Cystic Fibrosis: Diagnosis and Protocols, Volume II: Methods and Resources to Understand Cystic Fibrosis (Methods in Molecular Biology 742)

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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

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Cystic Fibrosis Diagnosis and Protocols, Volume II: Methods and Resources to Understand Cystic Fibrosis

Edited by

Margarida D. Amaral Centre for Biodiversity and Functional and Integrative Genomics, Faculty of Sciences, University of Lisboa, Lisboa, Portugal

Karl Kunzelmann Department of Physiology, University of Regensburg, Regensburg, Germany

Editors Margarida D. Amaral Centre for Biodiversity & Functional and Integrative Genomics University of Lisboa Lisboa 1749-016, Portugal [email protected]

Karl Kunzelmann Department of Physiology University of Regensburg Regensburg 93053, Germany [email protected]

ISSN 1064-3745 e-ISSN 1940-6029 ISBN 978-1-61779-119-2 e-ISBN 978-1-61779-120-8 DOI 10.1007/978-1-61779-120-8 Springer New York Dordrecht Heidelberg London Library of Congress Control Number: 2011925926 © Springer Science+Business Media, LLC 2011 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. Printed on acid-free paper Humana Press is part of Springer Science+Business Media (www.springer.com)

Foreword This book represents a milestone in the worldwide cystic fibrosis (CF) community’s efforts to continue to pave the way toward the development of new and innovative therapies that address the basic defect in CF. But no book on this subject would be possible without the invaluable contributions of the many patients, families, and disease-related organizations that played a key role in creating the science outlined in these chapters. As an orphan disease, CF does not receive sufficient funding from traditional supporting agencies but depends instead on a vast network of people who selflessly give their time and energy to raise the dollars to support the research that will lead to new treatments and a cure. Much of the science described in the pages that follow is the result of funds raised by the CF community, as well as the willingness of patients to provide tissue specimens, share their data in patient registries, and participate in clinical studies. These contributions have been critical to the success that CF research is experiencing worldwide. The global cystic fibrosis community is clearly unique and has often been described as a “culture of research.” Shared among the many patient groups that represent about 70,000 people with CF worldwide is the belief that we will ultimately cure this disease through research. The constancy of this shared mission to cure CF by focusing on research is part of what sets the CF community apart from other rare diseases. The clear promise of small molecules and the excitement over gene therapy have kindled a sense of optimism that is critical to sustaining the momentum toward finding a cure. In addition to the consistent focus on research, there are a number of other unique traits that the CF community around the world possesses that make it one of a kind. Some of the distinguishing qualities include the following: • Willingness to share: Because of the insidious nature of CF, there is a rare sense of cooperative spirit among scientists, physicians, caregivers, patients, and families all over the world who are dedicated to a cure. CF research data know no borders, and waiting until data are published is not part of the CF research culture. The advancement of science is an open book, and the rapid exchange of new ideas and approaches is a mainstay of CF conferences and workshops in North America and overseas. • Willingness to take risks: The search for the gene in the 1980s is an example of the risks and rewards of the pioneering work of the global CF populace. In the early 1980s, CF communities began to collect blood and tissue samples from families with multiplyaffected individuals with CF. With newly evolved technologies (such as chromosome jumping), which could be quickly applied to these samples, and the rapid exchange of information, numerous efforts to find the gene were launched. The discovery of the CF gene in 1989 was the result of an intricate and highly successful international collaboration and is hailed today as one of the major milestones in modern medical research. Because of the involvement of CF families, patients, and the US Cystic Fibrosis Foundation, this groundbreaking discovery occurred over 14 years prior to the publication of the human genome. Importantly, it gave scientists an opportunity to explore the relationship of the genetic defect with the pathogenesis associated with CF. This discovery was a prelude to the effort to move from a knowledge acquisition

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Foreword mode of research to the current CF research efforts, whereby scientists are using acquired knowledge about CF to develop new approaches to treat the disease.

• Willingness to take responsibility for its own destiny: Because there are only 70,000 CF patients throughout the world, there has been reluctance in the biopharmaceutical arena to enter the field of CF. Without their involvement, the ability to develop novel therapeutics is limited. In the late 1990s, frustrated by this fact, the US CF Foundation dramatically changed its business model and created a program to reduce risk of industry involvement in CF research by providing early funding and access to scientific and clinical expertise. This successful array of alliances with industry has led to an exciting clinical pipeline of products, including small molecules that are now being tested in centers worldwide, any of which could have a profound impact on individuals with CF. Similarly, upon realizing industry’s dwindling interest in gene therapy for CF, the British Trust launched a Gene Therapy Consortium that has painstakingly worked through some of the critical issues and problems associated with applying this pioneering mode of therapy for CF. As a result, and with a significant financial investment by the British Trust, the most comprehensive gene therapy clinical trial process is underway in the British Isles. More recently, clinical trial networks have been established throughout North America and Europe to facilitate the evaluation of new clinical entities in order to hasten the regulatory process leading to drug approval. These clinical trial networks are linked through the sharing of data, expertise, and experience to contribute to the worldwide clinical trial efforts. These are just a few examples of the willingness of the CF community to make strategic investments, some of which, in the case of other diseases, would be taken by industry or the government to bring us closer to accomplishing our mission. • Willingness to accept responsibility for the coordinating role in the areas of care, teaching, and research: In many countries, scientists and clinicians look to the government for funding – agencies like the US National Institutes of Health and other equivalent organizations. However, not only is the science of CF frequently funded by CF organizations, but its direction is often defined by these entities as well. Similarly, the outstanding care that is provided all over the world is driven by the standards and guidelines set by these universal CF organizations. These guidelines are commonly established in international forums sponsored by CF groups. Once again, the community looks to CF organizations for leadership. These volumes are the result of a distinct and worldwide undertaking. The environment, funding, and culture that have been put in place by patient organizations, coupled with the ability to bring the best minds to the field of CF, have made the science described in this book possible. This publication will be a useful tool as we continue to translate the knowledge acquired during decades of basic research to the development of new therapies that will modify and change the course of the disease in CF patients in the years ahead. Cystic Fibrosis: Diagnosis and Protocols is the fulfillment of decades of hard work by the volunteers and staff of the patient groups and organizations that have helped to pave the way toward our ultimate goal: a cure and control for cystic fibrosis. Bethesda, MD, USA

Robert J. Beall

Preface More than 20 years have passed since the identification of the gene responsible for cystic fibrosis (CF) and undoubtedly many milestones have highlighted this area of research. But we have to admit it, progress towards finding a way of curing the disease has been slower than we initially expected and wished. Apparently, this is not due to a lack of research efforts in the field, since in recent years, the CF research community has been producing on average ∼1,500 papers annually. So, probably we still need to dig deeper and with better tools to understand further the basic biological mechanisms underlying this complex disease. Nevertheless, it is increasingly difficult to grasp and use the already wide and still growing range of diverse methods currently employed to study CF so as to understand it in its multidisciplinary nature. The aim of these Cystic Fibrosis: Diagnosis and Protocols volumes is thus to provide the CF research community (and that in related fields) with a very wide range of high-quality experimental tools, as an easy way to grasp and use classical and novel methods applied to CF. Hence, it is expected that it will contribute to accelerate the advancement of knowledge in this area. The purpose is thus to offer selected “good practice protocols” with a level of technical detail which is rarely published in peer-reviewed journals. Moreover, it is expected that this information will also enable researchers to identify subtle differences regarding techniques in their own laboratories, which often account for apparently “contradictory” data in the literature. Co-authorship from both sides of the Atlantic was particularly encouraged. In the 2002 edition of this volume and in another previous comprehensive compilation of Methods for Cystic Fibrosis and CFTR Research,1 a large set of classical techniques used for CF research were already covered. So, here the focus is placed on innovative methodologies (some revolutionizing our way of doing science) by describing in detail how to perform and exploit these emergent techniques applied to CF. Moreover, a complete section has been devoted to available resources such as useful software and databases, as well as cell lines and animal models, reviewed for their usefulness towards multiple purposes. Notwithstanding, the more “classical” methods can also undergo improvements and thus their most up-to-date and revised versions are also recapped here by the leading experts. All book sections are introduced by an overview discussing the applicability and practicality of the protocols with examples. It is hoped that the methods presented and revised here will provide users with optimal working tools to address their pressing questions in the best technical way while helping

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Journal of Cystic Fibrosis (2004), volume 3 (Supplement 2), a special issue focused on “Methods for Cystic Fibrosis and CFTR Research” and The online “Virtual Repository of the Cystic Fibrosis European Network” at: http://central.igc.gulbenkian.pt/cftr/vr/index.htm

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all of us, as a research and clinical community, to move faster hand-in-hand towards unravelling the secrets of this (and possibly other) challenging disorder(s) and cure it. Finally, we wish to thank all authors for their enthusiasm in joining us in this project by contributing with their best protocols to this book and also for their patience with our multiple requests. Special thanks to Renata Vincent for her help in dealing with the manuscripts. Moreover, we would like to express our gratitude to the whole CF community in general, researchers, clinicians and all caregivers and other professionals, not forgetting CF patients and their families, for their continuous efforts towards finding a way out of this still devastating disease. We believe that we will be there soon and we hope this book somehow contributes to getting there sooner. Then, when our goals are met, all efforts will have been worthwhile, or as the Portuguese poet Fernando Pessoa has put it, “All is worthwhile if the soul is not small”. Lisboa, Portugal Regensburg, Germany

Margarida D. Amaral Karl Kunzelman

Contents Foreword . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Preface . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Contributors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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SECTION I: 1.

PATHOPHYSIOLOGY OF CYSTIC FIBROSIS

Introduction to Section I: Overview of Approaches to Study Cystic Fibrosis Pathophysiology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Mark T. Clunes and Richard C. Boucher

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Imaging CFTR Protein Localization in Cultured Cells and Tissues . . . . . . . . Silvia M. Kreda and Martina Gentzsch

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CFTR Regulation of Epithelial Sodium Channel . . . . . . . . . . . . . . . . . . Yawar J. Qadri, Estelle Cormet-Boyaka, Dale J. Benos, and Bakhrom K. Berdiev

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Methods for Evaluating Inflammation in Cystic Fibrosis . . . . . . . . . . . . . . Assem G. Ziady and Pamela B. Davis

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Methods for ASL Measurements and Mucus Transport Rates in Cell Cultures . . . Erin N. Worthington and Robert Tarran

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Measurement of Fluid Secretion from Intact Airway Submucosal Glands . . . . . Jeffrey J. Wine, Nam Soo Joo, Jae Young Choi, Hyung-Ju Cho, Mauri E. Krouse, Jin V. Wu, Monal Khansaheb, Toshiya Irokawa, Juan Ianowski, John W. Hanrahan, Alan W. Cuthbert, and Kim V. Tran

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Measurements of Intracellular Calcium Signals in Polarized Primary Cultures of Normal and Cystic Fibrosis Human Airway Epithelia . . . . . . . . . 113 Carla M.P. Ribeiro

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Identification and Quantification of Mucin Expression . . . . . . . . . . . . . . . 127 Kristina A. Thomsson and Gunnar C. Hansson

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Methods to Classify Bacterial Pathogens in Cystic Fibrosis . . . . . . . . . . . . . 143 Thomas Bjarnsholt, Xiaohui Chen Nielsen, Ulla Johansen, Lena Nørgaard, and Niels Høiby

10. Approaches to Study Differentiation and Repair of Human Airway Epithelial Cells . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 173 Sophie Crespin, Marc Bacchetta, Song Huang, Tecla Dudez, Ludovic Wiszniewski, and Marc Chanson

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SECTION II: OMIC APPROACHES TO STUDY CYSTIC FIBROSIS 11. Introduction to Section II: Omics in the Biology of Cystic Fibrosis . . . . . . . . 189 William E. Balch 12. Microarray mRNA Expression Profiling to Study Cystic Fibrosis . . . . . . . . . . 193 Shyam Ramachandran, Luka A. Clarke, Todd E. Scheetz, Margarida D. Amaral, and Paul B. McCray Jr. 13. Quantitative Differential Proteomics of Cystic Fibrosis Cell Models by SILAC (Stable Isotope Labelling in Cell Culture) . . . . . . . . . . . . . . . . 213 Ida Chiara Guerrera, Mario Ollero, Diane-Lore Vieu, and Aleksander Edelman 14. Application of Mass Spectrometry to Study Proteomics and Interactomics in Cystic Fibrosis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 227 William E. Balch and John R. Yates III 15. Functional Genomics Assays to Study CFTR Traffic and ENaC Function . . . . . 249 Joana Almaça, Shehrazade Dahimène, Nicole Appel, Christian Conrad, Karl Kunzelmann, Rainer Pepperkok, and Margarida D. Amaral 16. New Lipidomic Approaches in Cystic Fibrosis . . . . . . . . . . . . . . . . . . . 265 Mario Ollero, Ida Chiara Guerrera, Giuseppe Astarita, Daniele Piomelli, and Aleksander Edelman SECTION III: RESOURCES 17. Introduction to Section III: Resources for CFTR Research . . . . . . . . . . . . 281 Margarida D. Amaral 18. Primary Epithelial Cell Models for Cystic Fibrosis Research . . . . . . . . . . . . 285 Scott H. Randell, M. Leslie Fulcher, Wanda O’Neal, and John C. Olsen 19. Comparative Biology of Cystic Fibrosis Animal Models . . . . . . . . . . . . . . 311 John T. Fisher, Yulong Zhang, and John F. Engelhardt 20. CFTR Folding Consortium: Methods Available for Studies of CFTR Folding and Correction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 335 Kathryn W. Peters, Tsukasa Okiyoneda, William E. Balch, Ineke Braakman, Jeffrey L. Brodsky, William B. Guggino, Christopher M. Penland, Harvey B. Pollard, Eric J. Sorscher, William R. Skach, Philip J. Thomas, Gergely L. Lukacs, and Raymond A. Frizzell 21. Evaluation of the Disease Liability of CFTR Variants . . . . . . . . . . . . . . . . 355 Patrick R. Sosnay, Carlo Castellani, Mary Corey, Ruslan Dorfman, Julian Zielenski, Rachel Karchin, Christopher M. Penland, and Garry R. Cutting Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 373

Contributors JOANA ALMAÇA • Faculty of Sciences, BioFiG-Centre for Biodiversity and Functional and Integrative Genomics, University of Lisboa, Lisboa, Portugal; Department of Genetics, Centre of Human Genetics, National Institute of Health, Lisboa, Portugal MARGARIDA D. AMARAL • Faculty of Sciences, BioFiG-Centre for Biodiversity, Functional and Integrative Genomics, University of Lisboa, Lisboa, Portugal; Department of Genetics, Centre of Human Genetics, National Institute of Health, Lisboa, Portugal; EMBL-European Molecular Biology Laboratory, Heidelberg, Germany NICOLE APPEL • EMBL-European Molecular Biology Laboratory, Heidelberg, Germany GIUSEPPE ASTARITA • Drug Discovery and Development Unit, Italian Institute of Technology, Genoa, Italy; Department of Pharmacology, University of California, Irvine, CA, USA MARC BACCHETTA • Laboratory of Clinical Investigation III, Faculty of Medicine, Department of Pediatrics, Geneva University Hospitals and University of Geneva, Foundation for Medical Research, Geneva, Switzerland WILLIAM E. BALCH • Departments of Cell Biology, Molecular Biology and Chemical Physiology, The Skaggs Institute for Chemical Biology and the Institute for Childhood and Neglected Disease, The Scripps Research Institute, La Jolla, CA, USA; The Institute for Childhood and Neglected Disease, The Scripps Research Institute, La Jolla, CA, USA DALE J. BENOS • Physiology and Biophysics, University of Alabama at Birmingham, Birmingham, AL, USA BAKHROM K. BERDIEV • Department of Cell Biology and Gregory Fleming James Cystic Fibrosis Research Center, University of Alabama at Birmingham, Birmingham, AL, USA THOMAS BJARNSHOLT • Department of Clinical Microbiology, University of Copenhagen, Copenhagen, DenmarkDanish CF Centre, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark RICHARD C. BOUCHER • Cystic Fibrosis/Pulmonary Research and Treatment Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA INEKE BRAAKMAN • Cellular Protein Chemistry, Utrecht University, Utrecht, The Netherlands JEFFREY L. BRODSKY • Department of Biological Sciences, University of Pittsburgh, Pittsburgh, PA, USA CARLO CASTELLANI • Cystic Fibrosis Centre, Ospedale Civile Maggiore, Verona, Italy MARC CHANSON • Laboratory of Clinical Investigation III, Faculty of Medicine, Department of Pediatrics, Geneva University Hospitals and University of Geneva, Foundation for Medical Research, Geneva, Switzerland HYUNG-JU CHO • Cystic Fibrosis Research Laboratory, Stanford University, Stanford, CA, USA JAE YOUNG CHOI • Cystic Fibrosis Research Laboratory, Stanford University, Stanford, CA, USA; Department of Otorhinolaryngology, Yonsei University, Seoul, Korea

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LUKA A. CLARKE • Faculty of Sciences, BioFIG-Centre for Biodiversity, Functional and Integrative Genomics, University of Lisboa, Lisbon, Portugal MARK T. CLUNES • Department of Physiology and Neuroscience, St. George’s University, True Blue Campus, Grenada, West Indies CHRISTIAN CONRAD • EMBL-European Molecular Biology Laboratory, Heidelberg, Germany MARY COREY • The Hospital for Sick Children, University of Toronto, Toronto, ON, Canada ESTELLE CORMET-BOYAKA • Division of Pulmonary, Critical Care, and Sleep Medicine, Davis Heart and Lung Research Institute, The Ohio State University, Columbus, OH, USA SOPHIE CRESPIN • Laboratory of Clinical Investigation III, Faculty of Medicine, Department of Pediatrics, Geneva University Hospitals, and University of Geneva, Foundation for Medical Research, Geneva, Switzerland ALAN W. CUTHBERT • Department of Medicine, University of Cambridge, Addenbrooke’s Hospital, Cambridge, UK GARRY R. CUTTING • McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA SHEHRAZADE DAHIMÈNE • Faculty of Sciences, BioFiG-Centre for Biodiversity and Functional and Integrative Genomics, University of Lisboa, Lisboa, Portugal PAMELA B. DAVIS • Department of Pediatrics, Case Western Reserve University, Cleveland, OH, USA RUSLAN DORFMAN • The Hospital for Sick Children, University of Toronto, Toronto, ON, Canada TECLA DUDEZ • Laboratory of Clinical Investigation III, Faculty of Medicine, Department of Pediatrics, Geneva University Hospitals and University of Geneva, Foundation for Medical Research, Geneva, Switzerland ALEKSANDER EDELMAN • INSERM U845, Université Paris Descartes, Paris, France JOHN F. ENGELHARDT • Department of Anatomy and Cell Biology, Carver College of Medicine, University of Iowa, Iowa City, IA, USA; Department of Internal Medicine, Carver College of Medicine, University of Iowa, Iowa City, IA, USA; Center for Gene Therapy, Carver College of Medicine, University of Iowa, Iowa City, IA, USA JOHN T. FISHER • Department of Anatomy and Cell Biology, Carver College of Medicine, University of Iowa, Iowa City, IA, USA RAYMOND A. FRIZZELL • Department of Cell Biology and Physiology, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA M. LESLIE FULCHER • Cystic Fibrosis/Pulmonary Research and Treatment Center, The University of North Carolina at Chapel Hill, Chapel Hill, NC, USA MARTINA GENTZSCH • Cystic Fibrosis/Pulmonary Research and Treatment Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA; Department of Cell and Developmental Biology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA IDA CHIARA GUERRERA • Plateau Protéomes, IFR94, Université Paris Descartes, Paris, France; INSERM U845, Université Paris Descartes, Paris, France WILLIAM B. GUGGINO • Department of Physiology, Johns Hopkins University, Baltimore, MD, USA JOHN W. HANRAHAN • Department of Physiology, McGill University, Montreal, QC, Canada

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GUNNAR C. HANSSON • Department of Medical Biochemistry, University of Gothenburg, Gothenburg, Sweden NIELS HØIBY • Department of Clinical Microbiology, University of Copenhagen, Copenhagen, Denmark; Danish CF Centre, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark; Institute of International Health, Immunology and Microbiology, University of Copenhagen, Copenhagen, Denmark SONG HUANG • Epithelix, SàRL, Plan-les-Ouates, Switzerland JUAN IANOWSKI • Department of Physiology, University of Saskatchewan, Saskatoon, SK, Canada TOSHIYA IROKAWA • Health Administration Center, Tohoku University, Sendai, Japan ULLA JOHANSEN • Department of Clinical Microbiology, University of Copenhagen, Copenhagen, Denmark NAM SOO JOO • Cystic Fibrosis Research Laboratory, Stanford University, Stanford, CA, USA RACHEL KARCHIN • Department of Biomedical Engineering, Institute for Computational Medicine, Johns Hopkins University, Baltimore, MD, USA MONAL KHANSAHEB • Cystic Fibrosis Research Laboratory, Stanford University, Stanford, CA, USA SILVIA M. KREDA • Cystic Fibrosis/Pulmonary Research and Treatment Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA MAURI E. KROUSE • Cystic Fibrosis Research Laboratory, Stanford University, Stanford, CA, USA KARL KUNZELMANN • Department of Physiology, University of Regensburg, Regensburg, Germany GERGELY L. LUKACS • Department of Physiology, McGill University, Montreal, QC, Canada PAUL B. MCCRAY JR • Interdisciplinary Program in Genetics, Department of Pediatrics, University of Iowa, Iowa City, IA, USA XIAOHUI CHEN NIELSEN • Department of Clinical Microbiology, University of Copenhagen, Copenhagen, Denmark LENA NØRGAARD • Department of Clinical Microbiology, University of Copenhagen, Copenhagen, Denmark TSUKASA OKIYONEDA • Department of Physiology, McGill University, Montreal, QC, Canada MARIO OLLERO • INSERM U845, Université Paris Descartes, Paris, France JOHN C. OLSEN • Cystic Fibrosis/Pulmonary Research and Treatment Center, The University of North Carolina at Chapel Hill, Chapel Hill, NC, USA WANDA O’NEAL • Cystic Fibrosis/Pulmonary Research and Treatment Center, The University of North Carolina at Chapel Hill, Chapel Hill, NC, USA CHRISTOPHER M. PENLAND • Cystic Fibrosis Foundation, Bethesda, MD, USA RAINER PEPPERKOK • EMBL-European Molecular Biology Laboratory, Heidelberg, Germany KATHRYN W. PETERS • Department of Cell Biology and Physiology, University of Pittsburgh, Pittsburgh, PA, USA DANIELE PIOMELLI • Drug Discovery and Development Unit, Italian Institute of Technology, Genoa, Italy; Department of Pharmacology, University of California, Irvine, CA, USA

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HARVEY B. POLLARD • Department of Anatomy, Physiology, and Genetics, Uniformed Services University of the Health Sciences, Bethesda, MD, USA YAWAR J. QADRI • Medical Scientist Training Program, University of Alabama at Birmingham, Birmingham, AL, USA SHYAM RAMACHANDRAN • Interdisciplinary Program in Genetics, Department of Pediatrics, University of Iowa, Iowa City, IA, USA SCOTT H. RANDELL • Cystic Fibrosis/Pulmonary Research and Treatment Center, The University of North Carolina at Chapel Hill, Chapel Hill, NC, USA CARLA M.P. RIBEIRO • Department of Medicine, Cystic Fibrosis/Pulmonary Research and Treatment Center, The University of North Carolina, Chapel Hill, NC, USA TODD E. SCHEETZ • Department of Ophthalmology and Visual Sciences, Interdisciplinary Program in Genetics, University of Iowa, Iowa City, IA, USA WILLIAM R. SKACH • Department of Biochemistry and Molecular Biology, Oregon Health & Science University, Portland, OR, USA ERIC J. SORSCHER • Gregory Fleming James Cystic Fibrosis Research Center, University of Alabama at Birmingham, Birmingham, AL, USA PATRICK R. SOSNAY • McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA ROBERT TARRAN • Cystic Fibrosis/Pulmonary Research and Treatment Center, The University of North Carolina, Chapel Hill, NC, USA PHILIP J. THOMAS • Department of Physiology, University of Texas Southwestern Medical Center, Dallas, TX, USA KRISTINA A. THOMSSON • Department of Medical Biochemistry, University of Gothenburg, Gothenburg, Sweden KIM V. TRAN • Cystic Fibrosis Research Laboratory, Stanford University, Stanford, CA, USA DIANE-LORE VIEU • INSERM U845, Université Paris Descartes, Paris, France JEFFREY J. WINE • Cystic Fibrosis Research Laboratory, Stanford University, Stanford, CA, USA LUDOVIC WISZNIEWSKI • Epithelix, SàRL, Plan-les-Ouates, Switzerland ERIN N. WORTHINGTON • Cystic Fibrosis/Pulmonary Research and Treatment Center, The University of North Carolina, Chapel Hill, NC, USA JIN V. WU • Cystic Fibrosis Research Laboratory, Stanford University, Stanford, CA, USA JOHN R. YATES III • Department of Chemical Physiology, The Scripps Research Institute, La Jolla, CA, USA YULONG ZHANG • Department of Anatomy and Cell Biology, Carver College of Medicine, University of Iowa, Iowa City, IA, USA ASSEM G. ZIADY • Department of Pediatrics, Case Western Reserve University, Cleveland, OH, USA JULIAN ZIELENSKI • The Hospital for Sick Children, University of Toronto, Toronto, ON, Canada

Section I Pathophysiology of Cystic Fibrosis

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Chapter 1 Introduction to Section I: Overview of Approaches to Study Cystic Fibrosis Pathophysiology Mark T. Clunes and Richard C. Boucher Abstract Mutation of the CFTR chloride channel was identified as the genetic basis of cystic fibrosis over 20 years ago; however, correlation of the pathophysiological changes occurring in CF lung disease with the mutation of a chloride channel is ongoing. The failure of innate lung defense in CF, and the subsequent cyclical microbial colonization of airways, explains the gross anatomical changes that occur in CF pathophysiology. However, ongoing research is focused on how the lack of the CFTR channel explains the failure of innate lung defense. Hydration status of the mucus blanket is key to understanding this link, and this series of chapters details the recent progress that has been made in understanding the interplay between ion transport activity and innate lung defense, and the initiation of CF lung pathophysiology. Key words: Airway surface liquid, defective ion transport, dehydration, mucus layer, respiratory infection, water transport.

1. Introduction Identification of the link between the failure of innate airway defense and defective ion transport has been the goal of cystic fibrosis research since CFTR was identified as a chloride channel (1). Although this area of research has been a focal point for 20 years, identifying causal events linking the failure of ion transport to development of respiratory infection/inflammation has been more difficult than anticipated. However, from data emerging over the past decade, the simplest scenario to link abnormal CF ion transport to CF lung disease is that CF epithelia have (1) reduced chloride and water transport capability and (2) poorly M.D. Amaral, K. Kunzelmann (eds.), Cystic Fibrosis, Methods in Molecular Biology 742, DOI 10.1007/978-1-61779-120-8_1, © Springer Science+Business Media, LLC 2011

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regulated sodium absorption, both leading to dehydrated airway surfaces. Dehydration of the mucus layer results in very different rheological properties from normal, with mucus becoming thickened and adhesive and resistant to the flow that is usually sustained by ciliary action in the airways. Static, adherent mucus then harbors pathogens within the lumen of CF airways. Indeed, adherent mucus ultimately stimulates the development of biofilms that are difficult to treat with inhaled antibiotics due to the obstruction to airflow. In addition, thickened mucus, which is a dense polymer gel, forms an effective barrier to neutrophil infiltration, allowing bacteria to thrive in the glycoprotein-rich environment (2). Infection then becomes persistent, and repeated cycles of inflammation culminate in airway remodeling and the development of severe obstructive and restrictive lung disease. Figure 1.1 outlines the mucociliary clearance mechanisms in place in normal lung and the changes that occur in CF lung.

Fig. 1.1. Airway surface dehydration and the development of mucociliary stasis. The left panel shows the normal situation where the airway surface liquid is maintained by a balance between chloride secretion, through CFTR, and sodium absorption, through the epithelial sodium channel (ENaC). By changing the mass of solute on the apical surface, the osmotic gradient for water secretion or absorption can be controlled and the airway surface and mucus kept hydrated. Hydrated mucus flows to the proximal airways, propelled by ciliary action. Right panel shows that when the chloride secretory pathway is absent, as in CF, the mass of NaCl in the apical domain is reduced. This is because there is no tonically active chloride secretory pathway and because the absorptive pathway is potentiated in the absence of CFTR. The consequence of the lack of CFTR is that no osmotic gradient is generated for water secretion. The airway surface becomes dehydrated and the mucus inspissated and adhesive, resulting in ciliary collapse and mucociliary stasis. Within the static mucus, bacterial biofilms form; in addition the dense polymer network (mucus), with a reduced mesh size, hinders neutrophil infiltration. Infection thus becomes established and proves near impossible to eradicate.

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Effective disease management to date has focused on the amelioration of the symptoms of CF. Traditional therapies have focused on better nutrition and mechanical mechanisms that promote clearance of airway secretions, e.g., chest physiotherapy. Other therapies have centered on changing the rheological properties of mucus and controlling infection. The obstructive mucus plugs are the target of enzymes (e.g., DNase/RNase), reducing the viscoelastic properties of the DNA and promoting mucus clearance from the airways, either by ciliary action or by cough. In addition, aggressive antibiotic therapy, both parenteral and inhaled, has aimed to control existing infection and retard the development of further infection in “clear” areas of lung (3). More recently, therapies are being developed to treat the disease at more proximal steps in disease pathogenesis. For example, hypertonic saline delivered by nebulizer aims to rehydrate the mucus gel and restore clearance mechanisms (4, 5). Other therapies, e.g., denufosol, aim to re-direct salt transport from absorption to secretion, also hydrating airway surfaces. Further, as understanding of the molecular processes of CF pathophysiology have developed, whole new areas have opened up for targeted therapy. Therapies now aim to correct the basic defect in CF, namely defective CFTR processing and activation. 1.1. Localization of CFTR

The location of CFTR in the respiratory tree has been at the center of debate in CF physiology since initial studies, using polyclonal rabbit antibodies to CFTR, suggested that expression was dominant in the submucosal glands (6). This finding led to the conclusion that CF pathophysiology could be explained by submucosal gland dysfunction only. However, extrapolation of pathophysiological progression based on protein localization studies of epithelial channels traditionally has been difficult, as it is known that some channels, e.g., ENaC, are not abundantly expressed, nor detected immunohistochemically, despite robust physiological activity. So the question of how many channels are required to mediate significant physiological function remains unanswered. In addition, more recent studies, using sensitive mouse monoclonal antibodies with high-resolution laser confocal microscopy, have suggested that while submucosal glands can indeed express CFTR in the acinus, the ciliated duct is the predominant site of expression in the submucosal gland. Furthermore, the ciliated surface epithelial cells also routinely express CFTR both in the large and small airways (7). It seems, therefore, that CFTR is expressed and functional in both the proximal airway surface epithelium and the submucosal glands and that secretions from both sources may be defective in CF. In the small airways, where disease is initiated in CF, the ciliated cell selectively expresses CFTR.

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In Chapter 2, Silvia Kreda and Martina Gentzsch describe the latest methodologies used to immunohistologically visualize CFTR in human tissues and cultures, and in Chapter 6, Wine et al detail how intact whole submucosal glands can be prepared so that fluid secretion rates can be determined and their secretory regulation examined. Related to the issue of where CFTR is expressed is how CFTR is trafficked to the plasma membrane. Milder forms of CF pathophysiology are observed in which mutated CFTR channels are inserted into the membrane and allow some secretory function, e.g., R117H mutation (8). Yet, with F508, very little, if any, protein actually trafficks to the plasma membrane under normal circumstances. Under experimental low-temperature conditions, F508 CFTR can be trafficked to the membrane (9), and is known to have functional activity once in the membrane, albeit lesser than wild type (10). In addition, even when F508 CFTR is experimentally over-expressed in heterologous systems, its turnover in the plasma membrane is rapid, suggesting that some form of mechanism exists that recognizes mutated protein in the plasma membrane and responds by removing that protein (11). Understanding of how CFTR is trafficked to the membrane and the pathways that control and regulate this trafficking will undoubtedly provide a rich source of targets for pharmacological intervention. To this end, Martina Gentzsch and Jack Riordan have produced epitope-tagged forms of CFTR that can be easily traced throughout the lifetime of CFTR’s existence in the cell, from its formation in ER to its insertion into the membrane and subsequent turnover. This invaluable tool allows the natural history of F508 CFTR to be observed, and the importance of this tool is highlighted by research to discover “corrector” drugs that aim to deliver F508 protein to the membrane and potentiator drugs to stabilize and activate the protein once in the membrane. 1.2. Ion Transport and Airway Surface Liquid

The developmental aspects of ion transport in the CF fetal/neonatal lung are worth noting. CF is not widely regarded as a cause of intrauterine death. This is surprising, since lung development necessitates the secretion of fluid into the lung to generate the transmural pressure to stimulate lung growth (12). This fetal lung secretory process is apparently undisturbed in CF. For example, although problems that lead to a paucity of fluid in the fetal lung are recognized to produce small, underdeveloped lungs, e.g., oligohydramnios (13), this pathology is not generally a feature of CF. Although fetal CF genotyping is rare, only subtle changes in respiratory morphology have been reported in CF fetuses (14). In itself, this observation suggests that fetal CF lungs have the ability to secrete fluid, and that this secondary mechanism is not retained in the adult CF lung, or that mutated CFTR is handled very differently by the cell during embryonic development. An “alternative” chloride secretory pathway has

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been well defined as the P2Y2 receptor-mediated, calciumactivated chloride pathway [CaCC (15)] and is known to be active in the fetal (16) as well as the adult lung. Consequently, it is possible that CaCC, or as yet unrecognized Cl− channels, mediate fetal lung liquid secretion. Of note, the CaCC secretory pathway has been focused upon as a therapeutic target for the treatment of CF. These ionic conduction pathways are important, since transepithelial water flux is governed by the net rate of Na+ absorption vs. the net rate of Cl− secretion. It is the transepithelial secretion of chloride ions into the airway lumen that provides the electrical driving force (transepithelial potential difference) for Na+ to follow. Thus, NaCl is secreted onto the airway surface and provides an osmotic driving force for water transport. Two major routes for chloride secretion are utilized by the postnatal airway (1): the cystic fibrosis transmembrane conductance regulator (CFTR) and (2) the calcium-activated chloride conductance (CaCC). Although the dominant baseline secretory activity present in airway epithelial cells is the PKA-regulated CFTR Cl− channel, the loss of which results in dehydrated airways and CF lung disease, the CaCC pathway remains intact in CF and represents a second route for chloride secretion that can also be stimulated via a number of mechanisms. Salt and water absorption on the other hand is achieved solely by the activity of the apically located Na+ channel ENaC. The electrogenic transepithelial transport of Na+ from the apical surface liquid into the basolateral space provides the electrical driving force for paracellular anion transport; thus, NaCl is transported from the airway surface liquid to the basolateral interstitial space. The generated osmotic gradient produces transepithelial water absorption. Thus, fluid transport, and hence airway surface volume, is determined by the ratio of basolateral-to-apical Cl− secretion to apical-to-basolateral Na+ absorption. 1.3. Ion Transport In Vivo/In Vitro

The bioelectric properties of airway epithelia have been hard to assess in vivo because of the complex three-dimensional architecture of the respiratory tree. Perhaps one of the easiest in vivo measurements, and one that has now become diagnostic for CF, is the measurement of the airway transepithelial electric potential difference (PD) (17). The CF nasal epithelium exhibits a very high basal potential difference that is largely amiloride sensitive, indicating that the basal bioelectric properties are dominated by sodium hyperabsorption (18). Nasal PD measurements are a wonderful tool to study ion channel function in vivo. However, the nasal epithelium is not necessarily fully representative of the transport processes occurring deeper in the respiratory tree, particularly at the bronchiolar level where CF disease begins. In vivo PD measurements in the small airways would be exceedingly difficult, but the development of human-cultured bronchial epithelial cells

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has allowed the assessment of bioelectric and fluid handling properties of airway cells from all regions of the respiratory tree in a culture system. Human bronchial epithelial cells have been successfully cultured and their bioelectric properties studied in Ussing chambers for many years. However, it is the constant requirement for human tissue that limits this approach. Refinement of the culture methods so that cells more closely resemble native human tissue and extension of the useful life of cultured cells has been a priority in this field. Sophie Crespin et al (Chapter 10) examine the markers for well-differentiated human airway epithelial cells and discusses how cells can be maintained and studied in long-term culture (19). 1.4. Fluid Transport

The development of bronchial epithelial cell cultures has also been instrumental in gaining insight into the regulation of airway surface liquid volume. Use of large molecular weight fluorescent dyes (e.g., dextran-conjugated Texas Red) that are cell impermeable allows the airway surface liquid depth to be monitored using Z stack confocal microscopy. The advantage of this methodology is that liquid height can be resolved down to the micrometer range and, thus, ASL height can be monitored over time in live cultures. The permeable supports on which cultures are grown allow the epithelium to polarize and independent pharmacological manipulation of basolateral or apical domains is possible. This methodology has been used extensively to assess the function of both CFTR-mediated fluid secretion and CaCC-mediated fluid secretion in CF cultures. Robert Tarran and Erin Worthington (Chapter 5) discuss the latest developments in the assessment of airway surface liquid volumes using this technique.

1.5. Fluid and Mucus

Traditionally it had been thought that the mucus floated on the periciliary layer of fluid termed sol. In consequence, it was assumed that as the fluid depth diminished, the mucus would compress the cilia and retard their action, and indeed this is true [for review, see (20)]. It was also assumed that too much fluid would allow the mucin to lift away from the ciliary tips and that mucociliary transport would suffer due to a loss of traction by the cilia on the mucus blanket. Indeed, this may not be true. Mucus is a polymer gel; some mucins are tethered to the epithelial surface, while others are truly secreted into the luminal space; the hydration state of the mucus is critical for innate defense. However, it is now known that the polymer gel can swell and accommodate “extra” airway surface liquid, giving the gel a looser formation and actually increasing mucociliary transport rates (21). It is a paucity of fluid and the development of viscous, adherent mucus that precipitate CF pathophysiology. Günthar Hansson and Kristina Thomsson (Chapter 8) examine the latest proteomic

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methods used to identify the various mucins present in mucus and how these mucins can be adequately quantified (22). This is an essential step for CF pathobiology so that we can understand the exact solvent requirements for effective mucociliary clearance. 1.6. Mechanical Sensitivity – The CaCC Pathway

The lung is a dynamic organ, and both airways and alveoli are stretched during the respiratory cycle. The mechanical stimulation of airway cells, either by physical deformation or by flowinduced shear stress across the cells, results in the release of ATP [review (23)] and possibly other ATP/UTP metabolites into the lumen. ATP concentrations rise in the airway surface liquid with mechanical stimulation, along with the concentration of ATP metabolites such as ADP, AMP, and adenosine, generated by ecto-enzymes on the airway surface (24). ATP, an agonist of apical P2Y2 receptors, increases free intracellular calcium ([Ca2+ ]i ), leading to activation of CaCC and net transport of NaCl into the airway surface liquid, providing the osmotic force for water transport. In part, this mechanism explains why mechanical stimulation of the lungs results in “bursts” of secretion. Indeed, many mechanical “stimulants” are used in CF therapy, including airway clearance techniques, and percussion, either manually or with a mechanical “vest,” to assist airway mucus clearance. [Ca2+ ]i , in addition to activating CaCC, is an important modulator of mucin secretion and ciliary beat frequency and exhibits adaptation to inflammatory responses. [Ca2+ ]i , then, is important in the regulation of innate defense, and in the early 1990s, CF researchers took advantage of the newly developed tools for monitoring [Ca2+ ]i that had been developed by Roger Tsien (25). In Chapter 7, Carla Ribeiro examines these techniques and focuses on how the unique problems that airway researchers faced in [Ca2+ ]i measurements were overcome. [Ca2+ ]i was initially measured in dissociated cells that were grown or attached to a glass substrate. In this way, cells were easier to load with fluorescent dye (because they were rounded up), and they were positioned on a substrate with the right optical qualities to allow shortwavelength excitation light to reach the dye. This approach was suboptimal for airway research, since airway cells exhibit a polarized nature in which the basolateral and apical spaces are distinct. Long working distance fluorescent lenses, coupled with the use of dyes with a high quantum yield, like fura-2, allowed studies of polarized epithelia. Thus, airway cells could be grown on permeable supports as a sheet of epithelial cells and the basolateral and apical spaces could be independently accessed experimentally. This advance was important, since pharmacological interventions were shown to be able to selectively target the apical domain vs. the basolateral domain in isolation, and we now know that the resident receptor populations differ significantly between these domains (26) as well as calcium handling (27).

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1.7. Pathway Interaction – CaCC, CFTR, and ENaC

An increase in intracellular cAMP levels leads to an increase in CFTR activity and produces chloride and fluid secretion. To maximize this secretion, it is now clear that CFTR directly regulates the activity of ENaC and switches off absorption during activation of its secretory activity. In CF epithelia, this lack of antagonism of ENaC by CFTR is responsible for the hyperabsorption observed in CF airways. Early work with the patch clamp technique demonstrated this antagonistic nature between CFTR function and ENaC function (28) and suggested that proximity of the channels to one another was significant, since the area included in a single patch is less than 1 μm in diameter. This study suggested association between the channels, and later studies using FRET (Fluorescent Resonant Energy Transfer) have confirmed this close association between CFTR and ENaC. FRET studies require the expression of tagged CFTR and ENaC. For example, CFTR is tagged with ECFP (enhanced cyan fluorescent protein), while ENaC is tagged with EYFP (enhanced yellow fluorescent protein). Short-wavelength excitation of ECFP results in fluorescent emission of a longer wavelength that is suitable for excitation of EYFP and the resulting longer wavelength fluorescence of EYFP can then be measured. Very close association between the fluorescent molecules is required (<10 nm) for efficient energy transfer, and thus, close association of the proteins is required for a meaningful FRET signal. In this way, ENaC and CFTR were shown to have suitable proximity for direct interaction (29). Yawar Qadri et al (Chapter 3) discuss the latest methodologies that assess the interaction between CFTR and ENaC and the important functional consequences. It is also interesting to note that secretory absorptive antagonisms also exist in the CaCC- and ENaC-regulated pathways. Unlike the direct protein–protein interaction of CFTR and ENaC, this coordinated regulation is thought to be pathway dependent. P2Y2 receptor stimulation activates CaCC by increasing free intracellular calcium while inhibiting the absorptive ENaC-mediated pathway, likely by inner leaflet PIP2 hydrolysis (30) and/or by PKC (31). P2Y2 receptors, therefore, also represent a target to inhibit absorption and stimulate transient fluid secretion simultaneously.

1.8. The Inflammatory Response – Innate or Acquired

In CF it is clear that bacterial species such as Pseudomonas aeruginosa and Staphylococcus aureus can become permanent residents of the CF airway lumen, forming biofilms that are not easily treated, even by aggressive antimicrobial therapies [for review, see (32)]. Burkholderia cepacia is generally acquired later and clinically is of concern because of an associated necrotizing pneumonia and sepsis. The question remains as to what comes first, infection or inflammation?

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While it is clear that an inflammatory response would be initiated by infection, it is possible that CF epithelium is in some way compromised before infection begins. Recent work on β-ENaCoverexpressing mice has demonstrated that dehydrated airways produced by sodium hyperabsorption exhibit a phenotype that is not dissimilar to CF, i.e., chronic bronchitis and obstructive lung disease. The development of severe mucus plugging, neutrophilic infiltration, macrophage activation, and inflammatory cytokine elevation was all evident in the first 3 weeks of age in these mice, despite the fact that no bacterial colonization was evident (33, 34). Furthermore, necrotic cell death and hypoxemia were even earlier events, suggesting that pathogenesis progresses long before bacterial colonization. This issue is obviously important, since it suggests that CF therapies to keep airways hydrated should be started before infection is manifest in patients. The multiple animal models now available, most recently the CF pig, will allow thorough examination of these issues (35). In Chapter 4, Assem Ziady and Pam Davis examine the issues of inflammation in CF, with particular reference to the animal and cell models currently available, and the markers that can be used to assess the effectiveness of therapy. Traditionally, although S. aureus and P. aeruginosa are documented as the most prevalent microorganisms in infected CF airways, it is clear that other pathogens have an important role to play. B. cepacia is found in a number of CF patients (32), as is Haemophilus influenzae, Achromobacter xylosoxidans, and Stenotrophomonas maltophilia. The traditional methodologies used to determine which pathogens are present in CF sputum are inherently limited by the culture conditions chosen, and in recent years, more sophisticated methodologies involving 16sRNA, mass spectrometry (MALDITOF), and phenotypic microarray (BioLog) have broadened the potential microfauna basis for CF lung disease. Indeed, many of these more sensitive methodologies have identified possible pathogens that may be less abundant in CF lung, but that may nevertheless play an important role in the rate of CF pathogenesis. Thomas Bjarnsholt et al (Chapter 9) discuss the development of CF biofilms and examines the latest technologies used to determine the type and abundance of microorganisms present in CF infections.

2. Conclusion The last 20 years have seen an immense literature published on the nature of the link between a defective chloride channel and the development of respiratory infection. Although the link is still

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not definitive, we have gained a vast insight into the pathogenesis of CF lung disease and identified a number of pharmacotherapeutic targets that really offer the chance to manage CF. This is an exciting period for CF research, with two major classes of agents under broad clinical development. First, there are the airway “hydrators,” including hypertonic saline (HS), inhaled mannitol, long-acting P2Y2 agonists, and combination of HS and Na+ channel blockers. Second, there are mutant CFTR “correctors” and “potentiators,” drugs that will allow mutated protein to traffick and function in the cell membrane, and clinical trials show early promise (36). There is real optimism in CF research that we are now close to developing the tools that will make the development of pulmonary, and indeed systemic, CF pathophysiology a possibility, rather than certainty, for people with a CF genotype. References 1. Rich, D. P., Anderson, M. P., Gregory, R. J., Cheng, S. H., Paul, S., Jefferson, D. M., McCann, J. D., Klinger, K. W., Smith, A. E., and Welsh, M. J. (1990) Expression of cystic fibrosis transmembrane conductance regulator corrects defective chloride channel regulation in cystic fibrosis airway epithelial cells. Nature 347, 358–363. 2. Matsui, H., Verghese, M. W., Kesimer, M., Schwab, U. E., Randell, S. H., Sheehan, J. K., Grubb, B. R., and Boucher, R. C. (2005) Reduced 3-dimensional motility in dehydrated airway mucus prevents neutrophil capture and killing bacteria on airway epithelial surfaces. J Immunol 175, 1090– 1099. 3. Bjarnsholt, T., Jensen, P. O., Fiandaca, M. J., Pedersen, J., Hansen, C. R., Andersen, C. B., Pressler, T., Givskov, M., and Hoiby, N. (2009) Pseudomonas aeruginosa biofilms in the respiratory tract of cystic fibrosis patients. Pediatr Pulmonol 44, 547–558. 4. Donaldson, S. H., Bennett, W. D., Zeman, K. L., Knowles, M. R., Tarran, R., and Boucher, R. C. (2006) Mucus clearance and lung function in cystic fibrosis with hypertonic saline. N Engl J Med 354, 241–250. 5. Elkins, M. R., Robinson, M., Rose, B. R., Harbour, C., Moriarty, C. P., Marks, G. B., Belousova, E. G., Xuan, W., Bye, P. T. P. and for the National Hypertonic Saline in Cystic Fibrosis (NHSCF) Study Group (2006) A controlled trial of long-term Inhaled hypertonic saline in patients with cystic fibrosis. N Engl J Med 354, 229–240. 6. Engelhardt, J. F., Yankaskas, J. R., Ernst, S. A., Yang, Y., Marino, C. R., Boucher, R. C., Cohn, J. A., and Wilson, J. M. (1992) Sub-

7.

8.

9.

10.

11.

12.

13.

mucosal glands are the predominant site of CFTR expression in human bronchus. Nat Genet 2, 240–247. Kreda, S. M., Mall, M., Mengos, A., Rochelle, L., Yankaskas, J., Riordan, J. R., and Boucher, R. C. (2005) Characterization of wild-type and {Delta}F508 cystic fibrosis transmembrane regulator in human respiratory epithelia. Mol Biol Cell 16, 2154–2167. Sheppard, D. N., Rich, D. P., Ostedgaard, L. S., Gregory, R. J., Smith, A. E., and Welsh, M. J. (1993) Mutations in CFTR associated with mild-disease form Cl– channels with altered pore properties. Nature 362, 160–164. Denning, G. M., Anderson, M. P., Amara, J. F., Marshall, J., Smith, A. E., and Welsh, M. J. (1992) Processing of mutant cystic fibrosis transmembrane conductance regulator is temperature-sensitive. Nature 358, 761–764. Wang, F., Zeltwanger, S., Hu, S., and Hwang, T. C. (2000) Deletion of phenylalanine 508 causes attenuated phosphorylationdependent activation of CFTR chloride channels. J Physiol (Lond) 524 Pt 3, 637–648. Heda, G. D., Tanwani, M., and Marino, C. R. (2001) The Delta F508 mutation shortens the biochemical half-life of plasma membrane CFTR in polarized epithelial cells. Am J Physiol 280, C166–C174. Wilson, S. M., Olver, R. E., and Walters, D. V. (2007) Developmental regulation of lumenal lung fluid and electrolyte transport. Respir Physiol Neurobiol 159, 247–255. Kallapur, S. G., and Ikegami, M. (2006) Physiological consequences of intrauterine insults. Paediatr Respir Rev 7, 110–116.

Approaches to Study Cystic Fibrosis Pathophysiology 14. Ornoy, A., Arnon, J., Katznelson, D., Granat, M., Caspi, B., and Chemke, J. (1987) Pathological confirmation of cystic fibrosis in the fetus following prenatal diagnosis. Am J Med Genet 28, 935–947. 15. Mason, S. J., Paradiso, A. M., and Boucher, R. C. (1991) Regulation of transepithelial ion transport and intracellular calcium by extracellular adenosine triphosphate in human normal and cystic fibrosis airway epithelium. Br J Pharmacol 103, 1649–1656. 16. Barker, P. M., and Gatzy, J. T. (1998) Effects of adenosine, ATP, and UTP on chloride secretion by epithelia explanted from fetal rat lung. Pediatr Res 43, 652–659. 17. Knowles, M., Gatzy, J., and Boucher, R. (1983) Relative ion permeability of normal and cystic fibrosis nasal epithelium. J Clin Invest 71, 1410–1417. 18. Knowles, M., Gatzy, J., and Boucher, R. (1981) Increased bioelectric potential difference across respiratory epithelia in cystic fibrosis. N Engl J Med 305, 1489–1495. 19. Wiszniewski, L., Jornot, L., Dudez, T., Pagano, A., Rochat, T., Lacroix, J. S., Suter, S., and Chanson, M. (2006) Long-term cultures of polarized airway epithelial cells from patients with cystic fibrosis. Am J Respir Cell Mol Biol 34, 39–48. 20. Chambers, L. A., Rollins, B. M., and Tarran, R. (2007) Liquid movement across the surface epithelium of large airways. Respir Physiol Neurobiol 159, 256–270. 21. Kerem, E., Bistritzer, T., Hanukoglu, A., Hofmann, T., Zhou, Z., Bennett, W., MacLaughlin, E., Barker, P., Nash, M., Quittell, L., et al. (1999) Pulmonary epithelial sodium channel dysfunction and excess airway liquid in pseudohypoaldosteronism. N Engl J Med 341, 156–162. 22. Johansson, M. E., Thomsson, K. A., and Hansson, G. C. (2009) Proteomic analyses of the two mucus layers of the colon barrier reveal that their main component, the Muc2 mucin, is strongly bound to the Fcgbp protein. J Proteome Res 8, 3549–3557. 23. Button, B., and Boucher, R. C. (2008) Role of mechanical stress in regulating airway surface hydration and mucus clearance rates. Respir Physiol Neurobiol 163, 189–201. 24. Zuo, P., Picher, M., Okada, S. F., Lazarowski, E. R., Button, B., Boucher, R. C., and Elston, T. C. (2008) Mathematical model of nucleotide regulation on airway epithelia. Implications for airway homeostasis. J Biol Chem 283, 26805–26819. 25. Tsien, R. Y., Rink, T. J., and Poenie, M. (1985) Measurement of cytosolic free Ca2+

26.

27.

28.

29.

30.

31.

32.

33.

34.

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in individual small cells using fluorescence microscopy with dual excitation wavelengths. Cell Calcium 6, 145–157. Paradiso, A. M., Mason, S. J., Lazarowski, E. R., and Boucher, R. C. (1995) Membranerestricted regulation of Ca2+ release and influx in polarized epithelia. Nature 377, 643–646. Ribeiro, C. M., Paradiso, A. M., Livraghi, A., and Boucher, R. C. (2003) The mitochondrial barriers segregate agonistinduced calcium-dependent functions in human airway epithelia. J Gen Physiol 122, 377–387. Stutts, M. J., Canessa, C. M., Olsen, J. C., Hamrick, M., Cohn, J. A., Rossier, B. C., and Boucher, R. C. (1995) CFTR as a cAMPdependent regulator of sodium channels. Science 269, 847–850. Berdiev, B. K., Cormet-Boyaka, E., Tousson, A., Qadri, Y. J., Oosterveld-Hut, H. M., Hong, J. S., Gonzales, P. A., Fuller, C. M., Sorscher, E. J., Lukacs, G. L., et al. (2007) Molecular proximity of cystic fibrosis transmembrane conductance regulator and epithelial sodium channel assessed by fluorescence resonance energy transfer. J Biol Chem 282, 36481–36488. Ma, H. P., Saxena, S., and Warnock, D. G. (2002) Anionic phospholipids regulate native and expressed epithelial sodium channel (ENaC). J Biol Chem 277, 7641–7644. Yamagata, T., Yamagata, Y., Masse, C., Tessier, M. C., Brochiero, E., Dagenais, A., and Berthiaume, Y. (2005) Modulation of Na+ transport and epithelial sodium channel expression by protein kinase C in rat alveolar epithelial cells. Can J Physiol Pharmacol 83, 977–987. Gibson, R. L., Burns, J. L., and Ramsey, B. W. (2003) Pathophysiology and management of pulmonary infections in cystic fibrosis. Am J Respir Crit Care Med 168, 918–951. Mall, M. A., Harkema, J. R., Trojanek, J. B., Treis, D., Livraghi, A., Schubert, S., Zhou, Z., Kreda, S. M., Tilley, S. L., Hudson, E. J., et al. (2008) Development of chronic bronchitis and emphysema in beta-epithelial Na+ channel-overexpressing mice. Am J Respir Crit Care Med 177, 730–742. Livraghi, A., Grubb, B. R., Hudson, E. J., Wilkinson, K. J., Sheehan, J. K., Mall, M. A., O’Neal, W. K., Boucher, R. C., and Randell, S. H. (2009) Airway and lung pathology due to mucosal surface dehydration in ß-Epithelial Na+ channeloverexpressing mice: role of TNF-alpha and

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IL-4R-alpha signaling, influence of neonatal development, and limited efficacy of glucocorticoid treatment. J Immunol 182, 4357–4367. 35. Rogers, C. S., Abraham, W. M., Brogden, K. A., Engelhardt, J. F., Fisher, J. T., McCray, P. B., Jr., McLennan, G., Meyerholz, D. K., Namati, E., Ostedgaard, L. S., et al. (2008) The porcine lung as a potential model for cys-

tic fibrosis. Am J Physiol Lung Cell Mol Physiol 295, L240–L263. 36. Van Goor, F., Hadida, S., Grootenhuis, P. D., Burton, B., Cao, D., Neuberger, T., Turnbull, A., Singh, A., Joubran, J., Hazlewood, A., et al. (2009) Rescue of CF airway epithelial cell function in vitro by a CFTR potentiator, VX-770. Proc Natl Acad Sci USA 106, 18825–18830.

Chapter 2 Imaging CFTR Protein Localization in Cultured Cells and Tissues Silvia M. Kreda and Martina Gentzsch Abstract CFTR functions as a chloride channel at the apical membrane of airway, gastrointestinal, and other epithelial cells. Immunofluorescence microscopy is commonly used to assess the subcellular localization and relative abundance of CFTR. Visualization of heterologously overexpressed CFTR is typically unproblematic and straightforward, whereas detection of small quantities of endogenous CFTR in tissues can be challenging and requires highly specific antibodies and optimized staining protocols. CFTR tagged by green fluorescent protein can be employed to study trafficking in live cells. Tagging of CFTR with an extracellular epitope permits detection exclusively at the cell surface and subsequent chasing allows visualization of endocytic trafficking. Key words: CFTR immunostaining, CFTR expression, CFTR localization, airway epithelium, F508del-CFTR.

1. Introduction Immunostaining is a powerful technique to identify the spatial/temporal distribution of CFTR protein expression in the cell. In human tissues, CFTR protein is expressed at low levels, particularly in airway epithelia (1–3), and therefore, sensitive and specific antibodies are required to accurately detect native CFTR protein. Presently, only a few antibodies with these characteristics are available. A set of mouse monoclonal antibodies produced against the full-length human CFTR protein by J.R. Riordan and collaborators (University of North Carolina at Chapel Hill) detect CFTR protein in human native epithelia from airways, and also M.D. Amaral, K. Kunzelmann (eds.), Cystic Fibrosis, Methods in Molecular Biology 742, DOI 10.1007/978-1-61779-120-8_2, © Springer Science+Business Media, LLC 2011

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Fig. 2.1. CFTR immunolocalization in freshly isolated/frozen human tissues and fresh human airway primary cultures. (a, b) Skin and colonic tissues from normal and F508del homozygous individuals were rapidly frozen, sectioned, and subjected to immunostaining with CFTR antibody 528 (see Section 3.1). Images represent an overlay of the DIC (gray) and CFTR immunofluorescence (red) confocal channels and indicate that CFTR protein is mainly localized in the apical membrane of secretory cells of the sweat duct (a) and intestinal colonocytes (b) from normal (left panels) but not CF (right panels) individuals. Lumen is indicated by the asterisk. (c) Live, non-CF bronchial epithelial cultures were quickly fixed, subjected to co-immunostaining with CFTR antibody 528 and tubulin or MUC5AC antibodies, and cells scraped off the insert before mounting the specimen (see Section 3.3). Left panel represents an overlay of the DIC (gray), CFTR immunofluorescence (red), and cilia immunofluorescence (tubulin, green) confocal images, and right panel represents

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from other organs, with high specificity and sensitivity (2, 3). Using these antibodies, CFTR protein is immunolocalized at the apical membrane of ciliated cells throughout the airways, intestinal colonocytes, and secretory cells of sweat ducts of non-CF individuals (2, 3). In contrast, no plasma membrane-associated CFTR expression is observed in rectal, airway, and skin specimens from F508del homozygous individuals (2, 3) (see Fig. 2.1a, b and 2.2a, b). Because of the low levels of endogenous CFTR protein expression, preservation of the CFTR protein during tissue and cell specimen preparation and fixation is also a critical parameter in immunolocalization studies (4). Similarly, sensitive immunolocalization and microscopy techniques are necessary to detect endogenous CFTR protein. Thus, we favor the use of immunofluorescence techniques combined with confocal microscopy analysis in fresh and frozen rapidly fixed specimens. Immunolocalization analysis can be affected by many experimental parameters, and therefore, CFTR protein expression studies should not be based solely on immunolocalization data. Rather, CFTR chloride channel activity, biochemical detection, and/or mRNA in situ hybridization analyses should also be performed to interpret and confirm CFTR protein localization data. Immunostaining of heterologously expressed CFTR is a valuable technique to study many aspects of CFTR biology that are very difficult to accomplish using endogenous CFTR. For example, visualization of human CFTR heterologously overexpressed in cell lines provides a means to monitor the maturation of the protein. Stably expressed wild-type CFTR is usually detected as uniform staining over the entire cell surface and also intracellularly, whereas CFTR molecules with mutations that prevent maturation (e.g., F508del) are restricted to the endoplasmic reticulum, which appears often as a perinuclear network, as illustrated in Fig. 2.3a, b, and c (5, 6). When visualizing human CFTR in heterologous expression systems by immunofluorescence microscopy, it is strongly advisable to perform control experiments with native cells that do not express CFTR. Tagging of CFTR with an intrinsic fluorescent protein, e.g., green fluorescent protein (GFP), allows for easy visualization of the protein in fixed cells or by real-time microscopy. However, the addition of the 27-kDa GFP protein to the CFTR sequence may perturb processing and trafficking of the protein. In contrast, a

 Fig. 2.1. (continued) an overlay of the DIC (gray), CFTR immunofluorescence (red), and goblet cell (MUC5AC, green) confocal images. CFTR protein is localized in the apical membrane of ciliated, but not goblet cells (indicated by the arrow and MUC5AC staining, in the left and right panels, respectively). All scale bars, 10 μm. Images displayed in panel C were originally published in Mol. Biol. Cell (2005) 16, 2154 by Kreda et al. and reproduced with permission of ASCB/MBC.

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Fig. 2.2. CFTR immunolocalization in freshly isolated/frozen human airway tissues. (a) Snap-frozen bronchial tissues from normal and F508del homozygous individuals were quickly fixed, and consecutive tissue sections were subjected to immunostaining with antibodies against CFTR (clone 528) or ezrin; tissues were counterstained with fluorescently labeled phalloidin (see Section 3.1). The images represent CFTR (red) and actin cytoskeleton (phalloidin, green) confocal channels and ezrin (orange) channel. CFTR protein is mainly localized in the apical membrane of ciliated cells (arrow) of the superficial epithelium (SE) and ciliated ducts (CDs) in normal (top panels) but not CF (bottom panels) specimens. Submucosal gland serous ducts (SG, arrowhead) display negligible CFTR staining in many normal individuals. However, serous cells present robust staining for subapical ezrin and cortical actin (arrowhead). Bar, 40 μm. Images were originally published in Mol. Biol. Cell (2005) 16, 2154 by Kreda et al. and reproduced with permission of ASCB/MBC. (b) Schematics summarizing CFTR immunolocalization data in normal human airways using the protocols described in this chapter (see Section 3.1) and in (3). CFTR immunostaining is mainly localized in the apical membrane of ciliated cells (indicated by a thick red line on the cells) of the superficial epithelia of nose, large and small airways, and ciliated ducts of submucosal glands. CFTR is also observed in some serous cells (indicated by a dotted red line) and alveolar type II cells (indicated by a red line). CFTR immunostaining was negligible in goblet cells, small airway cuboidal cells, alveolar type I cells, and some gland serous cells. In situ hybridization studies indicate that CFTR mRNA expression is mainly localized in superficial ciliated epithelia and to a lesser degree in submucosal gland acini and alveoli (3), confirming CFTR protein immunolocalization results.

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Fig. 2.3. Visualization of heterologously expressed CFTR in cell cultures. (a) Immunofluorescence microscopy of wildtype and F508del-CFTR stably expressed in BHK-21 cells. WT and F508del-CFTR were detected in stably expressing BHK-21 cells with CFTR antibody 570 followed by Alexa Fluor 488 goat anti-mouse IgG conjugate. Wild-type CFTR localizes to the cell membrane, while F508del-CFTR is present only intracellularly. (b) Visualization of wild-type and F508del-CFTR fused to GFP. BHK-21 cells stably expressing WT and F508del-CFTR–GFP fusion proteins were fixed and immediately analyzed by confocal fluorescence microscopy. (c) Localization of WT and F508del-CFTR by confocal immunofluorescence microscopy in highly differentiated primary human epithelial cells adenovirally overexpressing Extope-WT or Extope-F508del-CFTR. Extope-CFTR was detected on fixed frozen culture sections with anti-HA antibody HA.11 followed by Alexa Fluor 488 goat anti-mouse IgG conjugate. Wild-type CFTR localizes to the apical membrane, while F508del-CFTR is present only intracellularly. (d) Schematic depiction of trafficking pathways of CFTR. Wild-type CFTR traffics through the Golgi and core sugars are elongated. CFTR reaches the apical membrane and is internalized. Endocytic CFTR recycles back to the membrane or is directed to late endosomes, multivesicular bodies (MVB), and lysosomes for degradation. F508del is recognized as misfolded by endoplasmic reticulum quality control and targeted for proteasomal degradation. (e) Intracellular distribution of surface and internalized CFTR over time. Cell surface pools of Extope-CFTR were labeled in stably expressing BHK-21 cells with anti-HA mAB HA.11 and cells were reincubated for indicated times. Internalized pools of Extope-CFTR were then detected on fixed cells with Alexa Fluor 488 goat anti-mouse IgG conjugate. All scale bars, 10 μm.

useful approach to study intracellular localization and trafficking of CFTR is the use of CFTR constructs that are extracellularly tagged with small epitope tags in locations where they do not affect maturation and function of the protein. For example, we express human CFTR containing an extracellular HA epitope tag to study CFTR protein trafficking in non-polarized cells (6) and in primary airway epithelial cells (7). This approach permits exclusive labeling of cell surface CFTR, visualization of CFTR internalization from the plasma membrane, and its recycling back to the cell surface (6, 7) (see Fig. 2.3e). Heterologous CFTR expression can also be introduced in transgenic animals. Thus, we produced a transgenic mouse expressing human CFTR in airway Clara cells under the CCSP promoter to investigate the role of CFTR in

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mucociliary clearance in mucus-obstructed lungs (manuscript in preparation). In conclusion, immunolocalization of CFTR is a powerful technique. However, close attention to experimental details is necessary and caution should be used when interpreting the results, specifically when studying endogenous CFTR in native tissues and primary epithelial cultures. Immunolocalization data should always be confirmed by evidence obtained by an alternative methodology.

