables are selected in both SUS plots. The 373 unique metabolites corresponding to these variables are likely to be endogenous biomarkers of a common effect between phenobarbital and one of the other treatments, either up or downregulated. They can be indicative of a common underlying mechanism (see Note 9). 7. The second group contains the variables specific to one of the treatments; the variables resulting from drug metabolites as well as endogenous metabolite biomarkers of the biological perturbations specifically induced or repressed by only one drug will be found in these groups. This is the case of the variables surrounded by yellow squares in Fig. 19.5; they are close to one axis because in one model they are not discriminative (see Note 10). 8. The upregulated variables exactly packed on one axis are good candidates for exogenous molecules; as they have a zero coordinate along the other axis, they are found only in one treated group and not found in the control group. The downregulated variables (close to the axes, on the left or at the bottom of the plot in Fig. 19.5) do not correspond to drug metabolites but to endogenous components specific of one treatment as they decrease in the treated group in comparison with the control one. 9. Among all of the variables common to rifampicin and phenobarbital (Fig. 19.5a; 154) or to CITCO and phenobarbital (Fig. 19.5b; 291), 50 downregulated and 32 upregulated variables were specific to rifampicin and phenobarbital treatments, whereas 99 downregulated and 120 upregulated variables were specific to CITCO and phenobarbital treatments (see the Venn diagram in Fig. 19.6). 10. Two new O-PLS analyses (rifampicin versus control on the one hand and CITCO versus control on the other hand) were then carried out on these 373 selected variables obtained from the two first SUS plots in order to validate
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Fig. 19.6. Venn diagram showing the selection (see dotted line squares in Fig. 19.5) of the 373 specific and common variables after treatment with phenobarbital, rifampicin, and CITCO. Among all of the variables common to rifampicin and phenobarbital (154) or to CITCO and phenobarbital (291), 50 downregulated and 32 upregulated variables were specific to rifampicin treatment, whereas 99 downregulated and 120 upregulated variables were specific to CITCO treatment.
the relevance of the selection. Those two O-PLS models were validated (data not shown), which permits the construction of the SUS plot (see Fig. 19.7). The strategy used for this subset selection guarantees the absence of exogenous metabolites. 11. A selection of 10 of the most discriminant variables between rifampicin and CITCO treatment is given in Table 19.3, with their relative variation against control. These variables, specific to only one treatment [and thus lying in the solid line rectangles in Fig. 19.7], can be used as fingerprints of a potential underlying mechanism of induction via a CAR and/or a PXR pathway. The endogenous metabolic profile measured after hepatocyte incubation with any new drug inducer could then be compared either to rifampicin or to CITCO-related variables and sorted according to CAR or PXR activation pathway (see Note 11).
3.5. Conclusion
The human hepatic primary culture (HHPC) has proven to be a very useful tool for in vitro induction studies. The UPLC–ToFMS-based metabolic profiling shows to be of great help to explore some of the underlying mechanisms involved in the induction process of reference inducers. However, care should be taken at each stage of the data analysis and the data processing in order to
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Fig. 19.7. SUS plot of rifampicin versus CITCO using the metabolite subset of 373 variables selected from Fig. 19.5. The strategy used for this selection guarantees the absence of exogenous metabolites. The solid line rectangles show the most specific (and endogenous) variables to rifampicin or CITCO treatment. These variables can be used as a fingerprint of the underlying mechanism of CAR and/or PXR activation pathway. A selection of 10 variables among them is given in Table 19.3.
Table 19.3 Ten of the most discriminant variables in the CITCO vs. rifampicin SUS plot (with 373 variables; see Fig. 19.7) m/z
r.t. (min)
304.286
7.07
294.146
Molecule
CITCO
Rifampicin
1
↓
↔
2.67
2
↓
↔
293.098
5.72
3
↓
↔
245.187
3.74
4
↓
↔
295.13
2.21
5
↔
↑
378.207
8.22
6
↑
↔
432.312
6.99
7
↔
↓
−448.308
7.01
8
↔
↓
414.303
7.02
9
↔
↓
433.316
6.4
10
↔
↓
m/z, mass charge ratio of the detected ions (negative value account for negative ionization mode); r.t., retention time. Arrows indicate the regulation against control.
optimize the data quality and to avoid confounding factors that could hamper data interpretation. This need to control every single step of an experimental design can be illustrated with the development of a new software
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to optimize peak detection from raw data as well as the inclusion of a dilution/filtration strategy to increase the data robustness. In addition, the use of new statistical and representation tools, such as SUS plot, has allowed the easy selection of a variable subset, free of exogenous metabolites. This profile has highlighted the differences between two inducers – rifampicin and CITCO – both of which share a (different) part of the inductive mechanism of the well-known inducer phenobarbital. Those differences could potentially be related to the specific activation of either PXR or CAR nuclear receptors. This profile can be readily used in order to classify a new compound based on its comparison with reference inducers. The identification effort on the most discriminant variables (biomarkers candidates) has to be completed, but already the described approach shows the power of metabonomics applied to in vitro cellular tools. It represents undoubtedly a complementary tool for a better understanding and validation of the possible CAR and PXR activation pathways in the induction processes.
4. Notes 1. This software was developed to improve data processing transparency and to use new features concerning especially peak detection. Other solutions are freely available (27). 2. Hepatic tissues from five different patients were available in this study, which is a minimum to account for the expected (and then observed) individual variations. Those variations are likely coming from normal genetic and epigenetic differences between patients and from the pathological stories of the hepatic samples. 3. The number of “dilution variable” samples (16) and of reference and blank samples could reach 33% of the whole sample list. It helped keeping steady chromatographic elution conditions and checking their steadiness afterward. 4. Many integration softwares have recently been developed to produce such tables from LC-MS data (27). However, the output of these softwares is very sensitive to the list of parameters obtained and can lead, for example, to a table with variables containing a lot of zeros. In order to circumvent this problem, we have developed the internal software “MassExplorer” based on a density map establishment from the raw data. The conversion from raw data to density map is done with a two-dimensional Gaussian curve
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that allows the smooth conversion between discrete and continuous data representation. 5. This operation removes all variables for which the MS intensity is not linked to the concentration of the samples. This is a major technical step that increases the data robustness. In addition, we can assess here the analytical quality which is linked to the variable fraction that is kept. The level of the correlation cutoff can be adapted in order to select signals with weaker linearity but monotonous relation between concentration and signal. The choice of this cutoff should be adjusted knowing that the lower the cutoff, the higher the risk of incorporating spurious signals and the higher the cutoff, the higher the risk of rejecting signals related to interesting metabolites. When applying this approach to hepatocyte extracts, one can illustrate the potential impact of such sorting strategy on the number of variables. Using a cutoff at 0.8, 14,233 variables were reduced to 3,381. When only the highest concentration gives a saturating signal or, on the contrary, the lowest concentration is below the detection limit, the correlation coefficient is not under 0.8 when using the dilution design presented here. The correlation distribution for the dilutions can also be used to assess the quality of the data acquired from the instrument and can thus provide information about the tuning and cleanness state of the mass spectrometer. The more the computed correlation distribution close to 1, the higher the data quality. 6. The principal cause of variability between samples is likely due to the genetic and/or the environmental background of the liver used to obtain the hepatocytes. We therefore cannot conclude on any effect of the different treatments if we consider only the two first principal components. 7. However, as the cells are treated with xenobiotics, the metabolites related to these compounds are detected and quantified simultaneously with endogenous metabolites. Hence, drug metabolites may produce a bias in the pattern recognition if not taken into account separately. This represents a major issue in metabonomic analysis because the statistical weight of drug metabolites being present only in the treated groups is far more important than most of the changes in endogenous metabolites observed with a treatment. 8. Metabolic profiles are effectively more difficult to interpret if we consider every treatment together in the same model because the output will be more focused on the specificity of one group versus all the others rather than the metabolic
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differences induced by one treatment. A pair-wise comparison between each treatment against control is therefore necessary. 9. Variables with high loading component values in each model are typically positioned on the first bisecting line of the plot, far from its center. This is the case of the variables surrounded by a dotted line red square in Fig. 19.5. If some variables have an opposite behavior (but still discriminative) in the two treatments, they will be positioned on the second bisecting line (pink hexagon in Fig. 19.5b). These variables are also common to both treatments but evolve in opposite directions against control group and can indicate the presence of different regulation pathways. 10. In the first place, we are not interested in further investigating those variables. Their study is out of the scope of this chapter. Indeed the initial biological question concerned common endogenous biomarkers between phenobarbital on the one side and rifampicin or CITCO on the other side. 11. In order to select variables that are specific to one treatment, one has to avoid the first bisecting line (the variables here are significant in both treatments) and the center of the plot. The (orange) solid line rectangles in Fig. 19.7 allow a selection of such 54 variables. References 1. Parmentier, Y., Bossant, M.-J., Bertrand, M., and Walther, B. (2007) In vitro studies of drug metabolism, Comprehensive Medicinal Chemistry II (Taylor, J.B. and Triggle, D.J. eds.), Elsevier, Amsterdam Netherland, pp. 231–257. 2. Handschin, C. and Meyer, U.A. (2003) Induction of drug metabolism: the role of nuclear receptors. Pharmacol. Rev. 55, 649–673. 3. Luo, G., Guenthner, T., Gan, L.S., and Humphreys, W.G. (2004) CYP3A4 induction by xenobiotics: biochemistry, experimental methods and impact on drug discovery and development. Curr. Drug Metab. 5, 483–505. 4. Tompkins, L.M. and Wallace, A.D. (2007) Mechanisms of cytochrome P450 induction. J. Biochem. Mol. Toxicol. 21, 176–181. 5. Konno, Y., Negishi, M., and Kodama, S. (2008) The roles of nuclear receptors CAR and PXR in hepatic energy metabolism. Drug. Metab. Pharmacokinet. 23, 8–13.
6. Maglich, J.M., Parks, D.J., Moore, L.B., Collins, J.L., Goodwin, B., Billin, A.N., Stoltz, C.A., Kliewer, S.A., Lambert, M.H., Willson, T.M., and Moore, J.T. (2003) Identification of a novel human constitutive androstane receptor (CAR) agonist and its use in the identification of CAR target genes. J. Biol. Chem. 278, 17277–17283. 7. Sueyoshi, T. and Negishi, M. (2001) Phenobarbital response elements of cytochrome P450 genes and nuclear receptors. Annu. Rev. Pharmacol. Toxicol. 41, 123–143. 8. Orans, J., Teotico, D.G., and Redinbo, M. (2005) The nuclear xenobiotic receptor pregnane X receptor: recent insights and new challenges. Mol. Endocrinol. 19, 2891–2900. 9. Pascussi, J.-M., Gerbal-Chaloin, S., Duret, C., Daujat-Chavanieu, M., Vilarem, M. J., and Maurel, P. (2008) The tangle of nuclear receptors that controls xenobiotic metabolism and transport: crosstalk and consequences. Annu. Rev. Pharmacol. Toxicol. 48, 1–32.
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10. Moreau, A., Vilarem, M.J., Maurel, P., and Pascussi, J.-M. (2008) Xenoreceptors CAR and PXR activation and consequences on lipid metabolism, glucose homeostasis, and inflammatory response. Mol. Pharm. 5, 35–41. 11. Nicholson, J.K., Lindon, J.C., and Holmes, E. (1999) ‘Metabonomics’: understanding the metabolic responses of living systems to pathophysiological stimuli via multivariate statistical analysis of biological NMR spectroscopic data. Xenobiotica 29, 1181–1189. 12. Bren, L. (2005) Metabolomics: working toward personalized medicine. FDA Consumer Magazine (November–December Issue) 39(6), 28–33. 13. Lindon, J.C., Holmes, E., and Nicolson, J.K. (2007) Metabonomics in pharmaceutical R&D. FEBS J. 274, 1140–1151. 14. Khoo, S.H. and Al-Rubeai, M. (2007) Metabolomics as a complementary tool in cell culture. Biotechnol. Appl. Biochem. 47, 71–84. 15. Isom, H.C. and Georgoff, I. (1984) Quantitative assay for albumin-producing liver cells after simian virus 40 transformation of rat hepatocytes maintained in chemically defined medium. PNAS 81, 6378–6382. 16. Brindle, J.T., Antti, H., Holmes, E., Tranter, G., Nicholson, J.K., Bethell, H.W., Clarke, S., Schofield, P.M., McKilligin, E., Mosedale, D.E., and Grainger, D.J. (2002) Rapid and noninvasive diagnosis of the presence and severity of coronary heart disease using 1HNMR-based metabonomics. Nat. Med. 8, 1439–1444. 17. Coen, M., Holmes, E., Lindon, J.C., and Nicholson J.K. (2008) NMR-based metabolic profiling and metabonomic approaches to problems in molecular toxicology. Chem. Res. Toxicol. 21, 9–27. 18. Gavaghan, C.L., Holmes, E., Lenz, E., Wilson, I.D., and Nicholson, J.K. (2000) An NMR-based metabonomic approach to investigate the biochemical consequences of genetic strain differences: application to the C57BL10J and Alpk:ApfCD mouse. FEBS Lett. 484, 169–174. 19. Fiehn, O., Kopka, J., Trethewey, R.N., and Willmitzer, L. (2000) Identification of uncommon plant metabolites based on calculation of elemental compositions using gas chromatography and quadrupole mass spectrometry. Anal. Chem. 72, 3573–3580.
20. O’Hagan, S., Dunn, W.B., Brown, M., Knowles, J.D., and Kell, D.B. (2005) Closed-loop, multiobjective optimization of analytical instrumentation: gas chromatography/time-of-flight mass spectrometry of the metabolomes of human serum and of yeast fermentations. Anal. Chem. 77, 290–303. 21. Shellie, R.A., Welthagen, W., Zrostlikova, J., Spranger, J., Ristow, M., Fiehn, O., and Zimmermann, R. (2005) Statistical methods for comparing comprehensive two-dimensional gas chromatography-time-of-flight mass spectrometry results: metabolomic analysis of mouse tissue extracts. J. Chromatogr. A 1086, 83–90. 22. Wilson, I.D., Nicholson, J.K., CastroPerez, J., Granger, J.H., Johnson, K.A., Smith, B.W., and Plumb, R.S. (2005) High resolution “ultra performance” liquid chromatography coupled to oa-TOF mass spectrometry as a tool for differential metabolic pathway profiling in functional genomic studies. J. Proteome Res. 4, 591–598. 23. Plumb, R.S., Rainville, P., Smith, B.W., Johnson, K.A., Castro-Perez, J., Wilson, I.D., and Nicholson, J.K. (2006) Generation of ultrahigh peak capacity LC separations via elevated temperatures and high linear mobile-phase velocities. Anal. Chem. 78, 7278–7283. 24. Want, E.J., Nordström, A., Morita, H., and Siuzdak, G. (2007) From exogenous to endogenous: the inevitable imprint of mass spectrometry in metabolomics. J. Proteome Res. 6, 459–468. 25. Wiklund, S., Johansson, E., Sjöström, L., Mellerowicz, E.J., Edlund, U., Shockcor, J.P., Gottfries, J., Moritz, T., and Trygg, J. (2008) Visualization of GC/TOF-MSbased metabolomics data for identification of biochemically interesting compounds using OPLS class models. Anal. Chem. 80, 115–122. 26. Pichard, L., Raulet, E., Fabre, G., Ferrini, J.B., Ourlin, J.C., and Maurel, P. (2006) Human hepatocyte culture. Methods Mol. Biol. 320, 283–293. 27. Katajamaa, M. and Oresic, M. (2007) Data processing for mass spectrometrybased metabolomics. J. Chromatogr. A 1158, 318–328.
Chapter 20 The Application of HepRG Cells in Evaluation of Cytochrome P450 Induction Properties of Drug Compounds Tommy B. Andersson Abstract The liver is the major organ metabolising drugs. The hepatocyte contains a number of drug-metabolising enzyme systems, which most often generate a complex pattern of drug metabolites. Isolated primary hepatocytes would be an ideal in vitro model for drug metabolism research but erratic availability and poor stability of functions in culture limit their value. Recently a hepatoma cell line HepaRG was developed showing promising functions and stability. In the differentiated stage the cell line showed stable expression of mRNA coding for key proteins in drug metabolism and liver-specific functions for over 6 weeks. The cell line was found to reflect important hepatic functions and has been evaluated as a convenient model for evaluating cytochrome P450 induction properties of drug compounds. HepaRG cells could therefore be an alternative to human hepatocytes in investigating drug metabolism and induction of drug-metabolising enzymes. Key words: CYP induction, human hepatocytes, hepatoma cell line, CYP1A2, CYP2B6, CYP3A4, drug metabolism, drug interactions.
1. Introduction The liver is a major organ determining the metabolic profile of drugs. Detailed studies of the metabolism of a drug compound in vitro often employ primary human hepatocytes as model systems. Primary human hepatocytes have, however, wellknown limitations such as erratic availability and variable quality. Another serious shortcoming when using primary liver cells is the loss of important hepatocyte characteristics in culture. Drugmetabolising enzyme activities in hepatocyte cell suspensions and cultures decrease rapidly, which limit the experimental period P. Maurel (ed.), Hepatocytes, Methods in Molecular Biology 640, DOI 10.1007/978-1-60761-688-7_20, © Springer Science+Business Media, LLC 2010
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considerably. Many of the new chemical entities developed in the pharmaceutical industry are slowly metabolised and therefore need long incubation times in the cell system. The metabolic turnover and the metabolite pattern identified in primary hepatocytes may in these cases not reflect a normal liver. A major step forward is the recent development of a human hepatoma cell line, HepaRG (1). The cells are differentiated after treatment with 2% DMSO. Two cell types appear. One resembles hepatocytes and another biliary canaliculi-like structures. After detachment both structures can trans-differentiate into progenitor cells, which are able to differentiate again (2). Differentiated cells express the major cytochrome P450 (CYP), drug-conjugating enzymes and nuclear receptors as well as other liver-specific functions at levels close to those found in primary hepatoytes (3, 4). HepaRG cells also show stable expression of drug-metabolising enzymes, transporter proteins and transcription factors over a period of at least 6 weeks when cultured in 2% DMSO (4). The level of CYP activities generally decreases when DMSO is removed from the medium but the relative content of drug-metabolising enzymes in HepaRG cells displays the highest resemblance with fresh human primary hepatocytes 1 day after removal of DMSO from the medium. The HepaRG cells are proven to be an excellent in vitro CYP induction model (5). Prototypical inducers of the major CYP enzymes show expected results and the degree of induction of CYP3A4 in vivo by drugs could be well predicted by investigating induction in the HepaRG cell line. Here a method to investigate CYP1A2, CYP2B6 and CYP3A4 induction by using cocktail incubations for activity assays and real-time PCR for mRNA detection is presented (see also Chapters 1 and 13).
2. Materials 2.1. Cell Culture
1. Low DMSO medium (after-shipment medium), high DMSO medium, enriched medium, basal HepaRG Medium (BHM) (Biopredic International, Rennes, France, www.biopredic.com). 2. D-PBS (1X) without CaCl2 and MgCl2 (Gibco Invitrogen Paisley, UK). 3. Hepatocyte suspension medium (HSM): 482.5 mL William’s medium E with NaHCO3 , without phenol red, without L-glutamine (Sigma-Aldrich, St Louis, USA), 12.5 mL 1 M N-2-hydroxyethyl-piperazine-N-2ethanesulphonic acid (HEPES) final concentration 25 mM
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(Gibco Invitrogen), 5 mL L-glutamine final concentration 2 mM (Gibco Invitrogen), adjust pH to 7.4 at room temperature. 4. Differentiated HepaRG cells seeded in plates (Biopredic International). The cells are differentiated before shipment. The cells can be purchased in different plate formats. The use of 96-well plates for studies of cytochrome P450 enzymes by drug compounds is described. 5. At arrival the transport medium is removed and fresh low DMSO containing HepaRG medium is added (100 μL/well). 6. The cells are recovered for 24 h before the medium is changed to high DMSO HepaRG medium. 7. The medium is renewed every second day for 6 days. 8. Before the induction experiment starts the high DMSO medium is replaced with “enriched medium” (100 μL/well). The induction experiment can start 3–5 days later. Cells are cultured in an incubator at 37◦ C in an atmosphere of 95% air and 5% CO2 . 2.2. mRNA Measurements
R 1. TRIzol Reagent (Gibco Invitrogen).
2. TE buffer 20X, RNase-free, 200 mM Tris-HCl, 20-mM EDTA pH 7.5 (Molecular Probes Invitrogen:Eugene, Oregon, USA). 3. SuperScript III First-Strand Synthesis System for RT-PCR (Invitrogen, Stockholm, Sweden). R 4. Primers and probes, TaqMan Gene Expression Assays, R TaqMan Universal Master Mix., nucleic acid purification lyses solution, RNA purification washes solution 1 and 2, absolute RNA wash solution, nucleic acid purification elution solution, RNA purification trays, 7500 Sequence Detector, Micro AmpTM optical adhesive film (PCR compatible, DNA/RNase free) (Applied Biosystems, www.appliedbiosystems.com).
5. NanoDrop (Saveen Werner AB, Limhamn, Sweden). 6. Acetonitrile HPLC grade and isopropyl alcohol (Rathburn Chemicals Ltd., Scotland). 7. Formic acid (Merck, Germany). 8. Chloroform reagent grade (Scharlau Chemie S.A, Barcelona, Spain). 2.3. CYP Enzyme Activities
1. Paracetamol Sigma-Aldrich (St Louis, USA). 2. Sodium dodecyl sulphate (SDS) (Biochemical BDH Chemicals Ltd Poole, England).
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3. Hydroxybupropion (Toronto Research Chemicals North York, Canada). 4. 1 -Hydroxymidazolam (Ultrafine UFC Limited, Manchester, UK). 5. Phenacetin (Sigma-Aldrich). 6. The internal standards: paracetamol-D4: Molecular weight 155.2, and 1 -1 -hydroxymidazolam-13 C3: Molecular weight 344.7 (Toronto Research Chemicals Inc.), hydroxybupropion-D6: Molecular weight 261.8 (Becton Dickinson). 7. Prepare stock solutions of probe substrates in methanol. The stock solution concentrations are phenacetin 26 mM, bupropion 100 mM and midazolam 3 mM. 8. Add 30 μL of each stock solution in a 50 mL test tube and evaporate under a stream of nitrogen. Dissolve the evaporated compounds in 30 mL HSM that will give final concentrations of phenacetin, bupropion and midazolam of 26, 100 and 3 μM, respectively. 9. For the standard curve, the three metabolites are dissolved in William’s medium E containing 13% acetonitrile. The concentrations of paracetamol, 1-OH midazolam and hydroxybupropion are 7.00, 2.00 and 1 μM, respectively. 10. Dilute the standards step wise five times in increments of three to get samples for a full standard curve. 11. The internal standards are prepared as a pool in William’s medium E. Suitable concentrations are paracetamolD4, 1 μM; hydroxybupropion-D6, 500 nM and 1 -hydroxymidazolam-13 C3, 1 μM. The internal standard mix (25 μL) is added to 200 μL sample or 200 μL of the standard curve samples. 12. Inducers, omeprazole (AstraZeneca R&D Mölndal) and rifampicin (Sigma Chemical Co. St. Louis, MO, USA), are dissolved in DMSO and diluted in BHM before addition to the HepaRG cells. 13. Prepare stock solutions of inducers in DMSO at a 1,000fold higher concentration than the highest concentration used in the cell culture. 14. Make a serial dilution of the stock solution in DMSO for all concentrations to be tested. For a dose–response curve ideally threefold dilution in every step may be applied. The stock solution is diluted 1,000-fold in BHM in two steps: a. 10 μL stock solution +190 μL BHM. b. 30 μL sample from (a) and add 1,470 μL BHM. 15. Use 100 μL/well of the diluted sample.
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16. Final concentration of DMSO in the HepaRG cell incubation is 0.1% for all inducer concentrations. 17. Prepare control incubation medium by adding DMSO (0.1% final concentration) to BHM. 2.4. Analytical Equipment
Suitable instruments are exemplified below. Other equivalent instruments can be used. 1. LC-pump: 2 LC-20AD pumps (Shimadzu, Japan). 2. Auto sampler with a thermostated sample compartment: SIL-HTc Auto Sampler (Shimadzu, Japan). The temperature of the sample compartment is set to 15◦ C. 3. Degasser: DGU-20A3 (Shimadzu, Japan). 4. Detector: triple-quadrupole mass spectrometer with turboionspray interface (Sciex API 4000). 5. Column: HyPURITY C18, 5 μm, separation column, 50×2.1 mm (Thermo Hypersil-Keystone, MA, USA). 6. 7500 Sequence detector and software v1.3.1 (Applied Biosystems).
3. Methods 3.1. Exposure of HepaRG Cells to Inducers
1. For the activity measurements each compound and concentration may be run in duplicate or triplicate. For the mRNA measurements two wells are pooled to get enough material, which means four wells per compound and concentration to get duplicate. Separate wells in the experiment can be used for protein determination. The protein content not only is used to understand the variation in cell content between the wells but can also be used to calculate specific enzyme activity based on total protein. Since the activity assay is designed to extract all metabolites from the incubation protein cannot be measured in the same well. Instead a mean value of protein content in each plate can be used. Alternatively the enzyme activity is calculated as activity per well. 2. Positive control inducer for each CYP form should be run in parallel with test compounds. Omeprazole for CYP1A2, phenobarbital or rifampicin for CYP2B6 and CYP3A4 can be used. Dose–response curves for the positive controls or a single top dose can be run. For omeprazole and rifampicin the highest dose needed is 40 and 20 μM, respectively. 3. Prewarm the induction medium at 37◦ C.
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4. Remove the enriched medium from the cells and add the prewarmed induction medium (BHM plus inducer), 100 μL/well. Control incubations contain basal HepaRG medium supplemented with 0.1% DMSO. Induction is performed at 37◦ C in an atmosphere of 95% air and 5% CO2 . For mRNA analysis and for CYP activity measurements exposure time to the potential inducers is 24 and 48 h, respectively. 5. After 24 h incubation of HepaRG cells to potential inducers wells for mRNA quantification are terminated: follow the protocol described in Section 3.2; the wells for CYP activity measurement should be incubated for another 24 h but the medium should be changed. 6. After 48 h exposure wells used for CYP activity are treated as described in Section 3.3. 3.2. Real-Time PCR
1. Remove the medium (see Note 1). R to each well. 2. Lyse the cells by adding 100 μL TRIzol
3.2.1. RNA Extraction, 96-Well Plates
3. Incubate for 5 min and then pipette up and down 5–10 times. 4. Pool the cell lysate from two wells to a 0.5 mL Eppendorf tube (see Note 2). 5. Add 40 μL chloroform (0.2 mL chloroform/mL R TRIzol ) and shake vigorously for 15 s. 6. Centrifuge the tubes for 15 min at 12,000×g, 4◦ C. 7. Pipette 60 μL of the upper layer to a new tube and add 100 μl isopropyl alcohol (0.5 mL isopropyl alcohol/mL R TRIzol ). Shake the tube by hand. 8. The RNA is precipitated. The tubes can be put into −20◦ C freezer to increase the yield of RNA) (see Note 2). 9. Centrifuge the tubes for 10 min, 12,000×g 4◦ C (see Note 3). 10. Remove the supernatant carefully with a pipette. Change tip between every sample. 11. Wash the pellet with 200 μL, 75% ethanol (1 mL R EtOH/mL TRIzol ). Shake the samples vigorously. 12. Centrifuge the tubes for 5 min, 7,500×g, 4◦ C and remove the supernatant (see Note 4). 13. Evaporate the solvent carefully from the pellet for 15–30 min on the lab bench (see Note 5). 14. Dissolve the pellet in 5 μL RNase-free water and incubate at 55–60◦ C for 10 min.
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15. Use 0.5 + 9.5 μL TE buffer for measuring the RNA concentration. Quantity and purity of the RNA is determined spectrophotometrically using a NanoDrop. Values above 2 for the ratios 260/280 and 260/230 are set as a quality criterion to proceed to cDNA synthesis. 3.2.2. cDNA Preparation and Real-Time PCR
1. Prepare cDNA from 0.5 μg of total RNA using 1.5 times the normal reaction volume in the SuperScriptTM III FirstStrand Synthesis System for RT-PCR with random hexamer primers according to the manufacturer’s protocol. 2. Run real-time PCR in a 7500 Sequence Detector, using R manufacturer designed TaqMan gene expression assays for human CYP1A2, CYP2B6, CYP3A4 and endogenous control (e.g. glyceraldehyde-3 phosphate dehydrogenase (GAPDH) or H36B4). 3. Dilute the cDNA sample 31.5 μL with 99.8 μL RNase-free water. 4. Prepare the following reaction mixture per gene multiplied by the number of samples that will be analysed +2 for losses during pipetting. For one sample the mixture contains 12.5 μL 2XTaqman Universal Master Mix, 1.25 μL manufacturer designed primer and probe mixture and add RNase-free water up to a volume of 20 μL. 5. Add to each PCR plate well 20 μL of the reaction mixture from 4 to 5 μL of the diluted cDNA from 3. 6. The same thermal cycle conditions are used for all genes analysed. The Initial steps of 50◦ C for 2 min followed by a 10 min step at 95◦ C and then 40 PCR cycles of 95◦ C for 15 s and 60◦ C for 1 min. 7. Each sample is analysed in triplicate and data are analysed using the 7500 Sequence detector software v1.3.1. GAPDH is used as endogenous control and the amount of mRNA is determined relative to that of control samples. 8. Figure 20.1 depicts real-time PCR analysis in a 7500 Sequence Detector of control cells and cells induced by rifampicin or omeprazole. The values used for calculations are the cycle number in the exponential phase of the curve called the Ct (cycle number threshold) value which can be set automatically by the instrument or chosen manually. 9. The induction response is calculated from the Ct values obtained from the real-time PCR by the following calculations: (a) Normalisation of the Ct value: Ct value of the target gene − Ct value of the endogenous control = Ct.
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Control HepaRG (0.1 % DMSO)
2B6
1A2
3A4 Ct = 29
Ct = 36.1
Induced HepaRg Rif,3A4 Ct = 20
Rif 2B6 Ct = 26
Ome 1A2
Ct = 29.7
R Fig. 20.1. TacMan analysis of CYP1A2, CYP2B6 and CYP3A4 mRNA in control cells and cells induced with rifampicin 20 μM (rif) or omeprazole (40 μM). Each sample is run in triplicate. The Ct values used for calculations are indicated in the figure.
(b) Subtract the Ct value from the cells exposed to potential inducer from the control sample. The value obtained is called Ct. Use the formula 2−Ct that will give the fold induction. 10. Figure 20.2 depicts mRNA dose–response curves for CYP1A2, CYP2B6 and CYP3A4 induction by omeprazole (CYP1A2) or rifampicin (CYP2B6 and CYP3A4).
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b
24 22 20 18 16 14 12 10 8 6 4
CYP1A2
22
CYP2B6
18 Fold induction
Fold induction
a
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14 10 6 2
1
1
10 Omeprazole (µM)
c
Rifampicin (µM)
10
260 240
CYP3A4
Fold induction
220 200 180 160 140 120 100 80 1
10 Rifampicin (µM)
Fig. 20.2. Dose–response curves for mRNA levels in HepaRG cells treated with model inducers omeprazole or rifampicin. (A) CYP1A2; (B) CYP2B6; (C) CYP3A4. The dotted line indicates twofold increase of mRNA levels over the baseline (F2 values).
The induction potency can be assessed by calculating the concentration which increases the mRNA to 50% of maximum induction (EC50 ) or if a maximum is not reached the concentration which increases the mRNA level twofold over baseline (F2) as depicted in Fig. 20.2 can be applied (5). 3.3. Activity Assay
1. After 48 h incubation of HepaRG cells with the investigated potential CYP inducer the cells are washed carefully twice with 100 μL prewarmed HSM. 2. Add 50 μL prewarmed HSM containing the substrate cocktail. Incubate for 60 min at 37◦ C in an atmosphere of 95% air and 5% CO2 . 3. At 60 min, transfer the incubation medium to a 96-deep well plate. Seal the plate with “adhesive PCR film” and place the plate in the fridge. 4. Quickly add 50 μL ice-cold lysing solution (acetonitrile with 0.8% formic acid) to each well in the incubation plate. Seal the plate with “adhesive PCR film”, place the plate in −20◦ C
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for about 30 min and thaw it in room temperature for about 10 min. To completely lyse the cells the freezing–thawing cycles should be repeated twice. 5. Combine the cell lysate (50 μL) with the corresponding medium transferred to the 96-deep well plate (Note 6). 6. Centrifuge the plate 20 min, 4,000 rpm at 4◦ C. 7. For analysis take 52 μL of the supernatant, add 148 μL H2 O and 25 μL pooled IS. The final concentration of acetonitrile should be 13%.
Table 20.1 LC gradient. The LC gradient for separation of the CYP-specific metabolites Gradient
Time (min)
%B
0.0
2
0.8
2
3.1
40
3.5
98
4.0
98
4.1
2
5.0
2
8.2e5 8.0e5 7.5e5 7.0e5 6.5e5 6.0e5
Intensity, cps
5.5e5 5.0e5 4.5e5 4.0e5 3.5e5 3.0e5 2.5e5 2.0e5 1.5e5 1.0e5 5.0e4 0.0
0.5
1.0
1.5
2.0
2.5 Time, min
3.0
3.5
4.0
4.5
Fig. 20.3. Chromatogram of paracetamol (tR 0.63), hydroxybupropion (tR 2.22), 1 -hydroxymidazolam (tR 2.85) in extracts from a HepaRG cell incubation.
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8. For protein determinations add 50 μL 0.2 M NaOH to each well. Seal the plate with “adhesive PCR film” and put the plate in −20◦ C for 30 min. Repeat thawing–freezing cycles as in Step 4 and determine protein concentration using standard methods. 3.4. Chromatographic Method
The substrate metabolites paracetamol, hydroxybupropion, 1 -hydroxymidazolam and their, respectively, isotope-labelled internal standard are injected onto a liquid chromatography column. Injection volume is 5 μL. The compounds are separated by reversed-phase liquid chromatography and measured by atmospheric pressure positive ionisation mass spectrometry. Ambient column temperature is used: Mobile phase A: 50 mL acetonitrile, 1.0 mL formic acid and 950 mL water are mixed. Mobile phase B: 950 mL acetonitrile, 1.0 mL formic acid and 50 mL water are mixed.The mobile
700 650 600 550 500 450 400 350 300 250 200 150 100
b
CYP1A2 Paracetamol formation
280 260
CYP2B6 Hydroxybupropion formation
240 % of control
% of control
a
220 200 180 160 140 120 100 0.1
1 10 Omeprazole (µM)
c
1 Rifampicin (µM)
10
280 260
CYP3A4 1'-hydroxymidazolam formation
% of control
240 220 200 180 160 140 120 100 0.1
1 Rifampicin (µM)
10
Fig. 20.4. Dose–response curves for CYP activities (metabolite formation) in HepaRG cells treated with model inducers omeprazole or rifampicin. a paracetamol (the metabolite of phenacetin) formation in omperazole-treated cells; b hydroxybupropion formation in rifampicin-treated cells; c 1 -hydroxymidazolam formations in rifampicin-treated cells.
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phases might have to be modified slightly to give a suitable retention time. A flow rate of 0.750 μL/min gives a retention time of about 0.63, 2.20 and 2.82 for paracetamol, hydroxybupropion and 1 hydroxymidazolam, respectively. The LC gradient is described in Table 20.1. The gradient may slightly be modified to give suitable retention times. A chromatogram showing the three metabolites is depicted in Fig. 20.3. 3.5. Calculation of Enzyme Activities
The activities could be reported as total amount of metabolites formed per well or be related to the protein concentration in the wells. Figure 20.4 illustrates a representative induction experiment where HepaRG cells have been induced by omeprazole or rifampicin and the model substrates for CYP1A2, CYP2B6 and CYP3A4 have been measured. The induction response is calculated as the percentage increase in metabolites formed in wells exposed to an inducer as when compared with the amount of metabolites in the control wells.
4. Notes 1. Always use gloves to prevent RNase contamination. 2. At this stage the cells can be frozen at −80◦ C. 3. Important to mark the tubes to localise the pellet, which is difficult to see by eye after centrifugation. 4. Change tips between every sample. 5. It is important that all solvent is evaporated. The absorbance 260/230 below 1.8 indicates a solvent contamination of the sample. 6. Protect the cell plate carefully from evaporation during the transfer step!
Acknowledgements The author would like to thank Kajsa P. Kanebratt, who made a major contribution for the development of the induction model. Katarina Rubin, Annika Janefeldt, Malin Darnell and Malin Forsgard are acknowledged for technical contributions.
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References 1. Gripon, P., Rumin, S., Urban, S., Le Seyec, J., Glaise, D. et al. (2002) Infection of a human hepatoma cell line by hepatitis B virus. Proc. Natl. Acad. Sci. USA 99, 15655–15660. 2. Cerec, V., Glaise, D., Morsna, S. Turlin, B. Drenou, B. et al. (2007) Transdifferentiation of hepatocyte-like cells from the human hepatoma HepaRG cell line through bipotent progenitor. Hepatology 45, 957–967. 3. Aninant, C., Piton, A., Glaise, D., Le Charpentier, T., Langouet, S. et al. (2006)
Expression of cytochromes P450, conjugating enzymes and their nuclear receptors in human hepatoma HepaRG cells. Drug Metab. Dispos. 34, 75–83. 4. Kanebratt, K.P. and Andersson, T.B. (2008a) Evaluation of HepaRG cells as an in vitro model for human drug metabolism studies. Drug Metab. Dispos. 36, 1444–1452. 5. Kanebratt, K.P. and Andersson, T.B. (2008b) HepaRG cells as an in vitro model for evaluation of cytochrome P450 induction in humans. Drug Metab. Dispos. 36, 137–145.
Chapter 21 The Use of Hepatocytes to Investigate Drug Toxicity María José Gómez-Lechón, José V. Castell, and María Teresa Donato Abstract The liver is very active in metabolizing foreign compounds and the major target for toxicity caused by drugs. Hepatotoxicity may be the result of the drug itself or, more frequently, a result of the bioactivation process and the production of reactive metabolites. Prioritization of compounds based on human hepatotoxicity potential is currently a key unmet need in drug discovery, as it can become a major problem for several lead compounds in later stages of the drug discovery pipeline. Therefore, evaluation of potential hepatotoxicity represents a critical step in the development of new drugs. Cultured hepatocytes are increasingly used by the pharmaceutical industry for the screening of hepatotoxic potential of new molecules. Hepatocytes in culture retain hepatic key functions and constitute a valuable tool to identify chemically induced cellular damage. Their use has notably contributed to the understanding of mechanisms responsible for hepatotoxicity (disruption of cellular energy status, alteration of Ca2+ homeostasis, inhibition of transport systems, metabolic activation, oxidative stress, covalent binding, etc.). Assessment of current cytotoxicity and hepatic-specific biochemical effects is limited by the inability to measure a wide spectrum of potential mechanistic changes involved in the drug-induced toxic injury. A convenient selection of endpoints allows a multiparametric evaluation of drug toxicity. In this regard, cytomic, proteomic, toxicogenomic and metabonomic approaches help to define patterns of hepatotoxicity for early identification of potential adverse effects of the drug to the liver. Key words: Hepatocytes, mechanisms of hepatotoxicity, cytotoxicity, metabonomics, toxicogenomics, proteomics, cytomics, cytochrome P450.
1. Introduction The liver is a major target of toxic effects of drugs. This vulnerability is a consequence of the unique vascular, secretory, synthetic and functional features of the liver and their role in the metabolic elimination of most drugs (1). The poor prognosis and idiosyncratic nature of some cases of drug-induced liver injury (DILI) make this type of reaction a major safety issue during P. Maurel (ed.), Hepatocytes, Methods in Molecular Biology 640, DOI 10.1007/978-1-60761-688-7_21, © Springer Science+Business Media, LLC 2010
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drug development, as well as the most common cause for the withdrawal of approved drugs from the pharmaceutical market (2). Understanding the molecular and cellular underlying mechanisms associated with DILI can help identify risk factors and may ultimately facilitate the development of strategies to predict and prevent DILI (3–5). Many of the drugs that cause DILI in human beings do not produce overt signs of significant liver damage during preclinical safety testing in experimental animals. Consequently, conventional safety studies in preclinical species are of limited value for prediction and management of DILI in man. To deal with these challenges, the establishment of in vitro screening systems reflecting human in vivo toxicity is demanded for earlier safety assessment. Cellular models from a human origin constitute valuable tools to understand the molecular and cellular processes of druginduced liver injury (DILI). This understanding can be used to influence drug design and selection with the least possible potential to initiate liver injury and to manage these candidates through clinical development. Current cytotoxicity assessments have been limited by their inability to measure multiple, mechanistic parameters that capture a wide spectrum of potential cytopathological changes. Cytotoxicity tests (MTT, XTT, Neutral Red, Alamar Blue, etc.) represent a first approach to assess cytotoxicity, but evaluation of these parameters alone may leave out of consideration xenobiotics that impair cell function without causing cell death. By examining the effects on hepatocyte-specific metabolism (i.e. gluconeogenesis, ureogenesis, plasma protein synthesis, GSH, NADH and ATP levels), it is possible to find out whether relevant hepaticspecific functions become altered by the presence of a xenobiotic (6). Multiparametric live cell approaches including evaluation of relevant metabolic functions are more predictive because they cover a wider spectrum of mechanistic effects. Recent technological advances in the fields of genomics, proteomics, cytomics and metabonomics are playing a very important role in uncovering novel biochemical pathways and biomarkers of hepatotoxicity (7, 8). The application of these novel disciplines to hepatotoxicity screening allows multiparametric analysis in the same cell preparations. The potential power of these methodologies will contribute to develop robust high-throughput reliable hepatic in vitro screening protocols and to heighten predictive capacity for human hepatotoxicity.
2. Hepatotoxins Substances capable of producing liver damage and, more specifically, hepatocyte damage are known as hepatotoxins. Intrinsic
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hepatotoxins are substances that exert their effects in all individuals, in a dose-dependent and hence predictable manner. DILI can be initiated by a direct interference of the drug itself on cell structures or functions or can be due to metabolites generated by biotransformation pathways (bioactivation) (3, 9–13). Many cases of drug hepatotoxicity are related to idiosyncratic reactions. Idiosyncratic hepatotoxicity has a geno- or phenotypic basis that results in the over/under expression of drug-metabolizing enzymes (i.e. genetic polymorphisms, altered enzyme pattern) that renders an unusual drug metabolism (different drug metabolism pattern, eventually abnormal production of a toxic metabolite) (metabolic idiosyncrasy). This altered metabolism can produce dose-dependent toxicity in susceptible individuals as a result of accumulation of toxic metabolites and an alteration of cell biochemical processes (10, 14). Idiosyncratic hepatotoxicity can also be elicited by an immune-mediated hepatocyte injury (allergic hepatitis) (12, 15).
3. Mechanisms of Hepatotoxicity The liver is very active in metabolizing foreign compounds and is often the primary site of exposure to these toxins. The hepatic biotransformation of xenobiotics enables the elimination of lipophilic substances that otherwise might accumulate in tissues, thereby causing toxic effects (9, 16). This process involves chemical modifications of the molecules mostly through redox reactions catalysed by cytochrome P-450 (P450) or flavin monooxygenase enzymes (phase I reactions). The result is the formation of new metabolites which are more polar and can be directly excreted or undergo further conjugation with endogenous molecules (glutathione, glucuronate or sulphate) in the phase II reactions. The conjugates are much more soluble thus facilitating the elimination in urine or bile of lipophilic substances. Although the presumable physiological role of biotransformation is to act as a self-defence mechanism, drugs can undergo bioactivation to toxic metabolites that can interfere with cellular functions and may have intrinsic reactivity towards certain cellular macromolecules (9, 17). The most widely recognized mechanism of metabolic bioactivation involves oxidative conversion of non-polar substances to electrophilic intermediates, free radicals or active oxygen species by P450 system promoting a variety of chemical reactions (covalent binding, oxidative stress, lipid peroxidation, alteration of Ca2+ homeostasis and mitochondrial injury) leading to hepatocyte injury (12, 17, 18). The propensity of a molecule to form toxic metabolites in phase I reactions depends on its chemical structure (9). Bioactivation of drugs
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by some phase II metabolites (i.e. acyl-glucuronides and acylCoA thioesters) also deserves mention (19). The conjugates of carboxylic acid drugs have been studied intensely since several NSAIDs, most of which are carboxylic acids, have been associated with hepatotoxicity (3, 20, 21). Several studies have shown that both acyl-glucuronides and acyl-CoAs are able to transacylate GSH and proteins (22, 23), hence it is very likely that these metabolites may play a role in the observed adverse reactions. Consequently, although drug biotransformation generally parallels a detoxication process, bioactivation is the most frequent cause of hepatocyte injury (16, 18). However, it is possible for chemicals to undergo bioactivation in the liver without causing hepatotoxicity. Ultimately it is the balance between bioactivation, detoxification and defence/repair mechanisms that determines whether a compound will or will not elicit a toxic effect. There are several processes known to play a role in the molecular events leading to drug-induced irreversible cell damage and death by apoptosis or/and necrosis (3, 11, 24, 25). Figure 21.1 summarizes the major mechanisms that can be involved in hepatocyte toxicity. Biotransformation involving high-energy reactions can result in the formation of intermediates capable of binding covalently to cell macromolecules to form stable adducts. Unsaturated carbonyl compounds, aldehydes, epoxides, glucuronides and sulphate conjugates are among the most frequently involved reactive groups, while proteins, DNA and RNA are the most frequent targets. Covalent modification of relevant critical target proteins (mitochondrial, endoplasmic reticulum, cytosolic proteins, transporters, receptors) is associated
Phase I/II
Inactive metabolites
Excretion Ph ase II
Bioa
Reactive metabolites
DNA
Proteins
Neoantigens
Immunotoxicity
Enzymes Transporters Receptors
Cytotoxicity Cholestasis
Red-ox cycling
Interaction with O2
Covalent binding
DNA damage
Genotoxicity
Drug
tion ctiva
Oxidative stress ( GSH)
Reactive oxygen species (ROS)
Mitochondrial injury
Lipid peroxidation
Alteration Ca+2 homeostasis
Cytotoxicity Apoptosis
Fig. 21.1. Molecular events leading to drug-induced irreversible cell damage and death by apoptosis or/and necrosis.
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with the toxicity of many electrophiles (1, 26–28). Reactive intermediates are capable of forming DNA adducts also and finally inducing genotoxicity (29). Binding to lipids leads to a degradation of membrane lipids by the radical chain reaction so-called lipid peroxidation (11, 16). The mitochondrion is a frequent major target of DILI and the alteration of its function has immediate effects on the energetic balance of cells (3, 30). Necrosis is typically the consequence of acute metabolic perturbation with ATP depletion. Hepatocytes are highly reliant on ATP for ureogenesis, gluconeogenesis and fatty acid metabolism among many other processes. Depletion of ATP is an early event in the course of drug-induced toxicity that precedes the irreversible stages of several modes of cell injury (31). Oxidative stress is imposed on cells when the generation of radical oxygen species exceeds the antioxidant protection of cells and is produced by compounds capable of undergoing repeated redox cycles or by molecules containing oxygen atoms that can either produce free radicals causing depletion of GSH. When GSH is depleted, cellular malfunction and death can be promoted. All of these chemical reactions have direct effects on organelles such as the mitochondria, the endoplasmic reticulum, the cytoskeleton, the microtubules or the nucleus or indirect through the activation or inhibition of signalling kinases, enzymes, transcription factors and gene expression profiles. Finally, cells may die by necrosis and/or apoptosis to an extent sufficient to result in compromised organ functioning or loss of homeostasis and, then, in toxic response (6, 16, 32). The development and progression of significant liver dysfunction is a multistep process, which involves initial chemical insult followed by biological response (2, 3). The balance between protective responses and responses that result in propagation and amplification of tissue injury and also individual susceptibility factors determines whether or not toxicity arises (2). In man, the most frequent clinical patterns of liver injury are hepatocellular (affecting hepatocytes), cholestatic (affecting the biliary system) and mixed hepatocellular/cholestatic (3). This indicates that it is especially important to focus on processes involved in the initiation and/or progression of injury affecting hepatocytes and also to consider bile formation and bile flow. Mitochondrial dysfunction could be a major mechanism of DILI. Microvesicular steatosis is the consequence of severe impairment of mitochondrial β-oxidation and is indicative of mitochondrial dysfunction, whereas cholestasis is likely related to impairment of bile production or secretion. Centrilobular necrosis is often attributed to the formation of reactive metabolites, consistent with findings of higher P450 enzyme activities and lower GSH concentration in that region.
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4. Hepatocytes: A Tool for Drug Toxicity Evaluation
Compound prioritization and optimization are critical tasks in drug development. Knowledge about metabolism, disposition, bioactivation, interaction with molecular processes and cell structures and functions of a particular compound could allow predictions of the type of liver damage it is likely to cause. The study of potential hepatotoxins would greatly benefit from having reliable experimental models capable of reproducing the phenomena that may take place in the human liver. Among cellular systems used for hepatotoxicity studies, primary hepatocytes are the closest to human liver in vivo (6, 19). Hepatocytes cultured under chemically defined conditions are differentiated cells expressing typical liver-specific functions and capable of reproducing in vitro the response of the liver to pathophysiological factors. Cultured hepatocytes efficiently synthesized glucose from lactate and other physiological gluconeogenic substrates, maintain intracellular glycogen storage similarly to that reported for fed human liver and synthesize and accumulate glycogen in previously depleted cells (33). Hepatocytes respond to hormonal stimulation (i.e. glucagon, insulin) and have been used to investigate regulatory mechanisms of carbohydrate metabolism in human liver (33–35). Similarly, plasma protein synthesis and secretion, urea production, lipid metabolism and transport, bile acids synthesis and canalicular transport have been extensively studied in hepatocytes. Moreover, human hepatocytes retain the entire hepatic drug-metabolizng enzyme equipment (phase I and phase II) in an integrated, functional and inducible form (19, 36, 37). All these features have notably contributed to recognized primary hepatocytes as a valuable tool for anticipating potential risk of drug-induced hepatotoxicity in man. They are widely used to screen cytotoxic and genotoxic compounds, to characterize the nature of the induced lesions, to identify the mechanisms involved in toxic insult and to determine the potential role of biotransformation pathways (detoxification, bioactivation) in drug hepatotoxicity. The restricted accessibility of human liver samples has greatly hindered the widespread use of human hepatocytes for hepatotoxicity studies. However, recent advances in hepatocyte cryopreservation protocols have notably contributed to increase their availability for screening purposes (38, 39). Another limitation of cultured hepatocytes is their relative phenotypic instability. A continuous and early decline in metabolic and functional capacity of hepatocytes is observed during culture, probably as a consequence of liver cell disaggregation with collagenase that could trigger a dedifferentiation process as well as hepatocyte adaptation to a new
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culture microenvironment which differs from that of liver in vivo (6, 40). Liver-enriched transcription factors are promptly downregulated and an altered expression pattern of specific hepatic genes involved in cellular processes (drug metabolism, basolateral and canalicular transport systems, fatty acid and lipid metabolism, apoptosis and proteasomal protein recycling) has been observed (40, 41). Changes in cell shape, alterations in cell architecture and loss of cell–cell interactions have been related to altered hepatocyte functionality (42). Different strategies have been attempted to preserve cell morphology and to control the loss of key metabolic activities. Modifications of medium composition (growth factors, hormones), cell density, extracellular matrix proteins (collagen, fibronectin, laminin, Matrigel), culture configuration (monolayer, sandwich, tridimensional) and cell–cell contacts (co-cultures with nonparenchymal cells) have a notable influence on hepatocyte survival and functions during culture (6, 42–44). Therefore, culture conditions need to be optimized and standardized for each hepatotoxicity protocol. For short-term studies, simple culture models (hormone-supplement chemically defined media and monolayer configuration) could be appropriate, whereas long-term cultures require the use of mitogenic factors that favour hepatocyte proliferation but could down-regulate certain enzymes (i.e. P450s), thus compromising drug-metabolizing capacity of cells (44, 45). Sandwich configuration is also recommended for long-term cultures and is particularly needed for hepatobiliary transport studies with hepatocytes (46–48).
5. Conventional In Vitro Hepatotoxicity Protocols
As pointed above, primary cultures of hepatocytes appear to be a powerful in vitro system for early screening of new chemicals and for studying cellular and molecular mechanisms of hepatotoxicity. Despite considerable progress in the understanding of the mechanism of liver toxicity, protocols are not yet available to a rational design of non-hepatotoxic drugs. In recent years, great efforts are being made to develop reliable screening methods to identify compounds that induce hepatocyte injury. To this end, it is essential to define the appropriate markers able to predict hepatotoxic potential of drug irrespectively of mechanism underlying hepatocellular damage. Cytotoxicity endpoints such as membrane integrity, cellular metabolite content or mitochondrial and lysosomal functions represent a first approach to assess hepatotoxicity (Table 21.1). Most studies involve incubation of hepatocytes with the tested compound for 24, 48 or 72 h followed
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Table 21.1 Endpoints and experimental parameters for hepatotoxicity studies in hepatocytes Cell viability–membrane integrity Trypan blue exclusion test
(49)
Cell number: total cell protein, DNA content, Hoechst dye staining
(50, 51)
Cell attachment/detachment
(52, 53)
Cytosolic enzyme leakage: LDH, AST, ALT, . . .