2. Materials 2.1. Human Tissue Specimens

1. Human lung and nasal tissue specimens are obtained from lung transplant normal donor tissues, resected CF lungs, non-CF nasal plastic surgery, and nasal polypectomy. Human skin biopsies and rectal biopsies are obtained from normal and CF volunteers. The use of human tissues for these studies is approved by the Institutional Review Board for Protection of Human Rights at the University of North Carolina at Chapel Hill. 2. All the tissues are processed within 1 h of surgical excision and are quickly embedded in OCT (Sakura Finetek, Torrance, CA) and cryopreserved at –80◦ C. 3. Cryosections (∼8 μm thick) are generated on plus glass slides (Fisher, USA) and stored at –80◦ C until experiments are complete.

2.2. Cell Cultures 2.2.1. Primary Airway Epithelial Cultures

Primary cultures are generated from human bronchial epithelial cells obtained from excess lung transplant normal donor tissues and resected CF lung tissues according to regulations of the Institutional Review Board for Protection of Human Rights (UNCCH). Cells are grown on permeable supports (Transwell-Col filters, 12 mm diameter, 0.4 μm pore size; Corning Costar Co, Cambridge, MA) using a formulated medium described in detail elsewhere (8). After 28 days, well-differentiated cultures develop, R te > 300  cm2 .

2.2.2. Culture of Cell Lines Heterologously Expressing CFTR

BHK-21 cells stably expressing CFTR, F508del, and GFP- or extracellularly HA epitope-tagged variants [Extope-CFTR; (6)] are grown in DMEM/F12, 5% FBS, and 500 μM methotrexate at low confluence on glass bottom microwell dishes (MatTek Corporation, USA) or BD BioCoat collagen-coated culture slides (BD Biosciences, USA) (see Note 1). In cell lines stably expressing CFTR, the levels of CFTR protein expression can be increased

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by addition of 2 mM sodium butyrate to the growth medium for 8–16 h before the experiment. 2.3. Frozen and Paraffin-Embedded Primary Cultures

1. Well-differentiated primary cultures are embedded in OCT and cryopreserved at –80◦ C. Cryosections are performed as above. 2. Well-differentiated primary cultures are fixed in buffered formalin (Fisher, USA) overnight at room temperature and then embedded in paraffin (Fisher, USA). Thin sections (∼5 μm thick) are generated on plus glass slides.

2.4. Mouse Tissue Specimens

2.5. Immunostaining Reagents

Excised mouse lungs and tracheas are quickly embedded in OCT and cryopreserved at –80◦ C. Cryosections are produced as described above. 1. Fixation. 4% paraformaldehyde solution freshly prepared by diluting 16% paraformaldehyde purchased from Electron Microscopy Sciences (Hatfield, PA; stored protected from light, airtight, at 4◦ C) in phosphate buffer solution with 100 μM each of calcium and magnesium (PBS). Methanol and acetone were obtained from Fisher (USA). 2. Permeabilization. 100% methanol (HPLC quality; Fisher, USA) or alternatively 0.1% Triton X-100 prepared fresh by diluting 10% Triton X-100 (Pierce, Rockford, IL; stored airtight, at 4◦ C) in PBS or 0.1% saponin prepared fresh by diluting 10% saponin (Sigma, USA) in PBS. 3. Blocking. 10–20% non-immune normal serum (NS) of secondary antibody species (Jackson ImmunoResearch Labs, West Grove, PA) or alternatively 1% fatty acid-free bovine serum albumin (BSA) of RIA quality (Sigma, USA). Serum dilution is freshly prepared. BSA solution is prepared from a 5% BSA/PBS stock solution aliquoted and stored at –20◦ C. 4. CFTR monoclonal antibodies. CFTR antibodies (clones 528, 769, 596, and 570) were developed and provided by Dr. John R. Riordan (University of North Carolina at Chapel Hill) (2, 3, 5, 9). 5. Other antibodies and probes. Ezrin mouse monoclonal antibody is from BD Biosciences (San Jose, CA), tubulin rat monoclonal to label cilia is from Chemicon (Temecula, CA), rabbit polyclonal antibody against MUC5AC to identify goblet cells/mucin granules is a kind gift from John Sheehan (UNC), and fluorescently labeled phalloidin to label actin cytoskeleton is from Molecular Probes (Eugene, OR). Anti-HA antibodies HA.11 (clone 16B12; Covance, USA) and 12CA5 (Roche, Germany) are used to visualize Extope-CFTR.

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6. Non-immune mouse IgG and fluorescently labeled secondary antibodies are from Jackson ImmunoResearch Labs and Molecular Probes (Invitrogen, USA), respectively. 7. Vectashield mounting medium containing DAPI, to label nuclei, is purchased from Vector Labs (Burlingame, CA) or alternatively SlowFade Gold antifade reagent is purchased from Molecular Probes (Invitrogen, USA). 8. Epitope retrieval solution is from DAKO USA (Carpinteria, CA) and used following manufacturer’s instructions to unmask CFTR epitopes in paraffin-embedded specimens. 9. Vector M.O.M. Basic Kit (Vector Labs) for immunostaining of mouse tissues with antibodies produced in mouse and Texas Red-labeled streptavidin (Jackson ImmunoResearch Labs) to detect mouse monoclonal antibody immunostaining. 10. Wet chamber. A plastic box with a fitted lid containing several plastic pipettes organized in parallel to hold glass slides and a clean piece of wet paper on the bottom to provide humidity. 11. Histology pen is purchased from Fisher (USA). 12. Glass cover slips number 1.5 are manufactured by Corning USA (Fisher, USA). 13. Nail polish to seal mounted specimens. 14. Leica laser confocal microscopy system SP2 AOBS with an upright microscope DM-RXA2 containing a 16× PL Fluotar (NA 0.5), 40× Apochromat (NA 1.25–0.75, oil), 63× PlanApo (NA 1.4–0.6) Leica lenses, and DIC/Nomarski illumination. The scanning system is equipped with a highprecision galvanometer stage for real-time xz scanning and four independent lasers, namely UV 351/364 nm for DAPI, Argon 488 nm for FITC and Alexa Fluor 488, solid state diode pump 561 nm for Texas Red and Alexa Fluor 568, and HeNe 633 nm for CY5 and Alexa Fluor 633. Zeiss LSM 510 confocal laser scanning microscope with high-precision galvanometer stage, a Plan Apochromat 63× lens (NA 1.4, oil), DIC/Nomarski illumination, and lasers Argon 488 nm, HeNe 543 nm for Texas Red and Alexa Fluor 568, and HeNe 633 nm.

3. Methods In this section we describe immunolocalization of endogenous and heterologously expressed CFTR protein in tissues and cell cultures. These techniques can be adapted to any type of cell culture and tissue. Protocols for fresh, frozen, and

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formalin-fixed/paraffin-embedded specimens are illustrated. We do not recommend the use of paraffin-embedded specimens because of variable and deficient preservation of CFTR protein levels and/or CFTR reactivity to antibodies. Instead, we use fresh or quickly frozen specimens preserved by controlled, mild fixation, since fixation can affect the capacity of antibodies to recognize CFTR (4). We use the CFTR monoclonal antibodies developed by Dr. John R. Riordan (UNC-CH) (2, 3, 5, 9). CFTR antibodies from other sources produce variable results in immunolocalization studies (2–4, 10, 11). We illustrate co-staining of CFTR antibodies with antibodies or probes reacting against cellular markers for identification of cell types or intracellular compartments to facilitate the interpretation of CFTR localization studies. Our protocols use fluorescence as the detection method and laser confocal microscopy for data collection and analysis. Confocal microscopy has optical advantages over epifluorescence microscopy, the former being more reliable in discriminating different fluorescent signals in co-staining experiments, identifying subcellular localization of fluorescent signals, and comparing localization of a fluorescent probe among different specimens (12). We will also discuss techniques for immunostaining of heterologously expressed human CFTR in cell cultures and mouse tissues. The high levels of CFTR protein expression in human heterologous cells allow immunostaining to be easier than in native cells. However, in mouse tissues, a different approach needs to be used to overcome the use of mouse monoclonal CFTR antibodies on mouse tissues. Because GFP-tagged CFTR can be used for trafficking studies, it has been included in this chapter. However, we favor the use of Extope-CFTR, which refers to CFTR with an externally accessible HA epitope inserted into an extended, modified extracellular loop 2 that contains sequences from the first and fourth extracellular loops to expose the HA epitope (6, 7). Extope-CFTR matures and functions like unmodified wild-type CFTR (6) and permits selective visualization of surface CFTR and chasing of labeled CFTR during internalization for monitoring of CFTR protein recycling in intact cells (6, 7). 3.1. Immunofluorescence Staining of Endogenous CFTR in Cryosections of Human Tissues

Cryosections of frozen freshly excised airway, rectal, or skin tissues mounted on glass slides can be processed for CFTR immunolocalization using the following protocol: 1. Fixation. Frozen tissue slides are air-thawed and promptly fixed with 4% paraformaldehyde/PBS solution for 5 min at room temperature (see Note 2). Fixative is eliminated and slides are washed twice for 5 min at room temperature. 2. Permeabilization. Tissue slides are rinsed with PBS and incubated with 100% ethanol for 2 min at –20◦ C (see Note 3). 3. Blocking. Slides are air-dried and tissue specimens encircled using a histology pen (see Note 4). Tissue wells are rinsed

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once with PBS and incubated in 10% normal serum/PBS blocking solution for at least 30 min at room temperature (see Note 5) using a wet chamber (see Note 6). 4. First antibody incubation. Incubation with CFTR antibodies, non-immune mouse IgG, and other antibodies is performed overnight at 4◦ C (see Note 7). Antibodies and IgG are diluted in blocking solution; CFTR antibodies and IgG are used at matching concentrations of 5–10 μg/ml, and ezrin, tubulin, and MUC5AC antibodies are employed at 0.5–1 μg/ml. In co-staining experiments, CFTR and other marker antibodies are added together at the specified concentrations. 5. Washes. Antibody solutions are discarded and tissues washed twice with PBS for 5 min at room temperature. 6. Secondary antibody incubation. Fluorescently labeled secondary antibodies are diluted in blocking solution at the time of the experiment, at the concentration recommended by the manufacturer, and added for 1 h at room temperature, protected from light. In co-staining experiments, all secondary antibodies are added together (see Notes 8 and 9). Fluorescently labeled phalloidin can be added at this step at 0.5–1 μM concentration. 7. Washes. Antibody solutions are discarded and cultures washed three times with PBS for 5 min at room temperature, protected from light. 8. Mounting. Most of the liquid should be eliminated without air-drying the tissue sections (see Note 6). A glass cover slip with a diameter larger than that of the tissue section is placed on a piece of absorbent paper and a drop of mounting medium is added on it. The glass slide is inverted with the tissue facing down and is carefully laid over the cover slip, starting from one side to avoid the formation of air bubbles. The excess mounting medium is allowed to drain into the paper for a few seconds without pressing on the glass (see Note 10). Any liquid on the glass is eliminated with a vacuum-attached Pasteur pipette and the cover slip is sealed with nail polish. It is stored at 4◦ C, protected from light. 9. Confocal microscopy and image analysis. Confocal microscopy analysis is performed by xy scanning using the appropriate lasers (see Note 11), a 63× lens, and Nomarski illumination (see Note 12). Parameters should be maintained constant throughout the analysis. Imaging analysis and montage are performed using Leica and Adobe PS software, respectively (see Note 13). Examples of the results obtained using this protocol are illustrated in Figs. 2.1a, b and 2.2a.

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3.2. Immunofluorescence Staining of Endogenous CFTR in Formalin-Fixed, Paraffin-Embedded Human Tissues

1. Formalin-fixed, paraffin-embedded tissues mounted on glass slides (see Note 14) are deparaffinized by sequentially immersing glass slides in xylol and 100, 95, and 70% alcohol solutions.

3.3. Immunofluorescence Staining of Endogenous Human CFTR in Fresh Well-Differentiated Primary Airway Epithelial Cultures

1. Fixation. Well-differentiated bronchial epithelial cultures are rinsed twice with PBS and fixed by adding 4% paraformaldehyde/PBS solution to both the apical and basolateral sides. Fixation is for 5 min at room temperature (see Note 2). Fixative is eliminated and washed twice for 5 min at room temperature.

2. Samples are air-dried and subjected to epitope retrieval with DAKO (pH 6) solution using a microwave for 1 min at full power followed by 10 min at 10% power. Samples are cooled to room temperature, rinsed with PBS, and subjected to the blocking and subsequent steps as described in Section 3.1 for frozen tissues.

2. Permeabilization. Cultures are incubated with 0.1% Triton X-100/PBS solution on both sides for 20 min at room temperature (see Note 3). 3. Blocking. Cultures are rinsed twice with PBS and incubated apically with 100 μl of 1% BSA/PBS blocking solution for at least 30 min at room temperature (see Notes 5 and 6). 4. First antibody incubation. Incubation with CFTR antibodies, non-immune mouse IgG, and other antibodies is performed as described in Section 3.1 for frozen tissues. A 12-mm insert requires 100 μl of antibody solution to cover the apical side. The basolateral side may be bathed in 100–200 μl of PBS (see Note 7). 5. Washes and secondary antibody incubation. Washes after the first and secondary antibodies, and incubation with fluorescently labeled secondary antibodies and fluorescently labeled phalloidin are performed as described in Section 3.1 for frozen tissues (see Notes 8 and 9). 6. Mounting. The membrane supporting the culture is carefully separated from the plastic cup insert using a surgical knife and placed flat on a glass slide with the help of forceps. A minimal amount of liquid should be present in the insert before starting this operation. With gentle outward movements, the edges of the cultured membrane are combed with a surgical knife to dislodge cell sheets; the center of the culture should remain intact. A glass cover slip with a diameter larger than that of the cultured membrane is placed on a piece of absorbent paper and a drop of mounting medium is added on it. The glass slide is inverted with the cell culture facing down and is carefully laid over the cover slip,

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starting from one side to avoid the formation of air bubbles. The excess mounting medium is allowed to drain into the paper for a few seconds without pressing on the glass (see Note 10). Any liquid on the glass is eliminated with a vacuum-attached Pasteur pipette and the cover slip is sealed with nail polish. It is stored at 4◦ C, protected from light. 7. Confocal microscopy and image analysis. For specimen imaging and analysis, we use a Leica laser confocal microscopy system SP2 AOBS with an upright microscope DM-RXA2. Specimens are imaged using the appropriate lasers (see Note 11) and a 63× lens by xz (cross section) scanning in the center of the cultures, where the epithelial architecture is left intact. Cells scraped off the membrane support are xy (in face) scanned using simultaneous DIC and fluorescence channels (see Note 12). The conditions for scanning are kept constant throughout the studies. Imaging analysis and montage are performed using Leica and Adobe PS software, respectively (see Note 13). An example of the results obtained using this protocol is illustrated in Fig. 2.1c. 3.4. Immunofluorescence Staining of Endogenous Human CFTR in Frozen or Formalin-Fixed/ Paraffin-Embedded, Well-Differentiated Primary Airway Epithelial Cultures

1. Frozen cell culture sections mounted on glass slides (see Note 15) are air-thawed and promptly fixed and processed for immunostaining following the protocol described in Section 3.1 for frozen tissues. 2. Formalin-fixed, paraffin-embedded culture sections mounted on glass slides are deparaffinized and processed for immunostaining as described in Section 3.2 for paraffinembedded tissues (see Note 14).

3.5. Immunostaining of CFTR Heterologously Expressed in Cell Cultures Using Anti-CFTR Antibodies Detecting Intracellular Epitopes

Cell cultures heterologously expressing human CFTR are rinsed twice with PBS and processed for immunostaining following the protocol described in Section 3.1 for frozen human tissues (see Notes 16, 17, and 18). An example of results obtained using this protocol is shown in Fig. 2.3a, c.

3.6. Visualization of CFTR Pools at the Plasma Membrane and in Endocytic Compartments, Using an Extracellular Epitope Tag

Surface CFTR is labeled with HA antibodies at 4◦ C to avoid internalization. 1. Wash cells (e.g., BHK-21 cells) stably expressing ExtopeCFTR three times with PBS. 2. Pre-cool cells for 15 min on ice in a cold room at 4◦ C. 3. Label cell surface Extope-CFTR for 30 min on ice in a cold room with anti-HA 16B12 raw ascites diluted 1:500 in PBS with 1% BSA (see Note 19).

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4. Wash cells four times with ice-cold PBS. If you intend to visualize surface CFTR, proceed to Step 5. For visualization of endocytosed CFTR, proceed to Step 8. 5. Fix cells with cold 4% paraformaldehyde for 10 min (see Note 20). 6. Block and incubate with goat anti-mouse IgG Alexa Fluor 488 antibody. 7. Perform washes, mounting, and confocal microscopy analysis in a Zeiss LSM 510 system as described in Section 3.1 for frozen tissues. 8. For visualization of endocytosed CFTR, add warm growth media to cells after Step 4 and reincubate cells at 37◦ C in a cell incubator for the indicated times. 9. Rinse cells twice quickly with PBS. 10. Fix cells in 4% paraformaldehyde in PBS at room temperature for 10 min (see Note 16). 11. Wash three times for 10 min with PBS at room temperature. 12. Permeabilize cells with 0.1% Triton X-100 in PBS for 10 min at room temperature (see Note 17). 13. Wash three times for 10 min. 14. Block at least for 1 h with blocking buffer. 15. Perform incubation with fluorescently labeled secondary antibodies, washes, mounting, and confocal microscopy analysis as described in Step 7. An example of results obtained using this protocol is shown in Fig. 2.3e. 3.7. Visualization of CFTR Recycling from an Intracellular Compartment to the Plasma Membrane, Using an Extracellular Epitope Tag

To study recycling of Extope-CFTR, HA antibodies bound to surface CFTR are removed by a low pH wash resulting in label remaining exclusively on CFTR in endocytic vesicles. CFTR that recycles to the surface after reincubation is then visualized on fixed, but not permeabilized cells. 1. Label cells (e.g., BHK-21) expressing Extope-CFTR by addition of monoclonal mouse anti-HA antibody 12CA5 to the growth medium for 10 min at 37◦ C. 2. Quickly remove 12CA5 antibody bound to cell surface pools of Extope-CFTR by rinsing cells twice for 30 s with ice-cold PBS (pH 3.7) (PBS + HCl), followed by a wash with PBS (pH 7.4). Fix one sample at this step with 4% paraformaldehyde to verify complete removal of apical label. 3. Reincubate cells in pre-warmed media for 5 min at 37◦ C. Fix cells with 4% paraformaldehyde, block, and incubate with goat anti-mouse IgG Alexa Fluor 488 antibody as described in Section 3.6 to visualize CFTR that has been recycled to the cell surface (see Note 20).

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4. Perform washes, mounting, and confocal microscopy analysis as described in Section 3.6. 3.8. Imaging of Green Fluorescent Protein-Tagged CFTR

Green fluorescent protein-tagged CFTR can be visualized in live cells or in previously fixed cells. Live cells are best observed in dye-free, HEPES-buffered growth medium (see Note 21) (see Fig. 2.3b).

3.9. Immunofluorescence Staining of Transgenic Human CFTR in Frozen Mouse Tissues

1. Frozen tissue sections are fixed in cold 100% acetone (see Note 22). 2. Immunostaining with antibodies against human CFTR is performed using the Vector M.O.M. Basic Kit (as per manufacturer’s instructions) for optimized immunodetection in mouse tissues, using mouse-raised antibodies. Briefly, CFTR antibodies are incubated at 10 μg/ml (prepared in M.O.M. diluent) for 60 min at room temperature. M.O.M. biotinylated anti-mouse IgG reagent is incubated for 10 min at room temperature. Texas Red streptavidin is incubated at 15 μg/ml (prepared in PBS) for 10 min at room temperature. 3. Mounting and confocal microscopy analysis are performed by xy scanning as described in Section 3.1 for human tissues.

4. Notes 1. Different cell lines have different requirements for none or specific coating for the glass substrata and growth media. 2. Fixation is critical for effective immunoreactivity with CFTR monoclonal antibodies. Paraformaldehyde dilution is freshly prepared from a high-quality source. Long fixation times may require an epitope retrieval step before incubation with CFTR antibodies and is not recommended. 3. Alternatively, permeabilization can be performed with 100% methanol or ethanol for 5 min at –20◦ C; when using this permeabilization, fixation can be done with 2% paraformaldehyde. Alcohol permeabilization usually works better in preserving cellular integrity in freshly excised frozen tissues. 4. The use of a hydrophobic histology pen to draw wells encircling the tissue specimens allows the use of reduced amounts of immunostaining reagents. If more than one tissue section is mounted on a glass slide, each section can be incubated with a different antibody if separated in different pen-drawn wells. Tissues should be sufficiently separated to

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ensure no cross-contamination between wells using different antibodies. 5. RIA-quality BSA is recommended because it is mostly devoid of other serum components. Immunostaining of cultures can be achieved using a low-concentration BSA solution for blocking non-specific antibody binding. In contrast, tissues may require better blocking. Thus, a solution prepared with 10–20% of non-immune (normal) serum from the secondary antibody species, with/without the addition of 3% BSA, usually works better than BSA alone in airway tissues. 6. Cultures should not be allowed to dry during the immunostaining proceeding to avoid staining artifacts. For specimens on glass slides, use a wet chamber, and for cell cultures grown on plates, replace the lid after each incubation step. 7. Incubation with CFTR antibodies overnight at 4◦ C yields a better signal/background ratio than does incubation for 2 h at room temperature. This is particularly important in airway tissues, due to the relative low expression of the CFTR protein vs. the high capacity of non-specific antibody binding of the different tissue structures. 8. Secondary antibodies should have minimal cross-reactivity with human proteins and the secondary antibody species. Fluorescently labeled Fab or F(ab )2 antibody fragments are very useful in avoiding cross-reactivity, particularly in airway tissues undergoing inflammation and mucous metaplasia. 9. The part of a compound that emits fluorescence is a fluorophore. In co-staining experiments, the selection of fluorophores labeling antibodies and phalloidin must be based on the excitation/emission characteristics of the molecules such that they do not interfere with each other in the microscope analysis. Fluorophores with broad excitation/emission characteristics should be avoided when costaining CFTR with other cellular markers. Information about fluorescent molecules can be accessed at Molecular Probes and Jackson ImmunoResearch Labs. 10. Mounting medium thickness is critical when using low working distance microscopy immersion lenses, because too much medium will render poor focusing. In contrast, too little medium will favor the generation of air bubbles and will compress the cultures between both glasses, altering the epithelial architecture. 11. Confocal microscopy is desired for the analysis of CFTR localization. The thin optical sectioning produced by laser

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confocal scanning ensures accurate spatial collection of immunostaining signal necessary to localize CFTR protein relative to other cellular structures or markers (e.g., ciliated cells, plasma membrane, and intracellular vesicles). Moreover, many laser confocal scanning systems are equipped to adjust to narrow excitation and emission bandwidths to optically discriminate different fluorophores present simultaneously in co-localization experiments. However, the success of co-localization experiments relies on selecting correctly a set of fluorophores that will be accurately detected and discriminated by the microscopy system. Laser confocal microscopy systems equipped with a galvanometer stage allow real-time xz scanning of epithelial cultures to image a cross section of the cells, as opposed to image reconstruction with specific software of a timeconsuming, high-resolution xy multi-focal stack. 12. Differential interference contrast (DIC) or Nomarski illumination produces images of detailed cell structure for morphology and localization analyses and is recommended for imaging immunolocalization data in tissues. 13. Unbiased image collection and analysis of CFTR immunostaining are crucial, mainly in specimens where CFTR localization may be differently affected (i.e., normal vs. CF airway epithelia). Thus, studies should be performed blind to the identity/phenotype of the specimens, and conditions used in image collection and analysis should be maintained constant throughout. Similarly, alterations introduced in the images for presentation or publication purposes should affect identically all the images. Image alteration should be avoided or kept to a minimum and should be done only for aesthetic or didactic reasons without affecting the integrity of the scientific data. 14. Formalin-fixed, paraffin-embedded, well-differentiated airway epithelial cultures or tissue specimens yield wellpreserved cell specimens that can be stored for long periods of time. However, most CFTR antibodies require strong epitope retrieval techniques in these specimens, with varying results; this means, the levels of CFTR immunoreactivity may misrepresent actual CFTR protein levels in the specimens, and comparison between different specimens may be difficult. Epitope retrieval techniques also often damage fine cellular architecture and preclude the use of high-power magnification/resolution microscopy techniques. Moreover, analysis of co-localization studies may be affected by blemished cell architecture integrity produced by the epitope retrieval technique. Therefore, caution should be exercised using formalin-fixed,

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paraffin-embedded specimens for CFTR immunostaining analysis. Culture and tissue specimens for long-term histology collections are usually preserved using the formalinfixation/paraffin-embedding techniques. However, cytological preservation, and therefore CFTR protein integrity, is affected by the timing between specimen collection and fixation, fixation method (e.g., fixative type and concentration, duration of fixation), paraffin-embedding method, and storing conditions (i.e., time, temperature, and humidity), which vary through time and between different laboratories. Thus, formalin-fixed, paraffin-embedded specimens are not suitable for studies aimed to characterize localization of CFTR or compare CFTR immunostaining levels between different specimens. These specimens should never be used as the primary source for a CFTR immunostaining study! 15. Frozen slides of well-differentiated airway epithelial cultures are very useful because many slices can be obtained from one culture. However, freezing and cutting epithelial cultures grown on membrane supports require an experienced hand. Often, cultures are damaged during the freezing or cutting steps and are not suitable for CFTR immunolocalization studies. 16. Alternatively, non-polarized cells may be fixed with ice-cold methanol at –20◦ C for 10 min. The permeabilization step is not necessary, since alcohol functions as both fixative and permeabilizing agent. 17. Alternatively, cells fixed with 4% paraformaldehyde may be permeabilized with 0.1% saponin in PBS for 1 h at 4◦ C. 18. For cells overexpressing CFTR, immunostaining may be performed using raw ascites fluid containing anti-CFTR monoclonal antibodies 570, 596, 528 diluted 1:500 and incubated for 1 h at room temperature or 1:1000 and incubated overnight at 4◦ C. 19. Anti-HA antibody HA.11 (clone 16B12; Covance, USA) is generally used to visualize the extracellular tag in ExtopeCFTR. HA.11 anti-HA antibody binds to epitope in Extope-CFTR even at pH 3–4 and is therefore not useful for studies in which the antibody has to be removed from the epitope. In contrast, anti-HA antibody 12CA5 (Roche, Germany) can be removed from cell surface Extope-CFTR by an acidic wash and is consequently used in recycling studies intended to monitor internalized Extope-CFTR. 20. Do not use MeOH for fixation, as this maneuver will permeabilize the cells. Similarly, do not permeabilize the cells

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with detergent before blocking, as this will lead to visualization of intracellular Extope-CFTR pools. If desired, intracellular pools of CFTR can be visualized in parallel permeabilized samples; however, keep these slides away from slides that will not be permeabilized to avoid contamination with detergent. 21. When observing live cells, avoid bleaching of the sample, alkalinization of the culture medium, and also excess heating by laser exposure. 22. Acetone fixation is recommended by the manufacturer of the M.O.M. kit to minimize background staining.

Acknowledgments The authors gratefully thank the CF and non-CF volunteers for their tissue specimen donation; Richard Boucher for his comments, John R. Riordan and John Sheehan for their generous gifts of CFTR antibodies and MUC5AC polyclonal antibody, respectively; James Yankaskas and Marcus Mall for human tissue specimen collection; Scott Randell and Leslie Fulcher for providing the primary airway epithelial cells, Kim Burns, Tracy Barlotta, and Donald Joyner for their expert technical assistance; Lisa Brown for editing this manuscript; Michael Chua and Neal Kramarcy for microscopy assistance; and the UNC M. Hooker Microscopy Facility for making accessible their microscopes. This work is supported by CFF grants GENTZS04G0 and GENTZS07G0 (MG) and KREDA01I0 (SMK), the Mary Lynn Richardson Fund (SMK), and NIH Grants HL34322 and HL 51818-06A1 (SMK). References 1. Kartner, N., Augustinas, O., Jensen, T. J., Naismith, A. L., and Riordan, J. R. (1992) Mislocalization of DF508 CFTR in cystic fibrosis sweat gland. Nat Genet 1, 321–327. 2. Mall, M., Kreda, S. M., Mengos, A., Jensen, T. J., Hirtz, S., Seydewitz, H. H., et al. (2004) The DeltaF508 mutation results in loss of CFTR function and mature protein in native human colon. Gastroenterology 126, 32–41. 3. Kreda, S. M., Mall, M., Mengos, A., Rochelle, L., Yankaskas, J., Riordan, J. R., et al. (2005) Characterization of wild-type

and {Delta}F508 cystic fibrosis transmembrane regulator in human respiratory epithelia. Mol Biol Cell 16, 2154–2167. 4. Claass, A., Sommer, M., de, J. H., Kälin, N., and Tümmler, B. (2000) Applicability of different antibodies for immunohistochemical localization of CFTR in sweat glands from healthy controls and from patients with cystic fibrosis. J Histochem Cytochem 48, 831–837. 5. Gentzsch, M., and Riordan, J. R. (2001) Localization of sequences within the C-terminal domain of the cystic fibrosis transmembrane conductance regulator which

CFTR Localization impact maturation and stability. J Biol Chem 276, 1291–1298. 6. Gentzsch, M., Chang, X. B., Cui, L., Wu, Y., Ozols, V. V., Choudhury, A., et al. (2004) Endocytic trafficking routes of wild type and DeltaF508 cystic fibrosis transmembrane conductance regulator. Mol Biol Cell 15, 2684–2696. 7. Cholon, D. M., O’Neal, W. K., Randell, S. H., Riordan, J. R., and Gentzsch, M. (2010) Modulation of endocytic trafficking and apical stability of CFTR in primary human airway epithelial cultures. Am J Physiol Lung Cell Mol Physiol 298, L304–L314. 8. Fulcher, M. L., Gabriel, S., Burns, K. A., Yankaskas, J. R., and Randell, S. H. (2004) Well-differentiated human airway epithelial cell cultures. Methods Mol Med 107, 183–206.

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9. Gentzsch, M., Cui, L., Mengos, A., Chang, X. B., Chen, J. H., and Riordan, J. R. (2003) The PDZ-binding chloride channel ClC-3B localizes to the Golgi and associates with cystic fibrosis transmembrane conductance regulatorinteracting PDZ proteins. J Biol Chem 278, 6440–6449. 10. Engelhardt, J. F., Yankaskas, J. R., Ernst, S. A., Yang, Y., Marino, C. R., Boucher, R. C., et al. (1992) Submucosal glands are the predominant site of CFTR expression in human bronchus. Nat Genet 2, 240–247. 11. Kälin, N., Claass, A., Sommer, M., Puchelle, E., and Tümmler, B. (1999) DeltaF508 CFTR protein expression in tissues from patients with cystic fibrosis. J Clin Invest 103, 1379–1389. 12. Pawley, J. B. (2006) Handbook of Biological Confocal Microscopy. Springer, New York, NY.

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Chapter 3 CFTR Regulation of Epithelial Sodium Channel Yawar J. Qadri, Estelle Cormet-Boyaka, Dale J. Benos, and Bakhrom K. Berdiev Abstract Cystic fibrosis (CF) is a lethal genetic disorder, characterized by both clinical and genetic complexities, and arises as a result of mutations in the cystic fibrosis transmembrane conductance regulator (CFTR) gene. The gene encodes a Cl− channel belonging to the ABC (ATP Binding Cassette) superfamily of transporters. The members of this superfamily use ATP hydrolysis to fulfill their function as active transporters. So far, CFTR is the only member of this family to function as a cAMP-activated Cl− channel. Intense research following the cloning of the CFTR gene has extended the role of the CFTR beyond that of a Cl− channel. One of the best recognized, yet still controversial, functions of the CFTR is its ability to modulate the functioning of other transporters. The modulation of epithelial Na+ channel (ENaC) function serves as a prime example of regulatory function of the CFTR. In this chapter, we will briefly describe an integrated protocol consisting of biochemical and electrophysiological approaches to study the regulation of ENaC by CFTR. Key words: CFTR, ENaC, bilayers, two-electrode voltage clamp, co-immunoprecipitation.

1. Introduction The cystic fibrosis transmembrane conductance regulator not only functions as an ATP- and PKA-dependent Cl− channel but also has the unique ability to influence the function of other transporters (1, 2). The modulation of epithelial Na+ channel (ENaC) is one of the best recognized, yet still debated regulatory functions of the CFTR. In this chapter, we will describe a protocol that combines biochemical and electrophysiological approaches to study the regulatory link between ENaC and CFTR.

M.D. Amaral, K. Kunzelmann (eds.), Cystic Fibrosis, Methods in Molecular Biology 742, DOI 10.1007/978-1-61779-120-8_3, © Springer Science+Business Media, LLC 2011

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2. Materials 2.1. Xenopus laevis Oocyte Preparation and Injection with cRNAs and Preparation of Oocyte Plasma Membrane Vesicles

1. Female X. laevis (Xenopus Express, Brooksville, FL, USA, or Le Bourg, France). 2. General anesthesia for amphibians. 3. Ca2+ -free OR-2 solution: 82.5 mM NaCl, 2.4 mM KCl, 1.8 mM MgCl2 , 5.0 mM HEPES (pH 7.4). 4. Collagenase type 1A. 5. Leibovitz (L-15) buffer (Sigma, St. Louis, MO). 6. cRNAs of the CFTR and ENaC in nuclease-free H2 O (see Note 1). 7. Rinsing buffer (high-K+ ): 400 mM KCl, 5 mM piperazineN,N-bis(2-ethanesulfonic acid), pH 6.8. 8. Protease inhibitor cocktail: phenylmethylsulfonyl fluoride, pepstatin, aprotinin, leupeptin. 9. DNase I. 10. Sucrose. 11. Resuspension buffer: 100 mM KCl, 5 mM MOPS, pH 6.8.

2.2. Planar Lipid Bilayers

1. The bilayer setup (Warner Instruments, Inc., Hamden, CT; see Note 2). 2. Ag/AgCl electrodes embedded in 3 M KCl/3% agar bridges (see Note 3). 3. The bathing solutions: 100 mM NaCl, pH 7.4 (see Note 4). 4. Bilayer-forming lipid: 10 mg/mL diphytanoyl phosphatidylethanolamine (Avanti Polar Lipids, Alabaster, AL) stock in chloroform. 5. Bilayer-forming lipid: 10 mg/mL diphytanoyl phosphatidylserine (Avanti Polar Lipids, Alabaster, AL) stock in chloroform. 6. Nitrogen gas. 7. Bilayer-forming solution (n-decane or n-octane). 8. Protein kinase A and MgATP (to phosphorylate CFTR Cl− channel), CFTR inhibitors (diphenylamine-2-carboxylate, glibenclamide, or anti-CFTR505-511 antibody), and ENaC inhibitors (amiloride or benzamil).

2.3. Two-Electrode Voltage Clamp

1. Two-electrode voltage clamp system including an amplifier, micromanipulators for electrode positioning, a vibration isolation table, and a Faraday cage (Warner Instruments, Inc., Hamden, CT; see Note 5).

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2. Perfusion system and recording chamber (Warner Instruments, Inc., Hamden, CT; see Note 6). 3. Electrode puller and glass. 4. Electrode solution, 3 M KCl. 5. Bath solution, primarily ND96: 96 mM NaCl, 1 mM MgCl2 , 1.8 mM CaCl2 , 2 mM KCl, and 5 mM HEPES (pH 7.4). 6. Amiloride, (IBMX). 2.4. Cell Culture, Transient Transfection

forskolin,

and

3-isobutyl-1-methylxanthine

1. Lysis buffer: PBS 1×/0.2% Triton X-100 containing R protease inhibitor cocktail (Roche Biochemical, Complete Mannheim, Germany). Cell culture solutions (see Note 7). 2. 4–15% gradient gel (Bio-Rad). 3. Running buffer (10×): 1×: 25 mM Trizma base, 192 mM glycine, 0.1% SDS. Store at room temperature. 4. Transfer buffer: 25 mM Trizma base, 192 mM glycine. Store at 4◦ C. 5. Tris-buffered saline (TBS): 150 mM NaCl, 25 mM Tris. Adjust pH to 7.5 with HCl. 6. Blocking buffer: TBS with 0.1% Tween-20 and 5% nonfat dry milk. 7. Primary and secondary antibodies diluted in antibody dilution buffer (TBS with 0.4% Tween-20, 8% glycerol, and 4% nonfat dry milk) (see Note 8). 8. 5× SDS loading sample buffer: 250 mM Tris–HCl (pH 6.8), 10% SDS, 30% glycerol, 5% β-mercaptoethanol, and 0.02% bromophenol blue.

3. Methods 3.1. Preparation and Injection of Xenopus Oocytes

1. Surgically remove oocytes from an anesthetized (ice/tricaine solution) adult female X. laevis kept at 18◦ C in chlorine-free water (3, 4). 2. Oocyte defolliculation: 2-h treatment with collagenase type 1A (1 mg/mL) in Ca2+ -free OR-2 solution. Exchange solution at least once, preferably twice. 3. Choose and isolate stage V/VI oocytes. 4. Allow oocytes to recover overnight in half-strength Leibovitz L-15 buffer.

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5. Divide oocytes into three groups (30–40 in each): ENaCs alone, ENaCs plus CFTR, and control. 6. ENaCs without CFTR group: inject oocytes with 2 ng/subunit cRNA (in nuclease-free H2 O) for each ENaC subunit (ENaC is comprised of three subunits giving a total of 6 ng cRNA; see Note 9). ENaCs with CFTR group: add CFTR cRNA (a total of 8 ng cRNA). Control group: inject oocytes with 50 nL of water only (no RNA). 7. Incubate injected oocytes for 48–72 h in L-15 or similar media. Change medium daily as some oocytes may not survive the injection procedure. 3.2. Preparation of Xenopus Oocyte Membrane Vesicles

1. Rinse injected oocytes with high-K+ buffer supplemented with 100 μM phenylmethylsulfonyl fluoride, 1 μM pepstatin, 1 μg/mL aprotinin, 1 μg/mL leupeptin, 1 μg/mL DNase I, and 300 mM sucrose (5). 2. Use a ground glass tissue grinder to homogenize oocytes in 300 μL (∼10 μL/oocyte) of the high-K+ buffer for 5 min. 3. On a discontinuous sucrose gradient (3 mL of 50% on bottom and 3 mL of 20% on the top in high-K+ buffer in the presence of protease inhibitors) layer homogenate. 4. Centrifuge at 23,500×g for 30 min. 5. Discard the top layer. 6. Collect the interface (white cloudy layer) and dilute threefold with high-K+ buffer. 7. Repeat centrifugation at 23,500×g for 30 min. 8. Discard the supernatant and resuspend pellet in 100 μL of resuspension buffer (100 mM KCl, 5 mM MOPS, pH 6.8). 9. Separate membrane vesicles into 15-μL fractions and store at −80◦ C until use.

3.3. Planar Lipid Bilayer System

1. The bilayer chamber has two parts (with cis and trans designation) (3, 4). These compartments are separated by a polycarbonate or a Teflon septum containing a small (150– 200 μm) hole. The voltage source is connected to the cis compartment of the bilayer chamber (via Ag/AgCl electrode and 3 M KCl/3% agar bridge). The current-to-voltage converter is connected to the trans compartment of the chamber (via Ag/AgCl electrode and 3 M KCl/3% agar bridge) and serves as a virtual ground (see Note 10). 2. To increase the chances of vesicle fusion, a mix of negatively charged (phosphatidylserine) and neutral (phosphatidylethanolamine) lipids is recommended. The ratio of the lipids can be varied (see Note 11). Lipids are available

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from Avanti Polar Lipids (Alabaster, AL, USA). The lipids should be stored at –20◦ C. The yellow color of the lipids is indicative of oxidation and such lipids should not be used. The solution for forming bilayer should be made daily. 3. The “painting” approach (6, 7) for bilayer formation is recommended; a bilayer is formed by applying a small amount of bilayer-forming solution over the hole in the septum that separates the cis and trans compartments. A membrane with the capacitance of 200–300 pF (0.67–0.95 μF/cm2 ) can be used for vesicle fusion. 3.4. Bilayer Incorporation

1. In a glass vial, mix 20 μL stock of diphytanoyl phosphatidylethanolamine with 10 μL stock of diphytanoyl phosphatidylserine. 2. Dry the lipid mixture under flowing nitrogen. 3. Use 35–60 μL of n-decane (or n-octane) to dissolve dried lipids (to a final lipid concentration of 12.5–25 mg/mL). 4. Add bathing solution to the cis and trans compartments of the bilayer chamber. 5. Connect the trans chamber of the bilayer system to the current–voltage converter using an Ag–AgCl electrode and 3 M KCl–3% agar. 6. Connect the cis chamber of the bilayer system to the voltage source using an Ag–AgCl electrode and 3 M KCl–3% agar. 7. Use “painting” method to form bilayer over the septum aperture using the lipid containing membrane-forming solution in n-decane described in Step 3 (see Note 12). 8. Establish the bilayer membrane formation by following membrane capacitance. 9. Place a small aliquot of the oocyte vesicle suspension into the trans chamber and wait for fusion to occur (see Note 13). 10. The voltage is changed and currents are recorded, stored, and analyzed using a computer running pCLAMP software (Axon Instruments, Burlingame, CA, USA). 11. Sensitivity to amiloride and benzamil is used to dissect ENaC activity in bilayers (see Note 14). 12. Phosphorylation by protein kinase A and MgATP is a requirement to detect CFTR Cl– channel. Also, the CFTR inhibitors (diphenylamine-2-carboxylate, glibenclamide, or anti-CFTR505-511 antibody) can be used to further identify CFTR (see Note 14).

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3.5. Two-Electrode Voltage Clamp System

1. A two-electrode voltage clamp system is designed for recordings of relatively large macroscopic currents from a single large cell such as the Xenopus oocyte in a much simpler manner as compared to the patch clamp technique. Depending on the length of the experimental protocol, tens to hundreds of oocytes can be screened in a week by a skilled operator. 2. Two sharp electrodes are used to impale a single cell. The electrodes act as either a “voltage” electrode or a “current” electrode, the former recording the transmembrane potential and the latter injecting current into the cell. Separate bath electrodes should be used to clamp the bath solution to ground, adding two Ag/AgCl wires which sit either directly in the solution or in an adjacent chamber connected to the oocyte chamber with 3 M KCl/3% agar salt bridges. This reduces the noise levels and helps remove series resistance. The agar salt bridges are advised as silver ions can be toxic to cellular processes and also the Ag/AgCl wires are sensitive to differences in chloride concentrations in the solutions. 3. Unlike single-channel bilayer recordings, two-electrode voltage clamp recordings are macroscopic measurements of all the channels expressed at the membrane of the oocyte. Though single-channel properties may be inferred, the recordings are of a large population of channels which may or may not change depending on trafficking or signaling events. This makes the technique dependent on the complexities of protein networks.

3.6. Two-Electrode Voltage Clamp Recordings of ENaC

1. The tips of two glass electrodes filled with 3 M KCl are lowered into the bath chamber and submerged in the bath solution (see Note 15). The electrical resistance of the individual electrodes should measure between 0.5 and 2 M. The resistance of the current electrode should ideally be less than that of the voltage electrode. Solution should not be actively flowing out of either electrode. 2. A single oocyte is placed within the chamber and the two electrode tips are pressed up against the oocyte. It may help to place a plastic mesh or some sort of support to keep the oocyte from moving into the chamber, though care must be taken to minimize disruption of the solution flow. The oocyte may then be impaled by the electrodes by gently advancing them until they pop through the membrane or by using the “buzz” feature on some amplifies. Minimal force is required to avoid damaging the oocyte and leaking cytosolic contents. Entry can be monitored by examining the voltage recording from the electrodes, as the uninjected oocyte

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resting membrane potential is expected to be in the –30 to –60 mV range, though large variations can be observed. 3. Although electrophysiological protocols vary, for ENaC and CFTR, the oocyte is generally held at a constant voltage, while the whole-cell current is recorded. For ENaC, –60 mV is commonly used to record the inward sodium current. Using voltage steps, it is possible to calculate a chord conductance (g) using Ohms law, Iion = gion (Vm –Vion ), where Vm is the holding potential, while Vion is the reversal potential for the ion. 4. Bath solutions are continuously applied, generally using a gravity-driven perfusion apparatus to bathe the oocyte, maintaining a constant volume of solution in the chamber. To measure the ENaC currents, solutions containing channel blockers such as 10 μM amiloride are bathed over the oocyte and currents are recorded. ENaC inhibition by amiloride should occur rapidly, though the timescale will depend on the perfusion system, and is reversible. The difference between recordings with and without amiloride can be used to determine the amiloride-sensitive ENaC currents. For CFTR, solutions containing a CFTR activator cocktail such as 10 μM forskolin with 0.2 mM 3-isobutyl-1methylxanthine (IBMX) are added. These reagents are used to increase cAMP levels within the oocyte and may take up to 10–15 min to reach full effect; therefore the current must be allowed to stabilize before measurements are made, and these effects are not rapidly reversible. The difference between recordings with and without this cocktail can be attributed to CFTR. When ENaC and CFTR are coexpressed, amiloride-sensitive currents can be measured before activation of CFTR and then repeated after activation of CFTR. The effect of these reagents on water-injected oocytes should be used as a control for endogenous currents. This can allow the isolation of CFTR or ENaC currents in the absence or the presence of the other. 5. In oocytes expressing CFTR alone, currents are not sensitive to 10 μM amiloride before or after activation of CFTR. Activation of CFTR by forskolin and IBMX leads to an increased outward chloride flux. 6. In oocytes expressing ENaC alone, application of 10 μM amiloride leads to a rapid reduction of the macroscopic current. Application of forskolin and IBMX has little to no effect on the amiloride-sensitive current. 7. In oocytes expressing both ENaC and CFTR, a smaller amiloride-sensitive current is observed before CFTR activation, showing a decrease in ENaC activity or expression.

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After amiloride washout, a forskolin- and IBMX-induced current is observed that is larger than when CFTR is expressed alone, indicating an increase in the CFTR activity or expression by the presence of ENaC. Further application of amiloride following CFTR activation shows a further reduced amiloride-sensitive current. 8. Succinctly, the presence of ENaC increases CFTR currents, while the presence of CFTR decreases ENaC currents, and activation of CFTR further reduces ENaC currents (see Note 16). 3.7. Cell Culture, Transient Transfection, Coimmunoprecipitation

1. Perform the cell culture and transient transfection under sterile technique in a laminar flow hood (8). 2. Maintain human embryonic kidney 293T (HEK293T) cells in DMEM media (GIBCO) supplemented with 10% FBS (HyClone) and penicillin/streptomycin (GIBCO) in tissue culture-treated flasks at 37◦ C with 5% CO2 . 3. One day before transfection, subculture the cells using trypsin and seed the cells in 35-mm dishes or six-well plates (see Note 17). 4. When the cells reach 80% confluence (usually on the second day), transiently transfect them with construct(s) of interest using Lipofectamine 2000 (Invitrogen). 5. Dilute 2.5 μL of Lipofectamine 2000 (2.5 μL Lipofectamine 2000/μL of cDNA) reagent with 100 μL of OptiR I and incubate at room temperature for 5 min. MEM Separately, dilute 1 μg of each cDNA construct with 100 R I. Incubate for 5 min; combine the μL of Opti-MEM diluted cDNA constructs with diluted Lipofectamine 2000 and allow 20 min for complex formation. 6. After incubation, add the transfection solution (containing the cDNA/Lipofectamine 2000 complex) to the cells in R I. Opti-MEM 7. Incubate the cells for 5 h at 37◦ C in a CO2 incubator. 8. After incubation, change the transfection solution to regular growth medium without antibiotics. 9. Perform co-IP studies after 24–48 h of incubation to allow for protein expression.

3.8. Preparation of the Samples for Detection by Western Blotting

1. Lyse the cells by adding 200 μL (per well of a six-well plate) of lysis buffer and leave on ice for 10 min. Then pipette up and down to homogenize and transfer to a centrifuge tube. 2. Discard non-soluble material with centrifugation (15,800×g for 10 min at 4◦ C).

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3. Keep 20 μL of supernatant (lysate) and incubate the rest of the supernatant with 1 μg of carboxy-terminal CFTR monoclonal antibody (R&D Systems, 24-1) cross-linked to 25 μL A/G agarose beads (Santa Cruz Biotechnology) for 2 h at 4◦ C (see Note 18). 4. Pellet the beads with centrifugation (3,000×g for 2 min) and wash three to five times with cold PBS containing 0.2% Triton X-100. 5. Elute the proteins from the beads by adding 5 μL of 5× SDS sample loading buffer and incubate for 10 min at 37◦ C. 3.9. SDS-PAGE and Transfer

1. When using precast ready gels, remove the comb and rinse the wells with distilled water. 2. Remove the seal located at the bottom of the gel as indicated in the manufacturer’s instructions. 3. Insert the gel in the unit and place them in the tank (mini PROTEAN system from Bio-Rad). 4. Add the diluted running buffer to the tank. 5. Load each supernatant from the co-IP to the wells. Include one well that will contain the prestained molecular weight markers (Precision Plus from Bio-Rad). 6. Complete the assembly of the unit and connect to a power supply that will be set to 200 V for 30–45 min. The gel can be run at room temperature or at 4◦ C. 7. Set up the transfer by immersing the PVDF membranes into methanol for 5–10 min. The PVDF membrane should be of the size of the gel. 8. Equilibrate the membranes by immersing them in transfer buffer for 15 min. 9. Take the gels (containing the proteins) and incubate in transfer buffer for 10 min. 10. Assemble the gel and the PVDF membrane so that the separated proteins present in the gel will be transferred to the PVDF membrane. The orientation of the gel can be marked by cutting a corner of the membrane. 11. Set up the assembly into a Bio-Rad Trans Blot Cell and add the cold transfer buffer (see Note 19). Connect to a power supply that will be set to 60 V for 1.5 h (if Trans Blot Cell with wire electrodes) or 80 V for 35 min (if Trans Blot Cell with plate electrodes). The transfer unit should be placed at 4◦ C.

3.10. Western Blotting for CFTR and ENaC

1. Unassemble the gel/PVDF membrane sandwich and rinse the membrane with distilled water. Make sure to place the side of the PVDF membrane that was in contact with the

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gel face up. This is the side that will be exposed to the film in Step 10. The molecular weight markers should now be present on the membrane. 2. Use a container that is close to the size of the PVDF membrane (blot). Add enough blocking solution to cover the blot (≈10 mL) and leave on rotator for 1 h at room temperature. 3. Add the anti-ENaC Ab that recognizes the different ENaC subunits diluted in antibody dilution buffer. Leave for 2 h at room temperature or overnight at 4◦ C. 4. Remove the primary antibody and wash with TBS/0.1% Tween-20 by adding 10 mL five times for 5 min each. The box containing the blot is placed on a rotator to enhance the washing. 5. Incubate the blot with 10 mL blocking solution for 10 min at room temperature. 6. Add the secondary antibody (anti-rabbit HRP from Pierce) at a dilution of 1/10,000 for 1 h at room temperature. 7. Repeat Step 4 (washings). 8. Remove the blot from the box and blot it to remove excess washing buffer by blotting the membrane with Kim-Wipes. Place in a clean box and add West Pico (Pierce) solution. Leave the solution for 5 min at room temperature. 9. Take the blot and remove the excess West Pico solution by blotting the membrane with Kim-Wipes. 10. Place the blot in a sheet protector and place in an X-ray film cassette. 11. In a dark room, add a film on the top of the sheet protector containing the blot and expose the film for a few seconds to several minutes depending on the intensity of the signals (see Fig. 3.2 for an example of the results). 12. Always run controls to assure the specificity of the association (see Note 20).

4. Notes 1. It is important that only nuclease-free water and appropriately prepared (nuclease-free) material are used to prevent cRNA degradation. 2. The bilayer setup can be assembled from both manufactured and homemade components (9–11). On the other hand, the complete bilayer setup (vibration isolation table,

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Faraday cage, amplifier, Bessel filter, cups and chambers, and various accessories) can be purchased from Warner Instruments. 3. Ag/AgCl electrodes are prepared by “chloriding” a silver wire in bleach for 10 min. 4. The content of the bathing solutions is dependent on the channel of interest. 5. The two-electrode system is contained within a Faraday cage to remove external electrical interference and requires the use of a stable platform to minimize vibration within the system. Although a fully active vibration isolation table is recommended by some, it is not essential. Furthermore, the micromanipulators used do not need to be electronically controlled or as finely controlled in movement as those required for patch clamp system as the dimensions traveled are much larger with the oocyte. However, drift or uncontrolled movements are dangerous, especially with long experiments where irreversible mechanical damage can occur to the oocytes. 6. There are multiple chambers available. Homemade chambers can be designed using a simple Petri dish. It is important that the perfusion system and the chamber used allow for relatively stable levels of solution with relatively laminar flow as the oocytes are sensitive to mechanical damage and the electrical recordings are sensitive to solution levels. 7. Prewarm the DMEM, Opti-MEM, and trypsin–EDTA solution to 37◦ C in a water bath; before transferring to the hood, decontaminate by wiping the surface of the bottles/tubes with 70% ethanol. 8. The addition of sodium azide to a final concentration of 0.02% can save primary antibodies for subsequent experiments. 9. cRNA for oocyte injection is made and purified with the Ribomax kit plus RNA cap analogue and GeneClean kits, respectively. 10. A magnetic bar and a stirring device, along with a perfusion system, are components of a bilayer setup. The bathing solutions should be made daily and filtered. The experiments are usually performed at 25 ± 10◦ C. 11. The lipid types/ratios as a bilayer-forming solution can be varied. 12. The pre-treatment of septum aperture with bilayer-forming solution (3–5 min before filling the compartments of chamber with bathing solution) helps bilayer formation and stability.

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13. The fusion can be promoted by bringing a fire-polished glass rod dipped into oocyte vesicle suspension in close proximity to the pre-formed planar bilayer membrane from the trans side. If this approach is implemented, the bilayer membrane should be clamped at a negative voltage. Following incorporation of ENaC into the planar bilayer, channels of uniform conductance with well-defined gating transitions become apparent. 14. The fusion of ENaC-containing vesicles results in the appearance of the conductance with well-defined gating. The CFTR is known to decrease the open probability (the time channel spends in open time) of ENaC. The CFTR effect on ENaC can be assessed using vesicles containing CFTR and ENaC. Alternatively, the ENaC vesicles can be incorporated first into bilayers followed by coincorporation of the CFTR-containing vesicles. However, the co-incorporation approach is technically difficult, and we recommend the incorporation of the vesicles containing both CFTR and ENaC. First, the vesicles are incorporated into bilayers and ENaC activity is measured. Then, CFTR activity is elicited by phosphorylation of the channel. Further, the CFTR identity is dissected by applying glibenclamide (the CFTR inhibitor), while the ENaC activity is blocked by amiloride (Fig. 3.1). 15. The glass electrodes tend to get clogged after extended use but they may be reused between oocytes if the resistance stays within 0.5–2.0 M. Multiple electrodes can be prepared in advance using a large container with clay to hold the glass in place and keep the tips from breaking. Depending on conditions, they may need to be covered to prevent dust and debris from accumulating, but these tips are less sensitive than patch electrodes. As with most glass electrodes backfilled with electrolyte solutions, bubbles are a serious problem, but these tips are generally easier to fill than patch clamp electrodes and can be easily backfilled with a MicroFil 34-gauge needle from World Precision Instruments, Inc. The 3 M KCl can be pushed through a syringe filter to remove debris. 16. Studies of ENaC and CFTR in the oocyte system are conflicting (see Ref. 2). In our hands, the results we share are readily apparent. The work of Georg Nagel has suggested that there is no electrophysiological interaction, finding no basal inhibition of ENaC by the presence of CFTR and no inhibition following activation of CFTR (12, 13). These authors suggest that the observations of an interaction are merely artifacts due to a combination of CFTR’s large conductance and a high series resistance due to improperly

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Fig. 3.1. CFTR modulation of αβγ-ENaC in bilayers. First, oocyte vesicles expressing ENaC alone were fused with bilayers (top trace) which spent roughly 52% of time in open state. The time spent in open state by ENaC decreased to roughly 37% with subsequent fusion of the oocyte vesicles expressing CFTR into bilayers (second trace; also, the same effect was observed with the bilayer fusion of the oocyte vesicles co-expressing both CFTR and ENaC). The phosphorylation (PKA+MgATP, third trace) revealed the presence of the CFTR which was inhibited by anti-CFTR antibodies (fourth trace, left panel) leaving only ENaC activity which in turn was inhibited by amiloride (fifth trace, left). If, on the other hand, amiloride was applied after phosphorylation, the CFTR activity was evident (fourth trace, right panel), which in turn was inhibited by DPC addition (fifth trace, right panel). This research (15) was originally published in The Journal of Biological Chemistry. Ismailov et al., 1996; 271:4725–4732. © The American Society for Biochemistry and Molecular Biology.

configured or absent bath electrodes (12, 13). Others have found no basal inhibition of ENaC by CFTR but rather one dependent solely upon the Cl– channel activity of CFTR (for review see 14). The discrepancies between the results have yet to be satisfactorily resolved. 17. The number of cells seeded should be that they reach 80% confluence the next day.

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Fig. 3.2. (a) β-ENaC co-immunoprecipitation with CFTR. Only simultaneous presence of both CFTR and β-ENaC, with the combinations of α/β-ENaC, β/γ-ENaC, or β-ENaC with CFTR (lanes 2–5), resulted in co-IP signal. The absence of either CFTR (lane 1) or β-ENaC (lane 6) eliminated the co-immunoprecipitation signal. The presence (lane 7) or the absence (lane 8) of β-ENaC signal was confirmed in lysates. The bottom panel of the figure shows the same blot reprobed with anti-CFTR Ab to confirm the presence of CFTR in the immunoprecipitate. (b) β-ENaC does not immunoprecipitate with the Cl– channel ECFP–CLCN1. Anti-GFP monoclonal Ab JL-8 (BD Living Colors) was used to immunoprecipitate CLCN1, and the blot was probed with the β-ENaC Ab. The expression of CLCN1 in the cells was confirmed using GFP Ab (lanes 2 and 4). An Ab against β-ENaC failed to detect a co-IP signal in immunoprecipitate of cells co-expressing β-ENaC and CLCN1 (lane 4, bottom panel). The expression of β-ENaC in the lysates was confirmed (lanes 1 and 2). This research (8) was originally published in The Journal of Biological Chemistry. Berdiev et al., 2007; 282:36481–36488. © The American Society for Biochemistry and Molecular Biology.

18. Keep 20 μL of cell lysate to confirm the expression of the ENaC subunits (see Fig. 3.2a, last two lanes). 19. Assemble the gel/PVDF membrane like a sandwich. Add the first sponge that was soaked in transfer buffer on the top of the black plate, then add a piece of Whatman paper that was wetted in transfer buffer, add the gel, then the PVDF membrane, and another piece of Whatman paper (wetted

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in transfer buffer). At this step, use a roller to eliminate any bubble that could be present between the gel and the PVDF membrane. Add the second sponge and close the sandwich with the red plate. 20. To check for the possibility that ENaC subunits bind nonspecifically to the beads, the ENaC subunits are expressed and incubated with non-specific antibody cross-linked to A/G beads. It is also possible that CFTR and ENaC binding occurs postlysis. Therefore, two sets of cells are transfected with ENaC subunits or CFTR cDNA. Mix these two lysates and perform coIP experiments; no ENaC signal suggests that the interaction between CFTR and ENaC does not occur post-lysis. Additionally, always reprobe the same blot with anti-CFTR Ab to confirm the presence of CFTR in the IP (Fig. 3.2a, bottom panel). Finally, substitute the CFTR with another Cl– channel that is not thought to interact with ENaC (ECFP–CLCN1, for example) and perform co-IP experiments. The absence of the co-IP signal suggests that ENaC does not interact with the chloride channel CLCN1 (Fig. 3.2b); this strengthens the specificity of the CFTR and ENaC association. As can be seen from Fig. 3.2b, we were unable to co-IP β-ENaC with ECFP–CLCN1. In this approach we used anti-GFP monoclonal Ab JL-8 (BD Living Colors) that recognizes CFP protein to IP CLCN1 and then probed with the β-ENaC Ab. The expression of CLCN1 in the cells was confirmed using GFP Ab (Fig. 3.2b). The cells expressing αβγ-ENaC and/or ECFP–CLCN1 were IPed with an Ab against GFP. While this Ab detected ECFP–CLCN1 in both crude lysates and IP of ECFP–CLCN1-expressing cells, an Ab against β-ENaC failed to detect a band in IP of co-expressing cells (top panel and right-hand lanes of bottom panel). However, this Ab did detect βENaC in the crude lysates from cells expressing either αβγ-ENaC alone or those co-expressing ECFP–CLCN1. These data suggest that β-ENaC does not interact with the chloride channel CLCN1.

Acknowledgments ENaC cDNAs were a kind gift of Dr B. Rossier (University of Lausanne, Lausanne, Switzerland). This work was supported by NHLBI grant R21HL085112 (BKB), UAB Health Services Foundation General Endowment Fund (BKB), and NIH grant DK37206 (DJB).

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References 1. Kunzelmann, K. (2001) CFTR: interacting with everything. News Physiol Sci 16, 167– 170. 2. Berdiev, B. K., Qadri, Y. J., and Benos, D. J. (2009) Assessment of the CFTR and ENaC association. Mol Biosyst 5, 123–127. 3. Awayda, M. S., Ismailov, I. I., Berdiev, B. K., and Benos, D. J. (1995) A cloned renal epithelial Na+ channel protein displays stretch activation in planar lipid bilayers. Am J Physiol 268, C1450–C1459. 4. Ismailov, I. I., Awayda, M. S., Berdiev, B. K., Bubien, J. K., Lucas, J. E., Fuller, C. M., et al. (1996) Triple-barrel organization of ENaC, a cloned epithelial Na+ channel. J Biol Chem 271, 807–816. 5. Perez, G., Lagrutta, A., Adelman, J. P., and Toro, L. (1994) Reconstitution of expressed KCa channels from Xenopus oocytes to lipid bilayers. Biophys J 66, 1022–1027. 6. Mueller, P., Rudin, D. O., Tien, H. T., and Wescott, W. C. (1962) Reconstitution of cell membrane structure in vitro and its transformation into an excitable system. Nature 194, 979–980. 7. Mueller, P., Rudin, D. O., Tien, H. T., and Wescott, W. C. (1962) Reconstitution of excitable cell membrane structure in vitro. Circulation 26, 1167–1171. 8. Berdiev, B. K., Cormet-Boyaka, E., Tousson, A., Qadri, Y. J., Oosterveld-Hut, H. M. J., Hong, J. S., et al. (2007) Molecular proximity of cystic fibrosis transmembrane conductance regulator and epithelial sodium channel assessed by fluorescence resonance

9.

10.

11. 12.

13.

14.

15.

energy transfer. J Biol Chem 282, 36481– 36488. Alvarez, O. (1986) How to set up a bilayer system, in (Miller, C., ed.), Ion Channel Reconstitution. Plenum Press, New York, NY, pp. 115–139. Alvarez, O., Benos, D. J., and Latorre, R. (1985) The study of ion channels in planar lipid bilayer membranes. J Electrophys Tech 12, 159–177. Hanke, W., and Schlue, W. R. (1993) Planar Lipid Bilayers. Academic, San Diego, CA. Nagel, G., Szellas, T., Riordan, J. R., Friedrich, T., and Hartung, K. (2001) Nonspecific activation of the epithelial sodium channel by the CFTR chloride channel. EMBO Rep 2, 249–254. Nagel, G., Barbry, P., Chabot, H., Brochiero, E., Hartung, K., and Grygorczyk, R. (2005) CFTR fails to inhibit the epithelial sodium channel ENaC expressed in Xenopus laevis oocytes. J Physiol 564, 671–682. Kunzelmann, K. (2003) Control of membrane transport by the cystic fibrosis transmembrane conductance regulator, in (Kirk, K. L., and Dawson, D. C., eds.), The Cystic Fibrosis Transmembrane Conductance Regulator. Kluwer Academic/Plenum Publishers, New York, NY, pp. 55–93. Ismailov, I. I., Awayda, M. S., Jovov, B., Berdiev, B. K., Fuller, C. M., Dedman, J. R., et al. (1996) Regulation of epithelial sodium channels by cystic fibrosis transmembrane conductance regulator. J Biol Chem 271, 4725–4732.

Chapter 4 Methods for Evaluating Inflammation in Cystic Fibrosis Assem G. Ziady and Pamela B. Davis Abstract Cystic fibrosis is characterized by excessive pulmonary inflammation, which presents early in life and becomes self-sustaining, eventually leading to the destruction of the lung. Treating inflammation is one of the most pressing needs in CF therapy and has been shown to slow lung function deterioration. However, it remains unclear whether excessive inflammation is a direct result of CFTR dysfunction, and thus innate, or develops in response to early stimulation of inflammatory pathways. Here, we will discuss clinically relevant studies and the methods employed by them. We will focus on investigations in cell and animal models as well as patients. Our discussion will describe the character of pulmonary inflammation in CF and present potential therapeutic approaches that can ameliorate excessive responses and improve disease prognosis. Key words: Inflammation, cytokines, transcription factors, anti-inflammatory agents.

1. Introduction Inflammation is a hallmark of cystic fibrosis (CF). Early in life, patients begin to exhibit exaggerated inflammatory profiles, especially in the lungs (1–4) in response to infection. Over time, these responses become more persistent and contribute to the destruction of lung tissue, pulmonary function deterioration, respiratory failure, and death. It is unclear whether infection causes the excessive inflammation observed in CF or whether dysfunction of the cystic fibrosis transmembrane conductance regulator (CFTR) in itself results in aberrant cell signaling that gives rise to abnormal inflammatory responses. A number of studies have described increases in pathways that promote inflammation (1–10) and decreases in pathways that are anti-inflammatory M.D. Amaral, K. Kunzelmann (eds.), Cystic Fibrosis, Methods in Molecular Biology 742, DOI 10.1007/978-1-61779-120-8_4, © Springer Science+Business Media, LLC 2011

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(11, 12), even in the absence of bacteria. However, many of these studies were conducted in immortalized cell line models of CF and thus require validation in animal models or primary CF patient tissues. Clinically, this has been a difficult issue to address. Reports of increased inflammatory cytokine production in the healthy non-infected lungs of CF newborns (13) do not preclude the possibility of recent infections that had cleared by the time of examination. Therefore, it is difficult to distinguish between the presence of innate abnormalities in inflammatory signaling and residual inflammation from prior infection. Other reports have focused on reduced airway clearance, which is directly linked to the lack of chloride ion secretion through functional CFTR and exaggerated sodium absorption through the epithelial sodium channel (ENaC), as the cause of increased bacterial adherence and established infections that perpetuate inflammatory signaling (14). Nevertheless, it is not disputed that inflammation exists and that controlling it provides significant benefits to patients (15, 16). Evaluations of inflammation and its impact on disease progression have been conducted on two levels: assessing inflammation using clinical samples obtained from patients and elucidating mechanisms that influence inflammation in primary cells and models of CF. Studies in patients have revealed that excessive levels of inflammatory cytokines (4–7) are produced in response to infection. Anti-inflammatory drugs, such as ibuprofen, are effective in limiting lung deterioration (15), but adverse effects have discouraged the use of both steroidal and non-steroidal anti-inflammatory drugs (16, 17). Nevertheless, alternative antiinflammatory therapies are an active area of research (18). To evaluate mechanisms that contribute to inflammation, investigators have relied on a variety of cell and animal models. The development of a number of immortalized matched epithelial cell pair models has allowed researchers to conduct the majority of mechanistic studies in the field, identifying the contribution of aberrant ion transport (14), protein expression (19) and processing (20), redox signaling (21), and lipid processing (22) to the proinflammatory phenotype. However, the field has called for the confirmation of these relationships in vivo or in primary cell culture, so methods have been developed to allow for the culture of primary airway epithelia collected from tissue discarded at transplantation, explants, or nasal scrapings from patients, as well as differentiated cells (23–25). The development of animal models has also been very active. However, no CF mouse model develops spontaneous pulmonary inflammation, and manipulations that force the establishment of infection are required to elicit differential inflammatory responses in the lung. Furthermore, there are significant anatomical differences between mice and humans; for example, submucosal glands, which are present in the human airway and

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believed to be a key site of CF airway disease, are rare in the mouse airway (26). Recent introduction of the ferret (27) and pig (28) models of CF that develop many of the phenotypes associated with CF without manipulation is very promising. Much of the current understanding of the inflammatory process in CF patients has come from sampling the airway surface liquid (ASL) via bronchoscopy and bronchoalveolar lavage (BAL). Cytokine content of BAL remains the best surrogate measure of inflammation in patients (4). BAL from young infants, even if not infected, contains elevated proinflammatory cytokines (4, 8). Studies focused on assessing inflammatory cell behavior in the CF lung find persistent infiltration of neutrophils in response to chemoattractants secreted by macrophages, epithelial cells, and the neutrophils themselves (29). Neutrophils also secrete oxidants and proteases and are the major source of DNA that increases the viscosity of CF sputum (4). In cell culture, investigators have assessed inflammation by measuring cytokines secreted by CF model cell lines or primary culture of CF epithelia following stimulation, compared with normal controls. Other studies have focused on the examination of intracellular signaling cascades including genes, proteins, or lipids that impact inflammation by gene array (30, 31), proteomic analyses (19, 21), or direct measurement. In general, these reports find an increase in the expression and/or activity of proinflammatory and a decrease in anti-inflammatory mediators. Many of these studies and their findings have been extended to and confirmed in CF animal models by sampling the BAL (32), micro-dissected (33) or whole lung (21, 32), and/or bowel tissues (34). For the most part, the proinflammatory characteristics observed in stimulated cells in cell culture have been reproduced in CF mouse tissues stimulated with inflammatory cytokines (32), bacteria (23, 30), or bacterial components (18). But the lack of inflammation in the unstimulated state continues to raise concerns about this model. Therefore, investigators have begun to evaluate cytokine, gene, and protein expression profiles in newer CF models in ferrets and pigs, both of which spontaneously develop inflammatory disease.

2. Materials For the purposes of this discussion, we will focus on airway epithelial cell models of CF. For in vivo studies, although CF models are now available in mice, ferret, and pig, we will outline materials and methods for use in studies of inflammation in the lungs of mice ∼25 g in weight. However, these methods can be extended to larger animal models.

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2.1. Cell Culture, Stimulation, and Treatment with Compounds

1. CF cell models of choice: We commonly use two airway epithelial cell lines and human primary tracheal epithelia (HTE) for our studies. For the cell lines, we use the 9HTEo− pCEP and pCEP-R cell pair and the 16HBEo− sense (S) and antisense (AS) cell pair. 9HTEo− cells are immortalized human tracheal epithelia that are stably transfected with an empty pCEP construct to produce normal controls or a pCEP-R construct that encodes for the regulatory (R) domain of CFTR to produce cells that lack CFTR function, but not CFTR itself (35). 16HBEo− are human bronchial epithelial cells that are stably transfected with a sense (S, normal control) or antisense (AS, CF cell pair) construct of nucleotides 1–131 of CFTR and which lack CFTR (35). For primary cell culture, we obtain cells from necropsy under institution-approved protocols. 2. 10% FCS in appropriate cell culture media as needed (see Note 1). For primary cell culture we use Ultra-ser G (Biosepra Inc., Marlborough, MA). 3. Selection compounds, such as hygromycin or G418, as needed. 4. Antibacterial and/or antimycotic compounds, such as penicillin, streptomycin, or fungizone, as needed (see Note 2). 5. Tissue culture-treated welled plates with or without semipermeable membrane inserts (Costar; Corning Inc., Corning, NY). 6. PBS: Dulbecco’s phosphate-buffered saline. 7. For mass spectrometric quantitation of labeled protein, protein labels (i.e., non-abundant isotopes of carbon or nitrogen) may be added to cell culture media as a supplement. 8. Ion channel modulating compounds, such as inhibitors of CFTR, which can produce the CF phenotype in treated cells (23). We usually use 20 μM CFTRinh -172 (SigmaAldrich, St. Louis, MO) in DMSO (see Note 3). 9. Stimulants such as bacteria, cytokines, or bacterial components can be used to activate inflammatory signaling. We have used 105 –109 cfu/mL of a laboratory strain of Pseudomonas aeruginosa, PAO1 (23, 32), 1 μg/mL LPS derived from P. aeruginosa (Sigma-Aldrich), or 10–100 ng/mL recombinant human tumor necrosis factor alpha (TNF-α) and 10–100 ng/mL recombinant human interleukin 1 beta (IL-1β). 10. For anti-inflammatory agents, we have used triterpinoids such as 2-cyano-3,12-dioxooleana-1,9 (11)-dien-28-oic

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acid (CDDO, 300 nM), pioglitazone (Cayman Chemical), and antioxidants such as N-acetyl cysteine. 2.2. Animal Models, Stimulation, and Treatment with Compounds

1. A number of CF animal models are available in mice (see Note 4). Some commonly used mouse models bred into the C57BL/6 background are the UNC knockout mouse (B6.129P2-Cftrtm1Unc ) and mutant murine Cftr mice such as the R117H mutant mouse (B6.129S6-Cftrtm2Mrc ). The gut-corrected knockout mouse (Cftrtm1Unc -TgN(FABPCFTR)#Jaw) is a more robust model that exhibits good survival. Ferret (27) and pig (28) models of CF are also available for study (see Note 5). 2. There is an age and sex effect on inflammatory responses. We prefer male mice that are 6–12 weeks old. 3. Animals should be housed in a sterile environment such as microisolator cages for mice. 4. Our preferred anesthetic cocktail is made up of 2.13 mg/mL xylazine, 0.36 mg/mL acepromazine, and 10.75 mg/mL ketamine. 5. One milliliter syringe with 27.5 or 30 gauge needle for intraperitoneal (IP) or intravenous (IV) injection, respectively. Larger gauge needles should be used as needed for larger animals. 6. To simplify IT administration or intubation of mice, a tilting workstation (Hallowell, Pittsfield, MA), animal laryngoscope (PennCentury, Philadelphia, PA) fitted with a magnifier to improve visualization, and a MicroSprayer (PennCentury, Philadelphia, PA) are useful. 7. For intratracheal (IT) administrations in mice, a 22 gauge plastic catheter (Abbocath; Abbot Laboratories) is used. Bronchoscopes have been used for larger animals. 8. Stimulation of inflammation is achieved with bacteria or their components. We have used 106 –109 cfu/mouse of PAO1 (23, 32) or 40 μg/kg LPS derived from P. aeruginosa (Sigma-Aldrich). 9. For anti-inflammatory agents, we have used 10–50 μg/kg CDDO, 30 mg/kg pioglitazone (Cayman Chemical), and antioxidants such as NAC. 10. A 24 or 18 gauge feeding needle can be used for mouse BAL collection or gavage, respectively. Bronchoscopes have been used for larger animals. 11. Enclosed chamber connected to a carbon dioxide gas tank and a charcoal filter (see Note 6).

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12. PBS: Dulbecco’s phosphate-buffered saline. 13. Protease inhibitor cocktail: one Complete Mini protease inhibitor tablet (Roche) + 10 mL PBS. 2.3. Measurement of Secreted Cytokines and Chemokines

1. Media collected from the apical surface of cultured cells or BAL fluid collected from animal. 2. Individual ELISA analysis kits (R&D Systems or Antigenix America Inc., for example) are widely available for the sensitive measurement of commonly measured proinflammatory mediators including IL-1β, IL-2, IL-4, IL-6, IL-8, IL-9, IL-19, GM-CSF, and TNF-α. In mice, the chemokine macrophage inflammatory protein (MIP)-2 and KC/N51 are analogs of human IL-8. ELISA kits are also available for the measurement of anti-inflammatory cytokines, such as IL-10. 3. An alternative to individual kits is the use of multi-analyses kits that measure a number of cytokines in the same biological sample. We have used the LINCOplex Multiplex kit (Linco Research, St. Charles, MO). 4. Urea detection kit for the measurement of urea in serum. A number of sensitive kits are available, such as the Infinity Urea Liquid Stable Reagent (Thermo Fisher Scientific, Inc.). 5. PBS: Dulbecco’s phosphate-buffered saline. 6. Protease inhibitor cocktail: one Complete Mini protease inhibitor tablet (Roche) + 10 mL PBS. 7. To assess bacterial load in fluids or tissue homogenates, sterile blood agar plates are used.

2.4. Histology and Immunohistochemical Staining

1. BAL or lungs harvested from CF mice and normal littermate. 2. Tissue freezing medium, such as OTC (Triangle Biomedical Sciences). 3. Paraformaldehyde dissolved in PBS at 2.5% wt/vol. 4. Paraffin wax and xylene (Thermo Fisher Scientific, Inc.). 5. Tissue microtome. 6. Hematoxylin and eosin stains (Sigma-Aldrich, St. Louis, MO). 7. Protein-of-interest specific primary antibody (Ab) and secondary HRP conjugated, or similar, Ab (see Note 7). 8. 10 mM sodium citrate buffer (pH 6.0). 9. Solution of 3% hydrogen peroxide in PBS. 10. Suitable substrate for HRP or otherwise Ab-conjugated catalytic enzyme.

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1. Rehydration/solubilization buffer: 7 M urea, 2 M thiourea, 1% DTT, 1% CHAPS, 1% ampholytes, and 1% Triton. Mix 2.1 g urea, 0.8 g thiourea, 50 mg CHAPS, 50 mg DTT, 50 μL BioLytes (BioRad), 50 μL Triton X-100. Bring volume up to 5 mL with water and dissolve with shaking (see Note 8). 2. Loading dye stock solution: 1% bromophenol blue in water. 3. Electrode wicks (Biorad), wetted with water. 4. 1D gel band or 2D gel IPG pI strip equilibration buffer: mix 5.4 g urea, 0.3 g SDS, 3.8 mL 1.5 M Tris-HCl (pH 8.8), and 3 mL glycerol in a 50 mL centrifuge tube. Adjust the total volume to 15 mL with water. Dissolve by shaking. 5. Protein reducing reagent: 120 mg DTT in 7.5 mL equilibration buffer. 6. Protein alkylation reagent: 150 mg iodoacetamide in 7.5 mL equilibration buffer with 100 μL 1% BPB. 7. Agarose for sealing 2D gel IPG pI strip (Biorad). This reagent can be stored at RT and used repeatedly over several months. 8. Running buffer suitable for purchased precast gel. For example, 1X Biorad Tris-glycine buffer. Cool on ice before use. 9. To decrease sample contamination, the use of precast gels is recommended. We use Criterion precast 1D or 2D gels (Biorad). 10. Gel-fixing solution: 50% ethanol and 10% acetic acid in water. 11. Protein label, such as GelCode BlueTM Coomassie stain (Pierce Biotechnology, Inc., Rockford, IL).

2.6. Western Blot Analyses

1. Primary Ab, suitable for Western blotting, raised against protein of interest. For inflammatory signaling, we have blotted for transcription factors such as NF-κB (18) or PPARγ (33). 2. Secondary Ab raised against the primary Ab species and conjugated to detectable enzyme, such as HRP. 3. 1D or 2D gel of CF and normal control cells or tissues. We often run different fractions of the cell (e.g., nuclear or cytoplasmic). 4. Immunoprecipitation (IP) buffer: 1% Triton X-100, 150 mM NaCl, 10 mM Tris, pH 7.4, 1 mM EDTA, and protease inhibitor cocktail. 5. Transfer buffer: 25 mM Tris, 190 mM glycine, and 10–20% methanol (vol/vol) in water. SDS

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(0.1–0.5% wt/vol) addition is sometimes necessary for the transfer of large proteins (>40 kDa). 6. Wash buffer: Tris-buffered saline (pH 7.4) with 1% Tween. 7. We use different blocking solutions depending on the protein of interest. We commonly use 5% nonfat dry milk in TBS-T or membrane blocking solution (Invitrogen, Inc.). 8. Polyvinylidene fluoride (PVDF) or nitrocellulose membranes (Millipore, Bedford, MA). 9. Enhanced chemiluminescence (ECL) reagent (Pierce, Rockford, IL). 2.7. Analysis of Promoter and/or Transcription Factor Activity

1. For evaluation of promoter activity, we use a luciferase assay-based analysis. For example, we have used firefly luciferase expression cassettes under the control of promoters for NF-κB (18), IL-8 (18), or Nrf2 (21, see Note 9). A control plasmid codes for Renilla luciferase under the control of a viral promoter (e.g., SV40). 2. For analysis of transcription factor activity, we use an ELISA-based approach such as the TransAM NF-κB p50 assay (Active Motif, Carlsbad, CA). 3. Cytoplasmic and nuclear fraction kit (Panomics). 4. Dual-Luciferase Reporter assay system (Promega, Madison, WI). 5. For examinations in cell culture, a suitable transfection reagent (see Note 10), such as LipofectinTM or Lipofectamine (Invitrogen, Inc.). 6. Plate reading luminometer. 7. For studies in animals, transgenic mice can be engineered to express luciferase under the control of a promoter of interest. 8. Animals can be imaged by a real-time bioluminescence imaging instrument, such as the Xenogen 200 (Caliper Life Sciences, Hopkinton, MA), which employs a CCD camera to sensitively detect photons emitted from tissues in living animals. 9. Small animal (<500 g): usually, we use mice that are 6–12 weeks old. All experimental groups should be age, sex, and strain matched. 10. Anesthetic cocktail as described in Section 2.2. 11. One milliliter syringe with small gauge needle (<25 gauge) for IP injections. 12.

D -Luciferin (Biosynthesis, Naperville, IL) dissolved at 30 mg/mL in PBS immediately before use.

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1. Treated and non-treated cultured CF cells, animal tissue, or laser-microdissected tissue fractions. 2. Phosphate-buffered saline (PBS). 3. RNA extraction system, such as ULTRASPEC RNA (Biotecx, Houston, TX). 4. Control transcripts, such as the prokaryotic genes bioB, bioC, bioD (genes for the biotin synthesis pathway from Escherichia coli). 5. Gene hybridization chip, such as the HG-U95Av2 chip (Affymetrix, Santa Clara, CA). 6. Gene chip reader, such as the Hewlett-Packard G2500A GeneArray Scanner. 7. Gene array examination software, such as Affymetrix MicroArray Suite version 5.0 (Affymetrix, Santa Clara, CA). 8. Computer suitable for controlling the gene array scanner and processing the data.

2.9. Proteomic Analyses

1. Cell pellet or section of tissue (see Note 11). 2. Polypropylene (15 mL) centrifuge tubes. Polypropylene is required for acetone precipitation. 3. Protease inhibitor cocktail: one Complete Mini protease inhibitor tablet (Roche) + 10 mL PBS. 4. Tris stock solution pH 7.8. Mix 0.5 M Tris-HCl, 50 mM MgCl2 . Mix 3 g Tris base, 0.3 g MgCl2 in 40 mL water, adjust pH with 6 M HCl, and bring total volume to 50 mL with water. 5. Suitable cell lysis buffer. Mix 0.5% SDS (wt/vol), 25 mM Tris-HCl (pH 7.8), 2.5 mM MgCl2 in water as needed (see Note 12). 6. Nuclease reagent: 1 mg/mL DNase, 1 mg/mL RNase (see Note 12). 7. HPLC-grade acetone, water, acetic acid (99.9%), acetonitrile (Burdick and Jackson, McGraw Park, IL), and ethanol at 95% USP grade. 8. Solubilization buffer solution: mix 7 M urea, 2 M thiourea, 1% DTT, 1% CHAPS, 1% ampholytes, 1% Triton in water and dissolve with shaking (see Note 8). 9. Nonstick low protein-binding Eppendorf tubes should be rinsed with ethanol prior to use. 10. Sequencing-grade modified trypsin (Promega Corp., Madison, WI). 11. Excised gel band wash reagent of 50% ethanol/5% acetic acid (vol/vol) in water.

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12. 100 mM bicarbonate solution in water. 13. Reducing reagent: mix 5 mg DTT per mL in 100 mM ammonium bicarbonate. 14. Alkylation reagent: mix 25 mg iodoacetamide per mL in 100 mM ammonium bicarbonate. 15. Protein digestion reagent such as trypsin in 50 mM ammonium bicarbonate (20 ng trypsin per μL). 16. Peptide digest extraction solution of 50% acetonitrile/5% formic acid (vol/vol) in water. 17. HPLC connected to mass spectrometer capable of ionizing and analyzing large molecules. 18. Suitable column packing material for separating peptide fractions, such as 10 μm C18 beads. 19. Data recording software such as XcaliburTM and protein database search software such as BioworksTM (both supplied by Thermo Fisher Scientific, Inc.).

3. Methods The study of inflammation in CF cells and tissues is conducted on two levels. First, investigators assess the nature of the inflammatory state by measuring markers such as proinflammatory cytokines and inflammatory cell recruitment, as well as examining tissue histology. These analyses also constitute the outcome measures used to evaluate the effects of anti-inflammatory therapies. Second, investigators study the mechanisms by which inflammation is brought about in CF cell and animal models.

 Fig. 4.1. Evaluation of inflammatory responses in cell culture. CF and well-matched normal controls are analyzed for inflammatory responses using a number of outcome measures. For a and b, human primary tracheal epithelia were isolated from discarded cadaveric tissues, plated on semipermeable membranes, and grown at the air–liquid interface. Once cells have formed tight junctions (assessed by resistance measurements) and become well differentiated, TNF-α and IL-1β (both at 10 ng/mL) were added to the basolateral and apical media in the absence and presence of the antiinflammatory agent CDDO and CFTRinh -172 (produces the CF phenotype), respectively. Following incubation for 24 h, apical media were collected from treated and untreated cells and ELISA was used to measure IL-8 (a) and IL-6 (b). For c and d, the sense (non-CF) and antisense (CF) cell line models were transfected with luciferase expression cassettes under the control of the full-length promoter for IL-8 (c) or a promoter for NF-κB (d). On the following day cells were stimulated with TNF-α/IL-1β for a further 24 h in the presence or absence of CDDO. Cells were then lysed and assayed for luciferase expression using the dual-luciferase assay system. Data are normalized and presented as a fraction of activity in non-stimulated sense (non-CF) cells. Western blot analysis for phospho-p65 in nuclear extracts and IκB in whole cell homogenates accompanies the promoter activity data. ∗ connotes significantly different from respective non-stimulated control; ∗∗ connotes significantly different from respective non-stimulated control and from response exhibited by CF cell pair.

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Fig. 4.1. (continued)

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We recommend the use of multiple models in parallel, to elucidate inflammatory signaling cascades that are aberrant in CF. This approach increases the likelihood that observations will be physiologically and clinically relevant. In our experience, when CF cell lines and primary cells treated with the CFTR inhibitor I172 are stimulated they produce significantly higher levels of proinflammatory cytokine versus matched controls (Fig. 4.1). Similar results are observed in CF model mice (Fig. 4.2). Conversely, the production of anti-inflammatory mediators, including IL-10 (11) and lipoxin A4 (LXA4 , 12), is significantly reduced in CF cells versus normal controls. In our experience, analyses of the mechanisms that result in excessive inflammation in CF often reveal the dysregulation of intracellular signaling cascades (18, 19, 21, 30, 31) and a number of transcription factors (18, 21). Examination of promoter activity demonstrates increased activity for proinflammatory factors, such as NF-κB (18), coupled to a decrease in function of anti-inflammatory factors, such as Nrf2 (21), in CF models versus normal controls. Appropriate inflammatory signaling can be restored with anti-inflammatory agents that target these pathways (Figs. 4.1 and 4.2). However, no single linear pathway linking CFTR dysfunction and all aspects of excess inflammation

Fig. 4.2. Evaluation of inflammatory response in R117H mutant CF mice. Mice were grown in microisolator cages to the age of 8–12 weeks and then given 1 μg of LPS derived from Pseudomonas aeruginosa by intubation using a microsprayer. For (a), some mice also received the anti-inflammatory agent CDDO (10 μg/mL) daily beginning at 2 days prior to and on the day of LPS administration. Six hours following administration of LPS, animals were killed and their lungs subjected to BAL. BAL fluid was then cytospun to sediment inflammatory cells onto slides for cell count and differential analyses. Polymorphonuclear cells (predominantly neutrophils) were counted and normalized to BALF volume (a). Protease inhibitor was added to the supernatant, which was then processed for cytokine levels by ELISA using the LuminexTM system (b). ∗ connotes significant difference from wild-type control and ∗∗ connotes significant difference from CF mice that received LPS alone.

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has been demonstrated. High-throughput approaches that screen for gene and protein expression are very useful in further analysis of aberrant signaling that gives rise to exaggerated inflammatory responses in CF cells. These approaches combined with the measurement of inflammation form the basis of the study of inflammation in CF, and although we focus here on studies in airway epithelial cell and mouse models, the approaches we outline can be applied to studies in a variety of tissues and in larger animal models. 3.1. Cell Culture Maintenance and Treatments

1. CF cell models and normal matched controls should be plated on cell culture-treated plastic. If the cells in use are capable of polarizing and forming tight junctions, they can then be seeded on semipermeable filters with media added to the basolateral compartment, allowing the cells to establish at an air–liquid interface. CF cell line and primary cell models and normal matched controls should be grown under identical conditions. 2. When desired confluence is attained (we recommend using samples that are 100% confluent), either intact live bacteria (e.g., PAO1 at 105 –109 cfu/mL), bacterial components (e.g., LPS at 1 μg/mL), or inflammatory cytokines (e.g., TNF-α and/or IL-1β at 10–100 ng/mL) are added to apical media. For increased accuracy mix agents into large volume of media and dispense to individual wells. Incubate cells for 1–24 h at 37◦ C. 3. For studies of anti-inflammatory agents, investigators should determine the appropriate time course for best drug effect. For example, we preincubate cells with and conduct inflammatory stimulation in the presence of anti-inflammatory agents (e.g., CDDO, N-acetyl cysteine) to achieve optimal control of inflammation. Preincubation can vary from 24 to 72 h depending on the drug. 4. At the desired time point, apical media are collected, supplemented with 10% (vol/vol) protease inhibitor cocktail, and frozen on dry ice. Samples can be stored at –20◦ C for later analysis. 5. Cells are harvested with a 0.25% (wt/vol) solution of trypsin as needed (see Note 13). 6. Cells are centrifuged, the trypsin solution decanted, and the cell pellet washed with 10% FCS-containing media. 7. Cells are centrifuged, the 10% FCS-containing media decanted, and the cell pellet washed with 1–2 mL PBS. Repeat centrifugation step and PBS wash two more times (see Note 14).

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3.2. Animal Maintenance and Treatments

1. Model and control animals should be age and sex matched and housed under pathogen-free conditions (e.g., microisolator cages). Antibiotic therapy is not required for CF mice. However, for ferrets and pigs, antibiotics reduce infection associated with these large animal CF models. 2. When using mice, the genetic background of the model needs to be carefully considered (see Note 15). 3. Animal body weights should be monitored daily throughout each experiment. 4. On the day of treatment mice can be sedated by inhaled (e.g., isoflurane) or injected (e.g., ketamine) anesthetic. When studying the lung, we recommend the use of injected over inhaled anesthetics, to decrease direct effects on the organ of interest. 5. Test level of sedation by pinching mouse toe. When sedation level is sufficient mouse will not retract the toe. 6. Once fully sedated, the mouse is placed on a tilting workstation and inclined at a 30◦ angle. 7. The vocal cords are visualized with a small animal laryngoscope and the trachea is intubated with a 22 gauge plastic catheter or MicroSprayer. 8. If pretreating with a test compound, instill desired dose in 25 μL volume of saline. For example, for a 25 g mouse administer 10 μM CDDO in 25 μL 3% DMSO in saline (dose 10 μg/kg). In this case, control animals are given 25 μL 3% DMSO in saline. 9. Instill dose of inflammatory stimulus (e.g., 106 –109 cfu/mouse of PAO1, 40 μg/kg LPS, or 40 μg/kg flagellin in 25 μL saline) following pretreatment period. 10. Mice should be placed in microisolator cages for recovery. 11. One day following inflammatory stimulation, mice are killed using carbon dioxide, followed by exsanguination by cardiac puncture. Plasma is prepared from blood by centrifugation and stored for urea analysis. 12. After mice are killed, BAL is performed by intubating the trachea and then instilling and withdrawing three 1 mL aliquots of sterile pyrogen-free PBS-containing protease inhibitor. 13. BAL fluid is centrifuged and sterile filtered. The supernatant is processed for cytokine and chemokine quantification as described in Section 3.3. 14. The cell pellets from BAL specimens are resuspended in sterile PBS and cytospun onto glass slides for microscopy to determine leukocyte content.

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15. Lungs are harvested for histological examination as described in Section 3.4. 3.3. Measurement of Cytokine Production

1. Collected BAL can be assayed for any pro- or antiinflammatory cytokines. We recommend assaying for IL-8, IL-6, granulocyte-macrophage colony-stimulating factor (GM-CSF), IL-10, and regulated on activation normal T cell expressed and secreted (RANTES) in human samples (e.g., media collected from human primary and cell line models). For samples collected from mice, we recommend assaying for MIP-2, Kc, IL-6, GM-CSF, IL-10, and RANTES. 2. Enzyme-linked immunosorbent assay (ELISA) kits are used to assay for specific cytokine of interest. Alternatively, multiplex analyses on multiple cytokines can be performed using the LuminexTM ELISA-based analysis platform. 3. For cell culture analyses, cells are lysed and protein is determined. Cytokine levels are normalized to protein levels and are usually expressed as picogram cytokine/milligram protein. 4. For analyses in mice, cytokine measurements are normalized to the urea dilution factor. The urea dilution factor is the level of dilution of urea measured in BAL fluid from urea levels in the blood for each animal.

3.4. Histological Analysis of Lung Tissue

1. Harvested lungs are immediately placed in 2% paraformaldehyde for 24 h and embedded in paraffin or frozen in tissue freezing medium (e.g., OTC) for preservation. 2. Paraffin-embedded tissues or tissues frozen in freezing medium are mounted on the tissue microtome and sectioned at either 5 or 10 μm per section. 3. Tissue depth should be surveyed. For example, three to five adjacent tissue sections should be collected for every 100–300 μm of lung tissue. Sections are affixed to polylysine-coated slides. 4. Slides containing sections in paraffin or freezing medium are deparaffinized by soaking in xylene or water, respectively. 5. At this stage sections are hydrated in PBS and either stained (e.g., with eosin and hematoxylin) or processed for immunohistochemistry (IHC). 6. For IHC, sections are permeabilized by soaking in 100% methanol at –20◦ C for 5 min. 7. For IHC involving the use of a peroxidase-conjugated antibody (e.g., horseradish peroxide-conjugated anti-rabbit

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secondary antibody), sections are incubated for 30 min in 3% hydrogen peroxide to quench endogenous peroxidase activity. 8. Sections are washed one time in PBS and then incubated with block solution (5% serum of the species the secondary antibody is raised in) for 3 h at room temperature. 9. Adjacent sections are then incubated with either 5% serum alone (no primary control) or 5% serum containing primary antibody directed against inflammation-related protein (see Note 16) for 1 h at 37◦ C or overnight at 4◦ C. Dilution of primary antibody is usually 1:200. 10. Sections are immersed in PBS and washed. This is repeated three times. 11. Reporter enzyme-conjugated secondary antibody (e.g., peroxidase-conjugated antibody) is added to sections for 0.5–1 h at room temperature. Dilution of secondary antibody is usually 1:1000. 12. Sections are immersed in PBS and washed. This is repeated three times. 13. Inflammation-related protein is detected by exposure of the sections to reporter enzyme substrate (e.g., 3,3diaminobenzene and H2 O2 ). 14. Following counterstaining with hematoxylin, protein stain is visualized by either fluorescent or light microscopy, depending on the reporter used. 3.5. Western Blot Analysis

1. Whole cell homogenates or cytoplasmic and nuclear extracts are prepared by cell fractionation. 2. For total whole cell or fraction protein analysis, nuclear (10 μg per 1D gel well or 50 μg per 2D gel pI focusing strip) and cytoplasmic extracts (40 μg per well or 100 μg per 2D gel pI focusing strip) are prepared and loaded onto 1D or 2D polyacrylamide gels. 3. For immunoprecipitation, whole cell or fraction protein in lysates is incubated with protein A- or G-conjugated beads for 30 min at room temperature and the beads centrifuged and discarded. 4. Cleared lysates are incubated with antibody (Ab) directed at the protein of interest (e.g., Ab against either the p50 or p65 subunit of NF-κB) for 2 h at room temperature. 5. Protein A or G beads are added to Ab-incubated lysates and the mixture is incubated for 1 h at room temperature. 6. Ab bound beads are centrifuged, washed three times with ice-cold IP buffer, and the immunoprecipitated protein is eluted with SDS-PAGE sample buffer and boiled.

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7. The eluate is loaded onto 1D or 2D gels. 8. Following completion of SDS-PAGE, 1D or 2D gels are transferred to nitrocellulose membranes by electroblotting. 9. Blots are blocked in 3% nonfat dry milk in wash buffer, gently rocked overnight at 4◦ C, and then incubated with affinity-purified monoclonal Ab directed against the protein of interest (e.g., mouse monoclonal anti-human NFκB p65 Ab at 1:200 dilution) for 2 h at room temperature. 10. Blots are washed three times with wash buffer for 15 min. 11. Reporter-conjugated secondary Ab (HRP-conjugated antimouse IgG) is added to the blot at 1:1000 dilution for 1 h at room temperature. 12. Blots are washed three times with wash buffer for 20 min. 13. Blots are developed using a chemiluminescent ECL detection system. 3.6. Analysis of Promoter and/or Transcription Factor Activity

1. For analysis by promoter activity, cells are co-transfected with two plasmids using a cell transfection reagent, such as lipofectamine. One plasmid codes for firefly luciferase under the control of the promoter sequence for a proinflammatory (e.g., NF-κB) or anti-inflammatory (e.g., Nrf2) transcription factor and the other codes for Renilla luciferase under the control of a viral promoter (see Note 10). 2. Lipofectamine-complexed plasmid DNA is added to cells for 6 h at 37◦ C. Firefly luciferase (promoter of interest) and Renilla luciferase plasmids are mixed at a 10:1 ratio for transfection. 3. One day after transfection, cells can be processed for analysis or stimulated with inflammatory stimuli for a further 24 h and processed for luminometer analysis with a dualluciferase reporter assay system. 4. Firefly luciferase activity is measured by luminometer for 10 s following the addition of 20 μL lysate to 80 μL firefly luciferase substrate. 5. Stop & Glo reagent is added to the sample to quench the firefly luciferase reaction and activate the Renilla luciferase reaction. Renilla luciferase activity is measured for 10 s. 6. Steps 4 and 5 can be programmed into a plate reading luminometer with two injectors for the addition of the firefly luciferase substrate and Stop & Glo reagent samples in the plate. 7. To control for transfection efficiency, values for firefly luciferase activity are normalized to Renilla luciferase activity.

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8. For the analysis of transcription factor activity, we use an ELISA-based assay for proteins such as NF-κB or Nrf2. 9. One day following treatment with vehicle or inflammatory stimuli nuclear extracts are prepared by centrifugation from cultured cells or mouse lungs, according to the ELISA TransAM kit. 10. Extracts are added to a microplate coated with an oligonucleotide sequence corresponding to the transcription factor binding sequence and incubated at room temperature for 1 h. 11. The plate is then incubated with a primary Ab specific to the transcription factor, such as a mouse monoclonal antiNF-κB p65 or Nrf2 Ab at a 1:200 dilution. 12. The plate is washed three times. 13. A reporter-conjugated (e.g., HRP) secondary Ab is directed against the primary Ab at a 1:2000 dilution. 14. Reporter substrate is used to develop the ELISA for 10 min and OD is recorded and plotted against standard curve. 15. Signal intensity reflects the level of binding of transcription factor in nucleus to target sequence and thus the transcription factor’s activity. 16. For studies in animals, we use transgenic CF mice that express firefly luciferase under the control of the promoter of a transcription factor of interest, such as NF-κB. 17. We sometimes remove tissues after in vivo imaging, homogenize and image them to obtain photon emission numbers that are not attenuated, as they are in vivo. 18. Animals are imaged 2 days following administration of inflammatory stimulus (e.g., LPS), anti-inflammatory agent (e.g., CDDO), or vehicle by animal microsprayer, and mice can be repeatedly imaged at different intervals, as needed. 19. Animals are anesthetized by an appropriate anesthetic throughout the imaging process. We recommend against the use of inhaled anesthetics as these may influence the lungs. 20. Inject 150 mg/kg D-luciferin in PBS IP 10 min before imaging to allow for diffusion throughout the body. 21. The side of the mouse nearest the tissue being imaged should be shaved to minimize photon attenuation by hair. 22. Mice are positioned on the imaging stage and images are acquired over a 6- to 15-min exposure time, as needed, then digitally filtered and processed to remove background and thermal noise.

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1. RNA is extracted from cells or animal tissue at intervals after exposure to inflammatory stimulus, anti-inflammatory agent, or vehicle. We typically extract RNA at 0, 0.5, 2, 6, 24, and 48 h following treatment. 2. At least three hybridization replicates are performed for the 0.5-, 2-, 6-, and 48-h time points and six hybridization replicates for the 0- and 24-h time points. 3. Cells or animal tissues are washed two times with cold PBS and total RNA is extracted using the ULTRASPEC RNA isolation system. 4. RNA is quantified by measurement at OD260 nm , and the integrity of RNA samples is checked by formaldehyde agarose gel electrophoresis. 5. Complementary RNA is prepared from 40 μg of total RNA as per instructions from Affymetrix and diluted in hybridization buffer to a total volume of 300 μL. 6. The hybridization buffer also contains the prokaryotic genes bioB, bioC, bioD (genes from the biotin synthesis pathway from E. coli), and CRE (recombinase gene from P1 bacteriophage) at a final concentration of 1.5, 5, 25 and 100 pM, respectively. 7. Samples are hybridized to HG-U95Av2 chip and probe arrays are read using a Hewlett-Packard G2500A GeneArray Scanner using an argon-ion laser to excite the fluorophores at 488 nm with a scanning wavelength of 570 nm. Data are analyzed with the Affymetrix MASS 5.0 software. 8. The variability of hybridization between arrays is assessed by examining the behavior of the probe sets for the prokaryotic genes, which should indicate that responses for CF and normal paired control are similar. In addition, the intensities should be proportional to the concentration. 9. The lowest detected limit of the assay is determined as being between the prokaryotic genes that the decision matrix within the Affymetrix MASS 5.0 software identifies as being ‘Absent’ and the least detected gene. Usually this range is between 1.5 and 5 pM. 10. Ratio of cDNA to cRNA synthesis is assessed by comparing the ratio of probe sets for the 3 to the 5 regions of two housekeeping genes in the array. We typically use GAPDH and β-actin, where the ratio of 3 to 5 sampling is 1.22 ± 0.03 to 2.09 ± 0.69 for GAPDH and 0.90 ± 0.05 to 1.33 ± 0.30 for β-actin.

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11. Data collected by the Affymetrix MASS 5.0 software are normalized using the robust multichip average (RMA) model and then analyzed using Gene Spring 6.0 and significance analysis of microarrays (SAM). 12. Differentially expressed genes are identified by parametric statistical analysis. 3.8. Proteomic Analysis

1. Treated and untreated cells are trypsinized, centrifuged, and washed three times in PBS and then frozen at –80◦ C. 2. For lung tissues, immediately after killing and BAL collection, tissue is separated, incubated in lysis buffer containing protease inhibitors, and frozen at –80◦ C. 3. Thaw frozen cell pellets or tissues to room temperature. Add 1–2 mL lysis buffer to each sample and homogenize (see Note 18). Mix well until sample becomes viscous due to the interaction of the DNA/RNA and SDS. 4. Heat the samples to 100◦ C for 5 min and mix by gentle vortex. Cool samples to room temperature. 5. Add 100 μL Nuclease reagent per mL of lysis solution, while mixing the sample. Viscosity of the sample will begin to clear as DNA/RNA is digested. Allow the reaction to continue for 1 h at room temperature. 6. Remove an aliquot for the protein assay. A detergentcompatible protein assay must be used. 7. Cool the homogenate on ice for 10 min, then add 6 mL ice-cold acetone per mL of homogenate and incubate at –20◦ C overnight. 8. Protein precipitate should be white and fluffy and should not appear stringy if DNA and RNA have been properly digested. Protein is sedimented by centrifugation at 6000 rpm for 5 min. Discard the acetone, without disturbing the protein pellet, blot residual acetone, and allow the acetone to dry thoroughly at room temperature. 9. Once dried, proteins are solubilized in solubilization buffer to a concentration of 5 mg protein/mL based on the protein measurement carried out in step 6. 10. For 2D SDS-PAGE, prepare the samples in 1.5 mL Eppendorf tubes: (a) For Coomassie blue-stained gels: 150 μL of sample (5 mg/mL) is added to 100 μL rehydration buffer and 10 μL 1% BPB and mixed well. (b) For silver-stained gels: 30 μL sample (5 mg/mL) is added to 220 μL rehydration buffer and 10 μL of 1% BPB and mixed well.

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11. Samples are transferred to a well in the isoelectric focusing (IEF) tray and bubbles are removed by pipette. 12. An IPG pH gel strip is placed face down in the sample, and the tray is gently rocked to ensure good wetting of the gel surface. Mineral oil is used to cover the strip to protect the gel from drying during rehydration and focusing. 13. The strip is rehydrated overnight at 25◦ C, under application of 50 V. Typical rehydration time is 12–16 h. 14. Once rehydration is complete, wetted electrode strips are placed at each electrode and the strip is placed in the facedown position and covered with mineral oil. 15. A typical isoelectric focusing program for a 11 cm, 5–8 pI range strip loaded with 500–750 μg protein is as follows: Step 1: to 250 V in 0:15 h Step 2: to 8000 V in 3:00 h Step 3: at 8000 V for 2.5 h total volt-hours = 44 kVh 16. When focusing is complete strips are equilibrated by placing them face up in the equilibration tray and treating with 3.5 mL of the reducing reagent for 15 min, followed by treatment with 3.5 mL of the alkylating reagent for 15 min. The strips are then placed in precast 2D gels for the running of the second dimension. 17. For 1D SDS-PAGE, sample (from step 9) can be loaded onto gel and routine methodology may be employed as long as fresh reagents and precast gels are used to decrease contamination. 18. 1D or 2D gels are run at a constant voltage of 200 V. The total run time should be approximately 70 min. Stop the run when the tracking dye just leaves the bottom of the gel. 19. Gels are fixed for 30 min at room temperature with gentle shaking, then stained with 125 mL of Gelcode Blue overnight at room temperature with gentle shaking, or stained with silver. 20. When staining is complete, each 1D or 2D gel is scanned using a BioRad QS-800 Calibrated Densitometer and images are imported into the Quantity OneTM 1D or PDQuestTM 2D gel analysis software and compared. 21. Protein bands from non-CF- and CF-matched pair models are compared and significant changes in protein expression levels in response to inflammatory stimuli, antiinflammatory agent, or vehicle are determined.

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22. Bands that are significantly different in CF versus normal are cut and placed in a rinsed, 1-mL Eppendorf tube. For Coomassie-stained gels go to step 24. 23. For silver-stained gels, excised bands are washed in 200 μL water two times, destained with 50–100 μL Farmer’s reducer for 15 min at room temperature, and then washed three times with 200 μL water. 24. Bands are then washed and destained by adding 200 μL wash reagent at room temperature for a further 30 min and then rinsed in 200 μL 100 mM bicarbonate. For 2D gels, go to step 26. 25. For 1D gel excised bands, proteins are reduced and alkylated to prevent refolding by dehydrating each band with 200 μL acetonitrile for 5 min, followed by drying the bands in a SpeedVac for approximately 3 min. DTT (50 μL) is added for 30 min at room temperature to reduce proteins followed by 50 μL iodoacetamide reagent for 30 min at room temperature to alkylate the proteins. Remove iodoacetamide before proceeding to step 26. 26. 1D and 2D gel bands are dehydrated by adding 200 μL acetonitrile for 5 min followed by the addition of 200 μL 50 mM bicarbonate for 5 min. Bicarbonate is removed, and the dehydration/hydration process is repeated two more times. Gel pieces are dried in SpeedVac for approximately 3 min, then rehydrated in 50 μL of trypsin reagent for 10 min on ice, and microfuged briefly. Excess trypsin is removed and 50 μL 50 μM bicarbonate is added, and protein digestion is allowed to proceed overnight at room temperature. 27. Gel pieces are microfuged briefly, incubated with 30 μL extraction reagent for 10 min. Extracts are transferred to 0.5 mL Eppendorf tube. Another 30 μL extraction reagent is added to gel pieces and incubated for a further 10 min, then supernatants are combined in the 0.5 mL Eppendorf tube. Extract is briefly microfuged, and the volume is reduced to less than 10 μL in SpeedVac. Sample volume is increased to 25 μL with 1% acetic acid (see Note 19). 28. At this stage the sample is ready for analysis by electrospray LC-MS-MS. To analyze samples by MALDI mass spectrometry, simply desalt the samples on desalting column or ZipTipTM (Millipore Corp., Billerica, MA). Mass spectrometric analysis can be used to identify proteins and post-translational modifications and to quantify proteins in mixtures by label-free quantitation.

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4. Notes 1. The choice of serum used for media supplementation should be considered carefully. Components of serum, which can include cytokines and other mediators of cell signaling, can heavily influence cell growth, viability, and responses to inflammatory stimulation. 2. Fungizone and other antimycotic agents can influence the behavior of mammalian cells in response to inflammatory stimuli and affect transfection efficiency, especially at high doses. We recommend the use of these agents only if necessary and at low doses. 3. The use of CFTRInh -172 inhibits chloride efflux through the CFTR channel, producing the primary CF defect. However, although cells exhibit this phenotype when treated with 20 μM inhibitor, other phenotypes such as those that might result from CFTR protein misfolding may not be produced by channel inhibition. Therefore, we recommend the use of this model in conjunction with other models to increase the clinical applicability of studies on inflammation. 4. The CF mouse does not exhibit spontaneous lung inflammation. However, inflammation can be induced using bacteria or inflammatory mediators. Nevertheless, this approach produces transient and acute inflammation that may not reflect the characteristics of the chronic inflammation observed in CF patients. This limitation should be considered when selecting CF mice for inflammatory studies. In addition, we find that mouse gender, genetic background, and age can all affect inflammatory responses. We recommend the use of male mice that are 8–12 weeks old and have the C57BL/6 genetic background. 5. Large animal models of CF including pigs and ferrets exhibit spontaneous airway and bowel disease that can become severe and result in death. Therefore, these animals may need treatment for these complications at an early age. 6. Euthanasia protocols should conform to federal and state guidelines for animal use as well as the guidelines outlined by the institutional animal care and use committee (IACUC).

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7. Reactions whereby the detection Ab is conjugated to multiple biotins that can then be reacted with avidin-conjugated HRP can markedly amplify immunohistochemical signals. 8. Do not heat any urea-containing solutions or samples to temperatures above 42◦ C. 9. Plasmid vectors may contain internal sequences that bind transcription factors and result in non-specific transcription of the reporter gene. Therefore, we recommend that plasmids that contain these sequences not be used for studies of specific promoter activity. 10. Transfection of cells can influence their behavior and response to inflammatory stimuli. Therefore, we recommend validation of responses by multiple approaches. 11. Precipitation of protein by acetone requires that at least 100 μg of protein be present in a cell pellet. If necessary, it is possible to combine the contents of two to three filters of cells to achieve the desired protein levels. 12. Depending on the cell type, complete cell lysis requires varying volumes of lysis buffer. The amount of lysis buffer necessary should be determined on a case-by-case basis. 13. To achieve efficient and rapid release of primary airway epithelia grown on semipermeable membranes at an air–liquid interface, trypsin should be added to the basolateral compartment. 14. Since data are normalized to protein per sample, thorough washes are necessary to remove all media from cells to prevent contamination of the sample with media proteins. 15. Genetic background can heavily influence the electrophysiological phenotype (e.g., nasal potential difference) and inflammatory responses in the lungs of CF mice. We recommend conducting animal experiments with mice that share a common genetic background. For example, when bred into the C57BL/6 background R117H mutant mice exhibit CF defects similar in magnitude to those observed in mice bearing the F508del or S489X mutation. 16. Hydrophobic barrier pens can be used to outline tissue sections on glass slides and confine the flow of solutions to that area. This allows for the use of small volumes and the conservation of precious reagents such as antibodies. 17. Animal coat color and the depth of the tissue of interest can heavily influence BLI signals, so we recommend the use of light-coated animals. Initial correlation of images obtained from live mice with images obtained from the respective tissues ex vivo after harvest is helpful for determining the level of attenuation.

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18. The volume of lysis buffer required depends on the number of cells harvested and the amounts of protein, RNA, and DNA present in the sample. These factors vary in different cells and should be determined experimentally. High levels of nucleic acids in a sample can decrease nuclease activity and result in incomplete digestion of RNA and/or DNA. Since undigested DNA/RNA affects protein migration on 1D and 2D gels, cell pellets should be homogenized in sufficient volume. 19. Samples that are analyzed by electrospray ionization should be either positively or negatively charged. For most protein analyses, acetic or formic acids can be used to protonate peptides. References 1. Tirouvanziam, R., de Bentzmann, S., Hubeau, C., Hinnrasky, J., Jacquot, J., Peault, B., et al. (2000) Inflammation and infection in naive human cystic fibrosis airway grafts. Am J Respir Cell Mol Biol 23, 121–127. 2. Rosenfeld, M., Gibson, R. L., McNamara, S., Emerson, J., Burns, J. L., Castile, R., et al. (2001) Early pulmonary infection, inflammation, and clinical outcomes in infants with cystic fibrosis. Pediatr Pulmonol 32, 356–366. 3. Cohn, L. A., Weber, A., Phillips, T., Lory, S., Kaplan, M., and Smith, A. (2001) Pseudomonas aeruginosa infection of respiratory epithelium in a cystic fibrosis xenograft model. J Infect Dis 183, 919–927. 4. Konstan, M. W., Hilliard, K. A., Norvell, T. M., and Berger, M. (1994) Bronchoalveolar lavage findings in cystic fibrosis patients with stable, clinically mild lung disease suggest ongoing infection and inflammation. Am J Respir Crit Care Med 150, 448–454. 5. Muhlebach, M. S., Stewart, P. W., Leigh, M. W., and Noah, T. L. (1999) Quantitation of inflammatory responses to bacteria in young cystic fibrosis and control patients. Am J Respir Crit Care Med 160, 186–191. 6. Kazachkov, M. Y., Muhlebach, M. S., Livasy, C. A., and Noah, T. L. (2001) Lipid-laden macrophage index and inflammation in bronchoalveolar lavage fluids in children. Eur Respir J 18, 790–795. 7. Wilmott, R. W., Kassab, J. T., Kilian, P. L., Benjamin, W. R., Douglas, S. D., and Wood, R. E. (1990) Increased levels of interleukin1 in bronchoalveolar washings from children with bacterial pulmonary infections. Am Rev Respir Dis 142, 365–368.

8. Hubeau, C., Le Naour, R., Abely, M., Hinnrasky, J., Guenounou, M., Gaillard, D., et al. (2004) Dysregulation of IL-2 and IL8 production in circulating T lymphocytes from young cystic fibrosis patients. Clin Exp Immunol 135, 528–534. 9. Hauber, H. P., Manoukian, J. J., Nguyen, L. H., Sobol, S. E., Levitt, R. C., Holroyd, K. J., et al. (2003) Increased expression of interleukin-9, interleukin-9 receptor, and the calcium-activated chloride channel hCLCA1 in the upper airways of patients with cystic fibrosis. Laryngoscope 113, 1037–1042. 10. Bonfield, T. L., Panuska, J. R., Konstan, M. W., Hilliard, K. A., Hilliard, J. B., Ghnaim, H., et al. (1995) Inflammatory cytokines in cystic fibrosis lungs. Am J Respir Crit Care Med 152, 2111–2118. 11. Soltys, J., Bonfield, T., Chmiel, J., and Berger, M. (2002) Functional IL-10 deficiency in the lung of cystic fibrosis (cftr(–/–)) and IL-10 knockout mice causes increased expression and function of B7 costimulatory molecules on alveolar macrophages. J Immunol 168, 1903–1910. 12. Karp, C. L., Flick, L. M., Park, K. W., Softic, S., Greer, T. M., Keledjian, R., et al. (2004) Defective lipoxin-mediated anti inflammatory activity in the cystic fibrosis airway. Nat Immunol 5 (4), 388–392. 13. Chow, C. W., Landau, L. I., and Taussig, L. M. (1982) Bronchial mucous glands in the newborn with cystic fibrosis. Eur J Pediatr 139, 240–243. 14. Boucher, R. C. (2007) Cystic fibrosis: a disease of vulnerability to airway surface dehydration. Trends Mol Med 13, 231–240.

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15. Konstan, M. W., Schluchter, M. D., Xue, W., and Davis, P. B. (2007) Clinical use of Ibuprofen is associated with slower FEV1 decline in children with cystic fibrosis. Am J Respir Crit Care Med 176, 1084–1089. 16. Nichols, D. P., Konstan, M. W., and Chmiel, J. F. (2008) Anti-inflammatory therapies for cystic fibrosis-related lung disease. Clin Rev Allergy Immunol 35, 135–153. 17. Konstan, M. W. (2008) Ibuprofen therapy for cystic fibrosis lung disease: revisited. Curr Opin Pulm Med 14 (6), 567–573. 18. Nichols, D. P., Ziady, A. G., Shank, S. L., Eastman, J. F., and Davis, P. B. (2009) The triterpenoid CDDO limits inflammation in preclinical models of cystic fibrosis lung disease. Am J Physiol Lung Cell Mol Physiol 297, L828–L836. 19. Pollard, H. B., Eidelman, O., Jozwik, C., Huang, W., Srivastava, M., Ji, X. D., et al. (2006) De novo biosynthetic profiling of high abundance proteins in cystic fibrosis lung epithelial cells. Mol Cell Proteomics 5, 1628–1637. 20. Martino, M. E., Olsen, J. C., Fulcher, N. B., Wolfgang, M. C., O’Neal, W. K., and Ribeiro, C. M. (2009) Airway epithelial inflammation-induced endoplasmic reticulum Ca2+ store expansion is mediated by X-box binding protein-1. J Biol Chem 284 (22), 14904–14913. 21. Chen, J., Kinter, M., Shank, S., Cotton, C., Kelley, T. J., and Ziady, A. G. (2008) Dysfunction of Nrf-2 in CF epithelia leads to excess intracellular H2 O2 and inflammatory cytokine production. PLoS One 3 (10), e3367. 22. White, N. M., Jiang, D., Burgess, J. D., Bederman, I. R., Previs, S. F., and Kelley, T. J. (2007) Altered cholesterol homeostasis in cultured and in vivo models of cystic fibrosis. Am J Physiol Lung Cell Mol Physiol 292, L476–L486. 23. Perez, A., Issler, A. C., Cotton, C. U., Kelley, T. J., Verkman, A. S., and Davis, P. B. (2007) CFTR inhibition mimics the cystic fibrosis inflammatory profile. Am J Physiol Lung Cell Mol Physiol 292 (2), L383–L395. 24. Becker, M. N., Sauer, M. S., Muhlebach, M. S., Hirsh, A. J., Wu, Q., Verghese, M. W., et al. (2004) Cytokine secretion by cystic fibrosis airway epithelial cells. Am J Respir Crit Care Med 169, 645–653. 25. Shah, A. S., Ben-Shahar, Y., Moninger, T. O., Kline, J. N., and Welsh, M. J. (2009) Motile cilia of human airway

26. 27.

28.

29.

30.

31.

32.

33.

34.

35.

epithelia are chemosensory. Science 325, 1131–1134. Wine, J. J., and Soo Joo, N. (2004) Submucosal glands and airway defense. Proc Am Thor Soc 1, 47–53. Sun, X., Yan, Z., Yi, Y., Li, Z., Lei, D., Rogers, C. S., et al. (2008) Adeno-associated virus-targeted disruption of the CFTR gene in cloned ferrets. J Clin Invest 118, 1578–1583. Welsh, M. J., Rogers, C. S., Stoltz, D. A., Meyerholz, D. K., and Prather, R. S. (2009) Development of a porcine model of cystic fibrosis. Trans Am Clin Climatol Assoc 120, 149–162. Vandivier, R. W., Richens, T. R., Horstmann, S. A., deCathelineau, A. M., Ghosh, M., Reynolds, S. D., et al. (2009) Dysfunctional cystic fibrosis transmembrane conductance regulator inhibits phagocytosis of apoptotic cells with proinflammatory consequences. Am J Physiol Lung Cell Mol Physiol 297, L677–L686. Perez, A., and Davis, P. B. (2004) Gene profile changes after Pseudomonas aeruginosa exposure in immortalized airway epithelial cells. J Struct Funct Genomics 5, 179–194. Xu, Y., Liu, C., Clark, J. C., and Whitsett, J. A. (2006) Functional genomic responses to cystic fibrosis transmembrane conductance regulator (CFTR) and CFTR(delta508) in the lung. J Biol Chem 281 (16), 11279– 11291. van Heeckeren, A. M., Schluchter, M. D., Drumm, M. L., and Davis, P. B. (2004) Role of Cftr genotype in the response to chronic Pseudomonas aeruginosa lung infection in mice. Am J Physiol Lung Cell Mol Physiol 287, L944–L952. Perez, A., van Heeckeren, A. M., Nichols, D., Gupta, S., Eastman, J. F., and Davis, P. B. (2008) Peroxisome proliferator-activated receptor-gamma in cystic fibrosis lung epithelium. Am J Physiol Lung Cell Mol Physiol 295, L303–L313. Norkina, O., Kaur, S., Ziemer, D., and De Lisle, R. C. (2004) Inflammation of the cystic fibrosis mouse small intestine. Am J Physiol Gastrointest Liver Physiol 286, G1032–G1041. Kube, D., Sontich, U., Fletcher, D., and Davis, P. B. (2001) Proinflammatory cytokine responses to P. aeruginosa infection in human airway epithelial cell lines. Am J Physiol Lung Cell Mol Physiol 280, L493–L502.

Chapter 5 Methods for ASL Measurements and Mucus Transport Rates in Cell Cultures Erin N. Worthington and Robert Tarran Abstract The healthy human respiratory tract is lined with a pseudostratified epithelia composed of ∼80% ciliated cells and ∼20% goblet cells. These cells produce and are bathed by a layer of airway surface liquid (ASL), which plays a critical role in lung defense by helping to maintain the sterility of the lung. This layer is composed of two phases: the mucus layer which functions to trap particulates, bacteria, and viruses, and the underlying periciliary liquid layer (PCL), which provides hydration, enabling mucus transport and clearance. This chapter describes the methods used to measure the structure and height of the ASL by XZ confocal microscopy and mucus transport rates using epifluorescent microscopy in live airway cultures. Furthermore, we also demonstrate that these methods are also applicable in novel ways to probe the ultrastructure of the airways including the establishment of pH gradients and the ability of the apical membrane glycocalyx in excluding larger molecules from the cell surface. Key words: ASL, airway surface liquid, CCD, charge-coupled device, MCC, mucociliary clearance, PCL, periciliary liquid layer, PFC, perfluorocarbon, airway epithelia, confocal microscopy.

1. Introduction Epithelial mucosal surfaces are lined with fluids whose volume and composition are precisely controlled to perform a variety of functions. In the conducting airways, a thin film of airway surface liquid (ASL) helps protect against infection by acting as a lubricant for efficient mucus clearance. The rate of mucus clearance is strongly influenced by the volume (height) of this layer. The ASL is comprised of a periciliary liquid layer (PCL), which lubricates the cell surface, and a mucus layer of variable thickness, which traps airborne particles and pathogens (1). A robust M.D. Amaral, K. Kunzelmann (eds.), Cystic Fibrosis, Methods in Molecular Biology 742, DOI 10.1007/978-1-61779-120-8_5, © Springer Science+Business Media, LLC 2011

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aid to the study of airway physiology has been the development of reliable cell culture models, which recapitulate the in vivo airway morphology in vitro. The well-differentiated human airway epithelial cell culture system closely mimics the in vivo proximal airways, i.e., the presence of ciliated and goblet cells, which produce separate periciliary and mucus layers and exhibit coordinated mucus transport (Fig. 5.1a) (2, 3). The ASL has been reported to range in height from 3 to 70 μm, which most likely represents differences in (i) genotype, (ii) the presence vs. absence of a significant mucus layer, and (iii) species differences (4–7). Normal human airway cultures have an ASL height of approximately 7 μm and cystic fibrosis airway cultures have an ASL height of approximately 3 μm (8). However, in the presence of mucus, ASL height may be much higher in both normal and CF airway cultures (2, 9) and under these high mucus conditions, measurements of mucus transport rates may be as informative (10). For example, even though we have shown CF airways to have an ASL height of up to 100 μm when mucus is present, they lack mucus clearance (9, 10). The reason for this is that these airways possess significantly dehydrated mucus (>20% solids), which adheres to the underlying epithelia, preventing it from being transported, unlike normal mucus which is <6% solids and can be transported by ciliary beating (10). When human airway cultures are mounted in Ussing chambers, native airway surface liquid is washed away, and Na+ absorption predominates (11). In contrast, under thin film conditions, where native airway surface liquid is preserved, Na+ absorption is volume sensitive and the capacity to spontaneously secrete Cl– and ASL is revealed (12). How ASL volume is sensed and reg-

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Fig. 5.1. Airway surface liquid and human airway cultures. (a) Differentiated airway epithelial culture. Human tracheobronchial epithelia are grown at an air–liquid interface on a semi-permeable support for 2–6 weeks after seeding. PCL, periciliary liquid layer; GC, goblet cell; CC, ciliated cell; BC, basal cell; SPM, semi-permeable membrane culture insert. (b) Imaging of live cells and ASL by XZ confocal microscopy. The cells were stained with calcein-AM and the ASL is visualized with Texas Red-dextran. (c) Representative image of ASL labeled with PBS/Texas Red-dextran (gray band) and mucus labeled with 100 nm fluorescent microspheres (light gray particles), which associate discontinuously with mucus.