(54–56)
Intracellular LDH
(56)
General metabolic parameters for basal cytotoxicity MTT test, XTT test (mitochondrial activity)
(55, 57–59)
Neutral Red uptake (lysosomal activity)
(51, 55)
Alamar blue (mitochondrial reductive activity)
(55)
Oxygen uptake rates
(60)
Intracellular Ca2+ levels
(54)
ATP content
(51, 54)
Protein synthesis
(56, 61)
ROS formation and intracellular accumulation
(57–59)
GSH levels
(49, 54, 57, 59)
Lipid peroxidation
(54, 57, 58)
Protein–drug adducts formation (covalent binding)
(62, 63)
Caspase-3 activation (apoptosis)
(36, 64–66)
Liver-specific endpoints Urea synthesis
(50, 56 57)
Glycogen accumulation/depletion
(50, 56)
Glucose formation and secretion
(56)
Plasma protein synthesis (albumin, transferrin, fibrinogen)
(50, 56, 57
Lipids synthesis (triglyceride, cholesterol, lipoproteins)
(51, 56, 67)
Lipid accumulation (Nile red staining)
(57, 66)
Taurocholate uptake and excretion
(47)
Cell morphology (bili canaliculin, lipid droplets, bleb formation, nuclear/cytoplasmic alterations)
(50, 51, 68)
P450 enzyme induction
(52, 53)
by quantitative assessment of selected parameters. The use of a wide range of concentrations allows to plot dose–response curves and to calculate IC50 values or other indicators of in vitro toxicity (7, 69). Comparison of IC50 values obtained for a series of compounds can be used to rank order their hepatotoxic potential. Known human hepatotoxic and nonhepatotoxic drugs are used as positive and negative controls, respectively (7, 70).
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The utility of primary cultures for basal cytotoxicity assessment was initially questioned, as undifferentiated (non-hepatic) cells are simpler models that could be used for toxicity studies (71). However, as cell lines do not necessarily represent normal cell physiology, hepatocytes retaining liver-specific properties are now recognized as a more realistic experimental system for early routine screening of hepatotoxicity in drug discovery and development (7, 69, 72). Of particular importance is the high biotransformation capacity (phase I and phase II enzymes) shown by primary hepatocytes in comparison to cell lines. Drug metabolism can be determinant in hepatotoxicity effects, as both detoxication and bioactivation processes can occur. Assays in non-metabolically competent cells could miss effects of bioactivable hepatotoxins (73). An additional advantage of using primary hepatocytes is the possibility of examining inter-species toxicity (74). Species differences in drug metabolism, target molecules and pathophysiology are important factors that must be considered in the interpretation of preclinical findings and in assessing their relevance to humans. Comparative studies using hepatocytes from different species including man are of great value in the judicious and justifiable selection of preclinical species for in vivo toxicology testing. When human hepatocytes are used the results can be subjected to high intrinsic donor variability (i.e. polymorphism of drug-metabolizing enzymes) and studies in multiple donors are recommended (7, 75). In general, cytotoxic endpoints are less sensitive to toxic effects than liver-specific metabolic or functional biomarkers (76). Classical cytotoxicity assays (i.e. increased release of cytoplasmic enzymes to culture medium) identify the toxic phenomena as a loss of survival signals followed by cell death. Irreversible lethal events are detected in late stages of toxicity. Evaluation of these parameters alone may leave out of consideration xenobiotics that impair cell function without causing cell death, which can explain the poor sensitivity of such assays. This may not be critical for the hepatocyte itself, but can be of toxicological significance for the whole organism (77). Early changes in specific structural, biochemical or metabolic components can result in serious functional alterations without compromising hepatocyte viability. Examination of the effects on hepatocyte-specific metabolism makes possible to find out whether relevant hepatic-specific functions become altered by the presence of a xenobiotic. Several metabolic parameters, representative of the most characteristic hepatic functions (i.e. gluconeogenesis, glycogen metabolism, ureogenesis, plasma protein synthesis) could be evaluated (Table 21.1). By the use of functional endpoints cell injury can be detected at sublethal concentrations of the hepatotoxin (48, 77). Because of the acceleration of compound synthesis through combinatorial chemistry, both high-fidelity and high-throughput screening assays are
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required. Absorbance, fluorescence or chemiluminescence-based assays adapted to 96-well plates have been successfully used for toxicity screening in hepatocytes (59, 69). Major advantages of performing screening assays in miniaturized formats are drastic reductions in the number of cells needed for each experiment (of particular importance for human hepatocytes assays) and in the amounts of test compounds (of critical importance in early discovery stages when compound is still limited), and the possibility of automation which notably contribute to lower costs and increase screening throughput. To achieve an accurate and reliable screening of drug-induced toxicity in hepatocytes, several key markers need to be used. A useful strategy is the combination of a few assays indicative of different endpoints. Mitochondria play a central role in energy metabolism, Ca2+ homeostasis and activation of apoptosis, and its dysfunction is increasingly implicated in the aetiology of drug-induced toxicity (30). Therefore, toxicity assays that measure mitochondrial function (mitochondrial membrane potential, intracellular Ca2+ , membrane permeability, ATP content, MTT test, lactate production, oxygen consumption, etc.) are commonly used to screen potential toxicity of drugs (7, 76, 78, 79). Similarly, rapid throughput assays have been developed to detect oxidative stress induced by free radical generators or apoptosis induced after hepatocyte treatment with chemicals (58, 65, 76). Drug-induced intracellular accumulation of lipids can also be detected in hepatocytes. Fluorescent phospholipids analogues and neutral lipid stains are very useful for in vitro detection of compounds that can potentially induce liver phospholipidosis or steatosis (fatty liver), respectively (57, 76, 80). Recently, a new cholestasis assay using a fluorescent bile acid scaffold has been proposed to evaluate impaired bile acid transport by drugs in isolated hepatocytes (81). High-throughput screening paradigms that combine analysis of data generated by in vitro assays in hepatocytes and other cellular models (i.e. liver-derived cell lines) have been proposed to help guide the risk assessment/decision-making process (7). A careful selection of a battery of tests can provide early clues to the underlying mechanisms of toxicity (82). However, more detailed studies are needed to identify the mechanism(s) responsible for the toxicity of a particular compound. Primary hepatocytes have been extensively used for mechanistic studies and are the recommended system for this purpose. Morphological, biochemical and molecular analyses have been applied to investigational studies. Intracytoplasmic lipid droplets or multilamellar inclusion bodies formation observed by microscope examination of cultured hepatocytes exposed to certain compounds (i.e. tetracycline, amiodarone) are indicative of drug-induced steatosis or phospholipidosis (51, 68, 83); hepatocellular cholestasis can be identified by
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pericanalicular cytoskeleton disturbances (84) and nuclear alterations (apoptotic bodies, chromatin fragmentation) are suggestive of apoptotic effects (85–87). A number of biochemical indicators including decreased β-oxidation, altered hepatobiliary transporter function or expression, induced lipid peroxidation (malondialdehyde generation), GSH depletion or mitochondrial or nuclear DNA damage have been used to ascertain which are the mechanisms responsible for DILI (14, 49, 51, 57, 65–67). Drug–drug interactions are a significant issue that not only can alter drug efficacy, but also its toxicity (88). Inhibition of an enzyme (i.e. P450s) that catalysed the major route of a drug can result in an accumulation of the drug with toxic effects. On the other hand, drug induction of metabolizing enzymes can lead to increased production of reactive metabolites. Primary hepatocytes are the only hepatocellular model expressing a full drugmetabolizing competence; therefore they are the “gold standard” for studying metabolism-based toxicity. A number of examples support the utility of cultured hepatocytes for assessing the role of metabolism in DILI. Studies using rat and human hepatocytes have shown that CYP2E1 induction by rifampicin exacerbates isoniazid toxicity (57) and CYP3A induction by phenobarbital increases diclofenac hepatotoxicity (89), whereas P450 induction by phenobarbital or dioxin attenuate cytotoxicity produced by the alkaloid sanguinarine (90). In the presence of known P450 inhibitors, cytotoxic effects of diclofenac (54) and ethanol (91) to hepatocytes are significantly reduced, whereas a potentiation of oxidative stress produced by redox-cycling quinones is observed (92). Metabolic activation of drugs to electrophilic reactive metabolites and their covalent binding to cellular macromolecules is a major cause of DILI and is considered to be involved in idiosyncratic toxicity. Detection of GSH–metabolite reactive adducts and covalent-binding assays has been used during lead optimization to minimize chemically reactive metabolite formation (9, 17). Recently, analysis by RT-PCR of induction profiles of certain genes related to phase II drug-metabolizing enzymes have been proposed as new markers of electrophilic stress caused by reactive metabolites in human hepatocytes (93). In summary, the application of cultured hepatocytes to the study of DILI has contributed to increase the knowledge of basic mechanisms of hepatotoxicity. Their use in early drug screening gives a better assessment of metabolic-dependent toxicity, helps in the identification of molecules able to induce hepatocyte damage and in the selection of those compounds in a series with a minor hepatotoxic potential which, in combination with quantitative structure–toxicity relationships, can provide scientific basis for a more reasonable selection of lead series (59, 94). It is hoped that through a better understanding of hepatocellular phenomena of liver damage, combined with the application of
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mechanistically directed analyses provided by “omics” disciplines, the accuracy and predictivity of in vitro screening for toxicants would be greatly improved.
6. Omic Technologies to Investigate DILI
With increased safety standards from worldwide regulatory agencies, there is an increased need for better safety biomarkers. Existing early biomarkers of toxicity are insufficient and this is demonstrated by the high failure rate of candidate therapeutics due to toxicity problems. The advent of “omic” technologies (genomics, proteomics, metabonomics and cytomics) will facilitate a comprehensive understanding of the perturbation of biological systems by toxic insults and, as such, will lead to better predictive models of toxicity to be used in drug development (Fig. 21.2). Despite the hope for biomarkers and the progress made so far, much
High throughput Automatization and standarization Need of low amount of sample (1–10 µg) No detection of post translational modifications No information about mRNA alternative splicing
Low throughput Partial automatization Need of high amount of sample (100–1000 µg) Detection of post translational modifications Information about mRNA alternative splicing
PROTEOMICS
GENOMICS
HEPATOCYTES
CYTOMICS Medium throughput High content Automatization and standarization Molecular phenotype of single cells Cell populations analysis Real-time kinetic monitoring Use of isolated or cultured cells Use of fluorescent probes
METABONOMICS High throughput Automatization and standarization Analytical reproduciblity No current standarisation of methods Need of low amount of sample (1–10 pmol) Analysis of disturbances of carbohydrates, fatty acids, amino acids and nucleic acids Real biological end points It can be applied noninvasively in culture medium
Fig. 21.2. Relationship of omic technologies to facilitate a comprehensive understanding of the perturbation of biological systems by toxic insults, leading to better predictive models of toxicity for use in drug development.
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challenge lies ahead. It should be considered that the total number of biomarkers of interest can be estimated to be ∼1,133,000, of which genome accounts for ∼25,000–30,000 (95), transcriptome 100,000 (96), proteome 1,000,000 (97) and metabonome ∼2,500–3,000 (95). Cytomics can be considered as the science of single cell-based analyses that links genomics, proteomics and metabonomics with the dynamics of cell and tissue function, as modulated by external influences. The fingerprinting approach for the evaluation of all these biomarkers and the development of a rational hypothesis for a causal association of biomarkers with efficacy or safety is a fascinating challenge for the near future. 6.1. Toxicogenomics
Gene expression analysis applied to toxicology studies, also referred to as toxicogenomics, is rapidly being adopted by the pharmaceutical industry as an useful tool to identify safer drugs in a quicker, more cost-effective manner (98). DNA microarrays allow to monitor the expression of hundreds or thousands of genes at the same time. In a recent study classical toxicology data were compared with the toxicogenomics approach for analysing toxicological mechanisms and toxicity assessments in the early stage of drug development. It was concluded that toxicogenomics would enable a more sensitive assessment at an earlier time point than classical toxicology evaluation (99). The study of early responses of liver toxicity upon treatment of human hepatocytes with the hepatotoxin Aroclor 1254 showed that more than 40 genes with biological functions, the majority coding for xenobiotic defence, were regulated by at least twofold change (100). By using microarrays it is possible to generate unique gene expression profiles (also called fingerprints or signatures) for compounds of known toxic mechanisms. This facilitates comparisons of control with toxicant-treated cells. Gene array analysis has allowed the differentiation between different subtypes of hepatotoxicity at the level of gene expression. Used as a database, comparison of gene expression profiles induced by new drugs with those induced by known toxicants obtained in a database could help to identify potential toxicities (101, 102). New predictive toxicogenomics approaches to better understand the hepatotoxic potential of human drug candidates have been developed using several types of clustering methods, based on comparison of sets of compounds and genes in vivo and in vitro. Robust classification rules were constructed for both in vitro (hepatocytes) and in vivo data, based on a high-dose, 24-h design (103). Similar comparative profiling of gene expression in rat liver and rat primary cultured hepatocytes treated with peroxisome proliferators (104) and known hepatotoxicants (105) have been performed. Gene expression analysis not only reveals chemical-specific profiles allowing to identify the mechanisms of underlying toxicity, but also to assign a compound to a mode-of-action class.
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Conversely, compounds belonging to a same class of toxicant yield similar gene expression patterns different from other profiles generated by other class of chemicals. Toxicogenomic analysis of drug-induced excessive phospholipid accumulation within the cells enabled the identification of 12 specific gene markers and the establishment of an in vitro screening assay for the assessment of the phospholipidosis-inducing potential of compounds (106). Drug-metabolizing gene expression in response to chemicals has a wide variety of implications in drug development including DILI. Simultaneous gene expression profiling of genes coding for 84 drug-metabolizing enzymes (phase 1 and phase 2 drug-metabolizing enzymes and transporters) in cultured human hepatocytes exposed to known inducers has been recently established as well as the underlying mechanisms (107). Microarray and cluster analyses were used to study cell responses to 118 cancer drugs with known mechanisms of action. The results showed that cellular responses to cancer drugs clustered according to the mechanisms of action of the drug regardless of the type of cell used (108). A strong correlation between gene expression profiles and the mechanisms of toxicity induced by 15 different known hepatotoxins has also been reported (109). Moreover, by exposing hepatocytes to 11 different hepatotoxicants selected on the basis of their variety of hepatocellular effects (necrosis, cholestasis, steatosis and P450 induction), it was shown that compounds inducing similar toxicological endpoints produced similar changes in gene expression (110). All the tested drugs generated a specific gene expression profile allowing the classification of the compounds with similar hepatocellular toxicities. However, over time generalized mechanisms of cell death have evolved (111), including apoptosis and necrosis irrespective of cell type, tissue or organ. Thus, the toxicogenomics approach of fingerprinting genes and identifying mechanism-specific toxicities has proven to be more difficult than anticipated. When applying these technologies to in vitro experiments, several issues need to be considered. First, the stability of basal gene expression in freshly isolated hepatocytes and the variability culture to culture; second, functional differences in primary hepatocytes compared with intact liver; and finally, whether the generated toxicogenomics data are reproducible between laboratories. Concerning the first question, gene expression in freshly isolated human hepatocytes is similar to that of the liver of origin. However, the gene expression is profoundly affected after plating. Specifically, in cultured human hepatocytes gene expression changes involved in cellular processes such as phase I/II metabolism, basolateral and canalicular transport systems, fatty acid and lipid metabolism, apoptosis and proteasomal protein recycling were observed. An oxidative stress response may be
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partially responsible for these changes in gene expression. In addition, basal gene expression is reported to be distinctively different from one culture to another, regardless of the culture conditions applied (41, 112), and a marked down-regulation of most of the assayed genes in the serum-containing cultures has been reported (113). Therefore, it needs to take into account gene expression changes taking place in hepatocyte cultures over time without any treatment. In particular, rodent hepatocytes exhibit a large number of gene up- and down-regulations, simply as a result of culture conditions (41). Related to the second issue, several toxicogenomic-based studies performed comparing rat hepatic in vitro models with the situation in vivo conclude that the main limitation of the hepatic models for toxicogenomic studies is the loss of liver-specific functions, in particular, P450 activities. The inability to predict if a metabolically bioactivated compound will cause toxicity in later stages of drug development or post-marketing is of serious concern. An approach for improving the predictive success of compound toxicity has been to compare the gene expression profile in preclinical models dosed with novel compounds to a gene expression database generated from compounds with known toxicity. While this guilt-by-association approach can be useful, it is often difficult to elucidate gene expression changes that may be related to the generation of reactive metabolites (114). It has been reported for coumarin-induced toxicity that collagen sandwich-cultured hepatocytes better represent the situation in vivo compared with standard cultures of hepatocytes (115). Therefore, further research is required to establish primary hepatocyte culture conditions that result in in vitro responses at the transcriptome level that more closely resembles the in vivo situation, and guarantees acceptable levels of drug-metabolizing enzymes and responsiveness to enzyme inducers (75, 116, 117). The third issue was addressed by four pharmaceutical companies in an interlaboratory study by evaluating gene expression pattern of methapyrilene (118). Appropriate statistical tools allowed to use gene expression profiles to correctly identify methapyrilene in an independently generated in vitro database, underlining that in vitro toxicogenomics could be a predictive tool for toxicity. From a mechanistic point of view, despite the observed site-to-site variability, there was good concordance regarding the affected biologic processes. Several subsets of regulated genes were obtained by analysing the data sets with one method or using different statistical analysis methods. 6.2. Proteomics
Proteomics holds the promise of global analysis of changes in the quantities and posttranslational modifications of the proteome. Proteomic analyses are most frequently conducted using 2D gel electrophoresis for protein separation and mass spectrometry (MS) for identification of proteins. Other recently developed
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technologies include surface-enhanced laser desorption ionization (SELDI), antibody microarrays and various types of liquid chromatography tandem mass spectrometry techniques (LC-MS/MS) (119, 120). The objective of this approach is to search for alternative toxicity biomarkers which could be detected with high sensitivity prior to the appearance of morphological changes or alterations of analytical conventional biomarkers. In the hepatotoxicity evaluation of compounds on an in vitro screening system, it is essential to set biomarkers well reflecting in vivo toxicity (121). The first successful applications have been the identification of potential markers of toxicity using a proteomics approach alone (122) or using proteomics in combination with other “omics technologies” (123). In addition to the conventional biomarkers, several protein biomarkers which relate to oxidative stress and metabolism regulation were investigated in more recent studies (124). Effects on protein expression of known hepatotoxins (acetaminophen, amiodarone, carbon tetrachloride and tetracycline) were determined in primary cultured hepatocytes with toxicoproteomic approach. The results showed that glutathione peroxidase and peroxiredoxins 1 and 2 could be utilized as early biomarkers of hepatotoxicity (125). Other recent study focused on eight proteins related to oxidative stress response (i.e. carbonic anhydrase III and 60 kDa heat shock protein) and energy metabolism (i.e. adenylate kinase). These proteins were affected by all four compounds examined. Moreover, hierarchical clustering analysis revealed the possibility to differentiate the groups based on their toxicity levels such as severity of liver damage (126). These results suggested that assessing the effects of hepatotoxicants on protein expression is worth trying to screen candidate compounds at the developmental stage of drugs. A recent study was undertaken to identify proteomic markers associated with hepatocellular steatosis (127). A compound (CDA) in preclinical development was administered to rats and hepatocyte cultures. The study showed similar alterations to the proteome in response to CDA in vivo and in vitro, thus indicating the potential of using the hepatocyte model in the development of highthroughput assays to identify protein markers for drug-induced steatosis (127). It was hypothesized that treatment of hepatocytes with drugs clinically linked to idiosyncratic hepatotoxicity would result in the release of extracellular protein biomarkers indicative of liver toxicity. To test this hypothesis, immortalized human hepatocytes which overexpress CYP3A4 were treated with 20 individual compounds. For all 20 drugs, two proteins, BMSPTX-265 and BMS-PTX-837, were reproducibly and significantly increased in the conditioned media from cells treated with each of the toxic compounds. These data support both the preclinical in vitro method as a means to identify new biomarkers of liver toxicity and the validity of the biomarkers themselves (128).
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Some drawbacks have been reported using a highly parallel two-dimensional electrophoretic (2-DE) protein separation system to analyse cells from culture systems. Significant variations in protein expression that were unrelated to chemical exposure have been reported (129). These artefactual protein alterations were the result of the variations in the culture conditions or cell manipulations or both. A study to assess the expression of hepatocyte proteins either by scraping/pelleting or direct in-well solubilization was conducted. Based on protein identification by peptide mass fingerprinting, the subcellular location of nearly all of the proteins whose abundance decreased were cytosolic and those few that increased were either microsomal, mitochondrial or cytoskeletal proteins. These results emphasize the variation introduced by cell handling during recovery of hepatocytes from culture plates and may explain at least some of the artefactual differences observed in earlier in vitro experiments. Regarding gene or protein expression profiling in cultured hepatocytes has provided valuable new data that may in the future improve our ability to predict toxicological endpoints. However, further research is needed to solve problems such as basal alterations in gene expression and to provide a better correlation with the in vivo situation. 6.3. Metabonomics
Metabonomics is defined as the quantitative measurement of the time-related multiparametric metabolic response of living systems to pathophysiological stimuli or genetic modification. Metabolomics is the comprehensive and quantitative analysis of all metabolites. Then, metabonomics and metabolomics have been defined as subsets of each other. Both are emerging fields in analytical biochemistry and can be regarded as the endpoint of the omics cascade. Metabonomics has emerged as a key technology in pharmaceutical discovery and development, evolving as the small molecule counterpart of transcriptomics and proteomics. It is a powerful tool for identifying any disturbances in normal homeostasis of metabolic processes, including those involving carbohydrates, fatty acids, amino acids and nucleic acids. These normal metabolic processes are highly regulated and are vital for cell structure and function. These functions are catalysed by various enzymes, which are in turn regulated by specific genes (130). Global metabolic profiling (metabonomics/metabolomics) has shown particular promise in the area of toxicology and drug development. In both preclinical screening and mechanistic exploration, metabolic profiling can offer rapid, noninvasive toxicological information that is robust and reproducible (131, 132). The main analytical techniques that are employed for metabonomics are based on nuclear magnetic resonance (NMR) spectroscopy and MS, but encompass the application of LC/MS,
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LC/MS/MS and LC/NMR as potentially powerful solutions to the problems of detector generality and structure determination (133). NMR is a very general detection method and can provide unique structural information. The electrospray ionization (ESI) technique has made polar molecules accessible to direct analysis by MS, as well as being compatible with HPLC separations. Quantification of multiple compounds in crude extracts can, in principle, be achieved in the same way as described for GC/MS, although automation of the procedure presents greater practical difficulties. LC/MS/MS provides additional structural information that can be a very useful aid in the identification of new or unusual metabolites or in the characterization of known metabolites in cases where ambiguity exists. Metabonomic evaluations have enormous potential to identify novel biomarkers of toxicity (132). The analytical method is quantitative and provides detailed structural information. One major challenge has been the acquisition and processing of raw analytical data. Characterizing a metabonome of 3,000 metabolites is not a trivial matter, and therefore several pattern recognition tools have been employed to differentiate and fingerprint the specific metabolites that may be elevated because of the insult from the toxin. Given the amount of data generated from a single spectrum, data analysis is a critical component of the interpretation of metabonomic results and involves the use of appropriate multivariate statistical methods. Mathematical models characterizing the effects of toxins on endogenous metabolite profiles enable rapid toxicological screening of potential drug candidates and the discovery of novel mechanisms and biomarkers of specific types of toxicity. Principal component analysis (PCA) is a widely used tool for the identification of those analyses that are most different from the control and provides a visual characterization of the data set. However, for pattern recognition and predictive model development, additional multivariate statistical models are required. Over the past 10 years, an extensive body of research has been generated demonstrating that metabonomic data are useful for assessment of toxic mechanisms and prediction of toxicity (131, 134). There is clear evidence that the pattern of changes noted, even with commonly occurring metabolites, is altered in a toxicity- and tissue-specific manner, a feature that is extremely powerful with respect to the predictive utility of metabonomic data. At the same time, there is the clear potential to identify unique and/or specific endogenous metabolites that are associated with a specific type of change, enabling the identification of biomarkers of toxic changes. The response of cells to toxic effects of drugs involves adjustment of intracellular and extracellular environments in order to maintain homeostasis. Both perturbation and adjustment are expressed as changes in the normal patterns in bio fluids of tissues that are
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characteristic (a “fingerprint”) of the nature of the toxic insult (135). One such example is the detection of phenylacetylglycine (PAG) as a potential useful biomarker for compound-induced phospholipidosis (136). As with any biomarker, careful validation is required to assess the overall utility of the biomarker (across species, sensitivity and specificity) and efforts continue in this regard. However, a biomarker need not be a single metabolite. Many metabonomic studies conducted to date have focused on assessing the patterns of change associated with toxicity and reporting the kinds of metabolites that have been altered by chemical treatment or physiological alteration. These reports are extremely useful for establishing databases that can be used for predicting toxic liabilities. However, efforts to use metabonomics to identify mechanisms of toxicity are also important. For example, the work from Mortishire-Smith et al. (137) provided evidence of altered fatty acid metabolism as a mechanism of hepatotoxicity and shows the potential for metabonomics to address mechanistically based hypotheses. In vitro approaches have been heavily researched. Preclinical toxicologists consider in vitro approaches as extremely useful when in vivo target link has been established. It might seem that metabonomics would also aid evaluation and interpretation of in vitro toxicity data. However, the literature in this area is still very limited (16, 131, 138). 6.4. Cytomics
Cytomics aims to determine the molecular phenotype of single cells. Within the context of the -omics, cytomics allows the investigation of multiple biochemical features of the heterogeneous cellular systems known as the cytomes. Cytomics can be considered as the science of single cell-based analyses that links genomics and proteomics with the dynamics of cell and tissue function, as modulated by external influences (139, 140). Inherent to cytomics are the use of sensitive, scarcely invasive, fluorescencebased multiparametric methods and the event-integrating concept of individual cells to understand the complexity and behaviour of tissues and organisms. Among cytomic technologies, flow cytometry (141) and confocal microscopy (142) are complementary and widely used. The dynamic nature of cytomic assays enables a real-time kinetic monitoring, based on sequential examination of different single cells, of multiple cellular biomarkers (multiparametric capacity) of processes that are critically involved in the pathogenesis of the toxicity. Cytomic endpoints may represent early or late parameters along the cytotoxic process. It has been recently reported that cytomic functional assays may detect specifically early or transient changes in the process of cytotoxicity, which makes these assays advantageous over other tests limited to the quantification of cell death as endpoint of cytotoxicity. It has been recently developed a cell-based model to assess human hepatotoxicity potential of drugs, based on automated epifluorescence
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microscopy and image analysis of cells in a microtiter plate format (143). A combination of critical model features including human hepatocytes with drug metabolism capability and measurement of multiple morphological and biochemical parameters indicative of prelethal cytotoxic effects, which are representative of different mechanisms of toxicity at the single-cell level, is used. The results showed that human hepatotoxicity is highly concordant with in vitro cytotoxicity in this novel model (143). A high-content multiparametric cytotoxicity assay based on simultaneous measurement of eight key cell health indicators associated with nuclear morphology, plasma membrane integrity and mitochondrial function has been recently developed (144). Simple cytotoxicity assays in hepatic cells are relatively insensitive to human hepatotoxic drugs. In comparison, a panel of pre-lethal mechanistic cellular assays holds the promise to deliver a more sensitive approach to detect endpoint-specific drug toxicities (76). The panel of assays covered by this study includes steatosis, cholestasis, phospholipidosis, reactive intermediates, mitochondria membrane function, oxidative stress and drug interactions. In addition, the use of metabolically competent cells or the introduction of human hepatocytes in these in vitro studies allow a more complete picture of potential drug side effect (76) and assessment of separate basal- and biotransformationdependent cytotoxicity (145). A battery of apoptotic markers designed to identify compounds triggering apoptosis in hepatocytes prior to necrosis for the screening of newly developed drugs has been also reported (86). Finally, it has been recently developed a fluorescence-based in vitro screen that is predictive of phospholipidosis using the cellomics high-content screening platform, which captures and analyses images from 96-well cell culture microtiter plates using multichannel fluorescence microscopy (146). It is expected that the phenotypic output from the multiparametric cytomic assays in combination with other highly sensitive approaches, such as microarray-based expression analysis of toxic signatures, will contribute to a better understanding and predictivity of human hepatotoxicity potential.
Acknowledgements The authors acknowledge the financial support from the ALIVE Foundation, and the European Commission, grants LSHB-CT2004-504761, LSHB-CT-2004-512051 and LSSB-CT-2005037499.
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Hepatocytes to Investigate Drug Toxicity 131. Keun, H.C. (2006) Metabonomic modeling of drug toxicity. Pharmacol. Ther. 109, 92–106. 132. Robertson, D.G., Reily, M.D., and Baker, J.D. (2007) Metabonomics in pharmaceutical discovery and development. J. Proteome Res. 6(2), 526–539. 133. Lindon, J.C. and Nicholson, J.K. (2008) Spectroscopic and statistical techniques for information recovery in metabonomics and metabolomics. Annu. Rev. Anal. Chem. 1, 45–69. 134. Lehman-MacKeenan, L.D. and Car, B.D. (2004) Metabonomics: application in predictive and mechanistic toxicology. Toxicol. Pathol. 32, 94–95. 135. Ellis, D.I., Dunn, W.B., Griffin, J.L., Allwood, J.W., and Goodacre, R. (2007) Metabolic fingerprinting as a diagnostic tool. Pharmacogenomics 8, 1243–1266. 136. Delaney, J., Neville, W.A., Swain, A., Miles, A., Leonard, M.S., and Waterfield, C.J. (2004) Phenylacetylglycine, a putative biomarker of phospholipidosis: its origins and relevance to phospholipid accumulation using amiodarone treated rats as a model. Biomarkers 9, 271–290. 137. Mortishire-Smith, R.J., Skiles, G.L., Lawrence, J.W., Spence, S., Nicholls, A.W., Johnson, B.A., and Nicholson, J.K. (2004) Use of metabonomics to identify impaired fatty acid metabolism as the mechanism of a drug-induced toxicity. Chem. Res. Toxicol. 17, 165–173. 138. Halegoua-De Marzio, D. and Navarro, V.J. (2008) Drug-induced hepatotoxicity in humans. Curr. Opin. Drug Discov. Dev. 11, 53–59. 139. Herrera, G., Diaz, L., Martinez-Romero, A., Gomes, A., Villamón, E., Callaghan, R.C., and O’Connor, J.E. (2007) Cytomix:
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a multiparametric, dynamic approach to cell research. Toxicol. In Vitro 21, 176–182. Gomase, V.S. and Tagore, S. (2008) Cytomics. Curr. Drug Metab. 9, 263–266. O’Connor, J.E., Callaghan, R.C., Escudero, M., Herrera, G., Martínez, A., Monteiro, M.C., and Montolíu, H. (2001) The relevance of flow cytometry for biochemical analysis. IUBMB Life 51, 231–239. Amos, W.B. and White, J.G. (2003) How the confocal laser scanning microscope entered biological research. Biol. Cell 95, 335–342. O’Brien, P.J., Irwin, W., Diaz, D., HowardCofield, E., Krejsa, C.M., Slaughter, M.R., Gao, B., Kaludercic, N., Angeline, A., Bernardi, P., Brain, P., and Hougham, C. (2006) High concordance of drug-induced human hepatotoxicity with in vitro cytotoxicity measured in a novel cell-based model using high content screening. Arch. Toxicol. 80, 580–604. Abraham, V.C., Towne, D.L., Waring, J.F., Warrior, U., and Burns, D.J. (2008) Application of a high-content multiparameter cytotoxicity assay to prioritize compounds based on toxicity potential in humans. J. Biomol. Screen. 13, 527–537. Martínez-Romero, A., Alvarez-Barrientos, A., Callaghan, R.C., Coecke, S., Arza, E., Nieto, R., Prieto, P., Torralbo, P. and O’Connor, J.E. (2004) Role of CYP2D6dependent metabolism in the cytotoxicity of mianserin and imipramin. Cytometry 69A, 48–49. Morelli, J.K., Buehrle, M., Pognan, F., Barone, L.R., Fieles, W., and Ciaccio, P.J. (2006) Validation of an in vitro screen for phospholipidosis using a high-content biology platform. Cell Biol. Toxicol. 22, 15–27.
Chapter 22 The Use of Human Hepatocytes to Investigate Bile Acid Synthesis Ewa C. S. Ellis and Lisa-Mari Nilsson Abstract De novo synthesis of bile acids is a liver-specific function that is difficult to maintain in cultured cells. There are significant species differences in both types of bile acids formed and more importantly in the regulation of bile acid homeostasis. This highlights the need for a good human in vitro model. Isolated primary human hepatocytes have the capacity to synthesize normal conjugated bile acids at a rate similar to that in vivo. In this chapter we describe the importance of different culture conditions such as choice of substrate, media and supplements on the total bile acid production as wells as the bile acid composition. Key words: Bile acids, CA, CDCA, human hepatocytes, EHS matrigel, collagen, CYP7A1.
1. Introduction Bile acid synthesis is a function performed by well-differentiated and polarized hepatocytes and in vitro studies have been difficult to perform due to the lack of cell lines producing normal bile acids. The hepatoblastoma cell line HepG2 cells synthesize some bile acids, but the levels are low and they are defective in oxidation of the side chain, conjugation, and transport (1–3). The rat hepatoma–human fibroblast hybrid cell line WIF-B9 has structural and functional characteristics of normal differentiated hepatocytes (4, 5) and they also produce normal bile acids with a human composition. However, they lack the ability to amidate primary bile acids (6). Primary human hepatocytes in culture synthesize the normal primary bile acids, cholic acid (CA), and chenodeoxycholic acid P. Maurel (ed.), Hepatocytes, Methods in Molecular Biology 640, DOI 10.1007/978-1-60761-688-7_22, © Springer Science+Business Media, LLC 2010
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(CDCA), at a ratio expected for hepatocytes taken out of the enterohepatic circulation (7). All bile acids produced are conjugated and excreted into the media (8). Their ability to transport bile acids also includes active uptake of conjugated bile acids as proven by their ability to inhibit CYP7A1 mRNA levels and synthesis of bile acids (9). Many investigators studied the regulation of mRNA levels of enzymes important for bile acid synthesis such as CYP7A1 and CYP8B1 (10–14) and different investigators also use different time points 1–2 days in culture (12, 13) or 2–3 days (10, 11, 14). It is therefore important to optimize culture conditions for expression of these enzymes and the subsequent synthesis and secretion of bile acids in primary human hepatocytes. In this chapter we describe the effect of different substrates, media composition, and time in culture on bile acid synthesis in primary human hepatocytes.
2. Materials 2.1. Collagen Extraction
1. Rats: Wistar (Charles River).
2.2. Matrigel Extraction
1. Mice: Female, 5–6 weeks old, C57Bl (Charles River).
2. Acetic acid (Merck).
2. Mouse sarcoma, EHS (American Type Culture Collection). 3. Buffer I: 3.4 M NaCl (Merck), 50 mM Tris (Merck), 4 mM EDTA (Merck), 2 mM NEM (N-ethylmaleimide) (Sigma), pH 7.4. 4. Buffer II: 2 M Urea (Merck), 50 mM Tris (Merck), 0.15 M NaCl (Merck), pH 7.4. 5. Buffer III: 0.15 M NaCl (Merck), 50 mM Tris (Merck), pH 7.4. 6. Freezing media: 5 ml HMM media (Lonza), 5 ml FBS (Lonza), 1 ml DMSO (Merck). 7. Media components: PEST (Lonza), FBS (Lonza).
2.3. Cell Cultures
1. Primary hepatocytes were isolated using a three-step perfusion technique as described previously (15). This will not be described in detail as this is described elsewhere in this book (see Chapters 3, 12, and 23). Primary human hepatocytes were isolated from unused donors or tissue obtained from resections due to underlying malignancies (n=8, four males and four females). Average tissue weight was 75.9 g and the average digestion time 22.1 min using collagenase XI from
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sigma C-7657. Average viability was 82% and the average yield 7 million hepatocytes/g liver. 2. Swedish media: Hepatocyte Maintenance Media: (Lonza), 12 nM insulin (HMM SingleQuot Kit) (Lonza). 3. Standard media: Hepatocyte Maintenance Media (Lonza), 120 nM insulin (HMM SingleQuot Kit) (Lonza), 100 nM dexamethasone (HMM SingleQuot Kit) (Lonza). 4. Plating media: SWE/STD media, 5% FBS (Lonza). 5. Cell culture materials: culture dishes (Falcon), rubber cell scrapers (Deutsch & Neumann). 2.4. Bile Acid Analysis
1. Reagents for bile acid analysis: deuterium-labeled cholic acid and chenodeoxycholic acid (CDN Isotopes), unlabeled cholic acid and chenodeoxycholic acid (Sigma), ethanol (Kemetyl), potassium hydroxide (Merck), diethyl ether (Merck), hydrochloric acid (Merck), trimethylsilyldiazomethane (Sigma-Aldrich), hexamethyldisilazane (Thermo Scientific), chlorotrimethylsilane (Alfa Aesar), pyridine (Thermo Scientific). 2. GC/MS analysis: Agilent 6890, Agilent 5973, Agilent HP-1 column (30 m × 0.25 mm).
2.5. Gene Expression Analysis
1. RNA extraction: TRIzol (Invitrogen), chloroform (Merck), 2-propanol (Merck), ethanol (Kemetyl). 2. cDNA synthesis: High Capacity cDNA Reverse Transcription Kit (Applied Biosystems), Gene Amp PCR System 9700 (Applied Biosystems). 3. Real-time PCR: Cyclophilin A Hs99999904_m1, CYP7A1 Hs00167982_m1, CYP8B1 Hs00244754_s1, CYP27A1 Hs00168003_m1 (all probes are from Applied Biosystems), Universal Mastermix (Applied Biosystems), 7000 Sequence Detection System (Applied Biosystems).
3. Methods 3.1. Collagen Extraction
Rat-tail type I collagen was extracted using 0.1% acetic acid as described by others (16, 17). 1. Rats are anesthetized and killed, the skin is removed from the tails. 2. The tail is broken between every other vertebrae. 3. The tendons are pulled out and air dried and sterilized under UV light overnight.
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4. Dried collagen fibers are stirred for 48 h in 0.1% acetic acid (1 g of collagen to 300 ml acetic acid). 3.2. Matrigel Extraction
3.2.1. Thawing of Tumors for Injection
EHS matrigel was prepared from Engelbreth-Holm-Swarm mouse sarcoma according to Kleinman et al. (18). In short, frozen tumors are thawed and injected in a few animals; the tumors are harvested for passage and injected into more mice. Following propagation the tumors are harvested for matrigel extraction and storage. All steps should be done at 4◦ C or on ice and sterile (see Note 1). 1. Tumors are thawed on ice and centrifuged at 100×g for 3 min. 2. Cold PBS (2 × volume) is added to the pellet. Samples are centrifuged by letting the centrifuge come up to 160×g and then switched off immediately. This step is repeated twice. 3. After the last centrifugation enough fluid is left to inject 0.5 ml per injection, PEST (0.1 × volume) is added to the tumors.
3.2.2. Injection
1. Mice are anesthetized and 0.5 ml tumor mixture is injected into the lateral side of the right hindleg. The 16G needle is inserted into the muscle.
3.2.3. Harvest of Tumors for Passage
1. Mice are sacrificed by cervical dislocation, thereafter the mice are dipped in 70% ethanol. 2. The skin surrounding the tumor is removed and the tumors are collected into separate 50 ml Falcon tubes. 3. PBS is added to the tumors and the mixture is squeezed through a 20 ml syringe, next this step is repeated but with a 16G needle fitted onto the syringe. 4. More PBS is added and the mixture shaken. 5. Samples are centrifuged by letting the centrifuge come up to 160×g and then switched off immediately. The supernatant is poured off and more PBS is added, samples are centrifuged again. This step is repeated twice. After the last spin enough fluid is left to make the mixture “slurry.” All samples are combined and PEST (0.1 × volume) is added. 6. Tumors are injected in the same way as described above.
3.2.4. Harvest of Tumors for Extraction of Matrigel
1. Tumors are collected into a preweighed beaker containing Buffer I (100 ml). 2. Tumors are homogenized in 3 × volume Buffer I (account for the 100 ml already in the beaker) and the mixture is filtered through one layer of gauze.
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3. Tumors are centrifuged at 10,000×g for 15 min, supernatant is discarded and the tumors are homogenized in Buffer I (same volume as before). Tumors are centrifuged and homogenized until no blood is left. 4. Tumors are homogenized in 1.5 × volume of Buffer II and transferred into a beaker with magnetic bar. The mixture is stirred at 4◦ C overnight. 5. Tumors are centrifuged at 10,000×g for 30 min, supernatant is saved. Tumor residue is homogenized in 1 × volume Buffer II and centrifuged at 10,000×g for 30 min, supernatant is saved. 6. Dialysis bags are filled with the combined supernatants. Supernatants are dialyzed in Buffer III with 0.5% CHCl3 for 2 h. Thereafter dialyzes are changed to Buffer III only, the mixture is dialyzed for 2 h. This step is repeated once. The final dialyzes are performed using media (HMM) for 2 h or overnight. 7. The dialyze bags are dipped in 70% ethanol and wiped before they are emptied into a beaker, 0.01 × volume PEST is added and the mixture is stirred for 30 min. 8. Matrigel is aliquoted and stored at −20◦ C. 9. Protein concentration is determined at 280 nm. 3.2.5. Harvest of Tumors for Storage
1. Tumors from two mice are harvested and put into one tube. 2. PBS is added to the tumors and mixture is squeezed through a 20 ml syringe, next this step is repeated but with a 16G needle fitted with the syringe. 3. More PBS is added and the mixture is shaken. Samples are centrifuged by letting the centrifuge come up to 160×g and then switched off immediately. The supernatant is poured off and media (HMM) with 10% FBS is added, samples are centrifuged again. This step is repeated twice. 4. Supernatant is discarded and the freezing media is added. Tumors are put on ice until settled, supernatant is discarded. 5. Matrigel is aliquoted into cryo-tubes and frozen at −70◦ C overnight. Finally, tubes are transferred to liquid N2 .
3.3. Cell Plating
1. Dishes for cells cultured on collagen are prepared by coating 6-well plates with 2 ml rat-tail type I collagen (0.03 mg/ml), after 30 min at 37◦ C the collagen solution is aspirated and the cells are plated. 2. EHS matrigel plates are precoated with 0.1 ml ice-cold EHS per well. A rubber cell scraper is used to spread the cold liquid EHS in the well, thereafter the plates are left at room temperature to allow the EHS to form a gel.
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3. 1.5 × 106 cells are plated per well (in plating media). After approximately 1 h the media is changed to either SWE or STD without any addition of FBS, thereafter the media is renewed daily until harvesting on day 5. 4. Cells cultured on collagen with EHS overlay are plated onto collagen-coated dishes, 24 h after the plating the media is changed to ice-cold cell media mixed with 0.23 mg/ml EHS (see Notes 2–5). 3.4. Bile Acid Analysis
We analyze bile acids in cell culture medium with GC/MS according to Björkhem and Falk (19) with some modifications: 1. Cell medium is mixed with internal standards (deuteriumlabeled cholic acid and chenodeoxycholic acid) and diluted with 50% ethanol. 2. The mixture is hydrolyzed with 1 M potassium hydroxide at 120◦ C for 12 h. 3. The samples are extracted with ethyl ether to remove neutral steroids. 4. After acidification with hydrochloric acid (6 M) to pH 1, samples are extracted with ethyl ether. 5. The extracts are washed with water until neutral, thereafter the samples are evaporated. 6. Samples are methylated with trimethylsilyldiazomethane and converted into trimethylsilyl ether derivates using hexamethyldisilazane and trimethylchlorosilane in pyridine. 7. Samples are analyzed by GC/MS. The oven temperature is 180◦ C during the injection, the temperature is then increased by 20◦ C/min to 260◦ C, thereafter the temperature is increased to 290◦ C with the rate of 3◦ C/min (see Notes 6 and 7).
3.5. Gene Expression Analysis
1. Cells are harvested in TRIzol. The samples are stored in −70◦ C until mRNA extraction. 2. Chloroform is added and the samples are shaken for 15 s. Samples are centrifuged at 12,000 rpm for 15 min. 3. The RNA is precipitated with 2-propanol and centrifuged at 12,000 rpm for 10 min. 4. The RNA is washed with ethanol, dried, and dissolved in RNase-free water. 5. Concentration is determined at 260 nm. 6. RNA is mixed with cDNA-kit reagents. cDNA is synthesized using the following reaction: 25◦ C for 10 min, 37◦ C for 120 min, 85◦ C for 5 s. 7. cDNA is diluted 1:10, mixed with probe and mastermix and run in triplicates.
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8. Real-time PCR is run with machine standard settings. 3.6. Statistics
Data are presented as means ± SEM. The significance of differences between groups was tested by one-way ANOVA followed by post-hoc comparisons of group means according to the LSD method (Statistica software, Stat Soft). In order to stabilize the variances, the data were log transformed.
4. Notes 1. Sterilize and chill the buffers before using them, Buffer I and III should be autoclaved, Buffer II should be sterile filtered. One tumor will give enough material to inject 5–10 mice. Hence, 40–50 tumors will give on average 300–600 ml matrigel. Check the mice regularly, it takes 2–4 weeks until harvest. 2. Primary human hepatocytes are commonly cultured on a substrate such as rat-tail collagen, collagen gels, fibronectin, or matrigel (EHS). In this chapter we show data on the difference in bile acid synthesis between hepatocytes cultured on rat-tail collagen and EHS matrigel. Hepatocytes cultured on EHS display a morphology completely different from that of the well-known cuboidal appearance on collagen (Fig. 22.1). Overlay with EHS matrigel onto hepato-
A
B
C
D
Fig. 22.1. Cell morphology. Primary human hepatocytes from one donor cultured on: (A) collagen, 10× magnification, (B) collagen, 20× magnification, (C) EHS, 10× magnification, (D) EHS, 20× magnification.
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cytes cultured on collagen gels or rat-tail collagen, so-called sandwich cultures, induce polarity and increase expression of transporters (20). However, overlay with EHS matrigel did not significantly change total bile acid production or bile acid composition (Fig. 22.2). 60 Percent of total BAs
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CA CDCA
50 40 30 20 10 0 Collagen
Coll. + EHS OL
Fig. 22.2. Bile acid production in primary hepatocytes cultured on collagen and on collagen with EHS overlay. Bile acid levels expressed as percent of total bile acids synthesized by each liver. Mean of hepatocytes isolated from three livers ± SEM. Hepatocytes are cultured in Swe media on collagen-coated plates or on collagen-coated plates with EHS overlay.
3. We use one of the commonly used media for primary human hepatocytes called hepatocyte Maintenance Media which is William’s medium E with HEPES and glutamine but without phenol red. Addition of serum to media will inhibit bile acid production (data not shown) therefore we use serumfree media. In Table 22.1 we present two different supplementation strategies, Standard (STD) media, which is the one commonly used for maintenance of CYP 450 s (21), and the Swedish media (SWE) which is used at our institute in Sweden (9, 22). We compared bile acid synthesis in media from hepatocytes isolated from four different livers cultured in STD or SWE media, on collagen or EHS matrigel. Cells cultured in either media produced more bile acids when cultured on EHS, Table 22.2. Cells cultured in STD media showed a marked different composition to cells cultured in SWE media, with a higher proportion of CA
Table 22.1 Cell media supplements Swe (nM)
Swe + Dex (nM)
Std w/o Dex (nM)
Std (nM)
Insulin
12
12
120
120
Dexamethasone
–
100
–
100
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Table 22.2 Bile acid production in primary hepatocytes (n=4) cultured on EHS or collagen-coated plates in Swe or Std media. Mean of μg bile acids/ml cell media ± SEM Total BAs (μg/ml)
CA (μg/ml)
CDCA (μg/ml)
EHS-Swe
0.6 ± 0.14
0.3 ± 0.07
1.9
0.8
EHS-Std
1.2 ± 0.44
0.1 ± 0.03
13.1
1.3
Collagen-Swe
0.1 ± 0.06
0.1 ± 0.04
1.5
0.2
Collagen-Std
0.6 ± 0.27
0.0 ± 0.01
16.9
0.6
CA/CDCA
leading to a much higher ratio of CA/CDCA, regardless of substrate, Fig. 22.3. Expression analysis of mRNA levels of the rate-limiting enzyme Cholesterol 7α-hydroxylase, CYP7A1, showed a similar pattern with significantly higher expression in SWE on EHS compared to SWE or STD on collagen. EHS in STD was not significantly different from the other groups, Fig. 22.4. The changes in mRNA levels of sterol 12α-hydroxylase, CYP8B1, the enzyme responsible for the formation of cholic acid, are in agreement with the bile acid composition. The expression was significantly lower in cells cultured in SWE media compared to cells cultured in STD media on both EHS and collagen. Expression of sterol 27-hydroxylase, CYP27A1, the first enzyme in
Percent of total BAs
50 40 30 20
CA CDCA
c **
c* c*
** d * b,c
10 * a
b ** a,d *
* a,d
0 EHS - Swe
EHS - Std
Collagen - Swe
** ca * Collagen - Std
Fig. 22.3. Bile acid production in primary hepatocytes cultured in different culture conditions. Bile acid levels expressed as percent of total bile acids synthesized by each liver. Mean of hepatocytes isolated from four livers ± SEM. Hepatocytes are cultured on EHS or collagen-coated plates in Swe or Std media. ∗ p ≤ 0.05, ∗∗ p ≤ 0.01, ∗∗∗ p ≤ 0.001. a = compared to EHS−Swe, b = compared to EHS−Std, c = compared to collagen−Swe, d = compared to collagen−Std.
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0.16 0.14 0.12 A.U.
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c,d *
c ** a*
0.10
*c
a*
0.08 *a
0.06 0.04
b,c,d *
*a
0.02
*a
b* b ** d *
*
a
0.00 CYP7A1
CYP8B1
CYP27A1
Fig. 22.4. Gene expression in primary hepatocytes cultured in different culture conditions. Gene expression in hepatocytes cultured on EHS or collagen-coated plates in Swe or Std media. Mean of four livers ± SEM. ∗ p ≤ 0.05, ∗∗ p ≤ 0.01, ∗∗∗ p ≤ 0.001. a = compared to EHS−Swe, b = compared to EHS−Std, c = compared to collagen−Swe, d = compared to collagen−Std.
the alternative pathway, was similar to that of CYP7A1, with significantly highest expression in cells cultured on EHS in SWE media. Since the difference between STD and SWE media is the concentration of both dexamethasone and insulin (Table 22.1), we carried out a second set of experiments on EHS only, where we included SWE media with dex (low insulin) and STD media without dex (high insulin). Analysis of bile acids in the media showed that insulin at these concentrations does not affect bile acid synthesis whereas addition and removal of dex significantly altered the production of both CA and CDCA, Fig. 22.5. Dexamethasone also increased the total production of bile acids, Table 22.3. In these experiments the expression levels of CYP7A1 and CYP27A1 did not significantly change, whereas CYP8B1 was significantly increased by dex, Fig. 22.6. 4. Out of the different conditions tested, hepatocytes cultured on EHS matrigel gave the highest production of bile acids. Although addition of dexamethasone increased the total production of bile acids, the effect on CYP8B1 and the altered CA/CDCA ratio might outweigh the benefit of increased synthesis. For in vitro studies on bile acid synthesis in primary human hepatocytes we currently recommend using EHS matrigel and a William’s medium E-based media without addition of dexamethasone. 5. We have previously investigated the time course for the formation of bile acids in human hepatocytes cultured in SWE
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Percent of total BAs
30 a,c ***
CA CDCA
a,c ***
20 *** b,d 10
b,d ***
b,d ***
*** b,d
*** a,c
*** a,c
0 Swe + dex
Swe
Std w/o dex
Std
Fig. 22.5. Bile acid production in primary hepatocytes cultured in different culture media. Bile acid levels expressed as percent of total bile acids synthesized by each liver. Mean of hepatocytes isolated from four livers ± SEM. Hepatocytes are cultured on EHS-coated plates in either Swe media, Swe media supplemented with 100 nM dexamethasone, std media without dexamethasone or in std media. ∗ p ≤ 0.05, ∗∗ p ≤ 0.01, ∗∗∗ p ≤ 0.001. a = compared to Swe, b = compared to Swe + dex, c = compared to Std w/o dex, d = compared to Std.
Table 22.3 Bile acid production in primary hepatocytes (n=4) cultured on EHS-coated plates in Swe media, Swe media supplemented with 100 nM dexamethasone, std media without dexamethasone or std media. Mean of μg bile acids/ml cell media ± SEM
Swe
CA (μg/ml)
CDCA(μg/ml)
CA/CDCA
Total BAs (μg/ml)
0.3 ± 0.08
0.3 ± 0.11
0.8
0.6
Swe + dex
0.7 ± 0.20
0.1 ± 0.03
5.5
0.8
Std w/o dex
0.3 ± 0.10
0.4 ± 0.11
0.8
0.6
Std
0.7 ± 0.21
0.1 ± 0.03
6.2
0.8
media on EHS (7). The formation was lowest on day 2, then increased four to six times on days 4 and 6, and thereafter declined slightly on day 8. Cholesterol 7α-hydroxylase mRNA levels increased several folds from days 2 to 4 and then declined. 6. Hepatocytes from different patients display different synthesis rate and the production varies a lot. In our own studies we have a range from 1 to 12 μM of total bile acids in media (7–9, 23, 24). 7. Bile acids can be separated and detected by many different methods, the most common techniques have been reviewed
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a,c *
* a,c
A.U.