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ulated by the airways is poorly understood. However, soluble, regulatory molecules have been found to exist in the ASL including ATP, ADO, and SPLUNC1 that can serve as volume-sensing signals whose dilution or concentration can alter specific cell surface receptors to set epithelial transport to either absorb or secrete airway surface liquid as needed (13, 14). In particular, the Ca2+ activated Cl– channel (now TMEM16A/Ano1) (15–17), CFTR, and the epithelial Na+ channel (ENaC) have been shown to be particularly affected by these volume-sensing systems (12, 14, 18). Furthermore, evidence is emerging that demonstrates that at least one of these sensing systems (i.e., adenosine/cAMP/CFTR) is dysregulated in CF airways, leading to ASL volume depletion (8, 19, 20). In this chapter, we describe the measurement of in vitro ASL height by vertical (XZ) laser scanning confocal microscopy techniques, which gives an index of ASL volume on the epithelial mucosal surface. The capacity of the epithelia to absorb or secrete ASL can be directly indexed as a function of ASL height. In addition, these measurements can be coupled with epifluorescence microscopy techniques to measure mucus transport rates (2, 3, 21, 22) and have been further refined to measure ASL pH and to probe the molecular structure of the ASL. 1.1. Choice of Fluorescent Probes and Cellular Dyes

We have historically labeled the ASL with Texas Red conjugated to 10 kDa dextran, which dissolves in the ASL and is relatively impermeable across the epithelia (Fig. 5.1b). Texas Red was initially chosen since it has a good quantum yield, is resistant to photobleaching, and worked well with the laser lines available at that time. However, additional fluorescent dyes that have been conjugated to dextran are available, which should also work well for labeling the ASL. For example, we have successfully used Oregon Green to label the ASL, also conjugated to 10 kDa dextran (2), and many more dyes, including the Alexa series from Molecular Probes/Invitrogen are now available. Principal determinants will include the laser lines available on your system and the cost of the dye vs. their lability and resistance to photobleaching. In addition, since airway cultures and the filter on which they are grown tend to autofluoresce more in the blue/green range (i.e., similar to FITC/Oregon Green excitation/emission wavelengths), we have a preference for red spectrum dyes which minimize this autofluorescence such as tetramethylrhodamine or Texas Red. The size of the dextran was initially chosen as 10 kDa since it was retained in the ASL for >24 h, unlike free dye, which rapidly perfuses through the tight junctions (23). Studies have indicated that higher molecular weight dextrans are excluded from the region close to the surface of cells (Fig. 5.2), likely by the glycocalyx which may also act as a barrier to the movement of high molecular weight molecules such as viruses (24). To test whether regions in the ASL could differentiate molecules based on size,

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Fig. 5.2. High molecular weight dextrans are excluded from the near-membrane region of the ASL. (a) FITC 10 kDa and Texas Red 500 kDa dextrans were added to the ASL in 20 μL PBS (both at 2 mg/mL) and their intensity measured 2 h later using the line scan function. (b) Typical line scan data of intensity vs. distance from cell surface (position; μm) taken from (a). (c) By comparing the intensity ratio of the two dextrans at different positions along the line scan, we can see that the ratio of dextrans varies. Thus, we can infer that the 500 kDa dextran is excluded from the 3 μm region closest to the cell surface. ∗ denotes p < 0.05 different to sub-3 μm region. All n = 5.

we added two different sized fluorescent dextrans to the ASL of airway cultures in 20 μL Ringer solution (Fig. 5.2a). Two hours after their addition, the larger (500 kDa) dextran was present at a lower concentration in the region immediately adjacent to the cell

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surface (i.e., 1–3 μm above the apical membrane) since the ratio of 10/500 kDa dextrans was lower in this region (Fig. 5.2c). In contrast, the ratio of 10/500 kDa dextrans was greater further away from the cell surface and was constant everywhere other than 3 μm near cell region (Fig. 5.2c). pH-sensitive fluorescent dextrans can also be added to the ASL. Possible choices include, but are not limited to BCECFdextran, Oregon Green-dextran and SNARF1-dextran. We measured ASL pH over time by the addition of SNARF1 conjugated to dextran. This methodology represents a significant deviation over previous studies since rather than scanning with an inverted microscope, we used an upright microscope and placed a dipping lens into the PFC over the culture (see Note 6). Since this method allows us to scan directly into the ASL without having to scan through the culture first, this may minimize any laser beam attenuation/scattering that may occur. Figure 5.3a clearly shows that

Fig. 5.3. Measurement of ASL pH by confocal microscopy. (a) Calibration of pH vs. emission ratio using 2 mg/mL SNARF1-dextran in pH-adjusted Ringer solution placed on a pre-washed airway culture. (b) Confocal XZ scanning of standard Ringer solution (pH 7.4) immediately after addition to the mucosal surface of an airway culture. Note the absence of pH gradient. (c) Left: typical pH scan 48 h after addition of 20 μL Ringer/SNARF to an airway culture. Height of 0–7 μm represents the PCL region and above that (>7 μm) is mucus/ASL. Right: typical pH scan from the same culture 5 days later. (d) Summary data of pH taken from (c). pH in the PCL at 2 and 7 days (closed bars) and pH in the mucus layer (open bars). All n = 6. ∗ denotes p < 0.05 between PCL and mucus pH. † denotes p < 0.05 between data points at 2 vs. 7 days.

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we can record changes in pH using this method in standard solutions over the physiological range (pH 6.6–7.6). To further verify this methodology, we measured the SNARF1-dextran emission ratios in pre-washed cultures after applying 20 μL of standard Ringer solution (pH 7.4) to the mucosal surface of an airway culture. Confocal scanning 2 h after Ringer addition revealed no depth-dependent change in pH (Fig. 5.3b). However, 48 h postRinger addition, a marked gradient is clearly visible, with an emission ratio indicative of a lower pH in the region (1–7 μm) associated with the PCL and a significantly higher emission ratio in the upper limit of the mucus-containing region >7 μm (Fig. 5.3c). However, after 7 days, when the PCL had collapsed and mucus had been allowed to accumulate, the emission ratio had increased and the gradient was less pronounced. Comparing the pH values in the 7 μm periciliary region in the presence and absence of a PCL (Fig. 5.3d), it can be seen that the pH has significantly risen from 6.7 to 6.95. Similarly, the pH in the top ∼7 μm of the mucus region had also increased although in a less pronounced fashion (pH 6.95–7.1). Importantly, as the PCL became depleted of liquid and increased its mucus content, the PCL pH rose (Fig. 5.3d). To visualize the cells, they can be labeled with cell-permeant acetoxymethyl ester (AM)-based dyes. Many live cell dyes are available commercially and we have successfully used calcein-AM to stain live cells in the epithelial layer (Fig. 5.2b). A color that is different to the one used to label the ASL and/or the mucus should be picked. We have also used SNARF1-AM as a cellular dye, even though its original purpose is as a pH-sensitive dye. Furthermore, other probes undoubtedly will prove useful in the future. Mucus can be labeled using fluorescent microspheres (100 nm), which co-localize to the “strands” in the mucus layer (Fig. 5.1c) and provide a general idea of mucus location in the ASL. Mucus transport rates can be measured using larger fluorescent microspheres (∼1 μm). There are many commercially available probes and dyes which are suitable for these measurements depending on the investigators’ individual needs. Extensive lists of probes and dyes can be found online at several vendors, including Molecular Probes. We have often triple-labeled our cells. For example, the ASL is labeled with Texas Red-dextran and the mucus is labeled with 100 μM FITC beads to give an indication of ultrastructure and also with 1 μm ultraviolet beads to measure rotational mucus transport rates. 1.2. Labeling of ASL for Confocal and Epifluorescence Microscopy

To standardize ASL height measurements, the cultures are prewashed to remove excess ASL and mucus, often at a predetermined time, in order to ensure similar starting ASL volumes. This is necessary since the airway cultures are primarily Na+ /volume

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absorbing and absorb excess ASL volume with time until a steadystate height is reached (8), similar to the proximal airway epithelia (11). Thus, cultures may be washed immediately before starting an experiment to study them under mucus-free conditions or may be washed 24–48 h before the experiment to allow mucus to accumulate and to facilitate the production of a “natural” ASL. Moreover, after washing, all liquid may be aspirated, so that ASL can be tracked from minimal starting levels (25). This is especially useful to look at ASL secretion. However, to study absorption, or absorption followed by secretion, a bolus of liquid (i.e., 20 μL) may be deposited on airway surfaces and followed with time (8). The desired fluorescent probes may be added either (i) days earlier, (ii) with the final wash of the mucosal surface followed by aspiration of the ASL to minimal levels, or (iii) in a bolus of liquid (i.e., 20–50 μL) at the start of the experiment. 1.3. Use of Perfluorocarbons

Since the ASL can easily evaporate when a culture is exposed to room air, care must be taken to avoid this. One approach is to provide a highly humidified environment that is present while imaging. This approach is feasible but is time-consuming and the atmosphere must be 100% humidified to prevent ASL evaporation. Another approach is to place oil over the culture to block ASL evaporation, but oil is not easily removed and is not O2 permeant (2). However, perfluorocarbon (PFC) is O2 permeant and evaporates with time and so it can be added to the mucosal surface during all ASL height and mucosal transport rate experiments to prevent the evaporation of ASL. PFC has been shown to have no affect on ASL height, the transepithelial voltage, or rotational mucus transport measurements and thus works well to prevent ASL evaporation (2, 7). In addition, PFC can be used as a vehicle for drug/compound additions and is used since it is immiscible with ASL (10). Given that addition of compounds in a liquid vehicle would directly increase the ASL volume, compounds are added as dry powder in a PFC suspension. By taking advantage of the fact that FC-72 PFC has a relatively low boiling point (56◦ C) compared to FC-77 PFC (97◦ C) the choice of PFC used can be tailored to the experiment. For example, we typically apply the shorter lasting FC-72 in order to measure baseline ASL volumes and for compound addition. Subsequently, FC-77 is added after addition of the compound/drug to prevent ASL evaporation.

1.4. XZ Confocal Microscopy and Measurement of the ASL

We prefer to use inverted confocal microscopes scanning in vertical (XZ) mode with high numerical aperture (1.2–1.3 NA) water or glycerol immersion lenses (see Note 6), to image from below the cultures (2). This system can obtain both qualitative and quantitative ASL data. Spinning disc confocals can also be used, although since they can only scan in the XY or horizontal mode, multiple images must be combined to make an XY stack

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and they only yield quantitative ASL data (6). We have also had some success at imaging ASL using an upright microscope (Fig. 5.3). However, high NA lenses cannot be used and instead, one must use a dry or a dipping lens (see Note 6). Furthermore, with upright microscopes, one is limited to the larger sized cultures (i.e., 30 mm diameter) since the lens cannot get close enough to the surface of the standard 10–12 mm diameter cultures. For scanning cultures on inverted microscopes, cultures are placed on a coverslip mounted in a chamber, which can either be heated or not. Several commercial designs are available (WPI and Invitrogen/Molecular Probes, etc.). The possibility also exists of using an oil lens and placing the culture directly onto the oil lens without a coverslip, but this method has not directly been tested. 1.5. Measurement of Mucus Transport Rates

The well-differentiated (ciliated) airway epithelial cultures coordinate ciliary beating to spontaneously transport mucus across the mucosal surface. This technique has revealed that the entire mucus layer moves as a single network as evidenced by the increase in linear velocity vs. the distance from the apparent center of rotation (Fig. 5.4b (2)). To measure rates of rotational mucus transport, we add 1–2 μm diameter fluorescent microspheres to the mucosal surface of the airway cultures, which preferentially segregate into the mucus layer. The microspheres are imaged in real time using conventional inverted epifluorescence microscope with a low-power dry lens and a digital camera. The mucus transport rate is then determined from 5-s exposure images (Fig. 5.4a). The movement of a single microsphere produces a streak of fluorescence in the image, with the length of the streak corresponding to the distance the microsphere has been transported in 5 s. The rotational mucus transport rates over the surface of the cultures are measured from these images, and the linear velocity of bead transport is normalized to a 1 mm distance from the center of rotation by linear regression analysis (Fig. 5.2b). Stationary mucus does not appear as streaks but can be imaged as plaques of mucus on the apical surface of the cultures (Fig. 5.4c). Alternatively, the rates of mucociliary clearance (MCC) can be determined from measurements of microsphere location changes from sequential images utilizing a high-speed CCD camera. The later technique is useful for constructing videos of the MCC (see (26)).

2. Materials 2.1. Measurement of ASL Height with Confocal Microscopy

1. Well-differentiated bronchial epithelial cell cultures. 2. Inverted confocal microscope which can perform vertical (XZ) scanning in two wavelengths simultaneously.

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Fig. 5.4. Measurement of rotational mucus transport. Epifluorescent microscopy of rotational mucus transport by airway epithelial cultures. (a) Five-second exposure image of mucus-associated fluorescent microsphere movements in a normal airway culture. (b) Plot of microsphere velocity against distance from the center of rotation (e.g., 1 mm). The slope of a best-fit line using linear regression analysis may be used to normalize transport to a set distance from the center. (c) Five-second exposure image of a stationary mucus plaque on a CF airway culture after all excess apical liquid has been absorbed by Na+ -led hyperabsorption.

Alternatively, an upright or spinning disc microscope can also be used. 3. Phosphate-buffered saline (PBS) (in mM): 125 NaCl, 4.2 KCl, 1.2 MgCl2 ·6H2 O, 1.2 CaCl2 ·H2 O, 9 K3 PO4 , pH 7.4. 4. Dextran-linked fluorescent probe. 5. Perfluorocarbon (PFC): FC-72, FC-77, or other electronic grade (3 M Company, Minneapolis, MN, USA).

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6. Ringer solution to add to the serosal side of the culture (in mM): 116 NaCl, 10 NaHCO3 , 5.1 KCl, 1.2 CaCl2 , 1.2 MgCl2 , 20 HEPES, 10 glucose, pH 7.4. 7. Cell chamber for viewing cultures on the microscope. 8. Analysis software: a. Image analysis software: e.g., ImageJ, which is freely available at http://rsb.info.nih.gov/ij/ or Metamorph b. Spreadsheet program: e.g., Excel, Microsoft, USA. 2.2. Measurement of Mucus Transport with Epifluorescent Microscopy

1. Well-differentiated (ciliated) bronchial epithelial cell cultures. 2. Inverted epifluorescent microscope with low-power lens. 3. Digital camera (either color or black and white) and image acquisition software. 4. Fluorescent microspheres (1–2 μm). 5. Perfluorocarbon (e.g., FC-77; but many other types are available with differing densities and boiling points). 6. Image analysis software (e.g., ImageJ or Metamorph).

3. Methods 3.1. Measurement of ASL (PCL and Mucus Layer) Height with Confocal Microscopy

1. Prewash cultures three times with PBS. Cultures that produce grossly visible mucus hurricanes may be excluded from ASL height measurement (see Note 1 (7)). 2. Add a PBS and fluorescent dye (0.5–2 mg/mL) to the mucosal surface of the bronchial cultures (e.g., 20 μL per 12 mm diameter culture). Then, either aspirate the excess dye to minimal ASL volumes or leave a predetermined amount of PBS/dye on the airway surface (see Notes 2 and 3). 3. Pending a suitable incubation time post-dye addition, PFC (∼100 μL) is added to the surface to prevent evaporation of the ASL and the culture is placed in the cell chamber with a serosal reservoir containing approximately 100 μL of modified HEPES-buffered Ringer solution and then placed on the scanning stage of the microscope (see Note 4). This amount of PFC was selected since it was sufficient to cover the ASL during recordings, yet evaporates soon after the cultures are returned to the highly humidified incubator (see Note 5). We have previously shown that PFC does not affect ASL height, pO2 , rotational mucus transport rates, or the transepithelial potential difference (2, 7, 9).

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4. Compounds (e.g., UTP) can be added to the ASL as dry powder suspensions in PFC. Compounds are resuspended as a slurry, either coarsely or after pulverizing in a mortar and pestle. PFC/compound slurries need to be sonicated or shaken just before addition to the cultures (see Note 5). 5. Obtain ASL heights from XZ scans of five predetermined points on each culture (one central and four circumferential) (see Note 6). 6. Import images into an image analysis software program, such as ImageJ (NIH freeware) or Metamorph (Universal Imaging). Images in a series can be opened and linked together using the stack function to speed up analysis. 7. Use the region of interest (ROI) function to measure the pixel width of the electronic magnification measurement bar from the confocal images to determine the number of pixels per micron. The scale can then be set within the program or later when analyzing in the spreadsheet. 8. Use the region of interest function to measure the height of the ASL by placing several regions of interest around the ASL that are later averaged for each image. Regions of interest are placed to avoid the 1 μm “fuzzy” interface between the ASL image and background image. Alternatively, one can perform a line scan-type analysis to measure ASL height (Fig. 5.2). 9. ASL height data acquired here are then moved to a spreadsheet, such as Excel, to analyze and determine the height. The multiple ASL heights taken for each image are averaged and then the averages for each of the five predetermined points on each culture are averaged to obtain the ASL height for that individual culture. 3.2. Fluorescent Imaging of Rotational Mucus Transport

1. Identify cultures for rotational mucus transport either visually or by phase contrast microscopy (see Note 7). 2. Add a 0.01% (vol/vol) fluorescent microsphere/PBS suspension to the mucosal surface, typically 20–50 μL per 12 mm diameter culture. 3. Add PFC to the apical surface of the cultures to prevent evaporation of the ASL. Note: The working distance of the low-power objective is adequate to image the microspheres/mucus while the cultures remain in their “longterm” culture dishes. Not removing the cultures from their dishes is advantageous as it maintains the sterility of the cultures since the dish lid of cultures does not need to be removed. 4. Using a low-power 4–10× inverted epifluorescent microscope coupled to a digital camera and data acquisition

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software, focus on the microspheres in the rotating mucus and acquire images over approximately 0.1 s, then switch to a 5-s exposure to image the “streaks” of moving microspheres. 5. Compounds suspended in PFC can then be added to the ASL. 6. Import the images into an image analysis software program. A series of images can be opened and linked together using the stack function to speed up analysis. 7. Then use the set scale function to set the size of the image based on comparison to an image of a reticule scanned under the same power. 8. Use the ROI selection tools to measure the distance (streak) the microsphere has traveled and the distance it is from the center of the hurricane. Log the data into a spreadsheet. Repeat these experiments multiple times for microspheres at varying distances from the hurricane center. 9. Plot the total distance of microsphere movement against the distance from the hurricane center, and using linear regression, extrapolate to set the distance from the center (we use 1 mm) to normalize microsphere movement. 3.3. Conclusions

In conclusion, we describe fluorescent microscopy-based methods to assess ASL structure/function. While these methods have traditionally been used to measure ASL height and mucosal transport rates, we also demonstrate that they can be employed to measure other ASL properties including the establishment of pH gradients and the molecular sieving properties of the glycocalyx. We believe these techniques will further aid in the understanding of respiratory diseases in which ASL properties are altered such as asthma, chronic pulmonary obstructive disease, and cystic fibrosis.

4. Notes 1. Cultures that spontaneously produced grossly visible mucus “hurricanes” and exhibited rotational mucus transport can be excluded from ASL height studies to remove the confounding effects of the mucus reservoir effect (7). To remove mucus from ALI cultures, approximately 0.5 mL of PBS is added mucosally and aspirated, repeating three times. In cases of excessive mucus production, the cultures may be incubated with 0.5 mL PBS at 37◦ C in the tissue culture incubator for 15 min and then aspirated. If this does not remove all mucosal mucus then the cultures can again be

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incubated with ∼0.5 mL PBS and 1 mM dithiothreitol for ∼15 min, followed by the 3× PBS rinse. 2. The fluorescent intensity of Texas Red-dextran slowly diminishes when placed in the ASL over days, due to either degradation, uptake by pinocytosis, or diffusion through the tight junctions. Hence, a greater amount of dye (2 mg/mL) will need to be added for longer duration experiments (i.e., over several days) than if they are to be examined immediately (0.2 mg/mL). 3. Depending on the experimental design, pre-washing the culture may be desirable or may obscure the response that is being measured. For example, pre-washing the cultures will remove all inhibitors of ENaC and result in a primarily absorptive phenotype (12, 14). Since there is no chemical gradient for Cl– secretion, and instead, Cl– must utilize an electrical gradient that is supplied by the inhibition of ENaC, this could be detrimental if a secretagogue was being studied under supposed physiological conditions (11). To avoid this problem amiloride (10–100 μM) or aprotinin (∼1 U/mL) can be added into the Texas Red bolus and left on the cultures. However, the natural inhibitors of ENaC that are present in the ASL are replenished within ∼24 h, so the cultures can also be washed, loaded with dye, and then used 24 h later making the addition of amiloride or aprotinin unnecessary (12, 14). 4. Our cultures are maintained under sterile conditions. However, the cultures risk exposure to pathogens (i.e., mold spores, bacteria, fungus) during all our experiments, which can destroy the cultures. The best approach to protect against infection has been to transfer the cultures from their “long-term” culture dishes (where they are kept in bronchial epithelial growth media, or BEGM) into a secondary dish containing Ringer’s solution (with PFC kept on the mucosal surface to prevent ASL evaporation). From this second dish the cultures can be transferred onto the stage of the confocal microscope. After the experiment, the cultures are washed several times in PBS and then transferred back to the “longterm” culture dish. Serial experiments over several days are thus possible but are more risky since the mucosal surface cannot be washed during the experiment since this will alter the ASL. However, with careful rinsing of the serosal surface and transference between “long-term” and temporary culture dishes after every time point we have routinely studied cultures over 5–7 days with no sign of contamination. In addition to careful handling of the cultures to minimize contamination, we also carefully wipe down our workspace around the microscope (e.g., the stage and microscope controls) and also clean the cell chamber with 70% ethanol (but

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not the lens which should only be cleaned with approved lens cleaner). When measuring ASL on multiple cultures it is recommended that the cell chamber be cleaned between either individual or small groups of cultures to prevent possible contamination from spreading. 5. Typically, the faster evaporating FC-72 will initially be added to cover the ASL, and once basal measurements have been made and the FC-72 has evaporated to minimal levels (which can be assessed visually), compounds are added to the apical surface in more FC-72. If the compounds have been added coarsely (e.g., from the packet or following grinding with a mortar and pestle), they will need to be sonicated/shaken immediately before adding them to the ASL to ensure even distribution in the PFC. An example of masses/volumes added would be to prepare 0.1 mg in 200 μL FC-72 and to aliquot a smaller amount into the ASL, such as 0.001 mg in 2 μL FC-72. 6. To image ASL by confocal microscopy, we have had the best results with a 63× water (1.2 NA) or a 63× glycerol immersion lens (1.3 NA) which has sufficient working distances (>200 μm) to image the cultures/ASL over a serosal bath with a volume <100 μL. However, we have also used dry lenses which have lower NAs but working distances measured in millimeters and dipping lenses. On upright microscopes, dipping lenses can be placed directly into the PFC. On inverted microscopes, dipping lenses can also be used, although your friendly microscope rep will likely tell you that this is not the case. Do not listen to them: we have had good success with placing a large drop of water on a 40× dipping lens used on an inverted scope. The higher NA (0.75) and a working distance of ∼3–5 mm make this lens ideal for measuring the very large volumes of mucus that sometimes occur on airway cultures, especially those exhibiting mucus hurricanes. 7. Not all cultures produce rotational mucus transport. The formation of mucus hurricanes is sometimes facilitated by washing the cultures every 2–3 days.

Acknowledgments We gratefully acknowledge the help and support of our colleagues in the UNC CF Center, especially the Michael Hooker Microscopy Center and the Tissue and Histology Cores. This work was funded by the British-American Tobacco Company, the Cystic Fibrosis Foundation, and the NIH/NHLBI.

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References 1. Wine, J. J. (1999) The genesis of cystic fibrosis lung disease. J Clin Invest 103, 309–312. 2. Matsui, H., Grubb, B. R., Tarran, R., Randell, S. H., Gatzy, J. T., Davis, C. W., et al. (1998) Evidence for periciliary liquid layer depletion, not abnormal ion composition, in the pathogenesis of cystic fibrosis airways disease. Cell 95, 1005–1015. 3. Matsui, H., Randell, S. H., Peretti, S. W., Davis, C. W., and Boucher, R. C. (1998) Coordinated clearance of periciliary liquid and mucus from airway surfaces. J Clin Invest 102, 1125–1131. 4. Rahmoune, H., and Shephard, K. L. (1995) State of airway surface liquid on guinea pig trachea. J Appl Physiol 78, 2020–2024. 5. Sims, D. E., and Horne, M. M. (1997) Heterogeneity of the composition and thickness of tracheal mucus in rats. Am J Physiol 273, L1036–L1041. 6. Jayaraman, S., Song, Y., Vetrivel, L., Shankar, L., and Verkman, A. S. (2001) Noninvasive in vivo fluorescence measurement of airwaysurface liquid depth, salt concentration, and pH. J Clin Invest 107, 317–324. 7. Tarran, R., Grubb, B. R., Gatzy, J. T., Davis, C. W., and Boucher, R. C. (2001) The relative roles of passive surface forces and active ion transport in the modulation of airway surface liquid volume and composition. J Gen Physiol 118, 223–236. 8. Tarran, R., Button, B., Picher, M., Paradiso, A. M., Ribeiro, C. M., Lazarowski, E. R., et al. (2005) Normal and cystic fibrosis airway surface liquid homeostasis. The effects of phasic shear stress and viral infections. J Biol Chem 280, 35751–35759. 9. Worlitzsch, D., Tarran, R., Ulrich, M., Schwab, U., Cekici, A., Meyer, K. C., et al. (2002) Effects of reduced mucus oxygen concentration in airway pseudomonas infections of cystic fibrosis patients. J Clin Invest 109, 317–325. 10. Tarran, R., Grubb, B. R., Parsons, D., Picher, M., Hirsh, A. J., Davis, C. W., et al. (2001) The CF salt controversy: in vivo observations and therapeutic approaches. Mol Cell 8, 149– 158. 11. Boucher, R. C. (1994) Human airway ion transport. Part one. Am J Respir Crit Care Med 150, 271–281. 12. Tarran, R., Trout, L., Donaldson, S. H., and Boucher, R. C. (2006) Soluble mediators, not cilia, determine airway surface liquid volume in normal and cystic fibrosis superficial airway epithelia. J Gen Physiol 127, 591–604.

13. Chambers, L. A., Rollins, B. M., and Tarran, R. (2007) Liquid movement across the surface epithelium of large airways. Respir Physiol Neurobiol 159, 256–270. 14. Garcia-Caballero, A., Rasmussen, J. E., Gaillard, E., Watson, M. J., Olsen, J. C., Donaldson, S. H., et al. (2009) SPLUNC1 regulates airway surface liquid volume by protecting ENaC from proteolytic cleavage. Proc Natl Acad Sci USA 106, 11412–11417. 15. Caputo, A., Caci, E., Ferrera, L., Pedemonte, N., Barsanti, C., Sondo, E., et al. (2008) TMEM16A, a membrane protein associated with calcium-dependent chloride channel activity. Science 322, 590–594. 16. Schroeder, B. C., Cheng, T., Jan, Y. N., and Jan, L. Y. (2008) Expression cloning of TMEM16A as a calcium-activated chloride channel subunit. Cell 134, 1019–1029. 17. Yang, Y. D., Cho, H., Koo, J. Y., Tak, M. H., Cho, Y., Shim, W. S., et al. (2008) TMEM16A confers receptoractivated calcium-dependent chloride conductance. Nature 455, 1210–1215. 18. Myerburg, M. M., Butterworth, M. B., McKenna, E. E., Peters, K. W., Frizzell, R. A., Kleyman, T. R., et al. (2006) Airway surface liquid volume regulates ENaC by altering the serine protease-protease inhibitor balance: a mechanism for sodium hypersabsorption in cystic fibrosis. J Biol Chem 281, 27942–27949. 19. Hentchel-Franks, K., Lozano, D., EubanksTarn, V., Cobb, B., Fan, L., Oster, R., et al. (2004) Activation of airway Cl- secretion in human subjects by adenosine. Am J Respir Cell Mol Biol 31, 140–146. 20. Lazarowski, E. R., Tarran, R., Grubb, B. R., van Heusden, C. A., Okada, S., and Boucher, R. C. (2004) Nucleotide release provides a mechanism for airway surface liquid homeostasis. J Biol Chem 279, 36855–36864. 21. Tarran, R. (2004) Regulation of airway surface liquid volume and mucus transport by active ion transport. Proc Am Thorac Soc 1, 42–46. 22. Tarran, R., and Boucher, R. C. (2002) Thinfilm measurements of airway surface liquid volume/composition and mucus transport rates in vitro. Methods Mol Med 70, 479–492. 23. Coyne, C. B., Ribeiro, C. M., Boucher, R. C., and Johnson, L. G. (2003) Acute mechanism of medium chain fatty acid-induced enhancement of airway epithelial permeability. J Pharmacol Exp Ther 305, 440–450. 24. Stonebraker, J. R., Wagner, D., Lefensty, R. W., Burns, K., Gendler, S. J., Bergelson,

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J. M., et al. (2004) Glycocalyx restricts adenoviral vector access to apical receptors expressed on respiratory epithelium in vitro and in vivo: role for tethered mucins as barriers to lumenal infection. J Virol 78, 13755– 13768. 25. Rollins, B. M., Burn, M., Coakley, R. D., Chambers, L. A., Hirsh, A. J., Clunes, M. T., et al. (2008) A2B adenosine receptors regulate the mucus clearance component of the

lung’s innate defense system. Am J Respir Cell Mol Biol 39, 190–197. 26. Tarran, R., and Button, B. (2004) Measurement of airway surface liquid height (volume) by confocal microscopy. Virtual Repository Cyst Fibros Eur Netw. http://central.igc.gulbenkian.pt/cftr/vr/ d/tarran_button_measurements_airway_ surface_liquid_height_confocal_microscopy. pdf

Chapter 6 Measurement of Fluid Secretion from Intact Airway Submucosal Glands Jeffrey J. Wine, Nam Soo Joo, Jae Young Choi, Hyung-Ju Cho, Mauri E. Krouse, Jin V. Wu, Monal Khansaheb, Toshiya Irokawa, Juan Ianowski, John W. Hanrahan, Alan W. Cuthbert, and Kim V. Tran Abstract Human airways are kept sterile by a mucosal innate defense system that includes mucus secretion. Mucus is secreted in healthy upper airways primarily by submucosal glands and consists of defense molecules mixed with mucins, electrolytes, and water and is also a major component of sputum. Mucus traps pathogens and mechanically removes them via mucociliary clearance while inhibiting their growth via molecular (e.g., lysozyme) and cellular (e.g., neutrophils, macrophages) defenses. Fluid secretion rates of single glands in response to various mediators can be measured by trapping the primary gland mucus secretions in an oil layer, where they form spherical bubbles that can be optically measured at any desired interval to provide detailed temporal analysis of secretion rates. The composition and properties of the mucus (e.g., solids, viscosity, pH) can also be determined. These methods have now been applied to mice, ferrets, cats, pigs, sheep, and humans, with a main goal of comparing gland secretion in control and CFTR-deficient humans and animals. Key words: Submucosal gland, exocrine secretion, CFTR, mucosal innate defense, ion channel, ion transporter, calcium-activated chloride channel (CaCC), cAMP, Ca2+ , myoepithelial cell, serous cell, mucous cell.

1. Introduction 1.1. The Method: Optical Measurement of Gland Mucus Secretion

The cartilaginous airways of most vertebrates are kept clean by a thin film of mucus that traps pathogens which are then removed by mucociliary clearance or cough. Mucus is produced in part by submucosal glands (Fig. 6.1a). In upper airways of human

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Fig. 6.1. (a) Microdissected human airway submucosal gland. Acinar region in the upper right belongs to a different gland, and portions of the acinar region of this gland are obscured in the lower right. (b) A field of mucus bubbles from a pig trachea stimulated for 30 min with 10 μM forskolin. This image was chosen to illustrate various features of the method. Some examples of bubbles that have wet the surface are merged and that would not be scored are marked with “M”. A field showing a clear example of “surface secretion” is circled with a dashed line. Seven bubbles within the circle were produced by glands (∗ ). These are distinguished by their larger size and responsiveness to agonists. Scale bars: a 250 μm, b 1 mm.

adults, each square centimeter of airway surface receives mucus from ~100 glands. The rate of secretion from individual glands can be monitored by first coating the prepared mucosal surface with oil, so that mucus emerging from the gland ducts forms spherical bubbles, which can be imaged at any desired interval, and the secretion rates then determined. An example of mucus bubbles in the later stage of an experiment with a pig trachea is shown in Fig. 6.1b. This method was first described in 2001 (1) based on an earlier method in which bubbles that formed under oil were monitored by manual collection with capillaries (2). In this chapter we give some of the rationales for making these measurements, list some alternative methods, discuss the pros and cons of the approach, and provide detailed instructions on how to perform the measurements. 1.2. Mucus and Airway Sterility

Healthy human airways are sterile in spite of the vast quantities of bacteria, viruses, and fungal spores we inhale. The mucosal innate immune system of the airways is highly evolved, with many

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interacting components that provide complementary and redundant protection. Nevertheless, in cystic fibrosis (CF) the loss of a single type of anion channel, CFTR, disrupts innate mucosal immunity sufficiently to allow infections to be readily established in the airways. This suggests that CFTR contributes to more than one aspect of airway mucosal defenses, consistent with the location of CFTR in ciliated airway surface epithelia (3), serous cells of airway submucosal glands (4), and airway macrophages (5). Mucus clearance is a critical component of airway defenses (6). Mucus can be cleared by the mucociliary escalator and by cough, and both are impaired in CF (7). In the upper airways of humans, where infections first begin in CF (8, 9), most of the mucus is produced by submucosal glands (10). It was predicted that gland mucus secretion would be defective in CF after CFTR was localized to gland serous cells (4), after anion secretion in the Calu-3 serous cell model was shown to depend upon CFTR (11), and after gland mucus secretion was blocked with anion transport inhibitors (12–20). Therefore, we developed methods to measure airway gland secretion directly (1) and have applied these methods to glands from a variety of animals (21, 22), control, and CF humans (23, 24). We refer to the mucus that exits from the gland ducts into the oil layer as primary gland mucus. Even though this mucus is “pure” compared with sputum (see below), it is nevertheless a highly heterogeneous mixture of mucins (primarily MUC5B), an array of at least 100 macromolecules that include antimicrobials like lysozyme (25); siderocalins that inhibit bacterial growth by sequestering iron-containing bacterial siderophores (26); protease inhibitors like secretory leukoprotease inhibitor (SLPI) (27); molecules like Splunc1 (28) that can regulate the epithelial Na+ channel ENaC (29); and a host of smaller molecules such as uric acid (30), other unidentified anti-oxidants (31), and thiocyanate, a critical component of the lactoperoxidase antimicrobial system (32, 33). All of the macromolecular components are stored in highly condensed form within storage granules of cells in the tubules and acini of the glands. They must expand in an orderly manner to form optimally protective mucus (34). The mucins, because of their extreme size and charge, pose special problems in this regard, and the root cause of cystic fibrosis may lie in deficiencies in this process, secondary to deficient anion-mediated fluid secretion (35, 36). 1.3. Mechanisms of Fluid Secretion

The major component of mucus is water, with solid content varying between 2 and 8% (37). In the glands, water secretion is driven by anion secretion, with Cl− and HCO3 − as the main anions. Measurements of pH in the secreted mucus at the gland orifice indicate that it has ~12–15 mM of HCO3 − (38). However, HCO3 − of the initial fluid secreted by the serous cells is probably

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higher. Calu-3 cells secrete very high levels of HCO3 − when stimulated with forskolin (39), and when HCO3 − is replaced by HEPES in the medium bathing the glands, gland mucus secretion is reduced by about 50% – about the same reduction that is seen when Cl− secretion is blocked with bumetanide (1, 21, 22, 40). In CF, secretion of both these anions and water that would accompany them is diminished. For CF glands stimulated via pathways that activate only CFTR-dependent secretion almost no fluid is secreted and the gland lumens fill with macromolecules (12, 23). For CF glands stimulated via pathways that activate nonCFTR, CaCC-dependent fluid secretion, fluid secretion occurs but it is diminished, resulting in mucus with a higher solid content, increased viscoelasticity (41), and lower pH (21). 1.4. Gland Mucus vs. Sputum

Mucus is a component of sputum, which is the mixture of all materials that make it to the airway surface such as gland mucus, mucins released from surface goblet cells (mainly MUC5AC), fluid and molecules secreted by surface epithelia, fluid that might arise in the alveoli (42), and white blood cells. When obtained by expectoration, sputum contains varying amounts of saliva. It seems highly likely that the properties of all mucus components have evolved to insure optimal interactions among themselves to yield the highly efficient defense system that protects the airways; these interactions are clearly not optimal in CF airways.

1.5. Structure and Distribution of Airway Glands

A microdissected airway gland is shown in Fig. 6.1a. Using serial sectioning as well as electron microscopy, Meyrick and colleagues (43) identified four components of a human airway gland from the human trachea: serous acini, mucous tubules, a collecting duct into which the mucous tubules empty, and finally a ciliated duct that is continuous with the airway surface. CFTR is expressed in the serous cells and ciliated duct (4) – low levels of expression in the mucous cells are also seen by some investigators (44) and in mucous cell cultures (45).

1.6. Species Differences in Airway Glands

Choi et al. carried out comparative studies of airway submucosal gland morphology and distribution in 11 species and related gland volume to airway diameter according to the formula V = 0.7d −0.3 where V is the gland volume in μL/cm2 of surface area and d is the tracheal diameter in mm (46). The rabbit trachea is a striking exception to this rule as tracheal glands are absent (47). The rabbit is an “obligate nose breather” and the nasal sinuses are unusually convoluted and packed with submucosal glands. These data in aggregate indicate that airway glands are strategically located to produce mucus onto the surfaces most likely to be impacted by inhaled pathogens.

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1.7. Previous Methods of Measuring Airway Mucus Secretion

Prior studies of secretion rates by individual airway glands are relatively rare (for summary, see table 1 in Joo et al., 2001) (1).

1.7.1. Labeled Glycoconjugates as Surrogates for Secretion

For many years, the most common method for measuring airway gland secretion was to collect the supernatant from mucosal explants after incubating them with various mediators and then estimating mucus secretion by quantifying the concentration of some marker that was thought to correlate with mucin release, such as macromolecules labeled with 35 S or various lectins (48). These methods cannot distinguish either the origin or the nature of the labeled molecules, had poor time resolution, and did not measure fluid secretion. Several methods were devised to overcome these limitations and provide data on volume secretion from single glands.

1.7.2. Tantalum Powder

In one of the earliest methods for studying individual gland secretions, powdered tantalum was placed on the airway surface to reveal “hillocks” of mucus that formed above gland ducts (49) that were subsequently visualized with neutral red staining (50). The tantalum method has been further refined by the use of computerized methods of measuring secretions (51).

1.7.3. Direct Micropipet Collection from Gland Duct Orifices

More elegantly, Nadel’s group collected single gland secretions directly, under oil, using a fire-polished, constant bore glass capillary, with internal diameter of 95 μM and filled with Sudan blackstained oil, by covering the gland orifice and collecting the mucus with a small amount of negative pressure (52). Nadel and his colleagues used this method in a series of studies on cats (53–55). To our knowledge this method has not been used on species other than cats and has not been used for many years. The discontinuation of the micropipet method is probably related to the technical difficulties involved, while its restriction to cats probably arises from the relative ease with which cat mucus can be collected. In our studies, we find cat mucus to be much less viscous than the mucus of the other species studied (unpublished data). The collection and manipulation of tiny quantities of higher viscosity airway mucus from single glands of other species present technical challenges that are circumvented by optical methods.

1.7.4. Collection of Oil-Trapped Secretions with Constant-Bore Capillaries

The first quantification of single airway gland secretions was carried out by Quinton who collected secretions from excised cat tissues under oil at timed intervals with constant bore micropipets (2). This allowed single gland secretion rates to be determined and also provided material for elemental analysis with the X-ray microdrop method (2).

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This method provided the starting point for our approach. We modified it to a purely optical method for two main reasons: as stated above, the constant bore collection method does not work well with species such as pigs, sheep, and humans which have much more viscous mucus than cats and the collections are time consuming, are prone to error, and limit the number of glands that can be studied. 1.7.5. Other Methods

Single gland secretion in pig bronchi has been studied with video microscopy, using a water immersion lens focused on the orifice of the gland duct (56). Secretion rates were not quantified, but the latency of the rapid response to carbachol was estimated by dilation of the gland duct and emergence of particles from the gland. Finally, an elegant series of studies of isolated glands from the cat has been carried out by Shimura and his colleagues starting in 1986 (57–70). These quantified mucus secretion with a variety of markers, such as glycoconjugates and Na+ efflux, measured myoepithelial contractions, and surveyed the agonists required for secretion.

1.8. Measuring Molecular Composition and Physical Properties of Primary Mucus

After bubbles of primary gland mucus are produced their composition and physical properties can be studied using microanalytical techniques. Because of space limitations these methods and protocols are not covered here. Interested readers can consult original articles on measurements of mucus pH (21, 38, 71), viscosity (71), other ions (71), and proteins (24). The solids content, viscoelasticity, and spinnability of primary mucus have been measured using methods that have been modified to work with small samples, but the results have so far only appeared in the abstract form.

1.9. Advantages and Limitations of the Optical, Single Gland Method 1.9.1. Advantages of the Single Gland Optical Method

Because glands are heterogeneous with regard to secretion rates, only single gland methods can determine the statistical basis for average responses obtained by other methods. When studying differences in the amount or composition of airway secretions caused by different treatments or associated with properties such as species, age, region of airway, or disease state, single gland studies can distinguish factors that are confounded when samples are pooled. For example, differential recruitment or loss of distinct populations of glands, changes in gland number, gland size, or temporal secretion properties are either lost entirely or obscured when samples are pooled.

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Compared with micropipet collections, the optical method allows secretion rates to be quantified more accurately, more frequently, and in more glands. Significant increases have occurred in the cost-effectiveness of digital imaging since this method was introduced and these are continuing, so that the tradeoff between accuracy (maximized with higher magnification and hence smaller area covered) and number of glands sampled in parallel is no longer an issue. 1.9.2. Limitations of the Single Gland Optical Method

This method is not optimal for long-term monitoring of secretion because the accumulating mucus bubbles fuse or lose their spherical shape. Long-term monitoring can be enabled by periodically collecting the secretions, but the collections introduce gaps in the monitoring and are labor intensive. Thus the single gland method complements the method of Ballard and his collaborators, in which bulk mucus is collected for several hours from entire bronchi (13, 14, 16, 18). The oil layer method eliminates the natural interaction between gland secretions and the surface epithelium, which can be useful or harmful depending upon the question being asked. Ultimately, it will be important to study how glands and airway surface epithelia interact to control the depth and composition of airway surface liquid, which in turn affect mucociliary clearance (72, 73). Some efforts along this line have been made by Widdicombe (72) and Ballard (41). The composition of primary gland mucus collected under oil will be altered to the extent that lipophilic constituents of the mucus partition into the oil. The most important limitation in these studies of gland secretion is that all uses of this method to date have been in isolated tissues studied in vitro. Glands in these conditions lack their normal blood supply and neural inputs, and so the natural responses of glands can only be inferred from these data. Regrettably, whole animal physiological studies have become increasingly expensive to carry out and as a result are a diminishing component of physiological studies. To our knowledge the most recent in vivo studies of single gland secretion were carried out by Nadel’s group in the 1980s, and Haxhiu’s group may be the last one still doing such work (74). For review see (75).

2. Materials We list below the equipment we use, but note that many variants are possible for either increased performance or decreased cost – we have not carried out a detailed cost–performance analysis.

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2.1. Equipment for Maintaining and Imaging Tissues 2.1.1. Cameras

Digital cameras should have the following minimal features: autofocus; zoom macrolenses capable of shooting tissue directly at a distance of ~2 cm; ability to use an adapter to attach the camera to a microscope for monitoring secretion in a smaller tissues; ability to be controlled by software that will automatically control imaging intervals and download images from the camera to computer. In most of our gland secretion studies, we used the Nikon Coolpix 995/4500 and Canon Powershot G9. When attached to a microscope, an adapter LNS-30D or 23D (Zarf Enterprises) was screwed on the camera’s lenses thread. The focusing length of the camera was left on infinity while using microscope to set the focus. Taking time-lapse macro- and micrograph was controlled through the USB port by downloaded software (Krinnicam).

2.1.2. Microscopes

Microscopes are needed when working with smaller tissues such as those from mice. We use binocular (Wild Heerbrugg, Switzerland) or trinocular (Canon Conversion lens Adapter) dissecting microscopes. Microscopes not designed for photomicrography can be used by purchasing or machining adaptors to mate the camera to one of the binocular eyepieces.

2.1.3. Physiological Chambers for Temperature/Gassing/Humidity Control

We use two kinds of physiological chambers to control the tissue environment. A micro-incubator chamber, LU-CB1, is connected to a temperature controller, either TC 202A or TC 102 model, Harvard Apparatus (Holliston, Massachusetts), and is adequate for most routine work; they also include an inlet ring that superfuses the preparation with supplied gas. Humidifying gas (95% O2 –5% CO2 or 100% O2 ) is supplied to the optical chamber by passing incoming gas from a gas tank through warm, sterilized, deionized water in a flask on a hotplate so that gas entering the chamber is ~37◦ C. Because CO2 is easily lost through plastic tubing, we use copper tubing when long distances must be traversed between the gas tanks and the preparation. The chambers are covered with a coverslip when not imaging to further minimize evaporative loss and keep the CO2 level accurate and the bath at pH 7.4. (In experiments with humidified HEPES-buffered solutions, 100% O2 is used as the gas.) Sensortek TS-4 Peltier effect stages allow cooling as well as heating and can maintain temperature more accurately. We have designed a chamber to be used with these devices so that we can superfuse humidified gas.

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Fig. 6.2. Schematic of setup. The piece of mucosa with attached glands is pinned to Sylgard cast within a 35 mm petri dish, so that the serosal side is immersed in 2 ml of KBR that is kept at 37◦ C by a thermistor-controlled heating block that also delivers warmed, humidified gas that superfuses the preparation. The bubbles are imaged via a camera or microscope and the digital images are analyzed off-line with ImageJ software; graphs of volume changes and secretion rates over time are produced with Excel.

2.1.4. Optical Chambers

These are made from 35 mm plastic culture dishes by adding 5 ml of Sylgard© resin (Dow Corning) mixed with catalyst per manufacturer’s instructions and cured at high humidity at 85◦ C. When prepared in this way, the Sylgard is thick enough to secure the pins needed to hold the tissue at the air/Krebs interface while allowing a bath volume of at least 2 ml. These dishes fit into the LU-CB1 chamber. In the chamber, the tissue is held horizontally at the air/solution interface by pins all cut to the same length. Pins are Austerlitz stainless steel insect pins (size 0), cut to a length of 1.2 cm; the top 2–4 mm of the unsharpened end is bent at a right angle. The experimental setup is shown in Fig. 6.2.

2.2. Reagents

Unless otherwise specified, all reagents were obtained from Sigma. The components of the buffers are not listed independently.

2.2.1. Krebs–Ringer Bicarbonate Buffer (KRB)

The KRB composition is (in mM) as follows: 115 NaCl, 2.4 K2 HPO4 , 0.4 KH2 PO4 , 25 NaHCO3 , 1.2 MgCl2 , 1.2 CaCl2 , and 10 glucose (pH 7.4). Osmolarity is measured on a Westcor vapor pressure osmometer and adjusted with distilled water to ~290 mOsm. To minimize tissue exposure to endogenously generated prostaglandins during tissue preparation and mounting, 1.0 μM indomethacin is present in the Krebs throughout the experiment unless otherwise indicated. During experiments the KBR is bubbled with 95% O2 –5% CO2 .

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2.2.2. Bicarbonate-Free Buffers (1-HEPES and 25-HEPES)

2.2.3. Agonists of Secretion

For these buffers, all HCO3 – in the Krebs buffer is replaced with either 25 mM N-2-hydroxyethylpiperazine-N -2-ethanesulfonic acid (HEPES, sodium salt) or 1 mM HEPES + 24 mM NaCl. The 1 and 25 mM levels of HEPES were adjusted to pH 7.4 after gassing with O2 . The 25 mM HEPES solution is predicted to provide the best control for intracellular pH, while the 1 mM HEPES solution minimizes the chance that alterations in secretion were secondary to ion gradients established between the bath and gland lumen. Most of our studies use 25 mM HEPES. The two concentrations have not been rigorously compared, but they appear to have comparable inhibitory effects on mucus secretion. 1. Carbachol dissolved in sterilized, deionized water at a stock concentration (S.C.) of 10 mM. 2. Phenylephrine dissolved in sterilized, deionized water at an S.C. of 10 mM. 3. Isoproterenol dissolved in sterilized, deionized water at an S.C. of 10 mM. 4. Forskolin dissolved in DMSO at an S.C. of 10 mM. 5. Vasoactive intestinal peptide dissolved in sterilized, deionized water at an S.C. of 1 mM.

2.2.4. Inhibitors of Secretion

1. Atropine dissolved in dimethyl sulfoxide (DMSO) at an S.C. of 1 or 10 mM. 2. Phentolamine dissolved in sterilized, deionized water at an S.C. of 10 mM. 3. Propranolol dissolved in sterilized, deionized water at an S.C. of 10 mM. 4. Acetazolamide dissolved in DMSO at an S.C. of 1 M. 5. Bumetanide dissolved in 0.5 N NaOH at an S.C. of 0.1 M.

2.2.5. Other Reagents

1. Indomethacin dissolved in absolute ethanol at an S.C. of 10 mM. 2. Water-saturated mineral oil is prepared by shaking and then sonicating a mixture of heavy mineral oil (EMD MX1560/1) and sterilized, deionized water (50:50 by volume) for about 5 min and stored at 4◦ C prior to use. 3. Tetrodotoxin dissolved in 0.2% acetic acid at an S.C. of 0.1 mM. 4. CFTRinh 172 dissolved in DMSO at an S.C. of 40 mM. 5. GlyH101 dissolved in DMSO at an S.C. of 50 mM. 6. Glibenclamide dissolved in DMSO at an S.C. of 1 M. 7. Benzamil dissolved in DMSO at an S.C. of 10 mM.

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3. Methods 3.1. Tissue Acquisition and Preparation 3.1.1. Human Transplant Recipient Lungs

Human transplant recipient lungs are obtained in the operating room as soon as they are removed and are placed into cold Physiol© solution for transport to the laboratory. All patients from whom lungs are harvested must first have given informed consent, which is requested by their physician who is also a member of the research team. Lungs are maintained at 4◦ C until use. Initial dissections are carried out by clamping the most proximal available bronchial ring with a straight Adson hemostat fixed to a rotatable fixture of adjustable height; tissues are then dissected away from the airways moving from proximal to distal until a sufficient length of bronchial tree is obtained. Bronchi are transected at the distal dissection margins with a scalpel, and the isolated bronchial tree is rinsed; transferred to clean, cold, gassed KBR; and maintained at 4◦ C until use.

3.1.2. Human Donor Tracheal/Bronchial Scraps

Human donor tracheal/bronchial scraps are obtained at the same time as the lungs from transplant recipients and are treated in the same way. Informed consent is not required for this tissue, which consists of ~0.5–2 cm lengths of tracheal/bronchial trimmings.

3.1.3. Sheep, Pig, and Ferret

Sheep (Suffolk–Rambouillet), pig (Yorkshire), ferret (Mustela putorius furos) tissues were harvested within 1-h post-mortem after animals were killed with pentobarbital injection and after acute experiments unrelated to the present studies. Tracheas were maintained in ice cold KBR until use (within 24 h).

3.1.4. Mouse

Mouse tracheas were dissected from C57black/6 or Balb/c mouse immediately after killing them by a brief exposure to a 100% CO2 gas atmosphere.

3.2. Mucosal Preparation 3.2.1. Mucosal Dissection and Mounting

For each experiment an airway section of about 1.5 cm is cut off (smaller if required down to a minimum usable size of ~0.5 cm), opened up along the dorsal (posterior) fold in ice-cold, oxygenated KRB, and pinned mucosal side up in a Sylgard-lined dish. The mucosa with underlying glands is carefully dissected from the cartilage and connective tissues and mounted in a 35 mm, Sylgard-lined plastic Petri dish with the serosa in the bath (2 ml

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volume) and the mucosa in air. Usually, only mucosa from the cartilaginous (ventral or anterior) portion of the trachea is used to avoid powerful muscle contractions induced by agonists acting on the trachealis muscles. 3.2.2. Mucosal Cleaning, Drying, Oiling

The tissue surface is gently cleaned with several cotton swabs moistened with distilled water and then further dried with a gentle but focused stream of gas (we use a gas stream, 95% O2 /5% CO2 , of about 2 mm at the source tip). The cleaning and drying process is important to insure that spherical bubbles of mucus form within the oil layer. During drying with the gas stream, the reflectance of the mucosal surface should change from shiny to dull as the residual water is dried from the surface. Immediately after drying, 30–40 μL of water-saturated mineral oil is placed on the surface. The exact amount is determined by the size of the tissue; it is important to avoid contact between the edge of the oil puddle and the Krebs solution, but the oil layer must be thick enough to accommodate the mucus bubbles.

3.2.3. Setup and “Basal” Secretion

The dish is transferred to the physiological chamber and warmed to 37◦ C at a rate not exceeding 1.5◦ C/min because rapid warming stimulates transient gland secretion. Secreting glands are also sometimes observed at room temperature and some glands will start secreting even when the bath is warmed slowly. Most such glands eventually stop secreting or secrete at exceedingly slow rates. The process of cleaning, drying, and oiling the epithelium did not appear to stimulate or inhibit secretion, because similar secretion is observed in tissues or areas not so treated. We use the term “basal” secretion to refer to secretion observed in otherwise unstimulated tissues.

3.3. Optical Measurements 3.3.1. Lighting

The refractive index between the aqueous bubbles and the mineral oil differs only slightly, so that adequate visualization of the mucus droplets requires methods to exaggerate this difference. We use two approaches. In one, the preparation is obliquely illuminated using fiberoptic illuminators: we use Fiber-Lite models 190 (Edmond Optics) or Dolan-Jennings MI-150 (Labtek), but any comparable illuminator should work. The appearance of the secreted mucus droplets is strongly dependent on details of illumination which are adjusted empirically for each preparation. More recently, the availability of inexpensive, small, and powerful LEDs has made it possible to design ring illuminators that achieve more uniform lighting. These are presently in development and when perfected we will use them exclusively.

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3.3.2. Direct Camera Capture

For imaging of larger species (human, sheep, and pig) a digital camera can be used in macromode without the need for additional lenses. When using the Nikon Coolpix (995/4500), with a 3.2/4.0 megapixel sensor, we image an area approximately 1 cm2 , giving roughly 30,000 pixels/mm2 . With a 10 megapixel sensor (Canon Powershot G9) we obtain ~90,000 pixels/mm2 . The live digital image is sent to a video monitor for final adjustment of the lighting and focus. Digital images were captured at intervals of 1–5 min using available software, PSRemote (Breeze Systems Limited) for the Canon Powershot and Krinnicam (aristarco.dnsalias.org) for the Nikon. The sensors and other properties of off-the-shelf digital cameras are constantly improving, so that a de novo setup would presumably use a camera with features considerably better than those described. However, cameras vary widely in terms of their macromodes and their ability to be controlled by computer software and improved models are introduced frequently. Therefore no specific recommendations for newer cameras are made here.

3.3.3. Digital Microscopy

Finer resolution is achieved by mating a digital camera (Nikon, the zoom lens for this camera is internal; therefore, there are no moving external elements, making it ideal for mounting to a microscope) with a dissecting microscope (Wild Heerbrugg, Switzerland). In a typical experiment, the image projected on the CCD sensor is captured as a bitmap representing an area of ~6.25 mm2 . For a camera sensor of 3.2 megapixels, this field yields ~500,000 pixels/mm2 ; for 10 megapixels it yields 1.5 million. This resolution provides a more accurate estimate of secretion rates for single glands, with the disadvantage of a small field area, allowing fewer glands to be monitored and perhaps providing a non-representative sample of gland densities and rates.

3.3.4. Image Storage, Analysis, and Presentation

At least three copies of captured images are stored on internal or external hard disks, with at least one copy being in a separate room. Image analysis is carried out using ImageJ (NIH, MD) and the results tracked and graphed in Excel. The captured image is calibrated using a 0.5 mm grid that is placed on the surface of the tissue for each experiment. When the surface is properly prepared as described in Section 3.2, the volume of secreted bubbles is easily determined because they form spheres that do not contact the surface except for continuity of the mucus at the gland duct opening. The area from the perspective of the optical axis of the microscope of each droplet is then measured and converted to volume (V) using the formula for a sphere V = 4/3πr3 .

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A typical analysis would measure the volumes of mucus bubbles produced by each of 5–40 glands, usually at 5-min intervals but sometimes at 1-min intervals for the early phases of rapidly increasing and decreasing rate changes observed with certain agonists. The secretion rate is the change in bubble volume per unit time. We typically present the secretion rates per gland per condition and the cumulative volume secreted by each gland. The basic response data can then be treated as appropriate depending upon the distribution of the response rates (which is not necessarily a normal distribution). A powerful analytical tool made possible by the single gland data is to present the results of each intervention as the percent change in responding using each gland as its own control, rather than using averaged data. Gland by gland analysis is preferable when gland responses are not homogeneous. Examples of plots for cumulative secreted volume and secretion rates are shown in Fig. 6.3.

Fig. 6.3. Example of volume and rate plots. (a) Cumulative volume secreted by each of three human glands in response to 10 μM carbachol added at time 0 and continuously present thereafter. In this experiment three different raters scored the bubble volumes: each point shows the mean ± S.D. for three separate measures of bubble size. (b) Rate data for gland 2 shown above. Rates are plotted per minute for the 0- to 5-min period when gland secretion to carbachol displays a rapid transient and per 5 min for all other times. Data are from subject HN23, a 19-year-old female donor.

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3.3.5. Measurement Errors

3.3.5.1. Non-spherical Bubbles

Bubble images that are ovoid can usually be approximated by a circle. The error of the calculated radius is proportional to the square root of short axis/long axis. Because this ratio is always less than 1, the rate calculation may underestimate the actual secretion rate. We do not score bubbles in which the long axis is more than 1.25× the short axis; therefore the maximal underestimate in our volume calculations will be 10%. The basis for non-spherical bubbles is not understood in all cases but probably relates to surface irregularities (see below) or heterogeneity of the primary mucus. It can also occur when two bubbles merge (see Section 3.3.5.3.)

3.3.5.2. Contact Angles

In the ideal situation the mucus bubble is connected only to the gland duct orifice, which makes an increasingly small contribution as the mucus bubble diameter grows and allows the spherical approximation to accurately reflect the volume of the bubble; the pseudo-“contact angle” in this case is ~180◦ . However, if for any reason the bubble wets part of the surface, it develops a true contact angle that can drop below 180◦ , and to the extent this occurs the volume of the bubble will be overestimated. For example, the volume of a bubble with a contact angle of 135◦ is 7% smaller than that of a true sphere. Joo et al. measured contact angles of mucus bubbles directly using a prism to view bubbles from the side and concluded that volumes might be overestimated on average by ~10% (1). Fortunately, more extreme examples of wetting are easily discerned optically as the bubbles appear to be irregular in shape (puddles) and those bubbles are eliminated from analysis. The single biggest contributor to wetting is an improperly prepared surface, but surface secretion occurs in some circumstances and can also increase wetting (1). Examples of various degrees of wetting can be seen in Fig. 6.1b. If contact angles need to be measured, the prisms can be obtained from CVI Melles Griot and the measurements carried out with the ImageJ contact angle plugin, available at http:// rsbweb.nih.gov/ij/plugins/contact-angle.html.

3.3.5.3. Merging of Bubbles

With prolonged or very strong stimulation, the growing bubbles of mucus from adjacent gland duct orifices will eventually merge. How these events are treated can influence the analysis, because if such glands are simply omitted from the analysis it can introduce a bias against faster secreting glands. This gives an underestimate of both the upper range of secretion rates and the average secretion rate. However, the error is not straightforward because close proximity between duct orifices also predisposes to merging. The best procedure is to measure the combined volume and apportion

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it to each gland according to their relative volumes (and hence secretion rates) at the time of merging. However, such bubbles can be non-spherical (see Section 3.3.5.1.) 3.4. Experimental Manipulations

Experiments have the following general sequence: 1. Slow warming of the tissue to minimize temperatureinduced secretion. Imaging began at the end of this period of warming. 2. After warming, a period in which the tissue is left undisturbed for at least 20 min to determine a baseline level of secretion. If glands are secreting at the start of this period their rates often declined toward the end of the period. 3. Addition of first drug. Drug stocks were usually diluted to 1:1000 with Krebs buffer continuously gassed with 95% O2 /5% CO2 or 100% O2 and prewarmed to 37◦ C in a water bath just before adding. Some drugs (i.e., glibenclamide) require special attention during dilution to avoid potential precipitation. For these, we added small increments of the stock drug to the Krebs, followed by shaking until the desired concentration was reached. Drugs were added by complete bath replacement. 4. Monitoring of response to first treatment. Depending on the treatment, the image sampling rate might be increased (fastest usually 1/min) from the standard of 1/5 min. Drugs are usually left until a stable level of responding is reached. Accurate estimates of transient response rates (such as those produced by carbachol) require more frequent sampling. 5. Either Washout or Addition of Second Treatment

4. Notes 1. When cleaning the mucosal surface with cotton swabs, usually swabs are wetted with distilled water for a final cleansing prior to the drying process with the gas stream. This removes potential residual salts (from Krebs buffer) after drying the surface. 2. When applying the oil puddle at room temperature, be aware that the subsequent warming of the tissue to 37◦ C reduces the viscosity of the oil and will cause it to spread. Thus the original size of the oil puddle should be conservative and high viscosity heavy mineral oil should be used. 3. Inadequate cleaning and drying of the mucosal surface is a main cause of failure. If strands of mucus are not removed

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from gland orifices, the secreted mucus may follow these instead of forming spheres. If wet areas remain close to ducts, the emerging mucus may contact these and then spread over the surface resulting in greatly decreased contact angles (see above). In this case it would be useful to restart the whole process after removing the oil from the surface. 4. Even though the physiological chamber constantly superfuses the preparation with humidified gas, for maximal control of humidity and gas composition the optical chamber can be covered with a glass slide to minimize evaporation and mixing with room air. This is especially important if the bath volume needs to be very small. To minimize fogging the cover is coated with Rain-X (Sopus products, Texas). 5. Bath replacement with gas-saturated, 37◦ C Krebs buffer at intervals of ≤15 min is highly recommended to maintain consistent bath conditions.

Acknowledgments We are grateful to the transplant patients and their families whose cooperation provided the tissues needed for studies of human gland secretion. For help in obtaining informed consent from patients we thank D. Weill, N.R. Henig, J. Theodore, T.E. Robinson, M. Wine, and K. Tran. For access to surgical tissues we thank B.A. Reitz, G.J. Berry, R.C. Robbins, R.I. Whyte, and the staff of the Stanford Transplant team. Jennifer Lyons provided useful discussions and comments. Technical help and data analysis were provided by Tracy Hsu, Christina Tseng, Molly Pam, Wei Chen, Sidney Chang, Kim Tran, and Jonathan Chen. The work was supported by NIH Grant DK-51817, the Cystic Fibrosis Foundation, and CFRI. References 1. Joo, N. S., Wu, J. V., Krouse, M. E., Saenz, Y., and Wine, J. J. (2001) Optical method for quantifying rates of mucus secretion from single submucosal glands. Am J Physiol Lung Cell Mol Physiol 281, L458–L468. 2. Quinton, P. M. (1979) Composition and control of secretions from tracheal bronchial submucosal glands. Nature 279, 551–552. 3. Kreda, S. M., Mall, M., Mengos, A., Rochelle, L., Yankaskas, J., Riordan, J. R., et al. (2005) Characterization of wild-type

and deltaF508 cystic fibrosis transmembrane regulator in human respiratory epithelia. Mol Biol Cell 16, 2154–2167. 4. Engelhardt, J. F., Yankaskas, J. R., Ernst, S. A., Yang, Y., Marino, C. R., Boucher, R. C., et al. (1992) Submucosal glands are the predominant site of CFTR expression in the human bronchus. Nat Genet 2, 240–248. 5. Di, A., Brown, M. E., Deriy, L. V., Li, C., Szeto, F. L., Chen, Y., et al. (2006) CFTR regulates phagosome acidification in

110

6.

7.

8.

9.

10.

11.

12.

13.

14.

15.

16.

17.

Wine et al. macrophages and alters bactericidal activity. Nat Cell Biol 8, 933–944. Knowles, M. R., and Boucher, R. C. (2002) Mucus clearance as a primary innate defense mechanism for mammalian airways. J Clin Invest 109, 571–577. Bennett, W. D., Olivier, K. N., Zeman, K. L., Hohneker, K. W., Boucher, R. C., and Knowles, M. R. (1996) Effect of uridine 5 -triphosphate plus amiloride on mucociliary clearance in adult cystic fibrosis. Am J Respir Crit Care Med 153, 1796–1801. Rosenfeld, M., Emerson, J., Accurso, F., Armstrong, D., Castile, R., Grimwood, K., et al. (1999) Diagnostic accuracy of oropharyngeal cultures in infants and young children with cystic fibrosis. Pediatr Pulmonol 28, 321–328. Roby, B. B., McNamara, J., Finkelstein, M., and Sidman, J. (2008) Sinus surgery in cystic fibrosis patients: comparison of sinus and lower airway cultures. Int J Pediatr Otorhinolaryngol 72, 1365–1369. Reid, L. (1960) Measurement of the bronchial mucous gland layer: a diagnostic yardstick in chronic bronchitis. Thorax 15, 132–141. Haws, C., Finkbeiner, W. E., Widdicombe, J. H., and Wine, J. J. (1994) CFTR in Calu3 human airway cells: channel properties and role in cAMP-activated Cl- conductance. Am J Physiol 266, L502–L512. Inglis, S. K., Corboz, M. R., Taylor, A. E., and Ballard, S. T. (1996) Regulation of ion transport across porcine distal bronchi. Am J Physiol 270, L289–L297. Inglis, S. K., Corboz, M. R., Taylor, A. E., and Ballard, S. T. (1997) Effect of anion transport inhibition on mucus secretion by airway submucosal glands. Am J Physiol 272, L372–L377. Inglis, S. K., Corboz, M. R., and Ballard, S. T. (1998) Effect of anion secretion inhibitors on mucin content of airway submucosal gland ducts. Am J Physiol 274, L762–L766. Trout, L., Gatzy, J. T., and Ballard, S. T. (1998) Acetylcholine-induced liquid secretion by bronchial epithelium: role of Cl- and HCO3- transport. Am J Physiol 275, L1095– L1099. Trout, L., King, M., Feng, W., Inglis, S. K., and Ballard, S. T. (1998) Inhibition of airway liquid secretion and its effect on the physical properties of airway mucus. Am J Physiol 274, L258–L263. Ballard, S. T., Trout, L., Bebok, Z., Sorscher, E. J., and Crews, A. (1999) CFTR involvement in chloride, bicarbonate, and liquid

18.