0.10
Swe Swe + Dex Std w/o Dex Std
0.08 0.06 b,d *
0.04
b,d *
0.02 0.00 CYP7A1
CYP8B1
CYP27A1
Fig. 22.6. Gene expression in primary hepatocytes cultured in different culture media. Gene expression in hepatocytes cultured on EHS-coated plates in either Swe media, Swe media supplemented with 100 nM dexamethasone, std media without dexamethasone or in std media. Mean of four livers ± SEM. ∗ p ≤ 0.05, ∗∗ p ≤ 0.01, ∗∗∗ p ≤ 0.001. a = compared to Swe, b = compared to Swe + dex, c = compared to Std w/o dex, d = compared to Std.
by Scalia (25) and Roda et al. (26). Levels of the individual bile acids in cell culture media can, for example, be determined by gas chromatography (GC) or high-performance liquid chromatography (HPLC) combined with a detection system, e.g., a UV detector or mass spectrometry (MS). An established method for bile acid determination is GC-MS which is both sensitive and specific; however, the method requires deconjugation and derivatization of the samples, see protocol above. Using HPLC samples can be analyzed as intact conjugates and during recent years new methods for bile acid quantification have been developed where HPLC is combined with an MS/MS system for detection (27, 28). For a detailed description of an extensive and analytically mild method detecting all oxysterols and bile acids in the media see Axelson et al. (8). There are also commercial kits available that determine the total bile acid levels by an enzymatic reaction and absorbance measurements. References 1. Axelson, M., Mork, B., and Everson, G.T. (1991) Bile acid synthesis in cultured human hepatoblastoma cells. J. Biol. Chem. 266, 17770–17777. 2. Everson, G.T. and Polokoff, M.A. (1986) HepG2. A human hepatoblastoma cell line exhibiting defects in bile acid synthesis and conjugation. J. Biol. Chem. 261, 2197–2201. 3. Einarsson, C., Ellis, E., Abrahamsson, A., Ericzon, B.G., Bjorkhem, I., and Axelson, M. (2000) Bile acid formation in primary human
hepatocytes. World J. Gastroenterol. 6, 522–525. 4. Bravo, P., Bender, V., and Cassio, D. (1998) Efficient in vitro vectorial transport of a fluorescent conjugated bile acid analogue by polarized hepatic hybrid WIF-B and WIF-B9 cells. Hepatology 27, 576–583. 5. Decaens, C., Rodriguez, P., Bouchaud, C., and Cassio, D. (1996) Establishment of hepatic cell polarity in the rat hepatoma-human fibroblast hybrid WIF-B9. A biphasic phenomenon going from a simple epithelial
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polarized phenotype to an hepatic polarized one. J. Cell Sci. 109, 1623–1635. Monte, M.J., Badia, M.D., Serrano, M.A., Sacristan, M.P., Cassio, D., and Marin, J.J. (2001) Predominance of human versus rat phenotype in the metabolic pathways for bile acid synthesis by hybrid WIF-B9 cells. Biochim. Biophys. Acta 1534, 45–55. Ellis, E., Goodwin, B., Abrahamsson, A., Liddle, C., Mode, A., Rudling, M., Bjorkhem, I., and Einarsson, C. (1998) Bile acid synthesis in primary cultures of rat and human hepatocytes. Hepatology 27, 615–620. Axelson, M., Ellis, E., Mork, B., Garmark, K., Abrahamsson, A., Bjorkhem, I., Ericzon, B.G., and Einarsson, C. (2000) Bile acid synthesis in cultured human hepatocytes: support for an alternative biosynthetic pathway to cholic acid Hepatology 31, 1305–1312. Ellis, E., Axelson, M., Abrahamsson, A., Eggertsen, G., Thorne, A., Nowak, G., Ericzon, B.G., Bjorkhem, I., and Einarsson, C. (2003) Feedback regulation of bile acid synthesis in primary human hepatocytes: evidence that CDCA is the strongest inhibitor. Hepatology 38, 930–938. Goodwin, B., Jones, S.A., Price, R.R., Watson, M.A., McKee, D.D., Moore, L.B., Galardi, C., Wilson, J.G., Lewis, M.C., Roth, M.E., Maloney, P.R., Willson, T.M, and Kliewer, S.A. (2000) A regulatory cascade of the nuclear receptors FXR, SHP-1, and LRH-1 represses bile acid biosynthesis. Mol. Cell 6, 517–526. Holt, J.A., Luo, G., Billin, A.N., Bisi, J., McNeill, Y.Y., Kozarsky, K.F., Donahee, M., Wang, D.Y., Mansfield, T.A., Kliewer, S.A., Goodwin, B., and Jones, S.A. (2003) Definition of a novel growth factor-dependent signal cascade for the suppression of bile acid biosynthesis. Genes Dev. 17, 1581–1591. Jahan, A. and Chiang, J.Y. (2005) Cytokine regulation of human sterol 12alphahydroxylase (CYP8B1) gene. Am. J. Physiol. Gastrointest. Liver Physiol. 288, G685–G695. Li, T., Jahan, A., and Chiang, J.Y. (2006) Bile acids and cytokines inhibit the human cholesterol 7 alpha-hydroxylase gene via the JNK/c-jun pathway in human liver cells. Hepatology 43, 1202–1210. Goodwin, B., Watson, M.A., Kim, H., Miao, J., Kemper, J.K., and Kliewer, S.A. (2003) Differential regulation of rat and human CYP7A1 by the nuclear oxysterol receptor liver X receptor-alpha. Mol. Endocrinol. 17, 386–394. Strom, S.C., Pisarov, L.A., Dorko, K., Thompson, M.T., Schuetz, J.D., Schuetz,
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E.G. (1996) Use of human hepatocytes to study P450 gene induction. Methods Enzymol. 272, 388–401. Ehrmann, R.L. and Gey, G.O. (1956) The growth of cells on a transparent gel of reconstituted rat-tail collagen. J. Natl. Cancer Inst. 16, 1375–1403. Strom, S.C. and Michalopoulos, G. (1982) Collagen as a substrate for cell growth and differentiation. Methods Enzymol. 82 (Pt A), 544–555. Kleinman, H.K., McGarvey, M.L., Hassell, J.R., Star, V.L., Cannon, F.B., Laurie, G.W., and Martin, G.R. (1986) Basement membrane complexes with biological activity. Biochemistry 25, 312–318. Bjorkhem, I. and Falk, O. (1983) Assay of the major bile acids in serum by isotope dilution-mass spectrometry. Scand. J. Clin. Lab. Invest. 43, 163–170. Liu, X., LeCluyse, E.L., Brouwer, K.R., Gan, L.S., Lemasters, J.J., Stieger, B., Meier, P.J., and Brouwer, K.L. (1999) Biliary excretion in primary rat hepatocytes cultured in a collagen-sandwich configuration. Am. J. Physiol. 277, G12–G21. Kostrubsky, V.E., Ramachandran, V., Venkataramanan, R., Dorko, K., Esplen, J.E., Zhang, S., Sinclair, J.F., Wrighton, S.A., and Strom, S.C. (1999) The use of human hepatocyte cultures to study the induction of cytochrome P-450. Drug Metab. Dispos. 27, 887–894. Gardmo, C., Kotokorpi, P., Helander, H., and Mode, A. (2005) Transfection of adult primary rat hepatocytes in culture. Biochem. Pharmacol. 69, 1805–1813. Ellis, E.C. (2006) Suppression of bile acid synthesis by thyroid hormone in primary human hepatocytes. World J. Gastroenterol. 12, 4640–4645. Nilsson, L.M., Sjovall, J., Strom, S., Bodin, K., Nowak, G., Einarsson, C., and Ellis, E. (2007) Ethanol stimulates bile acid formation in primary human hepatocytes. Biochem. Biophys. Res. Commun. 364, 743–747. Scalia, S. (1995) Bile acid separation. J. Chromatogr. B Biomed. Appl. 671, 299–317. Roda, A., Piazza, F., and Baraldini, M. (1998) Separation techniques for bile salts analysis. J. Chromatogr. B Biomed. Sci. Appl. 717, 263–278. Burkard, I., von Eckardstein, A., and Rentsch, K.M. (2005) Differentiated quantification of human bile acids in serum by high-performance liquid chromatographytandem mass spectrometry. J. Chromatogr. B Analyt. Technol. Biomed. Life Sci. 826, 147–159.
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28. Ye, L., Liu, S., Wang, M., Shao, Y., and Ding, M. (2007) High-performance liquid chromatography-tandem mass spectrometry
for the analysis of bile acid profiles in serum of women with intrahepatic cholestasis of pregnancy. J. Chromatogr. B Analyt. Technol. Biomed. Life Sci. 860, 10–17.
Chapter 23 Use of Human Hepatocytes to Investigate Blood Coagulation Factor Christine Biron-Andréani, Edith Raulet, Lydiane Pichard-Garcia, and Patrick Maurel Abstract Coagulation is the complex process by which activation of plasmatic haemostasis proteins ends up with the generation of fibrin. Most of the plasma coagulation proteins are synthesized in hepatocytes. The aim of this chapter is to describe experimental procedures allowing to measure the secretion by primary human hepatocytes and functional activity (including production of fibrillar material from extracellular medium) of haemostasis proteins including factors II, V, VII, VIII, PIVKA-II (protein induced by vitK 1 absence or antagonist II), antithrombin and protein S. In addition, we show how treatments of hepatocyte cultures with vitamin K and/or warfarin affect the secretion of haemostasis proteins. The results demonstrate that primary cultures of human hepatocytes constitute an invaluable model for investigating haemostasis protein expression and activity and therapeutic strategies targeting these proteins. Key words: Human hepatocyte, long-term culture, secretion, haemostasis, coagulant activity, vitamin K1, warfarin.
1. Introduction Coagulation is the complex process by which activation of plasmatic haemostasis proteins ends up with the generation of fibrin. This process is initiated when factor VII binds through a calcium ion to its specific cell receptor tissue factor (TF) which is present on the membrane of activated endothelial cells. This complex favours the conversion of factor VII to a serine protease (factor VIIa) which has two substrates, factor IX and factor X. Factor VIIa rapidly activates factor X which, in turn, catalyses the factor Va-mediated generation of thrombin from factor II P. Maurel (ed.), Hepatocytes, Methods in Molecular Biology 640, DOI 10.1007/978-1-60761-688-7_23, © Springer Science+Business Media, LLC 2010
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(prothrombin). The complex factor VIIa-TF also activates factor IX, although more slowly. Factor IXa interacts with factor VIIIa and generates additional amounts of activated factor X, while thrombin activates factor Va, thus amplifying the generation of thrombin. Eventually, thrombin converts fibrinogen into fibrin which is stabilized by activated factor XIII. Under normal conditions, coagulation is regulated by various system inhibitors including natural inhibitors (antithrombin, protein C and protein S), and the tissue factor pathway inhibitor (1). Several proteins including factors II, VII, IX, X, proteins C and protein S require a post-translational activation step, that is, gamma-carboxylation of glutamic residues. This carboxylation step which is mandatory for calcium ion binding and full activity of these factors and proteins is catalysed by the vitamin K1-dependent gamma glutamyl carboxylase (2, 3). The reduced form of vitamin K1 (vitamin K1 hydroquinone generated by the vitamin K epoxide reductase) is the cofactor of gamma glutamyl carboxylase and is converted to vitamin K1 epoxide during the reaction, so that carboxylation and epoxidation are tightly coupled. Vitamin K1 epoxide is then re-converted to vitamin K1 by vitamin K epoxide reductase. Vitamin K1 has been the target of pharmaceutical approaches for the prevention and treatment of thromboembolism. In this respect, warfarin and other coumarin drugs have been developed. Warfarin (and derivatives or analogs) inhibits vitamin K epoxide reductase, thus leading to decreased concentration of vitamin K1 and vitamin K1 hydroquinone, so that the carboxylation reaction is strongly reduced and the coagulation process is inhibited (4, 5). The liver plays a major role in haemostasis since it is responsible for the synthesis and metabolism of most of the plasma coagulation proteins including fibrinogen, factor II, factor V, factor VII, factors IX–XII, proteins C and S (6). Previous studies with isolated perfused rat liver have been instrumental in this respect (7–9). Then, the use of primary hepatocyte cultures from rodents allows to confirm that hepatocyte was the site of production of haemostasis proteins such as fibronectin, fibrinogen, factor V, factor XII, antithrombin and plasminogen activators or inhibitors (10–17). However, data on synthesis and secretion of haemostasis proteins from human hepatocytes in primary cultures remain very limited (18–21). The aim of this chapter is to describe experimental procedures allowing to evaluate the secretion by primary human hepatocytes and functional activity (including production of fibrillar material from extracellular medium) of haemostasis proteins including factors II, V, VII, VIII, PIVKA-II (protein induced by vitK 1 absence or antagonist II), antithrombin and protein S. In addition, we show how treatments of hepatocyte cultures with vitamin K and/or warfarin affect the secretion of haemostasis proteins.
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The results demonstrate that primary cultures of human hepatocytes constitute an invaluable model for investigating haemostasis protein expression and activity and therapeutic strategies targeting these proteins.
2. Materials 2.1. Human Liver Samples 2.2. Materials and Reagents
See Section 2.1 of Chapter 12, this volume. 1. See Sections 2.2 and 2.3 of Chapter 12, this volume, for reagents used in hepatocyte preparation and culture. 2. Vitamin K1, warfarin and dimethylsulphoxide (DMSO) are from Sigma, Saint Quentin Fallavier, France.
2.3. Hepatocyte Preparation and Culture
1. See Section 2.4 of Chapter 12, this volume. 2. Vitamin K 1 solution is prepared in DMSO and added to the cell culture medium at a final concentration of 50 ng/mL (see Note 1). 3. Warfarin solution is prepared in DMSO and added to the cell culture medium at a final concentration of 0.05, 0.5 and 5 μM.
2.4. Hepatocyte Culture Media
We use two different chemically and hormonally defined culture media for short-term (approximately 1 week) or longterm (approximately 1 month) cultures. The short-term culture medium is used for hepatocytes preparation and plating. Other investigations are carried out in the long-term culture medium.
2.4.1. Short-Term Culture Medium
1. Ham-F12 medium: Dissolve the amount of powdered medium required for 5 L in approximately 4.5 L of deionized water. Add 5.88 g NaHCO3 and, after 15 min bubbling with a mixture of 95% O2 and 5% CO2 , adjust to pH 7.4. Adjust volume to 5 L. 2. William’s medium E: Dissolve the amount of powdered medium required for 5 L in approximately 4.5 L deionized water. Add 11 g NaHCO3 and, after 15 min bubbling with a mixture of 95% O2 and 5% CO2 , adjust to pH 7.4. Adjust volume to 5 L. 3. Combine Ham-F12 and William’s E media and sterilize by passing through a 0.22-μm filter. The mixture is kept refrigerated in the dark in 1-L stoppered bottles. Ham-F12 and William’s E media may also be purchased (but at a higher price) as liquid media.
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4. The mix of additives (see Section 2.3.2) for complementing 25 L of Ham-F12/William’s E medium is prepared by combining the three submixes, 1, 2 and 3, and 75 mL of sterile fungizone solution (total volume 925 mL) (see Note 2). The mix is aliquoted in 37 mL fractions and store at −80◦ C. 5. The final chemically and hormonally defined short-term culture medium is prepared just before use by supplementing 1 L Ham-F12/William’s E medium with 37 mL mix and 2 mL vitamin C solution. 2.4.2. Submixes of Additives for the Short-Term Culture Medium
1. Submix 1: 8.75 g glutamine, 31.5 g glucose, 2.5×106 units penicillin and 2.5 g streptomycin are first dissolved in 500 mL water and the solution is sterilized through 0.22-μm filters. 2. Submix 2: 1.1 g sodium pyruvate, 1 mg dexamethasone (dissolved in 500 μL ethanol) and 1.25 g transferrin are dissolved in a final volume of 75 mL water. 3. Submix 3: 100 μL ethanolamine, 50 mg insulin (dissolved in 10 mL water containing 100 μL glacial acetic acid), 5 mg glucagon (dissolved in 10 mL water containing 100 μL of 1 M NaOH) and 37.5 mg linoleic acid are dissolved in a final volume of 25 mL water. 4. Vitamin C solution: 50 mg in 2 mL water. Sterilized by passing through a 0.22-μm filter. Prepare just before use.
2.4.3. Long-Term Culture Medium
1. Dissolve one 5-L doses powdered William’s E medium in approx. 4 L deionized water. Add 11.9 g HEPES and 11 g NaHCO3 and adjust to pH 7.2. Adjust volume to 5 L. 2. Sterilize by passing through a 0.22-μm filter and keep refrigerated in the dark in 500 mL stoppered bottles. 3. The mix of additives for complementing 5 L of William’s E medium is prepared by adding in a final volume of 250 mL of William’s E medium: 10 mL BSA–linoleic–linolenic solution, 5 mL insulin solution (50 mg), 1 mL transferin solution (25 mg), 50 μL selenium acetate solution (64 μg), 200 μL dexamethasone solution (0.2 mg), 100 μL liver growth factor solution (100 μg), 250 μL cAMP solution (12.25 mg), 500 μL prolactin solution (50 UI), 100 μL ethanolamine solution (0.3 μg), 5 mL glucagon solution (5 mg), 250 μL epidermal growth factor solution (250 μg), 50 mL glutamine solution (1.46 g), 50 mL penicilline/streptomycin solution (500,000 U and 500 mg). The mix is sterilized by passing through a 0.22-μm filter (PES, Nalgene). Add 15 mL sterile fungizone. The mix is aliquoted in 25 mL fractions and stored at −80◦ C.
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4. The final chemically and hormonally defined long-term culture medium is prepared just before use by supplementing 500 mL of William’s E medium with 25 mL of mix. 2.4.4. Additives for Preparing the Mix for the Long-Term Culture Medium
1. BSA–linoleic–linolenic acid solution: dissolve 1 g BSA (fraction V) in a final volume of 10 mL PBS (phosphate buffered saline). Add 20 μL linoleic acid and 20 μL linolenic acid. 2. Insulin: 100 mg in 10 mL 1% acetic acid. 3. Transferrin: 100 mg in 4 mL water. 4. Selenium acetate: 6.45 mg in 5 mL water. 5. Dexamethasone: 1 mg in 1 mL dimethylsulphoxide (DMSO). 6. Liver growth factor: 500 μg in 500 μL William’s E medium. 7. Cyclic AMP (N6,2 -O-dibutyryladenosine 3 -5 cyclic monophosphate): 49 mg in 1 mL water. 8. Prolactin (luteotropic hormone): 250 UI in 2.5 mL 10 mM chlorhydric acid. 9. Ethanolamine: 3 μL in 1 mL DMSO. 10. Glucagon: 5 mg in 5 mL water. 11. Epidermal growth factor: 500 μg in 500 μL water. 12. Glutamine solution: 200 mM (Sigma).
2.5. Collagenase Solution 2.6. Enzyme-Linked ImmunoSorbent Assay (ELISA) for Quantification of Factor II Antigen and Antithrombin Antigen
See Section 2.5 of Chapter 12, this volume. 1. Microplates, 96-well Immulon 4-HBX (Labsystems). 2. Coating buffer: 50 mM sodium carbonate (1.59 g of Na2 CO3 and 2.93 g of NaHCO3 up to 1 L. Adjust pH to 9.6). 3. Phosphate buffered saline, PBS. Dissolve 8.0 g NaCl, 1.15 g Na2 HPO3 in 1 L H2 O; adjusted at pH 7.4. 4. Washing buffer: PBS–Tween (0.1%, v/v): add 1 mL of Tween 20 (pH 7.4) to 1 L of PBS. 5. Sample diluent: HEPES–BSA–Tween 20: 5.95 g HEPES (free acid), 1.46 g NaCl, 2.5 g BSA (Bovine Serum Albumin) dissolved in 200 mL H2 O. Add 0.25 mL of Tween20, check and adjust pH to 7.2 with NaOH, then make up to a final volume of 250 mL with H2 O. Aliquot and store frozen at −20◦ C. 6. Substrate buffer: citrate-phosphate buffer pH 5.0, 2.6 g citric acid and 6.9 g Na2 HPO3 up to final volume of 500 mL with H2 O.
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7. O-Phenylenediamine substrate (OPD). Dissolve immediately before use 5 mg OPD in 12 mL substrate buffer then add 12 μL 30% H2 O2 (see Note 3). 8. Capture antibodies: polyclonal affinity purified anti-human FII or anti-antithrombin antibody (Kordia, Leiden, The Netherlands). 9. Detecting antibodies: peroxidase-conjugated sheep polyclonal anti-human FII or anti-antithrombin antibody (Kordia, Leiden, The Netherlands). 10. “Reference plasma” (see Note 4). 11. Equipment needed for all the ELISA assays for FII, FV, FVII, PIVKA-II and AT antigens. Multichannel pipets, plate-washing equipment and plate optical density reader set at 492 nm. 2.7. Enzyme-Linked ImmunoSorbent Assay (ELISA) for Quantification of Factor V Antigen
Complete commercial ELISA kit for the assay of factor V is used after adaptation to detect low values. In our experiments, we use the ZYMUTEST Factor V kit (Hyphen BioMed, Andresy, France) which is a two-side immuno-assay for measuring human factor V antigen in plasma or in any fluid where factor V is present. 1. Capture antibodies: monoclonal anti-human FV. 2. Detecting antibodies: peroxidase-conjugated horse polyclonal anti-human FV. 3. Reagent preparation, storage and stability are performed according to the recommendations of the manufacturer.
2.8. Enzyme-Linked ImmunoSorbent Assay (ELISA) for Quantification of Factor VII Antigen, Factor VIII Antigen, Protein Induced by vitK 1 Absence or Antagonist II Antigen (PIVKA-II:Ag) and Free Protein S Antigen
2.9. Coagulant Activity
Complete commercial ELISA kit for the assay of these factors is used after adaptation to detect low values. In our experiments, we R use the sandwich ELISA Asserachrom (Diagnostica Stago). 1. Capture antibodies: polyclonal anti-human FVII, monoclonal anti-human FVIII or anti-human PIVKA-II, or antihuman-free protein S. 2. Detecting antibodies: peroxidase-conjugated rabbit polyclonal anti-human FVII and anti-PIVKA-II, and peroxidaseconjugated mouse polyclonal anti-human FVIII and antihuman-free protein S. 3. Reagent preparation, storage and stability are performed according to the recommendations of the manufacturer. 1. Deficient plasmas (Diagnostica Stago, Asnières, France) which are immuno-depleted (STA-deficient II, STAdeficient V, STA-deficient VII) (see Note 5). 2. Human tissue thromboplastin Thromborel S from Dade Behring (Marburg, Germany) reconstituted as
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recommended by the manufacturer, warmed at 37◦ C during 30 min. 3. Calibration: the standard curve is obtained with dilutions R , Diagnostica Stago, of a reference plasma (Unicalibrator Asnières, France). The results are expressed in mIU/mL (see Note 6). 4. Controls are performed using dilutions of reference plasma R (Control N+P , Dignostica Stago). The mean normal plasma concentration is 100 μg/mL for FII, 10 μg/mL for FV and 0.5 μg/mL for FVII corresponding to 1 IU/mL. 5. Owren Koller buffer (pH 7.35 Veronal acetate saline buffer) (Diagnostica Stago) (see Note 7). 6. All the tests are performed in duplicate on a coagulation device (STA, Diagnostica Stago) and the results expressed in mIU/mL. 2.10. Immunofluorescence Staining of the Fibrillar Material
1. Human tissue thromboplastin (Thromborel S) reconstituted as recommended by the manufacturer) warmed at 37◦ C during 30 min. 2. Owren Koller buffer (Diagnostica Stago). 3. Glass slides for fibrin filament fixation. 4. Washing buffer: PBS (8.0 g NaCl, 1.15 g Na2 HPO3 up to 1 L, pH 7.4). 5. Blockage buffer: PBS–Bovine Serum Albumin (BSA) 2%. 6. Fluorescein isothiocyanate (FITC)-conjugated rabbit antihuman fibrinogen antibody (Dakopatts AB, Glostrup, Denmark) (dilution 1/50) (see Note 8). 7. Antibody dilution buffer: PBS–BSA 2%. 8. Controls include omission of the antibody and a rabbit isotype F(ab’)2 -FITC (Dakopatts AB, Glostrup, Denmark) as negative control and a 1/1,000-fold dilution of normal human plasma in Owren Koller buffer as a positive control. 9. Microscope slides. 10. Mounting medium: PBS pH 8, glycerol 50%. 11. Fluorescence microscope: Leica DMRA (Leica Microsystems, Wittzlar, Germany).
3. Methods 3.1. Preparation of Hepatocytes
1. SeeSections 3.1.1 and 3.1.2 of Chapter 12, this volume.
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2. At the end of the collagenase perfusion, the liver sample is transferred into a new stainless steel vessel, the Glisson’s capsula is opened in several places. 3. The tissue is gently disrupted with scissors. 4. The homogenate is complemented with 1 L of BSA–HEPES buffer. The procedures 1–3 must be carried out as quickly as possible to inactivate collagenase. 5. The homogenate is filtered through a nylon filter (250 mesh) and the filtrate is distributed into 150 mL centrifuge tubes. The filter is washed twice with approximately 200 mL of BSA–HEPES solution to collect the cells that are trapped in the undissociated tissue homogenate. 6. Tubes are centrifuged for 5 min at 50×g at room temperature to pellet hepatocytes. 7. The supernatant is collected (seeChapter 12, this volume, for progenitor preparation) and the pellet, representing the hepatocytes, is gently resuspended in 200 mL of BSA– HEPES solution per tube by five successive up and down runs with a pipet. 8. Steps 6 and 7 are repeated twice. At the end of the last centrifugation, the yield of the preparation may be roughly estimated by measuring the volume of the pellet: 1 mL of pellet represents approximately 108 cells. For more precise counting of cells, see next steps. 9. At the end of the last washing, the pellet is resuspended in an equal volume of BSA–HEPES solution and homogenized gently with a pipet as described in Step 7. 10. 500 μL of hepatocyte suspension is dispersed in 9.5 mL of the short-term culture medium. 250 μL of this suspension is placed in a polystyrene tube and supplemented with 50 μL of a 1% Trypan blue solution. After 2 min at room temperature, a 10-μL aliquot of this suspension is placed in the compartment of a haemocytometer cell for counting. 11. Yield and viability of cells are classically evaluated by examination under a microscope using the Trypan blue exclusion test. In our hands, the yield and viability are, on average, 7×106 cells/g of liver tissue and 85%, respectively (see Note 9). 3.2. Hepatocyte Plating and Culture
1. After evaluation of yield and viability, an appropriate amount of short-term culture medium is complemented with foetal calf serum (2.5% in volume). 2. The hepatocyte suspension is diluted in this medium to 106 viable cells/mL. The number of cells per dish corresponds approximately to a cell density of 12.5×104 cells/cm2 for a
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confluent monolayer (see Note 10). Care must be taken to rehomogenize cell suspension frequently by gentle circular agitation while distributing to the culture dish. 3. Cells are evenly distributed on the dish by gentle agitation (see Note 11). 4. Culture dishes are then placed in an incubator, in a humid atmosphere of air 5% CO2 at 37◦ C. 5. After 12 h, the serum-supplemented medium is discarded and replaced with new serum-free long-term culture medium (see Note 12). 6. The long-term culture medium is supplemented with 50 ng/mL vitamin K1, or 0.05, 0.5, or 5 μM warfarin, or both (final DMSO concentration: 0.2%) and is renewed every 24 or 72 h, depending on experiments. Control cultures are maintained in the presence of 0.2% DMSO. 3.3. Preparation of Samples for Assays for Quantification of Haemostasis Proteins by Enzyme-Linked ImmunoSorbent Assay or for Functional Assays 3.4. Enzyme-Linked ImmunoSorbent Assay (ELISA)
At selected times, an aliquot of medium is collected into trisodium citrate anticoagulant tubes from two different dishes, mixed, centrifuged 15 min at 3,500×g and stored at −80◦ C until analysis. Before starting the assay, test samples and reference plasma must be thawed at 37◦ C quickly and gently vortexed.
3.5. Coagulant Activity Measurement
The percentage of factor activity present in the medium is determined by the degree of correction of the clotting time when the medium is added to the substrate plasma. The clotting time obtained in the mixture is compared to the clotting time obtained with the dilutions of the reference (normal) plasma. Since overor under-estimation could occur (non-specific proteolysis or activation) it is very important to correlate results obtained from activity-based assays to those obtained from ELISA (Fig. 23.1). FII (FII:C), FV (FV:C), or FVII (FVII:C) activity is determined by a one-stage chronometric assay. 1. Calibration: a calibration curve for each test run is performed with STA unicalibrator. The unicalibrator is prepared according to the recommendations of the manufacturer. The exact concentration is indicated on the flyer provided. A complete dose–response curve by several dilutions of reference plasma is made (see Note 15). The standards are
The commercial kit is used according to the recommendations of the manufacturers (see Note 13). Only calibration curve must be adapted to detect low values according to the factor concentration indicated in the flyer provided in the kit for the calibrator. The tested sample dilution is then modified (see Note 14). Factor expression in hepatocyte culture medium is shown in Figs. 23.1, 23.2 and 23.3.
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F I I:C
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Fig. 23.1. Plasma coagulation factor expression and activity in extracellular medium. Hepatocytes were plated and cultured in long-term culture conditions as described. The culture medium was collected every 3 days (and replaced with fresh medium) and aliquots were analysed for factor II, V and VII antigen expression (in ng/million cells, black squares) and activity (in IU/mL of culture medium, crosses).
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Fig. 23.2. Effect of vitamin K1 on factor II and PIVKA expression in extracellular medium. Hepatocytes were plated and cultured in long-term culture conditions as described. At day 0 of experiment, cells were treated or not with 50 ng/mL vitamin K1 (0.11 μM). The culture medium was collected every day (and replaced with fresh medium) and aliquots were analysed for factor II (black squares and circles) and PIVKA-II (grey squares and circles) antigen expression (in ng/million cells).
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Fig. 23.3. Effect of vitamin K1 and warfarin on plasma coagulation factor expression in extracellular medium. Hepatocytes were plated and cultured in long-term culture conditions as described. Treatments started 2 days after plating. Cells were cultured in the absence or presence of 50 ng/mL vitamin K1 (0.11 μM) for all duration of experiment. At day 6, warfarin (0.05, 0.5 or 5 μM final concentration) was added to the culture medium and the culture was continued for 3 days; control cultures did not receive warfarin (0). At day 9, culture medium was collected and analysed for PIVKA-II, factor VII, II or protein S antigens. Factor levels were normalized with respect to control conditions (no vitamin K1 and no warfarin) taken arbitrarily at 100.
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automatically prepared by the analyser by dilution with Owren Koller according to the informations entered in the instrument for the assay. 2. The extracellular medium samples are assayed without dilution. 3. Controls are performed using dilutions of plasma controls in order to be able to measure low values between 0.01 and 0.1 mU/mL. 3.6. Immunofluorescence Staining of the Fibrillar Material
1. Prewarm tubes at 37◦ C. 2. 100 μL of Thromborel S (reconstituted as recommended by the manufacturer and warmed at 37◦ C during 30 min) are added to 500 μL of the culture medium or 1/1,000 diluted normal human plasma as control (see below). 3. After various time points (12, 24 and 48 h), the fibrillar material is isolated and removed gently. 4. After centrifugation at 600 rpm (500 g) for 10 min, the material is settled on microscope slides. In order to avoid non-specific interaction with the antibody, the slides are pretreated with a PBS–BSA solution for 15 min at room temperature. The material is incubated for 1 h at room
Fig. 23.4. Monitoring of the fibrin/fibrinogen network obtained with the extracellular medium. Hepatocytes were plated and cultured in long-term culture conditions as described. At day 22, the culture medium was collected and assayed for fibrillar network formation. (A) Fibrin/fibrinogen network obtained from culture medium; (B) fibrin/fibrinogen network obtained from control human plasma.
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temperature with the fluorochrome-conjugated rabbit antihuman fibrinogen antibody (dilution 1/50). 5. Controls include omission of the antibody as negative control and a 1/1,000-fold dilution of normal human plasma in Owren Koller buffer as a positive control. 6. The slides are examined under a microscope (Fig. 23.4).
4. Notes 1. Vitamin K is photosensitive and should be kept in the dark, and tubes should be protected by aluminium foil. 2. Because of the numerous additives required to supplement the basal culture medium, it is recommended to prepare a concentrated solution of all the additives, in either one or several submixes. 3. The colourless OPD/H2 O2 solution is stable for only 1 h at room temperature. 4. The reference plasma is a commercial normal plasma calibrated against international standards (WHO, National Institute for Biological Standards and Control (NIBSC)). An alternative source of reference plasma is plasma pooled from a suitable number of healthy donors (15 or more donors seem to be adequate). By definition it will contain 100% of normal activity of 1 U/mL. 5. Deficient plasmas obtained by immunodepletion are currently used to measure the levels of a specific factor. The choice of an artificial depleted substrate instead of a congenital deficiency is dictated by economic, safety and ethical decisions. Only deficient plasmas with factor content <0.01 U/mL must be accepted. To detect low values which can be expected in supernatant, it is important to carry out a “blank”, i.e. sample replaced by buffer to verify the complete depletion in the specific factor. 6. By definition normal activity of 1 U/mL corresponds to 100%. 7. Owren or imidazole buffer (3.4 g/L imidazole, 5.85 g/L NaCl, pH 7.4) are both suitable for this purpose. 8. The fluorochrome-conjugated rabbit anti-human fibrinogen antibody reacts with fibrin, fibrinogen and fibrinogen fragments. 9. As a general rule, we have observed that the quicker the procedure for the isolation of hepatocytes, the better the quality of cells and subsequent cultures. Therefore,
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isolation must be performed as rapidly as possible. Indeed, here, time is quality! Nevertheless, the yield and viability are widely variable from one sample to another and range between 1 and 10×109 cells, and 70 and 90%, respectively. The reasons for this variability are difficult to identify: parameters such as duration of cold ischaemia, health status of the liver, pathology, formation of intra-tissue clots or quality of perfusion (number and state of vessels used for perfusing) could possibly be involved. 10. The differentiated phenotype of hepatocytes is maintained in confluent but not in subconfluent cultures. Establishment of a homogeneous confluent cell monolayer throughout the dish is therefore critical. Once the dishes present on one tray are supplemented with culture medium and cells, the tray is held horizontally and gently agitated from left to right (1 cycle/s for 10 s) and back and forth (1 cycle/s for 10 s) with a pause of 5 s in between. This allows the suspension to be spread homogeneously on the dish and avoids rotational movement of the suspension which would result in preferential distribution of cells towards the periphery of the dish with low density in the centre. 11. The culture medium must be aspirated and poured gently to avoid detachment of cells. Medium changes will be facilitated by placing the trays on an inclined plane. 12. Phenotype characterization. Several markers of hepatic phenotype have been investigated and shown to be maintained in our cultures for at least a week (short-term cultures) and 5 weeks (long-term cultures) (22). 13. The enzymatic reaction resulting in colour development which starts with the addition of the OPD/H2 O2 must last exactly 3 min. 14. For example, the calibrator of the Zymutest FV is 92% (0.92 IU/mL). The standard solution with 0.25 mL of FV calibrator and 0.75 mL of FV sample diluent corresponds to 0.23 IU/mL which could be the first point of the low curve calibration. The sample dilution is 1/10 instead of 1/50. For FII:Ag the optimal dilution chosen is 1/100, for FVII:Ag 1/5, AT:Ag 1/50 and FVIII:Ag 1/1. 15. For choosing the most suitable standard dilutions it is advisable to inspect the dose–response curve and choose at least three dilutions which lie on the steeper and linear part of the curve. The dilution of the samples should be chosen in accordance with the expected factor activity. To avoid the time-trend deterioration of samples and reagents, the quicker the procedure, the better the quality. It is also advisable to take replicate readings in a balanced order.
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References 1. Tripodi, A. and Mannucci, P.M. (2007) Abnormalities of hemostasis in chronic liver disease: reappraisal of their clinical significance and need for clinical and laboratory research. J. Hepatol. 46, 727–733. 2. Merli, G.J. and Fink, J. (2008) Vitamin K and thrombosis. Vitam. Horm. 78, 265–279. 3. Wallin, R., Wajih, N., and Hutson, S.M. (2008) VKORC1: a warfarin-sensitive enzyme in vitamin K metabolism and biosynthesis of vitamin K-dependent blood coagulation factors. Vitam. Horm. 78, 227–246. 4. D’Andrea, G., D’Ambrosio, R., and Margaglione, M. (2008) Oral anticoagulants: pharmacogenetics relationship between genetic and non-genetic factors. Blood Rev. 22, 127–140. 5. Schulman, S. and Bijsterveld, N.R. (2007) Anticoagulants and their reversal. Transfus. Med. Rev. 21, 37–48. 6. Heinrich, J. and George, J. (2001) Hemostatic abnormalities in liver and renal disease, in Hemostasis and Thrombosis (Colman, R.W., Hirsh, J., Marder, A.W., Clowes, A.W., and George, J.N., eds.), Lippincott Williams & Wilkins, Philadelphia, pp. 955–960. 7. Dodds, W.J. (1969) Storage, release, and synthesis of coagulation factors in isolated perfused organs. Am. J. Physiol. 217, 879–883. 8. Olson, J.P., Miller, L.L., and Troup, S.B. (1966) Synthesis of clotting factors by the isolated perfused rat liver. J. Clin. Invest. 45, 690–701. 9. Owen, C.A., Jr. and Bowie, E.J. (1977) Generation of coagulation factors V, XI, and XII by the isolated rat liver. Haemostasis 6, 205–212. 10. Gordon, E.M., Gallagher, C.A., Johnson, T.R., Blossey, B.K., and Ilan, J. (1990) Hepatocytes express blood coagulation factor XII (Hageman factor). J. Lab. Clin. Med. 115, 463–469. 11. Hoffman, M., Fuchs, H.E., and Pizzo, S.V. (1986) The macrophage-mediated regulation of hepatocyte synthesis of antithrombin III and alpha 1-proteinase inhibitor. Thromb. Res. 41, 707–715. 12. Mazzorana, M., Cornillon, B., Baffet, G., Hubert, N., Belleville, J., Eloy, R., and Guguen-Guillouzo, C. (1989) Biosynthesis of factor V by normal adult rat hepatocytes. Thromb. Res. 54, 655–675.
13. Odenthal, M., Neubauer, K., Baralle, F.E., Peters, H., Meyer zum Buschenfelde, K.H., and Ramadori, G. (1992) Rat hepatocytes in primary culture synthesize and secrete cellular fibronectin. Exp. Cell Res. 203, 289–296. 14. Otto, J.M., Grenett, H.E., and Fuller, G.M. (1987) The coordinated regulation of fibrinogen gene transcription by hepatocytestimulating factor and dexamethasone. J. Cell Biol. 105, 1067–1072. 15. Stamatoglou, S.C., Hughes, R.C., and Lindahl, U. (1987) Rat hepatocytes in serumfree primary culture elaborate an extensive extracellular matrix containing fibrin and fibronectin. J. Cell Biol. 105, 2417–2425. 16. Uno, S., Nakamura, M., Seki, T., and Ariga, T. (1997) Induction of tissue-type plasminogen activator (tPA) and type-1 plasminogen activator inhibitor (PAI-1) as early growth responses in rat hepatocytes in primary culture. Biochem. Biophys. Res. Commun. 239, 123–128. 17. Yagi, K., Yamada, C., Serada, M., Sumiyoshi, N., Michibayashi, N., Miura, Y., and Mizoguchi, T. (1995) Reciprocal regulation of prothrombin secretion and tyrosine aminotransferase induction in hepatocytes. Eur. J. Biochem. 227, 753–756. 18. Biron-Andreani, C., Bezat-Bouchahda, C., Raulet, E., Pichard-Garcia, L., Fabre, J.M., Saric, J., Baulieux, J., Schved, J.F., and Maurel, P. (2004) Secretion of functional plasma haemostasis proteins in long-term primary cultures of human hepatocytes. Br. J. Haematol. 125, 638–646. 19. Ferrini, J.B., Pichard, L., Domergue, J., and Maurel, P. (1997) Long-term primary cultures of adult human hepatocytes. Chem. Biol. Interact. 107, 31–45. 20. Ingerslev, J., Christiansen, B.S., Heickendorff, L., and Munck Petersen, C. (1988) Synthesis of factor VIII in human hepatocytes in culture. Thromb. Haemost. 60, 387–391. 21. Mazzorana, M., Baffet, G., Kneip, B., Launois, B., and Guguen-Guillouzo, C. (1991) Expression of coagulation factor V gene by normal adult human hepatocytes in primary culture. Br. J. Haematol. 78, 229–235. 22. Pichard, L., Raulet, E., Fabre, G., Ferrini, J.B., Ourlin, J.C., and Maurel, P. (2006) Human hepatocyte culture. Methods Mol. Biol. 320, 283–293.
Chapter 24 Use of Human Hepatocytes to Investigate HCV Infection Lydiane Pichard-Garcia, Philippe Briolotti, Dominique Larrey, Antonio Sa-Cunha, Bertrand Suc, Sylvain Laporte, and Patrick Maurel Abstract Investigations on the biology of hepatitis C virus (HCV) have been hampered by the lack of small animal models. Efforts have therefore been directed to designing practical and robust cellular models of human origin able to support HCV replication and production in a reproducible and physiologically pertinent manner. Different systems have been constructed based on hepatoma or other cell lines, sub-genomic and genomic replicons, productive replicons, and immortalized hepatocytes. Although these models are practical for high-throughput screenings, they present several drawbacks related to the nature of the virions and the fact that the cells are not differentiated. Adult primary human hepatocytes infected with natural serum-derived HCV virions represent the model that most closely mimics the physiological situation. This chapter describes our experience with this culture model. Key words: Hepatitis C virus, interferon, infection, host response.
1. Introduction Within the last 20 years, hepatitis C has emerged as a common liver disease and approximately 170 million people are thought to be infected worldwide. Hepatitis C virus (HCV) infection is characterized by viral persistence and chronic liver disease in approximately 80% of cases. The complications of chronic hepatitis C include cirrhosis in 20% of cases and hepatocellular carcinoma, which has an incidence of up to 4–5% per year in patients with HCV-related cirrhosis (1, 2). Hepatitis C-related end-stage liver
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disease is now the principal indication for liver transplantation in industrialized countries. Efficient vaccine against HCV does not exist, and the only available treatment which associates pegylated interferon α (IFN) and ribavirine is efficient only in 50% of patients chronically infected with a virus of genotype 1 (the most frequent in Europe, Japan, and North America) or 4 and in approximately 80% of the patients infected with a virus of genotypes 2 and 3 (3). Investigations on the biology of HCV and development of therapeutic strategies against this virus have been hampered by the lack of animal model and of practical and robust cellular models of human origin able to support HCV replication and production in a reproducible and consistent manner. Different systems including cells and forms of virus have been constructed or worked out based on hepatoma or other cell lines, sub-genomic and genomic replicons, productive replicons, immortalized hepatocytes, and fetal and adult primary human hepatocytes (4–9). However, these models all present with both advantages and disadvantages (10). For instance, replicon systems are very practical for large screenings but present several drawbacks related to the nature of the virions and the fact that the cells are not differentiated. On the other hand, primary human hepatocytes (PHH) infected with serum-derived virions most closely mimic the physiological situation, although this model is difficult to use and not practical for large screenings. In 1998, we were the first group to report that primary cultures of human hepatocytes constitute a model to investigate serum-derived HCV (HCVser) infection (9). Since then, several groups have reported and confirmed that PHH are sensitive to natural HCVser lipoviroparticles infection and permissive to viral genome replication (11–14). Although the performances of these culture systems vary from one laboratory to another, depending on cell culture conditions, reported results are consistent and reproducible. HCV infection of PHH with natural different genotypes (from 1 to 5) has been assessed by detection of negative (replicative) RNA strand, increased intracellular accumulation of genomic RNA, production of infectious virions, generation of new quasi-species in culture, and inhibition of replication by IFN (9, 11–17). In addition, PHH were also shown to be infected by HCV-pseudotyped particles (18) and by Huh-7.5/JFH1-derived HCVcc particles (16). This model is clearly the one that most closely mimics the physiological situation. In this chapter, we are describing our experience with the in vitro infection of highly differentiated primary human hepatocytes by HCVser and HCVcc, viral particle production, and innate response of hepatocytes to IFN and HCV infection.
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2. Materials 2.1. Human Hepatocyte Culture
1. See Chapter 23 of this volume for the preparation of hepatocytes. 2. Hepatocytes are plated at confluence in culture dishes (6-, 12-, or 24-well plates) precoated with type I collagen (Beckton Dickinson) in our short-term culture medium (see Section 2.4.1 of Chapter 24) for the first 12 h in the presence of 5% fetal calf serum tested for hepatocyte cultures. 3. The standard medium is then replaced with our long-term serum-free culture medium (see Section 2.4.3 of Chapter 23).
2.2. Bank of HCV-Positive Serum Samples
1. Blood samples are collected from patients (after signing informed consent) who are anti-HCV antibody positive as detected by the Ortho HCV 3.0 Elisa test system with enhanced SAVe (Ortho-Clinical Diagnostics, Bucks, UK). 2. Serum samples are prepared by centrifugation for 10 min at 15◦ C (2,500 rpm) and stored at −80◦ C until use in an L3 confinement laboratory (L3). 3. In each serum sample, HCV RNA is genotyped by R HCV genotype assay (LiPA) designed the VERSANT to identify HCV genotypes 1–6 (Bayer Corporation, Tarrytown, NY, USA) and quantified by the COBAS AmpliPrep/COBAS TaqMan HCV test (Roche Diagnostics, Meylan, France). 4. None of the patients had received antiviral therapy prior to blood collection, and none is co-infected with HBV or HIV. 5. The term HCVser is used when referring to natural HCV particles from patient serum.
2.3. Production of Huh7.5/JFH1-Derived HCVcc Particles
1. Plasmid harboring the full-length JFH1 RNA transcription (pFGR-JFH1) has been kindly provided by Dr. T. Wakita (National Institute of Infectious Diseases, Department of Virology II, Tokyo, Japan) (6). 2. Plasmid pFGR-JFH1 is digested for 1–2 h with XbaI at 37◦ C (New England Biolabs). 3. The digestion product is chloroforme–isoamyl alcohol extraction, and finally ethanol pended in RNase-free water TX).
then purified (phenol– extraction, chloroform precipitation) and resus(Ambion, Inc., Austin,
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4. Following treatment with Mung Bean Nuclease (New England BioLabs) for 30 min at 30◦ C and purification, the linearized DNA is resuspended in RNase-free water. 5. In vitro transcript is generated at 37◦ C for 3 h using a MEGAscript T7 kit (Ambion, Inc., Austin, TX). 6. DNase I (included in the kit) is added for 15 min at 37◦ C. The reaction is stopped and the RNA is then purified with TRIzol LS (Invitrogen), according to the instructions of the manufacturer. 7. Transcript RNA is quantified by measurement absorbance at 260 nm. 8. Huh-7.5 cells have been kindly provided by Dr. C. Rice (Rockefeller University, New York) (7) and cultured in DMEN (Invitrogen), 10% fetal bovine serum (heat inactivated at 55◦ C for 30 min), 1X non-essential amino acids (Invitrogen), Penn/Strep (Invitrogen). 9. JFH1 RNA transcript is delivered to Huh-7.5 cells by electroporation (19). Viral stocks of HCVcc particles are obtained by harvesting cell culture supernatants for 72 h post-transfection. 10. Secondary viral stocks are obtained by additional amplifications on naive Huh-7.5 cells (20). For this purpose, Huh7.5 cells are plated in the presence of HCVcc at 0.05–0.1 HCV genome equivalent/cell (Geq/cell). After 24 h, cells are washed extensively and left to grow up to 70–80% confluence. 11. At this stage, cells are collected in trypsin/EDTA 0.05% (Invitrogen) and replated under one-third to one-fifth splitting and again left to reach 70–80% confluence. Trypsination and plating are repeated once. After 24 h, supernatant is collected and analyzed for JFH1 HCV RNA (typical range: 4×106 RNA copies/ml). 11. Small aliquots (100 μl) of supernatant are frozen at −80◦ C and used subsequently to infect Huh-7.5 cells and human hepatocytes. 2.4. Materials and Reagents
1. Guanidium isothiocyanate–acid phenol extraction solution (RNAble; Eurobio, Les Ulis, France). 2. Chloroform (Merck, Germany). 3. Glycogen 20 mg/ml (Roche Diagnostic, Germany). 4. Isopropanol (Fisher Scientific, UK). 5. Two block heaters (Stuart) allowing to work at 70◦ C (HCVser) or 65◦ C (JFH1 HCV) and at 95◦ C. 6. Eppendorf Mastercycler gradient tubes.
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7. PCR apparatus (Eppendorf Mastercycler gradient). 8. rTth DNA polymerase and chelating buffer (Applied Biosystems, Foster City, CA). 9. LightCycler (Roche Applied Science, Indianapolis, IN) and FastStart DNA Masterplus SYBR green I dye for detection (Roche Applied Science, Indianapolis, IN). 10. HighPure PCR product cDNA purification kit (Roche Applied Science, Indianapolis, USA). 11. PCR clean-up gel extraction kit (Macherey-Nagel, Düren, Germany). 12. Taq DNA polymerase (Invitrogen, USA). 13. Interferon α 2a (Roferon, Roche). 14. Lactoferrin (St. Louis, MO, USA). 15. M-MLV reverse transcriptase (Invitrogen, USA). 16. Ethanol (WWR, France).
3. Methods 3.1. Human Hepatocyte Infection
1. Infection is performed 3 days after plating (see Note 1) by overnight incubation of cells with either 25 μl of serum from HCV-positive patients (see Section 2.1) per 106 cells (see Note 2) or HCVcc particles (see Section 2.2) at different concentrations (from 0.03 to 1 Geq/cell) (see Note 3). The time zero for infection is noted as I0. 2. Following exposure, cells are washed three times with Williams’ E medium at 37◦ C and incubated in fresh serumfree long-term culture medium (see Section 2.4.3 of Chapter 23). 3. Cells are collected at various time intervals (I1–I7, referring to days after infection) in RNAble for total cellular RNA extraction and intracellular HCV RNA analysis.
3.2. RNA Extraction
1. At the time of cell harvest, the medium is removed, and the cultures are washed three times with cold phosphatebuffered saline. 2. Cells and/or medium are collected in RNAble and stored at −80◦ C. 3. RNA is purified from cells or 200 μl of medium or serum using RNAble. 4. Phase separation:
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a. 100 μl chloroform/ml of RNAble, cap the tube, and vortex for 15 s. b. Store the sample on ice for 5 min. c. Centrifuge the homogenate at 12,000×g for 15 min at 4◦ C. Following centrifugation, lower blue phenol– chloroform phase, interphase, and upper colorless aqueous phase are formed. RNA remains exclusively in the aqueous phase. The volume of the aqueous phase is about 50% of the initial volume of RNAble plus sample volume. Chloroform should not contain isoamyl alcohol or any other additives. 5. RNA precipitation: a. Transfer the aqueous phase to a clean tube with 1 μl glycogen (20 μg). b. Add the same volume of isopropanol, and store the sample for 1–2 h on ice. c. Centrifuge at 12,000×g for 15 min at 4◦ C. RNA precipitate (often not visible before centrifugation) forms a white-yellow pellet at the bottom of the tube. 6. RNA washing: a. Remove the supernatant and wash the RNA pellet once with 1 ml of 75% cold ethanol. b. Shaking or vortexing is necessary to dislodge the pellet from the side of the tube. c. Centrifuge for 10 min at 7,500×g at 4◦ C. 7. RNA solubilization: a. At the end of the procedure, dry the RNA pellet (10–20 min at room temperature). It is important not to let the RNA pellet dry completely as this greatly decreases its solubility. Do not dry RNA by centrifugation under vacuum. b. Dissolve RNA extracted from hepatocytes or medium/serum in 30 to 50μL or 10μL of ultra-pure water, respectively. The final preparation of RNA should exhibit a 260/280-nm absorbance ratio comprised between 1.6 and 1.9. c. Prepare some samples (1 μg/10 μl) for rTth RT-PCR and real-time PCR quantification to avoid freezing and thawing viral HCV (see Note 4). 3.3. Strand-Specific rTth RT-PCR
1. Extracted RNA is analyzed by a strand-specific rTth reverse transcription-PCR (RT-PCR) assay (see Note 5).
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2. The primer pairs located in the HCV or JFH1 HCV (accession: AB114136) 5 -non-coding region are as follows (see Note 6). 3. Antisense primer for HCV genotypes 1 and 2 is revHCV1.2: 5 -gcacggtctacgagacctccc-3 (nt 332–353). 4. Antisense primer for HCV genotypes 3, 4, and 5 is revHCV3.4.5: 5 -gctcatgttacacggtctacgag-3 (nt 321–345). 5. Sense primer for all HCV genotypes is sensHCV: 5 cactcccctgtgaggaact-3 (nt 51–69). 6. Antisense primer for JFH1 tggtgcacggtctacgagacctc-3 (nt 319–341).
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7. Sense primer for JFH1 HCV: 5 -ctgtgaggaactactgtct-3 (nt 44–62). 8. Positive-strand RNA assay: RT stage. a. 1 μg of cellular RNA in 10 μl of water is layered with mineral oil and heated at 95◦ C for 1 min. b. The temperature is lowered to 70◦ C for HCVser or to 65◦ C for JFH1 HCV for 10 min. c. 10 μl reaction mixture/sample preheated to 70◦ C for HCVser or to 65◦ C for JFH1 HCVcc is prepared and distributed for cDNA synthesis: 50 ng of primer antisense, 2 μl 10X reverse transcriptase buffer, 2 μl 10 mM MnCl2 solution, 200 μM (each) deoxynucleoside triphosphate, and 2 μl (5 U) of rTth DNA polymerase. Primer annealing is followed by the RT reaction at 70◦ C or 65◦ C for 20 min. 9. Positive-strand RNA assay: chelating stage. In order to inactivate the RT activity of rTth DNA polymerase, MnCl2 is chelated with 40 μl of a mixture containing 8 μl of 10X chelating buffer for 20 min at 70◦ C or 65◦ C. 10. Positive-strand RNA assay: PCR stage. a. Forty microliters of PCR mixture containing 50 ng of primer sense HCVser or JFH1 HCV and 3.75 mM MgCl2 (6 μl) is added to the reaction mixture. PCR is performed on the Eppendorf Mastercycler gradient and consists of the following steps: an initial denaturation step of 1 min at 94◦ C, 50 cycles consisting of 15 s at 94◦ C, 30 s at 58◦ C, and 30 s at 72◦ C, and a final extension step of 7 min at 72◦ C. 11. PCR products are analyzed by 2% agarose gel electrophoresis.
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12. The negative-strand HCV RNA assay is performed by the same procedure, except that the primers are used in a reversed order. An example of results on the accumulation of the negative strand in hepatocytes after infection with various HCVser samples is shown in Fig. 24.1.
A HCV- strand
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Fig. 24.1. Infection of primary human hepatocytes with HCVser samples. (A) Accumulation of the negativestrand HCV RNA in hepatocytes after infection with various HCVser samples. Hepatocytes were cultured and infected with different serum samples as indicated in Section 3.1. At day 3 post-infection, cells were harvested and total RNA was extracted. The HCV RNA-negative strand was analyzed as indicated in Section 3.3. Sa–Sj refers to different serum samples prepared from different patients chronically infected with HCV. Non-infected (NI): control hepatocytes not exposed to infectious serum. Water: PCR control in the absence of cDNA. cDNA refers to the positive-strand standard (see Section 3.5). MW std.: molecular weight standard. (B) Replication of HCV genomic RNA in hepatocytes as assessed by real-time PCR quantification. Hepatocytes were cultured and infected with two different serum samples S1 (right) and S2 (left) as indicated in Section 3.1. At days 1–7 post-infection, cells were harvested and total RNA was extracted. The HCV RNA positive strand was analyzed as indicated in Section 3.4. NI: non-infected hepatocytes. I1–I7 refers to days 1–7 post-infection. HCV genomic RNA copy number per microgram of total cellular RNA is plotted against time.
3.4. Real-Time PCR Quantification of Positive- and Negative-Strand HCV RNA
1. Both positive- and negative-strand HCVser or JFH1 HCV RNAs are quantified by a real-time PCR assay using LightCycler (Roche Applied Science, Indianapolis, IN) and FastStart DNA Masterplus SYBR green I (Roche Applied Science, Indianapolis, IN) dye for detection. 2. The primer pairs located in the HCVser or JFH1 HCV non-coding region are as follows. 3. Antisense primers revHCV (5 -cgcaagcaccctatcaggcag-3 , nt 300–324 for genotype 1, nt 291–316 for genotype 2, and nt 289–313 for genotypes 3, 4, and 5).
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4. Sense primers sensHCV (5 -gcagaaagcgtctagccatggcg-3 , nt 81–103 for genotype 1, nt 74–88 for genotype 2, and nt 66–89 for genotypes 3, 4, and 5). 5. Antisense primer revJFH1 HCV (5 -cgccctatcaggcagtacca3 , nt 283–302). 6. Sense primer sensJFH1 HCV (5 -gcctagccatggcgttagtatg3 , nt 76–97). 7. One microgram of cellular RNA (see Section 3.2) is used for cDNA synthesis. In some experiments, PCR amplification of glyceraldehyde-3-phosphate dehydrogenase (GAPDH) mRNA is performed as an internal control for the quality control of extracted cellular RNA and RT using primer revGAPDH-31 (5 -gcctgcttcaccaccttcttg3 , nt 869–849). cDNA is synthesized at 70◦ C (HCVser) or 65◦ C (JFH1 HCV) for 20 min, and generated cDNA is purified with the HighPure PCR product purification kit in a 50-μl volume. 8. Positive- and negative-strand HCV PCR amplifications are performed with 3 μl of purified cDNA in a 10-μl reaction mixture containing 2 μl of LightCycler-FastStart DNA Masterplus SYBR green I and 0.5 μM (each) HCVser or JFH1 HCV primer sense and rev. 9. PCR program consists of the following steps: an initial denaturation step of 10 min at 95◦ C, followed by 45 cycles of 15 s at 95◦ C, 5 s at 70◦ C (HCVser) or 63◦ C (JFH1 HCV), and 15 s at 72◦ C. All the samples are analyzed in triplicate. 10. For the PCR amplification of GAPDH mRNA the primers used are the primer sensGAPDH-51 (5 acagtccatgccatcactgcc-3 , nt 603–624) and the primer revGAPDH-31 (see sequence above). Two microliters of purified cDNA is used in 10 μl of mixture containing 2 μl of LightCycler-FastStart DNA Masterplus SYBR green I and 0.5 μM (each) primer. 11. DNA is quantified by measuring fluorescent dye incorporation into PCR products at 530 nm. At the end of each run, a DNA melting step is performed, and the fusion curve is recorded to control for the homogeneity and quality of the amplified DNA. In each run, 10-fold serial dilutions of cDNA standards (see below) are tested in duplicate to establish a standard curve to calculate the amount of positive- and negative-strand HCV RNA in each sample. 12. Ten-fold serial dilutions of purified GAPDH mRNA amplicons are tested in duplicate to quantify GAPDH mRNA in each sample. The measured amounts of HCV RNA are normalized with respect to the amount of GAPDH mRNA
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in each sample. An example of results on the accumulation of the positive HCV RNA strand in hepatocytes infected with HCVser or HCVcc particles is shown in Figs. 24.1 and 24.2, respectively (see Note 7).
Fig. 24.2. Infection of primary human hepatocytes with JFH1/HCVcc. (A) Replication of HCVcc genomic RNA in PHH as assessed by real-time PCR quantification. Hepatocytes were cultured and infected with Huh-7.5-derived JFH1/HCVcc at 1 Geq/cell, as indicated in Section 3.1. At days 1–7 post-infection, cells were harvested and total RNA was extracted. The HCV RNA-positive strand was analyzed as indicated in Section 3.4. NI: non-infected hepatocytes. I1–I7 refers to days 1–7 post-infection. HCV genomic strand is plotted as copy number per microgram of total cellular RNA as a function of time. For accumulation of the JFH1-replicative strand see Fig. 24.6A. (B) Re-infection of primary human hepatocytes with JFH1-derived HCV particles produced in the extracellular medium of previously infected hepatocytes. Protocol 1 (P1): hepatocytes (FT5) were cultured and infected with Huh-7.5-derived JFH1/HCVcc at 1 Geq/cell as indicated in Section 3.1. At day 7 post-infection, the extracellular medium was collected and the amount of virion genomic RNA was measured by quantitative RT-PCR. Note that in this experiment, 3 million copies of viral RNA were produced per million of hepatocytes. Protocol 2 (P2): next, 200-μl aliquots of extracellular medium from P1 were used to re-infect naive hepatocytes FT5 and hepatocytes from another culture FT6 at a Geq/cell of 0.3. Five days later, extracellular medium was collected and the amount of virion genomic RNA was measured by quantitative RT-PCR. Note that in these experiments, approximately 2–2.5 million copies of viral RNA were produced per million hepatocytes.
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1. Make a rTth RT-PCR amplification from 1 μg of RNA with primers rev and sense (see Section 3.3). Run at least three reactions in order to get at least 300 μl of PCR product. 2. cDNA is purified with the HighPure PCR product purification kit to eliminate all buffers and enzyme which might interfere with enzyme LightCycler FastStart DNA Masterplus SYBR green I for real-time PCR quantification 3. Alternatively, PCR products are separated by 1% agarose gel electrophoresis, the band of cDNA is extracted, and cDNA is purified with a PCR clean-up gel extraction kit. 4. cDNA concentration is measured by spectroscopic analysis at 260 nm.
3.6. Standard for HCV RNA Quantitation
1. These standards are prepared from a full-length HCV genome plasmid pSP73 (9) or from the pFGR-JFH1 plasmid kindly provided by Dr. T. Wakita (6) (see Section 2.3). 2. Make a PCR amplification (see program in Section 3.3) from 0.2 to 0.5 μg plasmid (VT=100 μl) with Taq polymerase (Gibco). 3. cDNA is purified and quantified as described in Section 3.5.
3.7. Treatment of Primary Hepatocytes with IFNα
1. IFNα is used at final concentrations of 0.1–500 IU/ml (see Note 8). 2. IFNα treatment starts at the time of infection with either serum samples (HCVser) or HCVcc particles and lasts for all duration of the experiments. Examples of results obtained on the inhibition of HCV infection by IFNα are shown in Fig. 24.3. These results emphasize the variability of inhibition of infection in a same hepatocyte culture exposed to different HCVser samples and in different hepatocyte cultures exposed to the same HCVser sample. 3. In some experiments, uninfected hepatocytes are treated with IFNα under the same conditions to analyze the cell response (Fig. 24.4).
3.8. Evaluation of Hepatocyte Innate Response Gene Expression After Infection with HCVser or HCVcc Particles
1. Pretreatment of either HCVser or HCVcc particles with lactoferrin is used in this respect (see Note 9). 2. HCVser or HCVcc particles are preincubated for 60 min at 4◦ C with 1.0 mg/ml lactoferrin. The mixture of HCV and lactoferrin is then added to the cells and incubated for 90 min at 37◦ C. 3. In control experiments, hepatocytes are or are not exposed to lactoferrin at a final concentration of 1.0 mg/ml and incubated for 60 min at 37◦ C. Then the cells are washed
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Fig. 24.3. Inhibition of HCV infection of hepatocyte by IFNα. Hepatocytes from different liver donors (FT1 and FT2) were cultured and infected with serum samples (S1, S2, or S3) from HCV-infected patients as indicated in Section 3.1 in the absence or presence of increasing concentrations of IFNα (0–500 IU/ml). At day 3 post-infection, cells were harvested and total RNA was extracted. The HCV RNA-positive strand was analyzed as indicated in Section 3.4. HCV genomic strand is plotted as percentage of control (absence of IFN, taken as 100) after normalization with respect to GAPDH mRNA. (A) Inhibition of infection in the hepatocyte culture FT1 exposed to different HCV-positive serum samples (S1 and S2). (B) Different hepatocyte cultures (FT1 and FT2) exposed to the same HCV-positive serum sample (S3).
Fig. 24.4. Gene response of PHH to IFNα treatment. Hepatocytes from different liver donors (FT3 and FT4) were cultured and treated with IFNα (0–500 IU/ml) as indicated in Section 3.7. At various time points (1–24 h) cells were harvested and total RNA was extracted. The gene response was analyzed as indicated in Section 3.8. mRNA of different IFN-responsive genes is plotted as % of control (absence of IFN, taken as 100) after normalization with respect to GAPDH mRNA. Note the different profiles with the different cultures, FT3 and FT4.
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three times with medium and exposed to HCVser or HCVcc particles for 90 min at 37◦ C. 4. At 3 days post-infection, total RNA is extracted and the intracellular HCV RNA strands are analyzed by strandspecific rTth RT-PCR (see Section 3.3). 5. Host response gene expression is evaluated by RT-PCR using M-MLV reverse transcriptase. The specific primer pairs used for real-time PCR quantification are as follows: 6. RNase L (accession: L10381): sense primer is sense RNase L 5 -gcacagaggggaagatgtgg-3 (nt 1443–1464) and antisense primer is rev RNase L 5 -gtggatctccagcccacttg-3 (nt 1626–1647). 7. OASp69 (accession: M87284): sense primer is sense OASp69 5 -acttcattcgctcccggccc-3 (nt 1607–1627) and antisense primer is rev OASp69 5 -ggtcccctccacccacgtca-3 (nt 1947–1968).
Fig. 24.5. Host response of PHH to HCVser infection. Hepatocytes were cultured and infected with serum sample S1 as indicated in Section 3.1, with or without previous exposition to lactoferrin (LF) as indicated in Section 3.7. (A) At day 3 post-infection, cells were harvested and total RNA was extracted. The HCV RNA-negative strand was analyzed as indicated in Section 3.3. S1 refers to hepatocytes infected with serum in the absence of LF. LF+S1 refers to hepatocytes infected with serum previously exposed to LF. LF refers to hepatocytes pretreated with LF. NI: non-infected hepatocytes. Water: PCR control in the absence of cDNA. cDNA refers to the positive-strand standard (see Section 3.5). MW std.: molecular weight standard. The data show that HCV RNA replication is totally inhibited when the infectious serum is exposed to LF before infection. (B) At day 3 post-infection, the mRNA of various host response genes was analyzed by real-time RT-PCR and normalized with respect to uninfected cells (arbitrarily taken as one). The data show that a host response is generated in hepatocytes after exposure to infectious HCV-positive serum samples. This response is totally inhibited when the infectious serum is pretreated with LF before infection. In control experiments (not shown), no host response was observed in cells exposed to serum samples collected from non-infected patients.
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8. ISG20 (accession: NM-002201): sense primer is sense ISG20 5 -ggtggtggccatggactgc-3 (nt 310–330) and antisense primer is rev ISG20 5 -gcttgcctttcaggagctgc-3 (nt 526–547). 9. SOCS3 (accession: NM-003955): sense primer is sense SOCS3 5 -caagaagccaaccaggagag-3 (nt 1170–1191) and antisense primer is rev SOCS3 5 -gttcagcattcccgaagtgt-3 (nt 1409–1430). 10. PCR program consists of the following steps: an initial denaturation step of 10 min at 95◦ C, followed by 45 cycles of 15 s at 95◦ C, 5 s at 65◦ C (RNase L and SOCS3) or 70◦ C (OASP69 and ISG20), and 15 s at 72◦ C. All the samples are analyzed in triplicate. 11. Examples of host response gene expression to HCV infection in primary human hepatocytes are shown in Figs. 24.5 (HCVser) and 24.6 (HCVcc particles).
Fig. 24.6. Host response of PHH to JFH1/HCVcc infection. Hepatocytes were cultured and infected with JFH1/HCVcc (0.05 Geq/cell) as indicated in Section 3.1, with or without previous exposition of LF as indicated in Section 3.7. (A) At day 3 post-infection, cells were harvested and total RNA was extracted. The HCV RNA-negative strand was analyzed as indicated in Section 3.3. JFH1 refers to hepatocytes infected with JFH1/HCVcc, in the absence of LF. LF+JFH1 refers to hepatocytes infected with JFH1/HCVcc particles previously exposed to LF (LF+cell). JFH1 refers to hepatocytes pretreated with LF, then washed extensively to remove LF, and finally infected with JFH1/HCVcc particles. NI: non-infected hepatocytes. Water: PCR control in the absence of cDNA. cDNA refers to the positive-strand standard (see Section 3.5). MW std.: molecular weight standard. The data show that HCV RNA replication is totally inhibited when JFH1/HCVcc are pretreated with LF before infection, but not when only hepatocytes are preexposed to LF. (B) At day 3 post-infection, the mRNA of various host response genes was analyzed by real-time RT-PCR and normalized with respect to uninfected cells (arbitrarily taken as 1). The data show that a host response is generated in hepatocytes after exposure to JFH1/HCVcc particles. This response is totally inhibited when HCVcc particles are exposed to LF before infection.
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4. Notes 1. In this system of hepatocytes infected with serum-derived HCV particles (HCVser), the best window for infection is between days 3 and 5 post-plating. Infection, culture, and RNAble extraction are carried out in an L3 confinement laboratory. 2. For this step, the volume of culture medium is reduced by 50% in order to increase the relative concentration of virions contained in the infectious serum sample. Under normal conditions, the volume of culture medium is 1 ml/106 hepatocytes. 3. Infection of hepatocytes in suspension by HCVcc particles is much less efficient and is therefore carried out after plating. Only infection of Huh7.5 cells is carried out in suspension. 4. Avoid freezing–thawing of HCV viral stock as this leads to loss of viral genome replication rate of, at least, one order of magnitude. 5. This assay is used primarily to demonstrate the presence of negative-strand HCV RNA in hepatocyte, a critical marker of active viral genome replication. 6. For the choice of primers of HCV, an alignment of the different sequences of different genotypes 1, 2, 3, 4, and 5 has been performed. Then, a consensus sequence for different genotypes was used. 7. The results shown in Fig. 24.2 demonstrate that in our conditions, PHH are productive after infection with Huh-7.5/JFH1-derived HCVcc particles and that PHHderived JFH1/HCVcc virions are able to infect naive hepatocytes. 8. This range of concentration allows encompassing the range of concentrations found in the serum of patients after pharmacological dosing. 9. In order to avoid the possibility that hepatocyte innate response is activated by any other component of the patient serum or JFH1/HCVcc culture medium, these experiments are carried out in the absence or presence of a pretreatment of inoculums with bovine lactoferrin (LF). This protein has been shown to inhibit HCV infection by sequestering viral particles (21, 22), as shown in Figs. 24.5 and 24.6 (lane 4).
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Acknowledgments Part of the work described has been supported by Roche Ltd., Neilly France. References 1. Chevaliez, S. and Pawlotsky, J.M. (2007) Hepatitis C virus: virology, diagnosis and management of antiviral therapy. World J. Gastroenterol. 13, 2461–2466. 2. Lavanchy, D. and Gavinio, P. (2000) Hepatitis C. Can. J. Gastroenterol. 14 Suppl B, 67B–76B. 3. Chevaliez, S. and Pawlotsky, J.M. (2007) Interferon-based therapy of hepatitis C. Adv. Drug Deliv. Rev. 59(12), 1222–1241. 4. Bartenschlager, R. (2005) The hepatitis C virus replicon system: from basic research to clinical application. J. Hepatol. 43, 210–216. 5. Lazaro, C.A., Chang, M., Tang, W. et al. (2007) Hepatitis C virus replication in transfected and serum-infected cultured human fetal hepatocytes. Am. J. Pathol. 170, 478–489. 6. Kato, T., Date, T., Murayam, A. et al. (2006) Cell culture and infection system for hepatitis C virus. Nat. Protoc. 1, 2334–2339. 7. Lindenbach, B.D., Evans, M.J., Syder, A.J. et al. (2005) Complete replication of hepatitis C virus in cell culture. Science 309, 623–626. 8. Zhong, J., Gastaminza, P., Cheng, G. et al. (2005) Robust hepatitis C virus infection in vitro. Proc. Natl. Acad. Sci. USA 102, 9294–9299. 9. Fournier, C., Sureau, C., Coste, J. et al. (1998) In vitro infection of adult normal human hepatocytes in primary culture by hepatitis C virus. J. Gen. Virol. 79, 2367–2374. 10. Gondeau, C., Pichard-Garcia, L., and Maurel, P. (2009) Cellular models for the screening and development of anti-hepatitis C virus agents. Pharmacol. Ther. 124, 1–22. 11. Buck, M. (2008) Direct infection and replication of naturally occurring hepatitis C virus genotypes 1, 2, 3 and 4 in normal human hepatocyte cultures. PLoS ONE 3, e2660. 12. Rumin, S., Berthillon, P., Tanaka, E. et al. (1999) Dynamic analysis of hepatitis C virus replication and quasispecies selection in long-term cultures of adult human hepatocytes infected in vitro. J. Gen. Virol. 80, 3007–3018.
13. Carriere, M., Pene, V., Breiman, A. et al. (2007) A novel, sensitive, and specific RTPCR technique for quantitation of hepatitis C virus replication. J. Med. Virol. 79, 155–160. 14. Chong, T.W., Smith, R.L., Hughes, M.G. et al. (2006) Primary human hepatocytes in spheroid formation to study hepatitis C infection. J. Surg. Res. 130, 52–57. 15. Castet, V., Fournier, C., Soulier, A. et al. (2002) Alpha interferon inhibits hepatitis C virus replication in primary human hepatocytes infected in vitro. J. Virol. 76, 8189–8199. 16. Molina, S., Castet, V., Pichard-Garcia, L. et al. (2008) Serum-derived hepatitis C virus infection of primary human hepatocytes is tetraspanin CD81 dependent. J. Virol. 82, 569–574. 17. Molina, S., Castet, V., Fournier-Wirth, C. et al. (2007) The low-density lipoprotein receptor plays a role in the infection of primary human hepatocytes by hepatitis C virus. J. Hepatol. 46, 411–419. 18. Codran, A., Royer, C., Jaeck, D. et al. (2006) Entry of hepatitis C virus pseudotypes into primary human hepatocytes by clathrin-dependent endocytosis. J. Gen. Virol. 87, 2583–2593. 19. Kato, T., Date, T., Miyamoto, M. et al. (2003) Efficient replication of the genotype 2a hepatitis C virus subgenomic replicon. Gastroenterology 125, 1808–1817. 20. Rouille, Y., Helle, F., Delgrange, D. et al. (2006) Subcellular localization of hepatitis C virus structural proteins in a cell culture system that efficiently replicates the virus. J. Virol. 80, 2832–2841. 21. Abe, K., Nozaki, A., Tamura, K. et al. (2007) Tandem repeats of lactoferrin-derived antihepatitis C virus peptide enhance antiviral activity in cultured human hepatocytes. Microbiol. Immunol. 51, 117–125. 22. Ikeda, M., Sugiyama, K., Tanaka, T. et al. (1998) Lactoferrin markedly inhibits hepatitis C virus infection in cultured human hepatocytes. Biochem. Biophys. Res. Commun. 245, 549–553.
Chapter 25 The Use of Hepatocytes to Investigate HDV Infection: The HDV/HepaRG Model Camille Sureau Abstract Worldwide, it is estimated that more than 350 million people are chronically infected with hepatitis B virus (HBV), approximately 15 million of whom are coinfected with hepatitis D virus (HDV), a satellite of HBV that uses the envelope proteins of the latter to assemble its infectious particles. For a long time after HBV discovery, research on the viral life cycle, viral entry in particular, has been hampered by the lack of practical tissue culture systems. To date, in vitro isolation and serial propagation of HBV are still problematic, but the examination of the entire HBV life cycle is possible using two separate systems: (i) permissive human hepatoma cell lines to study HBV DNA replication, viral transcription, translation, assembly, and release of viral particles and (ii) primary cultures of human or chimpanzee hepatocytes or the susceptible HepaRG cell line for viral entry examination. The experimental model described here for analyzing the function of HBV envelope proteins at viral entry is based on this dual tissue culture system, in which HDV is substituted to HBV for practical reasons. Key words: HBV, HDV, in vitro infection assay, HepaRG cells, HDV RNA.
1. Introduction The study of human hepatitis viruses has been, and still remains, limited by the lack of reliable cell culture systems. These technical limitations are likely to result from the very narrow host range of these viruses – most of them are strictly hepatotropic – and the highly differentiated nature of the target human hepatocytes (1). Among the various known human hepatitis viruses, the hepatitis B virus (HBV) has been one of the most difficult to propagate in tissue culture (2–4). In vitro production of HBV was achieved by transfection of human hepatoma cell lines (Huh-7 or HepG2) P. Maurel (ed.), Hepatocytes, Methods in Molecular Biology 640, DOI 10.1007/978-1-60761-688-7_25, © Springer Science+Business Media, LLC 2010
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with recombinant HBV DNA, some 20 years after HBV discovery (5–9). However, neither of these cell lines represented a satisfactory model because they were resistant to direct infection, thereby preventing the observation of the full HBV replication cycle. Prior to 2002, the early steps of HBV infection could only be observed in vitro using primary cultures of human or chimpanzee hepatocytes, which display characteristics closest to those of human liver cells when performed in the appropriate culture medium (10–13). However, primary cultures are accessible to a limited number of specialized laboratories, and they are most difficult to handle (2, 10, 14–17). The isolation in 2002 of the HBVsusceptible HepaRG cells thus represented an experimental breakthrough in allowing for the first time to perform in vitro infection assays in an established cell line (18). This represented indeed a major step forward for studying the mechanisms of HBV entry; yet it cannot be considered as the panacea until a chronic, productive infection of this cell line can be achieved, including the synthesis of circular covalently closed HBV DNA, a known marker of persistent infection in vivo. In laboratory practice, it is only when the permissive Huh-7 or HepG2 cell line system is associated with susceptible HepaRG cell cultures that the entire HBV replication cycle can be reconstituted in vitro (18–24). Replication of HBV DNA, viral transcription, viral protein expression, and production of virions can be achieved in Huh-7 or HepG2 cells and infectivity of the cell culture-generated virions monitored in HepaRG cells. Because a HBV-susceptible cell line has been lacking until recently, the characterization of HBV entry has been very limited, and the nature of cellular receptor(s) for HBV remains unknown. HBV causes acute and chronic infections in human, which are often associated with severe liver diseases such as cirrhosis and hepatocellular carcinoma (25). To date, it is estimated that 350 million individuals worldwide suffer from chronic infection despite the availability of an effective vaccine for more than 25 years (26). Remarkably, the development of a vaccine came rather soon after the HBV discovery, and this success was based, in part, on a very peculiar feature that is unique to the HBV replication cycle: viral envelope proteins that are essential for release and entry of HBV virions are produced in massive amounts (27). Owing to their capacity for auto-assembly, the vast majority is secreted as highly immunogenic empty particles (SVPs). Interestingly, the overexpression of HBV envelope proteins can provide a helper function to the hepatitis delta virus (HDV) in the case of coinfection (28, 29). The HDV genome is a single-stranded circular RNA molecule that can replicate to high levels in mammalian cells, and the progeny genomic HDV RNA molecules can associate with multiple copies of the HDV-encoded proteins to assemble a ribonucleoprotein (RNP) (30–32). However, the RNP cannot be released from the infected cell by lack of an export
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Fig. 25.1. (A) Supernatant (1 mL) containing approximately 8×108 genome equivalents (ge) of HDV virions was serially diluted prior to analysis by Northern blot hybridization with a genomic strand-specific, 32 P-labeled RNA probe (G). One milliliter of undiluted or 2- to 1,024-fold diluted wt. HDV-containing medium was added to HepaRG cells in the presence of 5% PEG 8000. (B) HepaRG cells were harvested 7 days after inoculation and analyzed for the presence of HDV RNA by Northern blot hybridization with an antigenomic (AG) or a genomic (G) strand-specific, 32 P-labeled RNA probe. Inoculum titers are expressed as microliters of transfected Huh-7 cell supernatant or HDV genome equivalents. Ribosomal RNA (rRNA), which hybridizes non-specifically to antigenomic-specific HDV RNA probe, serves as a loading control. The position of genomic (G) or antigenomic (AG) HDV RNA is indicated. (C) Northern blot hybridization signals for genomic HDV RNA, shown in panels A and B, were quantified using a bio-imaging analyzer. The curve represents the HepaRG cells dose-dependent response to HDV infection. Note that the dose-dependent response is considered linear for 3 ≤ moi ≤ 100.
system. It is only with the assistance of the HBV envelope proteins that packaging of the RNP can occur, leading to the release of HDV particles coated with HBV envelope proteins. These HDV virions can in turn enter HBV-susceptible cells (e.g., human
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hepatocytes) (33–35). HBV, thereby, ensures spreading of the satellite HDV. The HBV or HDV particles envelope consists of cell-derived lipids and the HBV envelope proteins, large, middle, and small bearing the HBV surface antigen (HBsAg) and referred to as L-HBsAg, M-HBsAg, and S-HBsAg, respectively. The coats of HBV and HDV particles being identical, we assume that the early steps of viral entry, including binding to cellular receptors, are also identical. In our laboratory, we thus use the in vitro HDV infection system described here, as a surrogate model to study the HBV envelope proteins functions at viral entry (19–21, 36–39). The HDV model presents a few practical advantages: (i) infection assays can be performed with inocula consisting of supernatants of transfected Huh-7 cells, without the need for prior concentration or purification of the HDV particles, as opposed to cell culture-derived HBV virions that require a greater than 10X concentration, (ii) HDV-infected cells accumulate very high levels of intracellular HDV RNA (up to 100,000 copies per cell) that can be easily detected by Northern blot hybridization or RT-PCR, (iii) infections being nonproductive in the absence of the helper HBV, the level of intracellular viral RNA post-infection is proportional to the inoculum viral load (Fig. 25.1), and (iv) the HDV in vitro infection system is easily amenable to reverse genetics for analyzing envelope protein functions. Thus, the use of HDV in association with the Huh-7 and HepaRG cell lines offers a robust experimental model for analyzing the activity of the HBV envelope proteins at viral entry (see also Chapters 1 and 13).
2. Materials 2.1. Plasmids Required for Production of HDV Particles
1. Plasmid pSVLD3 contains a head-to-tail trimer of the fulllength HDV cDNA for transcription of genomic HDV RNA from the simian 40 late promoter (40). Transfection of mammalian cells with pSVLD3 DNA leads to the synthesis of HDV RNA and proteins and the production of HDV RNPs. 2. Plasmid pT7HB2.7 contains a 2.7 kb HBV DNA fragment (genotype D) (nucleotides 2426–1987) for transcription of HBV mRNAs specific of the large, middle, and small HBV envelope proteins under the control of the endogenous HBV promoters and polyadenylation signal (41). Transfection of cells with pT7HB2.7 plasmid DNA leads to the production and secretion of the three HBV envelope proteins L-, M-, and S-HBsAg (see Note 1).
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3. Plasmid pSP72HDV contains a full-length cDNA copy of HDV inserted between the T7 and SP6 RNA polymerase promoter sequences for in vitro transcription of antigenomic or genomic HDV RNA using the T7 or SP6 RNA polymerase, respectively. 2.2. Huh-7 Cell Culture
1. Six-well tissue culture plates (Corning Costar). 2. Williams’ medium E (WME) (Gibco) supplemented with 10% fetal bovine serum (Fetaclone II, Hyclone), 50 μg/mL gentamicin (Gibco). 3. Dulbecco’s phosphate-buffered saline (DPBS) (Gibco). 4. 0.5 g/L trypsin and 0.2 g/L EDTA-4Na (Gibco). 5. FuGENE-HD, transfection reagent (Roche). 6. OptiMEM serum-free medium (Gibco).
2.3. HepaRG Cell Culture
1. Twelve-well tissue culture plates (Corning). 2. Growth medium: WME (Gibco) supplemented with 10% fetal bovine serum (Fetaclone, Hyclone), 5 μg/mL insulin (Sigma), 10−6 M dexamethasone (Sigma), 50 μg/mL gentamicin (Gibco), and 5 ng/mL epidermal growth factor (Sigma). 3. Differentiation medium consists of growth medium supplemented with 2% dimethyl sulfoxide (DMSO) (Sigma). 4. Polyethylene glycol (PEG) 8,000 MW (Sigma).
2.4. Northern Blot Analysis for Detection of HDV RNA
1. Horizontal gel electrophoresis unit (HE 100, Hoefer Scientific Instruments). 2. UV crosslinker (Spectrolinker XL 1000, Spectronics Corporation). 3. Shaking water bath (Jubalo SW20). 4. Fume hood. 5. Microcentrifuge (VWR Galaxy Mini). 6. Capillary transfer system (Turboblotter Schleicher & Schuell BioScience). 7. Bio-imaging analyzer (Fujifilm BAS-1800II). 8. Imaging plate (Fujifilm BAS-IP MS 2025). 9. 3MM chromatography paper (Whatman). 10. RNase AWAY (Molecular BioProducts). 11. RNeasy Mini Kit (Qiagen). 12. QIAamp viral RNA (Qiagen). 13. Nuclease-free water (Ambion). 14. NorthernMax formaldehyde load dye (Ambion).
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15. Positively charged nylon membrane (Roche). 16. 20X saline sodium citrate (20X SSC): 1X is 3 M NaCl, 0.3 M sodium citrate. 17. 3-(N-morpholino)-propanesulfonic acid (MOPS) (Sigma). 18. Formaldehyde solution at 36.5%. 19. Formamide. 20. Agarose (Eurogentec). 21.
uridine 5 triphosphate (UTP) 6,000 ci/mmol (Perkin Elmer). 32 P-labeled
22. Riboprobe combination system SP6/T7 RNA polymerase (Promega). 23. MiniQuick spin RNA columns (Roche). 24. Hybridization buffer: 6X SSC, 10% sodium dodecyl sulfate (SDS), 50% formamide. 25. Low stringency wash buffer: 1X SSC, 0.1% SDS. 26. High stringency wash buffer: 0.1X SSC, 0.1% SDS.
3. Methods 3.1. Production of HDV Particles in Huh-7 Cells
1. Twenty-four hours prior to transfection, seed Huh-7 cells in six-well tissue culture plates in WME, 10% fetal bovine serum at a density of 0.8×106 cells/mL per well, and incubate at 37◦ C and 5% CO2 . 2. For transfection of cells in one well of a six-well plate, prepare a mixture of 1 μg of pSVLD3 DNA and 1 μg of pT7HB2.7 DNA. 3. Dilute plasmid DNA (pSVLD3 + pT7HB2.7) in 100 μL of OptiMEM (Gibco) and vortex briefly. 4. Add 6 μL of FuGENE-HD reagent (Roche), vortex briefly, and incubate at room temperature for 30 min. 5. Add the transfection mix to the cells in a drop-wise manner. 6. Incubate cells at 37◦ C and 5% CO2 and replace medium 16 h post-transfection. 7. Change medium every other day and harvest HDVcontaining medium on days 7, 9, and 12 post-transfection (see Note 2). 8. Clarify HDV-containing supernatant by centrifugation at 5,000×g at 4◦ C for 30 min. The clarified medium can be used directly as inoculum in the in vitro infection assay.
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9. Store HDV inoculum at −70◦ C for future RNA extraction and in vitro infection assays (see Note 3). 3.2. HDV Infection Assays in HepaRG Cells
For infection assay, clarified supernatants containing HDV virions are used as inocula after quantification of HDV RNA by Northern blot analysis as described below. 1. Two weeks prior to inoculation, seed HepaRG cells in 12well tissue culture plates in HepaRG growth medium, at a density of 0.8×105 cells/mL per well, and incubate at 37◦ C and 5% CO2 . 2. Grow cells for 2 weeks, changing the medium every 2 days. 3. Two weeks post-seeding the growth medium is changed to differentiation medium, and the cells are maintained in the latter for two more weeks, replacing with fresh medium every 2 days. 4. Inoculate differentiated HepaRG cells (approximately 3.3×105 cells/20-mm diameter well) with 108 genome equivalents (ge) of HDV virions in the presence of 5% PEG 8000 (Sigma), and incubate at 37◦ C for 16 h (see Note 4). 5. Remove the inoculum, and replace with HepaRG growth medium, changing every 2 days until day 7 post-inoculation. 6. At day 7 post-inoculation, remove culture supernatant and wash the cell monolayer with cold DPBS. 7. After removal of DPBS, lyse cells with RLT lysis buffer (Qiagen) at room temperature for 15 min (see Note 5). 8. Total cellular RNA is then purified using the RNeasy Mini Kit (Qiagen cat. no.) as described by the manufacturer. 9. Purified RNA solution in nuclease-free water is stored at −70◦ C for future detection of HDV RNA by Northern blot hybridization (see Note 6).
3.3. Detection of HDV RNA in Inocula and Infected Cells 3.3.1. Detection of HDV RNA in Culture Medium of Transfected Huh-7 Cells
Extraction of viral RNA is carried out from 140 μL of inoculum using the QIAamp viral RNA mini kit (Qiagen). Purified HDV RNA is eluted from QIAamp columns in 10 μL of nuclease-free water (Fig. 25.1A). 1. Add 30 μL of gel loading buffer (Ambion) to the 10 μL RNA sample. 2. Heat sample at 70◦ C for 5 min. 3. Chill on ice. 4. Bring sample to room temperature before loading on gel. 5. RNA is subjected to electrophoresis at 100 V through a 2.2 M formaldehyde, 1.2% agarose gel for 1 h at room temperature (see Note 7).
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6. Transfer RNA from the agarose gel to a nylon membrane (Roche) using the Turboblotter device (Schleicher & Schuell) as described by the manufacturer. 7. After transfer, RNA is crosslinked to the membrane under UV irradiation (120 mJ/cm2 ) using a UV crosslinker. 8. Soak the membrane in nuclease-free 0.2X SSC. 9. Place the membrane in preheated hybridization buffer and incubate at 59◦ C for 5 h under shaking at 50 rpm. 10. Prepare the 32 P-labeled HDV RNA probe using the Riboprobe Combination System with T7, or SP6, RNA polymerase (Promega), and 32 P-labeled UTP as described by the manufacturer. In vitro transcription is carried out from a linearized pSP72HDV plasmid. The T7 promoter directs the transcription of antigenomic HDV RNA for the detection of genomic HDV RNA, and the SP6 promoter directs the synthesis of genomic HDV RNA for detection of antigenomic HDV RNA. 11. Purify labeled RNA using the MiniQuick Spin RNA Columns (Roche) as described by the manufacturer using a microfuge. 12. Add 32 P-labeled RNA probe (106 cpm/mL) to the membrane in hybridization buffer, and incubate overnight at 59◦ C under shaking at 50 rpm (see Note 8). 13. After hybridization, wash the membrane two times for 30 min in low stringency buffer at room temperature, then two times for 30 min in high stringency buffer at 65◦ C. 14. After washing allow the membrane to dry on a 3MM paper before exposure to a BAS-MS 2025 imaging plate for 1 h. 15. Record Northern blot hybridization image and quantify signals using a bio-imaging analyzer. 3.3.2. Detection of HDV RNA in HepaRG Infected Cells
The protocol for detection of HDV RNA in total cellular RNA is identical to that described above, except that extraction of HepaRG cellular RNA is carried out using the RNeasy Mini Kit (Qiagen) from cells harvested at day 7 post-inoculation, according to the supplier’s instructions (Fig. 25.1B,C). 1. Use 350 μL of RTL lysis buffer (Qiagen) per well of a 12well tissue culture plate. 2. After addition of gel loading buffer (Ambion) to purified cellular RNA, load the equivalent of 1/10 of total RNA (extract from a 20 mm diameter tissue culture well), per well of agarose gel. 3. Proceed to electrophoresis, transfer and hybridization as described above.
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4. Notes 1. The HBV DNA insert in pT7HB2.7 extends from nucleotide 2426 to nucleotide 1987 of the genotype D genome (and not from 2840 to 1987 as erroneously stated in (41)), thus including the pre-S1 promoter for synthesis L-HBsAg mRNA. 2. Harvesting at a later time after transfection (days 12–15) leads to lesser amounts of viral particles, but to higher ratios of virions/SVPs. 3. Preparation of HDV particles can also be stored at 4◦ C for several weeks without effect on infectivity. Storage at 4◦ C will prevent precipitation of serum proteins. 4. A 10X stock solution of PEG 8000 in WME (50% PEG) can be used. Heating the solution at 37◦ C will reduce viscosity and facilitate pipeting of small volumes. 5. Disrupt cells by vigorous up and down pipeting until viscosity is reduced. 6. RNA solution can be adjusted with Gel loading buffer prior to storing at −70◦ C if no future RT-PCR assay is programmed. 7. Pour and run formaldehyde gel under a fume hood. After transfer, discard formaldehyde-contaminated materials appropriately. 8. Hybridization buffer is prepared in a fume hood by adding 100 g of SDS powder to 500 mL of formamide preheated at 60◦ C on a stir plate. Then add 300 mL of 20X SSC. After SDS has dissolved, make 50 mL aliquots when still warm (hybridization buffer freezes up at room temperature) and store at −70◦ C. There is no need to use fresh hybridization buffer when adding the radioactive probe.
Acknowledgments The author acknowledges O. Hantz and C. Trépo for the gift of the HepaRG cell line. CS is a CNRS investigator; he is supported by contracts with ANRS and INTS. References 1. Seeger, C. and Mason, W.S. (2000) Hepatitis B virus biology. Microbiol. Mol. Biol. Rev. 64, 51–68.
2. Fournier, C., Sureau, C., Coste, J., Ducos, J., Pageaux, G., Larrey, D., Domergue, J., and Maurel, P. (1998) In vitro infection of
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Sureau adult normal human hepatocytes in primary culture by hepatitis C virus. J. Gen. Virol. 79 (Pt 10), 2367–2374. Lanford, R.E., Sureau, C., Jacob, J.R., White, R., and Fuerst, T.R. (1994) Demonstration of in vitro infection of chimpanzee hepatocytes with hepatitis C virus using strand-specific RT/PCR. Virology 202, 606–614. Sureau, C. (1993) In vitro culture systems for hepatitis B and delta viruses. Arch. Virol. Suppl. 8, 3–14. Sureau, C., Romet-Lemonne, J.L., Mullins, J.I., and Essex, M. (1986) Production of hepatitis B virus by a differentiated human hepatoma cell line after transfection with cloned circular HBV DNA. Cell 47, 37–47. Chang, C.M., Jeng, K.S., Hu, C.P., Lo, S.J., Su, T.S., Ting, L.P., Chou, C.K., Han, S.H., Pfaff, E., Salfeld, J. et al. (1987) Production of hepatitis B virus in vitro by transient expression of cloned HBV DNA in a hepatoma cell line. EMBO J. 6, 675–680. Sells, M.A., Chen, M.L., and Acs, G. (1987) Production of hepatitis B virus particles in Hep G2 cells transfected with cloned hepatitis B virus DNA. Proc. Natl. Acad. Sci. USA 84, 1005–1009. Tsurimoto, T., Fujiyama, A., and Matsubara, K. (1987) Stable expression and replication of hepatitis B virus genome in an integrated state in a human hepatoma cell line transfected with the cloned viral DNA. Proc. Natl. Acad. Sci. USA 84, 444–448. Yaginuma, K., Shirakata, Y., Kobayashi, M., and Koike, K. (1987) Hepatitis B virus (HBV) particles are produced in a cell culture system by transient expression of transfected HBV DNA. Proc. Natl. Acad. Sci. USA 84, 2678–2682. Jacob, J.R., Eichberg, J.W., and Lanford, R.E. (1989) In vitro replication and expression of hepatitis B virus from chronically infected primary chimpanzee hepatocytes. Hepatology 10, 921–927. Gripon, P., Diot, C., and Guguen-Guillouzo, C. (1993) Reproducible high level infection of cultured adult human hepatocytes by hepatitis B virus: effect of polyethylene glycol on adsorption and penetration. Virology 192, 534–540. Gripon, P., Diot, C., Theze, N., Fourel, I., Loreal, O., Brechot, C., and GuguenGuillouzo, C. (1988) Hepatitis B virus infection of adult human hepatocytes cultured in the presence of dimethyl sulfoxide. J. Virol. 62, 4136–4143. Sureau, C., Jacob, J.R., Eichberg, J.W., and Lanford, R.E. (1991) Tissue culture system
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for infection with human hepatitis delta virus. J. Virol. 65, 3443–3450. Blanc, P., Desprez, D., Fabre, J.M., Pageaux, G., Daures, J.P., Larrey, D., Saint-Aubert, B., Michel, H., and Maurel, P. (1996) Contribution of primary cultures of adult human hepatocytes to the pathophysiology of hepatocellular carcinoma. J. Hepatol. 25, 663–669. Ferrini, J.B., Ourlin, J.C., Pichard, L., Fabre, G., and Maurel, P. (1998) Human hepatocyte culture. Methods Mol. Biol. 107, 341–352. Pichard-Garcia, L., Gerbal-Chaloin, S., Ferrini, J.B., Fabre, J.M., and Maurel, P. (2002) Use of long-term cultures of human hepatocytes to study cytochrome P450 gene expression. Methods Enzymol. 357, 311–321. Jacob, J.R., Burk, K.H., Eichberg, J.W., Dreesman, G.R., and Lanford, R.E. (1990) Expression of infectious viral particles by primary chimpanzee hepatocytes isolated during the acute phase of non-A, non-B hepatitis. J. Infect. Dis. 161, 1121–1127. Gripon, P., Rumin, S., Urban, S., Le Seyec, J., Glaise, D., Cannie, I., Guyomard, C., Lucas, J., Trepo, C., and Guguen-Guillouzo, C. (2002) Infection of a human hepatoma cell line by hepatitis B virus. Proc. Natl. Acad. Sci. USA 99, 15655–15660. Abou-Jaoude, G. and Sureau, C. (2007) Entry of hepatitis delta virus requires the conserved cysteine residues of the hepatitis B virus envelope protein antigenic loop and is blocked by inhibitors of thiol-disulfide exchange. J. Virol. 81, 13057–13066. Blanchet, M. and Sureau, C. (2006) Analysis of the cytosolic domains of the hepatitis B virus envelope proteins for their function in viral particle assembly and infectivity. J. Virol. 80, 11935–11945. Engelke, M., Mills, K., Seitz, S., Simon, P., Gripon, P., Schnolzer, M., and Urban, S. (2006) Characterization of a hepatitis B and hepatitis delta virus receptor binding site. Hepatology 43, 750–760. Gripon, P., Cannie, I., and Urban, S. (2005) Efficient inhibition of hepatitis B virus infection by acylated peptides derived from the large viral surface protein. J. Virol. 79, 1613–1622. Lucifora, J., Durantel, D., Belloni, L., Barraud, L., Villet, S., Vincent, I.E., Margeridon-Thermet, S., Hantz, O., Kay, A., Levrero, M., and Zoulim, F. (2008) Initiation of hepatitis B virus genome replication and production of infectious virus following delivery in HepG2 cells by novel recombinant baculovirus vector. J. Gen. Virol. 89, 1819–1828.
Use of Hepatocytes to Investigate HDV Infection 24. Schulze, A., Gripon, P., and Urban, S. (2007) Hepatitis B virus infection initiates with a large surface protein-dependent binding to heparan sulfate proteoglycans. Hepatology 46, 1759–1768. 25. Ganem, D. and Prince, A.M. (2004) Hepatitis B virus infection-natural history and clinical consequences. N. Engl. J. Med. 350, 1118–1129. 26. Ganem, D. and Schneider, R.J. (2001) Hepadnaviridae: the viruses and their replication, in Fields Virology (Knipe, D.M. and Howley, P.M. eds.), Lippincott Williams & Wilkins, Philadelphia PA USA, pp. 2923–2970. 27. Heermann, K.H. and Gerlich, W.H. (1992) Surface proteins of hepatitis B viruses, in Molecular Biology of HBV (Maclachlan, A. ed.), CRC Press, Boca Raton Florida USA. 28. Bonino, F., Heermann, K.H., Rizzetto, M., and Gerlich, W.H. (1986) Hepatitis delta virus: protein composition of delta antigen and its hepatitis B virus-derived envelope. J. Virol. 58, 945–950. 29. Gerlich, W.H., Heermann, K.H., Ponzetto, A., Crivelli, O., and Bonino, F. (1987) Proteins of hepatitis delta virus. Prog. Clin. Biol. Res. 234, 97–103. 30. Lai, M.M. (1995) The molecular biology of hepatitis delta virus. Annu. Rev. Biochem. 64, 259–286. 31. Taylor, J.M. (2006) Structure and replication of hepatitis delta virus RNA. Curr. Top. Microbiol. Immunol. 307, 1–23. 32. Taylor, J.M. (2006) Hepatitis delta virus. Virology 344, 71–76. 33. Sureau, C., Guerra, B., and Lanford, R.E. (1993) Role of the large hepatitis B virus
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envelope protein in infectivity of the hepatitis delta virion. J. Virol. 67, 366–372. Sureau, C. and Lanford, R. (1993) Analysis of hepatitis B virus envelope proteins in assembly and infectivity of human hepatitis delta virus. Prog. Clin. Biol. Res. 382, 45–51. Wang, C.J., Chen, P.J., Wu, J.C., Patel, D., and Chen, D.S. (1991) Small-form hepatitis B surface antigen is sufficient to help in the assembly of hepatitis delta virus-like particles. J. Virol. 65, 6630–6636. Barrera, A., Guerra, B., Lee, H., and Lanford, R.E. (2004) Analysis of host range phenotypes of primate hepadnaviruses by in vitro infections of hepatitis D virus pseudotypes. J. Virol. 78, 5233–5243. Barrera, A., Guerra, B., Notvall, L., and Lanford, R.E. (2005) Mapping of the hepatitis B virus pre-S1 domain involved in receptor recognition. J. Virol. 79, 9786–9798. Barrera, A. and Lanford, R.E. (2004) Infection of primary chimpanzee hepatocytes with recombinant hepatitis D virus particles: a surrogate model for hepatitis B virus. Methods Mol. Med. 96, 131–142. Blanchet, M. and Sureau, C. (2007) Infectivity determinants of the hepatitis B virus preS domain are confined to the N-terminal 75 amino acid residues. J. Virol. 81, 5841–5849. Kuo, M.Y., Chao, M., and Taylor, J. (1989) Initiation of replication of the human hepatitis delta virus genome from cloned DNA: role of delta antigen. J. Virol. 63, 1945–1950. Sureau, C., Guerra, B., and Lee, H. (1994) The middle hepatitis B virus envelope protein is not necessary for infectivity of hepatitis delta virus. J. Virol. 68, 4063–4066.
Chapter 26 Rodent Models of Liver Repopulation Helène Gilgenkrantz Abstract The liver has an extraordinary faculty to regenerate. Hepatocytes are highly differentiated cells that, despite a resting G0 state in the normal quiescent liver, can re-enter the cell cycle to reconstitute the organ after an injury. However, the first cell therapy approaches trying to harness this specific characteristic of the hepatocytes came up against the competition with resident hepatocytes in the ability to proliferate. This review will describe the different rodent models that have been developed in the last 15 years to demonstrate the concept of liver repopulation with transplanted cells harbouring a selective advantage over resident hepatocytes. Examples will then be given to show how these models demonstrated the therapeutic efficiency of cell transplantation in specific disorders. The transplantation of human hepatocytes into some of these mouse models led to the creation of humanized livers. These humanized mice provide a powerful tool to study the physiopathology of human hepatotropic pathogens and to develop drugs against them. Finally, emphasis will be placed on the role of these rodent models in the demonstration of the hepatocytic potential of stem cells. Key words: Hepatocyte transplantation, liver regeneration, cell therapy, humanized liver, stem cells, selective advantage.
1. Introduction Primary hepatocytes, as illustrated in previous chapters, are not easily manipulated. They are difficult to maintain in a differentiated state in vitro, they do not expand easily and, although technical improvements have been performed, their cryopreservation remains a tricky procedure. The spontaneous dedifferentiation and the low proliferation rate of these cells in culture are in sharp contrast to their extraordinary capacity to regenerate an injured liver in the context of an entire organ. The most P. Maurel (ed.), Hepatocytes, Methods in Molecular Biology 640, DOI 10.1007/978-1-60761-688-7_26, © Springer Science+Business Media, LLC 2010
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studied rodent model of liver regeneration is the surgical excision of two-thirds of the liver, after which the remaining third expands to restore normal liver mass in about 1 week. During this process, nearly all hepatocytes enter the cell cycle and, after less than two cell cycles, replenish the missing liver mass. Therefore, provided that the proliferative capacity of hepatocytes is not blocked, there is no need for a progenitor cell compartment to regenerate the liver (1). The liver repopulation field began about 20 years ago, when this very unusual characteristic for a quiescent adult tissue prompted researchers to propose hepatocyte transplantation as an alternative for orthotopic liver transplantation. However, the limited number of cells that can be transplanted (the maximum hepatocyte mass transplantable in human trials is less than 5% of total liver mass to minimize potential complications related to massive cell intraportal infusion) and their low rate of spontaneous expansion in vivo hampered the development of clinical trials (2). Up to now, clinical trials using hepatocyte transplantation have mostly targeted metabolic disorders: familial hypercholesterolaemia, Crigler–Najjar syndrome type 1, urea cycle defects, infantile Refsum disease, glycogen storage disease type 1a, inherited factor VII deficiency and progressive familial intrahepatic cholestasis; for review, see (3). However, in most cases, these trials gave only partial or transient therapeutic effects. Attempts to increase the proportion of transplanted hepatocytes by stimulating liver regeneration or by repeating cell transplantation failed to show significant benefit, mostly because resident hepatocytes competed with transplanted ones to replace missing cells. In this historical context, it was demonstrated that it is possible to repopulate an almost entire mouse liver provided that transplanted cells have a selective advantage over resident cells. Various other models were then created. These models are particularly helpful in three different axes: – demonstrating or enhancing the therapeutic efficacy of a cell transplantation approach; – creating mice with a humanized liver; – demonstrating the capacity of stem cells or progenitor cells to engraft, maintain, differentiate and expand in vivo in the context of an entire liver. These three axes are indeed interconnected: the characterization of stem cells capable to differentiate into mature and functional hepatocytes will obviously open therapeutic issues; humanized livers will also help the development of new drugs targeted against hepatotropic infectious agents; and finally, the demonstration that it is possible to obtain in vivo mature differentiated hepatocytic cells from embryonic or adult stem cells will help to develop humanized mouse liver models.
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2. A Review of Existing Models 2.1. Two Historical Models of Mouse Liver Repopulation
The first model, called uPA mice, was obtained by transgenesis. These mice express urokinase-type plasminogen activator specifically in hepatocytes (4). They usually die from neonatal bleeding due to the toxicity of the transgene. Surviving mice show pale liver with a continuous cytolysis regeneration sequence, in which red nodules derived from a single cell that has inactivated the transgene spontaneously appear. Sandgren’s team demonstrated that the transplantation of normal hepatocytes into young uPA transgenic mice led to the replacement of more than 90% of the liver mass in less than 2 months (5). This model, backcrossed on a nude immunodeficient background, also allowed the in vivo clonal expansion of xenotransplanted hepatocytes from rat donors (6). The second model came from observations of pathologists on livers of children suffering from hereditary tyrosinaemia type 1 (HT1) and undergoing liver transplantation. This disease is caused by deficiency in fumarylacetoacetate hydrolase (FAH) that leads to an accumulation of toxic metabolites in the tyrosine degradation pathway, inducing liver failure. At the time of transplantation, the diseased livers showed large nodules of FAHpositive normal hepatocytes (7). A mouse phenocopy of this disorder has been created that is viable when a treatment with an inhibitor (NTBC) of the pathway is initiated in utero and maintained after birth. Transplantation of normal hepatocytes from congenic animals into FAH-deficient mice allowed survival after withdrawal of NTBC, demonstrating for the first time the therapeutic value of this approach. Analysis of recipient livers demonstrated again the clonal expansion of transplanted hepatocytes, with a more than 95% replacement of the hepatocytes 6 weeks after transplantation, only when NTBC is stopped (8, 9). One thousand hepatocytes are sufficient to reach more than 50% liver repopulation in the same period of time, underlining the huge selective pressure provided by this model (10).