19.

20.

21.

22.

23.

24.

25. 26.

27.

28.

29.

secretion by airway submucosal glands. Am J Physiol 277, L694–L699. Trout, L., Corboz, M. R., and Ballard, S. T. (2001) Mechanism of substance P-induced liquid secretion across bronchial epithelium. Am J Physiol Lung Cell Mol Physiol 281, L639–L645. Trout, L., Townsley, M. I., Bowden, A. L., and Ballard, S. T. (2003) Disruptive effects of anion secretion inhibitors on airway mucus morphology in isolated perfused pig lung. J Physiol 549, 845–853. Ballard, S. T., Trout, L., Garrison, J., and Inglis, S. K. (2006) Ionic mechanism of forskolin-induced liquid secretion by porcine bronchi. Am J Physiol Lung Cell Mol Physiol 290, L97–L104. Joo, N. S., Saenz, Y., Krouse, M. E., and Wine, J. J. (2002) Mucus secretion from single submucosal glands of pig. Stimulation by carbachol and vasoactive intestinal peptide. J Biol Chem 277, 28167–28175. Ianowski, J. P., Choi, J. Y., Wine, J. J., and Hanrahan, J. W. (2007) Mucus secretion by single tracheal submucosal glands from normal and cystic fibrosis transmembrane conductance regulator CFTR knock-out mice. J Physiol 580, 301–314. Joo, N. S., Irokawa, T., Wu, J. V., Robbins, R. C., Whyte, R. I., and Wine, J. J. (2002) Absent secretion to vasoactive intestinal peptide in cystic fibrosis airway glands. J Biol Chem 277, 50710–50715. Joo, N. S., Irokawa, T., Robbins, R. C., and Wine, J. J. (2006) Hyposecretion, not hyperabsorption, is the basic defect of cystic fibrosis airway glands. J Biol Chem 281, 7392–7398. Klockars, M., and Reitamo, S. (1975) Tissue distribution of lysozyme in man. J Histochem Cytochem 23, 932–940. Goetz, D. H., Holmes, M. A., Borregaard, N., Bluhm, M. E., Raymond, K. N., and Strong, R. K. (2002) The neutrophil lipocalin NGAL is a bacteriostatic agent that interferes with siderophore-mediated iron acquisition. Mol Cell 10, 1033–1043. Sagel, S. D., Sontag, M. K., and Accurso, F. J. (2009) Relationship between antimicrobial proteins and airway inflammation and infection in cystic fibrosis. Pediatr Pulmonol 44, 402–409. Casado, B., Pannell, L. K., Iadarola, P., and Baraniuk, J. N. (2005) Identification of human nasal mucous proteins using proteomics. Proteomics 5, 2949–2959. Garcia-Caballero, A., Rasmussen, J. E., Gaillard, E., Watson, M. J., Olsen, J. C., Donaldson, S. H., et al. (2009) SPLUNC1 regulates airway surface liquid volume by protecting

Measurement of Fluid Secretion from Intact Airway Submucosal Glands

30.

31.

32.

33.

34.

35. 36. 37.

38.

39.

40.

41.

ENaC from proteolytic cleavage. Proc Natl Acad Sci USA 106, 11412–11417. Peden, D. B., Hohman, R., Brown, M. E., Mason, R. T., Berkebile, C., Fales, H. M., et al. (1990) Uric acid is a major antioxidant in human nasal airway secretions. Proc Natl Acad Sci USA 87, 7638–7642. Peden, D. B., Brown, M. E., Wade, Y., Raphael, G. D., Berkebile, C., and Kaliner, M. A. (1991) Human nasal glandular secretion of novel antioxidant activity: cholinergic control. Am Rev Respir Dis (Now the Am J Respir Crit Care Med) 143, 545–552. Conner, G. E., Wijkstrom-Frei, C., Randell, S. H., Fernandez, V. E., and Salathe, M. (2007) The lactoperoxidase system links anion transport to host defense in cystic fibrosis. FEBS Lett 581, 271–278. Moskwa, P., Lorentzen, D., Excoffon, K. J., Zabner, J., McCray, P. B., Jr., et al (2006) A novel host defense system of airways is defective in cystic fibrosis. Am J Respir Crit Care Med 175, 174–183. Kesimer, M., Makhov, A. M., Griffith, J. D., Verdugo, P., and Sheehan, J. K. (2010) Unpacking a gel forming mucin: a view of MUC5B organization after granular release. Am J Physiol Lung Cell Mol Physiol 298, L15– L22. Wine, J. J., and Joo, N. S. (2004) Submucosal glands and airway defense. Proc Am Thorac Soc 1, 47–53. Quinton, P. M. (2008) Cystic fibrosis: impaired bicarbonate secretion and mucoviscidosis. Lancet 372, 415–417. Matsui, H., Wagner, V. E., Hill, D. B., Schwab, U. E., Rogers, T. D., Button, B., et al. (2006) A physical linkage between cystic fibrosis airway surface dehydration and Pseudomonas aeruginosa biofilms. Proc Natl Acad Sci USA 103, 18131–18136. Song, Y., Salinas, D., Nielson, D. W., and Verkman, A. S. (2006) Hyperacidity of secreted fluid from submucosal glands in early cystic fibrosis. Am J Physiol Cell Physiol 290, C741–C749. Irokawa, T., Krouse, M. E., Joo, N. S., Wu, J. V., and Wine, J. J. (2004) A “virtual gland” method for quantifying epithelial fluid secretion. Am J Physiol Lung Cell Mol Physiol 287, L784–L793. Joo, N. S., Krouse, M. E., Wu, J. V., Saenz, Y., Jayaraman, S., Verkman, A. S., et al. (2001) HCO(3)(-) Transport in relation to mucus secretion from submucosal glands. JOP 2, 280–284. Ballard, S. T., Parker, J. C., and Hamm, C. R. (2006) Restoration of mucociliary transport in the fluid-depleted trachea by surface-

42.

43. 44.

45.

46.

47.

48.

49.

50.

51.

52.

53.

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active instillates. Am J Respir Cell Mol Biol 34, 500–504. Lindert, J., Perlman, C. E., Parthasarathi, K., and Bhattacharya, J. (2007) Chloridedependent secretion of alveolar wall liquid determined by optical-sectioning microscopy. Am J Respir Cell Mol Biol 36, 688–696. Meyrick, B., and Reid, L. (1970) Ultrastructure of cells in the human bronchial submucosal glands. J Anat 107, 281–299. Jacquot, J., Puchelle, E., Hinnrasky, J., Fuchey, C., Bettinger, C., Spilmont, C., et al. (1993) Localization of the cystic fibrosis transmembrane conductance regulator in airway secretory glands. Eur Respir J 6, 169–176. Finkbeiner, W. E., Shen, B. Q., and Widdicombe, J. H. (1994) Chloride secretion and function of serous and mucous cells of human airway glands. Am J Physiol 267, L206–L210. Choi, H. K., Finkbeiner, W. E., and Widdicombe, J. H. (2000) A comparative study of mammalian tracheal mucous glands. J Anat 197, 361–372. Widdicombe, J. H., Chen, L. L., Sporer, H., Choi, H. K., Pecson, I. S., and Bastacky, S. J. (2001) Distribution of tracheal and laryngeal mucous glands in some rodents and the rabbit. J Anat 198, 207–221. Peatfield, A. C., Barnes, P. J., Bratcher, C., Nadel, J. A., and Davis, B. (1983) Vasoactive intestinal peptide stimulates tracheal submucosal gland secretion in ferret. Am Rev Respir Dis (Now Am J Respir Crit Care Med) 128, 89–93. Nadel, J. A., and Davis, B. (1980) Parasympathetic and sympathetic regulation of secretion from submucosal glands in airways. Fed Proc 39, 3075–3079. Nadel, J. A., and Davis, B. (1978) Regulation of Na+ and Cl- transport and mucous gland secretion in airway epithelium. Ciba Found Symp 54, 133–147. Phillips, J. E., Hey, J. A., and Corboz, M. R. (2002) Computer assisted measurement of airway gland secretions by the hillocks technique. Comput Methods Prog Biomed 68, 215–222. Ueki, I., German, V. F., and Nadel, J. A. (1980) Micropipette measurement of airway submucosal gland secretion. Autonomic effects. Am Rev Respir Dis (Now Am J Respir Crit Care Med) 121, 351–357. German, V. F., Ueki, I. F., and Nadel, J. A. (1980) Micropipette measurement of airway submucosal gland secretion: laryngeal reflex.

112

54.

55.

56.

57.

58.

59.

60.

61.

62.

63.

64.

Wine et al. Am Rev Respir Dis (Now Am J Respir Crit Care Med) 122, 413–416. German, V. F., Corrales, R., Ueki, I. F., and Nadel, J. A. (1982) Reflex stimulation of tracheal mucus gland secretion by gastric irritation in cats. J Appl Physiol 52, 1153–1155. Leikauf, G. D., Ueki, I. F., and Nadel, J. A. (1984) Autonomic regulation of viscoelasticity of cat tracheal gland secretions. J Appl Physiol 56, 426–430. Inglis, S. K., Corboz, M. R., Taylor, A. E., and Ballard, S. T. (1997) In situ visualization of bronchial submucosal glands and their secretory response to acetylcholine. Am J Physiol 272, L203–L210. Sasaki, H., Sasaki, T., Shimura, S., and Takishima, T. (1986) Effect of fenoterol on secretions of an isolated single submucosal gland from the trachea. Respiration 50 Suppl 2, 266–269. Shimura, S., Sasaki, T., Sasaki, H., and Takishima, T. (1986) Contractility of isolated single submucosal gland from trachea. J Appl Physiol 60, 1237–1247. Shimura, S., Sasaki, T., Okayama, H., Sasaki, H., and Takishima, T. (1987) Effect of substance P on mucus secretion of isolated submucosal gland from feline trachea. J Appl Physiol 63, 646–653. Shimura, S., Sasaki, T., Okayama, H., Sasaki, H., and Takishima, T. (1987) Neural control of contraction in isolated submucosal gland from feline trachea. J Appl Physiol 62, 2404– 2409. Shimura, S., Sasaki, T., Ikeda, K., Sasaki, H., and Takishima, T. (1988) VIP augments cholinergic-induced glycoconjugate secretion in tracheal submucosal glands. J Appl Physiol 65, 2537–2544. Sasaki, T., Shimura, S., Ikeda, K., Sasaki, H., and Takishima, T. (1989) Platelet-activating factor increases platelet-dependent glycoconjugate secretion from tracheal submucosal gland. Am J Physiol 257, L373–L378. Sasaki, T., Shimura, S., Sasaki, H., and Takishima, T. (1989) Effect of epithelium on mucus secretion from feline tracheal submucosal glands. J Appl Physiol 66, 764–770. Ishihara, H., Shimura, S., Sato, M., Masuda, T., Ishide, N., Miura, M., et al. (1990) Intracellular calcium concentration of acinar cells in feline tracheal submucosal glands. Am J Physiol 259, L345–L350.

65. Sasaki, T., Shimura, S., Ikeda, K., Sasaki, H., and Takishima, T. (1990) Sodium efflux from isolated submucosal gland in feline trachea. Am J Physiol 258, L112–L117. 66. Shimura, S., Sasaki, T., Ikeda, K., Yamauchi, K., Sasaki, H., and Takishima, T. (1990) Direct inhibitory action of glucocorticoid on glycoconjugate secretion from airway submucosal glands. Am Rev Respir Dis (Now Am J Respir Crit Care Med) 141, 1044– 1049. 67. Shimura, S., Sasaki, T., Ikeda, K., Ishihara, H., Sato, M., Sasaki, H., et al. (1991) Neuropeptides and airway submucosal gland secretion. Am Rev Respir Dis (Now Am J Respir Crit Care Med) 143, S25–S27. 68. Ishihara, H., Shimura, S., Satoh, M., Masuda, T., Nonaka, H., Kase, H., et al. (1992) Muscarinic receptor subtypes in feline tracheal submucosal gland secretion. Am J Physiol 262, L223–L228. 69. Shimura, S., Sasaki, T., Ishihara, H., Sato, M., Sasaki, H., and Takishima, T. (1992) Autonomic innervation to feline tracheal submucosal glands for mucus glycoprotein secretion. Am J Physiol 262, L15–L20. 70. Shimura, S. (2000) Signal transduction of mucous secretion by bronchial gland cells. Cell Signal 12, 271–277. 71. Jayaraman, S., Joo, N. S., Reitz, B., Wine, J. J., and Verkman, A. S. (2001) Submucosal gland secretions in airways from cystic fibrosis patients have normal [Na+] and pH but elevated viscosity. Proc Natl Acad Sci USA 98, 8119–8123. 72. Wu, D. X., Lee, C. Y., Uyekubo, S. N., Choi, H. K., Bastacky, S. J., and Widdicombe, J. H. (1998) Regulation of the depth of surface liquid in bovine trachea. Am J Physiol 274, L388–L395. 73. Widdicombe, J. H., Bastacky, S. J., Wu, D. X., and Lee, C. Y. (1997) Regulation of depth and composition of airway surface liquid. Eur Respir J 10, 2892–2897. 74. Haxhiu, M. A., Kc, P., Moore, C. T., Acquah, S. S., Wilson, C. G., Zaidi, S. I., et al. (2005) Brain stem excitatory and inhibitory signaling pathways regulating bronchoconstrictive responses. J Appl Physiol 98, 1961–1982. 75. Wine, J. J. (2007) Parasympathetic control of airway submucosal glands: central reflexes and the airway intrinsic nervous system. Auton Neurosci 133, 35–54.

Chapter 7 Measurements of Intracellular Calcium Signals in Polarized Primary Cultures of Normal and Cystic Fibrosis Human Airway Epithelia Carla M.P. Ribeiro Abstract The airways are continuously challenged by a variety of stimuli including bacteria, viruses, allergens, and inflammatory factors that act as agonists for G protein-coupled receptors (GPCR). Intracellular calcium (Ca2+ i ) mobilization in airway epithelia in response to extracellular stimuli regulates key airway innate defense functions, e.g., Ca2+ -activated Cl− secretion, ciliary beating, mucin secretion, and inflammatory responses. Because Ca2+ i mobilization in response to luminal stimuli is larger in CF vs. normal human airway epithelia, alterations in Ca2+ i signals have been associated with the pathogenesis of CF airway disease. Hence, assessment of Ca2+ i signaling has become an important area of CF research. This chapter will focus on measurements of cytoplasmic and mitochondrial Ca2+ signals resulting from GPCR activation in polarized primary cultures of normal and CF human bronchial epithelia (HBE). Key words: Cystic fibrosis, airway epithelia, inflammation, oxidative stress, G protein-coupled receptors, intracellular calcium, endoplasmic reticulum, mitochondria, unfolded protein response, X-box binding protein-1.

1. Introduction Chronic airway infection and inflammation are hallmarks of cystic fibrosis (CF) airway disease. The infectious and inflammatory CF airway environment impacts on the innate defense responses of the epithelia lining the airways. In accord with this notion, we have shown that the endoplasmic reticulum (ER) and its Ca2+ stores are expanded in native CF human airway epithelia (1, 2). The ER expansion can be recapitulated in normal human M.D. Amaral, K. Kunzelmann (eds.), Cystic Fibrosis, Methods in Molecular Biology 742, DOI 10.1007/978-1-61779-120-8_7, © Springer Science+Business Media, LLC 2011

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bronchial epithelia (HBE) by exposing the cells to supernatant from mucopurulent material (SMM) from human CF airways (1, 2). These studies illustrated that the ER Ca2+ stores expand when the demand to upregulate the innate response is imposed upon the secretory pathway. The upregulation of the ER Ca2+ stores is functionally relevant, because it provides a mechanism for amplification of intracellular Ca2+ (Ca2+ i )-dependent secretion of inflammatory mediators in inflamed CF HBE (2). Recently, we have addressed the mechanism responsible for the ER Ca2+ storage expansion in inflamed airway epithelia. Our findings suggested a model whereby airway epithelial inflammation triggers the unfolded protein response (UPR) due to ER stress resulting from an increased demand for newly synthesized, unfolded inflammatory mediators and epithelial repair proteins (3). This UPR is characterized, in part, by activation of inositol requiring enzyme 1 (IRE1)-mediated X-box binding protein-1 (XBP-1) mRNA splicing, which is directly responsible for the ER Ca2+ store expansion and upregulation of the protein secretory pathway (3). These alterations provide a mechanism for the ERderived Ca2+ -mediated hyperinflammation that occurs in polarized primary cultures of inflamed CF HBE and SMM-exposed HBE (2). Epithelial polarization is a central issue in studies addressing regulation of Ca2+ i signals in normal and CF airway epithelia. Polarized airway epithelial cells express specific Ca2+ i -dependent functions, e.g., Ca2+ i -regulated ion channels, confined to the apical or the basolateral domains (4, 5). Although apical or basolateral purinoceptor (P2Y2 receptor) activation induces Ca2+ i mobilization, Ca2+ i -mediated channel regulation at the apical or the basolateral membrane can only be elicited by ipsilateral receptor activation (4–7). Thus, GPCR activation can be used as a tool to study mechanisms by which Ca2+ i -dependent responses are compartmentalized within airway epithelia. The importance of epithelial polarization for Ca2+ i -mediated function has been further underscored by studies showing that mitochondria polarize toward the apical domain, are in close proximity to ER Ca2+ stores, and buffer ER-derived Ca2+ i signals triggered by apical P2Y2 receptor activation in HBE (5). CF airways also exhibit oxidative stress (8, 9), and the increased Ca2+ i signals in inflamed CF airway epithelia may be a contributing factor to the oxidative status of CF airways. Because mitochondrial respiration is a major source of intracellular reactive oxygen species (ROS) production, and mitochondrial Ca2+ uptake stimulates mitochondrial respiration-dependent ROS generation (10–15), we hypothesized that a direct correlation between the magnitude of Ca2+ i signals and the mitochondrial production of ROS exists in HBE. In fact, our preliminary findings suggest that rises in Ca2+ i induce ROS production,

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and inflammatory stimuli that elicit expansion of ER Ca2+ stores potentiate ROS production resulting from Ca2+ i mobilization in primary cultures of polarized HBE (16). Because these studies have underscored the role of Ca2+ i mobilization in airway epithelial responses relevant to CF pathophysiology, assessment of Ca2+ i signaling has become an important area of CF research. This chapter focuses on measurements of cytoplasmic and mitochondrial Ca2+ signals resulting from GPCR activation in polarized primary cultures of normal and CF HBE.

2. Materials 2.1. HBE Cultures

See Chapter 40 for a detailed description of these materials. (1) Transwell T-Clears (2) Collagen (3) Airway liquid interface (ALI) culture medium (4) Phosphate-buffered saline (PBS; 120 mM NaCl, 2.6 mM KCl, 8.1 mM Na2 HPO4 , 1.5 mM KH2 PO4 , pH 7.4)

2.2. Measurements of GPCR-Dependent Ca2+ i Signals

(1) Fura-2 (fura-2, AM “cell permeant”; Invitrogen, Carlsbad, CA, USA) is dissolved at 2.5 mM in dimethyl sulfoxide (DMSO), stored in aliquots at –20◦ C, and then added to the mucosal and serosal compartments of polarized cultures of HBE at a final concentration of 2.5 μM. (2) Fluo-4 (fluo-4, AM “cell permeant”; Invitrogen, Carlsbad, CA, USA) is dissolved at 2.5 mM in DMSO, stored in aliquots at –20◦ C, and then added to the mucosal and serosal compartments of polarized cultures of HBE at a final concentration of 2.5 μM. (3) Rhod-2 (rhod-2, AM “cell permeant”; Invitrogen, Carlsbad, CA, USA) is dissolved at 5 mM in DMSO, stored in aliquots at –20◦ C, and then added to the mucosal and serosal compartments of polarized cultures of HBE at a final concentration of 5 μM as required. (4) BAPTA (BAPTA, AM “cell permeant”; Invitrogen, Carlsbad, CA, USA) is dissolved at 100 mM in DMSO, stored in aliquots at –20◦ C, and then added to the mucosal and serosal compartments of polarized cultures of HBE at a final concentration of 100 μM. (5) Ham’s F-12 medium (modified with L-glutamine; Mediatech, Inc., Manassa, VA, USA).

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(6) HEPES-buffered saline solution (HBSS; 130 mM NaCl, 5 mM KCl, 1.3 mM MgCl2 .6H2 O, 1.3 mM CaCl2 , 10 mM HEPES (salt free), pH 7.4, and 5 mM glucose). (7) ATP/UTP (Amersham Pharmacia Biotech, Piscataway, NJ, USA) is dissolved at 100 mM in purified water, stored in aliquots at –20◦ C, and then added to the mucosal compartment of polarized cultures of HBE at a final concentration of 100 μM. (8) Bradykinin (bradykinin acetate salt, Sigma-Aldrich, St. Louis, MO, USA) is dissolved at 5 mM in purified water, stored in aliquots at –20◦ C, and then added to the mucosal compartment of polarized cultures of HBE at a final concentration of 5 μM. (9) Ionomycin (Invitrogen, Carlsbad, CA, USA) is dissolved at 5 mM in DMSO, stored in aliquots at –20◦ C, and then added to the mucosal compartment of polarized cultures of HBE at a final concentration of 5 μM. (10) Digitonin (Sigma-Aldrich, St. Louis, MO, USA) is used at a final concentration of 50 μM for background subtraction in fura-2 studies as described in detail in Section 3.

3. Methods 3.1. HBE Cultures

See Chapter 40 for a detailed description of how to culture primary human bronchial airway epithelia. Cells are obtained under the auspices of protocols approved by the Institutional Committee on the Protection of the Rights of Human Subjects. Excess tissues from human donor lungs and excised CF recipient lungs are obtained at the time of lung transplantation from main stem or lobar bronchi. Bronchial epithelial cells are provided by the UNC CF Center Tissue Core. Normal and CF (F508del homozygous or other CF mutation) cells are harvested and cultured in 12 mm Transwell Permeable Supports (Corning Incorporated – Life Sciences, Kennebunk, ME, USA), as previously described (6). Cultures are maintained at an air– liquid surface interface and polarized primary cultures are studied at 6–11 days (short-term monolayers) or 30–40 days later (long term, well differentiated). Normal and CF cultures are apically washed with sterile PBS and the serosal media replenished every 2–4 days.

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3.2. Measurements of Ca2+ i Signals Using Fura-2 or Fluo-4 as Reporters 3.2.1. HBE Loading with Fura-2 and Assessment of GPCR Activation-Induced Ca2+ i Mobilization in Fura-2-Loaded HBE 3.2.1.1. Fura-2 Loading

Fura-2 is a ratiometric and sensitive indicator dye for measuring Ca2+ i . Ratiometric measurements of Ca2+ i signals significantly reduce the effects of differences in dye loading, leakage, and photobleaching and minimize problems with Ca2+ measurements in cells of uneven thickness, such as primary cultures of airway epithelia. Polarized 6–11- or 30–40-day-old cultures of human bronchial epithelia are loaded with 2.5 μM fura-2/AM (final concentration) by exposing their mucosal and serosal compartments to 0.5 and 1 ml, respectively, of Ham’s F-12 medium containing fura-2 and incubating them at 37◦ C for 30 min in 5% CO2 /95% O2 as previously described (1, 2). Cultures are subsequently washed with HBSS and kept in HBSS (only at the serosal compartment) for ∼20–30 min to allow for de-esterification of fura-2 by endogenous esterases. Although in some cells optimal loading of fura-2 requires the use of the nonionic detergent Pluronic F-127 to increase dye solubility in physiological media, this step is not needed for fura-2 loading of primary cultures of human airway epithelia. Likewise, although the use of anion exchange inhibitors such as probenecid during dye loading and throughout an experiment is necessary for dye retention in certain cells, this procedure is not required in primary cultures of human airway epithelia.

3.2.2. Measurements of Ca2+ i

In our laboratory, two approaches have been used to evaluate Ca2+ i signals elicited by GPCR activation in primary cultures of polarized airway epithelia. Cultures loaded with fura-2 can be mounted in a miniature Ussing chamber, which can be bilaterally perfused to assess the mucosal and serosal effects of Ca2+ mobilizing agonists on airway epithelia, as previously described (5, 6). A simpler, alternative approach, which is indicated for evaluating the effect of mucosal agonists, is to mount the polarized cultures on a cover slip in a chamber that fits the stage of the microscope used. Fifty microliters of HBSS is added to the cover slip to keep the membrane-containing culture moistened. In this latter condition, 100 μl HBSS is added to the mucosal

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compartment. The chamber is positioned over an objective (e.g., Zeiss LD Achroplan 40X, NA 0.6; working distance 1.8 mm; or an equivalent objective) of an inverted microscope coupled to a PTI FeliX system containing the FeliX32TM platform (Photon Technology International, Lawrenceville, NJ) as previously described (1, 2, 5, 6). The system is equipped with a xenon lamp, beam splitter, two monochromators, and a rotating chopper mirror that permits excitation of fura-2 fluorescence at alternating wavelengths of 340–380 nm. The emitted light from cells (monitored at 510 nm) hits a photomultiplier, and the output emission intensities, collected over a 3-s time period at a given excitation wavelength, are averaged. The use of a long working distance objective allows focusing on the apical domain of the epithelia in studies addressing apically derived Ca2+ i signals. This is an important aspect, since Ca2+ i signals and Ca2+ i -mediated functions are compartmentalized at the membrane domain ipsilateral to GPCR activation in polarized airway epithelia (5). For measurements of Ca2+ i signals derived from the basolateral domain, a focal plane close to the membrane support should be chosen. We routinely measure changes in fura-2 fluorescence from a field of 30–50 cells. At the end of the experiment, background light levels at 340–380 nm originating from cells, optics of the microscope, and/or incomplete de-esterified fura-2 are measured by exposing the cultures to 50 μM digitonin (to permeabilize the cells) and 1 mM MnCl2 (to quench the fura-2 fluorescence). At the same instrument settings and spot studied, background values obtained in this manner should be in good agreement with the values from unloaded cells. Utilizing the FeliX32TM software (or equivalent), the background signals are subtracted from the corresponding signals measured from the fura-2-loaded cultures before taking the background light levels at 340–380 nm. In comparison to background, the minimum photon count rates of fura-2-loaded cells should be sufficiently high to exceed the background signals by four- to eightfold when cells are excited at 340–380 nm. If desired, the corrected ratio can be converted to [Ca2+ i ] using the formula derived from Grynkiewicz and colleagues (17) for dual-wavelength measurements: 

Ca2 +

 i

= Kd [(R − Rmin )/(Rmax − R)] (F380 max /F380 min )

where Rmin and Rmax are the ratios at 0 Ca2+ (e.g., in the presence of 2 mM EGTA) and saturating Ca2+ (addition of the ionophore ionomycin in the presence of 5 mM Ca2+ ), respectively; R is the experimental ratio (F340 /F380 ); Kd (145 nM at 22◦ C; 224 nM at 37◦ C) is the effective dissociation constant for fura-2; and F380max and F380 min are the fluorescence intensities at

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380 nm without and with Ca2+ , respectively. For a detailed description of basic practical considerations regarding measurements of Ca2+ i with fura-2 and other Ca2+ i -sensitive dyes, please see (18). Using polarized primary cultures, we have not observed any systematic differences between CF and normal airway epithelia as a result of differential fura-2 behavior, including dye loading. We have consistently observed similar baseline Ca2+ i levels in CF and normal airway epithelia (1, 2, 5, 6). 3.2.3. Assessment of GPCR ActivationInduced Ca2+ i Mobilization in Fura-2-Loaded HBE

Airway epithelia are constantly challenged by extracellular stimuli, many of which are ligands for seven transmembrane GPCRs. For example, activation of purinergic (P2Y2 ) receptors by ATP or UTP, or activation of bradykinin (BK) receptors, promotes stimulation of phospholipase C (PLC), resulting in the breakdown of plasma membrane phosphatidylinositol 4,5-bisphosphate and generation of inositol 1,4,5-trisphosphate (IP3 ). IP3 activates channel receptors in the ER Ca2+ stores, triggering channel opening and release of Ca2+ into the cytoplasm (19). Depletion of IP3 sensitive ER Ca2+ stores activates a Ca2+ influx pathway across the apical or the basolateral airway epithelial membrane that was originally termed “capacitative Ca2+ entry” (20, 21) and, later, “storeoperated Ca2+ entry” (22). The two phases of Ca2+ i mobilization resulting from release of Ca2+ from ER stores and Ca2+ entry can act in a concerted manner to regulate signal transduction events involved in airway epithelial inflammation (23). However, the quantity of releasable Ca2+ sequestered in ER stores plays a pivotal role, independently of capacitative Ca2+ entry, in inflammatory responses of CF airway epithelia (2, 3, 23). Although this chapter focuses on P2Y2 or BK receptor activation-induced Ca2+ i mobilization, airway epithelia also express another subclass of nucleotide receptors, the P2X receptor channels, which function as extracellular ATP-gated, Ca2+ -permeable non-selective cation channels (24). The following protocols are used in our laboratory to evaluate Ca2+ i mobilization triggered by GPCR agonists: (1) Measurement of GPCR activation-induced ER Ca2+ release and capacitative Ca2+ entry. Cultures are loaded with fura2/AM and mounted on the microscope stage as described earlier. To assess the effect of GPCR agonists on the first phase of Ca2+ i mobilization, e.g., ER Ca2+ release, baseline Ca2+ i tracings are obtained under “nominally Ca2+ free conditions” (e.g., HBSS without addition of CaCl2 ), followed by addition of 100 μM UTP or ATP, or 5 μM bradykinin, in the presence of nominally Ca2+ -free HBSS. To assess the effect of agonists on the second phase of Ca2+ i mobilization (capacitative Ca2+ entry), the agonist is subsequently added in HBSS containing 1.3 mM CaCl2 (Fig. 7.1a).

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Fig. 7.1. Evaluation of GPCR activation-triggered Ca2+ i signals in polarized cultures of HBE loaded with fura-2. (a) Representative tracing from 100 μM mucosal UTP-induced Ca2+ i mobilization. First and second phases of Ca2+ mobilization in the absence or presence of 1.3 mM extracellular Ca2+ illustrate UTP-induced release of Ca2+ from ER stores and capacitative calcium entry, respectively. (b) Representative Ca2+ i tracings depicting the effect of 5 μM mucosal bradykinin (BK)-mobilized Ca2+ i in primary cultures of HBE in the absence (top) and presence (bottom) of Ca2+ i buffering with BAPTA.

(2) Buffering Ca2+ i signals with BAPTA. In studies requiring chelation of Ca2+ i signals elicited by GPCR agonists, or agents that promote Ca2+ i mobilization independently of GPCR activation by inhibiting the ER Ca2+ -ATPase such as thapsigargin (1, 2), cultures are also loaded with 100 μM BAPTA/AM in Ham’s F-12 medium at 37◦ C for 30 min in 5% CO2 /95% O2 . Culture media containing concentrations of CaCl2 in the millimolar range should be avoided, since the Ca2+ buffering capacity of BAPTA will be decreased in media with higher Ca2+ levels. To confirm that Ca2+ i signals elicited by activation of GPCR have been buffered by BAPTA, cultures are simultaneously loaded with fura-2/AM and agonist-induced Ca2+ i mobilization is evaluated as shown in Fig. 7.1b. 3.2.4. HBE Loading with Fluo-4 and Confocal Microscopic Assessment of GPCR Activation-Induced Ca2+ i Mobilization in Fluo-4-Loaded HBE

Polarized HBE cultures are loaded on the mucosal and serosal surfaces with fluo-4 AM (5 μM) in Ham’s F-12 medium for 30 min at 37◦ C. Cultures are subsequently washed with HBSS and kept in HBSS (only at the serosal compartment). Cultures are then mounted on a glass cover slip over an objective coupled to a confocal microscope. Changes in fluo-4 fluorescence intensity

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(reflecting Ca2+ i mobilization) are measured at an excitation of 494 nm and emission of 516 nm, as previously reported (25). Unlike fura-2, which is a dual excitation wavelength ratiometric dye, fluo-4 is a single excitation, non-ratiometric dye. Images are captured by XY or XZ scans and changes in fluorescence intensity are determined with MetaMorph Imaging Systems (Universal Imaging Corporation, Downingtown, PA) or equivalent imaging software. Regions of interest are designated and the same region is quantified at each time point during a time course for, e.g., UTP-induced Ca2+ i mobilization. The same acquisition parameters (e.g., laser power, contrast, brightness, and pinhole value) are used throughout the time course. The fluorescence intensity values (in arbitrary units) from the designated regions are expressed as percentage of the fluorescence intensity from baseline (t = 0) in every experiment. Figure 7.2 illustrates a time course for UTP-induced Ca2+ i mobilization, based on changes in fluo-4 fluorescence intensity, in a 6-day-old polarized primary culture of HBE.

Fig. 7.2. Time course for mucosal UTP-induced Ca2+ i mobilization in polarized HBE loaded with fluo-2. Representative confocal XZ scans illustrating a time series for 100 μM mucosal UTP-induced Ca2+ i mobilization, indexed by changes in fluo-4 fluorescence intensity, in a polarized primary culture monolayer of HBE.

3.3. Measurements of Mitochondrial Ca2+ (Ca2+ m ) Using Rhod-2 as a Reporter 3.3.1. HBE Loading with Rhod-2

For confocal Ca2+ m measurements, polarized HBE cultures are loaded with rhod-2 by incubation with 5 μM rhod2/AM at 4◦ C for 18 h in HBSS, followed by incubation with 5 μM rhod-2/AM in Ham’s F12 medium at 37◦ C for 1 h as previously described (5). Cultures are subsequently washed with HBSS and kept in HBSS (only at the serosal compartment).

3.3.2. Confocal Microscopic Assessment of GPCR Activation-Induced Ca2+ m Mobilization in Rhod-2-Loaded HBE

Rhod-2-loaded cultures are mounted on a glass cover slip over an objective coupled to a confocal microscope. Ca2+ m mobilization (changes in rhod-2 fluorescence) is studied by laser confocal microscopy on the XY or XZ scanning mode, utilizing an excitation of 552 nm and an emission of 571 nm (5). The fluorescence intensity of rhod-2 can be measured with the MetaMorph software or equivalent imaging software. Regions of interest are designated for the apical or the basolateral domains, depending on the protocol (e.g., whether GPCR activation-induced Ca2+ m

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Fig. 7.3. Mitochondrial calcium (Ca2+ m ) uptake elicited by apical P2Y2 receptor activation is inhibited by mitochondrial uncouplers. Representative time series of XY confocal scans from the apical epithelial domain. (a) (top): Time course for Ca2+ m uptake (visualized as increases in rhod-2 fluorescence) after addition of 100 μM mucosal UTP to a polarized primary culture monolayer of CF human bronchial airway epithelia. A (bottom): Effect of subsequent mitochondrial uncoupling with 1 μM CCCP and 2.5 μg/ml oligomycin on Ca2+ m accumulation induced by apical P2Y2 receptor activation. Bar, 10 μm. (b) Summary of the time series studies depicted in A. Data are expressed as a percentage of baseline fluorescence and represent the mean of four experiments ± SEM. ∗ P < 0.05, 100 μM mucosal UTP-induced fluorescence vs. baseline (t = 0) fluorescence. From © Ribeiro et al., 2003. Originally published in The Journal of General Physiology. doi, 10.1085/jgp.200308893.

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mobilization is investigated in the mitochondria localized at the apical or the basolateral domains), and the same region is quantified at each time point during a time course for, e.g., UTPinduced Ca2+ m mobilization. The same acquisition parameters (e.g., laser power, contrast, brightness, and pinhole value) are used throughout the time course. The fluorescence intensity values (in arbitrary units) from the designated regions are expressed as percentage of the fluorescence intensity from baseline (t = 0) in every experiment. Figure 7.3 depicts a time series of XY confocal images from the apical domain of polarized CF HBE monolayers loaded with rhod-2. Mucosal application of 100 μM UTP, which activates apical P2Y2 receptors and triggers a rise in Ca2+ i , rapidly induces elevations of Ca2+ m (Fig. 7.3a, top panels). To confirm whether the changes in rhod-2 fluorescence result from P2Y2 receptor activation-dependent Ca2+ m uptake, subsequent treatment with 1 μM carbonyl cyanide m-chlorophenylhydrazone (CCCP) and 2.5 μg/ml oligomycin (to depolarize the mitochondria and abolish the driving force for Ca2+ m uptake) abolishes the UTPinduced rise in mitochondrial rhod-2 fluorescence (Fig. 7.3a, lower panels). Fig. 7.3b summarizes the time series studies illustrated in Fig. 7.3a. These studies show that Ca2+ i , released from IP3 -sensitive ER 2+ Ca stores after P2Y2 receptor stimulation, accumulates in functioning mitochondria in airway epithelia. As discussed earlier, rises in Ca2+ m may regulate mitochondrial function relevant to CF airway pathophysiology, e.g., mitochondria-mediated generation of ROS. Our laboratory is currently investigating the role of Ca2+ i signals released from ER Ca2+ stores in mitochondrial production of ROS.

4. Notes 4.1. Ca2+ i Signals in Short-Term vs. Long-Term Polarized Primary Cultures of Normal and CF HBE

When studying Ca2+ i signaling in polarized primary cultures of normal and CF human airway epithelia, the age of the cultures is a key issue. As mentioned earlier, apical P2Y2 or BK receptor activation induces greater Ca2+ i mobilization in short-term (6– 11-day-old) primary cultures of CF as compared to normal HBE due to an expansion of the apically confined ER Ca2+ stores in CF (1, 2). In contrast, similar levels of ER Ca2+ storage are found in long-term (30–40 days) primary cultures of CF and normal HBE (1, 2). Figure 7.4 depicts GPCR activation-triggered Ca2+ i signals in normal vs. CF short-term and long-term primary cultures. The ER Ca2+ store expansion in polarized primary cultures of CF HBE is an acquired epithelial response to chronic

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Fig. 7.4. Activation of apical GPCRs triggers larger Ca2+ i signals in short-term, but not long-term, primary cultures of CF vs. normal HBE. Top panel: Representative Ca2+ i tracings depicting the effect of apical UTP (100 μM)- or BK (5 μM)mobilized Ca2+ i in short-term (6–11-day-old) polarized primary cultures of normal and CF HBE. Bars depict compiled Ca2+ i values (peak – baseline Ca2+ i ) from UTP- or BK-stimulated cultures. Data are expressed as mean ± SEM (n = 4 for UTP studies in both groups; n = 3 for BK studies in both groups; ∗P < 0.05). Lower panel: Representative Ca2+ i tracings illustrating the effect of apical ATP (100 μM)-mobilized Ca2+ i in 30–40-day-old long-term cultures of normal and CF HBE, respectively. Bars depict compiled Ca2+ i values (peak – baseline Ca2+ i ) from ATP-stimulated cultures. Data are expressed as mean ± SEM (n = 3–5).

airway infection/inflammation based on the following observations. First, the increased ER mass and Ca2+ i signals revert to normal in primary CF HBE cultures maintained for a long term in the absence of luminal infection/inflammation (1, 2). Second, the CF phenotype (increased apical ER Ca2+ stores coupled to larger apical GPCR activation-induced Ca2+ i signals) can be transferred to normal HBE by luminal exposure to SMM, an infectious/inflammatory stimulus from human CF airways (1, 2). Because the ER Ca2+ store expansion in CF epithelia reflects an epithelial adaptation to the in situ infectious/inflammatory

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milieu of CF airways, which is lost in vitro with time in the absence of airway infection/inflammation, investigators studying alterations in Ca2+ i -dependent functions should take into consideration the age of their primary cultures. In agreement with this notion, while a Ca2+ i -mediated response (e.g., mucosal BKinduced interleukin-8 secretion) is upregulated due to expanded ER Ca2+ stores in short-term CF vs. normal HBE cultures, BKinduced interleukin-8 secretion is the same in long-term CF vs. normal HBE cultures with similar levels of ER Ca2+ storage (1, 2).

Acknowledgments The author thanks Lisa Brown for editorial assistance and Mary Braun Martino for technical assistance and has declared no conflict of interest. This work was supported by grants RIBEIR00Z0, RIBEIR00G0, and RIBEIR07G0 from The Cystic Fibrosis Foundation. References 1. Ribeiro, C. M. P., Paradiso, A. M., Carew, M. A., Shears, S. B., and Boucher, R. C. (2005) Cystic fibrosis airway epithelial Ca2+ i signaling. The mechanism for the larger agonist-mediated Ca2+ i signals in human cystic fibrosis airway epithelia. J Biol Chem 280, 10202–10209. 2. Ribeiro, C. M. P., Paradiso, A. M., Schwab, U., Perez-Vilar, J., Jones, L., O’Neal, W., et al. (2005) Chronic airway infection/Inflammation Induces a Ca2+ idependent hyperinflammatory response in human cystic fibrosis airway epithelia. J Biol Chem 280, 17798–17806. 3. Martino, M. E. B., Olsen, J. C., Fulcher, N. B., Wolfgang, M. C., O’Neal, W. K., and Ribeiro, C. M. P. (2009) Airway epithelial inflammation-induced endoplasmic reticulum Ca(2+) store expansion is mediated by X-box binding protein-1. J Biol Chem 284, 14904–14913. 4. Paradiso, A. M., Mason, S. J., Lazarowski, E. R., and Boucher, R. C. (1995) Membranerestricted regulation of Ca2+ release and influx in polarized epithelia. Nature 377, 643–646.

5. Ribeiro, C. M., Paradiso, A. M., Livraghi, A., and Boucher, R. C. (2003) The mitochondrial barriers segregate agonist-induced calcium-dependent functions in human airway epithelia. J Gen Physiol 122, 377–387. 6. Paradiso, A. M., Ribeiro, C. M. P., and Boucher, R. C. (2001) Polarized signaling via purinoceptors in normal and cystic fibrosis airway epithelia. J Gen Physiol 117, 53–68. 7. Clarke, L. L., and Boucher, R. C. (1992) Chloride secretory response to extracellular ATP in normal and cystic fibrosis nasal epithelia. Am J Physiol 263, C348–C356. 8. Winklhofer-Roob, B. M. (1994) Oxygen free radicals and antioxidants in cystic fibrosis: the concept of an oxidant-antioxidant imbalance. Acta Paediatr Suppl 395, 49–57. 9. Hudson, V. M. (2001) Rethinking cystic fibrosis pathology: the critical role of abnormal reduced glutathione (GSH) transport caused by CFTR mutation. Free Radic Biol Med 30, 1440–1461. 10. Gunter, T. E., Buntinas, L., Sparagna, G., Eliseev, R., and Gunter, K. (2000) Mitochondrial calcium transport: mechanisms and functions. Cell Calcium 28, 285–296.

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11. Byrne, A. M., Lemasters, J. J., and Nieminen, A. L. (1999) Contribution of increased mitochondrial free Ca2+ to the mitochondrial permeability transition induced by tertbutylhydroperoxide in rat hepatocytes. Hepatology 29, 1523–1531. 12. Urushitani, M., Nakamizo, T., Inoue, R., Sawada, H., Kihara, T., Honda, K., et al. (2001) N-methyl-D-aspartate receptormediated mitochondrial Ca(2+) overload in acute excitotoxic motor neuron death: a mechanism distinct from chronic neurotoxicity after Ca(2+) influx. J Neurosci Res 63, 377–387. 13. Wilkinson, J. A., and Jacob, R. (2003) Agonist-induced calcium and oxidative stress responses in endothelial cells. Biochem Soc Trans 31, 960–962. 14. Jou, M. J., Jou, S. B., Guo, M. J., Wu, H. Y., and Peng, T. I. (2004) Mitochondrial reactive oxygen species generation and calcium increase induced by visible light in astrocytes. Ann N Y Acad Sci 1011, 45–56. 15. Riess, M. L., Camara, A. K. S., Kevin, L. G., An, J., and Stowe, D. F. (2004) Reduced reactive O2 species formation and preserved mitochondrial NADH and [Ca2+ ] levels during short-term 17◦ C ischemia in intact hearts. Cardiovasc Res 61, 580–590. 16. Ribeiro, C. P., Wu, Y., Hurd, H., and O’Neal, W. (2005) A model for oxidative stress responses induced by calcium signals in human airway epithelia. Pediatr Pulmonol Suppl 28, 262. 17. Grynkiewicz, G., Poenie, M., and Tsien, R. Y. (1985) A new generation of Ca2+ indica-

18.

19.

20. 21. 22. 23.

24.

25.

tors with greatly improved fluorescence properties. J Biol Chem 260, 3440–3450. Simpson, A. W. M. (2006) Fluorescent measurement of [Ca2+ ]c, in (Lambert, D. G., ed.), Calcium Signaling Protocols. Humana Press, Totowa, NJ, pp. 3–36. Ribeiro, C. M. P., Paradiso, A. M., Lazarowski, E., and Boucher, R. C. (2001) P2Y2 receptors and Ca2+ -dependent Clsecretion in normal and cystic fibrosis human airway epithelia, in (Salathe, M., ed.), Cilia, Mucus and Mucociliary Interactions. Marcel Dekker, Inc., New York, NY, USA, pp. 303–314. Putney, J. W., Jr. (1986) A model for receptor-regulated calcium entry. Cell Calcium 7, 1–12. Putney, J. W., Jr. (1990) Capacitative calcium entry revisited. Cell Calcium 11, 611–624. Clapham, D. E. (1995) Intracellular calcium. Replenishing the stores. Nature 375, 634–635. Ribeiro, C. M. (2006) The role of intracellular calcium signals in inflammatory responses of polarised cystic fibrosis human airway epithelia. Drugs R D 7, 17–31. Zsembery, A., Fortenberry, J. A., Liang, L., Bebok, Z., Tucker, T. A., Boyce, A. T., et al. (2004) Extracellular zinc and ATP restore chloride secretion across cystic fibrosis airway epithelia by triggering calcium entry. J Biol Chem 279, 10720–10729. Coyne, C. B., Ribeiro, C. M., Boucher, R. C., and Johnson, L. G. (2003) Acute mechanism of medium chain fatty acid-induced enhancement of airway epithelial permeability. J Pharmacol Exp Ther 305, 440–450.

Chapter 8 Identification and Quantification of Mucin Expression Kristina A. Thomsson and Gunnar C. Hansson Abstract The major phenotype of CF is the accumulation of mucus, a phenomenon whose relation to the dysfunctional CFTR is still not fully understood. This means that studies of mucus and its main component, the mucins, are important. Due to the large size and high glycosylation level, such questions need special considerations and methodology. We describe methods for the general quantification of heavily glycosylated proteins as the mucins using dot/slot blot. We also describe the separation of the mucins by gel electrophoresis and the identification with specific antibodies on Western blot and by proteomics. Key words: Mucin, dot/slot blot, mass spectrometry, nano-LC, HPLC.

1. Introduction Although mucoviscidose is the original name for cystic fibrosis, there is still no understanding of the relation between a non-functional CFTR ion channel and the cystic fibrosis phenotype with its viscous and sticky mucus. However, an emerging new line of research addressing this connection is coming from the observation that CFTR is also able to transport bicarbonate and that this is more linked to disease severity than the chloride secretion (1). A major reason for the slow progress in understanding the relation between CFTR and mucus is the large difficulties in working with mucus and its major component, the mucins. The major type of mucins is the gel-forming mucins among which the MUC5B from the glands and the MUC5AC from the surface goblet cells are the major ones in the lungs, although small amounts of MUC2 can also be found in M.D. Amaral, K. Kunzelmann (eds.), Cystic Fibrosis, Methods in Molecular Biology 742, DOI 10.1007/978-1-61779-120-8_8, © Springer Science+Business Media, LLC 2011

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Fig. 8.1. Schematic diagram of possible workflow for the quantification and identification of mucins. ∗ means optional.

diseased lungs (2). All these mucins are large and heavily glycosylated proteins that occur as polymers. The monomeric building blocks are typically 2.5 MDa and the polymers can probably reach 100 MDa. This enormous size and the dense glycosylation poses large methodological difficulties. In this chapter, we describe some of the methods that can be used in studies of the mucins and their nature in the lungs and other organs. Depending on the question asked, there are many ways to analyze mucins, both qualitative and quantitative. Figure 8.1 shows a flowchart of potential ways to analyze mucins that are described in detail in the current chapter.

2. Materials 2.1. Mucin Preparation and Solubilization 2.1.1. Mucin Solubilization Using a Chaotropic Salt

1. Magnets, 3 mm diameter. 2. Mini pestle.

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3. Protease inhibitor (Complete, EDTA free; Roche). 4. Magnetic stirrer. 5. Centrifuge for Eppendorf tubes, minimum 16,000×g. 6. Guanidinium chloride buffer (GuHCl, 6 M with 5 mM EDTA, 0.1 M Tris, pH 8.0). 7. Dithiothreitol (DTT powder, solution in GuHCl with a final concentration of 1.0 M, stored at −20◦ C). 8. Iodoacetamide (IAA). Stock solution in GuHCl (1 or 2 M) freshly prepared in GuHCl before use. 9. Dialysis tubes (6–8 kDa MWCO). 10. Lyophilizer.

2.1.2. Mucin Solubilization Using Protein Gel Sample-Loading Buffer

1. 2× Sample buffer (0.75 M Tris–HCl (pH 8.1), 2% SDS, 0.01% bromophenol blue, 60% glycerol). 2. Protease inhibitor (Complete, EDTA free; Roche). 3. Dithiothreitol (DTT). 4. Iodoacetamide (IAA).

2.2. Slot/Dot Blotting

1. Slot/blot filtration manifold (PR648; GE Healthcare or similar). 2. Nitrocellulose membrane (Protran; Whatman). 3. Water aspirator.

2.3. Visualization/ Quantification of Mucins and Heavily Glycosylated Proteins on Nitrocellulose Membranes 2.3.1. Periodic Acid/Schiff (PAS) Staining

1. Solution A. Periodic acid (0.75 g) and acetic acid (4.5 ml concentrated acetic acid) dissolved in 150 ml mpH2 O (prepared fresh before use). 2. Solution B. Sodium disulfite (0.5 g) and hydrochloric acid (41.4 μl concentrated HCl) mixed with 500 ml mpH2 O (prepared fresh before use). 3. Schiff’s reagent (BDH, Poole, England).

2.3.2. Alcian Blue Staining

1. Alcian blue 8GX (Sigma-Aldrich): 0.125% (w/v) Alcian blue in 25% (v/v) ethanol and 10% (v/v) acetic acid.

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2.3.3. DIG Glycan Detection

1. DIG glycan detection kit (Roche).

2.3.4. Immunoblotting

1. Mucins transferred to nitrocellulose or PVDF membranes. 2. Blocking buffer (5% (w/v) nonfat dry milk, 0.1% (w/v) Tween 20 in PBS (pH 7.5)). 3. Wash buffer (0.1% Tween 20 in PBS). 4. Primary antibody. A number of antibodies are available for the major mucins in the lung, but several of these are less specific. Table 8.1 shows a list of antibodies that have been found to be useful for the human mucins. 5. Secondary antibody conjugated to horse radish peroxidase diluted in blocking buffer. 6. ECL reagent. SuperSignal West Pico chemiluminescent substrates (Pierce) and luminescence imaging system.

2.4. Composite Agarose– Polyacrylamide Gel Electrophoresis

1. Agarose (type 1-B: LowEEO; Sigma). 2. Acrylamide (40% solution, acrylamide/bis 19:1; Bio-Rad). 3. Ammonium persulfate (APS, 40% solution in mpH2 O, stored at −20◦ C; Bio-Rad). 4. TEMED (Bio-Rad). 5. 5× Tris–HCl buffer (1.875 M, pH 8.1). 6. Glycerol (50% solution). 7. Casting equipment (Bio-Rad Mini-Protean or equivalent). 8. Peristaltic pump (for example, GE Healthcare P-1 pump). 9. Large and small glass plates, two 1.5-mm spacers, two 0.75-mm combs. 10. Lower gel solution. Agarose (0.08 g) is mixed with 5× Tris– HCl buffer (pH 8.1, 1.6 ml), 50% glycerol (1.6 ml), and ddH2 O (1.6 ml). 11. Upper gel solution. Agarose (0.04 g) is mixed with 5× Tris– HCl buffer (pH 8.1, 1.6 ml) and mpH2 O (6.4 ml). 12. Gradient mixer and peristaltic pump (SG Gradient Makers and P-1 pump; GE Healthcare or equivalent). 13. Oven, 60◦ C. 14. Gel electrophoresis equipment (Bio-Rad or equivalent). 15. Running buffer (192 mM boric acid, 1 mM EDTA, 0.1% SDS, pH 7.6 (set with Tris base)).

OC125

MUC16

Mouse MAb

Rabbit PAb

Mouse MAb

Rabbit PAb

45M1

MUC5AC

Rabbit PAb

HPA006411

MUC2-N3

MUC2

Armenian Hamster MAb

MUC5B

CT2

MUC1

Antibody type

MUC7

Antibody name

Human mucin

Table 8.1 Suggested antibodies against human mucins

Antibodies-online

Atlas Antibodies and Sigma

See reference

Abcam

See reference

Abcam (called MH1)

Source

1:500–1:1000

1:150

1:100–1:1000

1:500–1:1000

1:500–1:1000

Suggested dilution

Need antigen retrieval

Only non-reduced

N-terminal end of MUC2

Detects small transmembrane fragments below 50 kDa

Comment

(10)

www.proteinatlas.org

(9)

(8)

(7)

(6)

Reference

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2.5. Visualization/ Quantification of Mucins and Heavily Glycosylated Proteins on Composite Gels 2.5.1. Protein-Based Detection

1. SYPRO Ruby protein gel stain kit (Molecular Probes).

2.5.2. Glycan-Based Detection

1. Alcian blue stain. (a) Fix solution. 50% (v/v) methanol and 1% (v/v) acetic acid in mpH2 O.

2. Imperial stain (Pierce).

(b) Equilibration solution. 25% (v/v) ethanol and 10% (v/v) acetic acid in mpH2 O. (c) Stain solution. 0.125% (w/v) Alcian blue 8GX (Sigma) in equilibration solution. The stain can be reused at least three times. A stock solution of Alcian blue can be stored in room temperature. (d) Destain solution. 50% (v/v) ethanol and 10% (v/v) acetic acid in mpH2 O. (e) Rehydration solution. 1% (v/v) acetic acid. 2.6. Quantification of Mucins and Glycoproteins on Membranes or Gels

1. Imager for fluorescence and luminescence.

2.7. Mucin/ Glycoprotein Transfer to PVDF Membrane

1. Wet blot equipment (Mini Trans-Blot electrophoretic transfer cell; Bio-Rad or equivalent).

2. Image J software (Research Services Branch, National Institute of Mental Health, Bethesda, MD).

2. Immobilon membrane (polyvinylidene fluoride (PVDF) PSQ ; Millipore). 3. Filter papers, 2 mm thickness (Schleicher & Schuell). 4. Wet blot buffer (25 mM Tris, 192 mM glycine, 0.04% SDS, and 20% methanol).

2.8. Trypsin Digestion

Use doubly distilled water or mpH2 O of high purity and free from salts (18 M) for all solutions. 1. Speedivac rotating vacuum evaporator. 2. Siliconized Eppendorf tubes. 3. Destain solution 1. 25 mM NH4 HCO3 in 50% MeOH. 4. Destain solution 2. 25 mM NH4 HCO3 in 50% acetonitrile. 5. Trypsin. 5–10 μg/ml in 25 mM NH4 HCO3 (sequencinggrade trypsin; Promega).

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6. Incubator or oven at 37◦ C. 7. Micro-centrifuge. 8. Extract solution 1. 1% (v/v) trifluoroacetic acid (TFA) in 50% acetonitrile. 9. Extract solution 0.1% (v/v) TFA in 50% acetonitrile. 10. 0.1% (v/v) formic acid or acetic acid. 2.9. Identification of Mucins with Proteomics

Reversed-phase nano-LC–MS/MS may be performed on many different systems which are used for the analysis of tryptic digests of proteins. The following system has been used by us: 1. HPLC system for a binary gradient. Agilent 1100 binary pump (Agilent Technologies, Palo Alto, CA). 2. Valco T valve with a fused silica restrictor, decreasing the flow down to 250 nl/min. 3. Mobile phase. A, 0.2% (v/v) formic acid; B, acetonitrile (HPLC grade; Sigma). 4. HTC-PAL autosampler (CTC Analytics AG, Zwingen, Switzerland) equipped with a 2-μl loop. 5. Analytical column (17 cm × 50 μm i.d.) packed with 3-μm particles Reprosil-Pur C18 -AQ (Dr. Maisch GmbH, Ammerbuch, Germany). 6. Mass spectrometer, LTQ Orbitrap (Thermo Electron., San Jose, CA) equipped with an online nanospray interface. 7. Peptide matching program (Mascot, Matrix Science, www. matrixscience.com). 8. Mucin database available on our homepage (www.medkem. gu.se/mucinbiology).

3. Methods 3.1. Mucin Preparation and Solubilization

Mucosal secretions are most efficiently solubilized using a chaotropic salt such as guanidinium chloride (see Section 3.1.1). This also helps to separate material bound to the sticky mucins. Many mucins contain multiple disulfide bonds that build up the multimeric complexes giving the mucosal secretion its gel-like properties. Due to this, we often reduce and alkylate the mucin and dialyze away the salt; despite that this takes several days. Alternatively, working with small sample volumes, we have dialyzed away salts using dialysis cups overnight (3). When mucins from mucosal secretions are to be analyzed with composite gel electrophoresis (see Section 3.3), a simpler sample preparation is sometimes sufficient, where the reduction and/or alkylation can

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be done in sample buffer (see Section 3.1.2), then alkylation may be excluded. However, we often see that we obtain better tryptic peptide coverage in proteomics after alkylation of the multimeric mucins. 3.1.1. Mucin Solubilization Using a Chaotropic Salt

1. The sample is collected and stored with protease inhibitor (25×) at −80◦ C. 2. Homogenization in GuHCl with protease inhibitor is performed using a plastic mini pestle. Add 200–400 μl guanidinium chloride buffer. 3. The homogenized material is stirred on a magnet stirrer gently overnight at +4◦ C. 4. Reducing agent DTT is added to a final concentration of 100 mM. The solution is stirred at 37◦ C for 5 h or overnight. 5. Alkylating agent IAA is added to a final concentration of 250 mM and stirred for 5 h or overnight at room temperature in the dark. 6. Sample is transferred to dialysis tubes and dialyzed against water (>4 l), two changes per day during 3 days. 7. Sample is lyophilized.

3.1.2. Mucin Solubilization Using Protein Gel Sample-Loading Buffer

1. The sample is collected and stored with protease inhibitor (25×) at −80◦ C. 2. Reduction with DTT (final concentration of 20 mM) in protein gel sample-loading buffer at 95◦ C under magnetic stirring for 30 min, followed by 2 h at 37◦ C. 3. Alkylation by addition of IAA to a final concentration of 50 mM under magnetic stirring for 1–3 h or overnight at room temperature in the dark.

3.2. Slot/Dot Blot Followed by Visualization/ Quantification of Mucins or Large Glycoproteins 3.2.1. Slot/Dot Blotting

1. The nitrocellulose membrane is rinsed with mpH2 O and placed inside the slot/blot filtration manifold. 2. The manifold is assembled and connected to a water aspirator. 3. Samples (40–450 μl) are loaded and allowed to vacuum pull the liquid until wells are dry. 4. The membrane is developed according to Sections 3.2.2, 3.2.3, 3.2.4, or 3.2.5.

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1. Wash membrane in mpH2 O for 1 min. 2. Incubate membrane in Alcian blue solution for 10–20 min. 3. Wash membrane in mpH2 O three times for 10 min. 4. Let the membrane dry. 5. Image the membrane (see Section 3.3.2).

3.2.3. PAS Staining of Mucins and Glycoproteins on Membranes (See Note 2)

1. Place the nitrocellulose membrane with the dried glycoproteins in a plastic basin. 2. Add 150 ml of mpH2 O and agitate the membrane gently at room temperature for 2 min. 3. Agitate the membrane in 150 ml of Solution A for 30 min. 4. Agitate the membrane in 150 ml of Solution B two times for 2 min. 5. Agitate the membrane in 100 ml of Schiff’s reagent for 15 min. 6. Remove the Schiff’s reagent, dry the basin quickly, and add 150 ml of Solution B and shake the membrane for 2 min. 7. Rinse membrane with mpH2 O. 8. Let the membrane dry. 9. Image the membrane (see Section 3.3.2).

3.2.4. Detection of Glycosylated Proteins with DIG Glycan Detection Kit (See Note 2)

1. The membrane is developed according to the protocol supplied with the kit.

3.2.5. Identification and Semiquantification of Mucins on Nitrocellulose and PVDF Membranes by Immunohistochemistry

1. Activate the PVDF membrane with methanol.

2. The membrane is imaged (see Section 3.3.2).

2. Incubate in blocking buffer for 1 h or overnight at 4◦ C. 3. Incubate with the primary antibody against a specific mucin (Table 8.1) at 4◦ C overnight. 4. Wash three times for 20 min in wash buffer. 5. Incubate for 2 h at room temperature with the secondary antibody. 6. Wash five times for 15 min in wash buffer. 7. Take away the major amount of solution from membrane, but avoid getting dry patches. 8. Develop the membranes with ECL according to the manufacturer’s instructions and image.

3.3. Composite Agarose– Polyacrylamide Gel Electrophoresis

The following protocol for analysis of mucins with composite agarose–polyacrylamide gel electrophoresis was originally developed by Dr. Niclas Karlsson and coworkers (4). Composite gel

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Fig. 8.2. Reduced and alkylated mucins from saliva, analyzed by composite polyacrylamide gel electrophoresis and visualized with Alcian blue. The mucins were identified by proteomics. Lane 1, whole saliva; Lane 2, saliva from submandibular/sublingual glands.

electrophoresis of mucins functions as a purification step where smaller proteins (approximately 10–100 kDa) migrate in the front. Figure 8.2 shows the analysis of reduced and alkylated salivary mucins, where MUC5B with a protein core of approximately 500 kDa separates readily from MUC7 with a protein core of approximately 100 kDa. Mucins like MUC5AC and MUC5B do not usually separate on the gel, since they are approximately of the same size. However, glycoforms can separate as we have shown for MUC5B in saliva (5), with the more acidic forms migrating further into the gel. 1. The gel casting equipment (glass plates and spacers) is mounted and placed in a 60◦ C oven, together with a gradient mixer and a pump. The pump is connected to the gradient mixer and a tubing connected to the pump is placed in-between the glass plates of the casting equipment. 2. A gel containing agarose (0.5–1% gradient), acrylamide (0–6%), and glycerol (0–10%) is prepared. The lower and upper gel solutions are prepared as described in Section 2.4, steps 10 and 11. Both solutions are boiled in a microwave oven until the agarose has melted and then immediately placed in the 60◦ C oven. 3. When the lower gel solution has cooled down to ∼60◦ C, acrylamide (40%, 1.2 ml) is added. 4. The upper and lower gel solutions (5 ml of each) are added to each chamber of the gradient mixer. APS (2 μl) and TEMED (2 μl) are added to the two chambers, respectively, and the solutions are mixed. The lower solution is stirred with a magnet and a magnetic stirrer.