2.2. A Second Generation of Liver Repopulation Models
Taking these two models as paradigms, one can schematically define two conditions for successful liver repopulation by transplanted cells: – Transplanted hepatocytes must harbour a selective advantage over resident ones. – Space must be made in the recipient liver to allow the expansion of transplanted cells. In the two previous models, the necessary space was created by the genetic damage induced by FAH deficiency or the uPA transgene. Based on these statements, new rodent models of liver
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repopulation were developed demonstrating again that 20–98% of the recipient hepatocytes can be replaced by this approach. In most of them, transplanted hepatocytes have a spontaneous proliferative advantage because proliferation of resident parenchymal cells has been blocked chemically or physically. On the other hand, various types of toxic injuries were developed to provide a stimulus for liver repopulation. These different approaches are summarized in Table 26.1 and developed below. 1. Vegetal alkaloids: retrorsine and monocrotaline. Shafritz’ group was the first to induce a persistent inhibition of host hepatocyte proliferation to allow liver repopulation by transplanted cells treating rats with a pyrrolizidine alkaloid called retrorsine (11). Retrorsine is taken up selectively by hepatocytes, where it is metabolized to its active form and alkylates cellular DNA inducing a proliferation arrest at the G2/M phase. The protocol consisted in two retrorsine intraperitoneal injections at 30 mg/kg 2 weeks apart followed, 4 weeks later, by a partial hepatectomy concomitantly with hepatocyte infusion. Four months after transplantation of 2 million hepatocytes, 98% of liver parenchymal cells came from the donor (11). Levels of repopulation around
Table 26.1 Rodent models of liver repopulation Cells
Donor cell advantage
Recipient liver damage
Prolif. stimulus
Ref.
NM (mice)
Spontaneous survival
uPA transgene
None
(5)
NM (mice)
Spontaneous survival
FAH deficiency
None
(8)
NM (rat)
Spontaneous proliferative ± survival
Retrorsine
PH
(11)
Retrorsine
T3
(12)
Retrorsine
None
(13)
Irradiation
PH
(Guha et al., 2002)
PH
(15)
NM (mice)
Spontaneous proliferative
Retrorsine+CCl4
(14, 21)
NM (mice and rat)
Spontaneous proliferative
Monocrotaline
NM (rat)
Spontaneous proliferative
Monocrotaline+CCl4
(16, 17)
Modified (mice)
Induced survival with Bcl-2
Fas-induced apoptosis
(18, 20)
Modified (mice)
Induced proliferative (p27–/– hepatocytes)
Retrorsine+CCl4
(21)
Modified (mice)
Induced proliferative (FoxM1B expressing)
uPA transgene
(22)
Rodent Models of Liver Repopulation
479
60–80% were obtained when partial hepatectomy was replaced by repeated injections of thyroid hormone T3 to stimulate transplanted cell proliferation (12). What appears particularly interesting in this model is the possibility to obtain an efficient level of liver repopulation in the absence of any exogenous proliferation stimulus (13). The induction of apoptosis of resident cells blocked in their cell cycle progression by retrorsine is probably responsible for this intrinsic selection of transplanted cells. This model has been adapted to mice (14): an average of 20% of liver repopulation was obtained after retrorsine injection (70 mg/kg) combined with three injections of CCl4 at 0.5 ml/kg to stimulate donor cell proliferation. In this rodent, however, only 1% liver repopulation was obtained if only retrorsine was used. Another alkaloid, monocrotaline, has been injected as an alternative to retrorsine-based cell transplantation, particularly in mice (15). Monocrotaline is known to provoke extensive endothelial injury, enhancing the engraftment of transplanted cells and inducing a significant liver repopulation after carbon tetrachloride liver injury (16, 17). 2. A vicious couple: Bcl-2/Fas pathway. Until then, transplanted hepatocytes were wild-type primary hepatocytes. Contrasting with these models, another approach has been developed that consisted in conferring a survival advantage to therapeutic cells. The idea here was to genetically modify hepatocytes before their transplantation in order to protect them against a specific attack in the host. In this model, the protective gene was the anti-apoptotic factor Bcl-2 and the injury of resident hepatocytes was induced by injection of a Fas-agonistic antibody. Bcl-2 expression renders hepatocytes resistant to the death receptor apoptotic pathway. Mice submitted to repeated weekly injections of a Fas-agonistic antibody showed 30% liver repopulation 2 months after transplantation of 1 million Bcl-2 transgenic hepatocytes (18, 19), reaching 85% when a retroviral vector expressing Bcl2 was used (20). By demonstrating the therapeutic efficacy of this approach in a mouse model of atherosclerosis and hypercholesterolaemia due to apolipoprotein E deficiency, the authors also demonstrated the functionality of transplanted hepatocytes that had clonally expanded in vivo (19). 3. Induced proliferative selective advantage. Could an induced proliferative advantage replace a survival one? To answer this question, proteins modulating the cell cycle positively or negatively were, respectively, induced or repressed in transplanted hepatocytes. P27Kip1 is a cyclin-dependent kinase inhibitor that stably interacts with cyclin A and cyclin E/Cdk complexes to negatively regulate cell proliferation.
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Hepatocytes deficient in p27 proliferate more rapidly than wild-type hepatocytes in vivo after partial hepatectomy. However, p27–/– hepatocytes, transplanted into a normal mouse liver, did not show a significant increase in proliferation rate after an acute regeneration stimulus compared to wild-type cells (21). In contrast, after repeated injury with carbon tetrachloride, liver repopulation by transplanted p27–/– hepatocytes was increased substantially compared to normal cells. FoxM1B is a key cell cycle regulator involved in both G1/S and G2/M progression. Primary hepatocytes overexpressing FoxM1B proliferate faster than non-modified hepatocytes (22). However, as with p27 null cells, FoxM1B overexpression in transplanted cells did not overcome proliferative restrictions imposed on hepatocytes in the context of a single regeneration stimulus. Nonetheless, after repeated liver injury, the enhanced proliferative capacity of FoxM1B hepatocytes led to a higher level of liver repopulation compared to wild-type cells (22). Overall, these reports reach the same conclusion: whatever the gene used to accelerate the proliferation of transplanted cells, it is not sufficient by itself to induce liver repopulation in the absence of chronic injury. Moreover, in the absence of a tight control, this approach could even accelerate liver tumorigenesis.
3. Creating Mouse Models of Liver Repopulation: What for? What Future Challenges? 3.1. Demonstrating Therapeutic Efficacy
Two categories of disorders could benefit from a liver repopulation approach: – Diseases in which there is a spontaneous environment for selection of normal transplanted hepatocytes: this rare situation will occur if recipient hepatocytes are exposed to a cytotoxic cell autonomous disease (see Table 26.2). – Diseases in which the liver is normal but a gene/toxic combination will allow the transplanted cells to proliferate selectively in response to controlled liver damage. Progressive familial intrahepatic cholestasis (PFIC) type 3 is an example of the first category of diseases. It is due to a mutation in the MDR3 gene encoding the hepatocanalicular phospholipid translocator and induces the absence of phospholipid secretion into the bile, leading to hepatotoxicity. In the mouse model of the human disease, hepatocyte transplantation leads to a 20% liver repopulation, restores phospholipids secretion and
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Table 26.2 Non-exhaustive list of human disorders amenable for spontaneous liver repopulation Hereditary tyrosinaemia type 1 Wilson disease Progressive familial intrahepatic cholestasis types 1, 2 and 3 α1-Antitrypsin deficiency Glycogen storage disease type 1 (Von Gierke disease), type 4 (Brancher enzyme deficiency) Galactosaemia Hereditary fructose intolerance Haemochromatosis Bile acid synthesis disorders Peroxisomal biogenesis disorders Indian childhood cirrhosis
diminishes liver pathology (23). However, in this model, a specific regimen enhances the recipient liver toxicity and the level of repopulation. In Wilson disease, liver repopulation is obtained without any selective pressure (24) but is higher with the use of retrorsine or hepatic irradiation (25–28). In analbuminaemia, there is no such selective pressure and the use of retrorsine was required to treat mutant rats (29). More recently, X-irradiation and mitotic stimulation of the hepatocytes by an adenovectorbased expression of hepatocyte growth factor was used to repopulate a mouse model of hyperoxaluria type 1 (30). These models (summarized in Table 26.3) not only demonstrate the real therapeutic impact of a liver repopulation approach but also allow us to better understand or improve hepatocyte homing and engraftment into the liver parenchyma. They also helped to investigate the minimal number of therapeutic cells necessary to correct a disease. In the phenylketonuria mouse model backcrossed on the FAH–/– background, it was, for example, demonstrated that a significant decrease in serum phenylalanine was achieved when liver repopulation exceeded approximately 5% (31). However, all these approaches are not clinically relevant. The protocols to destroy resident cells or block their proliferation (Fas-induced liver apoptosis, X-irradiation, mitotic stimulation or retrorsine treatment) are at risk for tumorigenesis or fulminant hepatitis. Therefore, one of the major actual challenges will be to develop new secure “Jekyll and Hyde couples” that would comprise a toxic compound targeting selectively hepatocytes and a gene that would protect them against this toxicity.
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Table 26.3 Therapeutic rodent models of liver repopulation Disease
Donor cell advantage
Recipient liver damage
Prolif. stimulus
Ref.
FAH (tyrosinaemia type 1)
Spontaneous
FAH deficiency
None
(8)
Wilson
Spontaneous
None
None
(24)
Retrorsine/irradiation
PH
(25) (27, 28)
PFIC (mdr2 deficiency)
Overexpress mdr2
Bile acids enhanced by regimen
None
(23)
Analbuminaemia
Spontaneous
Retrorsine
None
(29)
ApoE deficiency
Express Bcl-2
Fas-induced apoptosis
None
(19)
Hyperoxaliuria type 1
Spontaneous
X-irradiation
Adenovirus HGF
(30)
Hyperphenylalaninaemia
Spontaneous
FAH deficiency
3.2. Developing Rodent Models with a Humanized Liver
(31)
There are two main interests in developing small mammalian models with a humanized liver. 1. These models are the only way to study the life cycle and particularly the entry of hepatotropic infectious agents and to develop efficient drugs against them. Hepatitis B and C viruses or Plasmodium falciparum are excellent examples of pathogens that replicate only in human and in nonhuman primates. Chimpanzee is the best for HBV, HCV and P. falciparum studies, but are difficult to use as an animal model for financial, technical and obvious ethical reasons. Marmosets and Tupaia (shrew genus) are also permissive for HCV and other primates, such as rhesus, gibbons and orangutans, for HBV infection, but these are not easily obtained animal models as well. Human hepatocytes or human cell lines can be infected by these above-cited pathogens only if these cells maintain criteria of differentiation and maturity (see Chapters 24 and 25). For HBV or HCV, transient transfection strategies can result in production of virions but entry steps of the viruses cannot be studied by this approach. 2. The second major application is for toxicological studies. Hepatocytes from readily available mammalian species, such as the mouse, are not suitable for drug testing because they have a different set of metabolic enzymes and respond differently in induction studies than human cells. Moreover, immortal human liver cells or foetal hepatoblasts cannot replace fully differentiated adult cells because of the
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immaturity of their drug metabolism pathways. Being able to develop a true human cell factory in vivo could therefore be considered as real progress, considering the difficulty to obtain fresh human hepatocytes, to expand them in vitro and to cryopreserve them. When backcrossed onto various immunodeficient backgrounds (SCID, lacking B and T cells, Rag2–/– or Rag2–/– combined with perforin 1 knockout mice that show in addition a depletion in NK cells), uPA mice tolerate woodchuck (32, 33), Tupaia (34) and finally human hepatocytes (35, 36). This humanized liver mouse model has been progressively improved and used to recapitulate human infection by HBV, HCV or P. falciparum (37–40). More recently, prevention of HBV infection using entry inhibitors was even demonstrated (41). Six years were necessary to finally obtain a humanized liver in FAH-deficient mice (42, 43) (see Chapter 27). The transplantation of human hepatocytes into FAH–/– nude (lack of T cells), FAH–/– NOD/SCID or FAH–/–/Rag–/– mice (lack of both B and T cells) was unsuccessful. FAH–/– mice were then backcrossed with Rag2–/–/ Il2–/– to obtain animals lacking B, T and NK cells. This immunosuppressed background alone was not sufficient to achieve a satisfactory level of implantation and repopulation with human hepatocytes, and two very different strategies were developed in this background to obtain a mouse with a humanized liver. One group (42) injected an adenovirus encoding the urokinase plasminogen activator (uPA) to allow engraftment of human cells, while another group (43) used additional treatments such as clodronate and nafamostat mesilate to induce Kupffer cell depletion and prevent complement activation. Only in these conditions a 90% liver repopulation by human hepatocytes was obtained 3 months after transplantation with expression of various detoxification enzymes of human origin. The expression of more than 1 mg/ml of human albumin secretion in the serum was reported, but in only a low proportion of transplanted animals (42). While infection with HBV, HCV or Plasmodium has not yet been reported, these results suggest that this model could already be used for pharmacological studies. The different publications concerning these two models deserve some comments and comparisons. In the uPA-deficient mice, spontaneous reversion occurs frequently. Since human hepatocytes proliferate slower than mouse hepatocytes and because it has already been demonstrated that cells maintain their own replicative rate once transplanted in another species (44), reverted murine hepatocytes compete with human transplanted hepatocytes to repopulate a mouse liver. To avoid this drawback, homozygous transgenic mice are used as recipients. However, homozygous uPA transgenic mice on immunodeficient backgrounds are very fragile, do not breed easily and finally
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required the infusion of human cells in a very tiny window of time, the best being between 4 and 21 days after birth. FAH mice are more robust, provided that NTBC is sequentially introduced and removed. Only a few laboratories in the world handle this model correctly. Human hepatocytes can be transplanted at any time. However, additional treatment is required to obtain efficient human liver repopulation, either by injecting an adenovirus vector expressing uPA to enhance human hepatocyte engraftment (42) or by preventing human complement activation and inducing Kupffer cell depletion (43). This latter point raises the more general question of the immunosuppressive treatment required to obtain a reproducible and efficient humanized liver mouse model. It has been demonstrated that macrophage and NK cell control was necessary to obtain a longterm liver repopulation with human cells (40). One could wonder whether other liver repopulation rodent models described above will be suitable for engraftment, proliferation and maintenance of human hepatocytes. Rat hepatocytes, that are spontaneously resistant to Fas-induced apoptosis, repopulates the liver of SCID/beige immunodeficient mice (45). However, the absence of a continuous selective pressure will probably hamper the repopulation of the liver with human cells using this strategy. Finally, although it is beyond the scope of this chapter, two other models of humanized rodents are also suitable for infection with hepatotropic human viruses: immunotolerized rats and trimera mice (46, 47). In the first model, foetal rats are immunotolerized by in utero injection of a human hepatocyte cell line. After birth, neonates, which are not yet immunocompetent, receive human hepatocyte transplants and are consecutively infected by hepatotropic viruses HBV or HCV. The interest of this model is its immunocompetency, particularly for vaccine evaluation, and the absence of requirement of fresh human hepatocytes, but it is less physiological and only reaches 6% of liver cells as compared to 30–90% in a model of liver repopulation. In the second model, mice are irradiated, bone marrow transplanted and reconstituted with immunodeficient cells. Mice are then transplanted with a human liver fragment pre-infected with HBV or HCV, usually at an ectopic site (ear or kidney capsule). This latter model produces antibodies and has been used to evaluate the inhibitory capacity of drugs. While these two models are suitable to study some aspects of HCV and HBV biology, they only induce very low viraemia in contrast to uPA transgenic mice. 3.3. Entering the “Stem Cells Field Forever”
The search for an universal stem cell able to differentiate into mature and functional hepatocytes is as precious but as difficult to reach as the Holy Grail. Liver repopulation mouse models are useful tools for this quest. They provide the possibility to study
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the fate of transplanted stem cells in an in vivo context, particularly their ability to engraft, proliferate, be polarized and correctly organized, connect together and with adjacent cells, forming bile canaliculi and, finally, to reconstitute a normal parenchyma. Therefore, liver repopulation models bring more, although not all, criteria of functionality than in vitro or other in vivo studies. 1. Intrahepatic stem cells. Rat foetal hepatoblasts (48–50), embryonic mouse liver progenitor BMEL cells (51) or human foetal liver multipotent progenitor cells, hFLMPC (52), have been demonstrated to be bipotent with the help of liver repopulation models. However, one can observe that these stem cells are often less efficient in regenerating a rodent liver than primary hepatocytes of the same species and in the same context (51, 52). The monocrotaline approach also helped to show, although still controversial, the bone marrow origin of oval progenitor cells (53, 54). In contrast to adult hepatocytes, rat foetal liver epithelial cells have a specific behaviour: a partial hepatectomy is the only required acute stimulus allowing these cells to achieve levels of repopulation in the 20–30% range (55, 56). It has been shown that transplanted foetal cells induce apoptosis in neighbouring resident cells allowing the transplanted foetal liver cells to proliferate and repopulate the recipient liver without the need to block local hepatocyte proliferation, a phenomenon called cell–cell competition. However, an equivalent observation with human foetal cells is still pending. 2. Stem cells outside the liver. Tyrosinaemic mice have been particularly contributive in the breakthroughs on bone marrow stem cells plasticity. Indeed, in the FAH–/– mouse model, infusion of wild-type haematopoietic stem cells led to the correction of the metabolic defect and survival of the animals (57). Then, still using FAH mice, the nature of the cell involved was unveiled (58–61) and it was demonstrated that a fusion event between a bone marrow-derived myelomonocytic cell and a resident hepatocyte was mostly responsible for the phenomenon (62). Finally, various models were used to demonstrate the scarcity of this transdifferentiation event (63, 64) in comparison to the level of liver repopulation obtained after bone marrow transplantation with that obtained after hepatocyte transplantation in the same period of time. In most cases, engraftment and in vivo hepatocyte differentiation of stem cells (adult mesenchymal stem cells, embryonic stem cells, umbilical cord blood, etc.) were not demonstrated in liver repopulation rodent models stricto sensu but in mice submitted
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to an acute or a chronic liver injury (47). However, in these models, it is not possible to demonstrate a therapeutic effect nor to determine the true maturity of these differentiated stem cells that only scatter in the injured parenchyma. These models were, however, used to demonstrate the marginal capacity to differentiate in vivo into cells expressing hepatocyte markers. They also helped in discarding a fusion event with resident cells (65, 66), in uncovering a potential deleterious effect, such as a profibrogenic potential (67), or a potential therapeutic benefit due to a paracrine effect on resident hepatocytes (68). Until now, it has been difficult to compare all these experiments because they have used different rodent models, various routes of administration, various numbers of transplanted cells and, in the case of xenotransplantation, different immunosuppressive protocols. Clearly, efforts have to be made to standardize the use of these tricky models to really compare the efficiency of stem cells to regenerate a liver. Because of their strong continuous selective pressure and their ability to accept human hepatocytes, FAH- and uPA-immunodeficient mice remain the quintessential models to demonstrate the proliferative capacity and therapeutic potential of a given stem cell. However, a combination of both in vitro and in vivo approaches will probably be required to accurately define the hepatocyte fate of a stem cell and demonstrate the therapeutic benefit of its transplantation. Campard et al. (69) have elegantly illustrated this caveat with hepatocyte-like cells derived from the umbilical cord matrix. These cells show active cytochrome CYP3A4 activity; they are at least partially polarized in vitro and have the capacity to produce urea and to store glycogen. However, they also lack the expression of other mature hepatocyte markers and, as described for mesenchymal stem cell-derived hepatocytes (59), they also show the persistence of markers of their original lineage. One other example has recently been developed, using murine embryonic stem cellderived hepatic progenitor cells that give rise to cells with a hepatic phenotype but that show a very limited capacity to repopulate FAH/SCID mice, probably due to an immature phenotype (70). The same conclusion has been reached using hepatic precursors derived from human embryonic stem cells in the uPA-SCID mouse model (71). In conclusion, better than to look for one universal stem cell, would be to use a variety of bona fide stem cells with hepatocytic potential. It should be indeed emphasize that the criteria required to correct a specific metabolic disorder will be different from the ones required to treat liver deficiency in a cirrhotic patient. In any case, the demonstration that a stem cell repopulates efficiently a diseased mouse liver in vivo at a level not too far from normal hepatocytes will certainly be a decisive point.
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minor population of hepatocytes that can be selectively amplified in vivo. Hepatology 35, 799–804. Herrera, M.B., Bruno, S., Buttiglieri, S., Tetta, C., Gatti, S., Deregibus, M.C., Bussolati, B., and Camussi, G. (2006) Isolation and characterization of a stem cell population from adult human liver. Stem Cells 24, 2840–2850. Sato, Y., Araki, H., Kato, J., Nakamura, K., Kawano, Y., Kobune, M., Sato, T., Miyanishi, K., Takayama, T., Takahashi, M., Takimoto, R., Iyama, S., Matsunaga, T., Ohtani, S., Matsuura, A., Hamada, H., and Niitsu, Y. (2005) Human mesenchymal stem cells xenografted directly to rat liver are differentiated into human hepatocytes without fusion. Blood 106, 756–763. Valfre di Bonzo, L., Ferrero, I., Cravanzola, C., Mareschi, K., Rustichell, D., Novo, E., Sanavio, F., Cannito, S., Zamara, E., Bertero, M., Davit, A., Francica, S., Novelli, F., Colombatto, S., Fagioli, F., and Parola, M. (2008) Human mesenchymal stem cells as a two-edged sword in hepatic regenerative medicine: engraftment and hepatocyte differentiation versus profibrogenic potential. Gut 57, 223–231. Kuo, T.K., Hung, S.P., Chuang, C.H., Chen, C.T., Shih, Y.R., Fang, S.C., Yang, V.W., and Lee, O.K. (2008) Stem cell therapy for liver disease: parameters governing the success of using bone marrow mesenchymal stem cells. Gastroenterology 134, 2111–2121, e2111–e2113. Campard, D., Lysy, P.A., Najimi, M., and Sokal, E.M. (2008) Native umbilical cord matrix stem cells express hepatic markers and differentiate into hepatocyte-like cells. Gastroenterology 134, 833–848. Sharma, A.D., Cantz, T., Vogel, A., Schambach, A., Haridass, D., Iken, M., Bleidissel, M., Manns, M.P., Scholer, H.R., and Ott, M. (2008) Murine embryonic stem cell-derived hepatic progenitor cells engraft in recipient livers with limited capacity of liver tissue formation. Cell Transplant. 17, 313–323. Haridass, D., Yuan, Q., Becker, P.D., Cantz, T., Iken, M., Rothe, M., Narain, N., Bock, M., Nörder, M., Legrand, N., Wedemeyer, H., Weijer, K., Spits, H., Manns, M.P., Cai, J., Deng, H., Di Santo, J.P., Guzman, C.A., Ott, M.(2009)Repopulation efficiencies of adult hepatocytes, fetal liver progenitor cells, and embryonic stem cell-derived hepatic cells in albumin-promoter-enhancer urokinase-type plasminogen activator mice. Am J Pathol.175, 1483-1492.
Chapter 27 Chimeric Mice with Humanized Liver: Tools for the Study of Drug Metabolism, Excretion, and Toxicity Stephen C. Strom, Julio Davila, and Markus Grompe Abstract Recent developments in animal models have allowed the creation of mice with genetic alterations that cause hepatocyte damage that results, over time, in the loss of native hepatocytes. If donor, human hepatocytes are transplanted into these animals, they repopulate the host liver, frequently replacing over 70% of the native liver with human cells. Immunodeficient mice that overexpress urokinase-type plasminogen activator (uPA) and, alternatively, with a knockout of the fumarylacetoacetate hydrolase (Fah) genes are the two most common mouse models for these studies. These mice are called chimeric or “humanized” because the liver is now partially repopulated with human cells. In this report we will review the published work with respect to Phase I and Phase II metabolic pathways and the expression of hepatic transport proteins. While the studies are still at the descriptive stage, it is already clear that some humanized mice display high levels of repopulation with human hepatocytes, express basal and inducible human CYP450 genes, and human conjugation and hepatic transport pathways. When the strengths and weaknesses of these humanized mouse models are fully understood, they will likely be quite valuable for investigations of human liver-mediated metabolism and excretion of drugs and xenobiotics, drug–drug interactions, and for short- and long-term investigation of the toxicity of drugs or chemicals with significant human exposure. Key words: Human hepatocytes, cytochrome P450, conjugation, hepatic transport proteins, hepatotoxicity, drug–drug interactions.
1. Introduction By virtue of its expression of high levels of the enzymes involved in drug and xenobiotic metabolism and excretion, the liver has been the focus of much of the research related to drug metabolism and excretion. Also because of its critical role in xenobiotic and drug metabolism and excretion, the liver is a frequent P. Maurel (ed.), Hepatocytes, Methods in Molecular Biology 640, DOI 10.1007/978-1-60761-688-7_27, © Springer Science+Business Media, LLC 2010
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target for the toxic manifestations of these agents. In addition to toxicity from chemical entities, hepatotropic viruses, and parasitic infections are responsible for massive amounts of human suffering and billions of dollars in health-care costs across the globe. Since there are large differences in their expression of the metabolic pathways involved in drug or xenobiotic metabolism and excretion or in the susceptibility of the liver to viral or parasitic infections between commonly used laboratory animals and humans, experiments with animals do not always faithfully predict or model what is observed in human subjects. To overcome some of these issues, mouse models have been created whereby the native mouse liver is replaced with human liver cells. Although this area of science is relatively new, there is sufficient data published to indicate that chimeric or “humanized mice” will be useful for investigations of metabolic pathways normally expressed in human liver. While humanized mice have been shown to be amenable to viral infections with hepatitis B or C and the hepatic stage of malaria, this chapter will focus on the review of the literature on models of drug metabolism and excretory pathways in chimeric mice. A number of approaches have been tried to get data relevant to humans, including replicating human cell lines, transgenic insertions of human genes, short- or long-term cultures of human hepatocytes and now also mice with humanized livers. Replicating cell lines have been used extensively to model human metabolism. However, there are no continuously replicating cell lines that provide normal liver levels of metabolic activity over a wide range of functions. Thus, they provide poor predictive value with respect to human liver metabolism. A second method that has proven useful is to humanize a mouse via a transgenic approach where the mouse ortholog is first knocked out and the human gene, such as a CYP gene, is inserted and expressed (1, 2). This approach has proven useful; however, there are a number of factors that may induce inappropriate expression of the transgene. The chromosome and the exact location where the BAC integrates can have a profound effect on transgene expression (3–5). The genetic background of the mouse strain also influences transgene expression presumably because of the presence or absence of modifier genes expressed concurrently in the mouse cells (6–8). The particular BAC containing the selected human gene may or may not contain all of the requisite cis- or trans-regulatory sites/sequences needed to observe normal expression of the transgene (9, 10). Also, even if the transgene is expressed appropriately in mouse hepatocytes, the remaining cellular components such as inhibitor and activator proteins and the cofactors for the reactions are all derived from the mouse and may not interact as efficiently or effectively with the human genes/gene products. Finally, drug metabolism and elimination does not rely on the expression of a single enzyme,
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but rather on the expression of whole pathways including Phase I and Phase II enzymes, hepatic transport proteins and the coordinated flow through these pathways during the metabolism and elimination process. Thus, one cannot create whole humanized metabolic networks inserting one gene at a time via the transgenic approach. To overcome some of these limitations investigators have employed human hepatocytes in suspension or short- or longterm culture to investigate human-relevant drug metabolism processes (11–19). It is now clear that human hepatocytes provide the most useful and relevant data concerning the disposition of drugs by the human liver, but even these studies are limited to relatively short-term assays, the longest generally out to 30–40 days (20, 21). Recent efforts have focused on methods by which human liver metabolic pathways could be studied in long-term, in vivo, models. These models have had to be generated, not through cross-breeding of transgenic lines but in a brute-force approach whereby the liver of a suitable recipient animal is repopulated to high levels following the transplantation of human hepatocytes.
2. Mouse Models The mouse models used for repopulation studies have some common elements. The mice are severely immunodeficient so that they will accept the xenograft of human hepatocytes. The second common features are genetic alterations in genes expressed in the liver that result, over a period of time, in the destruction of native hepatocytes. The loss of hepatocytes in these models allows the donor-derived hepatocytes a niche for engraftment and the regenerative stimulus to promote proliferation of the donor cells in the mouse liver. The earliest reports of substantial repopulation of a mouse liver with human hepatocytes were published in 2001 by Dandri et al. (22) and Mercer et al. (23). In the report by Dandri, mice were rendered immunodeficient by knocking out the recombinant activation gene-2 (RAG-2) while in the report by Mercer, the investigators used animals with severe combined immunodeficiency (SCID). In both reports, the liver failure was induced by expression of an albumin-promoted urokinasetype plasminogen activator (uPA). A review of the background on previous studies with these types of animals is provided by Dr. Gilgenkrantz in Chapter 26. Cell damage in the uPA model is thought to be caused by the intracellular activation of plasminogen which in turn activates plasmin which induces
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proteolytic damage inside the hepatocytes, particularly in the endoplasmic reticulum. Since these initial studies were focused on propagation of hepatitis viruses, the low levels of repopulation (up to 15%) were sufficient for that application. More recently, through a combination of optimizing the protocol and selection of particularly useful donor hepatocytes, Tateno and coworkers report much more consistent and higher levels of repopulation with the Alb-promoted uPA/SCID (hereafter referred to as uPA/SCID) animals (24–28). Grompe and coworkers have used a different approach to generate humanized mice (29). They first generated mice in which fumarylacetoacetate hydrolase (Fah), a gene in the catabolic pathway for tyrosine, is deleted. Accumulation of the toxic metabolite fumarylacetoacetate induces chronic liver damage. The drug 2(2-nitro-4-trifluoro-methylbenzoyl)1,3-cyclohexedione (NTBC) blocks the accumulation of the toxic metabolite and prevents liver damage, so that animals can be maintained in a healthy state while on the drug and selective pressure for repopulation of the liver with donor (Fah-proficient) cells can be applied by withdrawal of NTBC. This strategy has proven to induce a robust expansion of transplanted cells (30, 31). When the Fah(–/–) mice were crossed with Rag-2(–/–) and interleukin 2 receptor common gamma chain(–/–) mice, a triple mutant mouse
FAH-/- mouse Catabolic Pathway for Tyrosine Tyrosine
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Selective growth of human hepatocytes (HH). HH proliferate extensively, replace damaged host hepatocytes and restore normal liver structure and function
Fig. 27.1. Humanized mouse liver model (FRG). A deficiency in Fah activity leads to the accumulation of metabolites of tyrosine that are toxic to native hepatocytes. Transplants of Fah-proficient hepatocytes lead to replacement of the native cells and repopulation of the liver with donor cells. Stem cells from various sources may be useful sources of hepatocytes in the future.
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was produced (FRG), which was immunodeficient at two loci and still retained the selective pressure provided by the Fah deficiency. When transplanted, the FRG mouse readily accepted the xenograft and mice are highly repopulated with human hepatocytes (29) (Fig. 27.1).
3. Properties of a Model Useful for Generating Chimeric Mice
A robust model for generating chimeric “humanized” mice would have some basic properties that are summarized in Table 27.1. When the uPA/SCID and FRGF models are compared, there are certain traits with the FRG model that are quite useful. The selective pressure to regenerate the liver is controllable in the FRG model but is lacking in the uPA/SCID animals. Since the FRG animals are maintained on NTBC prior to transplant, virtually no liver damage is observed in the animals. Selection can be initiated by withdrawal of NTBC at any desired time. Also since the animals are maintained in a healthy state on NTBC, the animals breed normally and because of this property homozygous Fah(–/–) mice can be used as breeders. There is high neonatal mortality with the Alb-uPA model and breeding is more difficult; heterozygous breeding pairs are normally maintained which lowers the yield of homozygous animals in any given litter that are useful for transplant studies. Also because of the overexpression of urokinase, the animals have a particularly severe bleeding problem which necessitates that the animals receive transplants within a short window of time prior to weaning. Since the selection cannot be controlled, the strong regenerative pressure put on the failing liver frequently results in the deletion of the uPA
Table 27.1 Properties useful for the generation of chimeric mice Extensive liver humanization
Albumin-uPA
FRG
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transgene in a small number of mouse hepatocytes that effectively compete with the transplanted human cells during liver repopulation. The FRG is a knockout and not a transgenic mouse model, so genotype reversion cannot occur, and this feature leads to perhaps one of the most important advantages of the FRG model, that is, serial transplantation. Because genotype reversion does not occur in the FRG model, the native mouse hepatocytes remain Fah(–/–) and cannot compete with Fah-proficient donor cells. Thus, human hepatocytes from one repopulated mouse can be recovered by collagenase perfusion and transplanted into additional mice, expanding the numbers of animals that can be repopulated from an original human donor. An example of serial transplants is presented in Fig. 27.2 that shows that hepatocytes from a single human donor generate which then can be used as donor cells for additional transplants. In the case shown, cells from one of the recipient mice eventually gave rise to 15 additional humanized mice through four serial transplants. This means that even small numbers of mice receiving primary transplants can be used to generate larger numbers of humanized mice through serial transplants for large studies or that unique or precious human genotypes can be maintained and passed on to subsequent generations of mice long past the lifetime of the original recipient mouse. An added feature of the serial transplants is also shown in Fig. 27.1, that is, the numbers of animals successfully engrafted with human hepatocytes generally improve with serial transplantation, perhaps because of the high viability of cells recovered from highly repopulated mice or possibly because the human cells somehow adapt to the mouse environment in the initial mice and engraftment and repopulation proceeds more effectively upon serial transplantation.
Human Hepatocytes Primary Recipient
Secondary Recipient
Tertiary Recipient
Quaternary Recipient
Fig. 27.2. Serial transplantation of human hepatocytes.
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Significant renal damage has been reported in Alb-uPA animals that are highly repopulated with human cells, whereas no renal damage was noted in highly repopulated FRG mice. A final advantage of the FRG model is its ability to accept xenografts from all human donors tested. In the initial study, successful engraftment was observed with hepatocytes from nine of nine different donor cases ranging in age from 1 to 64 years (29), while the reports with the Alb-uPA model generally rely on hepatocytes from a small number of young donor livers (24, 25, 27, 28, 32). It is important to point out, however, that high-level repopulation (>90%) with human hepatocytes can be obtained with both models, so that both approaches are highly effective when applied properly.
4. Methods for Generating Chimeric Humanized Mice in the FRG Model
The FRG mice are immune-deficient Fah knockout mice lacking the genes for Rag-2 and the common gamma chain of the interleukin receptor. These animals breed normally while on NTBC. These FRG mice can be readily repopulated with human hepatocytes after pre-treatment with a vector expressing urokinase 1–3 days prior to transplantation. The standard method involves injection of 250,000–1 million cells into the spleen of adult FRG mice. One to three days prior to transplantation, each mouse is given 1×109 pfu of an adenoviral vector expressing human urokinase (uPA). This manipulation significantly enhances initial cell engraftment. Any post-weaning animal can be transplanted and we prefer mice 4–6 weeks of age. Animals are given broad spectrum antibiotics prior to surgery and for 1 week after transplantation. NTBC is withdrawn on day 1 after transplantation to induce liver disease and graft selection. If a transplanted mouse loses >20% of its pre-transplant weight, NTBC is re-administered for 5 days. This break in selection permits the animal to recover before further selection. The level of engraftment and repopulation is monitored by measuring blood levels of human albumin monthly using an ELISA kit from Bethyl. Successful repopulation with mature human hepatocytes in chimeric mice is estimated by qRT-PCR for important markers of hepatocellular function, particularly drug metabolism. The expression of human hepatocyte-specific genes is normalized to human cyclophillin, beta-actin, and/or beta-2 microglobulin mRNA levels, and comparisons are made between the values obtained with chimeric mice and those observed in the donor tissue. The mRNA levels are also compared to human fetal liver.
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The panel of markers is informative to determine the maturity of the cells produced. In general, the degree of humanization of the liver correlates with human albumin blood levels in that 1 mg/mL corresponds to ∼20% human hepatocytes. In many animals very high levels of humanization can be achieved, as documented with immunohistochemistry for FAH or human albumin or cytokeratin expression, as well as FACS analysis of hepatocytes harvested from FRG mice stained with antibodies that react selectively with human or murine surface antigens (29). In serial transplantation, the liver of a previously humanized mouse is perfused with collagenase and the isolated cells are retransplanted into additional FRG mice. Since there is no possibility of genetic reversion in the FRG model, residual mouse cells in the transplant do not compete with the human cells for repopulation of the next generation mice (Fig. 27.2). Although the initial studies were conducted by the transplantation of hepatocytes into the spleen of 4- to 6-week-old mice, using the same model (FRG mice), Bissig et al. reported that neonatal mice could receive direct injections of hepatocytes into the liver parenchyma, and levels of repopulation up to 7% were obtained (33). In separate studies, we reported nearly identical levels of repopulation (6–8%) in a mouse model of a metabolic liver disease following direct liver injection of hepatocytes into neonatal mice (34). Although there is robust repopulation of the FRG mice with human hepatocytes, it is the result of integration and expansion of human cells, as there is no evidence of cell fusion in this model (29, 33). Also, the human cells are susceptible to transduction with lentivirus (33) or retroviruses (35) and express the transgene for at least 2 months, suggesting that the humanized models will also be useful for gene therapy protocols.
5. Expression and Induction of CYP450 Genes, Proteins, and Metabolic Activities in Humanized Mice
The first report of the investigation of human CYP450 gene expression in highly humanized uPA/SCID mice was by Tateno et al. in 2004 (24). She reported high levels of repopulation of many animals with human cells and indicated that nearly onethird of their transplants resulted in animals with a level of repopulation with human hepatocytes estimated to be greater than 70%. These investigators calculated what they termed the replacement index (RI), which was determined as the percent of the area occupied by human hepatocytes in representative tissue sections each made of six or seven liver lobes. Human cells were determined by
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immunohistochemistry with antibodies that specifically react with human but not mouse cytokeratin 8/18 or by in situ hybridization studies with hDNA probes. The RI as calculated from hDNA correlated well with the RI calculated by immunohistochemistry and both correlated well with the amount of hAlb in the mouse plasma or serum. In future studies, the RI calculated by immunohistochemistry and circulating hALB would be used to estimate the level of replacement of the mouse liver with human cells. Animals with 50% repopulation, or greater, suffered multisystem damage, particularly necrosis and atrophy of the kidney, that had to be treated with anti-complement drugs. It was suggested that the secretion of human complement factors by hepatocytes resulted in severe proteolytic damage to host tissues. Administration of Futhan, an anti-complement drug, reversed the symptoms and allowed higher level repopulation with human hepatocytes. These investigators could identify human-specific mRNA for CYPs 1A1, 1A2, 2C9, 2D6, and 3A4 and reported a profile of gene expression that was similar to the original donor liver. Protein expression of CYP2C9 was confirmed by Western blots. Microsomes isolated from chimeric mice showed diclofenac 4-hydroxylase activity that was significantly greater that the mouse control animals. These investigators reported that the level of many of the CYP genes was actually higher in chimeric mice with highly repopulated livers than in the original donor liver tissue. This observation was confirmed in subsequent reports. Expression of CYP enzymes, in vivo, was investigated in greater detail by Katoh et al. (25). These investigators measured the mRNA levels by quantitative RT PCR, protein expression by Western blots, and metabolic activity for specific human CYPs based on drug metabolism studies with microsomal proteins isolated from the chimeric mice. They reported the expression of all of the major human CYPs and like Tateno et al., previously, showed that the level of expression of the human CYP in the mouse liver correlated well with the levels of circulating hAlbumin (hAlb) detected in the serum of chimeric mice. Thus, the levels of repopulation of the chimeric mice can be assessed and estimated simply by monitoring the levels of circulating hALB. When compared to control, non-transplanted animals, microsomes from chimeric mice demonstrated significant metabolic activity generally attributed to specific CYPs including CYP2C9-mediated diclofenac-4-hydroxylase (DICOH), 3A4-mediated dexamethasone 6-hydroxylase (DEXOH), 2A6mediated coumarin 7-hydroxylase (COH), 2C8-mediated paclitaxel 6-hydroxylase (PTXOH), 2C9-mediated S-mephenytoin 4-hydroxylase (MPOH), and 2D6-mediated debrisoquine 4-hydroxylase (DBOH). These authors also observed that protein and activity levels measured in highly repopulated mice were frequently slightly higher than that observed in a sample obtained
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from the donor liver; however, in general they concluded that the mice maintained the genotype and phenotype of the donor. The expression of mature human liver genes in the FRG model was reported by Azuma et al. (29). In these studies the expression of the genes in the chimeric mouse liver was compared to adult liver (N=8 donors) and also to the levels of expression observed in fetal human liver tissue. The expression of the mature liver genes Alb, CYP1A2, and CYP3A4 was found to be expressed at the same levels as observed in the donor livers. The expression of alpha fetoprotein (Afp) was detected in all tissues, but the levels on the FRG mice were the same as those observed in mature human liver and much lower than those observed in fetal human liver. These data indicate that human hepatocytes maintain a mature phenotype following transplantation and engraftment into FRG mice. Similar studies of fetal versus the adult phenotype were not reported with the uPA/SCID animals. A more detailed investigation of CYP2D6-mediated metabolism of debrisoquin, in vivo, in chimeric mice was reported (36). Here the authors repeat the observations made previously that the metabolic activity associated with CYP2D6 correlates with the level of repopulation of the mouse liver with human hepatocytes, which in turn was indirectly estimated by measuring the levels of circulating hAlb. When debrisoquine (DB) is administered to non-transplanted control mice, metabolism of DB occurs, although the production of the specific metabolite, 4-hydroxy-DB (4-OHDB), was not observed. They also report that the production of 4-OHDB was significantly inhibited by prior administration of quinidine (100 mg/kg/day for 3 days), a known inhibitor of CYP2D6 in humans. Prior administration of peroxetine (30 mg/kg/day for 3 days), a selective serotonin reuptake inhibitor, and a mechanism-based inactivator of human CYP2D6 also caused a significant decrease in the area under the curve for the production of 4OHDB. It was reported that quinidine and paroxetine selectively inhibited the human hepatocyte-mediated production of 4-OHDB, but did not inhibit the background, mouse-mediated metabolism of DB, supporting the hypothesis that the 4-OHDB metabolite is human specific. Although intermediate levels of repopulation were not investigated, the specific production of 4OHDB in chimeric mice was observed in animals that were repopulated to a level of 70% or more with human hepatocytes, while mice with 10% or less repopulation with human hepatocytes were indistinguishable from control, non-transplanted animals. The level of repopulation required to observe metabolism attributable to the presence of human hepatocytes will likely differ between test drugs and will depend on the specificity of metabolite to human metabolism and the level of metabolism observed in non-transplanted mice for those metabolites that are not specific to human hepatocytes.
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The expression of CYP2A6 and coumarin hydroxylase activity was investigated in chimeric mice with an intention of determining if the level of repopulation of the liver could be estimated from the level of humanization of CYP2A6-mediated metabolism (37). Microsomes were prepared from chimeric animals with different levels of repopulation ranging from 0 to 84% as estimated by circulating hAlb levels and cytokeratin immunohistochemistry (24). The human liver expresses CYP2A6, and the mouse expresses Cyp2A5; however, there is significant overlap in substrate specificity. Since there was significant COH activity even in non-transplanted uPA/SCID animals, specific inhibitors of mouse and human COH activity were identified. Benzaldehyde and undecanoic-lactone (100 μM each) were identified as specific inhibitors of human (CYP2A6) or mouse (Cyp2A5)-mediated COH activity. As in the earlier papers, these authors attempted to correlate the RI with serum hAlb levels. In these studies, using large numbers of chimeric animals (N = 17) with a wide range of levels of repopulation, they did not see a good correlation between RI and hAlb levels until estimated levels of repopulation reached 50%. Thereafter there was a steep rise in hAlb as RI increased and a better correlation of RI and hAlb. This trend was not only observed with hAlb levels, as the estimated RI or hAlb levels did not correlate well with the COH activity until the level of repopulation reached or exceeded 50%. Thus, with respect to COH activity and hAlb secretion the mice did not display the humanized phenotype until a RI of 50% or more was obtained. These observations are unfortunate, because only 9 of the 17 mice used in these studies displayed RI of 50% or greater and would have provided reliable estimates of human-mediated metabolism. In addition to the basal levels, the induction of CYP enzymes, in vivo, in uPA/SCID chimeric mice was also investigated. Tateno et al. reported that when chimeric mice were administered prototypical CYP450-inducing agents such as rifampicin (Rif) or 3-methylcholanthrene (3-MC), in vivo, increased expression of mRNA for CYP3A4 and CYP1A1 and 1A2 was observed. Interesting, however, was that no increase in the expression of CYP2C9 or 19 was noted in these experiments following Rif administration. Katoh et al. reported that prior treatment of the mice for 4 days with rifampicin (50 mg/kg/day) induced the expression (RNA and protein) of CYP3A4 and DEXOH activity, CYP2A6 (RNA and protein) and COH activity, CYP2C9 (RNA and protein) and DICOH activity, and CYP2C19 expression (RNA) and MPOH activity (38). Except for CYP3A4, the level of induction of other genes was relatively small, and a subsequent report using this mouse model failed to demonstrate a significant induction of CYP2A6, 2C8, 2C9, or 2C19 following rifampicin treatment
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(32), so a certain amount of variability is to be expected in the system. Rifampicin treatment also increased the levels of mouse Cyp 3A11 expression and testosterone 6-beta-hydroxylase activity, which would confound in vivo metabolic studies of the metabolism of CYP3A substrates; however, prior induction with Rifabutin, a compound structurally similar to rifampicin, failed to induce mouse 3A expression of enzymatic activity, so rifabutin might be a useful and selective human CYP3A-inducing agent for in vivo studies with humanized mice. Basal and induced CYP1A family genes were also investigated in chimeric mice by Uno et al. (2). Because they are easier to use, many investigators prefer to use continuously growing cell lines or humanized transgenic animals carrying a single or only a few human CYP genes. In this chapter the authors compared the results of their investigation of CYP1A1 and CYP1A2 expression and metabolic activity between the chimeric humanized mice, a transgenic mouse strain carrying on a bacterial artificial chromosome (BAC) the human CYP1A1_CYP1A2 locus and lacking the mouse Cyp1a1 and Cyp1a2 orthologs and continuously growing cell lines Hepa-1c1c7 and HepG2. They reported that the transgenic humanized mouse strain expressed far lower CYP1A1-mediated metabolic activity than expected based on the RNA levels and what was observed in wild-type mice. In contrast hCYP1A2 appeared to function nearly as well as the mCyp1a2 in the wild-type mouse liver. These authors conclude that there are significant differences between the different models: chimeric mice, transgenic humanized mouse strains, and replicating cells lines. Depending on the application each can be used if one carefully characterizes the system and understands the limits of response. The results clearly indicated that the RNA expression and metabolic activity observed in the replicating cell lines were not reliable indicators of those processes, in vivo, and that the cells lines were no substitutes for authentic mouse or human liver. Since chimeric mice are quite rare, one does not necessarily want to have to terminate the animal and harvest liver tissue to conduct an analysisor to determine if CYP enzymes were induced by a specific treatment. A non-invasive method was reported for the examination of CYP3A4 metabolic activity in chimeric mice (39). When challenged with dexamethasone, human hepatocytes preferentially produce 6-b-hydroxydexamethasone while mouse hepatocytes preferentially produce 6-hydroxy-9 alpha-fluoro-androsta-14-diene-11 beta-hydroxy-16 alphamethyl-3,17-dione. Thus, human-specific metabolism of dexamethasone can be identified even when there is a significant background of metabolism contributed by the mouse liver. Emoto et al. (39) used these differences in metabolism to develop a non-invasive method to detect induction of CYP2A4 in chimeric mice with humanized liver. These investigators examined
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the change in the ratio of 6β-∼hydroxy DEX to DEX in the urine of animals before and after administration of rifampicin and determined that an increase in this ratio correlated with the induction of CYP3A4 in the human cells of chimeric mice. The authors also indicated that CYP3A5 was also able to metabolize Dex to the 6-hydroxy dexamethasone; however, the intrinsic clearance by CYP3A4 was approximately 50-fold higher than that of CYP3A5, so under ordinary circumstances the majority of DEXOH produced will be the result of CYP3A4-mediated metabolism. This technique works when one already understands the metabolic profile of the test drug when administered to mice and human subjects. A significant contribution of the mouse liver to the disposition of a drug in the uPA-SCID chimeric mice certainly confounds the analysis of drug metabolism and disposition using this model. Members of the CYP1A family were also induced by prior treatment of mice with 3-methyl cholanthrene (3-MC, 20 mg/kg/day) for 4 days. Steady state RNA levels for CYP1A1 and 1A2 were induced by 3-MC, and increases in CYP2A2 protein could be detected by Western blot. These investigators could not identify a metabolic assay for CYP1A activity because of high background activity in control mice. As expected, neither rifampicin nor 3-MC treatment increased CYP2D6 RNA, protein, or metabolic activity. In later studies, Nishimura et al. investigated the induction of CYP expression, ex vivo, in hepatocytes isolated from chimeric mice (27). In these studies hepatocytes were isolated and cultured from the liver of humanized mice. As expected, exposure of these cultured cells to prototypical inducers, beta-naphthoflavone (BNF) or rifampicin, resulted in significant increased expression (RNA) of CYP1A2 (2–6-fold) and CYP3A4 (2–8-fold), respectively. The authors did not report on the analysis of drug metabolic activity associated with these CYPs, perhaps due to excessive background metabolism by native mouse hepatocytes. This hypothesis is supported by the studies of Uno et al., where the authors analyzed microsomal proteins for CYP1A-mediated metabolism using four different assays (2). Ethoxyresorufin O-deethylase (EROD) and benzo(a)pyrene hydroxylase are general assays for CYP1A activity, but with a tendency to be more representative of CYP1A1 activity, while methoxyresorufin O-deethylase and acetanilide 4-hydroxylase are relatively more specific for CYP1A2 activity. The background activity in all four assays in control animals, that is, the non-transplanted uPA/SCID animals, was equal to or greater than the metabolic activity observed in human chimeric animals with repopulation indices of 50–70%. This was true of both the basal levels and the activity measured following maximal induction of CYP1A activity by prior exposure to TCDD. Like the CYP2A6-mediated metabolism of
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coumarin cited above, the background activity in the mouse interferes with the analysis of human-specific metabolism. This problem of high levels of background activity is not a characteristic of chimeric mice in general. In the FRG mice, animals with levels of repopulation with human hepatocytes estimated to be 10%, 30%, and 60% all showed basal EROD levels significantly higher than the non-transplanted mouse controls and also showed robust (8- to 40-fold) induction of EROD activity following a 2-day exposure to beta-naphthoflavone (29). As described above, the differences between these models most likely result from the spontaneous deletion of the transgene in the uPA/SCID model and competitive repopulation of the mouse liver with mouse cells concurrently with human hepatocyte repopulation. The mouse cells that have successfully deleted the transgene are robust and healthy and metabolize drugs in a manner characteristic for that mouse. Remnant mouse cells in the FRG mice are still deficient in Fah and are not robust or healthy when the animals are off of NTBC, thus they contribute little to the overall metabolic activity that can be measured in this model. Similar results were observed with CYP3A4-mediated metabolism of testosterone to the 6-beta-hydroxy metabolite, where the background activity with cultures of FRG hepatocytes alone contributed negligible amounts of product to that observed in control, rifampicin, or phenobarbital-induced cells from chimeric mice. The lack of competition and metabolic activity from the remnant mouse cells may be an important difference between the FRG and the uPA/SCID models especially when in vivo or ex vivo drug metabolism studies are planned.
6. Expression of Phase II Enzymes in Chimeric Mice
Chimeric humanized mice also express human Phase II enzymes, although the lack of specific substrates and useful specific antibodies prevented a detailed examination of some Phase II pathways (26). The expression (RNA) of UDP-glucuronyltransferase (UGT) 1A1, 1A9, and 2B7 was measured in chimeric mice, and the metabolic activity attributed to UGT2B7, morphine 6-glucoronyltransferase, was readily detected in assays of microsomal proteins. Troglitazone sulfotransferase activity attributed to sulfotransferase (SULT) 1A1 and estrone 3sulfotransferase activity attributed to SULT1E1 were analyzed in assays of subcellular fractions (microsomes and/or cytosolic proteins). Only RNA levels for SULT1B1 were analyzed because of a lack of suitable and specific metabolic assays and antibodies for Western blots. Sulfamethazine N-acetyl transferase attributed to
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N-aetyltransferase-2 (NAT2) activity was also measured in subcellular preparations derived from chimeric mice. As with SULT and NAT expression and metabolic activity, the expression of glutathione transferases (GST) genes 1A1, 1A2, and T1 correlated well with the levels of circulating hALB in chimeric mice. The authors concluded that the chimeric mice express functional Phase II genes and enzymatic activities and that the mice should be useful for investigations of these pathways in a manner relevant to humans. Elimination of drugs or xenobiotics from the body is dependent on the coordinated action of several pathways and normally includes metabolism by Phase I enzymes, conjugation of the parent drug and/or the metabolites, followed by transport out of the liver back into the circulation for possible urinary elimination or transport into the canicular space between hepatocytes which leads to biliary elimination in the feces. Since chimeric mice have humanized many parts of these pathways one might expect that following the administration of drugs, the mice would exhibit a human profile of drug elimination. This hypothesis was examined by Okumura et al. following administration of cefmetazole (CMZ), an antibiotic in the cephalosporin family (40). This drug is normally eliminated unchanged in rodents and humans, but by different routes. In humans, CMZ is eliminated predominately into the urine, while in rats and mice, the biliary pathway predominates. When CMZ was administered to uPA/SCID mice 23% of the dose was recovered in the urine while 59% of the dose was recovered in the feces. In chimeric mice with humanized livers, 81% of the dose was recovered in the urine over a 24-h period, while only 6% was recovered in the feces. These data indicate that when the liver of mice is repopulated with human hepatocytes, the preferred route of elimination of this drug changes from a rodent-type elimination to the general profile normally observed in humans. These data suggest that chimeric mice will be useful for investigating the pathways by which drugs or xenobiotics are excreted. Evidence of connections (immunohistochemical) between human hepatocytes and the mouse biliary tree was also reported by Meuleman et al., although drug elimination was not studied (41).
7. Toxicology Studies with Chimeric Mice with Humanized Liver
A long-sought goal of toxicology is the prediction of human toxicity using model systems (42). Chimeric mice offer the possibility of conducting toxicology studies with a compound toward human hepatocytes in vivo. Sato et al. reported the administration of
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acetaminophen to ICR mice and to uPA/SCID chimeric animals (43). Acetaminophen caused severe centrolobular necrosis in the ICR mice at doses of 400 or 1,400 mg/kg, while chimeric mice showed evidence of only mild vacuolation of hepatocytes, few TUNEL-positive cells, and a mild decrease in CYP2E1 expression as determined by immunohistochemical methods. At 24 h, all ICR mice were dead, while all chimeric animals were alive. Thus, selective APAP toxicity could be demonstrated between control and chimeric mice; however, in this case chimeric animals were much less sensitive to APAP toxicity as compared to control animals. The chimeric animals used for these studies showed high levels of repopulation with human cells (RI of 68–95%). Despite these high levels of repopulation with human cells, the animals still showed evidence of ongoing regeneration and proliferation in the human regions of the liver with a PCNA-labeling index ranging from 22 to 68%. The authors suggested that since the areas of liver containing human hepatocytes also showed evidence of continued replication, the human hepatocytes in the uPA/SCID animals may be functionally immature, and the resistance of the human cells to APAP toxicity might have resulted from the inability of the human cells to fully activate the toxicant. Clearly additional work needs to be done to determine the mechanism(s) responsible for the selective toxicity to mouse hepatocytes in this model.
8. Summary and Future Directions It is clear that the liver of mice can be humanized by the transplantation of human hepatocytes if specific genetic alterations in the mice allow the acceptance of the xenograft and also provide for a selective regenerative stimulus to the donor cells. It is also clear that virtually all of the human CYP or Phase II conjugation pathways and transport proteins examined are expressed in the chimeric animals. What is not entirely clear in many of the studies is how the levels of expression of these pathways in the chimeric mice compare to the expression of the same pathways in the donor liver. RNA levels or metabolic activity corresponding to CYP1A2 and 3A4 (24, 29) or 2C9 and 19 or 2A6 (24, 37) were reported, and animals with highly repopulated animals showed profiles that corresponded well with those observed in the donor tissue; however, additional CYPs, Phase II, and transport pathways need to be examined and quantified to get a clearer picture of the level of maturation of these pathways in chimeric mice. Since primers to quantify specific human genes can be devised, there is much
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more data available on the levels of RNA for the human genes than there is on protein levels or metabolic activity specific to the human hepatocytes. Thus, antibodies and assays that can discriminate between human and mouse cells are also needed. The presence of remnant mouse hepatocytes even in highly repopulated animals continues to be a significant problem, especially with the uPA/SCID animals (2, 27, 37), whereas the background mouse hepatocytes do not seem to contribute much metabolic activity in the FGR model (29). Although the drug-metabolizing genes are relatively well studied in these animals, additional basic studies are still needed to determine how the architecture of the remodeling/regenerating chimeric human liver might affect drug metabolism and excretion and overall hepatic metabolism. Relatively little is known of the level of interaction or connections between the human hepatocytes within the regenerative nodules. Careful studies will also be needed to identify the interaction of sinusoidal endothelial cells (mouse or human) with hepatocytes or to quantify the number of tight junctions between hepatocytes, the relative proportion of hepatocytes that form bile canicular structures, and the level of integration of the human hepatocytes with mouse or human components of the biliary tree. Sato et al. reported that in chimeric mice the human hepatocytes from trabecular cordlike structures and sinusoid-like structures were observed, that were lined with endothelial cells, although Kupffer cells were not apparent in the humanized areas (43). Since normal hepatic function relies on the proper interaction of hepatocytes with endothelial, Kupffer, stellate, and biliary components of the liver, these questions are not merely academic. Finally, other aspects of human liver metabolism can now be investigated. What are the levels and what types of bile acids are produced in chimeric mice? How functional is the enterohepatic circulation? What are the levels of cholesterol, HDL, LDL, and lipoproteins in chimeric mice? Can we induce fibrosis in the human portions of the mouse liver? Can we create other models of metabolic liver disease using this system? Will long-term toxicology studies with chimeric animals be able to predict the potential human toxicity of new drug candidates? Can we use chimeric mice to propagate or scale up unique genotypes, such as cells from specific ethnic groups, therefore addressing the concern about genetic diversity of the human population? Will long-term toxicology studies with chimeric animals be able to provide an earlier and more sensitive prediction of drug-induced liver injury (DILI) in human patients? Can we use the mice as continuous and real bio-reactors that could provide human hepatocytes on demand from our vivariums? Each of these questions is important and will surely be addressed in the near future.
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Chapter 28 Bioartificial Liver Support Systems Gesine Pless Abstract A variety of bioartificial liver support systems were developed to replace some of the liver’s function in case of liver failure. Those systems, in contrast to purely artificial systems, incorporate metabolically active cells to contribute synthetic and regulatory functions as well as detoxification. The selection of the ideal cell source and the design of more sophisticated bioreactors are the main issues in this field of research. Several systems were already introduced into clinical studies to prove their safety. This review briefly introduces a cross-section of experimental and clinically applied systems and tries to give an overview on the problems and limitations of bioartificial liver support. Key words: Bioartificial liver support, liver failure, hepatocytes, bioreactor.
1. Introduction: Therapies of Liver Failure
Since the liver is a complex organ which fulfils a variety of functions, its failure leads to a multitude of clinical symptoms. Usually, liver failure is divided into two main groups: while acuteon-chronic liver failure (AoCLF) is defined as acute decompensation of a chronic liver disease (e.g. alcohol-related cirrhosis and hepatitis), acute liver failure (ALF) occurs without liver-related prehistory. About 6% of all liver-related deaths and 7–8% of all liver transplantations are related to ALF in the United States. While in Europe and North America, the common causes for ALF are acetaminophen intoxication (almost 50% of all cases of ALF in the United States) and idiosyncratic drug reactions, hepatitis infection is the main cause in Asia and Africa. The mortality rate under intensive care treatment still reaches 60–90% (1–3). In liver failure, the accumulation of toxins, a disturbed regulation,
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and diminished synthesis capacity lead to derogated consciousness to the point of coma, encephalopathy, jaundice, coagulation problems, and impairment of renal and pulmonary function often leading to multiorgan failure. If the failing organ is not able to regenerate, the only effective therapy option until today is orthotopic liver transplantation. To replace some of the failing liver’s function, artificial detoxification devices were developed. Those devices are based on filtration and adsorption and are designed to remove toxins from the patients’ blood. The first attempts were made to clear water-soluble toxins by continuous venovenous haemodiafiltration (CVVHDF) or using simple adsorbers like activated charcoal. These treatments mainly removed water-soluble toxins as ammonia and mercaptans. Other more lipophilic toxic substances, for example, bilirubin, bile acids, aromatic amino acids, and fatty acids, are commonly bound to plasma albumin. To remove those toxins from the blood, several systems were developed that either use albumin as acceptor substance to remove toxins from the circulation (molecular adsorbent recirculation system (MARS) (4), single pass albumin dialysis (SPAD) (5), and Prometheus (6)) or remove the complete albumin–toxin complex from the circulation (plasmapheresis (7) and selective plasma exchange therapy (SEPET) (8)). With all systems a decrease in toxin concentration and, in some cases, an improved clinical status of the patient could be attained. However, those systems can only address the lack in detoxification by the liver, but not replace the regulation or synthesis capacity. This led to the development of bioartificial liver support devices, which follow the idea that the integration of a biological component in the form of liver cells can bring an additional benefit for the patient.
2. Cell Source The main issue of bioartificial liver support systems, and presumably the reason why most systems were never introduced to larger clinical trials, is to find an appropriate cell source. The ideal cell source would combine the following features: Availability (controlled and easy proliferation, unlimited sources) Highly active human liver-specific metabolism No inherent risk (zoonosis, virus transfer, metastasis formation, or immunogenicity)
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Unfortunately, all cell sources so far used for bioartificial liver support do not completely fulfil all the above criteria. Several systems are using adult primary cells – either of human or porcine origin – usually freshly isolated or sometimes cryopreserved and thawed before use. Those cells are in theory capable of the full amount of liver-specific metabolism. However, porcine cells may differ in some aspects from human metabolism, and not all synthesized proteins, especially when regarding coagulation factors, will have the desired effect in humans (9). Moreover, xenogenic cells carry the potential risk of zoonosis, such as porcine endogenous retroviruses (PERV), although no PERV transmission was seen so far in patients treated with porcine liver cells (10–12). Adult human cells may be obtained from discarded donor organs in sufficient quantity, but those organs are initially impaired and cells are further stressed by the isolation procedure, so that they will never reach their full metabolic potential. And finally, all primary adult liver cells lack the ability to proliferate in culture at sufficient rates, meaning that large amounts of cells have to be isolated in the first place and that metabolic capacity and viability of the cells inevitably decrease with time. To circumvent this fact, researchers investigate the use of foetal or embryonic stem cells or progenitor cells, which are still capable of proliferation, but do not yet display the same liverspecific metabolism as adult cells (13, 14). By first increasing the cell number while oppressing differentiation and then letting the cells differentiate to adult hepatocytes, one could attain large amounts of liver cells. The field of research is constantly worked on in rodent (15–17) and human cells (18, 19) by numerous groups. Instead of using progenitor cells, another possibility is to use cell lines derived from human liver tumours or to generate cell lines by immortalizing human hepatocytes. The cells should be able to proliferate to a large extent, although their proliferation can be controlled either by contact inhibition or by specific methods of genetic engineering. However, most cell lines only reach a fraction of the liver-specific metabolic activity of primary cells (20). C3A cells (from the hepatoblastoma cell line HepG2) were already clinically applied in a bioartificial liver support system (21). Other groups work in bioreactors with the HepG2 cell line (22–25) or other cell lines derived from hepatocellular carcinoma (26, 27). NKNT-3 cells introduced by Kobayashi et al. are human hepatocytes reversibly immortalized with a viral vector, which show gene expression of differentiated hepatocytes and proliferate in a defined growth medium (28). Several cell lines from immortalized foetal liver cells (29, 30) and immortalized adult liver cells (31–33) are tested for their applicability in bioartificial liver support.
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3. Bioreactor Design The idea to enhance the effectiveness of liver support systems by integrating a biological component already dates from the 1950s. The first approach was to introduce an intact liver extracorporally into the bloodstream via the large liver vessels (34–36). However, this method requires complicated logistics, because a freshly explanted liver has to be available and the tasks of connecting the liver to conventional tubing as well as to constitute a suitable surrounding for the organ are not trivial. This led to the development of culture devices to house isolated cells for extracorporeal liver support. In conventional cell culture, hepatocytes and hepatocyte-like cell lines are cultured in monolayers, usually on collagen-coated cell culture plastic surfaces. However, since for extracorporeal liver support, comparatively large cell masses are necessary to be able to attain a significant effect on the patient’s clinical status, this method is not feasible. Instead, most bioartificial systems offer a three-dimensional surface that serves as scaffold for the adherent cells. Hepatocytes can then reform tissue-like structures and a large cell mass can be cultured at high density, leading to relatively small bioreactor devices. The bioreactor has to provide sufficient surface of a suitable material for cells to adhere and reform aggregates. Further on, it has to ensure the medium and gas supply for the cells, keeping the diffusion distance between each cell and the nutrient/gas supply as small as possible. In most devices, the scaffold is provided in the form of hollow fibres sometimes combined with other matrix types. The matrix as well as the hollow fibres may be biodegradable (e.g. cellulose) and coated with collagen or other extracellular matrix. Usually, polyurethane, polyethersulfone, polyester, or resins are used. In some bioreactors, there are additional hydrophobic hollow fibres for decentralized gas supply, while in most devices, oxygen supply is implemented via direct medium oxygenation. Practically all clinically applied bioartificial liver support systems today are hollow fibre based. However, there are a variety of experimental systems which employ different means of bioreactor surrounding for the cells. An option to provide a threedimensional environment is the encapsulation of hepatocytes in beads or microcapsules. One of the most used encapsulation substances is alginate gel (37, 38). Within the hydrophilic gel, the cells can reform aggregates. Bead size is crucial to cell survival in the centre of the beads, since supply of nutrients and especially oxygen is limited by diffusion. The cell-containing spheres may then be utilized in a fluidized-bed bioreactor (39–41) or
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rotary systems mimicking microgravity (42–44). There are also attempts towards growing hepatocytes on biological structures such as loofa sponge (45) or on ceramic scaffolds (46). In radial flow bioreactors, medium flow is directed from the perimeter to the centre or vice versa, thus providing advantageous concentration gradients throughout the bioreactor. Cells within the system are seeded on microcarriers, enabling a threedimensional high-density culture (47–50). Already in the 1960s, some effort was directed towards culturing slices of liver tissue instead of using isolated cells (51–54). This method allows a very high-density culture and prevents cell damage caused by the digestion procedure. The cells remain within their normal microenvironment and nutrient and oxygen supply is established via capillary vessels. However, this type of culture is usually limited to several hours and was not yet applied in bioartificial liver support.
4. Bioreactor Systems for Clinical Application
In the 1980s, the first bioartificial liver support systems were applied clinically. Matsumura et al. published a case report of a man with inoperable bile duct carcinoma who was dialysed against a suspension of previously cryopreserved rabbit hepatocytes (55). Margulis et al. applied hemoperfusion through a suspension of porcine hepatocytes in a controlled study with 126 patients with acute liver failure of various origins (56). Both systems did not reappear in subsequent publications.
4.1. Extracorporeal Liver Assist Device (ELAD)
ELAD was developed by Sussman et al. It uses the human hepatocyte cell line C3A, which is derived from the hepatoblastoma cell line HepG2 (57). The cells are inoculated into the extracapillary space of one or two hollow fibre cartridges and are additionally separated from the patient’s blood by a filter to make a transfer of cells impossible. A membrane oxygenator and a charcoal adsorber are integrated into the circuit. The system was evaluated in anhepatic dogs (58) and several smaller clinical trials were performed (21, 59–61).
4.2. HepatAssist
This system applies 5–7×109 porcine hepatocytes which are previously cryopreserved. The bioreactor design is similar to that of the ELAD, resembling a dialysis cartridge with hollow fibres, where the cells are inoculated into the extracapillary space and the patients’ plasma is fed through the hollow fibres (62). As in ELAD, a charcoal adsorber serves additional detoxification and diminishes the toxin load applied to the cells, and a membrane
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oxygenator ensures the oxygen supply. The system was evaluated in several smaller clinical studies (63–66) and is the only bioartificial liver support device which has so far been evaluated in a prospective randomized controlled trial (67). 4.3. The Bioartificial Liver of the Amsterdam Medish Centrum (AMC-BAL) and the Radial Flow Bioreactor (RFB)
These clinically applied bioartificial devices have no additional membrane separating the patients’ plasma from the cells. In the AMC-BAL, about 1010 porcine hepatocytes are seeded in a nonwoven polyester matrix that is spirally wound within a cylindrical housing and encloses several layers of oxygenation capillaries (68, 69). Those capillaries are streamed with air containing 5% CO2 to bring decentralized oxygenation to the cells. The patients’ plasma is led in and out through ports at either end of the housing and comes into direct contact with the primary porcine liver cells, which are freshly isolated for application. Animal studies were performed in anhepatic pigs (70, 71) and therapy did significantly increase the survival time. Twelve patients were included in a clinical phase I trial showing the safety and efficacy of the system (72, 73). No PERV transmission could be detected in the patients (10). The RFB uses up to 1.5×1010 porcine hepatocytes in a bioreactor with radial flow geometry where the perfusion medium crosses the cell-filled compartment while flowing from the centre to the periphery. Inside a polycarbonate housing a combination of woven and non-woven polyester matrix layers (49, 74) provides cell adhesion surface. Precision-woven polyester screens with 1-μm cut-off prevent cell leakage from the matrix layers. Medium is recirculated through the bioreactor by a roller pump and oxygenation is achieved by bubbling 95% O2 /5% CO2 through the medium reservoir. The system was applied in seven patients; no adverse events occurred during treatment and no PERV transmission was observed (75).
4.4. Bioartificial Liver Support System (BLSS), TECA Hybrid Artificial Liver Support System (TECA-HALSS), and Hybrid Bioartificial Liver (HBAL)
These systems use freshly isolated porcine cells. TECA-HALSS and HBAL share the same bioreactor hardware, a polysulfone bioreactor with a membrane cut-off of 100 kD, while the BLSS uses cellulose acetate membranes with a similar cut-off. In contrast to most bioartificial liver support devices, the cells in those systems are not attached to microcarriers or the surface of a membrane or matrix, but kept in suspension and circulated through the extracapillary space of the hollow fibre cartridge. While TECA-HALSS and HBAL apply plasma perfusion, the BLSS is perfused with whole blood. Animal studies with TECA (76, 77) and BLSS (78–80) were performed in dogs. Both systems were introduced into clinical studies (81, 82). A clinical study with 12 patients was carried out with HBAL (83).
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4.5. Extracorporeal Bioartificial Liver Support System (EBLSS)
This system developed by Wang et al. also resembles a hollow fibre cartridge with polysulfone or cellulose nitrate/cellulose acetate membranes of a pore size of 0.2 μm. Cells are cultured in the extracapillary space and blood or plasma is perfused through the capillaries during treatment. Preclinical studies were carried out in an anhepatic dog model using 1×108 adult human liver cells cultured in spheroids (84) and a fulminant hepatic failure rabbit model with a bioreactor containing 1×108 human foetal liver cells (85). Three patients were treated with bioreactors containing up to 1.4×109 porcine liver cells (86).
4.6. Modular Extracorporeal Liver Support System (MELS)
This system developed by Gerlach et al. displays a more complicated architecture of hollow fibres. Two separate bundles of hydrophilic polyethersulfone capillaries for plasma perfusion and one hydrophobic multilayer fibre bundle for oxygenation are interwoven within a disc-like bioreactor and aggregated in six ports (two times plasma/medium in- and outflow and gas inand outflow) (87, 88). The bioreactor is inoculated with primary porcine or primary human liver cells which reform tissue-like structures between the hollow fibres. The bioreactor is perfused with the patients’ plasma during therapy. CVVHDF and SPAD can be included into the circuit as additional components. The bioreactor system was applied in hepatectomized pigs (89), evaluated in a phase I clinical trial with porcine cells in eight patients (11, 90) and the complete MELS system including CVVHDF and SPAD with primary human cells was applied in 12 patients (91, 92).
4.7. Limitations of Bioartificial Liver Support Systems
Although massive research has been directed towards bioartificial liver support systems for over 25 years now, none of the systems has yet been widely established in clinical use, in contrast to some purely artificial liver support systems, which are at least commercially available today. This has to do with several limiting aspects of bioartificial liver support, of which the main obstacle, although not the only one, still is the lack of an appropriate cell source. The available cell mass in most bioartificial systems reaches only less than 20% of normal liver mass of an adult (100–200 g cells). However, it is known from living donor liver transplantation that a minimum of 40% of ideal liver mass is necessary in order to diminish the risk of graft failure (93). This suggests that, even if the bioreactor construction is able to provide the full benefit of the available maximum metabolic capacity of the cells to the patient without further loss, it is questionable whether this capacity will be sufficient to actually substitute enough of the failing liver’s function to help the patient survive. Additionally, the cells are usually separated by one or two semipermeable
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membranes from the patient’s bloodstream, which have to be passed twice by the plasma. First the plasma is separated from the blood by a plasma filter and has, in most systems, to pass another membrane to enter the bioreactor, and then it has to cross the two membranes again to be returned to the patient’s circulation. This is bound to limit the mass transfer between the cells and the patient’s blood. Furthermore, the flow which can be applied within the extracorporeal system is limited by pressure developing in the circuit due to membrane resistance and decreased diameter. In contrast to a normal human liver, which is passed by 1.5 L of blood per minute, the flow in a bioartificial system only approaches about 300 mL/min at maximum. This means that the maximum possible clearance, which is dependent on the passing volume per time, is limited directly by the diminished flow rate (94). If we now have to assume that the liver-specific metabolism of the applied cells is lesser than that of healthy human hepatocytes due to the reasons already discussed in conjunction with the problem of an appropriate cell source, it becomes clear why it will be very difficult to prove the efficiency of the biological component of any bioartificial liver support system in the near future. Although several clinical trials have been carried out with bioartificial systems, most of them were uncontrolled phase I studies, which were merely able to demonstrate the safety of the respective system. Since liver failure is a clinical state with a variety of causes and a very unpredictable outcome, large numbers of patients have to be included in the study collective to be able to make a statistically significant statement towards the actual therapeutic value of bioartificial systems. This problem is additionally enhanced by the fact that many systems are applied in combination with or even integrated into artificial detoxification devices, such as dialysis or albumin dialysis, making it even harder to distinguish between the detoxification component which naturally influences clinical parameters such as ammonia and urea serum levels and the contribution of the applied liver cells to the overall effect. Published study results are very heterogeneous and even by extensive metaanalysis, no survival benefit could be proven for bioartificial liver support so far (95, 96). References 1. Khan, S.A., Shah, N., Williams, R., and Jalan, R. (2006) Acute liver failure: a review. Clin. Liver Dis. 10, 239–258, vii–viii. 2. Larson, A.M. (2008) Acute liver failure. Dis. Mon. 54, 457–485. 3. Lee, W.M. and Seremba, E. (2008) Etiologies of acute liver failure. Curr. Opin. Crit. Care 14, 198–201.
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human liver cells. World J. Gastroenterol. 5, 135–137. Wang, Y.J., Li, M.D., Wang, Y.M., Chen, G.Z., Lu, G.D., and Tan, Z.X. (2000) Effect of extracorporeal bioartificial liver support system on fulminant hepatic failure rabbits. World J. Gastroenterol. 6, 252–254. Wang, H.H., Wang, Y.J., Liu, H.L., Liu, J., Huang, Y.P., Guo, H.T., and Wang, Y.M. (2006) Detection of PERV by polymerase chain reaction and its safety in bioartificial liver support system. World J. Gastroenterol. 12, 1287–1291. Sauer, I.M., Neuhaus, P., and Gerlach, J.C. (2002) Concept for modular extracorporeal liver support for the treatment of acute hepatic failure. Metab. Brain Dis. 17, 477–484. Pless, G., Steffen, I., Zeilinger, K., Sauer, I.M., Katenz, E., Kehr, D.C., Roth, S., Mieder, T., Schwartlander, R., Muller, C., Wegner, B., Hout, M.S., and Gerlach, J.C. (2006) Evaluation of primary human liver cells in bioreactor cultures for extracorporeal liver support on the basis of urea production. Artif. Organs 30, 686–694. Gerlach, J., Trost, T., Ryan, C.J., Meissler, M., Hole, O., Muller, C., and Neuhaus, P. (1994) Hybrid liver support system in a short term application on hepatectomized pigs. Int. J. Artif. Organs 17, 549–553. Sauer, I.M., Kardassis, D., Zeillinger, K., Pascher, A., Gruenwald, A., Pless, G., Irgang, M., Kraemer, M., Puhl, G., Frank, J., Muller, A.R., Steinmuller, T., Denner, J., Neuhaus, P., and Gerlach, J.C. (2003) Clinical extracorporeal hybrid liver support – phase I study
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with primary porcine liver cells. Xenotransplantation 10, 460–469. Sauer, I.M., Zeilinger, K., Obermayer, N., Pless, G., Grunwald, A., Pascher, A., Mieder, T., Roth, S., Goetz, M., Kardassis, D., Mas, A., Neuhaus, P., and Gerlach, J.C. (2002) Primary human liver cells as source for modular extracorporeal liver support – a preliminary report. Int. J. Artif. Organs 25, 1001–1005. Sauer, I.M., Zeilinger, K., Pless, G., Kardassis, D., Theruvath, T., Pascher, A., Goetz, M., Neuhaus, P., and Gerlach, J.C. (2003) Extracorporeal liver support based on primary human liver cells and albumin dialysis – treatment of a patient with primary graft non-function. J. Hepatol. 39, 649–653. Lo, C.M., Fan, S.T., Liu, C.L., Wei, W.I., Lo, R.J., Lai, C.L., Chan, J.K., Ng, I.O., Fung, A., and Wong, J. (1997) Adult-to-adult living donor liver transplantation using extended right lobe grafts. Ann. Surg. 226, 261–269; discussion 9-70. Iwata, H. and Ueda, Y. (2004) Pharmacokinetic considerations in development of a bioartificial liver. Clin. Pharmacokinet. 43, 211–225. Liu, J.P., Gluud, L.L., Als-Nielsen, B., and Gluud, C. (2004) Artificial and bioartificial support systems for liver failure. Cochrane Database Syst. Rev. CD003628. Kjaergard, L.L., Liu, J., Als-Nielsen, B., and Gluud, C. (2003) Artificial and bioartificial support systems for acute and acuteon-chronic liver failure: a systematic review. JAMA 289, 217–222.
Chapter 29 Human Hepatocyte Transplantation Anil Dhawan, Stephen C. Strom, Etienne Sokal, and Ira J. Fox Abstract Over the last decade the interest in hepatocyte transplantation has been growing continuously and this treatment may represent an alternative clinical approach for patients with acute liver failure and lifethreatening liver-based metabolic disorders. The technology also serves as the proof of concept and reference for future development in stem cell technology. This chapter reviews the field of hepatocyte transplantation from bench to bedside. Key words: Hepatocyte transplantation, collagenase, cryopreservation, liver tissue source, GMP laboratory, metabolic liver disease, acute liver failure, stem cells, immunosuppression.
1. Introduction Orthotopic liver transplantation (OLT) is currently the treatment of choice for end-stage liver diseases and life-threatening liverbased metabolic disorders. The replacement of the diseased organ by OLT is curative, but carries surgical risks, associated with graft loss and with lifelong immunosuppressive therapy. Moreover, the increasing shortage of donor organs for OLT encouraged research for alternative therapies for liver diseases. The concept, derived from animal function to correct deficient liver function, was confirmed by the success of auxiliary liver transplantation in the management of patients with acute liver failure and certain liver-based metabolic disorders (1). This has further increased interest in using human hepatocytes for cell transplantation in the management of liver-based metabolic conditions and acute liver
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failure. Recent development in stem cell technology brings additional hope to overcome the problem of organ shortage.
2. Hepatocyte Transplantation There are several advantages in the concept of hepatocyte transplantation. It is less expensive and less invasive than OLT, as liver cells can be transplanted after radiological or surgical placement of a portal catheter. Unlike whole organs, hepatocytes can be cryopreserved and stored in cell banks, offering the advantage of immediate availability in emergencies. Theoretically, transplanted cells can functionally replace the hepatocytes of the diseased organ and restore its metabolic capacity either for a period of bridging to whole-organ transplantation or by engraftment and longterm function. Moreover, the native liver is preserved, leaving the possibility of innovative therapies for metabolic disorders open as soon as it becomes clinically available, such as gene therapy or stem cell-based regenerative medicine. This strategy would possibly release the recipient from lifelong immunosuppressive therapy or at least alleviate the requirements.
3. Methods for Isolation of Human Hepatocytes 3.1. Source of Liver Tissues
The major obstacle of hepatocyte transplantation is the limited supply of donor liver tissue for cell isolation. Normally, liver tissues that become available for hepatocyte isolation have been rejected for conventional OLT and consequently are of marginal quality. As a result, hepatocytes isolated from these livers are of a low quality and viability. It seems unlikely that this situation will change in the near future. It has been difficult to argue that an already limited donor pool should be shared between a still experimental program and an established whole-organ transplantation program. However, a few alternatives exist. Cell isolation can be performed on remnants of the liver after orthotopic transplantation of reduced or split liver grafts (segment IV), with a significant higher cell viability obtained from these tissues when compared to those rejected for OLT (2, 3). Additionally other alternative sources of hepatocytes are being studied, such as immortalized cell lines (4, 5), fetal hepatocytes (6), and stem cell-derived hepatocytes (7–9).
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There are well-established protocols for isolation of human hepatocytes based on collagenase digestion of perfused liver tissue at 37◦ C (2, 10). Once the liver tissue is digested and cells released, the hepatocytes are separated by low-speed centrifugation, and the pellets obtained are washed with ice-cold buffer solution to purify the cells. Cell viability and yield are then determined. Isolated hepatocytes need to be used as soon as possible for cell transplantation, preferably within 24 h of isolation, as function deteriorates even when kept at 4◦ C. For longer term storage, human hepatocytes are cryopreserved in a mixture of the organ preservation media, University of Wisconsin solution, and final concentration of 10% dimethyl sulfoxide (DMSO) using a controlled-rate cell freezer (11). Cryopreserved cells can then be stored at below –140◦ C until required for clinical use.
4. Pre-clinical Studies Extensive studies using experimental animal models of human liver disease established the feasibility and efficacy of hepatocyte transplantation into various sites such as liver, spleen, pancreas, peritoneal cavity, and sub-renal capsule. Identification of transplanted hepatocytes was documented by a number of different methods. Models have included hepatocyte transplantation into Nagase analbuminaemic rats, Gunn rats, and dipeptidyl peptidase IV-deficient rats. Engraftment and function of transplanted hepatocytes was confirmed by liver immunohistochemistry and serum albumin levels and reduction in serum bilirubin levels, in the case of Nagase analbuminaemic and Gunn rats, respectively (12, 13). Another approach used was the infusion of genetically modified donor cells secreting or expressing unique reporter proteins, including the green fluorescent protein, for direct identification of transplanted cells (14, 15). Hepatocyte transplantation has been described to improve the survival of animal models with acute liver failure induced either chemically (16–18) or surgically (19). A number of animal models have been developed to study human liver-based metabolic disorders. Complete or partial correction of the metabolic abnormality by means of hepatocyte transplantation has been reported in some animal models, including the Gunn rat (model for CN syndrome type I) (20), the Long Evans cinnamon rat (model of Wilson’s disease) (21), the hyperuricemic Dalmatian dog (22), among others. However, long-term function of transplanted hepatocytes with correction of the underlying metabolic defect has been difficult to demonstrate. Complete
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correction of the biochemical abnormality has required a significant level of engrafted cells. Repeated hepatocyte transplantation has shown to increase the number of engrafted liver cells (23), although better results have been seen in animal models where donor hepatocytes have a selective advantage over the native hepatocytes to proliferate and repopulate the recipient liver (20, 24).
5. Clinical Hepatocyte Transplantation
Initial clinical application of allogeneic human hepatocyte transplantation was for the treatment of patients with acute liver failure (ALF) (25). These initial trials demonstrated the safety of the technique and some improvement in the outcome of patients. Subsequently, other studies of hepatocyte transplantation for ALF using either fresh or cryopreserved cells have been reported in the literature, showing varying degrees of success (26, 27). Bridging patients to whole-organ transplantation or until recovery of the native liver are the goals of hepatocyte transplantation in ALF. Currently, the most successful outcome has been for patients with liver-based metabolic disorders. The cell requirement for transplantation may be lower in some inherited metabolic liver diseases where the aim is to replace a single deficient enzyme. The earliest report of patients to receive hepatocyte transplantation for treatment of an inherited liver-based metabolic disorder was done by Grossman et al. Five children with familial hypercholesterolemia were transplanted with autologous hepatocytes transduced ex vivo with a retroviral vector carrying the human LDL receptor gene. There was evidence of engraftment and over 20% reduction in LDL cholesterol in three of the five patients transplanted, but no sustained expression of the transgene (28, 29). Since then, many other patients have been treated with hepatocyte allotransplantation to correct metabolic diseases. One of the key early reports is from Fox et al. in which the case of a 10-year-old girl with CN syndrome type I treated with hepatocyte transplantation was reported. There was a reduction in her bilirubin levels and hours of phototherapy and an increase in bilirubin UDP-glucuronosyl transferase activity after hepatocyte transplantation. Long-term evidence of hepatocyte engraftment and function was demonstrated by the excretion of bilirubin conjugates in bile for up to 3.5 years (14, 30). To our knowledge, to date 22 patients with liver-based metabolic disorders were treated with hepatocyte allotransplantation worldwide. Either fresh or cryopreserved cells have been used. At least a transient improvement in bilirubin levels was reported in another four patients with CN type I treated with
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hepatocyte transplantation (Dhawan et al., unpublished; Allen K, Australia, personal communication) (31, 32). Six of the other patients treated with hepatocyte transplantation had an urea cycle defect (four with ornithine transcarbamylase deficiency, one with argininosuccinate lyase deficiency, and one with citrullinemia) (33–37) (Lee KW, South Korea, personal communication), one with infantile Refsum’s disease (38), three with glycogen storage disease type Ia (39) (Lee KW, South Korea, and Sokal EM, Belgium, personal communications), three with inherited coagulation FVII deficiency (40), two with progressive familial intrahepatic cholestasis type 2 (PFIC2) (Dhawan et al., unpublished), and two with α1-antitrypsin deficiency (26, 33). The described outcomes have been variable. The majority of patients experienced partial improvement of their metabolic abnormality, at least for a short period of time. Long-term function of transplanted hepatocytes has also been claimed (37–39). In one report, sustained engraftment of transplanted cells in the host liver parenchyma was demonstrated, together with de novo enzyme activity (37). No benefit was observed in the two patients with PFIC2 and the two others with α1-antitrypsin deficiency. These patients had already established fibrosis and/or cirrhosis that probably impaired engraftment of the transplanted hepatocytes. It is clear that cryopreserved hepatocytes display significant damages and seem to be less efficient than fresh cells: ATP production in plated thawed cells is absent, and this is related to strong damage to the mitochondria, as demonstrated by the loss of membrane potential, decreased respiration, cytochrome C release, and deficient activity of respiratory chain complexes 1 and 4 (41). Despite this, at least one report demonstrates successful metabolic control after infusion of cryopreserved cells only (36). On the other hand, use of fresh cells does not allow extensive safety checks on the infused cells, which may decrease safety of the technique, still comparable, however, to organ transplantation.
6. Cell Administration and Safety Concerns
The liver and the spleen are the most consistent sites for hepatocyte engraftment and function. Intraportal injection is the preferred delivery method for clinical hepatocyte transplantation for treating acute hepatic failure and liver-based metabolic diseases. The portal venous system can be accessed using different techniques: percutaneous transhepatic puncture of the portal vein, transjugular approach to the right portal vein, catheterization of the mesenteric vein or umbilical vein catheterization in newborn babies, or even permanent implantable catheters such as
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Port-a-cath or Broviac, allowing repeated infusions (42). Hepatic ultrasound and portal venous system Doppler examination is normally performed before the procedure to exclude any malformation or venous thrombosis, and portal venous pressure is monitored throughout the procedure. Portal hypertension and formation of thrombi of hepatocytes after transplantation appear to be minimized by adding heparin to the cell suspension and limiting the number of cells per infusion to 30–100×106 /kg of body weight at an infusion rate of 5–10 ml/kg/h and a concentration of 1–10×106 hepatocytes/ml (43). Thus, when large amounts of hepatocytes need to be injected repeated cell infusions are normally required. The spleen is considered an adequate site for hepatocyte transplantation, particularly in cirrhotic patients. Another attractive site for cell transplantation is the peritoneal cavity due to its large capacity and simple access. Experimental transplantation of encapsulated or matrix attached hepatocytes has prolonged cell survival in animal models (44).
7. Immunosuppression To date there is no consensus regarding immunosuppressive treatment, but most centers have used liver transplantation protocols. Combination of tacrolimus and steroids with or without sirolimus or mycophenolate mofetil (MMF) has been used. Some centers use monoclonal antibodies like basiliximab or daclizumab. However, the Edmonton protocol for islet cell transplantation may be the most promising.
8. The Future Considerable progress in the field has been made allowing clinical hepatocyte transplantation. However, the success of hepatocyte transplantation from animal model experiments has not been fully reproduced in humans. Although results in clinical studies have been encouraging, no complete correction of any metabolic disease in patients by hepatocyte transplantation alone has been reported. There are still a number of areas for improvement and development. 8.1. Limitations of Hepatocyte Transplantation
Hepatocyte transplantation has brought the proof of concept that a missing function can be restored in the deficient liver by metabolically active cells. However, the limited supply and quality of livers currently available to isolate hepatocytes is a major
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problem for hepatocyte transplantation. Techniques to improve the viability and quality of the cells isolated from marginal livers are required. Another limiting factor of the technique is the conservation and storage of isolated cells. Viability and metabolic capacity on thawing of cryopreserved hepatocytes can be improved by the use of protocols incorporating cryo/cytoprotective agents (45). However, there is still a need to improve the storage of hepatocytes, both for longer periods in the cold so they can be used fresh after a number of days and also better cryopreservation protocols for longer term storage. Fresh cells require an important logistic infrastructure, so that the technique will remain limited to few centers. The safety of the human biological material is also a limitation. It is also clear that many injected cells do not engraft into the recipient liver and are either cleared by the reticuloendothelial system or lose viability during this early phase. The outcome of hepatocyte transplantation would benefit from methods to enhance engraftment and repopulation by induction of a selective growth advantage over host hepatocytes, although the options for this in humans would be limited. Rejection of the allogeneic hepatocytes and eventual senescence of the cells transplanted are probably contributing factors for the loss of long-term function of these cells in clinical transplants.Experimental transplantation of hepatocytes encapsulated in semi-permeable membranes intraperitoneally in animal models has been shown to maintain long-term viability and function of the cells, without immunosuppression (46). More studies are needed to minimize or overcome the need of immunosuppression in liver cell transplantation. If tolerance could be achieved, hepatocyte transplantation would exhibit an exceptional advantage over OLT. 8.2. Alternative Cell Sources
It is not likely that the supply of hepatocytes will increase, so a wider use of hepatocyte transplantation will not be possible until alternative sources of cells are found. Stem cells have a selfrenewing capacity and may allow to overcome the problem of organ shortage. Mesenchymal stem cells have a differentiation capacity and may achieve hepatocyte-like phenotype. They can be obtained from various tissues, such as the amnion, the bone marrow, the cord jelly, or from the fetal and adult liver (47–50) (see also Chapters 8–12). As another approach, autologous hepatocytes could be genetically manipulated in vitro to express the missing enzyme in patients with liver-based metabolic deficiencies. Xenotransplants could be a potentially unlimited source of fresh hepatocytes; however, there are many concerns regarding rejection and transmission of infectious diseases that need to be overcome. In summary considerable experience has been gained so far in the handling of hepatocytes and techniques for hepatocyte
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transplantation allowing clinical hepatocyte transplantation. This will give a good basis for the future application of new technologies, particularly those based on stem cells which it is hoped will increase the utilization of cell transplantation. References 1. Pereira, S.P., McCarthy, M., Ellis, A.J., Wendon, J., Portmann, B., Rela, M. et al. (1997) Auxiliary partial orthotopic liver transplantation for acute liver failure. J. Hepatol. 26, 1010–1017. 2. Mitry, R.R., Hughes, R.D., Aw, M.M., Terry, C., Mieli-Vergani, G., Girlanda, R. et al. (2003) Human hepatocyte isolation and relationship of cell viability to early graft function. Cell Transplant. 12, 69–74. 3. Mitry, R.R., Dhawan, A., Hughes, R.D., Bansal, S., Lehec, S., Terry, C. et al. (2004) One liver, three recipients: segment IV from split-liver procedures as a source of hepatocytes for cell transplantation. Transplantation 77, 1614–1616. 4. Kobayashi, N., Fujiwara, T., Westerman, K.A., Inoue, Y., Sakaguchi, M., Noguchi, H. et al. (2000) Prevention of acute liver failure in rats with reversibly immortalized human hepatocytes. Science 287, 1258–1262. 5. Cai, J., Ito, M., Nagata, H., Westerman, K.A., Lafleur, D., Chowdhury, J.R. et al. (2002) Treatment of liver failure in rats with end-stage cirrhosis by transplantation of immortalized hepatocytes. Hepatology 36, 386–394. 6. Dan, Y.Y., Riehle, K.J., Lazaro, C., Teoh, N., Haque, J., Campbell, J.S. et al. (2006) Isolation of multipotent progenitor cells from human fetal liver capable of differentiating into liver and mesenchymal lineages. Proc. Natl. Acad. Sci. USA 103, 9912–9917. 7. Avital, I., Feraresso, C., Aoki, T., Hui, T., Rozga, J., Demetriou, A. et al. (2002) Bone marrow-derived liver stem cell and mature hepatocyte engraftment in livers undergoing rejection. Surgery 132, 384–390. 8. Miki, T., Lehmann, T., Cai, H., Stolz, D.B., and Strom, S.C. (2005) Stem cell characteristics of amniotic epithelial cells. Stem Cells 23, 1549–1559. 9. Ruhnke, M., Ungefroren, H., Nussler, A., Martin, F., Brulport, M., Schormann, W. et al. (2005) Differentiation of in vitromodified human peripheral blood monocytes into hepatocyte-like and pancreatic islet-like cells. Gastroenterology 128, 1774–1786. 10. Strom, S.C., Dorko, K., Thompson, M.T., Pisarov, L.A., and Nussler, A.K. (1998) Large
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tocytes without immunosuppression: longterm survival. Surgery 117, 189–194. Miki, T., Marongiu, F., Ellis, E.C., Dorko, K., Mitamura, K., Ranade, A., Gramignoli, R., Davila, J., and Strom, S.C. (2009) Production of hepatocyte-like cells from human amnion. Methods Mol. Biol. 481, 1–14. Lysy, P.A., Campard, D., Smets, F., Malaise, J., Mourad, M., Najimi, M., and Sokal, E.M. (2008) Persistence of a chimerical phenotype after hepatocyte differentiation of human bone marrow mesenchymal stem cells. Cell Prolif. 41, 36–58. Najimi, M., Khuu, D.N., Lysy, P.A., Jazouli, N., Abarca, J., Sempoux, C., and Sokal, E.M. (2007) Adult-derived human liver mesenchymal-like cells as a potential progenitor reservoir of hepatocytes? Cell Transplant. 16, 717–728. Campard, D., Lysy, P.A., Najimi, M., and Sokal, E.M. (2008) Native umbilical cord matrix stem cells express hepatic markers and differentiate into hepatocyte-like cells. Gastroenterology 134, 833–848.