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5. The pump is started at a maximum rate (10 on a GE Healthcare P-1 pump) and the two valves of the gradient mixer are opened. The gel must be casted within 2 min. 6. Two combs (2 mm × 0.75 mm) are put into the gel which is polymerized at RT for at least 6–7 h, or after 1–2 h at RT followed by +4◦ C overnight. The gels can be stored (with combs) at +4◦ C wrapped in plastic with wet papers for at least a week. 7. If the gel around the combs has shrunk, the gel can be reconstituted with the upper gel solution that has been reheated in the microwave oven. 8. Prior to electrophoresis, the combs are removed carefully, the gel is placed in the electrophoresis equipment, and running buffer is added. The wells are carefully washed with running buffer prior to use. The outer and inner containers are filled with running buffer to keep the gel cool during electrophoresis. 9. The electrophoresis container is placed on ice in a cold room (+4◦ C). After samples are loaded (sample volume limit is the well size, approximately 50–60 μl), the gel is run for 3 h at 30 mA/gel. 10. The gel is developed with a stain (see Section 3.3.1) and can then be stored in a sealed plastic bag in 1% acetic acid for at least 2 weeks. 3.3.1. Visualization of Mucins on Composite Gels

We have included three examples of stains that are all nondestructive, allowing further analysis by proteomics. Due to the dense glycosylation of mucins, these are often easily visualized with Alcian blue as there are often acidic groups present. However, for quantitative purposes, protein stains are more attractive as the type of glycosylation can vary between samples. We use Imperial stain, which is an improved Coomassie-based stain and compatible with proteomics. The commercial product SYPRO Ruby stain is a more sensitive fluorescent protein stain (in the same range as silver staining) and as this is developed for quantification of proteins in gels, this is the best for quantitative purposes. In contrast to the silver stain, this is fully compatible with subsequent proteomics.

3.3.1.1. SYPRO Ruby Staining

1. Remove the gel from the glass plates and place it in a plastic container. 2. Cover the gel with 50 ml SYPRO Ruby protein gel stain and gently agitate for 3 h or overnight. 3. Rinse gel in 10% MeOH/7% HAc for 30–60 min. 4. Wash gel in mpH2 O.

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3.3.1.2. Imperial (Coomassie) Stain

1. Remove the gel from the glass plates and place it in a plastic container and fix with 50% methanol, 10% HAc 1 h or over night. 2. Add Imperial stain and agitate the gel for 1–2 h on an orbital shaker. 3. Remove the stain and wash with mpH2 O. Destain the gel with 200 ml mpH2 O while shaking on an orbital shaker for 1–24 h.

3.3.1.3. Alcian Blue Stain

1. Fix the mucins in the gel by washing with 50% methanol and 1% acetic acid in mpH2 O for at least 1 h. 2. Equilibrate the gel by washing with 25% ethanol and 10% acetic acid in mpH2 O two times for 15 min. 3. Stain the gel with Alcian blue for 20 min. 4. Destain the gel with 50% ethanol and 10% acetic acid in mpH2 O three times for 10 min, or until satisfied. 5. Rehydrate the gel with 1% acetic acid in mpH2 O for 30 min.

3.3.2. Quantification of Mucins on Composite Gels or Blots

1. Image the SYPRO Ruby-stained gel by UV light using a fluorescent imager that allows quantification. Image the Coomassie-, PAS-, DIG-, or Alcian blue-stained gel by a visual scanner. 2. Analyze the bands by the Image J software or software coming with the fluorescent imager. Subtract background and relate the intensities to appropriate controls.

3.4. Mucin/ Glycoprotein Transfer to PVDF Membrane (See Note 3)

1. The gel is wet blotted in a Mini Trans-Blot electrophoretic transfer cell. Immobilon (PVDF PSQ ) membrane and filter papers (2×2 mm thickness) are cut out in the size of 6 cm × 9 cm. The wells of the gel are cut off before mounting the wet blot sandwich (mounting according to the manual). 2. The sandwich is placed in the transfer cell (with the gel facing the cathode), which is filled with transfer buffer and put on stirring on ice in the cold room (+4◦ C). 3. The blotting is performed at 40 W (gives ∼350–450 mA over time) for 1.5–3 h. 4. The membrane is developed with immunohistochemistry according to Section 3.2.5.

3.5. Sample Preparation for Proteomics on Mucins (See Note 4)

1. Wash the gel with mpH2 O. 2. Cut out the bands of interest on a glass plate using a scalpel. 3. Divide the gel pieces in 1.5 mm3 pieces (to facilitate enzymatic digestion) and place them into siliconized Eppendorf tubes.

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4. Destain/wash the gel plug with 0.5 ml destain solution 1 with gentle agitation for 20 min (see Note 5). 5. Destain/wash the gel plug with destain solution 2 with gentle agitation three times for 30 min or until the majority of the stain has been washed away. 6. Remove the liquid and dry the gel plugs in the speedivac. 7. Add 5–10 μl of trypsin solution to the gel pieces. If the gel plugs are not sufficiently hydrated, small aliquots of 25 mM NH4 HCO3 can be added. 8. Seal the tubes and incubate at 37◦ C overnight. 9. Add 15 μl of extract solution 1 and shake the tubes for 30 min. 10. Spin down the liquid in micro-centrifuge for a few seconds and transfer the extracted peptides to a new tube. 12. Add 20 μl of extract solution 2. 13. Shake for 30 min and pool peptide extracts. 14. Dry the peptides with vacuum centrifugation and immediately re-dissolve in 10–20 μl 0.1% HAc or HCOOH. Samples can be stored at −20◦ C. 3.6. Identification of Mucins with Proteomics

We have been more successful with nano-LC/MS than MALDI MS of tryptic peptide digests of mucins to obtain good peptide coverage. One explanation for this is that if the preparation contains the large trypsin-resistant domains, these can interfere with the crystallization on the plate. Other problems are contaminating proteins from cell debris as these can interfere with the ionization and detection of the mucin-derived peptides. It should be taken into account that most mucins generate few nonmodified tryptic peptides due to lack of frequent arginine and lysine residues and especially that many peptides do not have the expected mass due to glycan modifications. For a high-quality identification of the few non-modified peptides usually generated from mucins, each peptide should be characterized both by sequencing and with high accuracy as can be obtained by ion cyclotron resonance (ICR) or Orbitrap mass spectrometers. 1. The peptides (2 μl) are trapped on a precolumn and analyzed on the analytical column containing C18 particles. Nano-LC/MS was performed on a linear ion trap, LTQ (Thermo Finnigan). The fused silica emitter tip was held at 1.4 kV, the heated capillary at 220◦ C, and capillary voltage at 44 V. Normal scan range m/z 300–2000 (two microscans, 100 ms), data-dependent MS2 scans of the five most abundant ion in each scan, also with two microscans (100 ms), normalized collision energy of 35%, isolation window of 4.0 u, and an activation time of 30 ms.

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2. The data files obtained from nano-LC/MS of the tryptic protein digests are searched against a mucin database containing the mucin sequences that have been assembled from human and mouse genome data (see Note 6). Searches were performed using the search program MASCOT (Matrix Science).

4. Notes 1. Alcian blue is a cationic dye that binds to negatively charged carboxyl and sulfate groups on oligosaccharides. When comparing samples from different sources, it should thus be taken into account that there can be a natural variation in the amount of acidic residues, such as, for example, on salivary MUC5B in healthy individuals (5). 2. The chemistry behind both the PAS stain and the DIG glycan detection kit involves mild oxidation of vicinal hydroxyl groups in saccharide residues to aldehydes, which then are further conjugated to form a bright red dye (PAS) or to a spacer-linked steroid hapten digoxigenin (DIG). DIG is detected using an antibody conjugated to alkaline phosphatase. 3. Mucins can also be transferred to PVDF membrane using semidry blot, but large mucins with protein cores of 500 kDa or more are more efficiently transferred using wet blot. 4. Stains compatible with proteomics are the Alcian blue, Imperial stain, and SYPRO Ruby stains. The gel can be stored in 1% HAc for at least 1–2 weeks in an enclosed plastic bag, before being further processed for proteomics. Work in a clean area and work with gloves to avoid keratin contamination. 5. Alcian blue will never be removed from the gel piece. 6. The annotation and sequences of mucins in public databases have been poor, but recently these have been improved by taking advantage of our mucin database found at www. medkem.gu.se/mucinbiology/. This database contains individually assembled mucin sequences as curated by us. The database also contains assembled sequences of mucins in the FASTA format ready to be used in proteomics search engines such as MASCOT.

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Acknowledgments This work was supported by the Swedish Research Council (no. 7461, 21027, and 342-2004-4434), The Swedish Cancer Foundation, The Knut and Alice Wallenberg Foundation (KAW2007.0118), IngaBritt and Arne Lundberg Foundation, Sahlgren’s University Hospital (LUA-ALF), EU-FP7 IBDase, Wilhelm and Martina Lundgren’s Foundation, Söderbergs Stiftelser, Swedish CF Foundation, and The Swedish Foundation for Strategic Research – Innate Immunity, and The Mucosal Immunobiology and Vaccine Center (MIVAC). References 1. Garcia, M. A., Yang, N., and Quinton, P. M. (2009) Normal mouse intestinal mucus release requires cystic fibrosis transmembrane regulator dependent bicarbonate secretion. J Clin Invest 119, 2613–2622. 2. Caramori, G., DiGregorio, C., Carlstedt, I., Casolari, P., Guzzinati, I., Adcock, I. M., et al. (2004) Mucin expression in peripheral airways of patients with chronic obstructive pulmonary disease. Histopathology 45, 477–484. 3. Larsson, J. M., Karlsson, H., Sjövall, H., and Hansson, G. C. (2009) A complex, but uniform O-glycosylation of the human MUC2 mucin from colonic biopsies analyzed by nanoLC/MSn . Glycobiology 19, 756–766. 4. Schulz, B. L., Packer, N. H., and Karlsson, N. G. (2002) Small-scale analysis of O-linked oligosaccharides from glycoproteins and mucins separated by gel electrophoresis. Anal Chem 74, 6088–6097. 5. Thomsson, K. A., Schulz, B. J., Packer, N., and Karlsson, N. G. (2005) MUC5B glycosylation in human saliva reflects blood group and secretor status. Glycobiology 15, 791–804. 6. Schroeder, J. A., Thompson, M. C., Gardner, M., and Gendler, S. J. (2001) Transgenic

7.

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MUC1 interacts with epidermal growth factor receptor and correlates with mitogenactivated protein kinase activation in the mouse mammary gland. J Biol Chem 276, 13057–13064. Godl, K., Johansson, M. E. V., Karlsson, H., Morgelin, M., Lidell, M. E., Olson, F. J., et al. (2002) The Ntermini of the MUC2 mucin form trimers that are held together within a trypsinresistant core fragment. J Biol Chem 277, 47248–47256. Lidell, M. E., Bara, J., and Hansson, G. C. (2008) Mapping of the 45M1 epitope to the C-terminal cysteine-rich part of the human MUC5AC mucin. FEBS J 275, 481–489. Thornton, D. J., Gray, T., Nettesheim, P., Howard, M., Koo, J. S., and Sheehan, J. K. (2000) Characterization of mucins from cultured normal human tracheobronchial epithelial cells. Am J Physiol 278, L1118–L1128. Bast, R. C., Feeney, M., Lazarus, H., Nadler, L. M., Colvin, R. B., and Knapp, R. C. (1981) Reactivity of a monoclonal antibody with human ovarian carcinoma. J Clin Invest 68, 1331–1337.

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Chapter 9 Methods to Classify Bacterial Pathogens in Cystic Fibrosis Thomas Bjarnsholt, Xiaohui Chen Nielsen, Ulla Johansen, Lena Nørgaard, and Niels Høiby Abstract Many bacteria can be detected in CF sputum, pathogenic and commensal. Modified Koch’s criteria for identification of established and emerging CF pathogens are therefore described. Methods are described to isolate bacteria and to detect bacterial biofilms in sputum or lung tissue from CF patients by means of conventional culturing and staining techniques and by the PNA FISH technique. Additionally, the confocal scanning laser microscopy technique is described for studying biofilms in vitro in a flow cell system. The recA-gene PCR and the RFLP-based identification methods are described for identification of isolates from the Burkholderia complex to the species level. DNA typing by PFGE, which can be used for any bacterial pathogen, is described as it is employed for Pseudomonas aeruginosa. A commercially available ELISA method is described for measuring IgG antibodies against P. aeruginosa in CF patients. Key words: Biofilm, Koch’s criteria, Pseudomonas aeruginosa, Burkholderia, FISH, Pseudomonas antibodies, pulsed field gel electrophoresis, confocal scanning laser microscopy, recA-gene PCR, microbiology.

1. Introduction The lower respiratory tract of normal persons and CF patients does not harbor a normal microbiological flora. On the other hand, aspiration of secretion from the pharynx occurs during, e.g., sleep, and exposure to aerosols also leads to repeated daily exposure of the defense system of the lungs to microbes carried by droplets, droplet nuclei, and minor solid particles (1). Due to the basic defect in CF which implies reduced volume of the periciliary fluid of the respiratory mucosa, the non-inflammatory mucociliary clearance of inhaled microorganisms is impaired, and the patients therefore have to recruit the inflammatory defense M.D. Amaral, K. Kunzelmann (eds.), Cystic Fibrosis, Methods in Molecular Biology 742, DOI 10.1007/978-1-61779-120-8_9, © Springer Science+Business Media, LLC 2011

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mechanisms which may imply inflammation (2, 3). When respiratory secretion is obtained for routine detection of supposed CF pathogens, such secretions are nearly always contaminated by microbes from the pharynx and mouth, where aerobic, facultative, and anaerobic bacteria are part of the normal flora (4, 5). Actually, any mouth contains at least 100–200 different bacterial species (not all can be cultured) and the number of bacterial cells is approximately 108 /ml saliva. Well-established CF pathogens such as Staphylococcus aureus, Haemophilus influenzae, Streptococcus pneumoniae, and Moraxella catarrhalis may be members of the normal flora (4). Other CF pathogens such as Pseudomonas aeruginosa, Burkholderia cepacia complex, Stenotrophomonas maltophilia, Achromobacter xylosoxidans, and MOTT are not members of the normal human flora but are environmental bacteria which may occur in water (including tap water), soil, and even food (6). The fungus Aspergillus fumigatus (7) is also an environmental microorganism which is found in humid niches in buildings, e.g., bathrooms, kitchens, and air ventilation tubes. The major problem is therefore not to detect microbes in the respiratory secretions from CF patients but to identify whether the detected microbes originate from the lower respiratory tract and whether they are causing any damage (pathogens) or rather are innocent bystanders which only contaminate the secretions (sputum) from the lower respiratory tract on its way through the major bronchi. This is of clinical importance, since sputum is a waste product located outside the body’s mucosa – like stools – but it may contain pathogens which are also present in the lower respiratory tract – the respiratory zone of the lungs – and contribute to the pathogenesis of the tissue damage in the lungs of the CF patient. It is therefore important to identify the characteristic features of those microorganisms which play a role in the pathogenesis of the lung pathology of CF patients. It is also important to realize that sputum of CF patients is anaerobic and anaerobic bacteria may play a role during exacerbations of the CF lung symptoms (8–10). 1.1. What Is a CF Pathogen?

In the golden era of bacteriology 130 years ago where many of the major and specific pathogens were detected, confusion of pathogens and contaminants was common but the famous postulates of Koch-Henle (11) were very helpful in the identification of the etiology of “specific” infectious diseases like tuberculosis: (1) The organism must be present in every case of the disease in question and under circumstances which can account for the pathological changes and clinical course of the disease. (2) The organism occurs in no other disease as a fortuitous and non-pathogenic parasite. (3) After being fully isolated from the body and repeatedly grown in pure culture it can induce the disease anew.

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Obviously these postulates did not work on “non-specific” infectious diseases like pneumonia, where several microbes may give rather similar symptoms and pathology. The postulates have therefore subsequently been modified (12): (1) Epidemiology: The organism should be detected more frequently and/or in larger numbers from patients with disease than in those without; (2) Antibody: an antibody response measured by any of several available techniques, should be demonstrated in the infected host; (3) Response to treatment: Clinical and microbiological cure after treatment with an antimicrobial agent to which the organism is susceptible in vitro; (4) Transmissibility: The organism should infect an animal host from which they can be recovered and, in so doing, produce disease similar to that seen in man. Based on lessons learned from P. aeruginosa in CF, further modifications of the postulates are necessary to identify criteria which should be fulfilled before isolated microbes are considered CF pathogens (6): (1) Correct species identification of suspected pathogens – every time it is isolated from the patient. Chronic infections may not be diagnosed if the microbe’s name is changing from time to time in the same or different laboratories (e.g., Gramnegative rods → P. aeruginosa → non-fermenter). Even change of taxonomic classification may give rise to such diagnostic errors (e.g., Pseudomonas maltophilia → Xanthomonas maltophilia → S. maltophilia) in a patient who actually fulfilled the criteria of chronic infection by culture (continuous presence of the bacteria for ≥6 months based on monthly visits or >50% positive cultures during 1 year based on visits every 3 months) and/or increased antibody response (13–16). Furthermore, phenotypic variations of colony morphology are common in CF, so each phenotype should be identified and its antibiotic susceptibility should be examined (e.g., mucoid, non-mucoid, and small colony variants of P. aeruginosa; Fig. 9.1) (2). Are the identified microbes causing inflammation in the CF airways and decrease of pulmonary function and eventually lung transplantation or death, or is it an innocent bystander to another established CF pathogen which is also present, e.g., S. aureus? (3) Are there any clinical and bacteriological effects of antibiotic therapy to which the organism is susceptible in vitro or is it an innocent bystander to another established CF pathogen, e.g., S. aureus, which is also present and also susceptible to the antibiotic therapy? It is, however, important to realize that biofilm-growing bacteria such as mucoid P. aeruginosa are generally not eradicated by antibiotic therapy, although their number may decrease for a period of time. In spite of that, a clinical response to antibiotic therapy is regularly seen (4). Epidemiology: Is there any spread of the microorganism to other CF patients as determined by genotyping of the isolates? (5) Antibody response: chronic infections in CF are characterized by a pronounced and diagnostic important

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Fig. 9.1. Culture (72 h, 37◦ C, modified Conradi–Drigalski medium) selective for Gramnegative rods (blue plates) of sputum from a CF patient with chronic P. aeruginosa lung infection. Top arrow: Mucoid phenotype (alginate producing), middle arrow: non-mucoid phenotype, bottom arrow: small colony variant. All three phenotypes had the same PFGE DNA type = the same clone.

antibody response but cross-reactive antibodies are found in CF, so the specificity of the antibody response may be questioned and absorbance experiments carried out (16) (6). Although the microbes may possess recognized virulence factors and toxins, they may not play a role during chronic infection because of induction of neutralizing antibodies (17). Actually during chronic infections, especially if biofilm-growing bacteria (e.g., P. aeruginosa) are involved, immune complex-mediated inflammation dominates the pathology of the lung tissue damage (18). 1.2. Isolation and Identification of Pathogenic Bacteria from the CF Lung 1.2.1. Microscopy of Gram-Stained Specimens

Sputum can be obtained by coughing or, in non-sputum producers, by deep throat culture, endolaryngeal suction, and bronchoscopic lavage (4). Obviously, bronchoscopy is not suitable for routine screening purpose, although the risks are small (19). Results obtained by that method and deep throat culture simultaneously indicate that the predictive values of throat cultures positive for S. aureus or P. aeruginosa were 91 and 83%, respectively, whereas the negative predictive values were 80 and 70%, respectively (4). In the Danish CF Centre in Copenhagen, tra-

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cheal secretion is obtained by endolaryngeal suction and the bacteriological examination of the secretion comprises microscopy and culture of the secretion. Gram-stained films of the specimens are examined by microscopy and the bacterial flora associated with areas consisting of respiratory epithelial cells and polymorphonuclear leukocytes and mucus but without squamous epithelial cells is described, whereas the flora associated with oral epithelial cells is considered to be predominantly of oral or pharyngeal origin, and not described (4). Based upon these criteria, 85% of the culture-positive samples (P. aeruginosa 91%, S. aureus 81%, H. influenzae 87%, and S. pneumoniae 85%) were in accordance with the results obtained by microscopy (4). A presumptive bacteriological diagnosis can frequently be obtained by the microscopic examinations (Fig. 9.2) as a guideline for urgent chemotherapy if this is indicated, but in most cases the chemotherapy can be withheld until the results of the culture are obtained. Indication for antimicrobial chemotherapy includes that the bacteria in question have been cultured as well as found by microscopy according to the principles described above, since microscopy of Gram-stained smears is the best routine method to distinguish between oral contaminants and microbes present in secretions from the lower respiratory tract (4). 1.2.2. Media and Culture Conditions

The media used for culturing the bacteria from CF sputum include the following (1): enriched standard media, since auxotrophic mutants requiring specific amino acids as growth factors are common in CF (4), e.g., chocolate agar and horse or sheep blood agar; (2) selective media from Gram-negative enteric and non-fermentative bacteria (Enterobacteriaceae, Pseudomonas species, Achromobacter species, S. maltophilia); (3) selective media (mannitol salt agar) containing 7.5% NaCl for S. aureus (20); furthermore, for detection of methicillin-resistant S. aureus (MRSA), several chromogenic media are on the market such as MRSA ID (BioMerieux, France) (21). When distinct green colonies (MRSA) are grown, then the mecA gene can be detected by PCR or DNA hybridization techniques using, e.g., mecA EVIGENETM (AdvanDx, MA, USA) (22). (4) Selective media containing colistin for Burkholderia species (4, 6). (5) In some centers also selective media for H. influenzae, Sabouraud agar for fungi (e.g., A. fumigatus), and Löwenstein–Jensen medium for mycobacteria other than tuberculosis (MOTT), but decontamination of the secretion with 0.25% N-acetyl-L-cystein and 1% NaOH followed by 5% oxalic acid is necessary to detect the mycobacteria in the presence of, for example, P. aeruginosa (4, 6). In the Danish CF Centre in Copenhagen, a blood agar plate for primary sensitivity testing with antibiotics (tablets or disks) active to P. aeruginosa (colistin, tobramycin, piperacillin+tazobactam, ceftazidime, aztreonam, meropenem, and ciprofloxacin) is also

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Fig. 9.2. Gram-stained smears from three CF patients with chronic P. aeruginosa (all had mucoid phenotypes) lung infection. The red arrows show biofilms of P. aeruginosa and the black arrows show polymorphonuclear leukocytes. Notice the great diversity of the appearance of the biofilms. Magnification 1000×.

used to detect minority populations of resistant mutants in the presence of a majority of susceptible phenotypes. Incubation takes place for 72–96 h at 37◦ C (6 weeks for mycobacteria, but frequently MOTT isolated from CF patients are rapid growing (Mycobacterium chelonei, Mycobacterium fortuitum) and colonies are detected within 1 week). The chocolate agar medium is incubated in 5% CO2 atmosphere. Anaerobic culture is generally not

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useful unless quantitative cultures are used or if the secretion is obtained by bronchial alveolar lavage, since heavy growth of the normal anaerobic flora from the mouth. The isolated bacteria are then identified to the species level using standard biochemical tests and secondary sensitivity testing to relevant antibiotics is carried out. The phenotypic appearance of the colonies (e.g., mucoid and non-mucoid and small colony variants of P. aeruginosa; Fig. 9.1) is described in the report from the laboratory and the antibiotic susceptibility of each phenotypic variant is determined. It is important to realize that notably P. aeruginosa phenotypes change during the chronic lung infection, leading to changed LPS (rough or semi-rough), small colony variants, auxotrophy, loss of pigment or changed pigment production, slow growth, and changed phenotypic colony morphology (Fig. 9.1) (e.g., mucoid colonies) (4, 6, 23, 24). The identification of such phenotypic variants may therefore be difficult leading to misclassification (25, 26). Classical biochemical tests not included in the commercial identification panels may therefore often be necessary to employ for identification of the species. Newer methods based on the profile of proteins of the bacteria detected directly from an intact bacterial cell surface by matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF) (27) or sequencing of the 16S rDNA gene may therefore be indicated in uncertain cases (28). In order to investigate suspected epidemiologically related isolates, genotyping by, e.g., PFGE or other DNA-based typing methods is necessary (29). Chronic infection of P. aeruginosa or other pathogens is defined by the Copenhagen criteria (4) or by Leed’s criteria (15) but requires 6–12 months observation time. However, detection of a significant rise of specific anti-Pseudomonas IgG antibodies shows about 90% predictive value of a positive test and 90% predictive value of a negative test ability to detect chronic infection with these bacteria (16). 1.3. Identification of Pathogenic Bacteria from the CF Lung – Molecular Biology Methods vs. Conventional Methods

For chronic infections, it can be very problematic to isolate pathogenic bacteria. An exception is actually CF in which the easily accessible purulent sputum coughed up by the patients on a regular basis harbors the bacteria. The next problem which also applies for CF is the identification of the bacteria present. In the clinical microbiology laboratory, many techniques and procedures are available for identifying the bacteria such as microscopy, culture, PCR, and sequencing of 16S rRNA gene. Each method has its advantages and disadvantages. For culturing, the problem is to collect and grow the offending pathogen. Since sputum is coughed up through the trachea and oral cavity, oral bacteria might be abundantly present as well. Also the bacteria of the chronic CF lung infections may have very slow growth rate (30) in vivo and

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in vitro. Due to these possible contaminations, one has to analyze cultures of CF sputum very carefully. On the other hand, if bacteria are cultured, both identification and susceptibility to antibiotics can be done. The usage of molecular techniques such as PCR will detect even tiny amounts of DNA or RNA available in the sample (31). Here again contamination of the oral flora has to be avoided. The second problem is to avoid eliminating the minor fraction of prokaryotic DNA/RNA by the eukaryotic DNA/RNA, which might either interfere with the PCR reaction (fairly easy to solve) or outcompete the capacity for DNA/RNA extraction. Another problem with PCR is that every DNA/RNA fragment homologous to the primers will be detected, including defragmented DNA/RNA, which may generate false positives. Additionally, just because a bacterium is present does not necessarily indicate that it contributes to the pathogenesis of the infection (see above), so it might not need to be treated. The final problem which may be the biggest challenge in the coming years for biofilm infections in CF patients is to reveal the significance of the numerous microorganisms detected by molecular techniques (see above). 1.4. Visualization of Bacteria in Sputum and Lung Tissue

Chronic bacterial infections are caused by the ability of bacteria to organize themselves in micro-colonies, also called biofilms (3, 32–36). In this state, the bacteria are imbedded in a self-produced protective matrix, often with surrounding inflammatory cells (36, 37). Bacteria living in biofilms are very well protected against antibiotics and the host defense. Due to this, it is a necessity to consider whether the isolated and identified pathogenic bacteria were as single, planktonic cells, which are easy to treat, or as difficult-to-treat biofilms, which is the problem in CF and other chronic infections. Microscopy enables direct visualization of the infecting bacteria (Fig. 9.2), but in case of the presence of several similar looking bacteria (Gram-negative rods), identification of the bacteria in, e.g., a biofilm in sputum is not always possible. This can be done using fluorescent antibody probes (3, 8) or DNA probes for FISH (3), see later.

1.5. In Vitro Study of Biofilms

The developmental processes of biofilms have been thoroughly studied in surface-based in vitro systems and are relevant for studies on CF pathology and microbiology (3). The most studied bacterium in this context is P. aeruginosa. The ability of P. aeruginosa to form biofilms is thought to be one of its main survival strategies in an infectious process and is considered an important pathogenicity trait. The in vitro-formed biofilm consists of micro-colonies encapsulated by exopolysaccharide (EPS) produced by the bacteria

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itself, though most of the biofilms are made up of water channels which are thought to operate as a distribution system of nutrients and oxygen. An oxygen gradient is present from the surface decreasing downward to the substratum (8, 38). Pseudomonas aeruginosa forms biofilms on almost any surface and any condition, both nutritional and environmental. From time to time, it is stated that biofilm formation, from planktonic to sessile mode of growth, is a complex and highly regulated process (39). This slight variation in biofilm structure by the same strain of P. aeruginosa indicates that biofilm formation, and the successive growth and development, is a complex but somewhat arbitrary process. It has also been suggested that biofilm formation is dependent on the expression of a specific biofilm program (40). However, based on all the in vivo observations present today, it is more likely that biofilm formation proceeds through a series of temporal events that probably reflect adaptation to nutritional and environmental conditions (41–43). The in vitro, surface-based, biofilm developmental process can be divided into different stages: (i) attachment, (ii) maturation, and (iii) dispersion, as indicated by Sauer et al. (44) and Klausen et al. (45).

2. Materials 2.1. Biofilm Detection in Sputum and Tissue (3, 4, 46) 2.1.1. Gram Stain

2.1.2. PNA FISH of Tissue and Sputum

Material for investigation has to be either (a) fresh sputum or (b) section of lung tissue and the following: 1. Microscope slides. 2. Gram stains (crystal violet for staining, Lugol’s iodine as mordant, 99% ethanol for decolorizing, and basic carbol fuchsin for counterstaining) (20). 1. Material for investigation has to be either (a) fresh sputum or (b) sections of lung tissue: a. For paraffin-embedded tissue sections: i. Xylene. ii. 99.9% ethanol. iii. 96% ethanol. iv. Sterile water. 2. Microscope slides for fluorescence microscopy. 3. Cover slips, thickness 0.15 mm. 4. Staining dish with slide holder. 5. Heating block (55◦ C).

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6. Water bath (55◦ C). 7. PNA FISH probes (AdvanDx, MA, USA). 8. 60× wash solution (AdvanDx, MA, USA). 9. Vectashield mounting medium with DAPI (Vector Laboratories, Burlingame, CA, USA). 10. Fluorescence microscope equipped with a 60–100× oil objective, camera for fluorescence, and the correct filters for the probes to be used. 11. Immersion oil. 2.2. In Vitro Flow Cell Biofilm

1. Bacterial strains: The investigated bacteria have to express a fluorescent protein (like GFP) by genetic manipulation or staining with a DNA stain. 2. AB trace minimal growth medium: Add 1 mM MgCl2 , 0.1 mM CaCl2 , and 100 μL/L trace metals (see description later) to water and sterilize the solution by autoclaving. Thereafter add 10% A10 (see description later). Media should be heated to 37◦ C before use. 3. Trace metal solution: 200 mg/L CaSO4 ·2H2 O, 200 mg/L FeSO4 ·7H2 O, MnSO4 ·H2 O, 20 mg/L CuSO4 ·5H2 O, 20 mg/L ZnSO4 ·7H2 O, 10 mg/L CoSO4 ·7H2 O, 12 mg/L Na2 MoO4 ·H2 O, and 5 mg/L H3 BO3 . Can be stored at room temperature for several months. Remember to mix before use. 4. A10: Add 20 g (NH4 )2 SO4 , 60 g Na2 HPO4 , 30 g KH2 PO4 , and 30 g NaCl to 1 L water. Adjust pH to 6.4 and sterilize solution by autoclaving. Store at 4◦ C. 5. Glucose. Use 0.3 mM. 6. BactoTM casamino acid. 7. 16-Channel Watson Marlow 205S peristaltic pump. 8. Equipment to assemble the system: 8.1. A: Silicon tube, internal diameter: 2 mm, external diameter: 4 mm (Ole Dich, Denmark). 8.2. B: Silicon tube, internal diameter: 1 mm, external diameter: 3 mm (Ole Dich, Denmark). 8.3. 1: Straight connectors 1/8 in. (Buch & Holm, Denmark). 8.4. 2: T-connectors 1/8 in. (Buch & Holm, Denmark). 8.5. 3: Reducing connectors 1/8 in. × 1/16 in. (Buch & Holm, Denmark). 8.6. 4: Barrel tip cap orange (Diatom, 5113-XM). 9. Silicone to assemble the flow chamber to the cover slip.

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10. Surface-attached mono species biofilms are cultivated in flow chambers with channel dimensions of 1 mm × 4 mm × 40 mm. 11. The substratum consists of a microscope cover slip (24 mm × 50 mm). 12. For sterilization of biofilm system: Use sodium hypochlorite (NaClO) solution (13%), bleach, and dilute it in water to 0.5% (Note 1). 2.2.1. Confocal Scanning Laser Microscopy

2.3. recA-Gene PCR and RFLP-Based Identification Approach for B. cepacia Complex

Image acquisitions of biofilms are performed using a confocal scanning laser microscope (CSLM) such as Leica SP5 (Leica Lasertechnik, GmbH, Heidelberg, Germany) equipped with a detector and a filter set for monitoring GFP and propidium iodide (PI). In addition, a reflection detector for acquiring bright-field images is installed. Images should be obtained using a 40–100× oil objective. Image scanning is carried out with the 488-nm laser line from an Ar/Kr laser. Imaris software package (Bitplane, AG) can be used to generate pictures of the biofilm. 1. MagNa Pure LC DNA Isolation Kit III (Bacteria, Fungi) (Roche). 2. dNTP (10 mM; Qiagen Laboratories, Inc.). 3. PCR buffer, 10× (Qiagen Laboratories, Inc.). 4. Q-solution, 5× (Qiagen Laboratories, Inc.). 5. Taq polymerase (Qiagen Laboratories, Inc.). 6. Sterile distilled water. 7. Primers for B. cepacia complex-specific PCR: BCR 1: 5 -TGA CCG CCG AGA AGA GCA A-3 (50 μM; DNA Technology, Aarhus, Denmark). BCR 2: 5 -CTC TTC TTC GTC CAT CGC CTC-3 (50 μM; DNA Technology, Aarhus, Denmark). 8. Primers for Burkholderia multivorans-specific PCR: BCRBM 1: 5 -CGG CGT CAA CGT GCG GGA T-3 (50 μM; DNA Technology, Aarhus, Denmark). BCRBM 2: 5 -TCC ATC GCC TCG GCT TCG T-3 (50 μM; DNA Technology, Aarhus, Denmark). 9. PCR mastermix (per sample): 1.25 μl dNTP, 2.0 μl primer 1, 2.0 μl primer 2, 5.0 μl 10× PCR buffer, 10.0 μl 5× Q-solution, 0.5 μl Taq polymerase, 19.25 μl sterile distilled water. 10. Agarose (Sigma A-4010 low gelling). 11. HaeIII restriction enzyme (10 units/μl; New England Biolabs, Inc., MA, USA).

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12. TBE buffer 10× conc. (27 mM Tris base, 27 mM boric acid, 0.75 mM EDTA, pH 8.5). 13. Ethidium bromide (AMRESCO, Inc., Cleveland, OH, USA). 14. Loading buffer: TE EC-1028 (orange sample buffer; EmpiTec, CA, USA). 15. Molecular marker (DNA 100-bp ladder, N3231S) (New England Biolabs, Inc., MA, USA). 16. Molecular marker (DNA 50-bp ladder N3236S) (New England Biolabs, Inc., MA, USA). 17. Criterion TBE ready polyacrylamide gel 10% (Bio-Rad, CA, USA). 2.3.1. Instruments

1. MagNa Pure LC (Roche, Switzerland). 2. FlexCycler (AH Diagnostics). 3. Bio-Rad PowerPac Basic and Criterion Cell. 4. Agarose electrophoresis apparatus Power Pack Base (BioRad, CA, USA). 5. Gel Doc (Bio-Rad, CA, USA). 6. Galaxy minister centrifuge (VWR Instruments, Korea).

2.4. DNA Typing by Pulsed Field Gel Electrophoresis (PFGE) for Typing of P. aeruginosa or Other Species (29, 50)

1. SE buffer (75 mM NaCl, 25 mM EDTA, pH 7.4). 2. Agarose (Sigma A-4010 low gelling). R Gold agarose (BioWhittaker Molecular Applica3. SeaKem tions, Inc., Rockland, ME, USA).

4. ES buffer (1% (w/v) N-lauroylsarcosine, 0.5 M EDTA, pH 9.5). 5. Proteinase K (AMRESCO, Inc., Solon, OH, USA). 6. Spe1 restriction enzyme (New England Biolabs, Inc., MA, USA). 7. Bovine serum albumin (Sigma A 7030 albumin). 8. Tris–borate buffer (27 mM Tris base, 27 mM boric acid, 0.75 mM EDTA, pH 8.5). 9. TE buffer with bovine serum albumin (BSA) (50 mM potassium acetate + 20 mM Tris–acetate + 10 mM magnesium acetate + 1 mM DTT, pH 7.9 + 2.5 mg BSA/ml). 10. Thiourea (thiocarbamide, 99%; Bie & Bernsen, Denmark). 11. Ethidium bromide (AMRESCO, Inc., Cleveland, OH, USA). 12. TRE buffer (10 mM Tris base + 10 mM EDTA, pH 7.4).

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13. NEBuffer 4 (50 mM potassium acetate + 20 mM Tris– acetate + 10 mM magnesium acetate + 1 mM DTT, pH 7.9; BioLabs, MA, USA). 2.5. ELISA for Measuring IgG and IgA Antibodies Against Bacterial Sonicate (16, 53)

Pseudomonas-CF-IgG ELISA kit (Statens Serum Institute, Copenhagen, Denmark) contains the following: 1 MaxiSorp R ), 9 mg lyophilized antigen (sonication of ELISA plate (NUNC P. aeruginosa serotypes O-1 through O-17), 1 vial pooled human standard antiserum (antibodies against P. aeruginosa), 0.5 ml sterile distilled water, 12 ml coating buffer, 250 ml washing buffer, 250 ml dilution buffer, 0.1 ml rabbit–anti-human IgG HPR, 12 ml sulfuric acid (2 M), 12 ml TMP plus standard, and ELISA reader set at 450 nm.

3. Methods 3.1. Gram Stain 3.1.1. Sputum

1. A thin smear is produced by gently spreading purulent sputum on top of the microscope slide by a loop and is left for air-drying. 2. The slide with the dried smear is then gently heat fixated. 3. Gram staining is performed according to the routine of the laboratory. 4. Using immersion oil and 1000× magnification, aggregated bacterial cells which appear to be surrounded by a self-produced matrix are searched. There is a great variation in the size and shape of biofilms and the specimen has to be examined for 5–10 min in order to detect possible biofilms. Mucoid P. aeruginosa regularly produce detectable biofilms in sputum which resemble smears of mucoid colonies from solid media (23). Biofilms of A. xylosoxidans, B. cepacia complex, and S. maltophilia can also be detected, but such biofilms appear more condensed compared to biofilms of mucoid P. aeruginosa (46). Non-mucoid P. aeruginosa do not appear to produce biofilm in vivo in CF (3).

3.2. PNA FISH of Tissue and Sputum 3.2.1. Sputum 3.2.1.1. Tissue Sections

1. A thin and uniform smear, of the freshly isolated sputum, is made on a microscope slide (intended for fluorescence). 2. The material is heat fixated. Before hybridization of paraffin-embedded tissue, paraffin has to be removed from the tissue sections.

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De-paraffinization protocol 1. Immerse slides in xylene (2 × 5 min). 2. Immerse slides in 99.9% ethanol (2 × 3 min). 3. Immerse slides in 96% ethanol (2 × 3 min). 4. Immerse slides in water (3 × 3 min). 5. Air-dry. Slides are stable for months at RT. 3.2.2. PNA FISH

The de-paraffinized tissue sections and the sputum smears were analyzed by fluorescence in situ hybridization (FISH) using peptide nucleic acid (PNA) probes. In a recent study, we used a mixture of Texas Red-labeled, P. aeruginosa-specific PNA probe and fluorescein-labeled, universal bacterium PNA probe (AdvanDx, MA, USA) (3). 1. The probe of choice is added to each section or sputum smear. 2. A cover slip is placed on top of the material; a pencil is used gently to spread the probe under the slide and to remove bubbles. 3. The microscope slide is placed on a heating block for hybridization at 55◦ C for 90 min covered by a lid. 4. The slides are washed for 30 min at 55◦ C in wash solution (AdvanDx). 5. Vectashield mounting media with 4 ,6-diamidino-2phenylindole (DAPI) (Vector Laboratories, Burlingame, CA) are applied, and a cover slip is added to each slide; a pencil is used gently to spread the probe under the slide and to remove bubbles. 6. Slides are inspected using a fluorescence microscope equipped with a camera and appropriate filters like a fluorescein isothiocyanate (FITC), a Texas Red, a DAPI, a dual FITC/Texas Red, and a dual DAPI/Texas Red filter (Fig. 9.3) (3) (Note 2).

3.3. In Vitro Flow Cell Biofilm

Using an in vitro continuous culture flow cell system (47) enables continuous non-invasive investigation of biofilm development. This biofilm flow cell system is perfect for visual inspection of formation, disruption, and killing of biofilms using a CSLM. The biofilm is monitored using either fluorescent-tagged bacterial cells or a DNA stain such as Syto9. The killing of the bacteria is monitored using PI which will stain the DNA of cells with impaired membrane, i.e., dead cells. PI fluoresces red which is why another color such as green is needed for the live bacteria.

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Fig. 9.3. Pseudomonas aeruginosa biofilms surrounded by PMNs visualized by PNA FISH and DAPI, located intraluminally in the conductive zone of the lung of a CF patient.

1. Assemble the flow cells for minimum 24 h prior to use by gluing (use silicone) a 24 mm × 50 mm glass cover slip onto the top of the flow cell (see Fig. 9.4B). 2. Assemble the rest of the system as shown in Fig. 9.4A. 3. The following description is based on a 16-channel pump from Watson Marlow (205S). Sterilize the whole system using 1 L of 0.5% NaClO solution in sterilized Milli-Q water. Set the pump at 90 rpm to fill the whole system. When the bobble traps are filled, put on the caps and set the pump at 12 rpm. Sterilize for approximately 2 h. Make sure that nothing is leaking, otherwise use silicone to stop it. Remember to wear gloves and glasses when working with NaClO. 4. Drain the system for liquid setting the pump at 90 rpm. 5. Wash the system two times with 1 L of sterilized water in the same way as with the NaClO. Set the pump at 5– 50 rpm when the system is filled. Empty the system after one 1 L and fill up again with the new flask (see Note 3). 6. After the last wash, drain the system and fill with AB trace minimal medium. Place the system at 37◦ C overnight (see Note 3). 7. Make an overnight culture of the bacteria to be investigated.

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Fig. 9.4. A: In vitro continuous culture biofilm flow cell system setup. The numbers and letters refer to the designation in the material section of the different connectors and tubes. B: Three-channel flow cell, in which the biofilms are cultivated. Confocal scanning laser microscopy.

8. Before inoculation with the overnight culture, stop the flow and clamp off the tubes between the flow channels and the bubble traps. 9. Inoculate the flow chambers using 250 μL of the overnight culture diluted to an OD600 of 0.001–0.1 in 0.9% NaCl. Inject the diluted culture in the flow channels by using a syringe needle which is inserted into the tubing next to the flow channel inlet. Close the injection hole with a thin layer of silicone. 10. Arrest the medium flow for 30–60 min to allow efficient bacterial attachment to the glass surface. Turn the flow cell upside down placing it on the glass surface. 11. Turn the flow cells again so that the glass slides are facing up. Remove the clamps and start the medium flow. The medium should be pumped at a constant rate of 1.75 rpm for a 16-channel pump and 2.00 rpm for a 12-channel pump which corresponds to approximately 3.3 ml/h using the peristaltic pumps from Watson Marlow (205S). 12. Let the biofilm develop. We allow the biofilm to develop and mature in the flow chambers for 3–4 days for antibiotic tolerance investigations.

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13. At the day of treatment, the growth medium is changed to fresh growth medium containing antibiotics or other relevant substance. The medium is changed by (1) stopping the flow (2); clamping of the tube between the flow cells and bubble traps (3); emptying the bubble traps by pulling the syringe off and quickly again (4); removing the barrel tip cap and filling the bubble traps with the new growth medium containing antibiotics, e.g., at 90 rpm (5); stopping the system when the bubble traps are filled up and removing the clamps; and (6) starting the system again at 1.75 rpm. 14. Investigate the biofilm approximately at any given time point relevant to the treatment. 15. For examination of the biofilm with CSLM, a viability staining kit is used: If a non-GFP-tagged P. aeruginosa strain is used, LIVE/DEAD viability staining kit can be applied (Fig. 9.5). Syto 9 (Invitrogen, cat. no. S-34854) and PI (Sigma, P-4170) are added at a concentration of 0.005 and 0.01 mM, respectively, 15 min before examination of the flow cells by injecting it in the same way as the bacterial culture explained in Section 9–10 (DNA stains are often light sensitive, which is why the system should be shielded from light – see Note 4). 16. If a GFP-tagged P. aeruginosa strain is used, only PI is added to the flow chambers. 3.4. recA-Gene PCR and RFLP-Based Identification Approach for B. cepacia Complex

The B. cepacia complex is a very diverse group of bacteria. RecA gene has proven to be useful for the identification of B. cepacia complex species (26, 48). The method described includes three steps: Step 1. PCR amplification of B. cepacia complex recA gene. By applying primers (BCR1 and BCR2) that are specific for B. cepacia complex, a single 1,043-bp amplicon will be generated from all strains representative of the B. cepacia complex. Step 2. Burkholderia multivorans species-specific PCR. By applying primers (BCRBM1 and BCRBM2) that are specific for the species B. multivorans, a single 714-bp amplicon will be generated for strains representative of the species B. multivorans. Step 3. Restriction fragment length polymorphism (RFLP) analysis of the B. cepacia complex recA-gene PCR product. The recA-gene PCR product from step 1 is subjected to digestion with restriction enzyme HaeIII. The generated RFLP profile is going to be compared with the unique profiles generated from reference strains representative of the different species in the B. cepacia complex (49).

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A

B

C

D

Fig. 9.5. Images of 3-day-old P. aeruginosa biofilms grown in flow chambers. Biofilm shown in (a) and (b) are nontreated biofilms. In pictures (c) and (d), biofilms have been treated with tobramycin for 24 h. Live bacterial cells appear green and dead cells appear red.

3.4.1. DNA Extraction

1. One to two colonies of the B. cepacia complex-like bacteria are harvested from an overnight culture on a routine solid medium and thoroughly suspended in 1 ml sterile distilled water. 2. Bacterial suspension (100 μl) is mixed with 130 μl bacteria lysis buffer and 20 μl proteinase K (from the MagNa Pure LC DNA Isolation Kit III) and incubated at 65◦ C for 10 min. The mixture is then incubated at 95◦ C for 10 min to inactivate the proteinase K, followed by cooling for 5 min. 3. The sample is then quick-spin centrifuged for a few seconds. Two hundred and fifty microliters of the supernatant

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is transferred to a well in the sample tray in the MagNa Pure LC machine and the DNA extraction process is started. When the process is finished, the purified DNA product is ready for PCR amplification. 3.4.2. PCR Reaction

1. Purified DNA (10 μl) is mixed with 40 μl PCR mastermix in a microcentrifuge tube. 2. The PCR amplification is carried out using a Flex-Cycler with the following program: a. B. cepacia complex: 94◦ C for 2 min, then 30 cycles of 94◦ C for 30 s, 58◦ C for 45 s, 72◦ C for 60 s, 72◦ C for 10 min. b. B. multivorans: 94◦ C for 2 min, then 30 cycles of 94◦ C for 30 s, 62◦ C for 45 s, 72◦ C for 60 s), 72◦ C for 10 min.

3.4.3. Agarose Gel Electrophoresis

1. PCR product (8 μl) and 2 μl TE EC-1028 (orange) are mixed and the 10 μl mixture is transferred to the application wells in the 3% agarose gel. A molecular marker (100-bp DNA ladder) is also applied. 2. Electrophoretic migration of the PCR product is carried out at 100 V for 45–60 min using TBE buffer containing ethidium bromide. 3. The results are documented by photos using Gel Doc hardware and software (Fig. 9.6, top and middle).

3.4.4. RFLP Analysis

1. PCR product (10 μl) is mixed with 10 μl restriction enzyme mastermix (2 μl NEB2, 0.5 μl HaeIII enzyme, and 7.5 μl distilled water) and incubated at 37◦ C overnight. The restriction enzyme reaction is then stopped with 2 μl EDTA. 2. Cleaved PCR product (10 μl) and 2 μl TE EC-1028 (orange) are mixed and then transferred to the application wells in 10% TBE polyacrylamide gel. A molecular marker (50-bp DNA ladder) is applied in-between every four samples. 3. The electrophoretic separation is carried out at 200 V for 45 min in 1× TBE buffer. 4. After electrophoresis, the polyacrylamide gel is stained in 0.035% ethidium bromide solution for 15–30 min and afterward washed in water for 30 min. 5. The results are documented by photos using Gel Doc hardware and software (Fig. 9.6, bottom). The generated RFLP profile is compared with the unique profiles generated from reference strains representative of the different species in the B. cepacia complex.

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Fig. 9.6. Applying recA-gene PCR-based approach for identification of clinical isolates of the B. cepacia complex from CF patients with chronic lung infection. Top: PCR products after B. cepacia complex-specific PCR. Lanes of 100-bp DNA ladder (MW) and the PCR products of the strains LMG 18830 (Burkholderia cenocepacia), LMG 16654 (B. cenocepacia), LMG 16230 (Burkholderia vietnamiensis), LMG 19182 (Burkholderia ambifaria), LMG 20980 (Burkholderia anthina), LMG 14191 (Burkholderia pyrrocinia), ATCC 25416 (B. cepacia), 10534/08 (clinical strain = B. vietnamiensis), water control (vand), and LMG 18829 (B. cenocepacia). All the isolates generated a specific band at about 1 kbp after the PCR reaction,

Classification of Bacterial Pathogens in CF

3.5. DNA Typing by Pulsed Field Gel Electrophoresis (PFGE) for Typing of P. aeruginosa or Other Species

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1. Overnight peptone broth culture (600 μl) (or any other liquid culture in a shaking flask, 37◦ C) is diluted with 2.4 ml SE buffer (1:5). 2. The suspension is washed with SE buffer (3000 rpm) and resuspended in SE buffer. 3. Sigma agarose (500 μl) and 500 μl resuspended bacteria in SE buffer are mixed at 50◦ C, final agarose concentration is 1%. 4. The agarose blocks are casted in 100-μl tubes sealed with plastic tape and refrigerated (5◦ C) for 15–20 min to become solid. 5. The tape is removed and the agarose blocks are transferred to 1.8-ml round bottom plastic tubes (NUNC) containing ES buffer, and 10 μl proteinase K (50 mg/ml) is added and mixed carefully and left at 56◦ C overnight (15–20 h). 6. In case of “smears” on the PFGE (high endonuclease activity), 250 mg/ml proteinase K is added instead of 50 mg/ml and this procedure is repeated three times on three successive days. 7. The agarose block is removed and the remaining ES buffer and enzyme are discarded. Cold TE buffer (1 ml) is added to the agarose block to stop the enzymatic reaction and left for 1 h. 8. The agarose block is cut into three equally sized pieces (squares) and transferred to a new NUNC tube containing cold TE buffer for 1 h. 9. The TE buffer is removed and 250 μl NE buffer is added and changed three times every 30 min at room temperature. 10. NE buffer 4 (with BSA) containing Spe1 restriction enzyme (150 μl TE buffer + 2 μl Spe1 for one block) is added and left to react overnight at 37◦ C.

 Fig. 9.6. (continued) thereby all isolates belong to B. cepacia complex. Middle: B. cepacia complex-specific PCR (left) and B. multivorans PCR (right) results of two clinical isolates (22923/06 and 15782/06). Lanes of 100-bp DNA ladder (MW) and control water (Kontrol vand) and the PCR products. Both isolates generated a specific band at about 1 kbp after the B. cepacia complex PCR, thereby both isolates belong to the B. cepacia complex. The isolate 22923/06 generated a specific band at 714 bp, and thereby the species identification is B. multivorans. The 15782/06 isolate failed to generate a PCR product after the B. multivorans-specific PCR and the species identification has to be further determined by RFLP analysis and it turned out to be a B. cenocepacia. Bottom: RFLP profiles of eight Burkholderia isolates. Three lanes of molecular markers (MW) and HaeIII-cleaved PCR products of ATCC25418 (B. cepacia), LMG 13010 (B. multivorans), LMG 12614 (B. cenocepacia), LMG 14294 (B. stabilis), LMG 16230 (B. vietnamiensis), LMG 19182 (B. ambifaria), LMG 20980 (B. anthina), and LMG 14191 (B. pyrrocinia). Each species presented a unique profile.

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11. The NE buffer with Spe1 enzyme is removed and 1 ml cold TE buffer is added to stop the reaction. It is left for 1 h at room temperature. 12. The TE buffer is removed and 1 ml fresh TE buffer is added. The block is now ready for PFGE. 13. SeaKem agarose (1%) is casted in Tris–borate buffer and the square block is placed at the top of the gel in the appropriate well avoiding air bubbles and the well is sealed with agarose. DNA size markers (Lambda Ladder; BioLabs) are run in triplicate on each gel (left, middle, and right lanes). 14. In case of smear (see step 6), it is necessary to add 500 μM thiourea to the buffer and agarose gel. 15. The PFGE is now run, e.g., on a GenePath PFGE system (Bio-Rad, CA, USA) using Program 1 (PSU) for P. aeruginosa (run time 19.5 h); for other bacteria, shorter or longer time may be required to separate the bands. 16. The PFGE gel is transferred to ethidium bromide (175 μl ethidium bromide (10 mg/ml) in 500 ml Tris– borate buffer diluted 1:20) staining solution and left for 30 min; thereafter it is washed twice for 30 min with distilled sterile water. 17. The PFGE gel is examined and photos are taken, e.g., using the Gel Doc hardware and software for analysis and comparison with other gels stored in the memory (Fig. 9.7). 18. The criterion for evaluating similarity and differences between two gels follows the guidelines by (51, 52), accepting one mutation in a strain leading to disappearance of one lane and appearance of two new lanes, whereas more differences are regarded as different strains. In CF strains during chronic infections, there may sometimes occur clusters of similar but not identical patterns, indicating the evolution by time of the infecting strain. No firm guidelines can be offered in such cases. 3.6. ELISA for Measuring IgG and IgA Antibodies Against Bacterial Sonicate

The Pseudomonas-CF-IgG ELISA kit is a traditional ELISA setup. More than 64 different antigens are detectable in the antigen pool. The results from the pooled human standard serum are used to calculate the concentration of antiserum in the patient sample. Other methods are also available on the market (54).

3.6.1. Principle 3.6.2. Limitations

Non-specific antibodies due to cross-reactivity between P. aeruginosa and other bacterial species are low and correlate with taxonomic relatedness. The human standard antiserum and unknown samples should be assayed in duplicates.

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Fig. 9.7. (Top) Pulsed field gel electrophoresis (PFGE) of molecular weight markers (MW lane) and 12 isolates of colistinresistant P. aeruginosa (lanes 2–13) from 12 CF patients with chronic lung infection and a PAO1 control P. aeruginosa strain (lane K). Restriction enzyme Spe1 was used. Lanes 2, 5, 7, 8, 11, and 13 are identical, and the remaining lanes differ only by 1–2 bands which means that they belong to the same DNA type (55). (Middle) PFGE of molecular markers (3 MW lanes) and 12 isolates of P. aeruginosa (lanes 13–24) from 12 CF patients with chronic lung infection. Lanes 13, 14, 16, 20, and 21 are identical; lanes 15, 17, and 18 differ by more than three lanes (non-identical) and so do lanes 22 and 23 which are identical but differ from lanes 18 and 19 which are identical. (Bottom) From another PFGE gel, a dendrogram has been produced with a computer-based similarity and clustering program (NTSYS; Applied Biostatistics) (29) to facilitate comparison of strains, but this is necessary only if many lanes have to be compared.

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3.6.3. Preparation of Dilutions

Solution A: Antigen solution for coating ELISA plate: Add 100 μl sterile distilled water to the vial containing 9 mg Pseudomonas-CF-IgG antigen and resolve the lyophilized antigen. Dilute the amount to be used the same day 1:2000 in coating buffer. Store the remaining undiluted antigen stock at -20◦ C from where it can be frozen and thawed up to 20 times. Solution B: Dilution of human standard antiserum: Add 100 μl sterile distilled water to the vial with human standard antiserum and resolve the antiserum. Dilute the human standard antiserum to be used the same day by twofold dilution from 1:500 to 1:64,000 in dilution buffer. Store the remaining undiluted human standard antiserum at -20◦ C. The human standard antiserum may be repeatedly frozen and thawed until empty without any change of activity. Solution C: Dilution of patient serum: The patient serum to be measured on the same day has to be diluted 1:100 in dilution buffer (e.g., 10 μl serum added to 990 μl dilution buffer). Solution D: Dilution of rabbit–anti-human IgG HRP: Dilute the rabbit–anti-human IgG HRP 1:20,000 in dilution buffer (e.g., 1 μl rabbit–anti-human IgG HRP is added to 20 ml dilution buffer). Mix thoroughly. Dilute only the amount to be used the same day. 1. Coating of the wells: Add 100 μl diluted antigen (solution A) to each well and incubate for 1 h at room temperature (RT). Aspirate and wash three times with washing buffer. Add 100 μl dilution buffer to each well and incubate for 1 h at RT or overnight at 2–8◦ C. Aspirate and wash two times with washing buffer. 2. Add to each of the appropriate wells either 100 μl of the human standard antiserum dilutions (solution B) or 100 μl diluted patient serum (solution C) and incubate for 1 h at RT. Aspirate and wash three times with washing buffer. 3. Add 100 μl diluted rabbit–anti-human IgG HRP (solution D) to each well and incubate for 1 h at RT. Aspirate and wash five times with washing buffer. 4. Add 100 μl TMB plus standard to each well and incubate for 1 h at RT (dark). 5. Add 100 μl 1 M sulfuric acid to each well and read the absorbance within 10 min using an ELISA reader set to 450 nm.

3.6.4. Calculation of Results

The absorbance of the human standard antiserum dilutions is used to construct a standard curve with OD450 values as a function of log10 ELISA units, e.g.

Classification of Bacterial Pathogens in CF

Dilution factor of human standard serum:

ELISA unit

OD450 value

1:2000

50.00

2.34

1:4000

25.00

1.71

1:8000

12.50

1.13

6.25

0.71

1:16,000

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The normal ELISA unit value of non-infected persons of P. aeruginosa IgG is 0.66 ± 1.64 (mean ± 2 times standard deviation). The 95% upper normal limit is therefore 2.30 and a significant increased titer compared to normal controls is >2.30. The normal ELISA unit value of non-P. aeruginosa-infected CF patients of P. aeruginosa IgG is 0.57 ± 2.39 (mean ± 2 times standard deviation). The normal 95% upper normal limit is therefore 2.96 and a significant increased titer compared to non-P. aeruginosa-infected CF patients is ≥2.96. The difference between non-infected persons and non-P. aeruginosa-infected CF patients is due to crossreactive antibodies induced by, e.g., H. influenzae infections.

Culture positive for P. aeruginosa

Culture negative for P. aeruginosa

IgG ELISA unit > 2.96

A

B

IgG ELISA unit ≤ 2.96

C

D

Group A: Probably chronic P. aeruginosa infection, maintenance therapy is indicated. Group B: Probably not chronic P. aeruginosa infection, but repeat culture. Group C: Probably intermittent P. aeruginosa colonization, eradication therapy is indicated. Group D: Probably not P. aeruginosa colonization or chronic infection. The predictive value of a positive test of Pseudomonas IgG to diagnose chronic P. aeruginosa infection is about 90% and the predictive value of a negative test of Pseudomonas IgG to rule out chronic P. aeruginosa infection is about 90%.

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4. Notes 1. Be aware that NaClO is an alkaline that may cause skin irritation; therefore wear protective clothes, gloves, and goggles. 2. Autofluorescence may appear, make sure that the fluorescent signal is correlated to size and morphology of the investigated cells. 3. It is important that there are no bubbles in the flow chambers. If bubbles are present, try to remove them by gently knocking the flow chamber on the inlet side to the table. Remember to check for bubbles in the flow chamber during the entire experimental period, but after the flow cells are inoculated with bacteria, removing of bubbles should be avoided. If larger bubbles are generated, the biofilm development can be affected, resulting in unusable results. Smaller bobbles can be consumed by the bacteria and will therefore not affect the result. 4. Syto 9 and PI are light sensitive and have to be covered with aluminum foil. Remember to also cover the flow cells with alumina foil during the 15 min of staining. It is possible to add PI to the medium from the beginning of the experiment or when the medium is changed to contain antibiotics and QSI. If this procedure is used, the final concentration of PI in the media has to be 0.0015 mM. Remember to cover every medium containing part with aluminum foil. The flask has to be warmed in a 37◦ C incubator before use. References 1. Westh, J. B. (2001) Pulmonary Physiology and Pathophysiology. Lippincott Williams & Wilkins, Philadelphia, PA. 2. Boucher, R. C. (2004) New concepts of the pathogenesis of cystic fibrosis lung disease. Eur Respir J 23, 146–158. 3. Bjarnsholt, T., Jensen, P. Ø., Fiandaca, M. J., Pedersen, J., Hansen, C. R., Andersen, C. B., et al. (2009) Pseudomonas aeruginosa biofilms in the respiratory tract of cystic fibrosis patients. Pediatr Pulmonol 44, 547–558. 4. Høiby, N., and Frederiksen, B. (2000) Microbiology of cystic fibrosis, in (Hodson, M. E., and Geddes, D. M., eds.), Cystic Fibrosis, 9th ed. Arnold, London, pp. 83–107. 5. Wilson, M. (2005) Microbial Inhabitants of Humans. Cambridge, Cambridge University Press. 6. Høiby, N., and Pressler, T. (2006) Emerging pathogens in cystic fibrosis. Eur Respir

Monog Cyst Fibros Eur Respir Soc 35, 66–78. 7. Skov, M., Koch, C., Reimert, C. M., and Poulsen, L. K. (2000) Diagnosis of allergic bronchopulmonary aspergillosis (ABPA) in cystic fibrosis. Allergy 55, 50–58. 8. Worlitzsch, D., Tarran, R., Ulrich, M., Schwab, U., Cekici, A., Meyer, K. C., et al. (2002) Effects of reduced mucus oxygen concentration in airway Pseudomonas infections of cystic fibrosis patients. J Clin Invest 109, 317–325. 9. Kolpen, M., Hansen, C. R., Bjarnsholt, T., Moser, C., Christensen, L. D., van Gennip, M., et al. (2010) Polymorphonuclear leukocytes consume oxygen in sputum from chronic Pseudomonas aeruginosa pneumonia in cystic fibrosis. Thorax 65, 57–62. 10. Worlitzsch, D., Rintelen, C., Bohm, K., Wollschlager, B., Merkel, N., Borneff-Lipp, M., et al. (2009) Antibiotic-resistant obligate

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11. 12. 13.

14.

15.

16.

17.

18.

19.

20.

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anaerobes during exacerbations of cystic fibrosis patients. Clin Microbiol Infect 15, 454–460. Koch, R. (1884) Die Aetiologie der Tuberkulose. Mittheil Kaiserl Gesundheitsamt 2, 1–88. Taylor-Robinson, D. (1983) The role of M. genitalum in non-gonococcal urethritis: a review. Yale J Biol Med 56, 537–543. Høiby, N. (1974) Epidemiological investigations of the respiratory tract bacteriology in patients with cystic fibrosis. Acta Pathol Microbiol Scand B 82, 541–550. Lee, T.W.R., Brownlee, K.G., Conway, S.P., Denton, M., and Littlewood, J.M. (2003) Evaluation of a new definition for chronic Pseudomonas aeruginosa infection in cystic fibrosis patients. J Cyst Fibros 2, 29–34. Proesmans, M., Balinska-Miskiewicz, W., Dupont, L., Bossuyt, X., Verhaegen, J., Høiby, N., et al. (2006) Evaluating the “Leeds criteria” for Pseudomonas aeruginosa infection in a cystic fibrosis center. Eur Respir J 27, 937–943. Pressler, T., Karpati, F., Gramström, M., Knudsen, P.K., Lindblad, A., Hjelte, L., et al. (2009) Diagnostic significance of measurements of specific IgG antibodies to Pseudomonas aeruginosa by three different serological methods. J Cyst Fibros 8, 37–42. Döring, G., Buhl, V., Høiby, N., Schiøtz, P. O., and Botzenhart, K. (1984) Detection of proteases of Pseudomonas aeruginosa in immune complexes isolated from sputum of cystic fibrosis patients. Acta Pathol Microbiol Scand C 92, 307–312. Høiby, N. (2002) Understanding bacterial biofilms in patients with cystic fibrosis: current and innovative approaches to potential therapies. J Cyst Fibros 1, 249–254. Wainwright, C. E., Grimwood, K., Carlin, J. B., Vidmar, S., Cooper, P. J., Francis, P.W., et al. (2008) Safety of bronchoalveolar lavage in young children with cystic fibrosis. Pediatr Pulmonol 43, 965–972. Murray, P. R., Baron, E. J., Jorgensen, J. H., Landry, M. L., and Pfaller, M. A. (2007) Manual of Clinical Microbiology, 9th ed. ASM Press, Washington DC. Diederen, B. M. W., van Leest, M. -L., van Duijin, I., Willemse, P., van Keulen, P. H. J., and Kluytmans, J. A. J. W. (2006) Performance of MRSA ID, a new chromogenic medium for detection of methicillin-resistant Staphylococcus aureus. J Clin Microbiol 44, 586–588. Levi, K., and Towner, K. J. (2003) Detection of methicillin-resistant Staphylococcus

23.