SUBJECT INDEX
A
Albumin dialysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 512, 518 -eGFP . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 242–243, 245 production . . . . . . . . . . . . . . . . . . . . . . . . . . . . 204, 211, 220 secretion . . . . . . . . . . . . . . . . . . . . . 116, 118, 216, 220, 483 Alcohol-related cirrhosis . . . . . . . . . . . . . . . . . . . . . . . . . . . . 511 Aldolase . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 188 Aldolase B . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9, 263 Alginate gel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3, 514 Alkaline phosphatase . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 188 Allergic hepatitis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 391 Allyl alcohol . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 171 Alpha-lipoic acid . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87 2-aminophenol . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 311 Amiodarone . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 398, 404 Ammonia detoxification . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 204 metabolism . . . . . . . . . . . . . . . . . . . . . . . . . . . 129, 220, 239 Amnion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 531 Analbuminaemia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 481–482 Angioma . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 249 Anhepatic dog model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 517 dogs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 515, 517 pigs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 516 Anionic conjugates . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 219 Anteroposterior pattern . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 160 Anti-apoptotic factor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 479 Antibody microarrays . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 404 Anti-complement drug . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 499 Antifreeze protein type I . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 97 Anti-inflammatory . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 120 Antioxidant . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22, 92, 267, 393 protection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 393 Antiseizure agent . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 129 Antithrombin . . . . . . . . . . . . . . . . . . . . . . . . . . . . 432, 435–436 α-1-antitrypsin . . . . . . . . . . . . . . . 51, 124, 188, 220, 240, 252 deficiency . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 481, 529 Antiviral innate response . . . . . . . . . . . . . . . . . . . . . . . 269–270 AP-1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 116, 120, 128, 219 A1PI . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 220 Apical . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 119, 121, 265 Apolipoprotein E deficiency . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 479 expression . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 163 Apoptosis . . . . 12, 21, 88, 92, 129, 139–154, 210, 304–305, 392–393, 395–396, 398, 402–403, 408, 478–479, 481–482, 484–485 resistance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 140, 149–153 Apoptotic bodies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 399 Argininosuccinate lyase . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 529 Argininosuccinate synthetase . . . . . . . . . . . . . . . . . . . . . . . . 220
ABCG2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 196, 265 Absorption, distribution, metabolism, and excretion (ADME) . . . . . . . . . . . . . . . . . . . . . . . . . . . 355–356 Acetaminophen . . . . . . . . . . . . . 267, 285, 315, 404, 506, 511 intoxication . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 511 4-acetamidophenol . . . . . . . . . . . . . . . . . . . 297–298, 300–301 Acetanilide 4-hydroxylase . . . . . . . . . . . . . . . . . . . . . . . . . . . 503 Acetate. . . . . . . .92, 250–251, 300, 313–314, 318, 333, 352, 434–435, 437, 516–517 Acetonitrile . . 283, 287, 299–300, 315, 352, 360, 377–378, 383–386 2-acetylaminofluorene . . . . . . . . . . . . . . . . 171–172, 197–198 Acidic fibroblast growth factor . . . . . . . . . . . . . . . . . . . . . . 238 Acidic fibroblast growth factor (aFGF) . . . . . . . . . . 238–241 Actin polymerization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 119 Activated charcoal . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 512 Activator protein-1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 219 Activin A . . . . . . . . . . . . . . 159–160, 207, 212–213, 240–241 Activin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 163, 188, 207 Activity assay . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 376, 379, 383–385 measurement . . . . . . . . . . . . . . . . . . . . . 379–380, 439–442 Acute-on-chronic liver failure (AoCLF) . . . . . . . 23–24, 511 Acute liver failure . . . . . . . . 23, 25, 107, 174–175, 182, 511, 515, 525, 527–528 Acute phase proteins . . . . . . . . . . . . . . . . . . . . . . . . . . . 128, 274 Adducts . . . . . . . . . . . . . . . . . . . . . . 16, 18, 392–393, 396, 399 Adenoma . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 249 Adenomatosis polyposis coli gene . . . . . . . . . . . . . . . . . . . . . . . 164 Adenosine triphosphate (ATP) -binding cassette transporter family . . . . . . . . . . . . . . . 196 content . . . . . . . . . . . . . . 88, 284, 291, 302, 304, 396, 398 depletion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 393 hydrolysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 328 levels . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 390 Adenovector . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 481 Adenoviral vector . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 497 Adenovirus vector . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 484 Adenylate kinase . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 404 Adipose tissue . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 204, 215 α1-adrenoceptor antagonism . . . . . . . . . . . . . . . . . . . . . . . . 172 Adsorption . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 512 Adult hepatic stem cells . . . . . . . . . . . . . . . . . . . . . . . . . . 6–7, 170 primary cells . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 513 stem cells . . . . . . . 6–7, 25, 168, 173–174, 202–205, 476 Aflatoxin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18, 267 AFP, see α-fetoprotein (AFP) Akt . . . . . . . . . . . . . . . . . . . . . 12, 128, 140, 142, 149–151, 265 Alb-promoted uPA/SCID . . . . . . . . . . . . . . . . . . . . . . . . . . 494
P. Maurel (ed.), Hepatocytes, Methods in Molecular Biology 640, c Springer Science+Business Media, LLC 2010 DOI 10.1007/978-1-60761-688-7,
535
HEPATOCYTES
536 Subject Index Argininosuccinate synthetase (ASSL) . . . . . . . . . . . . . . . . 220 Aroclor 1254 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21, 401 Aromatic amino acids . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 512 Artificial detoxification devices . . . . . . . . . . . . . . . . . . . . . . . 512, 518 livers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 183, 214, 516, 517 Aryl hydrocarbon receptor (AhR). . . . . . . 6, 11, 21–22, 218, 252, 257, 267, 311–312, 319 nuclear translocator . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 218 Ascorbic acid . . . . . . . . . . . . . . . . . . . 43, 62, 92, 251, 296, 357 Asialoglycoprotein receptor (ASGPR) . . . . 7, 214, 224, 240 Asymmetric cell division . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 184 divisions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 168 Atherosclerosis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 479 Atorvastatin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 329 Atovaquone . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 310 Attachment medium . . . . . . . . . . . . . . . . . . . . . . . . . . 63–64, 71 Automated epifluorescence microscopy . . . . . . . . . . . . . . . . 19 5 -azido thymidine . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54–55
B Baculovirus . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 270 Barrett’s esophagus . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 174 Basal lamina . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 185 Basement membrane . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 185 Basiliximab . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 530 Basolateral . . . . . . . . . . . . . . . . . . . 14, 119, 121, 219, 395, 402 membranes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 121 Bcl-2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 478–479, 482 Bcl-2/Fas pathway . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 479 Benzaldehyde . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 501 Benzo(a)pyrene hydroxylase . . . . . . . . . . . . . . . . . . . . . . . . . 503 Beta-Naphthoflavone . . . . . . . . . . . . . . . . . 302–303, 503–504 Bicarbonate homeostasis . . . . . . . . . . . . . . . . . . . . . . . . . . . . 129 Bile acid composition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 424–425 homeostasis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 356 metabolism . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 216 production . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 424–428 quantification . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 428 synthesis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 417–428, 481 Bile canalicular transport . . . . . . . . . . . . . . . . . . . . . . . . . . . . 140 Bile canaliculi . . . . . . . . . . 2, 5, 13–14, 19–20, 118, 121–122, 145, 152–153, 173, 199, 263, 283, 485 Bile duct ligation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 191 necrosis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 191 Bile salt export pump (BSEP) . . . . . . . . . . . 14, 219, 267, 328 Biliary canaliculi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 376 cells . . . . . . . . . . . . . . . 6, 9, 12–13, 30, 158, 162, 194, 209 differentiation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 162 ductal epithelial cells . . . . . . . . . . . . . . . . . . . . . . . . . . . . 171 ductule cells . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 171 elimination . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 505 epithelial cells . . . . . . . 171, 189, 191–193, 196, 209–210 epithelium . . . . . . . . . . . . . . . . . . . . . . . . . . . . 185, 193, 196 excretion . . . . . . . . . . . . . . . . . . . . . . . 58, 90, 219, 283, 328 -like cell . . . . . . . . . . . . . . . . . . . . . . . . . 5, 9, 263–264, 268 lineage . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 162, 192 markers. . . . . . . . . . . . . . . . . . . . . .162, 193–194, 209, 248 tree . . . . . . . . . . . . . . . . . . . . . . . . . 182, 208–209, 505, 507 Bilirubin conjugate . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 528
conjugation assays . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 220 glucuronides . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 219 metabolizing defects . . . . . . . . . . . . . . . . . . . . . . . . . . . . 222 UDP-glucuronosyltransferase . . . . . . . . . . . . . . . . . . . . 309 Bioactivation . . . . . . . . . . 14, 18–19, 217, 391–392, 394, 397 Bioartificial liver of the Amsterdam Medish Centrum (AMC-BAL) . . . . . . . . . . . . . . . . . . . . . . . . . . . . 516 liver support system (BLSS) . . . . . . . . . . . . . . . . . 511–518 support . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 517–518 system . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 247 Bioartificial systems . . . . . . . . . . . . . . . . . . . . . . . 514, 517–518 Biochemical pathways . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 390 Bioengineered matrices . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 183 Biofluids . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 359, 406–407 Biological stress . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 356 Biomarkers . . . . . . . . . 19, 356, 358–359, 366–368, 371, 373, 390, 397, 400–401, 404, 406–407 of hepatotoxicity . . . . . . . . . . . . . . . . . . . . . . . . . . . 390, 404 Biopsy specimens . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 200–201 Bioreactor. . . . . . . . . . . . . . . . . . . . . . 3, 23, 117–118, 513–518 Biotransformation activity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 116, 118, 125 enzymes . . . . . . . . . . . . . . . . . . . . . 125–126, 129, 131, 282 pathways . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 391, 394 products . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 356 reactions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 58 Bipotent capacity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 194 cell . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 192, 194 hepatoblasts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9, 161–163 population . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 194 progenitor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5, 8, 42, 248 progenitor cells . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42 Bipotential cell . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 171 Blastocyst . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 169, 205–206 Blood coagulation factor . . . . . . . . . . . . . . . . . . . . . . . . . . 431–444 vessels. . . . . . . . . . . . . . . . . . . . .59, 65, 119, 158, 188, 208 BMS-PTX-265. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .404 BMS-PTX-837. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .404 Bone marrow -derived cells . . . . . . . . . . . . . . . . . . 174–175, 202, 222 transplantation . . . . . . . . . . . . 174, 197, 200–201, 485 Bone morphogenic proteins (BMP) . . . . . . . . 160, 187, 193, 207–208, 213, 240–241 Bovine serum albumin (BSA) . . . . . . . . . . 43–44, 52, 62, 79, 92, 121, 141, 143, 146, 153, 240, 250, 254, 275, 299, 335, 341, 357, 434–435, 437–438, 442 Brachyury . . . . . . . . . . . . . . . . . . . . . . . 159, 163, 206, 209, 240 Breast cancer resistance protein (BCRP) . . . . 196, 219, 328
C C3A cells . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23, 513 Ca2+ homeostasis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 391, 398 Cadherin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22, 198, 240 Calcium-free buffer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 116 Canalicular . . . . . . 13–14, 58, 119, 121, 131, 140, 219, 328, 394–395, 399, 402, 480 Canalicular membrane . . . . . . . . . . . . . . 13, 58, 121, 219, 328 Canals of Hering . . . . . . . . . . . . . . . . 171, 182, 185, 195–196 Cancer drugs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 402 Capillaries . . . . . . . . . . . . . . . . . . 118, 190, 360, 467, 515–517 Capsule of Glisson . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 158
HEPATOCYTES Subject Index 537 Carbamyl phosphate synthetase I (CPS) . . . . . . . . . . . . . . 220 Carbohydrate . . . . . . . . . . 8, 10, 98, 101, 217, 394, 400, 405 Carbonic anhydrase III . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 404 Carbon tetrachloride . . . . . . . . 191, 198, 221, 404, 479–480 Carboxylation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 432 Carboxylic acid drugs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 392 Carcinogenesis. . . . . . . . . . . . . . . . . . . . . . . . . . . .167, 172, 266 Carcinoma . . . . . . . . . . . . . 4–5, 118, 266, 447, 464, 513, 515 Cardiac mesoderm . . . . . . . . . . . . . . . . 42, 157–158, 186, 188, 207 mesodermal cells . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 238 myoblasts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 169–170 Cardiogenic mesoderm . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 160 Cardiotrophin-1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 211 Carp hepatocytes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 97, 102 CAR retention protein (CCRP) . . . . . . . . . . . . . . . . . . . . . 130 Cartilage . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42, 204 Caspase . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12, 265–266 Caspase-3 . . . . . . . . . . . . . . . . . . 142, 145–148, 151–153, 396 Catalase . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 92 Catecholamines . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11, 310 β-catenin . . . . . . . . . . 129, 159, 162, 187, 209–210, 264–265 CD10 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 265 CD13 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 240, 265 CD14 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 203 CD24a . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 194 CD26 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 205, 240, 265 CD29 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 265 CD33 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 265 CD34 . . . . . . . . . . . . 169, 171–174, 182, 194, 196, 200–201, 203, 248, 264–265 CD38 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 206 CD44 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 265 CD45 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 169, 196, 203 CD49 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 264–265 CD71 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 265 CD105 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 204 CD133 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 172, 198 CD138 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 265 C-DNA preparation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 381–383 synthesis . . . . . . . . . . . . . . . . 314, 321, 381, 419, 453, 455 Cdx2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 206 C/EBPβ . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 219, 274, 277–279 C/EBP . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 C/EBPα . . . 8, 116, 120, 125, 193, 203, 209–210, 219, 274 Cefmetazole . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 349, 505 Cell –cell competition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 485 –cell contact . . . . . . . . . . . . 8, 80, 118, 122, 202, 305, 395 –cell junctions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 185 count . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 70, 287, 305, 312 culture . . . . . . . . . . . . . . 5, 17, 43, 62, 101, 117–121, 140, 144–145, 152, 158–163, 172, 213, 249, 251, 253, 269, 274, 283–284, 296–297, 299, 302–303, 335, 356–357, 376–378, 408, 418–419, 422, 428, 433, 448, 450, 463–464, 466–467, 514 cycle . . . 12, 116, 128, 140, 190, 211, 220, 476, 479–480 cycle progression . . . . . . . . . . . . . . . . . . . 12, 128, 140, 479 density . . . . . . . . . . . 9, 71, 75, 79, 93–94, 279, 299, 395, 438–439 -ECM adhesion sites . . . . . . . . . . . . . . . . . . . . . . . . . . . 120 engraftment . . . . . . . . . . . . . . . . . . . . . . . . . . . 222–224, 497 fate . . . . . . . . . 8, 158–159, 173, 187, 200, 206, 209, 214 fusion . . . . . . . . . . . . . . . . . . . . . . . 168, 175, 200–203, 498
injury . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 393, 397 isolation methods . . . . . . . . . . 46–47, 100, 102, 116, 168, 515, 526 lineages . . . . . . . . . . . . . . . . . . . . . . 169–170, 187, 193, 210 lysate . . . . . . . . . . . . . . . . . . . . . . . . . . . . 146, 341, 380, 384 monolayer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 74, 444, 469 morphology . . . . . . . . . . . . . . . . . . 205, 255, 395–396, 423 plating . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 421–422 polarity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6, 75 source . . . . . . . . . . . . . 182, 192, 221, 512–513, 517–518, 531–532 suspension . . . . . . . . 3, 20, 46, 51, 61, 69–71, 79, 84–87, 89, 100, 109–112, 244–245, 255, 299, 338–339, 375–376, 439, 530 therapeutic programs . . . . . . . . . . . . . . . . . . . . . . . . . . . . 222 therapies . . . . . . . . . . . 164, 199, 215, 221–223, 225, 237 transduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51 transplantation . . . . . . . . . 42, 51–53, 108, 113, 174, 183, 221–222, 476, 479, 525–527, 530–532 turnover . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 167, 182 viability . . . . . . 54, 85, 113, 299, 304–307, 396, 526–527 Cellomics high-content screening . . . . . . . . . . . . . . . . . . . . 408 Cellular aggregate formation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 172 ATP content . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 284, 291 -based therapies. . . . . . . . . . . . . . . . . . .183, 194, 202, 221 innate antiviral response . . . . . . . . . . . . . . . . . . . . . . . . . 270 receptor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 464, 466 reprogramming . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 175 therapy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 273, 279 Cellulose nitrate/cellulose acetate membranes . . . . . . . . . 517 Central nervous system . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 167 vein . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 164, 189–190 Centrilobular injury . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 171 necrosis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 191, 393 Centrolobular necrosis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 506 Ceramic scaffolds . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 515 C-fos . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 116 Chemical injury . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 171, 191 sympathectomy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 172 Chemically-induced cellular damage . . . . . . . . . . . . . . 84, 392 Chemiluminescence-based assays . . . . . . . . . . . . . . . . . . . . 398 Chemokine CXC motif receptor 4 (CXCR4) . . . . 159–160, 172, 206, 209, 240 Chemometric analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 361–363 tools . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 356 Chemotaxis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 182 Chenodeoxycholic acid (CDCA) . . . . . . . . . . . 417–419, 422, 424–427 Chicken hepatocytes . . . . . . . . . . . . . . . . . . . . . . . . . . . . 97, 102 Chimeric animals . . . . . . . . . . . . . . . . . . . . . . . . . . 501, 503, 506–507 mice . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 491–507 Chimeric humanized mice . . . . . . . . . . . . 497–498, 502, 504 Chimpanzee . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 464, 482 hepatocytes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 464 Cholangiocyte . . . . . . . . . . 42, 158, 162, 168, 172, 182, 188, 190, 212, 248 Cholangiocytic lineages . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 189 Cholecystokinin octapeptide . . . . . . . . . . . . . . . . . . . . 331, 344 Cholestasis . . . . . 16, 58, 392–393, 398–399, 402, 408, 476, 480–481, 529
HEPATOCYTES
538 Subject Index Cholestatic . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 172, 203, 393 Cholesterol 7α-hydroxylase . . . . . . . . . . . . . . . . . . . . . . . . 218, 425, 427 transport . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 128 Cholic acid (CA) . . . . . . . . . . . . . . . . 417–419, 422, 424–427 Choline-deficient diets . . . . . . . . . . . . . . . . . . . . . . . . . 172, 198 Chromatin condensation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 147–149 fragmentation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 399 staining . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 148–149 Chromatographic method . . . . . . . . . . . . . . . . . . . . . . 385–386 Chronic infections . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 464 liver disease . . . . . . . . . . . . . . . . . . . . . . 222, 266, 447, 511 Ciliary neurotrophic factor . . . . . . . . . . . . . . . . . . . . . . . . . . 211 Cirrhosis . . . . . . . . . . . . 17, 60, 181, 191, 222, 261, 266, 447, 464, 481, 511, 529 Cirrhotic liver . . . . . . . . . . . . . . . . . . . . . . . . . . 24, 67, 486, 530 CITCO . . . . . . . . . . . . . . . . . . . . 356–357, 359, 365–371, 373 Citrullinemia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 529 C-jun . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 116, 127–128, 193 phosphorylation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 127 CK18 . . . . . . . . . . . . . 202–205, 215, 239–240, 252, 256, 264 CK19 . . . . . . . . . . 43, 49, 171, 196, 203, 205, 239–240, 248, 264–265 C-kit . . . . . . . . . . . . . 169, 171, 196, 200–201, 209, 248, 265 Claudin-7 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 198 Clinical application . . . . . . . . . . . 27, 108, 237–238, 515–518, 528 studies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 516–517, 530 trials . . . . . . . . . . . 224, 281–282, 476, 512, 515, 517–518 CLint,all . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 328–329, 331 Clodronate . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 483 Clonal populations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 172 Clotting factors . . . . . . . . . . . . . . . . . . . . . . . . . . . 128, 216, 220 Clozapine . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 267 Clustering methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 401 C-met . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27, 162, 210 C-myc . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 116 Coactivator proteins . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 130 Coagulant activity . . . . . . . . . . . . . . . . . . . . 436–437, 439–442 Coagulation activity . . . . . . . . . . . . . . . . . . . . . . . . . . . 436–437, 439–442 factor . . . . . . . . . . . . . . . . . . . . . . . . . . 8, 113, 431–444, 513 problems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 512 Cocaine . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 198 Cocktail incubation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 376 Co-culture . . . . . . . . 117, 202–203, 207–208, 211–212, 240, 274, 293, 395 Collagen gel . . . . . . . . . . . . . . 86, 140–141, 144, 151–152, 423–424 gel matrix . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 140, 144 sandwich . . . . . . . . 13, 140, 144–145, 149, 151–154, 403 type I . . . . . . . . . . . . . . . . . . . . . . . . . . 73, 75, 212, 239, 241 Collagenase . . . . . . . . 1–2, 42–43, 46, 54, 62, 67–68, 77–78, 90, 108, 116, 120, 250–251, 254, 258, 262, 275, 298, 302, 312, 333–334, 337–338, 350, 357, 359, 394–395, 418–419, 435, 438, 496, 498, 527 digestion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 78, 90, 527 Colon . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 215 Columnar epithelium . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 174 Coma . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 512 Combinatorial chemistry . . . . . . . . . . . . . . . . . . . . . . . 397–398 Committed cells . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5, 169
Compensatory growth . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 170 hyperplasia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 190–191 Competitive repopulation . . . . . . . . . . . . . . . . . . . . . . . . . . . 504 Complement . . . . . . . . 8, 173, 216, 254, 278, 296, 319, 366, 371, 407, 434, 438, 483–484, 499 Concentration gradients . . . . . . . . . . . . . . . . 95, 295–296, 515 Condensed nuclei . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 148–149 Confluence . . . . . . . . . . . 4–6, 17, 20, 72, 243, 255, 263–264, 305–306, 340, 449–450 Confluent culture . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 152, 444 Confocal microscopy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 407 Conjugated bile acids . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 418 Conjugation enzymes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 310 reaction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 310–311 Connexins 26 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 121 32 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 124, 173 Consensus stem cell definition . . . . . . . . . . . . . . . . . . . . . . . 168 Constitutive androstane receptor (CAR) . . . . . . . . . . . 4, 126, 129–130, 218, 267, 311–312, 319, 356, 366, 369–371 Contact inhibition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 513 Continuous venovenous hemodiafiltration (CVVHDF) . . . . . . . . . . . . . . . . . . . . . . . . 512, 517 Controlled-rate freezer . . . . . . . . . . . . . . . . . . . . . . . . . 109–111 Copper . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 216, 274 depletion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 274 Cord jelly . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 531 Coumarin 7-hydroxylase . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 499 hydroxylase activity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 501 Covalent binding . . . . . . . . . . . . . . . . . . . . . 391–392, 396, 399 Covalently closed circular DNA (cccDNA) . . . 26, 268, 464 Cre/Lox based strategy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 175 Crigler-Najjar syndrome . . . . . . . . . . . . . . . . . . . . . . . . 25, 476 Cripto . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 207 Cryoinjury . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 86, 88, 97 Cryopreservation . . . . . . . . 3, 5, 83–102, 107–113, 282–283, 296, 339, 351, 394, 475, 531 Cryopreservation optimization . . . . . . . . . . . . . . . . . . . . . . 394 Cryopreserved hepatocyte recovery medium . . . . . . . . . . . . . . . . 283–284 hepatocytes . . . . . . . . . . . . . 15–16, 83, 87–88, 90, 94–95, 97–98, 100, 111–113, 282–284, 286, 292, 298, 304, 312, 314, 330–331, 334, 338–339, 343, 347, 350–351, 529, 531 human hepatocytes . . . . . . . . 15, 90, 281–293, 296, 298, 301–302, 305, 307, 348 Cryoprotectants . . . . . . . . . . . . . . . . . . . . . . 90–93, 98–99, 108 Culture conditions. . . . . . . . . .2–7, 15–16, 28, 30, 116, 123, 127, 172–173, 204, 258, 267, 304, 395, 403, 405, 418, 425–426, 440–442, 448 medium . . . . . . . . . . 10, 19, 47, 50, 54, 76, 88, 118, 120, 160, 202, 205, 240, 255, 258, 269, 274–275, 277, 279, 286, 296, 299, 303, 312, 314, 340–341, 357, 397, 400, 422, 433–435, 438–444, 449, 451, 461, 464, 469–470 Culturing procedures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 282 Cyclin A . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 479 Cyclin-dependent kinase inhibitor . . . . . . . . . . . . . . . . 12, 479 Cyclin E/Cdk . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 479 Cyclins D1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 211
HEPATOCYTES Subject Index 539 Cyclins D2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 211 Cyclosporin A . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 329 Cynomolgus monkeys . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 224 CYP 1A1 . . . . 6, 173, 239, 252, 257, 267, 297, 300, 303–304, 307, 501–503 1A2 . . . . . . 126–127, 216–217, 239, 267, 285, 290–291, 297–298, 300, 304, 306–307, 376, 379, 381–383, 385–386, 500, 502–503, 506 2A2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 267, 503 2B6 . . . . . . . . 4, 126, 130, 204, 216–218, 239, 252, 257, 285, 290–291, 376, 379, 381–383, 385–386 2C8 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 216, 285 2C9 . . . . . . . . . . . . . . . 126, 216, 285, 290–291, 298, 302, 305–306, 499, 501 2C18 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 217 2C19 . . . . . . . . . . . . . . . . . . . . . . . . . . . . 216, 285, 291, 501 2D6 . . . . . . . . . . . . . . . 126, 216, 218, 267, 285, 298, 302, 306–307, 500, 503 2E1 . . . . . . . . . . . . 19, 126–127, 263, 285, 305, 399, 506 3A4 . . . . . . . . . . . . . . 2–4, 7, 9, 15, 18–20, 126, 130, 209, 216–218, 220, 239–240, 252, 257, 263, 267, 285, 290–291, 297–298, 300, 302–307, 324, 329, 376, 379, 381–383, 385–386, 404, 486, 500–504 3A5 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 218, 503 3A7 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6, 48, 216, 218 3A11 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 209 4A11 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 267 4F3 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 267 7A1 . . . . . . 209, 214, 216, 218, 239–240, 267, 277–278, 418–419, 425–426, 428 8B1 . . . . . . . . . . . . . . . . . . . . . . . . . 418–419, 425–426, 428 27A1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . 419, 425–426, 428 activity . . . . . . . . . . . . . . . 3, 296, 302, 306, 376, 380, 385 enzyme . . . . . 5, 209, 212, 215–216, 295–307, 310, 319, 323–324, 350, 376–379, 499, 501–502 gene induction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 296 induction . . . . . . . . . . . . . . . . . . . . . 98, 215, 302, 304, 376 isoforms . . . . . . . . . . . . . . . . 218, 220, 298–299, 304, 306 isoform-selective substrates . . . . . . . . . . . . . . . . . . . . . . 298 CYP3A4 inhibitor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 329 CYP450 . . . . . . . . . . . . . . . . . . . . . . . 58, 60, 79, 127, 498–504 Cytochrome c . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 266, 529 P450 . . . . . . . . . . . 8, 17, 58, 87, 125, 131, 173, 191, 199, 209, 212, 215–216, 219, 240, 266–267, 274, 278, 289, 297, 300, 375–386, 391 Cytogenetic analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 174 Cytokeratins 7/19 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 248 8/18 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 248 Cytokines . . . . . . . . . . . 7, 11–12, 23, 27, 139–142, 144–145, 163, 205, 211–212 Cytomegalovirus immediate early promoter . . . . . . . . . . . . 51 Cytomes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 407 Cytometry . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 263–264, 407 Cytomic assays . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 407–408 endpoints . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 407 Cytomics . . . . . . . . . . . . . . . . . . . . . . . 390, 400–401, 407–408 Cytoplasmic CAR retention protein . . . . . . . . . . . . . . . . . . . . . . . . . . 130 enzyme leakage . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 291 Cytoprotectant agent. . . . . . . . . . . . . . . . . . . . . . . . . . . . 88, 531 Cytoprotective compounds . . . . . . . . . . . . . . . . . . . . 86–88, 97
Cytoskeletal organization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 118–119 rearrangement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 119 Cytoskeleton . . . . . . . . . . . . . . . . . . . . . . . . . . 12, 119, 393, 399 Cytosol . . . . . . . . . . . 120, 263, 312, 316, 318, 320, 392–393, 396, 405, 504 Cytosolic compartment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 316 Cytotoxicity assays . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16, 291, 397, 408 endpoints . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 291, 395 tests. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .19, 390
D Daclizumab . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 530 Data analysis . . . . . . . . . . . . . . . 322, 357–358, 361–363, 365, 368–370, 406 Debrisoquine . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 499–500 4-hydroxylase . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 499 Decompensation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 511 Deconjugation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 428 Dedifferentiation/de-differentiation . . . . . . . . 116, 121–125, 131, 140, 145, 151–153, 394–395, 475 process . . . . . . . . . . . . . . . . . . . . . . . . . . . 124, 151, 394–395 Definitive endoderm . . . . 159, 186, 206–207, 209, 213, 241 Dehydroepiandrosterone . . . . . . . . . . . . . . . . . . . . . . . . . . . . 311 Delta-like kinase . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 172 Delta-like kinase (DLK) . . . . . . . . . . . . . . . . . . . . . . . 172, 193 Derivatization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 358, 428 Desmosomes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 116 Detoxication process . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 392 Detoxification . . . . . . . . . . 8, 10, 18, 57, 116, 129, 204, 211, 217, 220, 327–328, 392, 394, 483, 512, 515–516, 518 enzymes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 483 Developing heart . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 158, 160 Development . . . . . . . . . . . 4, 8–9, 14, 17, 21, 25, 27–29, 42, 54, 68, 73, 158–161, 163, 171, 175, 181–225, 266, 268, 282–283, 287–291, 310, 319, 370, 376, 390, 393–394, 397, 400–406, 444, 448, 464, 476, 512, 514, 526, 530 Developmental studies . . . . . . . . . . . . . . . . . . . . . . . . . 157–164 Dexamethasone . . . . . . . . 62–63, 73, 78, 120–121, 123–124, 127–129, 140, 144, 152, 163, 173, 204, 211–212, 240–241, 251, 274–277, 279, 297, 313, 319, 357, 419, 424, 426–428, 434–435, 467, 499, 502–503 6-hydroxylase (DEXOH) . . . . . . . . . . . . . . 499, 501, 503 Dextran . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 91 Dextromethorphan . . . . . . . . . . . . . . . . . . . . . . . . . . . . 297–301 Dextrorphan . . . . . . . . . . . . . . . . . . . . . . . . . 297–298, 300–301 D-galactosamine . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24, 198 2D gel electrophoresis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 403 DHBV . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26, 268 Dialysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 421, 512, 515, 518 4 -diaminodiphenylmethane . . . . . . . . . . . . . . . . . . . . . . . . 191 2,6-dichloro-4-nitrophenol . . . . . . . . . . . . . . . . . . . . . . . . . 311 Dickkopf-1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 164 Diclofenac . . . . . . . . . . . . . . . . . . . . . . . . . . . 297, 304, 399, 499 4-hydroxylase activity . . . . . . . . . . . . . . . . . . . . . . . . . . . 499 Dietary . . . . . . . . . . . . . . . . . . . . . . . . . . . 19, 21, 116, 129, 310 3,5-diethoxycarbonyl-1,4-dihydrocollidine (DDC) . . . . . . . . . . . . . . . . . . . . 171–172, 196, 198 Differentiated morphology . . . . . . . . . . . . . . . . . . . . . . . . . . . 118–119, 262 phenotype . . . . . 116–118, 127, 194, 264–265, 305, 444
HEPATOCYTES
540 Subject Index Differentiation . . . . . . . . 4–11, 19, 25–26, 28, 115–131, 140, 145, 152–153, 157–164, 167–175, 182–189, 192–194, 196–197, 200–214, 216, 221, 223, 225, 237–241, 244, 247–259, 263–268, 401, 467, 469, 482, 485–486, 513, 531 Differentiation/de-differentiation markers . . . . . . . . . . . 125, 163–164, 211 Differentiation-inducing agents . . . . . . . . . . . . . . . . . . . . . 164 Diffusible factor-mediated interactions . . . . . . . . . . . . . . . 157 Diffusible factors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 157–158 Dimethylsulfoxide (DMSO) . . . . . . . . 3, 5–6, 15, 20, 26, 62, 73, 84, 86, 89–92, 95, 98, 100, 102, 108–109, 130, 141–142, 144, 173, 239–241, 250, 262–263, 267–268, 275, 283, 297, 299, 302–305, 307, 312–314, 317, 320, 351, 357, 359, 365–367, 376–380, 382, 418, 433, 435, 439, 467, 527 Dioxin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 399 Dipeptidyl peptidase IV . . . . . . . . . . . . . . . . . . . 121, 197, 527 -deficient rat . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 527 Disaccharides . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 92 Discarded donor organs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 513 Dispersion model . . . . . . . . . . . . . . . . . . . . . . . . . 349–350, 352 Disposition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 394, 493, 503 DNA adducts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18, 393 methylation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 129 microarrays . . . . . . . . . . . . . . . . . . . . . . . . . . . 266–267, 401 DNase I digestion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 303 Docetaxel-induced neutropenia . . . . . . . . . . . . . . . . . . . . . . 330 Dog . . . . . . . . . . . . . . . . . . . . . . 86–87, 96, 288, 515–517, 527 Donor -derived dendritic cell progenitors . . . . . . . . . . . . . . . . 223 -derived leukocyte microchimerism . . . . . . . . . . . . . . . 223 liver . . . . . . . 108, 113, 249, 497, 499–500, 506, 517, 526 variability . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2, 6, 397 Dopamine . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 311 Dorsal endoderm . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 186 Double-stranded RNA (dsRNA) . . . . . . . . . . . . . . . . . . . . 269 Drosophila ovarian niche . . . . . . . . . . . . . . . . . . . . . . . . . . . 185 Drug biotransformation . . . . . . . . . . . . . . . . . . . . . . . . . . 118, 392 candidates . . . . . . . . . . . 29, 281, 292, 319, 401, 406, 507 conjugating enzyme . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 376 conjugation enzyme . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 310 discovery . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4, 225, 397 –drug interaction . . . . . . . . 4, 14–15, 215, 217, 281–293, 300, 310, 312, 322–324, 355–356, 399 evaluation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 58, 262 excretion . . . . . . . . . . . . . . . . . . . . . . . . . 328, 392, 491–507 -induced hepatotoxicity . . . . . . . . . . . . . . . . . . . . . . . . . 394 -induced liver injury (DILI) . . . . . . . . 16, 388–391, 393, 399–408, 507 -induced toxic injury . . . . . . . . . . . . . . . . . . . . . . . 393, 494 metabolic activities . . . . . . . . . . . . . . . . . . . . . . . . . 282, 503 metabolism . . . . . . 20, 22, 139–140, 216–218, 220–221, 261–270, 281–293, 295–307, 310–311, 319, 321, 356, 368, 391, 395, 397, 408, 483, 491–507 metabolites . . . . . . . . . . . . . . . . . . . . . . . 356, 366–368, 372 -metabolizing activities . . . . . . . . . . . . . . . . . . . 4, 296, 302 metabolizing enzyme pathways. . . . . . . . . . . . . . . . . . .288 metabolizing enzymes . . . . . . . . . . . 4, 15, 126, 216, 241, 283, 285, 289–290, 295, 300, 305–306, 309, 319, 391, 397, 399, 402–403 toxicity . . . . . . . . . . . . . . . . . . . . . . . . . . . 282, 291, 389–408 transport . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13
transporters . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13, 215, 327 uptake transporters . . . . . . . . . . . . . . . . . . . . . . . . . 327–352 Drug-induced liver injury (DILI) . . . . . . . 16, 388–391, 393, 399–408, 507 Duck hepatitis B virus . . . . . . . . . . . . . . . . . . . . . . . . . . 27, 268
E E-cadherin . . . . . . . . . . . . . . . . . . 75, 173, 193, 206, 209, 265 Ectoderm . . . . . . . . . . . . . . . . . . . . . . . . . . . . 159, 169–170, 205 Edmonton protocol . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 530 Efflux . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 219, 327–328 transporters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 328 E2 17βG . . . . . . . . . . . . . . . . . . . . . . . . 331, 346–348, 350–351 EHS matrigel . . . . . . . . . . . . . . . . . . . 420–421, 423–424, 426 Electrophiles . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 393 Electrophilic intermediates . . . . . . . . . . . . . . . . . . . . . . . . . . 391 Electrospray ionization (ESI) . . . . . . . . . . . . . . . . . . . 315, 406 ELISA assay . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 436 Embryo . . . . . . . . 6, 157–161, 163, 169, 186, 193, 210, 214, 223, 237 Embryogenesis . . . . . . . . . . . . . . . . . . . . . . . 187, 193, 237–238 Embryoid bodies (EBs) . . . . . . . . . . 205–206, 212, 238–242, 244–245 Embryonic development . . . . . . . . 171, 186, 191, 193, 195, 213–214 explant cultures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 160 germ cells . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 169, 206 germ layers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 237–238 liver . . . . . . . . . . . . . . . . . . . . . . . . . 162, 187, 189, 192–193 stem cell . . . . . . . . . 6–7, 25, 30, 120, 124, 159, 163, 169, 183, 197, 205–214, 223, 237–245, 248, 485–486, 513 Encapsulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 514 Encephalopathy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24, 512 Endocrine . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 115, 189 Endocytosis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 139 Endoderm development . . . . . . . . . . . . . . . . . . . . . . . . . . 159, 206, 209 differentiation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 174, 188 identity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 159, 207 -like cells . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 161 Endodermal cells . . . . . . . . . . . . . . . . 160, 186–187, 192–193, 208, 241 explants . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 160 patterning. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .186 Endogenous biomarkers . . . . . . . . . . . . . . . . . . . . . . . 356, 366, 368, 373 metabolites . . . . . . . . . . . . . . . . . . . . . . . 356, 368, 372, 406 Endoplasmic reticulum . . . . . . . . . . . . . . . 316, 392–393, 494 Endothelial cell . . . . . . . 9, 17, 42, 161, 171, 173, 188–189, 200, 208, 210–212, 259, 431, 507 injury . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 479 Endothelin antagonists . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 332 Endothelium . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 169–170 End-stage liver diseases . . . . . . . . . . . . . . . . . . . . . . . . 183, 525 Energetic balance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 393 Energy metabolism . . . . . . . . . . . . . . . . . . . . . . . . . . . . 398, 404 Engelbreth-Holm-Swarm mouse sarcoma . . . . . . . . . . . . 420 Engraftment . . . . . . . . 24, 41, 174–175, 182, 201, 222–224, 479, 481, 483–485, 493, 496–497, 500, 526–529, 531 Enhanced green fluorescent protein (eGFP) . . . . . . 241–245 Enhancer . . . . . . . . . . . . . . . . . . . . 51, 125, 130, 208, 240, 274 Enterohepatic circulation . . . . . . . . . . . . . . . . . . . . . . . 418, 507
HEPATOCYTES Subject Index 541 Envelope proteins . . . . . . . . . . . . . . . . . . . . . 27, 269, 464–466 Environmental toxins . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 129 Enzyme active site . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 295–296 activities . . . . . . . . . . 74, 91, 96, 116, 212, 216, 283, 285, 289, 305, 319, 375–379, 386, 393, 529 expression . . . . . . . . . . . . . . . . . . . . . . . . . . 58–59, 125, 319 inducers. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .5, 311, 403 induction . . . . . . . . . . . . . . 4, 15, 131, 283–285, 290–291, 295–307, 312, 356, 396 inhibition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 285 mapping . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 295 Epidermal growth factor (EGF) . . . . . . . . . 12–13, 120–121, 203–204, 250, 263, 275, 434–435, 467 receptor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 121 Epithelial cell . . . . . . . . . . . . . . 6, 42, 58, 171, 173–174, 182, 187–189, 191–193, 196, 209–210, 215, 253–258, 274, 485 Epithelial cell adhesion molecule (EpCAM) . . . . . . . . . . . . 6, 206, 240 Epoxidation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 432 ERK1/2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12 Erythrocytes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 169 ES derived-hepatocytes . . . . . . . . . . . . . . . . . . . . . . . . 160, 205 Estradiol . . . . . . . . . . . . . . . . . . . 310–311, 314, 324, 346, 350 -17β-glucuronide . . . . . . . . . . . . . . . . . . . . . . . . . . 346, 350 17β-estradiol . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 311 Estrone-3-sulfate (E-sul) . . . . . . . . . 330–331, 344, 346–348 Estrone 3-sulfotransferase. . . . . . . . . . . . . . . . . . . . . . . . . . .504 Ethanol . . . . 43, 64, 109, 129, 140, 275–276, 283, 313–314, 317–318, 320, 337, 380, 399, 419–422, 434, 449, 451–452 Ethinylestradiol . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 310, 324 Ethnic groups . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 507 Ethoxyresorufin O-deethylase (EROD) . . . . . . . . . . 503–504 Eukaryotic initiation factor 1 alpha (EF1α) . . . . . . . . . . . . 51 Evolutionary divergence . . . . . . . . . . . . . . . . . . . . . . . . . . . . 161 Excretion . . . . . . . . 14, 58, 90, 116, 121, 128, 217, 219, 263, 283, 328, 355–356, 392, 396, 491–507, 528 Excretory pathways . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 492 Exocrine . . . . . . . . . . . . . . . . . . . 115, 189, 274, 276–277, 279 Export system . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 464–465 Extracellular compartment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 306 matrix . . . . . . . . . . 9, 12, 74–77, 118, 145, 158, 185, 195, 208, 395, 514 Extracorporeal bioartificial liver support system (EBLSS) . . . . . . . . . 517 liver support . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 514, 517 Extracorporeal liver assist device (ELAD) . . . . . . . . 515–516 Extraembryonic endoderm . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 159, 206–207 tissues . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 169 Extrahepatic stem cells . . . . . . . 183, 195, 199–202, 221–223
F FACS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 239–241, 244, 498 Factor VII deficiency . . . . . . . . . . . . . . . . . . . . . . . . . . 113, 476 FAH -deficient . . . . . . . . . . . . . . . . . . . . . . . . . 201, 221, 477, 483 /SCID . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 486 FAH–/– NOD/SCID . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 483 nude . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 483 /Rag–/– . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 483
Familial hypercholesterolemia . . . . . . . . . . . . . . . . . . . . . . . 528 Fas-agonistic antibody . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 479 Fas-induced liver apoptosis . . . . . . . . . . . . . . . . . . . . . . . . . . 481 Fat . . . . . . . . . . . . . . . . . . . . . 42, 45, 58, 67, 71, 147, 153, 204 Fatty acid . . . . . . . . 10, 16–17, 240, 357, 393, 395, 400, 402, 405, 407, 512 Fatty liver . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17, 90, 398 Feces . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 505 Ferritin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 266 Fetal hepatocytes . . . . . . . . . . . . . . . . . . 6–7, 163, 212, 214, 526 human liver . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 500 liver . . . . . . . . . . . . 25, 124, 158, 183, 186, 192–197, 199, 209–211, 218, 223, 241, 497 liver hematopoiesis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 211 α-fetoprotein (AFP) . . . . . . . 6, 48, 124–125, 160, 163, 171, 173, 187–188, 193–196, 199, 205, 208–209, 211, 214–215, 239–240, 248, 264, 500 FGF10 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 187 FGF1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 186–187, 204 FGF2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 186 FGF8 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 186–187 FGFR . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 187, 240 FGFR2-IIIb isoform . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 187 FGF signaling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 186, 207 Fibrillar material . . . . . . . . . . . . . . . . . . . . . 432, 437, 442–443 Fibrin . . . . . . . . . . . . . . . . . . . . . . . . . . 431–432, 437, 442–443 Fibrinogen . . . . . . . . 203, 220, 240, 252, 257–258, 396, 432, 437, 442–443 Fibroblast growth factor (FGF) . . . . . . . . . 160, 186–187, 203–205, 207–208, 212–213, 238–240, 242, 244–245, 250–251 -like protrusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 123 -like spinous processes . . . . . . . . . . . . . . . . . . . . . . 122–123 Fibronectin . . . . . . . . . . . . 119, 185, 240, 277, 395, 423, 432 Fibrosis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17, 222, 507, 529 Filtration . . . . . . . . . . . . . . . . . . . 258, 299, 363–365, 371, 512 Flavin monooxygenase enzymes . . . . . . . . . . . . . . . . . . . . . 391 Flow cytometry . . . . . . . . . . . . . . . . . . . . . . . . . . . 263–264, 407 Flt-3 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 196, 265 Fluconazole . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 311 Fluidized-bed bioreactor . . . . . . . . . . . . . . . . . . . . . . . 514–515 Fluorescence -based assays . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 398 -based in vitro screen . . . . . . . . . . . . . . . . . . . . . . . . . . . . 408 Fluorescent activated cell sorter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 241 bile acid . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 398 phospholipids . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 398 Foetal cell populations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42, 485 cells . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42, 49, 51, 485 hepatic cells . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42–43, 51 hepatocytes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41–55 livers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42, 485, 513, 517 Folate . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 216 Foregut endoderm . . . . . . . . . . . 42, 157–158, 160–161, 186–187, 207–208, 274 lumen . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 157 Forkhead box A (FOXA) . . . . . . . . . . . . . . . . . . 187, 207–208 FoxA1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8, 206, 208–209 FoxA2 . . . . . . . . . . . . . . . . . . . . . . . . . . 161–163, 206, 208–209 FoxM1B. . . . . . . . . . . . . . . . . . . . . . . . . . . . .193, 210, 478, 480 Free radicals . . . . . . . . . . . . . . . . . . . . . . . . . . 92, 391, 393, 398
HEPATOCYTES
542 Subject Index Freezing profile . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 84–85 rates . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 84 regimens . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 84, 89 Fresh human hepatocytes . . . . . . 86, 90, 296, 298, 302, 306, 483–484 FRG mouse . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 494–495 Frizzled-related protein. . . . . . . . . . . . . . . . . . . . . . . . . . .5, 161 Frog . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 161 Fructose . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42–43, 87 Fulminant hepatic failure . . . . . . . . . . . . . . . 23, 222, 247, 517 rabbit model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 517 Fumarylacetoacetate hydrolase . . . . . . . . 174, 197, 201, 221, 477, 494 Functional hepatocytes . . . . . . 2–3, 202, 212–213, 238, 241, 476, 484 Fusion . . . . . . . . . . . . . . 84–85, 110, 168, 170–171, 175, 197, 200–202, 455, 486, 498
G Gabrp . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 198 Gallbladder . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 209 GAPDH . . . . . . . . . . 150, 153, 277–278, 321, 381, 455, 458 Gas chromatography. . . . . . . . . . . . . . . . . . . . . . . . . . . .358, 428 supply . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 514 Gastric reflux . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 174 Gastrointestinal epithelium . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 167 tract . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 174, 201, 310 Gastrulation . . . . . . . . . . . . . . . . . . . . . 157, 159–160, 186, 206 GATA4 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 239–240 GATA6 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 161, 203 GATA-binding protein . . . . . . . . . . . . . . . . . . . . . . . . 206, 209 G1 checkpoint . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 129 G-CSF . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 182, 265 GCTM-5 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 193 Gelled collagen . . . . . . . . . . . . . . . . . . . . 73, 75, 144–145, 152 Geltrex . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63, 73, 75–77, 80 Gene array analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 401 expression . . . . . . 7–8, 10, 20–22, 58, 73, 125–126, 158, 160, 163, 183, 187, 194, 198, 203, 205–208, 212–214, 220, 238, 267, 300, 303–304, 306, 340, 377, 381, 393, 401–403, 405, 419, 422–423, 426, 428, 457–460, 490, 498–499, 513 therapies . . . . . . . . . . . . . . . . . . . . . . . . . 175, 183, 498, 526 transfer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51 Genetic engineering . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 513 manipulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29, 238 polymorphism . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 306, 391 Genome-wide association study . . . . . . . . . . . . . . . . . . . . . 330 Genomic replicons . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 448 Genotype reversion . . . . . . . . . . . . . . . . . . . . . . . . . . . . 495–496 Germ cells . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 169, 206 layers . . . . . . . . . . . . . . . . . . . . . . . . 159, 205–206, 237–238 stem cells . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 185 G0/G1 transition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 116 Glisson’s capsula . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 438 Glucagon . . . . . . . . . . . . . . . . . . . . . . . 296, 357, 394, 434–435 Glucocorticoid . . . . . . . . . . 78, 120, 123, 163, 211, 268, 274 receptor (GR) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 120, 130
Gluconeogenesis . . . . . . . . . . . . 8, 87–88, 220, 390, 393, 397 Glucose . . . . . . 10–11, 17, 62, 87, 95, 97, 99, 108–109, 112, 128, 204, 209, 216, 220, 240, 242, 250–251, 274, 296, 333–334, 340, 357, 394, 396, 434 Glucose-6-phosphate . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87 Glucuronidation . . . . . . . . . . . . 220, 298, 310–312, 316–319, 323–324 Glutamyl carboxylase . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 432 γ-glutamyl transpeptidase (GGT) . . . . . . . 88, 188, 193, 196 Glutathione peroxidise. . . . . . . . . . . . . . . . . . . . . . . . . . . . . .404 Glutathion-S-transferase (GST) A1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 239, 267 A4 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 267 M1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 239, 267 P1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 124–125 Glycerin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 90 Glycerol . . . . . . . . . . . . . . . . . . . . 10, 45, 54, 87, 275, 312, 437 Glycogen accumulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 163, 396 breakdown . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 220 storage . . . . . . . . . . . . . . . . . . . . . . 116, 128, 220, 241, 394 storage disease . . . . . . . . . . . . . . . . . . . . . . . . 476, 481, 529 Glycogenolysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87 G2/M phase . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 478 Good Manufacturing Practice (GMP) conditions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 108 Goosecoid (GSC) . . . . . . . . . . . . . . . . . . . . . . . . . 206, 209, 240 Gp130 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 211, 265 receptor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 211 Graft function . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 224 versus host disease . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 174 rejection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 224 selection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 497 Green fluorescent protein . . . . . . . . . . . . . . . . 29, 44, 241, 527 GR-interacting protein 1 (GRIP-1) . . . . . . . . . . . . . . . . . . 130 Growth -arrested phenotype . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 116 factors . . . . . . . . . . . . 10, 12, 47, 120–121, 139–140, 144, 159–162, 186, 188, 203–207, 209–212, 238, 240–242, 250, 274, 395, 434–435, 467, 481 reduced glutathione (GSH) . . . . . . 86–89, 97, 100, 193, 390, 392–393, 396, 399 G1/S . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12, 480 GSTπ, see Glutathion-S-transferase (GST), P1 Guinea pig . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 288 Gunn rat . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 527 Gut . . . . . . . . . . . . . . . . . . . . . . . . 157–159, 170–171, 187, 211 endoderm . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 159
H Haemostasis factor II . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 431–432 factor V . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 432 factor VII . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 431–432 factor VIII . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 432 factor IX . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 432 factor X . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 432 factor XIII . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 432 protein . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 431–433, 439 Hamster . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 131, 274 HBV DNA replication . . . . . . . . . . . . . . . . . . . . . . . . . . . 268, 464 envelope proteins. . . . . . . . . . . . . . . . . . . . . . . . . . .464–466 life cycle . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 268
HEPATOCYTES Subject Index 543 promoters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 268, 466 replication cycle . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 464 surface antigen (HBsAg) . . . . . . . . . . . . . . . . . . . . 466, 471 -susceptible cells . . . . . . . . . . . . . . . . . . . . . . . . . . . 464–466 -susceptible HepaRG cells . . . . . . . . . . . . . . . . . . . . . . . 464 variants . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 269 HCVcc . . . . . . . . . . . . . . . . . 28, 269, 448–451, 453, 456–461 Heat shock protein . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 404 Hecogenin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 311 HEK293 cells . . . . . . . . . . . . . . . . . . . . . . . . 340–341, 345–347 Helper function . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 464 Hematopoiesis . . . . . . . . . . . . . . . . . . . . . . . 185, 194, 210–211 Hematopoietic cells . . . . . . . . . . . . . . . . 163, 169, 174, 186, 194, 197, 211 progenitors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 186, 196 stem cells . . . . . . . . . . 169–171, 173, 185, 194, 196–200, 202–203, 211–212, 223, 248 Hemochromatosis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 266 Hemoperfusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 515 Hepa-1c1c7 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 502 Hepadnavirus . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 268 HepaRG cells . . . . . . . 4–7, 9–11, 14–15, 17–19, 21–22, 26, 261–270, 376–380, 383–386, 464–467, 469–470 Heparin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 333, 337, 530 HepatAssist . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 515–516 Hepatectomized pigs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 517 Hepatic acinus . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 190 artery . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 189–190 bud. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .186 capacities . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 216 clearance . . . . . . . . 14, 288, 323, 328–332, 347–350, 352 differentiation . . . . . . . . 8–9, 11, 160, 188, 202–214, 266 differentiation markers . . . . . . . . . . . . . . . . . . . . . . 163, 211 disorders . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24, 181 drug uptake . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 58 -enriched nuclear factors . . . . . . . . . . . . . . . . . . . . 125–127 fate . . . . . . . . . . . . . . . . . . . . . . . . . 161, 186, 207–210, 213 foci . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 274 glutamine metabolism . . . . . . . . . . . . . . . . . . . . . . . . . . . 129 homeostasis . . . . . . . . . . . . . . . . . . 193, 219–220, 266, 356 identity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 160 induction . . . . . . . . . . . . . . . 160–161, 188, 207–209, 356 intrinsic clearance . . . . . . . . . . . . . . . . . . . . . . . . . . 288, 331 irradiation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 481 -like cells . . . . . . . . . . . . . . . . . . . . . . . . . 212, 215, 238–241 lineages . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 120, 124, 209 lobule . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 173 marker . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 172–173 maturation . . . . . . . . . . . . . . . . . . . . . . . 210–212, 216, 220 metabolism . . . . . . . . . . . . . . . . . 10, 15, 58, 215, 293, 507 nuclear factors (HNF) . . . . . . . . . . . . . . . . . . . . . . 126, 265 phenotype . . . . . . . . . 7–8, 128–130, 205, 208, 212, 248, 265, 278, 444, 486 regulators . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8, 162 sinusoids . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 158 specification . . . . . . . . . . . . . . . . . . . . . . 160–161, 208–210 stage . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 492 stem cell . . . . . . . . . . . . . 6–7, 42, 167–175, 181–225, 485 stress response pathways . . . . . . . . . . . . . . . . . . . . . . . . . 129 structure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59 transport protein . . . . . . . . . . . . . . . . . . . . . . 218–220, 493 uptake . . . . . . . . . . . . . . . . . . . . . . . 328–332, 343–347, 349 uptake clearance . . . . . . . . . . . . . . . . . . 332, 343, 347, 349 xenobiotic biotransformation enzymes . . . . . . . . . . . . 282
Hepatitis. . . . . . . . . . . . . . .262, 266–270, 463, 481, 494, 511 infection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 239, 511 Hepatitis B infection . . . . . . . . . . . . . 27, 253, 261–262, 267–269, 492 virus . . . . . . . . . . . . . . . . 27, 251, 253, 267–269, 274, 463 Hepatitis C infection . . . . . . . . . . . . . . . . . . . . . . . . . 261, 447–461, 492 virus . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 253, 447 Hepatitis C virus (HCV) infection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 447–461 -pseudotyped particles . . . . . . . . . . . . . . . . . . . . . . . . . . 448 -related cirrhosis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 447 Replication . . . . . . . . . . . . . . . . . . 3, 27–28, 269–270, 448 RNA quantitation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 457 subgenomic replicon . . . . . . . . . . . . . . . . . . . . . . . . . . . . 269 virion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 269 Hepatitis delta virus (HDV) genome . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 464–465 -infected cells . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 466 infection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 463–471 model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 466 particles . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 465–469, 471 RNA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 268, 464–470 in vitro infection system . . . . . . . . . . . . . . . . . . . . . . . . . 466 Hepatobiliary excretion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 283 transport . . . . . . . . . . . . . . . . . . . . . . . . . . 13, 121, 395, 399 Hepatoblast . . . . . . . 6–7, 9, 30, 42, 158, 160–163, 187–189, 191–193, 195–196, 199, 209–211, 248, 417, 482–483, 485, 513, 515 Hepatocanalicular phospholipid translocator . . . . . . . . . . 480 Hepatocarcinogenesis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 172 Hepatocarcinoma . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 266 Hepatocellular carcinoma . . . . . . . . . . . . . . . . . . . . . . . . 266, 447, 464, 513 damage . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 395 differentiation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 216 function . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 497 steatosis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 404 Hepatocyte attachment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 117–119 availability . . . . . . . . . . 6, 25–26, 58, 107, 113, 116, 131, 215, 296, 312, 350, 375, 394, 526, 530–531 cryopreservation . . . . . . . . . . . . . . 107–108, 282–283, 394 culture media . . . . . . . . . . . . . . . . . . . . . 120, 241, 433–435 culture medium . . . . . . . . . . . . . . . . . . . . . . . 240, 312, 439 cytotoxicity assays . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 291 cytotoxicity measurements . . . . . . . . . . . . . . . . . . . . . . . 291 -defining enzymatic properties . . . . . . . . . . . . . . . . . . . 225 differentiation . . . . 5, 7–11, 26, 115–131, 159, 161–162, 173, 175, 188, 202–203, 214, 265–266, 485–486 dynamics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 118 gap junctions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 124 growth factor . . . 47, 161–162, 188, 203–204, 210, 212, 240–241, 250, 481 heterogeneity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 164 homing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 481 injury. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .391–392, 395 innate response . . . . . . . . . . . . . . . . . . . . . . . . . . . . 457–461 integrity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 127–128 isolation. . . . . . . . . . . . . .15, 60, 62, 68, 88, 98, 112, 116, 282–283, 306, 526–527 -like progenitor cells . . . . . . . . . . . . . . . . . . . . . . . . . . . . 199 -like progenitors . . . . . . . . . . . . . . . . . . . . . . . . . . . 173, 199 lineage . . . . . . . . . . . . . . . . . . . . . . . . . . . 161–163, 197, 266
HEPATOCYTES
544 Subject Index Hepatocyte (cont.) markers . . . . . . 7, 124, 173–174, 203–204, 215, 221, 486 maturation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 162–163 metabolism medium . . . . . . . . . . . . . . . . . . . . . . . . 284, 287 metabolite stability assay . . . . . . . . . . . . . . . . . . . . . . . . 287 morphology . . . . . . . . . . . . . . . . . . . . . . . 79, 123, 140, 145 necrosis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 191 plating . . . . . . . . . . . . . . . . . . . . . . 284, 290–291, 438–439 proliferation . . . . . 11–12, 171–172, 187, 189, 191–192, 197–198, 395, 478, 485 sandwiches . . . 3, 13–14, 18, 73, 75, 117–118, 120, 123, 126–127, 131, 145, 148–149, 395, 403 -specific transcriptional factors . . . . . . . . . . . . . . . . . . . 219 suspension medium . . . . . . . . . . . . . . . 284, 286, 376–377 therapies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23–25 transplantation . . . . . . . . . . . . . 24–25, 41, 107–108, 476, 480–481, 485, 525–532 turnover . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 168 viability . . . . . . . . . . . . . . . . . . . . . . . . . . 118, 286, 291, 397 yield . . . . . . . . . . . . . . . . . . . . . . 1–2, 54, 60, 212, 284, 419 Hepatocyte-like cell . . . . . . . . . 3, 6–7, 18, 26, 205, 211–216, 247–259, 262–264, 266, 268, 270, 486, 514 Hepatocytic lineage . . . . . . . . . . . . . . . . . . . . . . . . . . . . 160, 182 Hepatoma cell line . . 4, 9, 18, 20, 26–27, 29, 124–126, 130, 144, 267, 376, 463–464 Hepatotoxicants . . . . . . . . . . . . . . . . . . . . . . 267, 401–402, 404 Hepatotoxic drugs . . . . . . . . . . . . . . . . 18, 282, 395–396, 408 Hepatotoxicity . . . . . 16–17, 19–21, 58, 215–216, 281–293, 390–401, 404, 407–408, 480 screening . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 291–292 Hepatotoxins . . . . . . . . . . . 390–391, 394, 397, 401–402, 404 Hepatotropic viruses . . . . . . . . . . . . . . 27, 253, 266, 484, 492 HepG2 cells . . . . . . . . . . . 4, 17, 19, 124–126, 417, 464, 513 HepPar-1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 205 Hereditary liver diseases . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 477 tyrosinemia type 1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 222 HESC lines . . . . . . . . . . . . . . . . . . . . . . . . . . 239, 241–243, 245 Hesx1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 206 Hex . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 206 HGF, see Hepatocyte, growth factor High content imaging . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19–20 High-performance liquid chromatography . . . . . . . 359, 428 High-performance liquid chromatography (HPLC) . . . 283, 289–290, 313, 315–318, 320, 359, 377, 406, 428 High-throughput screening . . . 5, 16–17, 19, 287, 397–398 HNF1α. . . . . . . . . . . . . . . . . . . . . . . .8, 26, 162, 203, 219, 265 HNF3α . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 161 HNF3β . . . . . . . . . . . . . . . . . . . . . . . . . 161–162, 203, 239–240 HNF4α . 8, 26, 48, 162–164, 193, 203, 208, 219, 239–240, 252, 256, 265, 268, 278 HNF6 . . . . . . . . . . . . . . . . . . . . . . . . . . . 48, 162, 208–210, 219 Hollow fibre cartridges. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .515–517 membrane . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 515–517 Homing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 172, 182, 223, 481 Homogenization buffer . . . . . . . . . . . . . . 63, 74, 78, 312, 316 Honeycomb shape . . . . . . . . . . . . . . . . . . . . . . . . 145, 152–153 Hormones . . . . . . . 7–8, 10–12, 68, 120, 125, 129–130, 163, 216–217, 219–220, 250–251, 310, 356, 395, 435, 479 Host response . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 459–460 House keeping gene . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 303 HPLC/MS/MS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 315 HSP90 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 120, 130
Huh7 . . . . . . . . . . . . . . 4, 20, 27–28, 126–127, 269, 463–469 Huh-7,5/JFH1-derived HCVcc particles . . . . . . . . 448, 461 Human clinical trial failures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 282 cryopreserved hepatocytes . . . . . . . . . . 87, 330–331, 334, 338–339, 343, 347, 350–351 CYP1A1 CYP1A2 locus . . . . . . . . . . . . . . . . . . . . . . . . 502 drug metabolism . . . . . . . . . . . . . . . . . . . . . . . . . . . 282, 296 embryonic stem cell . . . . . . . . . . . . . 7, 163, 237–245, 486 foetal liver cells . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 517 hepatocyte . . . . . . . . . . . . . 2–8, 10, 13, 15–17, 26, 28–29, 70–74, 125, 130, 203, 216, 267, 375, 418, 426, 431–444, 448, 454 hepatocyte cryopreservation . . . . . . . . . . . . . . . . . 107, 282 hepatocyte infection . . . . . . . . . . . . . . . . . . . . . . . . . . . . 451 hepatoma cell lines . . . . . . . . . . 4, 20, 124–126, 130, 376, 463–464 liver tissue fractions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 282 metabolism . . . . . . . . . . . . . . . . . . . . . . . 289, 492, 500, 513 primary hepatocytes . . . . . . . . . . 261–262, 266, 268, 376 -specific drug properties . . . . . . . . . . . . . . . . . . . . . . . . . 282 toxicity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 505, 507 toxicology testing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 397 Humanized liver . . . . . . . . . . . . . . . . . . . . . . . . . 476, 482–484, 491–507 phenotype . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 501 Hybrid bioartificial liver (HBAL) . . . . . . . . . . . . . . . . . . . . 516 Hydatid cyst . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 249 Hydrocortisone . . . . . . . . . . . . . . . . . . . . 43, 78, 250–251, 262 Hydrophobic cationic compounds . . . . . . . . . . . . . . . . . . . 219 6-hydroxy-9 alpha-fluoro-androsta-14-diene-11 beta-hydroxy-16alpha-methyl-3,17-dione . . 502 Hydroxybupropion . . . . . . . . . . . . . . . . . . . 285, 378, 384–386 6-hydroxydopamine . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 172 3-hydroxy-3-methylglutaryl-coenzyme A . . . . . . . . . . . . . 218 1 -hydroxymidazolam . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 385 Hydroxyprogesterone caproate . . . . . . . . . . . . . . . . . . . . . . 218 4-hydroxytamoxifen . . . . . . . . . . . . . . . . . . . . . . . . . . . 297, 304 6β hydroxytestosterone . . . . . . . . . . . . . . . . . . . . . . . . 7, 15, 217 4-hydroxytolbutamide . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 300 Hypercholesterolemia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 528 Hyperoxaluria type 1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 481 Hyperplasia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 190–191 Hyperuricemic dalmatian dog . . . . . . . . . . . . . . . . . . . . . . . 527 Hypothermosol-FRS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 60–61 Hypoxic cell culture . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 172
I ICAM . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 265 Ice crystal formation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 84 Idiosyncratic drug reactions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 511 hepatotoxicity. . . . . . . . . . . . . . . . . . . . . . . . . . . . . .391, 404 reactions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 391 IFN . . . . . . . . . . . . . . . . . . . . . . . . 269–270, 448, 451, 457–458 IL-1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23 IL-6 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23, 163, 211 ILK . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 119–120, 124 Immature phenotype . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 486 Immortalized adult liver cells . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 513 cell line . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4, 526 foetal liver cells . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 513 hepatocytes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 448 human hepatocytes . . . . . . . . . . . . . . . . . . . . . . . . . . 16, 404
HEPATOCYTES Subject Index 545 Immortalizing human hepatocytes . . . . . . . . . . . . . . . . . . . 513 Immune-mediated hepatocyte injury . . . . . . . . . . . . . . . . . 391 Immunocompetency . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 484 Immunodeficient . . . . . . . . . 27, 42, 204, 221, 477, 483–484, 486, 493, 495 Immunodeficient Pfp/Rag2 mice . . . . . . . . . . . . . . . . . . . . 204 Immunofluorescence . . . . . . . . 124, 251–253, 256–258, 263, 277–278, 437, 442–443 Immunogenicity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 223, 512 Immunohistochemistry . . . . . . . . . . . . 46, 498–499, 501, 527 Immunostaining . . . . . . . . . . . . . . . . . . . . . . . . . . 43–44, 49, 74 Immunosuppressant . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 120 Immunosuppression . . . . . . . . . . . . . . . . . . . . . . . 223, 530–531 Immunosuppressive protocol . . . . . . . . . . . . . . . . . . . . . . . . 486 Immunosuppressive treatment . . . . . . . . . . . . . . . . . . 484, 530 Immunotolerance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 223 Immunotolerized rats . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 484 Inborn errors of metabolism . . . . . . . . . . . . . . . . . . . . . . . . . 247 Induced pluripotent stem cells . . . . . . . . . . . . . . . . . . . 25, 169 Inducer concentration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 379 potency . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 307, 383 Induction mechanism . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 369, 371 pathways . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 129 Inductive drug–drug interactions . . . . . . . . . . . . . . . . 289–291 Infection, assays . . . . . . . . . . . . . . . . . . . . . . 464, 466, 468–469 Infectious disease . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 449, 531 particles. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .28 virions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28, 448 Inflammatory infiltrate . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 248 Inherited defect . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 222 Inhibition, of apoptosis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 129 Inhibitor . . . . . . . 12, 23, 27–28, 44, 54, 142, 144, 149–151, 154, 161, 201, 220, 222, 268, 275, 285, 290, 293, 295, 311, 329, 333, 335, 341, 346–347, 399, 432, 477, 479, 483, 492, 500–501 Inhibitory drug–drug interactions . . . . . . . . . . . . . . . 289–290 Inner cell mass . . . . . . . . . . . . . . . . . . . . . . . . . . . . 169, 205, 237 Innervation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 185 Insulin . . . . . . 10, 12, 43, 45, 53, 62–63, 79, 87, 97, 99, 121, 203–204, 207, 212, 239, 241, 250–251, 296, 312, 357, 394, 419, 426, 434–435, 467 Integration plot analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . 332 Integrins family . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 119 -linked kinase . . . . . . . . . . . . . . . . . . . . . . . . . 119–120, 124 receptors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 185 signaling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 119 Intercellular communication . . . . . . . . . . . . . . . . . . 9, 119, 121 Interferon . . . . . . . . . . . . . . . . . . 269–270, 448, 451, 457–458 Inter-individual variability . . . . . . . . . . . . . . . . . . . . . . . . . . 306 Interleukin 2 receptor common gamma chain . . . . . . . . . 494 Interleukin 3 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 203, 265 Interleukin-6 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 163, 211 Intermediate filament proteins . . . . . . . . . . . . . . . . . . . . . . . 188 Inter-preparation variability . . . . . . . . . . . . . . . . . . . . . . . . . 306 Inter-species . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 397 Interspecies differences . . . . . . . . . . . . . . . . . . . . . . . . . . 14, 161 Interstitial flow . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 118 Intestine/intestinal . . 42, 189, 206, 213, 215, 218, 220, 329 Intracellular compartment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15 metabolism . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 327 transporter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 295
Intrahepatic bile ducts . . . . . . . . . . . . . . . . . . . . 158, 189, 195, 209–210 stem cells . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 195–199, 485 Intralobular bile ducts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 182 Intraportal infusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 476 injection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 529 Intrinsic clearance . . . . . . . . 15, 288, 295, 323, 328–329, 331, 503 hepatic clearance . . . . . . . . . . . . . . . . . . 328–329, 349, 352 metabolic clearance . . . . . . . . . . . . . . . . . . . . . . . . . 306–307 IPS. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .25, 169 Iron homeostasis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11, 92, 262 storage . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 266 Ischaemia time. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 108 Isoniazid toxicity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 399 Isopropanol . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49, 85, 98, 452 In vitro hepatic model systems . . . . . . . . . . . . . . . . 58, 74–75, 116 infection assay . . . . . . . . . . . . . . . . . . . . . . . . . 464, 468–469 production of HBV . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 463 uptake clearance . . . . . . . . . . . . . . . . . . . . . . . . . . . 331–332 In vivo biliary clearance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 332 functional reconstitution . . . . . . . . . . . . . . . . . . . . . . . . . 168 uptake clearance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 332 Ito cells . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 189 Itraconazole . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 329
J Jaundice . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 512 JFH1 strain. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .269
K Keratinocyte growth factor . . . . . . . . . . . . . . . . . . . . . . . . . . 274 Keratinocytes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 170 Ki-67 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 199 Kidney capsule . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 484 Kinases . . . . . . . . . 10, 12, 128, 144, 149–150, 172, 188, 196, 393, 404, 479 Knockout mice. . . . .120, 161, 164, 193, 209–210, 483, 497 Kupffer cell . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 483–484
L Lactate dehydrogenase . . . . . . . . . . . . . . . . . . . . . 89, 123–124, 396 production . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 398 Lactic dehydrogenase . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 188 Lactoferrin . . . . . . . . . . . . . . . . . . . . . . . . . . 451, 457, 459, 461 Lamellipodia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 152 Laminin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 118, 185, 395 Lamotrigine . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 310 Latent heat of fusion . . . . . . . . . . . . . . . . . . . . . . . . 84–85, 110 Lateral membrane . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 121 LC/MS-MS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 300 LDL receptor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 528 Lentiviral vector . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45, 51–52 Lentivirus . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45, 51, 498 Leukaemias . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51 Leukemia inhibitory factor . . . . . . . . . . . . . . . . . . . . . 196, 211 Leukotriene C4 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 219 LIF . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 196, 211 LIF-R . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 265
HEPATOCYTES
546 Subject Index Lineage differentiation . . . . . . . . . . . . . . . . . . . . 120, 168, 170 Linoleic acid . . . . 43, 79, 121, 250–251, 296, 357, 434–435 Lipid bilayer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 91 droplets . . . . . . . . . . . . . . . . . . . . . . . . . 16–17, 71, 396, 398 peroxidation . . . . . . . . . . . . . . . . . . 88, 391–393, 396, 399 Lipophilic toxic substances . . . . . . . . . . . . . . . . . . . . . . . . . . 512 Lipoproteins. . . . . . . . . . . . . .10, 25, 204, 216, 218, 396, 507 Lipoviroparticles . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 448 Liv2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 193 Liver assist devices . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 183, 515 -associated congenital pathologies . . . . . . . . . . . . . . . . 238 -based metabolic disorders . . . . . . 24, 107, 525, 527–528 biopsies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 224, 295 biotherapy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 247 bud . . . . . . . . . . . . 158, 161, 186–187, 193, 208, 210–211 cell line . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2–4, 16–17, 29 cell transplantations . . . . . . . . . . . . . . . . . . . . . . . . 221, 531 development . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 181–225 disease . . . . . . 23, 25, 181, 183, 199–200, 205, 214, 222, 247, 464, 498, 507, 511, 525, 527–528 dysfunction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 393 -enriched transcription factors . . . . . . . . . . 120, 188, 395 Enzyme . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 58–59, 73 epithelial cells . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 485 explants . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 162 failure . . . 11, 23–25, 107, 174–175, 182, 213, 511–512, 515, 528 hypoplasia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 162 injury . . . . . . . . . . . 16, 18, 171–172, 191, 195–196, 199, 201–202, 210, 222–223, 389–390, 393, 486, 507 lobule . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 118, 189–191 microsomes . . . . . . . . . . . . . . . . . . . . . . . . . . . 287, 293, 323 morphogenesis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 161 multipotent progenitor cells . . . . . . . . . . . . . . . . . . . . . . 485 non-parenchymal cells . . . . . . . . . . . . . . . . . . . . . . 158, 259 parenchyma . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 162 parenchymal cells . . . . . . . . . . . . . . . . . . . . . 8, 13, 182, 478 physiopathology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 247 precursor cells. . . . . . . . . . . . . . . . . . . . . . . . . . . . . .158, 187 progenitor cell (LPC) . . . . . . . . . 25, 182, 192–193, 223, 247–259 receptor homolog (LRH) . . . . . . . . . . . . . . . . . . . 1, 8, 162 regeneration . . . . 24, 116, 167, 170, 172, 182–183, 187, 189–191, 198, 212, 221–222, 476 renewal . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 189–192 repair mechanisms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 221 repopulation . . . . . . . . . . . . . . . . . 199, 201, 475–486, 496 resection . . . . . . . . . . . . . . . . . . . . . . . . . 59–60, 63, 68, 170 specification . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 160, 186 specific function . . . . 5, 8–9, 29, 211, 266, 376, 394, 403 -specific gene expression . . . . . . . . . . . 125–126, 203, 212 specific genes . . . . . . . . . . . . . . . . . . . . . . . . . . 7–9, 208, 212 stem cells . . . . . . . . . . . . . . . 167–168, 182, 190, 192–202 tissue fractions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 282 tissue source . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 526 transplantation . . . . . 2, 23–24, 182, 296, 448, 476–477, 512, 517, 525, 530 tumorigenesis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 480 zonation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 164 Lobectomies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 249 Long Evans cinnamon rat . . . . . . . . . . . . . . . . . . . . . . . . . . . 527 Long term albumin secretion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 118
culture . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 493 storage . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 282 Loofa sponge . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 515 Low-density lipoprotein . . . . . . . . . . . . . . . . . . . . 25, 204, 218 Low density lipoprotein receptor . . . . . . . . . . . . . . . . . 25, 218 LPC (liver progenitor cells) . . . . 25, 192–193, 247–259, 261 LRH 1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8, 162 Lung . . . . . . . . . . . . . 160, 170, 174, 186, 206, 215, 220, 293 Lymphocytes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 169 Lysosomal functions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 395
M Macrophage . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 203, 484 Malaria . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29, 492 Maleylacetoacetate . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 201 Malondialdehyde generation . . . . . . . . . . . . . . . . . . . . . . . . 399 MAPCs (Multipotent Adult Progenitor Cells) . . . . . . . . 205 MAPK . . . . . . . . . . . . . . . . . . . . . . . . . 115, 120, 127–128, 149 Marrow aplasias . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 223 stroma . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 185, 204 MARS (molecular adsorbent recirculation system). . . . . 512 Mass spectrometry . . . . . . . . . . 289, 315–316, 318, 358, 385, 403–404, 428 Matrigel . . . . . . . . . 3, 63, 73, 75–77, 80, 117–119, 121–128, 130–131, 173, 203, 208, 240–241, 250–251, 256–257, 395, 417–418, 420–421, 423–424, 426 Matrix -induced apoptosis resistance . . . . . . . . . . . . . . . . . . . . 139 -induced hepatocyte differentiation . . . . . . . . . . . . . . . 124 Mature hepatic function . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 215 hepatocyte . . . . . . . . . . . . . . 124, 163, 173, 213, 221, 486 phenotype . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 124, 500 MCM-2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 199 MDR . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 219 MDR1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 328 MDR3 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 480 Mechanical stress . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 95, 118 Medium oxygenation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 514 MEF . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 239, 242 Mefenamic acid . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 311 MEK1/2, 149–151 Membrane fluidity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 92 repolarization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 131 Menadione . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 297, 304 Mercaptans . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 512 Mesenchymal -epithelial transition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42 stem cell . . . . . . . . . . . . . . 6, 169, 200, 204, 485–486, 531 Mesenchyme . . . . . . . . . . . 160, 162, 187–188, 207–208, 210 Mesendoderm . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 159, 206 Mesoderm . . . 6, 42, 157–160, 169, 186–188, 205–208, 238 Metabolic activation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 191, 216, 399 activity . . . . . . . . . . . . . . 15, 217, 221, 282, 350, 395, 492, 498–507, 513 changes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 356 diseases . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41, 528–530 disorder . . . . . . . . . . 24–25, 107, 222, 476, 486, 525–528 enzymes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 330, 482 idiosyncrasy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 391 liver disease . . . . . . . . . . . . . . . . . . . . . . 222, 498, 507, 528
HEPATOCYTES Subject Index 547 pathways . . . . . . . . . . . . . 10, 28, 116, 164, 293, 492–493 perturbation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 393 profile . . . . . . . . . . . . . 4, 15, 267, 363–369, 372, 375, 503 profiling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 360, 369, 405 reaction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 295 responses . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 356, 405 stability . . . . . . . . . . . . . . . . . . . . . . 282, 284, 287–288, 292 states . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 164 turnover . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 376 Metabolically active cells . . . . . . . . . . . . . . . . . . . . . . . . . . . . 530 Metabolism-based toxicity . . . . . . . . . . . . . . . . . . . . . . . . . . 399 Metabolite defect . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 222, 485, 527 pattern . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 376 profiling . . . . . . . . . . . . . . . . . . . . . 101, 284, 288–289, 292 Metabolomics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20, 405 Metabonome . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 401, 406 Metabonomics . . . . . . . . . 355–373, 390, 400–401, 405–407 Metaplasia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 174, 273 Metaplastic conversion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 273 Metastasis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 249, 512 formation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 512 Methanol . . . . . . . . . . . . 50, 73, 143, 283, 300, 342, 352, 378 Methapyrilene . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 403 Methoxyresorufin O-deethylase . . . . . . . . . . . . . . . . . . . . . 503 3-methylcholanthrene . . . . . . . . . . . . . . . . 311, 313, 319, 501 4-methylhydroxytolbutamide . . . . . . . . . . . . . . . . . . . 297–298 Michaelis–Menten rate equation. . . . . . . . . . . . . . . . . . . . .318 Microcapsules . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 514 Microcarriers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24, 515–516 β2-microglobulin . . . . . . . . . . . . . . . . . . . . . . . . . 203, 303–304 Microgravity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 515 Microsomal fraction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 316–317 proteins. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .499, 503–504 Microsomes . . . . . . . . . 16, 95, 287, 293, 312, 316, 318, 320, 323, 499, 501, 504 Microtubules . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 75, 393 Microvesicular steatosis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 393 Midazolam-1-hydroxy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 378 Midazolam . . . . . . . . . . . . . . . . . . . . . . . . . . 267, 297–300, 378 Mitochondrial dysfunction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 393 injury . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 391–392 Mitochondrion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 393 Mitogen-activated growth . . . . . . . . . . . . . . . . . . . . . . . . . . 128 Mitogenic factors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12, 395 Mitotic stimulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 481 Mixed hepatocellular/cholestatic . . . . . . . . . . . . . . . . . . . . . 393 MMP-9. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .182 Modular Extracorporeal Liver Support System (MELS) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 517 Molecular Adsorbent Recirculation System . . . . . . . . . . . 512 Moloney murine leukaemia virus. . . . . . . . . . . . . . . . . . . . . .51 Monkey . . . . . . . . . . . . . . . . . . . . 3, 97–98, 120, 224, 274, 288 Monoclonal antibodies . . . . . . . . . . . . . . . . . . . . . . . . . 193, 530 Monocrotaline . . . . . . . . . . . . . . . . . . . . . . . . . . . . 478–479, 485 Monocytes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6, 203 Mononucleate cells . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 173 Monooxygenases . . . . . . . . . . 8, 125, 216, 282, 289, 300, 391 Morphine . . . . . . . . . . . . . . . . . . . . . . . 310–311, 314, 323, 504 6-glucoronyltransferase . . . . . . . . . . . . . . . . . . . . . . . . . . 504 Morphogenetic growth . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 187 Mouse embryonic stem . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 183
hepatocyte . . . . . 10, 93–94, 97, 102, 144–145, 148–149, 151, 483, 492, 496, 502–503, 506–507 MRNA extraction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 320, 422 measurement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 377, 379 MRP . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 219 MRP1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 219 MRP2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 219, 239, 328 MTor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 265 MTT Metabolism . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 101, 291 test . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 396, 398 Mucin-1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 198 Multidrug resistance 1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 328 Multidrug resistance-associated protein 2 . . . . . . . . . . . . . 328 Multi drug resistance associated proteins . . . . . . . . . . . . . 219 Multidrug resistance (MDR) proteins . . . . . . . . . . . . . . . . 219 Multidrug therapy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 300 Multilamellar inclusion bodies . . . . . . . . . . . . . . . . . . . . . . . 398 Multilayer fibre . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 517 Multilineage differentiation . . . . . . . . . . . . . . . . . . . . . . . . . 168 Multi-organ donors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 58, 63 Multiorgan failure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25, 512 Multiple indicator dilution (MID) method . . . . . . . . . . . 332 Multipotent adult progenitor cells . . . . . . . . . . . . . . . . . . . . . . . . . . . . 205 stem cell . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42, 169 Murine embryonic fibroblasts . . . . . . . . . . . . . . . . . . . . . . . 242 Muscle . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 204, 211, 330, 420 Mycophenolate mofetil . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 530 Myofibroblasts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 187
N 1,4-bis[N ,N ’-di(ethylene)-phosphamide]piperazine . . . 198 N-acetyl-L-cysteine . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 88 N -acetyltransferase-2 . . . . . . . . . . . . . . . . . . . . . . . . . . 504–505 NADH . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 390 Nafamostat mesilate . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 483 Nagase analbuminaemic rat . . . . . . . . . . . . . . . . . . . . . . . . . 527 Naloxone . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 267 β-naphthoflavone. . . . . . . . . . . . . . . . . . . . .302–303, 503–504 1-Naphthol . . . . . . . . . . . . . . . . . . . . . . . . . . 310–311, 314, 324 α-naphthyl isothiocyanate . . . . . . . . . . . . . . . . . . . . . . . . . . . 191 NAT2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 505 Na+ -taurocholate co-transporting polypeptides . . . . . . . . 14 NCAM . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 265 NCE . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 288 Necrosis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 393 Negative-strand HCV RNA assay . . . . . . . . . . . . . . . . . . . 454 Neoplasia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 273 Neuroectodermal cells . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 170 Neuronal . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 205 Neutral lipid . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 396 Neutrophil . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 169, 220 elastase . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 220 New chemical entities. . . . . . . . . . . . . . . . .287, 296, 300, 376 NFE2L2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 266 Niche. . . . . . . . . . . . . . . . . .184–185, 195, 198–199, 238, 493 Nicotinamide . . . . . . . . . . . . . . . . . . . . . 12, 204, 250–251, 275 4-nitrophenol . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 311 2-(2-nitro-4-trifluoro-methylbenzoyl)-1,3cyclohexanedione . . . . . . . . . . . . . . . . . . . . 174, 201 NK cell . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 483–484 NKNT-3 cells . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 513 NMR . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 358, 405–406
HEPATOCYTES
548 Subject Index Nodal . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 159, 207 Node . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 159 Non-hepatotoxic drugs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 395 Non-invasive method . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 502 Non parenchymal epithelial cell . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 253–255 liver fraction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 172 Normal liver mass . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 476, 517 Notch . . . . . . . . . . . . . . . . . . . . . . . . 8, 185, 188, 209–210, 265 NSAID . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 392 NTBC . . . . . . . 174–175, 201, 477, 484, 494–495, 497, 504 NTCP . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 219, 328, 330, 350 Nuclear factor-kB (NF-kB) . . . . . . . . . . . . . . . . . . . . . . . . . . 23, 219 magnetic resonance (NMR) spectroscopy . . . . . 358, 405 receptor . . . . . . . . 6, 10, 21, 23, 129, 263, 267, 319, 356, 371, 376 receptor superfamilies . . . . . . . . . . . . . . . . . . . . . . . . . . . 356 translocation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 120, 130 Nuclear magnetic resonance . . . . . . . . . . . . . . . . . . . . 358, 405 Nucleosomes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 208 Nucleus . . . . . . . . . . . . . . 18–19, 72, 120, 130, 256, 268, 393 Nutrient/gas supply . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 514
O OAT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 219, 328 OATP1B1 -expressing cells . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 347 inhibitor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 329 substrate . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 330 OATP1B3 . . . . . . . . . . . . . . . . . . 328, 330–331, 336, 344–347 -expressing cells . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 345 OATP2B1 . . . . . . . . . . . . . . . . . . 328, 331, 336, 344, 346–347 OATP . . . . . . . . . . . . 327, 332, 334–336, 340–347, 350, 352 OCT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 219, 328 Oct4 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 163, 205 OLT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 182, 525–526, 531 Omeprazole . . . . . . . . . . . 291, 297, 302, 304, 307, 378–379, 381–383, 385–386 Oncoretrovirus . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51 Oncostatin M . . . . . . . . . . 163, 188, 204, 211, 240, 274–277 Organ donor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 58, 63, 247 preservation media . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 527 Organic acidemias . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 222 anion transporters OAT . . . . . . . . . . . . . . . . . . . . 219, 240 anion-transporting polypeptides . . . . . . . . . . . . . . . . . . 219 cation transporters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 219 solvents . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 129, 283, 352 Ornithine transcarbamylase . . . . . . . . . . . . . . . . . . . . . 220, 529 Orthotopic liver transplantation. . . . . . . .182, 476, 512, 525 Osmolarity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 84, 95 Osmosis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 84, 95, 102 Osmotic imbalance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 91 OTC . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 220 Otx2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 206 OV1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 264 OV6 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 264 Oval cell progenitors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 171 cells . . . . . . . . . . . . . . . . 171–173, 192, 195–199, 248, 264 Oval progenitor cells . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 485 Overall intrinsic hepatic clearance (CLint,all ) 328–329, 331 β-oxidation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 393, 399
Oxidative conversion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 391 metabolism . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 216, 300 stress . . . . . . . . . . 21–22, 71, 92, 391–393, 398–399, 402, 404, 408 Oxygen consumption . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 398 species . . . . . . . . . . . . . . . . . . . . . . . . . . . 5, 14, 88, 391–393 supply . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 514–516 Oxygenation capillaries . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 516 Oxysterols . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 428
P p23 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 120 p27Kip1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 479 p42/44 MAPK . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 127–128 p53 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9, 264 P450 activities . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17, 403 induction . . . . . . . . . . . . 87, 290–291, 375–386, 399, 402 inhibitors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 293, 399 isoforms . . . . . . . . . . . . . . . . . . . . . 283, 285, 287, 290, 293 patterns . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 306 Paclitaxel 6-hydroxylase. . . . . . . . . . . . . . . . . . . . . . . . . . . . .499 Pancreas . . . . . . . . . . . . 42, 157, 186, 209, 213, 274–275, 527 -to-liver transdifferentiation . . . . . . . . . . . . . . . . . . . . . 274 Pancreatic acinar cells. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .274–275 AR42J-B13 cell model . . . . . . . . . . . . . . . . . . . . . . . . . . 274 cells . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 187, 273–279 epithelial cells . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 274 exocrine cells . . . . . . . . . . . . . . . . . . . . . 274, 276–277, 279 fate . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 187 islet . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 208 Paracetamol . . . . . . . . . . . . . . . . 310, 315, 377–378, 384–386 Paracrine effect . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 486 Parasitic infections . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 492 Parasitology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25–29 Parenchymal cells . . . . . . . 8, 13, 58, 68, 158, 167, 173, 182, 189, 196, 208, 212, 259, 282, 395, 478 Parietal endoderm . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 206 yolk sac . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 206 PARP . . . . . . . . . . . . . . . . . . . . . . . . . . 145–148, 150–151, 153 Partial hepatectomy . . . . . . . . . . 60, 171, 187, 190, 197–199, 221, 248, 296, 305, 478–480, 485 Patients blood . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 515, 518 bloodstream . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 518 circulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 518 plasma . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 515, 518 PB-responsive enhancer modules . . . . . . . . . . . . . . . . . . . . 130 PCR . . . . . . . . . . . . . 243, 251–252, 278, 297, 303, 307, 314, 321–322, 377, 381, 383, 385, 451, 453, 455, 457 PDGFRa . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 206, 209 Pegylated interferon α . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 448 Penicillin . . . . . . . . 43, 62–63, 121, 140, 242, 250–251, 262, 275–276, 296, 312, 335, 357, 434 Pentachlorophenol . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 311 Peptide mass fingerprinting . . . . . . . . . . . . . . . . . . . . . . . . . 405 Percoll . . . . . . . . . . . 60, 62–64, 70, 86, 95–96, 100–102, 351 Percutaneous . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 224, 529 Percutaneous liver biopsies . . . . . . . . . . . . . . . . . . . . . . . . . . 224 Pericanalicular . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 399
HEPATOCYTES Subject Index 549 Pericentral areas. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .191 proteins . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 164 Peripheral blood . . . . . . . . . . . . . . . . . . . . . . 195, 201, 203–204 Periportal areas. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .191 hepatocytes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 164, 190 Peritoneal cavity . . . . . . . . . . . . . . . . . . . . . . . . . . . 24, 527, 530 Permissivity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 268–269 Peroxetine . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 500 Peroxiredoxins . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 404 Peroxisomal proliferator-activated receptor-γ coactivator 1α (PGC1α) . . . . . . . . . . . . . . . . . . . . . . . . . . . . 130 Peroxisome proliferators . . . . . . . . . . . . . . . . . . . . . 5, 129, 401 PERV . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 513, 516 PFIC . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 480, 482, 529 Pharmacokinetics . . . . . . . . . . . . . . . . . . . . . . . . . 282, 329–330 Pharmacology . . . . . . . . . . . . . . . . . . . . . . . . . 58, 126, 215, 247 Phase I . . . . . . . . . . 5, 14–15, 18, 22, 58, 116, 129, 216, 287, 295, 328, 391–392, 394, 397, 402, 493, 505, 516–518 clinical trial . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 517 Phase II conjugation pathways . . . . . . . . . . . . . . . . . . . . . . . 129, 506 metabolic profile . . . . . . . . . . . . . . . . . . . . . . . . . . . 116, 295 Phenacetin . . . . . . . . . . . . . . . . . . . . . . 285, 297–301, 378, 385 Phenobarbital . . . . 11, 20, 22, 129–130, 198, 217, 311, 313, 319, 356–357, 359, 365–369, 371, 373, 379, 399, 504 Phenotype . . . . . . . . . 7–9, 79, 116–118, 120, 124, 127–130, 144, 149, 152–153, 174, 194, 200–201, 203, 205, 208–210, 212, 215, 238, 248, 263–266, 277–278, 298, 305–307, 400, 407, 444, 486, 500–501, 531 Phenotypic instability . . . . . . . . . . . . . . . . . . . . . . . . . . . 20, 394 Phenotyping . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 301, 311 Phenylacetylglycine . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 407 Phenylalanine . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 481 Phenylketonuria . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 481 Phosphatidylinositol 4,5-bisphosphate (PI(4,5)P2) phosphatase . . . . . . . . 119 signaling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 119 3’-phosphoadenosine 5’-phosphosulfate . . . . . . . . . . 310, 313 Phospholipid accumulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 402 secretion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 480 Phospholipidosis . . . . . . . . . . . . . . . . . . 16, 398, 402, 407–408 PH regulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 129 Phthalate esters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 129 PI3K . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12, 151, 207, 240 PI3 kinase . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 128 Pig hepatocytes . . . . . . . . . . . . . . . . . . . . . . . . . . 85, 87, 97, 100 Pitavastatin . . . . . . . . . . . . . . . . . . . . . . . . . . 331, 346–347, 349 PIVKA-II . . . . . . . . . . . . . . . . . . . . . . . . . . . 432, 436, 440–441 PKB . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 127 Plasma membrane . . . . . . . 5, 14, 71, 84, 88, 90, 92, 98–99, 101, 121, 295, 304, 408 perfusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 516–517 protein . . . . . . . . . . . 11, 90, 124–126, 390, 394, 396–397 protein synthesis . . . . . . . . . . . . . 124, 390, 394, 396–397 Plasmapheresis. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .512 Plasminogen activator inhibitor . . . . 27, 432, 477, 483, 493 Plasmodium falciparum . . . . . . . . . . . . . . . . . . . . . . . . . 29, 482 Plasmolysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 84 Platelet, -derived growth factor receptor-a . . . . . . . . . . . . 206
Plating, medium . . . . . . . . 43, 46–47, 50–51, 284, 290–291, 296, 302 Pluripotent stem cells . . . . . . . . . . . . . . . . . . . . . . . . . . . 25, 30, 169, 197 tumors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 169 Polarity . . . . . . . . . . . . . . . . 6, 26, 75, 119, 121, 140, 310, 424 Polyadenylation signal . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 466 Poly-amino-urethane-coated fabric . . . . . . . . . . . . . . . . . . 241 Polybrene . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54 Polychlorinated hydrocarbons . . . . . . . . . . . . . . . . . . . . . . . 129 Polyester . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 514, 516 Polyethersulfone . . . . . . . . . . . . . . . . . . . . . . . . 61–62, 514, 517 Polyethylene glycol . . . . . . . . . . . . . . . . . . . . . 26, 92, 267, 467 Polysomes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 265 Polysulfone . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 516–517 Polyurethane . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 514 Polyvinylpyrrolidone . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 91 Porcine cells . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 513, 516–517 endogenous retroviruses . . . . . . . . . . . . . . . . . . . . . . . . . 513 hepatocytes . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23, 515–516 liver cells . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 513, 516–517 Portal hypertension . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 222, 530 mesenchyme . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 162 spaces . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 164, 192 triads . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 182, 189 Posterior endoderm . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 160 Post-thaw viabilities . . . . . . . . . . . 86–87, 90–92, 95, 98, 100 PPARα . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 267, 319 PPARδ . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 266 PPAR-γ agonists. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .172 Pravastatin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 329, 349 PRB . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 264 Precursor cells . . . . . . . . . . . . . . . . 25, 158, 169, 187, 190, 193 Prediction . . . . . . . . . . 4, 15–17, 21, 306, 331–332, 347–350, 390, 394, 406, 505, 507 Pref-1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 193 Pregnane X receptor . . . . . . . . . . . . . . . . 5, 126, 218, 311, 356 Pre-implantation embryos . . . . . . . . . . . . . . . . . . . . . . . . . . 237 Primary bile acids . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 417 culture . . . . . . . . . . 2–3, 20, 26–27, 58, 70, 75, 130–131, 139, 145, 148, 219, 257, 268, 355–373, 395, 448, 464 hepatocytes . . . . . . . . . . . 3, 5, 7–8, 11, 14, 18, 20–21, 26, 28–29, 57–80, 116–117, 120, 124, 126–127, 130–131, 199, 211, 213, 220, 241, 266, 268, 292, 376, 394, 397–399, 425–428, 432, 479–480 human hepatocytes . . . . . . . . 2–8, 10, 13, 15–17, 19–20, 22, 26, 28–29, 70–74, 125, 130, 203, 216, 267, 319, 375, 418, 424, 426, 431–444, 448, 454 tumor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 249 Primitive gut . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 157, 187 Primordial germ cells . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 169 Principal component analysis . . . . . . . . . . . . . . . . 22, 358, 406 Procarcinogens. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .129 Profibrogenic potential . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 486 Progenitor cell compartment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 476 population . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 187, 199 transplantation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 199 Programmed differentiation . . . . . . . . . . . . . . . . . . . . . . . . . 164 Progressive familial intrahepatic cholestasis. . . . . . . . . . .476, 480–481, 529
HEPATOCYTES
550 Subject Index Proliferation . . . . . . 5–6, 11–12, 16–17, 120, 158, 161–162, 171–173, 184, 186–187, 189, 191–193, 195–199, 210–211, 248, 263, 265, 395, 475, 478–481, 484–485, 493, 506, 512–513 Prometheus . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 170, 190, 512 Propofol . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 311, 314 Prospero-related homeobox factor (Prox) . . . . . . . . . . . 1, 161 Proteasomal protein recycling . . . . . . . . . . . . . . . . . . . 395, 402 Protein C . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 274, 432 Protein S . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 432, 436, 441 Proteomics . . . . . . . . . . . . . . 20, 390, 400, 401, 403–405, 407 Prothrombin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 432 Prox1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 193 PSuptake . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 328–329, 331 Punc E11 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 194 PXR . . . 5, 8, 11, 21, 23, 126, 218, 240, 252, 257, 267, 311, 319, 356, 366, 369–371 Pyrrolizidine alkaloid . . . . . . . . . . . . . . . . . . . . . . . . . . 199, 478 Pyruvate . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87, 296, 357, 434 Pyruvate kinase . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10, 188
Q Quasi-species . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 448 Quick-thaw method . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 95 Quiescent . . . . . . . . . . . . . . . . . . . 41, 170, 184, 189, 190, 476 Quinidine . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 285, 500 Quinones . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 399
R Rabbit . . . . . . . . . . . . . . 45–46, 131, 142, 252, 278, 342, 351, 436–437, 443, 515, 517 Radial flow bioreactors . . . . . . . . . . . . . . . . . . . . . . . . . 515–516 Radical . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 92, 391, 393, 398 Rag2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 204, 483, 493 Rag2-/-/Il2-/- . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 483, 494 Rapid freezing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 84 Rat hepatocyte . . 2, 6, 10, 12–13, 16, 18, 24, 54, 89, 93–94, 97, 100, 123, 127–128, 131, 219, 332–334, 337, 339, 342, 484 hepatoma . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 267, 417 -human fibroblast hybrid cell line . . . . . . . . . . . . . . . . 417 -isolated hepatocytes . . . . . . . . . . . . . . . . . . . . . . . . . . . . 350 -tail type I collagen . . . . . . . . . . . . . . . . . . . . . . . . . 419, 421 Reactive intermediates . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 393, 408 metabolites . . . . . . . . . . . . . . . . 14, 16, 392–393, 399, 403 Real time PCR . . . . . . . . 252, 297, 303, 314, 321–322, 376, 380–383, 419, 423, 452, 454–456, 459 Recombinant activation gene-2 . . . . . . . . . . . . . . . . . . . . . . 493 Recombinant lentiviruses . . . . . . . . . . . . . . . . . . . . . . . . . 45, 51 Red blood cells . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 173 Redox cycles . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 393 Reductase . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 218, 240, 432 Refsum disease . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 476 Regenerative medicine . . . . . . . . . . . . . . . . . . . . . . . . . 175, 181, 215, 526 nodules . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 507 Reichert’s membrane . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 206 Rejected donor organs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 60 Rejected livers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59 Rejection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 223–224, 531 Relative activity factor (RAF) method . . . . . . . . . . . . . . . . 330 Renal damage . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 495, 497
Replacement index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 498 Replicating cell lines . . . . . . . . . . . . . . . . . . . . . . . . . . . 492, 502 Replication . . . . . . . . . . . . . . 3–4, 25–28, 171, 173, 190–191, 199, 267–270, 274, 448, 454, 456, 459–461, 464, 506 Repopulation . . . . . . . . . . 175, 184, 199, 201, 216, 222, 224, 475–486, 493–501, 503–504, 506, 531 Reporter protein . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 527 Reprogramming. . . . . . . . . . . . . . . . . . . . .9, 25, 175, 200, 273 Resection . . . 58–60, 63, 65, 67–68, 170, 248–249, 306, 418 Resins . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 514 Respiratory chain complex . . . . . . . . . . . . . . . . . . . . . . . . . . 529 Reticuloendothelial system . . . . . . . . . . . . . . . . . . . . . . . . . . 531 Retinoic acid . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23, 160 Retinoid X receptor . . . . . . . . . . . . . . . . . . . . . . . 218, 240, 356 Retrorsine . . . . 173, 195, 198–199, 221, 478–479, 481–482 Retroviral Receptor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 528 transduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51–52, 54 vectors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 479 Retroviruses . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51, 498, 513 Reverse-phase chromatography . . . . . . . . . . . . . . . . . . . . . . 315 Reverse transcription . . . . . . . . . 43, 251, 268, 303, 419, 452 Ribavirine . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 448 Ribonucleoprotein . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 464 Rifabutin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 502 Rifampicin . . . . . . . . . 15, 217, 220, 297, 303–304, 307, 311, 313, 319, 324, 356–357, 359, 365–371, 373, 378–379, 381–383, 385–386, 399, 501–504 Risk assessment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 131, 398 RNA extraction . . . . . 121, 251, 314, 320, 380–381, 419, 422, 451–452, 469 precipitation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 452 solubilization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 452 washing. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .452 Ros-1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 198 Rotary systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 515 RT-PCR . . . 47–48, 124, 257–258, 277–279, 300, 303, 377, 381, 399, 452–454, 456–457, 459–460, 466, 471, 497 RXR . . . . . . . . . . . . . . . 23, 120, 127, 130, 218, 239–240, 356
S Safety biomarkers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 400 Sandwich culture . . . 14, 117–120, 127, 131, 141, 145–146, 148–149, 152, 403, 424 Sanguinarine . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 399 SAPK . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 120, 127–128 SAPK/JNK . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 120, 127–128 Sca-1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 169, 193, 196, 201 Scaffold . . . . . . . . . . . . . . . . . . . 3, 23, 118, 239, 398, 514–515 SCID . . . . 6, 42, 45, 52, 266, 483–484, 486, 493–495, 498, 500–501, 503–507 SDF-1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 182 Secretion . . . . . . . 5, 10, 12–14, 57, 116, 118–119, 121, 185, 204, 216, 220, 240, 393–394, 396, 418, 431–444, 466, 480, 483, 499, 501 SEK-1, 193 Selective advantage . . . . . . . . . . . . . . . . . . . . . . . . 476–477, 479, 528 pressure . . . . . . . . . . . . . . . . . 477, 481, 484, 486, 494–495 Selective Plasma Exchange Therapy (SEPET) . . . . . . . . 512 Self-renewal . . . . . . . . . . . . . . . . . . . . . . . . . 167–169, 191, 237 Semi-permeable membranes . . . . . . . . . . . . . . . . . . . . . . . . 531
HEPATOCYTES Subject Index 551 Senescence . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 191, 531 Senescent cells . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 184 Septum transversum . . . . . . . . . . . . . . 42, 158, 160, 186–188, 207–208, 210 Serial transplantability . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 184 transplants . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 496 Serine proteases . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 220 Serotonin reuptake inhibitor . . . . . . . . . . . . . . . . . . . . . . . . 500 Serum albumin . . . . 43–44, 52, 62, 92, 108, 250, 275, 335, 341, 348, 357, 435, 437, 527 -derived HCV virions . . . . . . . . . . . . . . . . . . . . . . 448, 461 -free medium . . . . . . . . . . . . 6, 51, 79, 120, 152, 320, 467 Severe combined immunodeficiency (SCID) . . . . . . . . 6, 42, 45, 52, 266, 483–484, 486, 493–495, 498, 500–501, 503–507 Sex determining region-Y box 17 . . . . . . . . . . . . . . . . . . . . 209 Shear stress . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 118 Shock freeze . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85 Short-term culture . . . . . . . . . . . . . . . 433–434, 438, 444, 449 Side population . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 196 Signaling activities. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .139–154 factors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 157–164 pathway . . . . 11, 118, 120, 127–128, 187–188, 207, 210 Signal transduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . 142, 152 Simvastatin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 329–330 lactone . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 329–330 Single Pass Albumin Dialysis (SPAD) . . . . . . . . . . . 512, 517 Sinusoidal . . . . . . . . . . . . . . . . . 13, 17, 58, 119, 121, 187, 190 endothelial cells . . . . . . . . . . . . . . . . . . . . . . . . 17, 171, 507 Sinusoid-like structures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 507 Sinusoids . . . . . . . . . . . . . . . . . . . . . . . . . . . . 121, 158, 187, 190 Sirolimus . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 530 In situ hybridization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 499 Skeletal myoblasts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 169–170 Skin epithelia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 170 epithelium . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 184 SLC family . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 219 Slices . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3–4, 515 Slow freezing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 84–85 SMAD . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 193 Smad2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 142, 150 Small-cell colonies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 173 Small hepatocyte-lik eprogenitor cells (SHPC) . . . 173, 199 Small hepatocyte (SH) . . . . . . . . . . . . . . . . . . . . . . . . . 173, 199 Small intestine . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 215 S-Mephenytoin 4-hydroxylase . . . . . . . . . . . . . . . . . . . . . . . 499 SNPs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 330 Sodium butyrate . . . . . . . . . . . . 163, 212, 241, 335, 340, 352 Soltran . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 60 Somite . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 207 Sox17a/b . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 206, 209 Space of Disse . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 118, 219 Species comparison . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 288–289 differences . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 97, 289, 397 Species–species differences . . . . . . . . . . . . . . . . . . . . . 281–282 Species-specific phenotypic differences . . . . . . . . . . . . . . . . . . . . . . . . . . 131 xenobiotic metabolism . . . . . . . . . . . . . . . . . . . . . . 281–282 Spectroscopy . . . . . . . . . . . . . . . . . . . . . . . . . 358–359, 405–406
Spheroids . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 117, 517 Spleen . . . . . . . . . . . . 6, 24, 53, 224, 266, 494, 497–498, 527, 529–530 Squamous epithelium. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .174 SRY-box containing transcription factor 17 (Sox17) . . . . . . 159–160, 163, 206–207, 239–240 SSEA-4 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 205 Standard isolation method . . . . . . . . . . . . . . . . . . . . . . . . . . 116 Stat3 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 211 Statin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 330 -induced severe myopathy . . . . . . . . . . . . . . . . . . . . . . . 330 Steatosis . . . . . . . . . 16–17, 60, 108, 248, 393, 398–399, 402, 404, 408 Stellate cells . . . . . . . . . . . . . . . . . . . . . . 17, 127, 171, 187–188 Stem cell biology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 168, 181 compartment . . . . . . . . . . . . 182, 194–195, 198, 221, 225 -derived cells . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 222 -derived hepatocyte . . . . . . . . . . 215–218, 220–225, 486, 494, 526 differentiation . . . . . . . . . . . . . . . . . . . . . . . . . 157–164, 208 function . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 172, 223 niche . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 184–185 paradigm . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 168 plasticity . . . . . . . . . . . . . . . . . . . . . 168, 174–175, 200, 203 pool . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 184 Steroid hormones . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 217, 219, 356 receptor coactivator 1 (SRC-1) . . . . . . . . . . . . . . . . . . . 130 Steroid receptor coactivator 1 (SRC-1) . . . . . . . . . . . . . . . 130 Sterol 12α-hydroxylase . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 425 27-hydroxylase . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 425 Stomach . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42, 157–158 Storage conditions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 84–86 Streptomycin . . . . . . . . . . . 43, 121, 140, 242, 250–251, 262, 275–276, 296, 312, 335, 357, 434 Stress activation responses . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 127 cascades . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 127 pathways . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 127–128 Stromal cells . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 173, 183, 185 Structure–toxicity relationships . . . . . . . . . . . . . . . . . 399–400 Subconfluent monolayers . . . . . . . . . . . . . . . . . . . . . . . . . 71–72 Sub-lethal concentrations . . . . . . . . . . . . . . . . . . . . . . 397–398 Substrate cocktail . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 383 Sulfamethazine N-acetyl transferase . . . . . . . . . . . . . 504–505 Sulfation. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .310–312 Sulfotransferase . . . . . . . . . . . . . . . . . . 283, 285, 309–324, 504 SULT 1A1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 311, 322 2A1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 311, 319, 322 1A3 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 310–311, 322 1B1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 311, 322, 504 1E1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 311, 319, 322, 504 superfamilies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 310 Surface antigens . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 498 Surface-enhanced laser desorption ionization (SELDI) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 404 Surgical liver resection. . . . . . . . . . . . . . . . . . . . . . . . . . . .59–60 Susceptibility factors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 393 Suspension culture . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 212, 238 Swarm-Engelbreth-Holm carcinoma . . . . . . . . . . . . . . . . 118 Synthase . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 218
HEPATOCYTES
552 Subject Index T Tacrolimus . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 530 Taurine . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 92 Taurocholate . . . . . . . . . . . . . . . . . . . . . . . . . . 14, 219, 350, 396 TCDD . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 319, 503 TECA Hybrid Artificial Liver support System (TECA-HALSS) . . . . . . . . . . . . . . . . . . . . . . . . 516 Telmisartan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 346–348 Telomerase activity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 205 Telomere shortening . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 191 Tendon . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 141, 204, 419 Teratomas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 169, 223 Testicular seminoma . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 193 Testosterone . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7, 15, 285, 504 6-beta-hydroxylase activity . . . . . . . . . . . . . . . . . . . . . . 502 Tetracycline . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 398, 404 Tetratricopeptide repeat-containing protein . . . . . . . . . . . 130 Tetratricopeptide repeat proteins. . . . . . . . . . . . . . . . . . . . .120 TGF-β-induced apoptosis . . . . . . . . . . . . . . . . . 147, 150–152 Thawing . . . . . . . . . . . 3, 80, 84, 86–87, 92, 94–96, 100, 102, 107–109, 111–113, 262, 282–284, 286–287, 292, 298–299, 305, 334, 338–339, 384–385, 420, 452, 461, 531 techniques . . . . . . . . . . . . . . . . . . . . . . . . 84, 92, 94–95, 102 Thin layer chromatography (TLC) . . . . . . 16, 313, 317, 323 Three-dimensional bioreactors . . . . . . . . . . . . . . . . . . 117–118 Thrombin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 431–432 Thy1 . . . . . . . . . . . . . . . . . . . . . . . . . . . 171, 174, 201, 203, 265 Thyroid hormones . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 310 Tight junction . . . . . . . . . . . . . . . . 28, 58, 116, 119, 265, 507 Time-of-flight mass spectroscopy . . . . . . . . . . . . . . . . . . . . 359 Tissue -like structures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 514, 517 remodeling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 210 renewal . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 167–169 -specific stem cells . . . . . . . . . . . . . . . . . . . . . . . . . 169, 273 TLC plates . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 313, 317 α-tocopherol . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 92 Tolbutamide . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 285, 297–301 Tolerogenic . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 223 Totipotent . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 169 Toxicity . . . . . . . . . . . . . . 14–23, 91, 100, 102, 123, 215, 222, 266–267, 282, 289, 291–292, 389–408, 477, 481, 491–507 assessments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 401 Toxic metabolites . . . . . . . 174, 201, 222, 291, 391, 477, 494 Toxicogenomics . . . . . . . . . . . . . . . . . 16, 20–21, 30, 401–403 Toxicological endpoints . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 402, 405 screening . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 237, 406 Toxicotranscriptomics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 405 TRA-1–60 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 205 TRA-1–81 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 205 Trabecular cordlike structures . . . . . . . . . . . . . . . . . . . . . . . 507 Transcription factor . . . . . . . . . . . . . . . 6–9, 26, 120, 126, 129, 158–162, 164, 187–188, 193, 203, 206, 208–212, 219–221, 266, 268, 274, 319, 356, 376, 393, 395 Transdifferentiation. . . . . . . 5–7, 29–30, 196–197, 200–203, 273–279, 485 Transduction . . . . . . . . . . . . . . . . 25, 51–52, 54–55, 142, 152, 265–266, 498 Transferrin . . . . . 9, 11, 51, 76, 79, 101, 121, 124–125, 199, 203–204, 219, 240, 242, 274, 278–279, 296, 312, 357, 396, 434–435
Transforming growth factor-β (TGF-β) . . . . 129, 144–145, 147–150, 152, 154, 159, 162, 188, 207, 210, 265 Transgene expression . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 492 Transgenic insertions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 492 Transit amplifying . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 172, 196 cells . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 184, 195 Transjugular . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 529–530 Transplantable hepatocytes . . . . . . . . . . . . . . . . . . . . . . . . . . 184 Transplantation . . . . . . . . . 2, 7, 23–25, 30, 41–55, 107–108, 112–113, 160, 168–174, 182–184, 194, 197, 199–201, 203–204, 206, 213, 220–225, 239–241, 247–249, 264, 274, 296, 305, 448, 476–481, 483, 485–486, 493, 495–498, 500, 506, 511–512, 517, 525–532 Transplanted hepatocytes. . . . . .53, 476–480, 483, 527, 529 Transporter -expressing cell lines . . . . . . . . . . . . . . . 330, 335, 340–341 expression systems . . . . . . . . . . . . . . . . . . . . . . . . . 330, 345 -mediated uptake . . . . . . . . . . . . . . . . . . . . . . . . . . 344, 346 protein . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 216, 376 substrates . . . . . . . . . . . . . . . . . . . . . . . . 329–332, 347–350 Transthyretin . . . . . . . . . . . . . . . . . . . . . . . . 124–126, 160, 240 Trehalose . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 92, 98 Trimera mice . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 484 Triphenylcarboxylic acid . . . . . . . . . . . . . . . . . . . . . . . . . . . . 311 Troglitazone sulfotransferase . . . . . . . . . . . . . . . . . . . . . . . . 504 Trypan blue . . . . . . 47, 62, 70, 94, 96, 98–99, 101, 112, 284, 286–287, 299, 312, 315, 322, 334, 338–339, 396, 438 Tryptophan 2,3-dioxygenase . . . . . . . . . . . . . . . 204, 209, 240 Tumorigenesis . . . . . . . . . . . . . . . . . . . . . . . . . . . . 129, 480–481 Tumorigenicity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 223 Tumorigenic potential . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 172 Tumors . . . 2, 4, 6, 58–59, 63, 169, 205, 357, 420–421, 423 TUNEL . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 506 Tupaia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26, 267, 482–483 Turnover . . . . . . . . . . . . . . . . . . . 167–168, 182, 190, 305, 376 Two-dimensional electrophoretic (2-DE) protein separation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 405 Two-dimensional Matrigel sandwich configuration . . . . 126 Two-dimensional sandwich culture . . . . . . . . . . . . . . 117–120 Two-step liver digestion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 70 Type IV collagen . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 185 Tyrosine-aminotransferase . . . . . . . . . . . . 204, 209, 240, 278 Tyrosine degradation pathway . . . . . . . . . . . . . . . . . . . . . . . 477 Tyrosinemia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 191, 201, 222 Tyrosinemia mice . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 191, 201
U UDP -glucuronic acid . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 310 -glucuronosyltransferase . . . . . . . . . . . . . . . . 220, 309–324 UGT 1A1 . . . . . . . . . . . 220, 267, 310–311, 319, 321–322, 324 1A3 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 311, 322 1A4 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 311 1A6 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 311, 319, 322, 324 1A9 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 311, 319, 322 2B7 . . . . . . . . . . . . . . . . . . . . 266, 311, 319, 322, 324, 504 2B15. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .311, 322 superfamilies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 310 Ultra-performance liquid chromatography (UPLC) . . . 357, 359–360, 362 Umbilical cord blood. . . . . . . . . . . . . . . . . . . . . . . . . . .204, 485 Umbilical cord matrix . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 486
HEPATOCYTES Undecanoic-lactone . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 501 Unipotent . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 189, 195 University of Wisconsin solution (UW solution) . . . 59–60, 108–109, 298, 527 Unstirred water layer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 332 UPA-deficient mice . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 483 UPA mice . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27, 477, 483 UPA/SCID mice . . . . . . . . . . . . . . . . . . . . . . . 6, 266, 498, 505 UPLC-ToF-MS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 359–362 UPLC-TOF-MS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 359–362 Uptake intrinsic clearance (PSuptake ) . . . . . . . . . . . . . . . . . . . . 328 transporters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 327–352 Urea cycle defect . . . . . . . . . . . . . . . . . . . . . . . 113, 222, 476, 529 production . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 220, 394 Ureogenesis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 390, 393, 397 Urinary elimination . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 505 Urokinase plasminogen activator (uPA) . . . . . . 27, 477–478, 483–484, 486, 493, 495, 497
V Valproic acid . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 310 Valsartan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 347, 349–350 Variability . . . . . . . 2, 5–6, 15, 26, 29, 75, 87, 217, 239, 270, 297–298, 306–307, 372, 397, 402–403, 444, 457, 502 Vascular endothelial growth factor receptor-2 (VEGFR2) . . . . . . . . . . . . . . . . . . . . . . . . . 206, 209 Vascular Endothelial Receptor . . . . . . . . . . . . . . . . . . . . 2, 161 VE-cadherin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 209 Vegetal alkaloids . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 478 Ventral endoderm . . . . . . . . . . . . . . . . . . . . . . . . . 42, 158, 160, 207 foregut . . . . . . . . . . . . . . . . . . . 42, 158, 186–187, 207–208 Vesicular stomatis G (VSV-G) envelope . . . . . . . . . . . . . . . 51 Vimentin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 252, 256 Viral entry . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28, 466 genome replication . . . . . . . . . . . . . . . . . . . . . . . . . 448, 461 life cycle . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27, 29, 268 particles . . . . . . . . . . . . . . . . . . . . . . . . . 26–28, 51, 461, 471 transcription . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 464 vectors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 513 Virion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28, 267–268, 456 Virology . . . . . . . . . . . . . . . . . . . . . . 25–29, 247, 261–270, 449 Virus . . . . . . . . 26–28, 51, 54, 251, 253, 258, 262, 267–270, 274, 447–448, 463–464 transfer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 512 Visceral endoderm . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 206–207 yolk sac . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 206 Vitamin A . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 216 B12 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 216 C . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 312, 434
Subject Index 553 D . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11, 216 K1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 432–433, 439–441 K1hydroxyquinone . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 432
W Warfarin . . . . . . . . . . . . . . . . . . . . . . . . . . . . 432–433, 439, 441 Water-soluble toxins . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 512 Well-stirred model . . . . . . . . . . . . . . . . . . . . . . . . 349–350, 352 Western blot . . . . . . . . . . . 44–45, 49–50, 128, 143, 145–153, 253, 263, 320, 331–332, 335–336, 341–346, 499, 503–504 White adipose tissue. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .215 blood cells . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 173–174 WIF-B9 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 417 Wilson disease . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 481 Wnt antagonist . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 161, 164 signaling . . . . . . . . . . . . . . . . . . . . . 161–162, 164, 209–210 Wnt/β-catenin signaling pathway . . . . . . . . . . . . . . . . . . . . 187
X Xbp1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 210 Xenobiotic biotransformation . . . . . . . . . . . . . . . . . . . . . 129, 282, 391 elimination . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 58, 391, 505 inducers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 129 inducing agents . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 129 induction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 129 metabolism . . . . . . . 4–5, 14–23, 116, 266, 282, 491–492 metabolizing CYPs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 129 response elements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 218 responsiveness. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .14, 79 substances . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 129 Xenobiotic responsive element (XRE) . . . . . . . . 22, 218, 319 Xenogenic cells . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 513 hepatocytes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 513 Xenograft . . . . . . . . . . . . . . . . . . . . . . . . . . . 493, 495, 497, 506 Xenotransplantation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 486 Xenotransplanted hepatocytes . . . . . . . . . . . . . . . . . . . . . . . 477 X-irradiation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 481–482
Y Y chromosome . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 174, 197 Young donor livers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 497
Z Zebrafish . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 161, 187 Zidovudine . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 310–311 ZO1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 265 Zonation pattern . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 164 Zoonosis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 512–513