24.

25.

26.

27.

28.

29.

30.

31.

169

aureus (MRSA) in blood with the EVIGENE MRSA detection kit. J Clin Microbiol 41, 3890–3892. Hoffmann, N., Rasmussen, T. B., Jensen, P. Ø., Stub, C., Hentzer, M., Molin, S., et al. (2005) Novel mouse model of chronic Pseudomonas aeruginosa lung infection mimicking cystic fibrosis. Infect Immun 73, 2504– 2514. Haussler, S., Ziegler, I., Lottel, A., von Gotz, F., Rohde, M., Wehmhohner, D., et al. (2003) Highly adherent small-colony variants of Pseudomonas aeruginosa in cystic fibrosis lung infection. J Med Microbiol 52, 295–301. Balke, B., Schmoldt, S., Haussler, S., Suerbaum, S., Heesemann, J., and Hogardt, M. (2008) A German external quality survey of diagnostic microbiology of respiratory tract infections in patients with cystic fibrosis. J Cyst Fibros 7, 7–14. Coenye, T., Vandamme, P., Govan, J. R. W., and Lipuma, J. J. (2001) Taxonomy and identification of the Burkholderia cepacia complex. J Clin Microbiol 39, 3427–3436. Degand, N., Carbonelle, E., Dauphin, B., Beretti, J. -L., Bourgeois, M. L., Sermet.Gaudelus, I., et al. (2008) Matrixassisted laser desorption ionization-time of flight mass spectrometry for identification of nonfermenting Gram-negative bacilli isolated from cystic fibrosis patients. J Clin Microbiol 46, 3361–3367. Wellinghausen, N., Kothe, J., Wirths, B., Sigge, A., and Popperts, S. (2005) Superiority of molecular techniques for identification of Gram-negative, oxidase-positive rods, including morphological nontypical Pseudomonas aeruginosa, from patients with cystic fibrosis. J Clin Microbiol 43, 4070–4075. Fluge, G., Ojeniyi, B., Høiby, N., Digranes, A., Ciofu, O., Hunstad, E., et al. (2001) Typing of Pseudomonas aeruginosa strains in Norwegian cystic fibrosis patients. Clin Microbiol Infect 7, 238–243. Yang, L., Haagensen, J. A. J., Jelsbak, L., Johansen, H. K., Sternberg, C., Høiby, N., et al. (2008) In situ growth rates and biofilm development of Pseudomonas aeruginosa populations in chronic lung infection. J Bact 190, 2767–2776. Xu, J., Moore, J. E., Murphy, P. G., Millar, B. C., Redmond, A. O. B., and Elborn, J. S. (2004) Molecular (PCR) detection of Pseudomonas spp. other than P-aeruginosa directly from the sputum of adults and children with cystic fibrosis. Br J Biomed Sci 61, 147–149.

170

Bjarnsholt et al.

32. Høiby, N. (1977) Pseudomonas aeruginosa infection in cystic fibrosis. Diagnostic and prognostic significance of Pseudomonas aeruginosa precipitins determined by means of crossed immunoelectrophoresis. A survey. Acta Path Microbiol Scand Suppl 262 C, 3–96. 33. Bjarnsholt, T., Kirketerp-Møller, K., Jensen, P. Ø., Madsen, K. G., Phipps, R., Krogfelt, K., et al. (2008) Why chronic wounds won’t heal: a novel hypothesis. Wound Rep Regen 16, 2–10. 34. Bjarnsholt, T., Tolker-Nielsen, T., Givskov, M., Janssen, M., and Christensen, L. H. (2009) Detection of bacteria by FISH in culture-negative soft tissue filler lesions. Dermatol Surg 35, 1620–1624. 35. Høiby, N., Johansen, H. K., Moser, C., Song, Z. J., Ciofu, O., and Kharazmi, A. (2001) Pseudomonas aeruginosa and the biofilm mode of growth. Microb Infect 3, 1–13. 36. Donlan, R. M., and Costerton, J. W. (2002) Biofilms: Survival mechanisms of clinically relevant microorganisms. Clin Microbiol Rev 15, 167–178. 37. Bjarnsholt, T., Jensen, P. Ø., Burmølle, M., Hentzer, M., Haagensen, J. A. J., Hougen, H. P., et al. (2005) Pseudomonas aeruginosa tolerance to tobramycin, hydrogen peroxide and polymorphonuclear leukocytes is quorum-sensing dependent. Microbiology 151, 373–383. 38. Walters, M. C., Roe, F., Bugnicourt, A., Franklin, M. J., and Stewart, P. S. (2003) Contributions of antibiotic penetration, oxygen limitation, and low metabolic activity to tolerance of Pseudomonas aeruginosa biofilms to ciprofloxacin and tobramycin. Antimicrob Agents Chemother 47, 317–323. 39. O’Toole, G., Kaplan, H. B., and Kolter, R. (2000) Biofilm formation as microbial development. Ann Rev Microbiol 54, 49–79. 40. Sauer, K. T. (2003) The genomics and proteomics of biofilm formation. Genome Biol 4, 219–229. 41. Hentzer, M., Eberl, L., and Givskov, M. (2005) Transcriptome analysis of Pseudomonas aeruginosa biofilm development: anaerobic respiration and iron limitation. Biofilms 2, 37–61. 42. Purevdorj, B., Costerton, J. W., and Stoodley, P. (2002) Influence of hydrodynamics and cell signaling on the structure and behavior of Pseudomonas aeruginosa biofilms. Appl Env Microbiol 68, 4457–4464. 43. Reimmann, C., Ginet, N., Michel, L., Keel, C., Michaux, P., Krishnapillai, V., et al.

44.

45.

46.

47.

48.

49.

50.

51.

52.

53.

(2002) Genetically programmed autoinducer destruction reduces virulence gene expression and swarming motility in Pseudomonas aeruginosa PAO1. Microbiology 148, 923–932. Sauer, K., Camper, A. K., Ehrlich, G. D., Costerton, J. W., and Davies, D. G. (2002) Pseudomonas aeruginosa displays multiple phenotypes during development as a biofilm. J Bact 184, 1140–1154. Klausen, M., Aaes-Jorgensen, A., Molin, S., and TolkerNielsen, T. (2003) Involvement of bacterial migration in the development of complex multicellular structures in Pseudomonas aeruginosa biofilms. Mol Microbiol 50, 61–68. Hansen, C. R., Pressler, T., Nielsen, K. G., Jensen, P. Ø., Bjarnsholt, T., and Høiby, N. (2010) Inflammation in Achromobacter xylosoxidans infected cystic fibrosis patients. J Cyst Fibros 9, 51–58. Christensen, B. B., Sternberg, C., Andersen, J. B., Palmer, R. J., Nielsen, A. T., Givskov, M., et al. (1999) Molecular tools for study of biofilm physiology. Biofilms 1, 20–42. Coenye, T., Mahenthiralingam, E., Henry, D., LiPuma, J. J., Laevens, S., Gillis, M., et al. (2001) Burkholderia ambifaria sp. nov., a novel member of the Burkholderia cepacia complex including biocontrol and cystic fibrosis-related isolates. Int J Syst Evol Microbiol 51, 1481–1490. Mahenthiralingam, E., Bischof, J., Byrne, S. K., Radomski, C., Davies, J. E., AvGay, Y., et al. (2000) DNA-based diagnostic approaches for identification of Burkholderia cepacia complex, Burkholderia vietnamiensis, Burkholderia multivorans, Burkholderia stabilis, and Burkholderia cepacia genomovars I and III. J Clin Microbiol 38, 3165–3173. Romling, U., and Tümmler, B. (2000) Achieving 100% typeability of Pseudomonas aeruginosa by pulsed-field gel electrophoresis. J Clin Microbiol 38, 464–465. Tenover, F. C., Arbeit, R. D., Goering, R. V., Mickelsen, P. A., Murray, B. E., Persing, D. H., et al. (1995) Interpreting chromosomal DNA restriction patterns produced by pulsed field gel electrophoresis. Criteria for bacterial strains typing. J Clin Microbiol 33, 2233– 2239. Struelens, M. J. (1996) Consensus guidelines for appropriate use and evaluation of microbial epidemiologic typing systems. Clin Microbiol Infect 2, 2–11. Pressler, T., Frederiksen, B., Skov, M., Garred, P., Koch, C., and Høiby, N. (2006) Early rise of anti-Pseudomonas antibodies

Classification of Bacterial Pathogens in CF and a mucoid phenotype of Pseudomonas aeruginosa are risk factors for development of chronic lung infection – a case control study. J Cyst Fibros 5, 9–15. 54. Ratjen, F., Walter, H., Haug, M., Meisner, C., Grasemann, H., and Döring, G. (2007) Diagnostic value of serum antibodies in early Pseudomonas aeruginosa infection in cys-

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tic fibrosis patients. Pediatr Pulmonol 42, 249–255. 55. Johansen, H. K., Moskowitz, S. M., Ciofu, O., Pressler, T., and Høiby, N. (2008) Spread of colistin-resistant non-mucoid Pseudomonas aeruginosa among chronically infected Danish cystic fibrosis patients. J Cyst Fibros 7, 391–397.

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Chapter 10 Approaches to Study Differentiation and Repair of Human Airway Epithelial Cells Sophie Crespin, Marc Bacchetta, Song Huang, Tecla Dudez, Ludovic Wiszniewski, and Marc Chanson Abstract One of the main functions of the airway mucosa is to maintain a mechanical barrier at the air–surface interface and to protect the respiratory tract from external injuries. Differentiation of human airway epithelial cells (hAECs) to polarized airway mucosa can be reproduced in vitro by culturing the cells on microporous membrane at the air–liquid interface. Here, we describe approaches to study differentiation as well as repair of the hAECs by using a commercially available airway cell culture model called MucilAirTM . Key words: Human airway epithelial cell culture, MucilAirTM , differentiation, wounding techniques, repair, cystic fibrosis.

1. Introduction The respiratory epithelium plays a fundamental role as a line of defense against pathogens. Among other lung diseases, cystic fibrosis (CF) has been associated with a damaged airway mucosa consequently to chronic lung inflammation and with an abnormal repair (1, 2). Various models were developed by researchers aiming to study the behavior of the respiratory epithelium and its repair. Animal models appear to be useful for CF research (see related chapter in this book). Focusing on lung functions and

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repair, several strategies have already been described in the literature using these models (for a review, see (3)). In vivo approaches consist in the inhalation of gases or the intratracheal instillation of drugs. Ex vivo airway epithelial xenograft models have also been developed. In this case, immunocompromised mice were used to receive grafts subcutaneously. Using this approach, Hajj et al. (4) studied the regeneration of human CF airway epithelium and reported a delayed and abnormal re-differentiation. Nonetheless, these animal-based models exhibit some troubles. First of all, the study of mouse lung regeneration in the context of CF brings into question that mice do not exhibit a CF phenotype in the control conditions (without injury). So, even if we may draw conclusions about repair of the normal epithelium, the extrapolation to the CF epithelium based on CFTR knockout mice might be biased. Second, in the xenograft model, grafts are transplanted heterotypically, leading to a complete change of the normal tissue environment. Closer to the native human healthy or pathologic airway epithelium, several groups developed in vitro cultures using hAECs obtained from surgical resection or brushing. Epithelial cells from the airway epithelium are isolated by explant culture or enzymatic dissociation (for review, see (5)). A key concept is the switch from submerged cultures to an air–liquid interface allowing the development of differentiated airway epithelia (6, 7). To this end, inserts with porous membranes in tissue culture wells were used (8). On the same basis of air–liquid interface culture, at least two kinds of models were developed. One is based on the plating of isolated hAECs on collagen IV-coated inserts (9). The culture is usually viable for about 1 month after the beginning of the culture (4). The other model consists in a first step of hAEC proliferation followed by a second step of differentiation (10, 11). These models present the advantage to amplifying a rare material, especially for CF tissues. The MucilAirTM system presents the characteristics of the human airway epithelium with the presence of basal cells, goblet cells, and ciliated cells organized in a pseudostratified epithelium. An advantage of this system is the possibility to keep the airway epithelium differentiated for up to 6–9 months enabling to monitor epithelial repair, a process that lasts days to weeks depending on the extent of the lesion. The aim of this chapter is to first describe the characteristics of a well-differentiated airway epithelium maintained in primary culture. Thus, different protocols concerning the states of differentiation are given: epithelial morphology and expression of specific markers (Ki67, β-tubulin, and connexins). Second, a strategy mimicking an injury in vitro is described. Finally, the last part of this chapter concerns methods to monitor epithelial repair, including measurement of the kinetics of wound closure, cell proliferation, and migration.

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2. Materials 2.1. hAEC Cultures and Media 2.1.1. hAEC Cultures

2.1.2. hAEC Media

2.2. Other Reagents and Solutions

Differentiation and repair of hAECs were evaluated on the commercially available in vitro airway epithelium cell model MucilAirTM (Epithelix, Plan-les-Ouates, Switzerland). The respiratory epithelium is reconstituted from primary hAECs freshly isolated from nasal polyps or from tracheal/bronchial biopsies, according to methods that are extensively described in this book. Briefly, hAECs are seeded onto 33-mm2 Costar Transwell inserts (Costar, ref. number 3470) with transparent microporous membranes (0.4-μm pore). Two days after seeding, hAECs are switched to an air–liquid interface for at least 45 days. This leads to the differentiation of hAECs to a mucociliated pseudostratified airway epithelium that is maintained in a homeostatic state for months (11). The transparent microporous membrane allows direct observation of the cells under a conventional inverted microscope. Moreover, the polyethylene membranes are more resistant than polycarbonate membranes and can withstand mechanical forces. Typically, the medium used to maintain hAEC cultures at the air– liquid interface is a 3:1 mix of DMEM with GlutaMax (Invitrogen, ref. number 31966-021) and F12 (Invitrogen, ref. number 21765-029), supplemented with penicillin–streptomycin (15,000 units and 30 μg/ml, respectively; GIBCO, ref. number 15140148) and amphotericin B (Amimed, ref. number 4-05F00-H). Other commercially available “ready-to-use” media can also be purchased from Epithelix (Plan-les-Ouates, Switzerland), Clonetics Corp. (San Diego, CA), or PromoCell GmbH (Heidelberg, Germany). 1. Buffered NaCl solution: Isotonic saline solution containing 0.9% NaCl supplemented with 10 mM HEPES and 1.25 mM CaCl2 . 2. Dulbecco’s phosphate buffered saline (DPBS) with calcium and magnesium (GIBCO, ref. number 14040). 3. PFA solution: Make 4% paraformaldehyde solution freshly from powder (Sigma, ref. number P6148) in DPBS. Adjust pH at 7.2. 4. Triton X-100 solution: Make 0.3% Triton X-100 (Sigma, ref. number T8787) solution freshly in DPBS. 5. 0.5 M NH4 Cl solution in DPBS. 6. BSA solution: Make 2% bovine serum albumin solution in DPBS freshly.

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7. Lucifer yellow 4% solution: Prepare the Lucifer yellow solution (Sigma, ref. number L0259) in 150 mM LiCl buffered to pH 7.2 with 10 mM HEPES. Keep the solution at 4◦ C in dark and spin down before use to remove any possible aggregates. 2.3. Materials for Wounding

1. A conventional airbrush (Triplex, Gabbert). 2. A source of compressed air. 3. Pressure regulator (0.1 and 0.5 bar). 4. Flexible pipe allowing the connection between the pressure regulator and the airbrush.

2.4. Other Equipments

1. Inverted microscope equipped with fluorescein filters and UV illumination, standing on an anti-vibration table. A micromanipulator is also required to position thin-tip microelectrodes. 2. Borosilicate glass capillaries with an internal filament (for example, Kwik-FilTM 1B120F-4 from World Precision Instruments, Inc.) and a microelectrode puller (typically, we use a vertical Narishige PC-10, Tokyo, Japan). 3. Module allowing the measurement of the transepithelial electrical resistance (for example, EVOMX from World Precision Instruments, Inc.).

3. Methods 3.1. Approaches to Study Differentiation of hAEC

hAECs grown on filters lose their differentiated features. Differentiation can be triggered by exposing the apical surface of hAECs to air (7). Below, we describe approaches to monitor the differentiation of hAECs to a full polarized airway epithelium.

3.1.1. Morphology of the Differentiating Airway Epithelium

The differentiation of hAEC can be evaluated by paraffinembedded sections of the cultures, although the procedure on Transwell inserts is delicate: 1. Fix the hAEC culture with the 4% PFA solution for at least 1 h. 2. Carefully remove the microporous membrane from the insert using a scalpel blade. Avoid tearing/bending of the membrane. 3. Follow a usual protocol of dehydration (succession of baths of ethanol from 70 to 100%, xylol) and embedding in paraffin. Embed the membrane vertically in paraffin. We

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use an automatic embedding machine for treating histological examination (Tissue Processor; Leica Microsystems, TP1020). 4. Make 5-μm-thick sections with a microtome and mount R slides). See Note 1 them on charged slides (as Superfrost for tips and tricks. 5. Rehydrate the samples (succession of baths of xylol, ethanol from 100 to 70%, distilled water) before staining (hemalun– eosin, periodic acid Schiff coloration, Alcian blue, etc.). The morphology of hAECs grown at the air–liquid interface for increasing the amount of time is illustrated in Fig. 10.1 (top panels). With time, hAECs become taller and cilia appear at the apical surface. The presence of basal and mucous cells is also observed. The typical morphology of the respiratory epithelium is maintained on the long term.

Fig. 10.1. Long-term differentiation of MucilAirTM hAEC cultures. Paraformaldehyde-fixed, paraffin-embedded (PFPE) sections of MucilAirTM cultures. hAECs organized as a monolayer during the first week of culture. At this time, a high proliferation rate (Ki-67 staining) is associated with an undifferentiated state (few cells stained for β-tubulin) and a high level of Cx26 expression. After 7 weeks, the hAEC culture exhibits a pseudostratified ciliated epithelium with goblet cells (arrowhead). This differentiation is correlated with a low proliferation rate, a huge amount of β-tubulin staining, and the absence of Cx26 expression. The latter profile is maintained over months (as shown as an example at 14 weeks). Bar, 25 μm.

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3.1.2. Immunohistochemical Detection of Markers of hAEC Differentiation

Typically, differentiation is associated with inhibition of hAEC proliferation and occurrence of neociliogenesis. Several markers of hAEC differentiation can be detected by immunohistochemistry. To this end, immunofluorescence is performed for Ki-67 (a nuclear marker of cell proliferation) and β-tubulin (a component of ciliae). We also use connexin26 (Cx26, a gap junction protein) and Cx43 as key markers of differentiated hAECs (12): 1. Fix the hAEC culture with the PFA solution for 15 min. Wash with DPBS. 2. Permeabilize hAECs with the Triton X-100 solution for 15 min. Wash with DPBS. 3. To avoid non-specific staining, incubate the culture first in the NH4 Cl solution for 15 min followed by the BSA solution for 30 min. 4. Primary and secondary antibodies are incubated for at least 90 min at room temperature. 5. After careful washing, cut the microporous membrane out of the insert using a scalpel blade and mount between slide and coverslip with a photobleaching-preventing mounting R , Clinisciences, ref. number H-1000; medium (Vectashield Aquamount, Thermo Scientific, ref. number 14-390-5). See Note 2 for tips and tricks. Examples of immunostaining for Ki-67, β-tubulin, and Cx26 at different times of culture are shown in Fig. 10.1. At early time after the air–liquid interface has been established, hAEC cultures exhibit mostly a monolayer appearance, high proliferation rate, and absence of ciliae. With longer time at the air–liquid interface, proliferation ceased while differentiation is evidenced by the absence of Ki-67 detection and numerous cilia covering 90% of the epithelial surface after 45 days of culture. Of interest is the marked decrease in the expression of the gap junction proteins Cx26 and Cx43 with differentiation of hAECs (12), as illustrated in Fig. 10.1 for Cx26.

3.1.3. Monitoring Gap Junctional Intercellular Communication

The loss of Cx43 and Cx26 with time at the air–liquid interface allows evaluating hAEC differentiation by monitoring gap junctional intercellular communication. In human, 20 different genes coding for connexin have been found. These connexins are associated with specific pattern of tissue expression, and depending on connexin composition, gap junction channels exhibit different permeability to molecules and dyes. We describe below an approach to microinject the fluorescent dye Lucifer yellow in hAEC cultures: 1. Cut the top of the Transwell insert half a centimeter above the cell culture. See Note 3 for tips and tricks.

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2. Place the insert on a drop of culture medium onto a glass slide and move the preparation to the stage of the inverted microscope equipped for fluorescein detection. 3. Pull a microelectrode (typically 20–50 M). Bend the pipette over a thin flame (away for the tip) to an angle of about 10–20◦ . This will help to position the electrode onto the cell surface within the narrow space provided by the insert. 4. Fill the pipette tip with the Lucifer yellow solution. See Note 4 for tips and tricks. 5. Connect the microelectrode to the micromanipulator and bring the tip in close contact to the cell surface. The fluorescence of Lucifer yellow helps to locate the microelectrode. The cell impalement should be as gentle as possible to maintain cell viability; usually one brief finger tap on the anti-vibration table is sufficient. 6. Allow the dye to diffuse out of the electrode into the cells for 3 min and then rapidly remove the pipette. Dye coupling can be evaluated immediately by counting the number of fluorescent cells. Use a new electrode for each microinjection. An extensive cell-to-cell diffusion of the tracer will be indicative for a not yet differentiated airway epithelium. Ciliated cells within a well-polarized and differentiated airway epithelium do not communicate in terms of Lucifer yellow diffusion. This does not mean that ciliated cells are devoid of gap junctions; in fact, they express Cx30, another gap junction protein which is not permeable to Lucifer yellow (12). 3.1.4. Cytokine and Mucin Production

The production of IL-8 and mucin is changing with hAEC differentiation. Il-8 was measured using an ELISA kit (CLB, Amsterdam, The Netherlands or BD OptEIATM , BD Biosciences, UK) in basal medium that was collected every 2 days. Typically, a well-polarized and differentiated airway epithelium produces 5–15 ng/ml of IL-8 per day. Quantification of mucin production can be evaluated with the enzyme-linked lectin assay (ELLA). At time 0, the apical surface is rinsed with the buffered NaCl solution and cultures are returned to the incubator for various amount of time. At appropriate time points, the accumulated mucus at the apical surface is recovered with 200 μl of buffered NaCl. Glycoproteins in the mucus are captured by Helix pomatia lectin (HPA–lectin) and then revealed by HPA–horseradish peroxidase lectin conjugate (HPA–HRP). The amount of mucus secreted on the epithelial surface is calculated by dividing the obtained values with the number of days of accumulation (ng/ml/day). Mucins are not present in the basolateral compartment.

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3.2. Approaches to Study Repair of hAECs

Following injury, hAECs migrate and proliferate to cover the wound. Covered areas exhibit hAECs that stop proliferating but re-differentiate into a pseudostratified airway epithelium (13). All these processes take place simultaneously with progression of the wound closure. Below, we describe approaches to wound the airway epithelium and to monitor its repair.

3.2.1. Wounding

Several approaches may be considered for wounding a MucilAirTM culture (see Notes 5–7 for alternative wounding techniques). In the specific context of in vitro hAEC cultures on Transwell inserts, these approaches are limited by the fragility of the microporous membrane and the lack of accessibility to the cell surface. We report below the method we are using to make reproducible, regular, and circular wounds. Targeted cells are locally removed from the insert without damaging adjacent cells on the membrane by using an airbrush linked to a pressure regulator. As shown in Fig. 10.2, the diameter of the airbrush fits in the

Fig. 10.2. Procedure for wounding well-differentiated airway epithelia. a Classic airbrush use for making a wound in hAEC cultures (top). The airbrush and the Transwell insert exhibit nearly similar diameters (middle), allowing standardization of the wound by keeping a distance of 4 mm between the airbrush nozzle and the microporous membrane (bottom). b Typical view of a wound (bottom) made with the airbrush under a 0.5 bar pressure maintained for 1 s. A non-wounded hAEC culture of at least 6 weeks old is shown for comparison (top).

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Transwell inserts (Fig. 10.2a). As these inserts are particularly calibrated, the same distance between the airbrush nozzle and the epithelial surface is kept. Note that these parameters depend mainly on the companies where airbrush and inserts are from: 1. Rinse the apical surface of hAEC cultures with the buffered NaCl solution. 2. Every pieces of the airbrush should be carefully cleaned. Also manage a clean area under sterile conditions (typically a culture hood) for wounding. 3. To avoid drying of the apical surface while wounding, the reservoir of the airbrush is filled with the buffered NaCl solution. 4. Adjust the air pressure between 0.1 and 0.5 bar. 5. Introduce the airbrush head into the insert until the end (about 4 mm). 6. Apply a brief pulse of air for 1–2 s. This parameter is highly dependent on the equipment and should be adjusted by each user. Depending on the pressure and the number of pushes on the airbrush, the size of the wound varies between 2 and 15 mm2 . 7. Remove debris and detached cells by carefully washing the surface with the buffered NaCl solution and return the cultures to the incubator to allow cell repair. Images of the circular wound that is obtained following this procedure are shown in Fig. 10.2b. 3.2.2. Monitoring Wound Closure: Kinetics

One of the most convenient, reliable, and non-destructive methods to monitor wound closure is the measurement of transepithelial electrical resistance (TEER). The TEER of wounded cultures should be compared with that of empty Transwell inserts with culture medium in both basal and apical compartments. With repair and re-establishment of junctional complexes, TEER sharply increases to about 400–500  cm2 , which is typical for in vitro human airway epithelia (see Discussion in reference 11). The kinetics of recovery obviously depends on the wound size. Another approach to monitor the kinetics of wound closure is by image analysis. To this end, we use an automated inverted microscope (DMIRE2; LEICA) equipped with a DMSTC XY stage and a digital camera (Ds-5Mc; Nikon) connected to a personal computer. At regular intervals, the surface area of each insert is scanned. Typically, 35 images using a 5× objective are needed to complete the scanning of one insert. Reconstitution of the culture surface is performed by the analysis of pictures with the Image Pro Plus 6.0 software (Media Cybernetics). Alternatively, the ImageJ software (National Institutes of Health, Bethesda) can also be used (http://rsb.info.nih.gov/ij/). Typical images of progression of hAEC repair are shown in Fig. 10.3a, b also

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Fig. 10.3. Monitoring wound closure. a The wound closure is monitored by the acquisition of images taken at different times using an automated inverted microscope equipped with an automatized XY stage and a digital camera. The area covered within a determined period of time allows estimating the rate of epithelial repair. b View of the morphology of the repairing airway epithelium, as investigated using PFPE sections. Bar, 50 μm.

shows a paraffin section of an airway culture 96 h after wounding. Note the change in the height of the epithelium characterized by non-ciliated migrating/proliferating hAECs. To quantify wound closure, the wound area X is measured at different times (T1 , as a circle, allowing the T2 , etc.). The wound area X is considered √ determination of its radius R:R = (X /π). The distance covered by the migrating/proliferating hAECs between time intervals is then given by the difference between R1 and R2 , with R1 and R2 being the radii determined at times T1 and T2 , respectively. 3.2.3. Monitoring Wound Closure: Cell Behavior

It is also possible to monitor wound healing by live imaging. The approach is limited by many factors, including time (it takes days for the epithelium to repair), cell focus (change from a tall differentiated epithelium to a migrating cell monolayer), maintenance of pH of the culture medium, and humidity of the cell environment. However, live imaging can be used within shorter time frames (several hours) at higher resolution to monitor cell behavior at edges of the wound. Thus, depending on the time after wounding, it is in principle possible to observe cell migration, division, and/or differentiation in specific and restricted areas of the repairing airway epithelium. Typically, one needs an inverted microscope equipped with a close chamber enabling control of temperature, CO2 , and humidity. The microscope is

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also equipped for time-lapse imaging. For good (but not optimal) resolution of cell behavior cultured on Transwell inserts, refer to Note 8 for tips and tricks. 3.2.4. Criteria of Repaired Airway Epithelium

As expected from a well-differentiated and polarized airway epithelium, the very same criteria hold for a fully repaired epithelium after injury, including the following: 1. A tall pseudostratified mucociliated morphology. 2. Positive and massive immunostaining for β-tubulin but no detection of Ki-67, Cx26, and Cx43. 3. Lack of Lucifer yellow-mediated gap junctional intercellular communication. 4. Low basal production of IL-8 but sustained apical secretion of mucins.

4. Notes R 1. Superfrost slides are positively charged allowing a better adhesion of samples and avoiding the use of fixation or glue. Alternatively, regular slides may be used after a poly-lysine treatment.

2. To avoid pressing the airway mucosa during the mounting of the samples after immunostaining, an alternative is to use small strips of tape on each edge of the Superfrost slide to create a small chamber where the sample is placed. Then, cover the sample with a coverslip. 3. To easily cut off the top part of inserts, we used a thin inox wire connected to a 6.3-A, 2–8-V DC generator (typically generators used for microscope bulbs). We designed a system whereby the positioning of the wire height could be changed to adapt for various plastic wares (Transwell inserts, Petri dishes, etc.). 4. To easily backfill microelectrodes with the Lucifer yellow solution, we recommend the MicroFilTM needle from World Precision Instruments, Inc. (Microfil MF34G). 5. Mechanical wound may be performed by using the tip of a pipette (14, 15). This technique is particularly simple when performed on a plastic dish but becomes more challenging on membrane inserts. The main inconvenience remains the risk to damage the microporous membrane and to tear the tall airway epithelium apart. 6. Mechanical wound may also be performed following the methodology reported by Vermeer et al. (16). A

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home-designed wounding device performs a reproducible ring-shaped wound when lowered onto cells and turned 360◦ C. 7. Chemical wounding consists of the deposit of a small volume of 1 M sodium hydroxide and its rapid neutralization with DPBS. Tournier et al. (17) reported that a drop of 1 μl leads to a circular wound area of 30 mm2 . Transposed to our model (insert area of 33 mm2 ), this technique would need to be adapted for smaller volumes. 8. To monitor the cell behavior by live imaging, we are using 35-mm Petri dishes with a glass bottom (12 mm, ref. number 73911035; Milian) and for which a hole has been drilled through the covers. The diameter of the hole is slightly larger than that of the bottom of the insert. This simple trick allows holding the insert in proximity to the glass bottom, which is of help for imaging using a 40× objective. The dish is filled with culture medium, while 100 μl is added to the wounded surface. This allows to bath cells with sufficient medium and to ensure humidity and gas exchange in the Petri dish.

Acknowledgments This work was supported by the grants from the Swiss National Science Foundation and by Vaincre la Mucoviscidose. References 1. Puchelle, E., and Zahm, J. M. (2006) Repair process of the airway epithelium, in (Lenfant, C., and Dekker, M., eds.), Airway Environment: From Injury to Repair. Series Lung biology in health and diseases. Marcel Dekker, New York, NY, pp. 1576–1582. 2. Voynow, J. A., Fischer, B. M., Roberts, B. C., and Proia, A. D. (2005) Basal-like cells constitute the proliferating cell population in cystic fibrosis airways. Am J Respir Crit Care Med 172, 1013–1038. 3. Liu, X., Driskell, R. R., and Engelhardt, J. F. (2006) Stem cells in the lung. Methods Enzymol 419, 285–321. 4. Hajj, R., Lesimple, P., Nawrocki-Raby, B., Birembaut, P., Puchelle, E., and Coraux, C. (2007) Human airway surface epithelial regeneration is delayed and abnormal in cystic fibrosis. J Pathol 211 3, 340–350. 5. Gruenert, D. C., Finkbeiner, W. E., and Widdicombe, J. H. (1995) Culture and transfor-

6.

7.

8.

9.

mation of human airway epithelial cells. Am J Physiol 268 3 Pt 1, L347–360. Yamaya, M., Finkbeiner, W. E., Chun, S. Y., and Widdicombe, J. H. (1992) Differentiated structure and function of cultures from human tracheal epithelium. Am J Physiol 262, L713–L724. de Jong, P. M., van Sterkenburg, M. A., Hesseling, S. C., Kempenaar, J. A., Mulder, A. A., Mommaas, A. M., et al. (1994) Ciliogenesis in human bronchial epithelial cells cultured at the air–liquid interface. Am J Respir Cell Mol Biol 24, 224–234. Johnson, L. G., Dickman, K. G., Moore, K. L., Mandel, L. J., and Boucher, R. C. (1993) Enhanced Na+ transport in an air– liquid interface culture system. Am J Physiol 264, L560–L565. Karp, P. H., Moninger, T. O., Weber, S. P., Nesselhauf, T. S., Launspach, J. L., Zabner, J., et al. (2002) An in vitro model of

Airway Epithelium Repair

10.

11.

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differentiated human airway epithelia. Methods for establishing primary cultures. Methods Mol Biol 188, 115–137. Fulcher, M. L., Gabriel, S., Burns, K. A., Yankaskas, J. R., and Randell, S. H. (2005) Well-Differentiated Human Airway Epithelial Cell Cultures. Human Cell Culture Protocols, 2nd ed, Methods Mol. Med., vol 107. Springer, New York, NY, pp. 183–206. Wiszniewski, L., Jornot, L., Dudez, T., Pagano, A., Rochat, T., Lacroix, J. S., et al. (2006) Long-term cultures of polarized airway epithelial cells from patients with cystic fibrosis. Am J Respir Cell Mol Biol 34, 39–48. Wiszniewski, L., Sanz, J., Scerri, I., Gasparotto, E., Dudez, T., Lacroix, J. S., et al. (2007) Functional expression of connexin30 and connexin31 in the polarized human airway epithelium. Differentiation 75, 382–392. Puchelle, E., Zahm, J. M., Tournier, J. M., and Coraux, C. (2006) Airway epithelial repair, regeneration, and remodeling after injury in chronic obstructive pulmonary disease. Proc Am Thorac Soc 3, 726–733.

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14. Planus, E., Galiacy, S., Matthay, M., Laurent, V., Galvrilovic, J., Murphy, G., et al. (1999) Role of collagenase in mediating in vitro alveolar epithelial wound repair. J Cell Sci 112, 243–252. 15. Lechapt-Zalcman, E., Prulière-Escabasse, V., Advenier, D., Galiacy, S., Charrière-Bertrand, C., Coste, A., et al. (2006) Transforming growth factor-beta1 increases airway wound repair via MMP-2 upregulation: a new pathway for epithelial wound repair?. Am J Physiol Lung Cell Mol Physiol 290, L1277–L1282. 16. Vermeer, P. D., Einwalter, L. A., Moninger, T. O., Rokhlina, T., Kern, J. A., Zabner, J., et al. (2003) Segregation of receptor and ligand regulates activation of epithelial growth factor receptor. Nature 422, 322–326. 17. Tournier, J. M., Maouche, K., Coraux, C., Zahm, J. M., Cloëz-Tayarani, I., NawrockiRaby, B., Bonnomet, A., et al. (2006) alpha3alpha5beta2-Nicotinic acetylcholine receptor contributes to the wound repair of the respiratory epithelium by modulating intracellular calcium in migrating cells. Am J Pathol 168, 55–68.

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Section II Omic Approaches to Study Cystic Fibrosis

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Chapter 11 Introduction to Section II: Omics in the Biology of Cystic Fibrosis William E. Balch Abstract Cystic fibrosis (CF) is a disease that manifests itself in the context of cell, tissue, and organismal (patho)physiology. While a strong focus on the cystic fibrosis transmembrane conductance regulator (CFTR) since its discovery in 1989 has dominated the field with a wealth of experiments that have provided substantial insight into protein function and structure, a largely untapped area of high relevance to both our basic understanding of CFTR function and its role in clinical disease is the realization that CFTR operates in the context of a cellular network. This is a composite of protein–protein interactions and specific cellular and subcellular environments that balance ion conductance at the cell surface with trafficking through the exocytic and endocytic pathways to promote tissue hydration. To address challenges critical for understanding the system responsible for CFTR physiology and CF pathophysiology, a new era of technologies and methodologies focused on systems-level approaches to analysis of cell and tissue function has emerged. These technologies focus our understanding on the environment supporting protein function (referred to genomics) and the protein composition of the cell (referred to as proteomics) that dictates function. In this section, four chapters focus on emerging “omic” approaches to understanding the cellular environment imposed by message levels in the cell (genomics), the protein composition of the cell and network of interactions dictating cell and CFTR function (proteomics), and the lipid environment (metabolomics) that dictates the functionality of numerous membrane environments in the cell that are integral to CFTR function. Key words: CFTR, cellular networks, protein–protein interactions, proteomics, subcellular environments, systems biology.

Cystic fibrosis (CF) is a disease that manifests itself in the context of cell, tissue, and human (patho)physiology. A strong focus on the cystic fibrosis transmembrane conductance regulator (CFTR) since its discovery in 1989 has dominated the field with a wealth of key experiments that have provided substantial insight into CFTR function and structure. In contrast, a largely untapped area of high relevance to our basic understanding of both CFTR

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function and its role in clinical disease is the realization that CFTR operates in the context of a cellular network; this is a composite of protein–protein interactions and specific cellular and subcellular proteomic and metabolomic environments that balance ion conductance at the cell surface with trafficking through the exocytic and endocytic pathways to promote tissue hydration. While it is clear from Mendelian genetics that CFTR variants are defective in function, the underlying loss of function(s) and gain of toxic function(s) observed in human lung, intestine, and pancreatic physiologies as a consequence of disconnecting CFTR from its interacting partners in the network are largely unknown. The challenge defined by the network biology that dictates normal and pathologic CFTR function is now recognized as a problem in “omics” biology. Omics biology refers to the “system” or systems biology in a given cell type that is required to generate, maintain, and protect the proteome in health and that is subject to dysfunction leading to human diseases such as CF. To address the challenges critical for understanding the network of interactions responsible for CFTR physiology and CF pathophysiology, a new era of technologies and methodologies focused on systems-level approaches to analysis of cell and tissue function has emerged. These technologies focus our understanding on the environment-supporting protein function (referred to as genomics/transcriptomics) and the protein composition of the cell (referred to as proteomics) that dictates function. At the root of both genomics and proteomics lies metabolomics, that is, the small molecule lipid and soluble metabolite pools of the cell that regulate organismal health in response to nutrition and multiple environmental factors that stress the cell and challenge both the genome and the proteome function. The pathophysiology of CF is intimately connected to each of these omic categories and an understanding of their individual contributions will undoubtedly provide critical insight necessary to provide benefit to clinical disease. In this section, four chapters focus on emerging omic approaches to understanding the cellular environment imposed by message levels in the cell (genomics/transcriptomics), the protein composition of the cell and network of interactions dictating cell and CFTR function (proteomics), and the lipid environment (metabolomics) that dictates the functionality of numerous membrane environments in the cell that are integral to CFTR function. Chapter 12 discusses current technologies applicable to defining the genomic/transcriptomic environments that may contribute to disease and that could serve as hallmarks for disease progression given the ease at which these approaches can be used in the clinic. Chapters 13, 14, 15, and 16 focus on various aspects of defining the proteomics of CFTR function in health and disease. Chapter 14 gives a broad overview of rapidly evolving mass

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spectrometry approaches that can be used to ascertain the precise composition of cellular proteomes, protein complexes responsible for CFTR function, and metabolites that may contribute to function in a healthy cell and which become defective in disease. This chapter is designed to motivate CF investigators to begin to adapt these diverse technologies in their own studies. Chapter 15 (functional genomics) and 16 (lipidomics) give specific detailed methodologies that illustrate application of proteomic approaches and mass spectrometry to the study of CF. Omics coupled to bioinformatics remains an emerging field that tackles the challenging problem of the systems biology of disease, rather than simply focusing on a single target protein, in this case CFTR. The real problem in CF disease affecting human health lies in the disruption of the operation of the system, not just the protein. While we have much to learn, the promise of understanding the system at genomic, proteomic, and metabolomic levels offers the opportunity for future therapeutic approaches to use the system, that is, the biology, to correct the pathobiology of CF disease.

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Chapter 12 Microarray mRNA Expression Profiling to Study Cystic Fibrosis Shyam Ramachandran, Luka A. Clarke, Todd E. Scheetz, Margarida D. Amaral, and Paul B. McCray Jr. Abstract To understand the links between CFTR mutations and the development of cystic fibrosis (CF) phenotypes, it is imperative to study the transcriptome in affected cell types. Microarray expression profiling provides a platform to study global gene expression in detail. This approach may provide the necessary information to segregate phenotypic characteristics of CF, differentiate between genetic or environmental factors, and assess the advent and progression of disease phenotypes. Moreover, if a “CF signature” of genes with altered expression is defined, this can be used to monitor effectiveness of treatment. We provide here detailed protocols and tips for collecting and preserving tissues and cells, and preparing total RNA. We also outline novel strategies for experimental design and data analysis, and describe some powerful gene and pathway discovery tools. Key words: GeneChip, mRNA, hybridization, Gene set enrichment analysis, Ingenuity pathway analysis, ANOVA, GeneGo, normalization, quality control, differential expression.

1. Introduction 1.1. Overview of Microarray Technology in Studying Cystic Fibrosis

Microarrays or nucleic acid arrays are comprised of thousands of nucleic acid fragments immobilized onto a solid substrate (1–3). Such an “array” or a chip can represent the entire genome of a species, the transcriptome of a specific tissue, or may be designed to fulfill a specific function like assaying for splice junctions, SNPs, copy number polymorphisms, or insertions and deletions. In this chapter, we focus on the use of microarrays to generate an mRNA expression profile of a given sample from distinct sources. Thus,

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a well-designed experimental approach in combination with the right microarray chip will be invaluable in studying, for example, the following: • differences in gene expression between cystic fibrosis (CF) and non-CF patients or animal models in a tissue- or a celltype-specific manner; • changes in mRNA expression profile of a tissue or a cell type in response to an intervention or as CF disease progresses; • genotype/phenotype correlations; • effects of modifier genomic loci; • microbiome of the CF or non-CF airway; and • effectiveness of a treatment in correcting the basic defect in CF. This chapter takes the reader through all the steps involved in conducting a successful microarray experiment. While for every technique there are alternatives, the authors recommend kits and protocols that have worked repeatedly and provided reproducible results. Furthermore, this chapter is written from the perspective of using an Affymetrix GeneChip platform (Affymetrix, Inc.) and thus recommends following the manufacturer’s protocol where applicable. The authors also reference a number of published studies that have used microarray technology to ask a variety of questions pertaining to the field of CF (4–17). These mRNA expression profile studies have been published using samples from model cell lines, primary airway epithelial cell cultures, animal models, and human samples (4–17). These references are meant purely as a guide, to help investigators design appropriate experiments depending on the question they wish to address. To date, the field has not seen meta-analysis approaches where all existing microarray data are compared. To achieve this end a variety of tools are required to normalize, compare, and mine these diverse data sets, which will be addressed (18, 19). Although beyond the scope of this chapter, investigators are encouraged to consider the option of RNA deep sequencing (RNA-seq) as an alternative to microarrays. A benefit of deep sequencing is the absence of hybridization bias that is associated with microarrays, allowing the investigator to “assay all RNA species” instead of just the probes designed for the array. A variety of platforms are now available (e.g., Illumina Genome Analyzer, Illumina HiSeq 2000 Roche FLX 454 Genome Sequencer, ABI SOLiD) that can be adapted to generate the mRNA expression profiles from samples (20, 21). Total RNA from samples can be processed using commercially available kits to create a qualitative and semi-quantitative expression profile (see Note 10). Deep sequencing is a rapidly emerging technology that is receiving increasing applications as the associated costs decline.

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2. Materials 2.1. General Requirements

1. –20 and –80◦ C freezers, ice, RNase-free water, RNaseZAP (Ambion). 2. RNase-free 1.5- and 2.0-ml tubes.

2.2. Collection and Long-Term Storage of Tissues and Cells for Microarray Analysis

1. RNAlater RNA Stabilization Reagent (Ambion). 2. RNAlater-ICE RNA Stabilizing Reagent (Ambion) (for liquid nitrogen flash-frozen samples).

2.3. Preparation of Samples for RNA Isolation 2.3.1. Mortar and Pestle/Liquid Nitrogen Method

1. Mortar, pestle, stainless steel spatula, liquid nitrogen, RNaseZAP (Ambion).

2.3.2. Tissue Homogenization

1. Motorized tissue homogenizer, double-distilled water, 100% ethanol, 25% ethanol, RNaseZAP, RNase-free water, 12 mm × 75-mm glass tubes.

2.4. RNA Isolation 2.4.1. TRIzol/TRI Reagent Solution

2.4.2. mirVana miRNA Isolation Kit (Ambion)

2.5. RNA Quality and Optional Cleanup

1. TRIzol reagent (Invitrogen) or TRI reagent (Ambion), refrigerated centrifuge, chloroform, isopropanol, 75% ethanol. 1. Pre-heated (95◦ C) nuclease-free water, sterile RNase-free blades, 5-ml RNase-free tubes. 1. Agilent Model 2100 Bioanalyzer (Agilent Technologies). 2. Qiagen RNeasy Mini Kit (Qiagen). 3. RNase-free DNase kit (Any manufacturer of choice).

2.6. RNA Storage

1. Glycogen, 3 M NaOAc (pH 5.2), pre-chilled (–20◦ C) 100% ethanol (to precipitate RNA).

2.7. Microarray Experiment 2.7.1. Affymetrix Sample Preparation and Microarray Analysis

1. Affymetrix GeneChip one-cycle (Affymetrix, Inc., Santa Clara, CA).

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2. Affymetrix GeneChip (as per user requirement; Affymetrix). 3. Affymetrix Model 450 Fluidics Station. 4. Affymetrix Model 3000 Scanner.

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2.7.2. NuGEN Pico/Exon Method Procedure

1. NuGEN WT-Ovation Pico RNA Amplification System, v.1.0 (NuGEN Technologies, Inc.). 2. WT-Ovation Exon Module, v.1.0 (NuGEN). 3. Qiagen Min Elute Kit (Qiagen). 4. FL-Ovation cDNA Biotin Module V2 kit (NuGEN). 5. Streptavidin–phycoerythrin stain (Molecular Probes, Inc.). 6. Anti-streptavidin antibody (Vector Laboratories). 7. Affymetrix Model 450 Fluidics Station. 8. Affymetrix Model 3000 Scanner. 9. GeneChip Operating Software (GCOS), v.1.4.

2.8. Candidate Gene Discovery Tools 2.8.1. Gene Pattern

Unsupervised Hierarchical Clustering (22).

2.8.2. Gene Set and Pathway Analysis of Candidate Genes

1. Ingenuity pathway analysis (IPA) (23). 2. Gene set enrichment analysis (GSEA) (24). 3. Database for annotation, visualization, and integrated discovery (DAVID) (25). 4. GeneGo MetaCore (26). 5. STRING and related databases (27, 28, 29).

3. Methods 3.1. Collection and Long-Term Storage of Tissue and Cells for Microarray Analysis 3.1.1. RNAlater RNA Stabilization Reagent (Ambion)

(a) It is recommended that tissues be cut into small bits of ∼5 mm3 size, allowing for better preservation of the sample and easy access to tissue later on (see Note 1). (b) Label and fill 2 ml cryo-vials with 500 μl of RNAlater reagent and place not more than 4–5 pieces of tissue per tube. (c) Top off the vial with RNAlater solution and store overnight at 4◦ C. The following morning, store the vials at –80◦ C for long-term storage.

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(d) Primary air–liquid interface (ALI) epithelial cell cultures may also be stored in the following manner. Cut out the membrane containing the cells and drop not more than four filters into a cryo-vial containing 1 ml of RNAlater reagent. (e) To remove frozen tissue for analysis, place the vial in an ice bucket until the RNAlater thaws. Wash the tissue pieces well in sterile RNase-free water. 3.1.2. RNAlater-ICE (Ambion) (see Note 2)

(a) It is recommended that samples be cut into small bits of ∼5 mm3 size before freezing in liquid nitrogen. (b) Soak the frozen tissue in RNAlater-ICE at –20◦ C overnight to allow complete permeation of tissue. Samples may be stored indefinitely at –20◦ C in this state. (c) RNAlater-ICE has a blue dye to help distinguish between RNAlater-ICE-untreated and RNAlater-ICE-treated sample. Thus, it is recommended to wash the sample pieces in sterile RNase-free water before RNA extraction.

3.2. Preparation of Samples for RNA Isolation 3.2.1. Mortar and Pestle/Liquid Nitrogen Method

(a) Clean the mortar, pestle, and spatula. Make sure they are RNase free. (b) Chill the mortar, pestle, and spatula in a dry ice ethanol bath. (c) Remove frozen tissue from –80◦ C. Weigh out tissue to be processed before homogenizing so as to calculate correct reagent amounts for the sample (see Note 3). (d) After weighing, place the tissue in the mortar and add liquid nitrogen. When the liquid nitrogen stops bubbling, the sample is completely frozen. (e) Grind the tissue into a fine powder with the pestle. (f) Transfer the powder to an RNase-free, 1.5-ml tube using the chilled spatula and add lysis/binding buffer depending on the RNA isolation protocol being used.

3.2.2. RNAlater or RNAlater-ICE Method

(a) Remove tissue from RNA stabilization solution and weigh out the required amount (see Note 3). (b) Rinse tissue in sterile, nuclease-free water (see Note 4).

3.2.3. Tissue Homogenization

(a) Use a handheld tissue homogenizer (Tissue-Tearor, PotterElvehjem tissue grinder) attached to a variable speed 3/8-in. drill. (b) Wash the homogenizer in the following solutions between samples, in the following order: double-distilled

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H2 O, 100% EtOH, 25% EtOH, double-distilled H2 O, RNaseZAP, RNase-free H2 O. (c) Label glass tubes (12 mm × 75 mm), add 1.0 ml homogenization buffer (TRIzol, lysis buffer, etc.) to each tube, and pre-chill tubes in ice. (d) Transfer required tissue sample from RNAlater or RNAlater-ICE into glass tube containing homogenization buffer. Recommended tissue sample size: approx. three pieces of 5 mm3 tissue specimens. (e) Tubes containing the tissue and the homogenization buffer must be kept in an ice bucket during the homogenization process. (f) Twelve to 15 passes of the homogenizer through the sample should homogenize the sample completely. Avoid heating the sample (see Note 5). (g) Wash the homogenizer (as in step 1) before using for next sample. 3.3. RNA Isolation 3.3.1. TRIzol/TRI Reagent Solution Methodology

(a) Homogenize sample as described above. Transfer homogenate to a 1.5-ml tube. Add 1 ml TRIzol reagent and mix thoroughly by vortexing. Let the tube sit for 5 min at 4◦ C. (b) Add 200 μl chloroform, shake vigorously for 15 s, let stand for 5 min at room temperature, shake again. Centrifuge at 16,000×g for 15 min at 4◦ C. (c) Transfer upper phase to a new tube, be very careful not to touch or disturb the interface as it contains RNases (see Note 6). (d) Add 500 μl isopropanol, shake. Store for 30 min at –20◦ C. This is a good stopping point and samples may be stored overnight at –80◦ C if required. (e) Centrifuge at 16,000×g for 10 min at 4◦ C. (f) Wash the pellet with ice-cold 75% ethanol, vortex briefly. (g) Centrifuge at 7,500×g for 10 min, remove supernatant, and air-dry the pellet (or use a Speed-Vac). (h) Dissolve the pellet in 50 μl RNase-free H2 O and heat at 65◦ C for 10 min to completely dissolve the RNA. (i) Quantitate the RNA and store at –80◦ C.

3.3.2. mirVana miRNA Isolation Kit (Ambion) Method

Although this kit is sold as a small RNA isolation kit, it has a very effective and reproducible total RNA isolation protocol. We recommend the use of the manufacturer’s protocol to isolate total RNA from both tissues and cells grown on plastic (see Note 7).

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RNA from primary air–liquid interface (ALI) cultures of airway epithelial cells may be prepared using the mirVANA protocol with the following variation: (a) Using a sterile blade, cut out the filters from culture plate inserts on which the cells are growing. (b) Place a maximum of four filters into a 5-ml tube and add 1.0 ml lysis/binding buffer. (c) Keep on ice for 2 min. Vortex for 30 s. Repeat three times. (d) Transfer all lysis/binding buffer to a fresh 2.0-ml tube. (e) Follow the manufacturer’s total RNA isolation protocol in the mirVANA kit.

3.4. RNA Quality and Optional Cleanup

The authors recommend the DNase treatment of RNA at this stage. The use of a RNase-free DNase kit from any manufacturer will efficiently remove DNA contamination that can confound data in any downstream application. It is recommended to test the quality of RNA isolated on an Agilent Model 2100 Bioanalyzer (Agilent Technologies). Only samples with an RNA integrity number (RIN) over 7.0 should be submitted for microarray analysis. If consistently poor RIN values are achieved, any commercially available RNA cleanup protocol may be used to improve the purity of the sample. A recommended kit is the Qiagen RNeasy Mini Kit (see Note 9).

3.5. RNA Storage (see Note 8)

Short-term storage: RNA dissolved in RNase-free water at –20 or –80◦ C. Long-term storage: RNA may be stored at –20◦ C as ethanol precipitates.

3.6. Considerations in Designing a Microarray Experiment (See Note 11) 3.6.1. Confounding Variables

In order to minimize every possible origin of variation introduced by experimental design, investigators are encouraged to avoid, as far as possible, the following common sources: (1) different lots of reagents including microarrays themselves; (2) different sources or protocols utilized to obtain the experimental samples; (3) different methods in preparing and storing RNA; (4) different people preparing, labeling, and hybridizing the RNA; (5) changes in tissue and RNA integrity of samples over long storage; and (6) performing the hybridizations on different days.

3.6.2. Unknown Confounders

An additional confounding issue that arises with human samples is the potential for differential probe affinity due to variations in the underlying genomic sequence. For example, a single nucleotide

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variation from a G to an A may significantly alter the affinity of several of the eleven 25-nt probes within a probe set. This is not an issue when dealing with a single, highly inbred organism. However, even in highly inbred organisms, experiments that deal with genetic crosses between two strains (e.g., C57BL/6 and DBA2 mice) will have similar probe affinity-based variations. 3.6.3. Batch Effect

There is a practical limit to the capacity of any facility to perform a large number of microarray hybridizations at the same time. If the sample size of the study is large, investigators are recommended to design their experiment to also minimize the confounding variations that arise due to the performance of hybridizations on different days (batch effect). One such strategy is to rearrange the samples such that each batch of hybridizations represents an equal number of samples across all groups being studied. In the case of replicate samples, these should be run on different days to aid in ascertaining the variability between runs.

3.7. Microarray Experiment

Microarray hybridizations are performed by the following two methods at the University of Iowa DNA Core Facility (see Note 12).

3.7.1. Affymetrix Sample Preparation and Microarray Analysis

(a) Only RNA samples that attain a minimum of 7.0 RIN using the Agilent 2100 Bioanalyzer (Agilent Technologies) are processed. (b) Total RNA (5 μg) is processed using the Affymetrix GeneChip one-cycle target labeling kit (Affymetrix) according to the manufacturer’s recommended protocols. (c) The resultant biotinylated cRNA is fragmented and then hybridized to the Affymetrix GeneChip (GeneChip Porcine Genome Array or the GeneChip Human Genome U133 Plus 2.0 array). (d) The arrays are washed, stained, and scanned using the Affymetrix Model 450 Fluidics Station and Affymetrix Model 3000 scanner using the manufacturer’s recommended protocols.

3.7.2. NuGEN Pico/Exon Method Procedure

(a) RNA quality is assessed using the Agilent Model 2100 Bioanalyzer (Agilent Technologies) and a total RNA within the range of ≥500 pg to ≤50 ng is used. (b) The RNA is processed using the NuGEN WT-Ovation Pico RNA Amplification System, v.1.0 along with the WT-Ovation Exon Module, v.1.0 (NuGEN Technologies) according to the manufacturer’s recommended protocols. This generates sense target (ST)-cDNA. (c) After purification of the ST-cDNA yield (Qiagen Min Elute Kit), 5 μg of ST-cDNA is fragmented and labeled with the FL-Ovation cDNA Biotin Module V2 kit (NuGEN

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Technologies) and combined with hybridization control oligomer (B2) and control cRNAs (bioB, bioC, bioD, and creX) in hybridization buffer and hybridized with an Affymetrix GeneChip as per the manufacturer’s recommended protocols. (d) The arrays are washed and stained with streptavidin– phycoerythrin (Molecular Probes). The signal is amplified with an anti-streptavidin antibody (Vector Labs) using the Affymetrix Model 450 Fluidics Station. (e) Arrays are scanned using the Affymetrix Model 3000 (7G) scanner and the data collected using the GeneChip Operating Software (GCOS), v.1.4. 3.8. General Concepts in Data Analysis 3.8.1. Normalization

A critical component in the analysis of microarray data is normalization of the expression array data. Normalization is the process through which the summarized image data from the CEL files are transformed into numerical values that are comparable across arrays. While early strategies are relatively simple (e.g., global scaling), modern protocols use programs such as RMA (30), GCRMA (31), and PLIER (32). These methods normalize all arrays simultaneously, allowing for variability of intensity to be computationally corrected (see Note 13).

3.8.2. Quality Control

As in any experiment, it is important to implement quality control metrics to isolate and remove erroneous data. The most common techniques for microarray data sets include assessment of any embedded control probe sets, assessment of RNA degradation, and the utilization of pattern-finding computational methods to identify outliers. Affymetrix arrays have a set of probe sets to several housekeeping genes (e.g., GAPDH) allowing relative comparison of intensity of the 3 and 5 probe sets. Because 3 -end labeling is used to generate the labeled cRNA, all molecules should hybridize to the 3 probe set and only the handful that generate very long labeled products should hybridize to the 5 probe set. A similar technique may be used to assess overall RNA degradation among all probe sets. With this procedure, each of the 11 probes for every probe set is categorized based upon their relative position (most 5 to most 3 ) in the gene structure. A plot of the average intensity values for each of the 11 categories should have the highest value at the 3 -end. A characteristic dip is observed in the 3 most probe categories in case of RNA degradation. Finally, pattern-finding methods such as PCA (principal component analysis) and hierarchical clustering may be used to identify samples that are drastically different from others of the same class or category.

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3.8.3. Differential Expression

The most common microarray analysis is an assessment of differential expression. This identifies the set of genes that are expressed at significantly different levels. Many methods are available to determine if a gene is differentially expressed. Two such methods grounded in statistics are the student’s t-test and ANOVA (analysis of variance). In general, ANOVA is the more generalized approach, allowing for more than two classes to be analyzed simultaneously and for multiple explanatory variables (if needed). Both methods return a p value, representing the significance of the differential expression. Because genome-wide experiments are characterized by extensive hypothesis testing (one per probe set), approaches designed to compensate for multiple hypothesis testing may be overly conservative (e.g., Bonferroni correction). Therefore, methods such as the false discovery rate (FDR) are recommended (33). Such methods attempt to control the number of expected false positives, i.e., the proportion of genes expected to be incorrectly present in the list of significant (differentially expressed) genes.

3.9. Candidate Gene Discovery Tools

Here, we provide a list of publicly available and proprietary analysis tools that have been selected for their individual merits. These resources come with detailed instructions that are simple to follow and user friendly, but are by no means exhaustive. Thus, the following sections do not provide instructions on how to use these web-based resources but highlight their individual merits and how you may adapt them to your specific needs.

3.9.1. Gene Pattern

Hosted and developed by the Broad Institute, MIT, Gene Pattern is an open-access online analysis resource (22). It is a compilation of modules, each focused at a particular format of analysis. Most useful from the perspective of analyzing microarray data, the cluster analysis and gene set enrichment analysis tools have been widely used by our research groups. Clustering is a method of unsupervised learning, widely used to segregate samples into groups based on their gene expression profiles. The hierarchical clustering tool in Gene Pattern has been used by our group for pattern recognition in microarray data. Hierarchical clustering helps to segregate samples in an unbiased manner into groups based purely on the expression pattern of samples being tested (see Fig. 12.1a). Thus, this tool functions as a first-pass analysis algorithm for investigators to assess if their samples segregate based on genotype, tissue, gender, age, or non-biological confounding factors like batch effects.

3.9.2. Analysis of Variance (ANOVA)

The one-way ANOVA analysis has been used by our group to determine differences in gene expression among independent groups of samples. Typically, the output consists of all genes in

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the microarray experiment, with each gene accompanied by a fold change and a p value (or FDR) to indicate the amount of change and the significance of change in gene expression across the independent groups of samples. Thus, a candidate gene list may be made based on the fold change and significance of differential expression properties of each gene. If candidate gene lists are large, it is recommended to either make the p value more stringent or consider the FDR q value instead of the p value (see Fig. 12.1b,c). Furthermore, cutoffs based on fold change may help narrow down the gene list to the genes that change by the greatest fold. The authors used the Partek Genomics Suite (36) for the ANOVA analysis. 3.9.3. Gene Set and Pathway Analysis of Candidate Genes

While identification of candidate genes is essentially the crux of a well-planned microarray experiment, an investigator is often confronted with the scenario of having either too many candidates or candidates of unknown relevance to CFTR or CF. In this respect, it helps to look at genes from the perspective of their functional relationships based on knowledge of pathways, protein interactions, and sequence composition. A variety of manually curated databases exist online (see below), both open-access and commercial source, that classify gene products based on their functional interactions, cellular localizations, sequence similarities, and binding motifs to name a few. While this information does not necessarily hand the investigator answers on a silver platter, it does fill in several missing links and puts the raw data in a format that may provide more biological meaning to the investigator. Described below are gene discovery tools that have been used by the authors. A word of caution: the following online resources are compiled based on published literature involving microarray studies, immunoprecipitation experiments, etc. Thus, there is a level of inherent error in these analysis tools based on the character of the curation and the interests of the developers, and the investigator is recommended to vigorously validate candidates before studying their biological and functional roles.

3.9.3.1. Ingenuity Pathway Analysis (IPA)

IPA is an extensive, manually curated proprietary database, classifying gene products based on their functional interactions with other gene products (23). The power of IPA lies in its userfriendly approach. Any list of genes can be uploaded in the form of a text file. Herein lies its greatest limitation. The gene list is put together by the investigator, thus the utility of the output is limited by the relevance of the input gene list. IPA, based on its vast database of interactions, then classifies genes into networks, filling in the blanks with transcription factors and other proteins to form complete pathways (see Fig. 12.1c). IPA is extremely user friendly because it allows the user to access network information,

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Fig. 12.1. The data set used for this analysis consists of primary well-differentiated airway epithelial cultures isolated from seven different normal human donors, grown at an air–liquid interface (ALI) (34). Half of all primary cultures from each donor were subjected to a pro-inflammatory cytokine cocktail treatment comprising IFN-γ, TNF-α, and IL-1β, at a final concentration of 100 ng/ml each for 24 h (35). Total RNA was isolated and cDNA microarray analysis was performed comparing the gene expression profile of these two sample groups. Presented here are data output samples using the following tools: unsupervised hierarchical clustering (Gene Pattern), gene set enrichment analysis (GSEA), ingenuity pathway analysis (IPA), and a heat map of differentially expressed genes (based on ANOVA). (a) Unsupervised hierarchical clustering: Samples 1–, 3–, 6–, 8–, 5–, 7–, and 9– constitute the “untreated” group, while samples 2+, 4+, 10+, 11+, 12+, 13+, and 14+ are treated with the pro-inflammatory cytokine cocktail. The combined unsupervised hierarchical clustering (22) of the 14 samples reveals 2 distinct clusters. All untreated samples segregate and form a separate cluster, while the cytokine-treated samples segregate into a different cluster. The dendrogram height of each cluster reveals that the sample groups have a distinct gene expression profile that is similar within each group but different between the two groups. (b) Heat map of the most significant differentially expressed genes: The one-way ANOVA analysis tool available in the Partek Genomic Suite (36) was used to compare the gene expression profile of the two sample groups from (a) and

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source literature, and gene product characteristics on site. It also allows the user to modify the presentation to adapt it to the user’s own personal and research requirements. 3.9.3.2. Gene Set Enrichment Analysis (GSEA)

GSEA analyzes microarray data based on a priori defined sets of genes, compiled from published literature describing biochemical pathways and co-expression profiles (24). GSEA stands apart from other analysis algorithms as it looks at pathways and signaling programs as a whole. This enables GSEA to detect whole networks and signaling cascades that might change owing to differences in expression of a few key representative genes of that pathway (see Fig. 12.1d). GSEA draws its strength from the fact that it ranks all genes in the experiment and considers even the smallest change in expression of every gene. Thus, the algorithm compiles the cumulative effect of changes in gene expression within a pathway and determines which gene set has the closest correlation with the phenotype. This complex, three-tier analysis enables the user to view processed data from the perspective of pathways or biological processes and to simultaneously focus on individual genes and their differential expression. Investigators can also develop custom gene sets based on the biology or tissue of their interest and use it with this tool.

 Fig. 12.1. (continued) characterize genes based on their differential expression. Change in expression was rated based on false discovery rate (FDR). By setting an FDR stringency of FDR <0.000001, 30 of the most significant differentially expressed genes were determined and plotted as a heat map using the Cluster 3.0/Java Treeview application (37). Only three genes (lowermost three) decreased in expression in the cytokine-treated samples. The remaining 27 genes in this gene list increased in expression in the cytokine-treated samples. (c) Ingenuity pathway analysis: The one-way ANOVA analysis tool available in the Partek Genomic Suite (36) was used to compare the gene expression profile of the two sample groups from panels A and B and characterize genes based on their differential expression. Change in expression was rated based on p value. The top 500 most significantly differentially expressed genes (lowest p-value) were used in ingenuity pathway analysis (23). Presented here is a gene interaction network involving 29 genes from the 500 gene input and is ranked among the top three enriched networks. Ingenuity is especially useful at identifying nodal genes that influence the expression of a large number of other differentially expressed genes. In this example, TGFB1 is represented as the nodal gene, involved in the direct or indirect regulation of 28 other proteins that were differentially expressed, providing the investigator useful information and direction for future functional experimentation. In this representation, the solid lines represent gene interactions proven by biological experimentations. The dotted lines represent proposed gene interactions based on CHIP experiments, computational predictions of protein interactions, and pull-down assays. (d) Gene set enrichment analysis: On comparing the gene expression profile of the two sample groups using gene set enrichment analysis (GSEA) (24), a total of 987 gene sets were upregulated (p value <0.1%) in the cytokine-treated samples. Of these, 343 gene sets were significantly (FDR <25%) upregulated. Presented here is the enrichment plot of two significantly upregulated gene sets in the cytokine-treated samples (NFκB_INDUCED and TOLL-LIKE_RECEPTOR_SIGNALLING). In each of the enrichment plots, the “negative correlation” and the steep slope of the green “enrichment profile” refer to the “enrichment” of upregulated genes within each gene set, in the cytokinetreated samples. The vertical black lines represent individual genes within each gene set and the accumulation of the black vertical lines toward the right in both gene sets once again represents the “enrichment” of upregulated genes in cytokine-treated samples.

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3.9.3.3. Database for Annotation, Visualization, and Integrated Discovery (DAVID)

The DAVID algorithm is a useful blend of IPA and GSEA, developed and maintained by the NIAID at the NIH (25). It is perfect for users who prefer the computing depth of GSEA but prefer to generate their own gene lists based on ANOVA or other statistical algorithms. Like GSEA, DAVID classifies genes into functionally related gene groups based on their biological function, functional domains and motifs, interacting proteins, pathways, and signaling cascade interactions. This enables the user to visualize genes from multiple different perspectives. Nevertheless, as mentioned earlier, DAVID utilizes a gene list submitted by the user, and this often undermines the relevance of the data generated by DAVID.

3.9.3.4. GeneGo MetaCore

MetaCore is a software suite similar to ingenuity, based on proprietary manually curated literature databases of human protein– protein, protein–DNA, and protein–compound interactions (26). It has been curated to contain known CF-specific interactions (38). MetaCore can be used to arrange user-uploaded gene lists into networks or pathways of user-defined complexity based on functional interactions (see Fig. 12.2a,b). MetaCore also identifies subsets of list genes with particular relevance to GO processes, molecular functions or cellular localizations, and human diseases. Furthermore, list genes and their associated expression data can be superimposed over a collection of 500 interactive maps, including a series of pathway maps and network models specific to CF. Following analysis, high-resolution images of pathways and networks can be exported, and data can be saved online for future reference or reanalysis. As for the previous platforms mentioned, the quality of MetaCore’s output is only as good as the quality of data entered, and unlike GSEA and DAVID, the software package is not open access, although 2-week free trials are available.

3.9.3.5. STRING and Related Databases

A number of additional open-access tools exist which can help to derive biological significance once a list of top candidates from the microarray experiments is generated. Here, we list some generated by the European Molecular Biology Laboratory (EMBL)

 Fig. 12.2. (a) GeneGo maps: This functional map, entitled “Immune response: IFNα/β signalling pathway,” was identified as the most significantly enriched (p = 7.266 × 10−7 ) GeneGo map following analysis of the gene list of 500 significantly regulated genes in cytokine-treated airway epithelial cell cultures. The 10 list genes represented in the 24 protein network are identified by thermometers which, when moused over in MetaCore (26), show respective expression data and p values. GeneGo map legends allow the user to interpret object shapes and colors, and all nodes and edges in the diagram contain hyperlinks to abstracts justifying their inclusion in the network. (b) GeneGo networks: The top 100 most significantly differentially expressed genes (lowest p value) were used in GeneGo MetaCore network analysis. Presented here is a gene interaction network involving 31 genes from the 100 gene inputs. GeneGo (26) uses a curated literature database for its interaction data, allowing functional data for each object to be accessed

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Fig. 12.2. (continued) by clicking on nodes or edges. Based on this information, nodes and edges can be deleted, and new objects can be added at will. The direction and nature of proven protein–protein interactions is represented by the direction and color of connecting arrows, and the shape of each object is representative of protein function. The circular targets shown beside each object give expression values (red for upregulation and blue for downregulation) and p values from the input list and can be visualized by mousing over.

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which are distinguished by their high number of entries and highquality curation as well as for their open-source access: • STRING (search tool for the retrieval of interacting genes/proteins) (27) is a database and web resource dedicated to known and predicted protein–protein interactions, including both physical and functional interactions. The latter are defined as “the specific and meaningful interaction between two proteins that jointly contribute to the same functional process.” The interactions in STRING are derived from four sources: genomic context, high-throughput experiments, (evolutionary conserved) co-expression, and previous knowledge (i.e., the literature in general). STRING quantitatively integrates interaction data (scoring and weighing them) from these sources for a large number of organisms and augments it with predicted interactions. The various subtypes of evidence underlying each interaction are stored separately in the database so that the user can fine-tune the search and the quality of the results to requirements (see Note 14). The current version of STRING (8.0) covers ∼2.6 million proteins from 630 distinct organisms to a total of more than 50 million stored interactions, providing a comprehensive view on protein–protein interactions (39). • STITCH (search tool for interactions of chemicals) (28) is a sister project of the STRING protein–protein interaction tool which searches known and predicted interactions between proteins and chemicals. It compiles information about interactions from metabolic pathways, crystal structures, binding experiments, and drug–target relationships. Compounds are linked to other chemicals and to proteins by: (1) evidence-derived data (i.e., raw results from experiments); (2) other databases; and (3) literature sources. Prediction of relations between chemicals is based on information from phenotypic effects, text mining, and chemical structure similarity, and each proposed interaction can be traced back to the original data sources. STITCH contains interactions for over 68,000 chemicals, including 2200 drugs, and connects them to 1.5 million proteins in 373 different species and their interactions contained in the STRING database (40). • eggNOG (evolutionary genealogy of genes: non-supervised orthologous groups) (29) is a database of orthologous groups of genes identified through reciprocal best BLAST matches. The orthologous groups are annotated with functional descriptions, which are derived by identifying a common denominator for the genes based on their individual textual descriptions, annotated functional categories, and predicted protein domains. The very recently released

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version of the eggNOG database (2.0) counts ∼2.2 million proteins, derived from 630 complete genomes (529 bacteria, 46 archaea, and 55 eukaryotes), functionally describing ∼1.9 million (41). 3.10. Approaches to Validating Candidate Genes

Investigators are recommended to validate their candidate genes before embarking on functional studies. While every effort is made during data analysis to keep false negatives to a minimum, there exists a fine balance between eliminating false negatives and keeping false positives to a minimum, as in all high-throughput approaches. Nevertheless, there is always the chance that the candidate genes selected might be false positive. Validation may be done at the RNA level (real-time RT-PCR, northern blot) and/or at the protein level (Western blot, immunohistochemistry, and quantitative immunofluorescence), or even a functional assay. Eventually, it is up to the investigator to design appropriate validation and functional experiments depending upon the unique protein being studied.

4. Notes 1. Tissue cut into smaller pieces and soaked overnight at 4◦ C in RNAlater RNA Stabilizing Reagent is stored better over a longer period of time owing to better perfusion of tissue with the stabilizing agent. Tissues are best stored at –80◦ C. 2. While flash freezing samples in liquid nitrogen is probably the best method to preserve the RNA composition and integrity of a tissue sample, thawing the sample for tissue homogenization and RNA extraction results in rapid RNA degradation and changes in the RNA profile of the sample. To preserve the merits of flash freezing and to avoid the thawing-associated degradation of RNA, RNAlaterICE may be used as an alternative. 3. RNA yield, in both quality and quantity, varies from tissue to tissue and between each individual RNA preparation. Thus, caution is advised on how much tissue should be used as per RNA preparation. 4. Samples stored in RNAlater-ICE should be washed thoroughly with sterile RNase-free water before RNA extraction to prevent the interference of the blue dye in RNA extraction and downstream processing. 5. When using the handheld tissue homogenizer, it helps to make 12–15 passes through the sample to achieve complete homogenization. If the tissue sample has cartilage or

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is extremely fibrous, it is recommended to chop the tissue into small bits using a sterile blade to further aid in homogenization. 6. During RNA isolation using TRIzol/TRI reagent solutions, be careful not to touch/disturb the interface after spinning at 16,000×g for 15 min at 4◦ C. The white interface contains RNases and if it has been disturbed, it is recommended to vortex the tube and to repeat the spinning step. 7. The mirVana miRNA Isolation Kit sold by Ambion is an excellent kit that can be used to isolate total RNA. The authors routinely used this kit to isolate total RNA from tissues, cells grown on plastic, and primary cell cultures for the use of microarrays, RNA-seq, reverse-transcription QPCR, etc. This kit is reliable and highly reproducible, generating total RNA of very good quality. 8. When storing RNA, always make aliquots. RNA that has been through a freeze–thaw cycle more than twice is inappropriate for analysis. 9. RNA isolation from the pancreas is especially difficult owing to the high concentration of RNases. While the authors have tried a variety of different kits that claim to counter the effect of RNases, our best recommendation is to isolate RNA from fresh pancreatic tissue. Most RNA isolation kits work equally well when processing pancreatic tissue within 5–10 min of harvesting. 10. As mentioned in Section 1, an alternative method to look at the transcriptome is by deep sequencing (RNA-seq). RNA preparation techniques and concerns remain the same for both microarray and RNA-seq technologies. 11. Every microarray facility has limited capacity on the number of samples they can hybridize/process simultaneously. It is advised to work closely with the microarray facility staff and design experiments accordingly to minimize confounding variables. 12. The NuGEN Pico/Exon kit for microarray sample preparation required less RNA than did the Affymetrix sample preparation method. Furthermore, the NuGEN protocol has an amplification step that helps overcome poor RNA quality. These factors may be considered when choosing a sample preparation method. However, the investigator is advised to use the same sample preparation kit throughout the length of the research project. 13. It is important to recall that although normalization allows comparison of probe set intensity values across a set of

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hybridizations, it does not allow accurate comparison of probe set intensity between probe sets. Although relative measurements are possible (e.g., increased intensity after treatment), different probe affinities for each probe set make generalized comparison of the absolute probe set intensity values intractable. 14. STRING includes resources from other databases, namely MINT (the Molecular INTeraction database), HPRD (Human Protein Reference Database), BIND (Biomolecular Interaction Network Database), DIP (Database of Interacting Proteins), BioGRID (The Biological General Repository for Interaction Datasets), KEGG (Kyoto Encyclopedia of Genes and Genomes), Reactome (a curated knowledge base of biological pathways), IntAct (opensource database system and analysis tools for protein interactions), EcoCyc (Encyclopedia of Escherichia coli K-12 Genes and Metabolism), NCI (Nature Pathway Interaction) Database, and Gene Ontology (GO) protein complexes. The new STRING application programming interface (API) facilitates the integration of STRING into network tools like Cytoscape and allows retrieval of individual STRING entries into various output formats. References 1. Churchill, G. A. (2002) Fundamentals of experimental design for cDNA microarrays. Nat Genet 32 Suppl, 490–495. 2. Duggan, D. J., Bittner, M., Chen, Y., Meltzer, P., and Trent, J. M. (1999) Expression profiling using cDNA microarrays. Nat Genet 21, 10–14. 3. Freeman, W. M., Robertson, D. J., and Vrana, K. E. (2000) Fundamentals of DNA hybridization arrays for gene expression analysis. Biotechniques 29 1042–1046, 1048–1055. 4. Hybiske, K., Ichikawa, J. K., Huang, V., Lory, S. J., and Machen, T. E. (2004) Cystic fibrosis airway epithelial cell polarity and bacterial flagellin determine host response to Pseudomonas aeruginosa. Cell Microbiol 6, 49–63. 5. Perez, A., and Davis, P. B. (2004) Gene profile changes after Pseudomonas aeruginosa exposure in immortalized airway epithelial cells. J Struct Funct Genomics 5, 179–194. 6. Reiniger, N., Ichikawa, J. K., and Pier, G. B. (2005) Influence of cystic fibrosis transmembrane conductance regulator on gene expression in response to Pseudomonas aeruginosa infection of human bronchial epithelial cells. Infect Immun 73, 6822–6830.

7. Wright, J. M., Zeitlin, P. L., Cebotaru, L., Guggino, S. E., and Guggino, W. B. (2004) Gene expression profile analysis of 4-phenylbutyrate treatment of IB3-1 bronchial epithelial cell line demonstrates a major influence on heat-shock proteins. Physiol Genomics 16, 204–211. 8. Xu, W., Zheng, S., Goggans, T. M., Kiser, P., Quinones-Mateu, M. E., Janocha, A. J., et al. (2006) Cystic fibrosis and normal human airway epithelial cell response to influenza a viral infection. J Interferon Cytokine Res 26, 609–627. 9. Dasgupta, N., Wolfgang, M. C., Goodman, A. L., Arora, S. K., Jyot, J., Lory, S., et al. (2003) A four-tiered transcriptional regulatory circuit controls flagellar biogenesis in Pseudomonas aeruginosa. Mol Microbiol 50, 809–824. 10. Haston, C. K., Cory, S., Lafontaine, L., Dorion, G., and Hallett, M. T. (2006) Straindependent pulmonary gene expression profiles of a cystic fibrosis mouse model. Physiol Genomics 25, 336–345. 11. Srivastava, M., Eidelman, O., and Pollard, H. B. (1999) Pharmacogenomics of the cystic fibrosis transmembrane conductance regulator (CFTR) and the cystic fibrosis drug CPX

212

12.

13.

14.

15.

16.

17.

18.

19.

20.

21. 22. 23.

Ramachandran et al. using genome microarray analysis. Mol Med 5, 753–767. Virella-Lowell, I., Herlihy, J. D., Liu, B., Lopez, C., Cruz, P., Muller, C., et al. (2004) Effects of CFTR, interleukin-10, and Pseudomonas aeruginosa on gene expression profiles in a CF bronchial epithelial cell Line. Mol Ther 10, 562–573. Wolfgang, M. C., Jyot, J., Goodman, A. L., Ramphal, R., and Lory, S. (2004) Pseudomonas aeruginosa regulates flagellin expression as part of a global response to airway fluid from cystic fibrosis patients. Proc Natl Acad Sci USA 101, 6664–6668. Wright, J. M., Merlo, C. A., Reynolds, J. B., Zeitlin, P. L., Garcia, J. G., Guggino, W. B., et al. (2006) Respiratory epithelial gene expression in patients with mild and severe cystic fibrosis lung disease. Am J Respir Cell Mol Biol 35, 327–336. Xu, Y., Clark, J. C., Aronow, B. J., Dey, C. R., Liu, C., Wooldridge, J. L., et al. (2003) Transcriptional adaptation to cystic fibrosis transmembrane conductance regulator deficiency. J Biol Chem 278, 7674–7682. Xu, Y., Liu, C., Clark, J. C., and Whitsett, J. A. (2006) Functional genomic responses to cystic fibrosis transmembrane conductance regulator (CFTR) and CFTR(delta508) in the lung. J Biol Chem 281, 11279–11291. Zabner, J., Scheetz, T. E., Almabrazi, H. G., Casavant, T. L., Huang, J., Keshavjee, S., et al. (2005) CFTR DeltaF508 mutation has minimal effect on the gene expression profile of differentiated human airway epithelia. Am J Physiol Lung Cell Mol Physiol 289, L545– L553. Rhodes, D. R., Yu, J., Shanker, K., Deshpande, N., Varambally, R., Ghosh, D., et al. (2004) Large-scale meta-analysis of cancer microarray data identifies common transcriptional profiles of neoplastic transformation and progression. Proc Natl Acad Sci USA 101, 9309–9314. Cahan, P., Rovegno, F., Mooney, D., Newman, J. C., St Laurent, G., 3rd, and McCaffrey, T. A. (2007) Meta-analysis of microarray results: challenges, opportunities, and recommendations for standardization. Gene 401, 12–18. Mortazavi, A., Williams, B. A., McCue, K., Schaeffer, L., and Wold, B. (2008) Mapping and quantifying mammalian transcriptomes by RNA-Seq. Nat Methods 5, 621–628. Wang, Z., Gerstein, M., and Snyder, M. (2009) RNA-Seq: a revolutionary tool for transcriptomics. Nat Rev Genet 10, 57–63. http://www.broadinstitute.org/cancer/ software/genepattern/ http://www.ingenuity.com/

24. 25. 26. 27. 28. 29. 30.

31.

32. 33.

34.

35.

36. 37. 38.

39.

40.

41.

http://www.broadinstitute.org/gsea/ http://david.abcc.ncifcrf.gov/ http://www.genego.com/ http://string-db.org/ http://stitch.embl.de/ http://eggnog.embl.de/ Irizarry, R. A., Hobbs, B., Collin, F., BeazerBarclay, Y. D., Antonellis, K. J., Scherf, U., et al. (2003) Exploration, normalization, and summaries of high density oligonucleotide array probe level data. Biostatistics 4, 249–264. Wu, Z., Irizarry, R. A., Gentleman, R., Murillo, F. M., and Spencer, F. (2004) A model based background adjustment for oligonucleotide expression arrays. J Am Stat Assoc 99 468, 909–917. http://www.affymetrix.com/support/ technical/technotes/plier_technote.pdf Pawitan, Y., Michiels, S., Koscielny, S., Gusnanto, A., and Ploner, A. (2005) False discovery rate, sensitivity and sample size for microarray studies. Bioinformatics 21, 3017–3024. Karp, P. H., Moninger, T. O., Weber, S. P., Nesselhauf, T. S., Launspach, J. L., Zabner, J., et al. (2002) An in vitro model of differentiated human airway epithelia. Methods for establishing primary cultures. Methods Mol Biol 188, 115–137. Winder, A. A., Wohlford-Lenane, C., Scheetz, T. E., Nardy, B. N., Manzel, L. J., Look, D. C., et al. (2009) Differential effects of cytokines and corticosteroids on Toll-like receptor 2 expression and activity in human airway epithelia. Respir Res 10, 96. http://www.partek.com/ http://bonsai.ims.u-tokyo.ac.jp/~mdehoon/ software/cluster/software.htm#ctv Wright, J. M., Nikolsky, Y., Serebryiskaya, T., and Wetmore, D. R. (2009) MetaMiner (CF): a disease-oriented bioinformatics analysis environment. Methods Mol Biol 563, 353–367. Jensen, L. J., Kuhn, M., Stark, M., Chaffron, S., Creevey, C., Muler, J., et al. (2009) STRING 8 – a global view on proteins and their functional interactions in 630 organisms. Nucleic Acids Res 37, D412–D416. Kuhn, M., von Mering, C., Campillos, M., Jensen, L. J., and Bork, P. (2008) STITCH: interaction networks of chemicals and proteins. Nucleic Acids Res 36, D684–D688. Muller, J., Szklarczyk, D., Julien, P., Letunic, I., Roth, A., Kuhn, M., et al. (2009) eggNOG v2.0: extending the evolutionary genealogy of genes with enhanced nonsupervised orthologous groups, species and functional annotations. Nucleic Acids Res.

Chapter 13 Quantitative Differential Proteomics of Cystic Fibrosis Cell Models by SILAC (Stable Isotope Labelling in Cell Culture) Ida Chiara Guerrera, Mario Ollero, Diane-Lore Vieu, and Aleksander Edelman Abstract Differential proteomics represents an enticing strategy to unmask the proteins involved in CF pathogenesis and to discover potential therapeutic targets and/or markers of disease progression. Quantitative proteomics is possible nowadays owing to the recent progress in protein labelling and/or in label-free approaches, combined to sensitive detection by mass spectrometry (MS). In this chapter, we present one strategy to perform differential quantitative proteomic studies on different cellular compartments of proliferating cell lines expressing wild-type (WT) CFTR and F508del-CFTR using stable isotope labelling in cell culture (SILAC). Key words: SILAC, DRM, nanoHPLC, MS, MS/MS.

1. Introduction The application of mass spectrometry (MS)-based techniques for qualitative and quantitative analyses of proteome in samples derived from complex mixtures has had a big impact on investigations addressing the pathogenesis of several diseases (1). One of the first applications of comparative proteomics was based on bidimensional SDS-polyacrylamide gel electrophoresis (2D SDSPAGE) protein separation (2–5). Although proven powerful in the separation of protein isoforms, this strategy presents some major pitfalls, such as the inability to separate membrane proteins and the low yield of globally identified and quantified proteins for a given cellular fraction, owing especially to the high amounts of proteins required. M.D. Amaral, K. Kunzelmann (eds.), Cystic Fibrosis, Methods in Molecular Biology 742, DOI 10.1007/978-1-61779-120-8_13, © Springer Science+Business Media, LLC 2011

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In recent years, we have attended to continuous developments in relative protein quantification based on MS measurements. Strategies allowing high-throughput identification and quantification of proteins include stable isotope labelling, chemical tagging and, more recently, label-free techniques (6). Most of the pitfalls encountered in 2D SDS-PAGE quantitative proteomics are now overcome, at the expense of protein isoform characterization. The main problem that the different proteomic approaches have in common is still the inability to identify and/or quantify low-abundant and membrane proteins. This is the case for CFTR, which falls into both categories. Its function and regulatory features lie within membrane and/or microdomain compartments (7–9). To gain insight into the proteins regulating CFTR functions, more sensitive methods for identification and quantification are needed. One possible solution is to enrich the sample in the protein of interest as much as possible before starting the proteomics experiment. This can be obtained by purifying the subcellular structures where the protein is expected to be localized. Consequently, in this chapter we present different proteomic PLAN

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Fig. 13.1. General strategy for SILAC-based quantitative proteomics of total, microdomain and microsomal proteins in proliferating cells.

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strategies that could be applied to the analysis of microsomal, microdomain-associated and plasma membrane proteins in cellular CF models. As an example of quantitative proteomic method, we describe a protocol for stable isotope labelling of amino acids in cell culture (SILAC) applied to proliferating transfected HeLa cells (see Fig. 13.1). This protocol could virtually be applied to every proliferating cell line, but not to primary cells in culture, for which the use of chemical tagging of proteins, such as ITRAQ (isobaric tag for relative and absolute quantitation), is recommended (10).

2. Materials 2.1. Cell Culture and SILAC

1. Dulbecco’s modified Eagle’s medium lacking L-arginine and L-lysine (Thermo scientific) supplemented with penicillin/streptomycin (HyClone, Ogden, UT) and 10% dialysed foetal bovine serum (Thermo Scientific). 2. Trypsin solution (0.25%) with 1 mM ethylenediaminetetraaceticacid (EDTA) (HyClone). 3. Dulbecco’s (Invitrogen).

phosphate-buffered

saline

(D-PBS)

4. Normal isotopic abundance Scientific).

L -arginine

(Arg0) (Thermo

5. Normal isotopic abundance Scientific).

L -lysine

(Lys0) (Thermo

6. Normal isotopic abundance Aldrich).

L -proline

(Pro0) (Sigma-

7. [13 C6 ]-L-Arginine (Arg6) (Thermo Scientific). 8. [13 C6

15 N ]- L -Arginine 4

(Arg10) (Thermo Scientific).

9. Light SILAC media: Arg- and Lys-free DMEM medium (Thermo Scientific) supplemented with Pro0, Arg0 and Lys0. 10. Medium SILAC media: Arg- and Lys-free DMEM medium supplemented with Pro0, Arg6 and Lys0. 11. Heavy SILAC media: Arg- and Lys-free DMEM medium supplemented with Pro0, Arg10 and Lys0. 2.2. Total Protein Extraction

1. Dulbecco’s (Invitrogen).

phosphate-buffered

saline

(D-PBS)

2. Lysis buffer: 0.1% SDS, 50 mM Tris–HCl (pH 7.5), 125 mM NaCl, 1% Triton X-100, 1% Na deoxycholate, protease inhibitor cocktail (Roche Applied Science, Laval, QC).

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2.3. Microsomal Protein Extraction

1. Rubber cell scrapers (Sarstedt, Montreal, QC). 2. Dulbecco’s phosphate-buffered saline (D-PBS) (Invitrogen). 3. Lysis buffer: 10 KCl, 10 Tris (pH 7.4), 1.5 mM MgCl2 , protease inhibitors. 4. Hand or mechanical homogenizer. 5. 1-mL syringe with 19-G and 23-G needle.

2.4. Microdomain Protein Extraction

1. Lysis buffer containing 1% Triton X-100 (Sigma-Aldrich) in 25 mM morpholinoethanesulphonic acid (MES, SigmaAldrich) at pH 6.5. Protease inhibitor cocktail (Roche Applied Science, Laval, QC) added fresh. Solution must be kept ice cold. 2. DC protein assay (Bio-Rad). 3. MBS (MES-buffered saline): 25 MES (pH 6.5), 150 mM NaCl. 4. 90% Sucrose in MBS. 5. 5% Sucrose in MBS. 6. 3-mL syringe with 25-G needle. 7. Rubber cell scrapers (Sarstedt, Montreal, QC). 8. Semimicrovolume disposable polystyrene cuvettes (BioRad, Hercules, CA). 9. Ultracentrifuge XL-70 with SW41Ti rotor (Beckman) or equivalent.

2.5. “In-Solution” Tryptic Digestion

1. Water (LiChrosolv grade; Merck or Fischer Scientific). 2. Acetonitrile (HPLC gradient grade; Merck or Fischer Scientific). 3. Ethanol (HPLC gradient grade; Merck or Fischer Scientific). 4. Formic acid (reagent grade; Merck). 5. Trifluoroacetic acid (Uvasol grade; Merck). 6. Sodium acetate (Sigma-Aldrich). 7. Invitrosol LC/MS protein solubilizer 5× (Invitrogen). 8. RapiGest SF surfactant (Waters). 9. Ammonium bicarbonate (Sigma-Aldrich) 200 mM stock, prepare daily 50–100 mL and discard after use. 10. 10 mM dithiothreitol (DTT; Sigma-Aldrich) in 50 mM ammonium bicarbonate, prepare shortly before use.

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11. 55 mM Iodoacetamide (IAA; Sigma-Aldrich) in 50 mM ammonium bicarbonate, prepare shortly before use and keep in the dark. 12. Trypsin (porcine, sequencing grade, modified; Promega Corp.), final concentration of 13 ng/μl in 25 mM ammonium bicarbonate containing 5 mM CaCl2 . Keep at 4◦ C at all times. Make shortly before use; discard unused volume. Trypsin stock solution (1 mM HCl) must be aliquoted and stored at –20◦ C before use. 13. Extraction buffer: 1% TFA, 50% acetonitrile. 14. Acidification solution: 3% acetonitrile, 1% TFA and 0.5% acetic acid 2.6. Peptide OFFGEL Separation

1. 3100 OFFGEL Fractionator. 2. Peptides OFFGEL stock solution (1.25×): Mix 6 mL glycerol solution and 600 μl OFFGEL ampholytes (pH 3–10) (Agilent or GE Healthcare) in 50 mL of dH2 O. Peptide OFFGEL stock solution can be stored in smaller tubes at –20◦ C for 4 months (to avoid multiple freeze/thaw cycles). 3. Freshly prepare OFFGEL solution (1×): 700 μl to be used as peptide IPG strip rehydration solution and 1800 μl to redissolve dried peptides. 4. Mineral oil (cover fluid) (Agilent or GE Healthcare). 5. IPG strips 12 cm (stored at –20◦ C) (Agilent or GE Healthcare).

2.7. Peptide Separation by NanoLC and MS/MS Analysis

1. NanoHPLC (Ultimate 3000; Dionex). Other nanoHPLC systems could be equally used. 2. Probot microfraction collector (Dionex). 3. Mass spectrometer capable of MS/MS (MALDI TOF/TOF 4800; Applied Biosystems). Other mass spectrometers could be equally used. 4. Sample solution: 0.1% trifluoroacetic acid, 3% acetonitrile in water. 5. Buffer A: 0.1% trifluoroacetic acid in water (HPLC grade; Carlo Erba). 6. Buffer B: 20% buffer A; 80% acetonitrile (HPLC grade; Carlo Erba). 7. PepMapC18 column (Dionex; 3 μm particles, 10 nm pore size, 75 μm i.d.). 8. C18 stop and go extraction (STAGE) tips (Proxeon). 9. Sample buffer: 3% acetonitrile, 1% trifluoroacetic acid.

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10. MALDI matrix, α-cyano-4-hydroxycinnamic acid (CHCA) (Laser Biolabs). The final matrix solution of 2 mg/mL in 70% CAN, 0.1% TFA (Pierce), must be prepared daily. 11. Glu-fibrinopeptide (Sigma-Aldrich).

3. Methods 3.1. Cell Culture and SILAC

MS-based relative quantitation can be done on proteins derived from either cells in culture or tissues. Proliferating cell lines in culture are perfectly suitable for metabolic labelling techniques such as SILAC (11–13), and some examples have also been published in tissues from animal models (14). This technique can be used for the analysis of proteins derived from stably transfected cell lines that have been established to investigate CF-related questions and from cell lines expressing large amounts of CFTR/mutated CFTR. The former include cell models expressing wild-type (WT) CFTR and F508del-CFTR (HeLa (15), HEK and FRT), and the latter include cells derived from adenocarcinomas (e.g. glandular pulmonary cells Calu-3, intestinal adenocarcinoma T84 and HT29) (16–19). In addition, cell lines derived from CF patients (e.g. 16HBEO-, CFBEO-) are also suitable (20). Although HeLa cells are used as a model for proliferating cells, any cell type that can be grown in the appropriate substituted medium is suitable for this protocol. Nevertheless, certain cell types might not respond as well as others. The description below includes light, medium and heavy isotopic forms of arginine. Arginine is one of the amino acids of choice because virtually one out of the two peptides resulting from tryptic digestion will contain it. Furthermore, using three isotopic forms provides three quantification points. 1. Prepare the light, medium and heavy SILAC media according to manufacturer’s instructions. Always keep 50 mL of serum-free medium for starvation medium. 2. Grow WT-HeLa cells in the minimal amount of light SILAC medium for 2 full weeks, allowing at least five passages. 3. In parallel, grow F508del-HeLa and control HeLa cells (transfected with the vector alone) in medium and heavy SILAC media, respectively. 4. Check the efficiency of the Arg incorporation by MS. 5. Amplify the labelled cell lines and stock in liquid nitrogen.

3.2. Total Protein Extraction

1. Start with at least one 10-cm confluent plate of WT-HeLa (light), F508del-HeLa (medium) and control HeLa cells (heavy).

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2. Remove the media, wash them once with PBS and add enough serum-free DMEM for 18 h of starvation. 3. Wash cells three times with ice-cold PBS and place on ice immediately. 4. Scrape cells in D-PBS and collect them via centrifugation for 5 min at 800×g. 5. Add 500 μl of ice-cold lysis buffer to each cell line pool. Pass samples through a syringe to disrupt cells. 6. Rotate the three lysates on a rotating wheel for 1 h at 4◦ C. 7. Clarify each lysate by centrifuging the heavy and light tubes for 15 min at 15000×g in a centrifuge cooled to 4◦ C and collect the supernatants. 8. Measure protein concentration using the DC protein assay and mix the three samples in equal protein amounts; aliquot sample can be kept at –80◦ C for several months. 3.3. Microsomal Protein Extraction

1. Start with at least three 10-cm confluent plate of WT-HeLa (light), F508del-HeLa (medium) and control HeLa cells (heavy). 2. Wash cells three times with ice-cold D-PBS keeping culture flasks on ice all time. 3. Scrape cells in PBS and collect them via centrifugation for 5 min at 800×g. 4. Incubate each cell type pool with 500 μl of lysis buffer at 4◦ C, with agitation. 5. Homogenize cells at 4◦ C (300 strokes using a hand homogenizer or 2 min at 1000 rpm on a motorized homogenizer). 6. Spin the suspension at 200×g for 4 min (4◦ C) and collect the milky supernatant. 7. Spin the supernatant at 100,000×g for 1 h at 4◦ C to get total cell membranes (microsomes). 8. In order to get a preparation enriched in plasma membranes, you can first spin the milky 200 g supernatant via centrifugation for 15 min at 15,000×g, which will isolate the heavy membranes (from mitochondria and rough endoplasmic reticulum), and perform centrifugation at 100,000×g on the supernatant obtained at this first step. 9. Resuspend the 100,000×g pellet in lysis buffer (200 μl) and pass sequentially through a 19-G and a 23-G needle. 10. Measure the protein content of the preparation; mix the three extracts in equal amounts and aliquot it for storage at –80◦ C.

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3.4. Microdomain Protein Extraction

This protocol is intended for the analysis of proteins associated with the membrane microdomains known as detergent-resistant membranes (DRMs). 1. Start with at least six 10-cm confluent plate of WT-HeLa (light), F508del-HeLa (medium) and control HeLa cells (heavy). 2. Replace the media with serum-free DMEM for 18 h of starvation. 3. Wash cells three times with ice-cold D-PBS and place on ice immediately. 4. Add 1.2 mL of ice-cold D-PBS to each plate and scrape cells off with a rubber cell scraper and collect them via centrifugation for 5 min at 800×g. 5. Pool the cells from each cell line and add 500 μl of lysis buffer and rotate the three lysates in an end-over-end rotator for 1 h at 4◦ C, then clarify each lysate by centrifuging for 10 min at 600×g in a centrifuge cooled to 4◦ C. 6. Measure the relative protein concentrations of each clarified lysate using the DC protein assay. Continue with exactly the same amount (in μg) for the three samples. 7. Add the same volume of 90% sucrose in MBS equal to the combined volume of the three mixed lysates. Mix well and transfer to a clean 13.6-mL thin-walled ultracentrifuge tube. 8. On top of the lysate solution, carefully layer 5 mL of 35% sucrose in MBS and fill the remaining space in the tube with 5% sucrose in MBS. Place a small mark at the 5/35% interface. 9. Centrifuge the sucrose density gradient for 18 h at 166,000×g at 4◦ C in a swinging-bucket rotor. 10. Collect 12 fractions, including the light-scattering, fuzzy white band, using a 25-G needle connected to a syringe. Test the fraction by western blotting for the presence of microdomain markers, such as caveolin-1 (Fig. 13.2). Keep the fraction enriched at the same time in caveolin and flotillin, in our case fraction 4 in Fig. 13.2. 11. Transfer into a 13.6-mL tube and dilute to 8 mL with ice-cold MBS. Mix well and transfer to a clean 13.6-mL thick-walled ultracentrifuge tube and pellet microdomains by centrifuging for 3 h at 166,000×g at 4◦ C. 12. Remove supernatant and wash the three pellets gently with MBS.

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3

4

5

6

7

8

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9

48kDa

Flotillin-1

22kDa

Caveolin-1

Fig. 13.2. Western blot analysis with antibodies against flotillin-1 and caveolin-1 on protein fractions obtained by sucrose gradient separation.

13. Solubilize DRM pellet in 100 μl urea/thiourea. Pipette up and down vigorously to break up pieces of membrane and transfer solution to a clean 1.5-mL microfuge tube. 3.5. “In-Solution” Trypsin Digestion

1. Add 1 mL absolute ethanol, 40 μl 2.5 M sodium acetate, mix well and allow to stand for 90 min at room temperature. 2. Pellet proteins by centrifuging at 16,000×g for 10 min at room temperature. Discard supernatant and note the size of the pellet. For microdomain preparations, consider that a pellet of diameter 2–3 mM corresponds to approximately 25 μg of protein, as there will not be enough protein to measure it directly. 3. Re-solubilize the protein pellet in RapiGest (20 μl at 1%) and Invitrosol 5× (20 μl), heat sample at 60◦ C for 10 min, sonicate in a bath for 5 min and vortex (repeat three times). Spin to bring the sample to the bottom of the tube. 4. Add 60 μl of 8.3 mM DTT in 50 mM ammonium bicarbonate. Vortex to mix and then spin. 5. Incubate tubes at 60◦ C for 1 h. 6. To each tube, add 10 μl of 150 mM iodoacetamide in 50 mM ammonium bicarbonate. 7. Incubate tubes at room temperature for 30 min in the dark. 8. Reconstitute a vial of trypsin with 25 μl of Milli-Q, vortex to mix and then spin. 9. To each sample tube, add 1 μl trypsin solution, vortex to mix and then spin. 10. Incubate tubes at 37◦ C overnight (12–16 h). 11. Spin to bring the sample digest to the bottom of the tube. 12. Decompose RapiGest by incubating acidified digest with 35 μl of the acidification solution for 3 h at 37◦ C and clarify RapiGest breakdown products by centrifuging for 10 min at 16,000×g (see Note 1). 13. Keep the supernatant to dry down and use it shortly.

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3.6. OFFGEL Peptide Separation

Peptides can be separated according to their pI on a 3100 OFFGEL Fractionator and using the OFFGEL Kit 3–10 (both from Agilent Technology). For membrane proteins, a separation in 12 fractions can be used, loading between a minimum of 25 μg and a maximum of 3 mg for very complex samples, according to the starting material and the yield of purification. For total protein fraction, we advise a separation over 24 fractions (see Note 2). 1. Place the IPG strip, 12 cm, pH 3–10, in the tray with the gel side up and pull the strip as far left as possible until the strip touches the left edge of the tray, keeping the low pH side (anode) at the left side. 2. Assemble the IPG frame according to manufacturer’s instructions. 3. Pipette 40 μl OFFGEL solution into each of the wells, never touching the gel. 4. Position the electrode pads according to manufacturer’s instructions. 5. Wait for 15 min to allow the IPG gel to swell. Resuspend dried peptides in 1800 μl OFFGEL solution (1×). If necessary, neutralize the pH using 100 mM NaOH (see Note 3). 6. Load 150 μl in each well. 7. Place the cover seal over the frame and press down gently on each well to secure proper fit; place the tray on the instrument. 8. Pipette 200 μl cover fluid (mineral oil) onto the gel strip cathode and 1 mL cover fluid at the cathode side (movable electrode) in several steps without moving the electrode pads. 9. Assemble the electrodes according to manufacturer’s instructions. 10. Launch the fractionation run using the standard method for peptides at pH 3–10, and 12 well frames (OG12PE01 OFFGEL default method). 11. After fractionation, carefully remove the cover seals. Use a pipette to carefully recover the sample solution from the frame wells while avoiding aspirating the IPG gel and transfer to a fresh Eppendorf tube (see Note 4). Dry all the fractions down. These can be stored at –20◦ C for several weeks.

3.7. Peptide Separation by NanoHPLC and MS/MS Analysis

Different chromatography-MS configurations are available for high-throughput identification and quantification. The following protocol describes the chain nanoHPLC-Probot (Dionex)

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with MALDI TOF/TOF (Applied Biosystems). We also strongly advise to use, when possible, the nanoHPLC-LTQ Orbitrap (Thermo Scientific) set-up. The parameters given in this paragraph could be easily adjusted for other configurations. The 12 peptidic fractions issued from the OFFGEL Fractionator should be analysed sequentially in a short lapse of time. 1. Dried mixtures are resuspended with 25 μl of sample buffer. Ideally 0.5–1 μg of peptides should be injected (Ultimate3000 series HPLC). 2. Peptides should be separated on a gradient rising from 7 to 50% of solvent B in 40 min. Fractions are spotted online on a MALDI target using a Probot fraction collector. Spotted fractions are mixed 1:3 with the matrix solution and Glufibrinopeptide at 3 fmol/spot as internal calibrants. One hundred and ninety-two fractions are collected and ready to be analysed using a 4800 MALDI TOF/TOF analyser (ABI). 3. Spectra acquisition and processing are performed using the 4000 Series Explorer software (ABI) in positive reflectron mode at fixed laser fluency with low mass gate and delayed extraction. External plate calibration is performed using four calibration points spotted throughout the plate, with additional internal calibration being performed using the Glufibrinopeptide (m/z=1570.677). For each fraction, steps of 50 spectra in the range of 700–4000 Da are acquired and summed up to 500 spectra and processed to obtain monoisotopic values from isotope clusters with a raw spectra S/N ratio of 20. 4. In each MS spectrum, the eight most abundant peaks are selected for fragmentation starting with the least abundant. One thousand MS/MS spectra per precursor are summed by increments of 50 ranging from 200 Da to the parent ion mass. Global MS/MS peak lists, including those of all OFFGEL fractions, are searched against the latest SwissProt release database using Mascot Distiller (MatrixScience software; www.matrixscience.com). The mass error allowed on the ion parent and of the fragment ions is set at 20 ppm and 0.3 Da respectively set at 20 ppm and 0.3 Da, respectively, partial modification (oxidation) of methionines must be allowed, as well as CAM (carbamidomethylation), and both Label:13C(6) (R) and Label:13C(6)15 N(4) (R). Filters must be applied to the search in order to reduce both false positives and matching redundancies of the same peptide in several hits. Bold red, peptide score above 25, and false discovery rate (FDR) below 3% must be required.

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4. Notes 1. Acidified sample will degrade if left at 4◦ C for a few days. If you want to test one aliquot for direct nanoHPLC MS/MS, always acidify only the required amount of sample (10% is enough) just prior the analysis. Dry the rest of the digest and store at –20◦ C. 2. Substances that can interfere with IEF separation, such as salts, should be avoided. Total salt concentration in the sample should not exceed 10 mM for optimal fractionation. Non-ionic or zwitterionic detergents like CHAPS can be used in OFFGEL electrophoresis but may interfere with downstream analysis by MS and are, therefore, not recommended. In case you have additives, such as salt and urea, desalt OFFGEL peptide fractions if they must be analysed directly by MS. Glycerol in peptide fractions can interfere with speed-vac concentration (by increased viscosity), with direct injection into reverse phase LC or with crystallization on a MALDI target. Glycerol can be removed by C18 Stage. You can also omit glycerol from the OFFGEL solution. This may lead to reduced liquid levels in some wells. These wells can be refilled every few hours of fractionation with ampholyteand glycerol-free OFFGEL solutions. However, we find that the amount of glycerol described in the protocol is tolerated by the nanoHPLC. 3. We find that 2–5 μl of 100 mM NaOH solution is enough to bring the pH to 7. Remember in any case to keep the final salt concentration of the solution to less than 2.5 mM. 4. Do not be alarmed if the volumes of the different fractions may not be equal, this is only a sign of different peptide content in each fraction. References 1. Ollero, M., Brouillard, F., and Edelman, A. (2006) Cystic fibrosis enters the proteomics scene: new answers to old questions. Proteomics 6, 4084–4099. 2. Bensalem, N., Ventura, A. P., Vallee, B., et al. (2005) Down-regulation of the antiinflammatory protein annexin A1 in cystic fibrosis knock-out mice and patients. Mol Cell Proteomics 4, 1591–1601. 3. Davezac, N., Tondelier, D., Lipecka, J., Fanen, P., Demaugre, F., Debski, J., et al. (2004) Global proteomic approach unmasks involvement of keratins 8 and 18 in the

delivery of cystic fibrosis transmembrane conductance regulator (CFTR)/deltaF508CFTR to the plasma membrane. Proteomics 4, 3833–3844. 4. Pollard, H. B., Eidelman, O., Jozwik, C., Huang, W., Srivastava, M., Ji, X. D., et al. (2006) De novo biosynthetic profiling of high abundance proteins in cystic fibrosis lung epithelial cells. Mol Cell Proteomics 5, 1628–1637. 5. Roxo-Rosa, M., Davezac, N., Bensalem, N., Majumder, M., Heda, G. D., Simas, A., et al. (2004) Proteomics techniques for cystic

Quantitative Proteomics in CF

6.

7.

8.

9.

10.

11.

12.

13.

fibrosis research. J Cyst Fibros 3 Suppl 2, 85–89. Wong, J. W., and Cagney, G. (2010) An overview of label-free quantitation methods in proteomics by mass spectrometry. Methods Mol Biol 604, 273–283. Borot, F., Vieu, D. L., Faure, G., Fritsch, J., Colas, J., Moriceau, S., et al. (2009) Eicosanoid release is increased by membrane destabilization and CFTR inhibition in Calu3 cells. PLoS One 4, e7116. Dudez, T., Borot, F., Huang, S., Kwak, B. R., Bacchetta, M., Ollero, M., et al. (2008) CFTR in a lipid raft-TNFR1 complex modulates gap junctional intercellular communication and IL-8 secretion. Biochim Biophys Acta 1783, 779–788. Kowalski, M. P., and Pier, G. B. (2004) Localization of cystic fibrosis transmembrane conductance regulator to lipid rafts of epithelial cells is required for Pseudomonas aeruginosa-induced cellular activation. J Immunol 172, 418–425. Aggarwal, K., Choe, L. H., and Lee, K. H. (2006) Shotgun proteomics using the iTRAQ isobaric tags. Brief Funct Genomic Proteomic 5, 112–120. Guerrera, I. C., Keep, N. H., and GodovacZimmermann, J. (2007) Proteomics study reveals cross-talk between rho guanidine nucleotide dissociation inhibitor 1 posttranslational modifications in epidermal growth factor stimulated fibroblasts. J Proteome Res 6, 2623–2630. Kruger, M., Moser, M., Ussar, S., Thievessen, I., Luber, C. A., Forner, F., et al. (2008) SILAC mouse for quantitative proteomics uncovers kindlin-3 as an essential factor for red blood cell function. Cell 134, 353–364. Ong, S. E., Blagoev, B., Kratchmarova, I., Kristensen, D. B., Steen, H., Pandey, A., et al. (2002) Stable isotope labeling by amino acids in cell culture, SILAC, as a simple and

14.

15.

16.

17.

18.

19.

20.

225

accurate approach to expression proteomics. Mol Cell Proteomics 1, 376–386. Amanchy, R., Kalume, D. E., and Pandey, A. (2005) Stable isotope labeling with amino acids in cell culture (SILAC) for studying dynamics of protein abundance and posttranslational modifications. Sci STKE 2005, pl2 Fanen, P., Labarthe, R., Garnier, F., Benharouga, M., Goossens, M., and Edelman, A. (1997) Cystic fibrosis phenotype associated with pancreatic insufficiency does not always reflect the cAMP-dependent chloride conductive pathway defect. Analysis of C225RCFTR and R1066C-CFTR. J Biol Chem 272, 30563–30566. Baudouin-Legros, M., Brouillard, F., Cougnon, M., Tondelier, D., Leclerc, T., and Edelman, A. (2000) Modulation of CFTR gene expression in HT-29 cells by extracellular hyperosmolarity. Am J Physiol Cell Physiol 278, C49–C56. Baudouin-Legros, M., Brouillard, F., Tondelier, D., Hinzpeter, A., and Edelman, A. (2003) Effect of ouabain on CFTR gene expression in human Calu-3 cells. Am J Physiol Cell Physiol 284, C620–C626. Besancon, F., Przewlocki, G., Baro, I., Hongre, A. S., Escande, D., and Edelman, A. (1994) Interferon-gamma downregulates CFTR gene expression in epithelial cells. Am J Physiol 267, C1398–C1404. Brouillard, F., Bensalem, N., Hinzpeter, A., Tondelier, D., Trudel, S., Gruber, A. D., et al. (2005) Blue native/SDS-PAGE analysis reveals reduced expression of the mClCA3 protein in cystic fibrosis knock-out mice. Mol Cell Proteomics 4, 1762–1775. Cozens, A. L., Yezzi, M. J., Kunzelmann, K., Ohrui, T., Chin, L., Eng, K., et al. (1994) CFTR expression and chloride secretion in polarized immortal human bronchial epithelial cells. Am J Respir Cell Mol Biol 10, 38–47.

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Chapter 14 Application of Mass Spectrometry to Study Proteomics and Interactomics in Cystic Fibrosis William E. Balch and John R. Yates III Abstract The cystic fibrosis transmembrane conductance regulator (CFTR) does not function in isolation, but rather in a complex network of protein–protein interactions that dictate the physiology of a healthy cell and tissue and, when defective, the pathophysiology characteristic of cystic fibrosis (CF) disease. To begin to address the organization and operation of the extensive cystic fibrosis protein network dictated by simultaneous and sequential interactions, it will be necessary to understand the global protein environment (the proteome) in which CFTR functions in the cell and the local network that dictates CFTR folding, trafficking, and function at the cell surface. Emerging mass spectrometry (MS) technologies and methodologies offer an unprecedented opportunity to fully characterize both the proteome and the protein interactions directing normal CFTR function and to define what goes wrong in disease. Below we provide the CF investigator with a general introduction to the capabilities of modern mass spectrometry technologies and methodologies with the goal of inspiring further application of these technologies for development of a basic understanding of the disease and for the identification of novel pathways that may be amenable to therapeutic intervention in the clinic. Key words: Cystic fibrosis, mass spectrometer, multidimensional, MudPIT, LC-MS/MS, spectral counting, proteome, proteomics.

1. Introduction Cystic fibrosis remains a formidable challenge to understand the etiology of the disease and to treat in the clinic (1). Considerable effort has focused on understanding the mechanism by which the cystic fibrosis transmembrane conductance regulator (CFTR) orchestrates chloride conductance and tissue hydration through its channel activities and the clinical manifestations of disease. M.D. Amaral, K. Kunzelmann (eds.), Cystic Fibrosis, Methods in Molecular Biology 742, DOI 10.1007/978-1-61779-120-8_14, © Springer Science+Business Media, LLC 2011

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In contrast, much less is known about how WT or F508del (as well as other variants) of CFTR is integrated into the biological network that drives normal physiology and how it is disrupted in disease. A vast metabolic and proteomic network supports the generation, maintenance, and degradation of CFTR – each step of which is critical for human health and is defective in disease. The protein “interactome” network (2) is supported by a cellular environment, that is, the proteome system that balances CFTR function with all other aspects of cell, tissue, and human physiology to achieve normal function. • One well-established approach to examine function at the systems biology level is to measure mRNA abundance (genomics/transcriptomics) that uses DNA microarray technologies to study gene expression (see Chapter 12, this volume). In terms of protein function, this approach is largely indirect and has limitations regarding its utility to give an accurate assessment of protein activity in CF physiology given the multiple translational, co-translational, and posttranslational modifications that regulate protein stability and function. A more direct, but as yet largely untapped resource is the application of mass spectrometry (MS) technologies to rigorously quantitate the metabolome (lipid- and watersoluble metabolite profile of cells), the cellular proteome (the protein composition of a cell), and the interactome, that is, the protein–protein interactions that directly or indirectly influence CFTR WT function or loss-of-function/toxic gainof-function in response to variants that trigger disease. Proteomic MS technologies can identify the composition of a specific complex recovered by immunoprecipitation or be used to examine whole cell, tissue, or plasma composition (3, 4). Furthermore, it has the important capability to precisely quantify protein concentrations in a sample and to determine the extent of modification that includes, among others, phosphorylation, glycosylation, methylation, acetylation, sumoylation and ubiquitination, all adducts that significantly contribute to protein function and organismal physiology (4). Mass spectrometry (MS) uses mass analysis for both metabolite and protein characterization and is a remarkably versatile tool whose potential impact is largely untapped for the study of human diseases such as CF. Mass spectrometry has high potential for solving many of the riddles that plague both the scientist and the physician in understanding and devising approaches to restore CFTR function in the clinic. The instrumentation required for these studies and the methodologies used to generate proteomic and metabolomic data are diverse, highly specialized, and rapidly evolving (4).

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Mass spectrometry has been applied to the study of CF at a number of different levels over the past 10 years. Early efforts focused on the use of a combination of two-dimensional gel electrophoresis (2D-PAGE) and matrix-assisted laser desorption ionization (MALDI) with time-of-flight (TOF) mass spectrometry of excised spots to define the high-abundance proteome using whole cell lysates that potentially contribute to function in WT and F508del-CFTR-expressing cells (5) (literature prior to 2004 reviewed in (6)). More recently, Zeitlin, Pollard, and colleagues have focused on proteomic analysis of whole cell lysates from lung cell lines using 2D-PAGE and MALDI-TOF. This has led to a number of important insights into the differences in the high-abundance proteome found in WT CFTR- and F508del-expressing cells and their response to treatment with the pharmacophore 4-phenylbutyrate (4-PBA) (7–10). These studies highlighted the potential importance of chaperone systems and inflammatory signaling pathways in disease. In addition, gel-based separations followed by MALDI-TOF are being more frequently used to characterize the proteomic composition of bronchoalveolar lavage (BAL) fluid from the CF patient to identify biomarkers of disease etiology (11–21). Proteins that interact directly or indirectly with WT or F508del have been detected using affinitybased approaches to CFTR domains followed by gel-based separation and MALDI-TOF (22) or through direct immunoprecipitation of CFTR followed by shotgun proteomics (2). The former led to the discovery of the role of filamins in modulating the cell surface trafficking, while the latter led to the first description of the CFTR interactome and the discovery of the role of Aha1, an ATPase activator, in Hsp90-directed folding of WT and F508del-CFTR, leading to rescue of cell surface channel expression. Recent studies have used 2D-PAGE and MALDI-TOF to identify differentially expressed proteins in response to lowtemperature shift, emphasizing the possible importance of coldshock chaperones in trafficking (23), whereas a study using similar techniques has described proteome responses to RXR motif inactivation (24). Using more quantitative approaches, a multiple reaction monitoring approach was developed for absolute quantification of levels of WT and F508del-CFTR in cells (25). As is apparent, application of proteomic methodologies to CF is beginning to provide insight into both specific and systemslevel changes in cell, tissue, and human physiology that could be of importance in disease. Below, we give the CF investigator an overview of the different MS technologies and methodologies for the study of CF. We refer the reader to the specific references in each section that describe in detail state-of-the-art technologies/methodologies that may be applicable to their particular question(s). Specific applications of these technologies are

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described in Chapters 13, 15, 16 and hereunder that focus on the use of mass spectrometry and related approaches to study protein interactions in the secretory pathway (Chapter 15), the role of lipid metabolites in CF disease (Chapter 16), and quantitative approaches to define differential proteomics in CF (Chapter 13). Where appropriate, we cite past and present mass spectrometric approaches that have been used to gain insight into CF disease using cellular and organismal models as well as human patient samples. While we focus on proteomic methodologies, the general principles and instruments utilized for mass analysis are equally applicable to understanding the lipid metabolome as described in Chapter 16.

2. MS Proteomic Approaches Applicable to CF

MS strategies for proteomics can utilize top-down (whole protein) or bottom-up (protein fragments) technologies. These encompass a number of steps and technologies that must be used in a systematic manner to generate reliable results. These include method of sample preparation, front-end separation to reduce sample complexity, ionization technologies to generate interpretable data with high precision and throughput, data acquisition, and data analysis technologies. Each of these steps differs considerably depending on not only the sample complexity, but the question at hand (26).

2.1. Ionization Techniques

An important development in instrumentation that has driven the emergence of proteomics is the use of “soft” ionization methods. These are specifically applicable to proteins and peptides given that these molecules are polar, non-volatile, and thermally unstable species that require an ionization technique that can transfer an analyte into the gas phase without extensive breakdown. Techniques that have paved the way for MS proteomics are matrixassisted laser desorption ionization (MALDI) (27, 28) and electrospray ionization (ESI) (29).

2.1.1. MALDI

MALDI requires a matrix that can absorb laser energy to create a rapid sublimation of matrix and analyte into the gas phase. Ion– molecule reactions during the sublimation process result in the creation of [M+H]+ ions of analyte in the gas phase. MALDI ionization requires several hundred laser shots to achieve an acceptable signal-to-noise ratio for ion detection. Because MALDI requires hundreds of laser activation events to generate singly charged ions, MALDI is a technique best suited for instruments that perform pulsed analysis. Limitations include low shot-to-shot

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reproducibility and sensitivity to sample preparation methods (30, 31). Related techniques such as SALDI (32) and DIOS (33) utilize porous graphite and silicon, instead of a matrix, and have higher tolerance toward detergents and salts. AP-MALDI (34), or atmospheric pressure MALDI, allows easy interchange between MALDI and ESI sources (see later). MALDI has also stimulated interest in surface-enhanced laser desorption ionization (SELDI) technologies (35) that introduce affinity or “chromatographic” functionality to the plate surface to help analyze specific target protein and peptide molecules. 2.1.2. ESI

3. MS Technologies Applicable to CF

3.1. Instrumentation

While MALDI requires application of samples to surfaces, ESI produces ions from solution by application of a high voltage between the emitter at the end of a tube (e.g., chromatography column) and the start of the mass spectrometer. ESI produces a fine spray at the end of the tube which is directed to an inlet in the mass spectrometer. Liquid is removed from the droplet by the application of heat and/or through collisions with inert gases to leave behind ions. The most practical features of the technique are that it creates multiply charged species, its concentration sensitivity and thus (36) low flow rate chromatography such as found in micro- and nano-ESI improve the method’s sensitivity (37, 38), and it can be used on continuous analysis instruments.

MS couples evolving separation technologies as a first step to reduce sample complexity with rapidly advancing instrumentation technologies to achieve high-throughput capability and high mass accuracy for identification of the proteome. Mass spectrometers are generally constructed to have an ion source and optics, a mass analyzer, and various data processing capabilities. Mass analyzers have been developed that can store ions and separate them based on mass-to-charge ratios (m/z) or that can analyze a beam of ions. Among these, ion trap (IT), Orbitrap, and ion cyclotron resonance (ICR) mass analyzers store ions and then separate ions based on their m/z resonance frequency. A quadrupole mass analyzer (Q) uses a beam of ions and measures m/z by controlling which ions pass through the quadrupole to the detector, while time-of-flight (TOF) analyzers use flight time. Each mass analyzer has particular capabilities including mass range, analysis speed, resolution, sensitivity, ion transmission, and dynamic range that define the utility of instrument for specific applications. Hybrid instruments contain more than one mass

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analyzer to expand inherent limitations of a given technology, and the reader is referred to many excellent articles and reviews on the topic (26, 39, 40–45). 3.2. Mass Analyzer Technologies

Mass analyzers include the scanning and ion beam mass spectrometers such as TOF and Q; and the “trapping” mass spectrometers that include the IT, Orbitrap, and FT-ICR. TOF analyzers are often interfaced with MALDI because of the pulsed nature of ion production, while the ion beam/trapping instruments are utilized in conjunction with continuous ESI source. In the field of proteomics, select instruments have emerged as useful technologies and include ion traps (3D ion trap – QIT, linear ion trap – LIT (46)) and triple quadrupole (TQ). LTQOrbitrap (47–49) (Thermo Scientific), LTQ-FT-ICR (50, 51) (Thermo Scientific), TQ-FT-ICR hybrid instruments, TQ-TOF (52), and IT-TOF (53) (Shimadzu) are generally the hybrid technologies of choice, although each of these technologies is evolving rapidly.

3.3. Ion Trap Technologies

Ion trap instruments (26, 41, 54) are generally a driving force in proteomic studies because they feature fast scan rates, MSn scans, high duty cycle, high sensitivity and acceptable resolution (M/M ∼2,000), and mass accuracy (100 ppm). For example, the LTQ ion trap from Thermo Scientific combines a 10-fold higher ion storage capacity than 3D traps and higher resolution capability at a faster scan rate. LTQ radial ion ejection offers higher sensitivity than other 2D ion trap instruments because of the use of two detectors (55). Stand-alone ion trap instruments are best suited for the bottom-up LC-MS/MS protein identification studies from complex samples and whole cell lysates where the fast scanning rates and high sensitivity of LITs offer high proteome coverage. An LTQ is often used as the front end of several hybrid instruments, the LTQ-Orbitrap, LTQ-FT-ICR, and LTQ-TOF, where it is used for ion trapping, ion selection, and ion reactions, respectively. The LTQ-Orbitrap deserves a special mention as an application for CF proteomics. An Orbitrap uses orbital trapping of ions in static electrostatic fields (26, 48, 49) (where the ions orbit around a central electrode and oscillate in axial direction) and utilizes a fast Fourier transform (FFT) algorithm to convert time-domain signal into mass-to-charge spectrum. The device has high resolving power (M/M up to 150,000), high mass accuracy (2–5 ppm), a mass-to-charge range of 6000, and dynamic range greater than 103 (48, 49). The LTQ ion trap-Orbitrap hybrid instrument combines the high resolution and mass accuracy of the Orbitrap and the speed and sensitivity of the LTQ. Such a hybrid instrument can carry out MS full scans, while the LTQ carries out fragmentation reactions at the same time, greatly

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accelerating proteomic applications applicable to CF (26, 40, 41, 43, 56–58). Some of the recent applications of the LTQ-Orbitrap for biological samples include quantification of low-abundance peptides (59), profiling very complex biological samples such as human plasma (60), and identification of proteins from the limited sequence proteomes (61). High mass accuracy facilitates integration of database searches, de novo searches, peptide mass fingerprinting (PMF) searches, and the library lookup into a proteomic pipeline to achieve higher coverage and accuracy (62, 63). While the LTQ-Orbitrap is the instrument of choice for bottom-up approaches, FT-ICR benefits from a broader mass-tocharge range and is well suited for top-down protein analysis (51). Metabolites further benefit from a specialized hybrid combination of instrumentation (Chapter 16). 3.4. Separation Technologies

For both proteomes and metabolomes, mass spectrometry is necessarily highly dependent on separation technologies to simplify highly complex biological samples prior to mass analysis that would necessarily overwhelm the capabilities of the mass spectrometer. Because proteins are identified by the mass-to-charge ratios of their peptides and fragments, the goal of separation technologies is to attempt to achieve sufficient separation for unambiguous identifications of large numbers of peptides. Moreover, front-end separation is essential to detect low-abundance species that would be masked by higher abundance signals that would predominate in the mass spectrometer. Thus, both chemical separation and the mass resolution dimension (contributed by the instrumentation) provide separation of molecules (26, 41). Chemical separation is the first step in designing a useful proteomic approach to a particular experimental question that could provide new insights into CF disease etiology.

3.4.1. 2D-PAGE/MALDI

The two approaches most widely used in proteomics are twodimensional polyacrylamide gel electrophoresis (2D-PAGE) and gel-free (in solution) approaches. As indicated in Section 1, 2D-PAGE approaches have been used by a number of investigators to study various facets of the CF proteome. Gel-based methods often use MALDI instruments where the protein band can be excised, digested, and off-line sampled with MALDI source. This approach is technically challenging, considerably limits throughput, and has limited value in the identification of membrane proteins, an important consideration in understanding the CF proteome. There are many reviews that cover gelbased approaches to proteomics and the reader is referred to these articles (i.e. (64–67),). Below we briefly address the use of solution-based shotgun methodologies as a more comprehensive and versatile approach to study the CF proteome and interactome in human health and disease.

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3.4.2. HPLC

High-pressure liquid chromatography (HPLC) is a standard front end for most biological applications (26, 41, 45, 68). Highpressure reversed-phase chromatography is as essential to LC-MS as 2D-PAGE is to gel-based proteomics. It is usually coupled to instruments with an ESI source as HPLC-based separation is compatible with a continuous ionization source, and both can be readily interfaced with scanning or trapping mass analyzers (LTQ, QqLIT, QqTOF, LTQ-Orbitrap, and LTQ-FTMS). HPLC chromatographic materials used commonly for proteomics include ion exchange (IEX), reversed phase (RP) and HILIC (hydrophilic interaction chromatography), affinity, size exclusion, and various emerging hybrid materials. Reversed-phase (RPLC or RP) resins utilize hydrophobicity to separate and are highly compatible with ESI (69). Analytical RPLC is used as the single phase and the last dimension of multidimensional separation before mass analysis. Peak capacity, sensitivity, reproducibility, and analysis speed are all important features that can be optimized to improve proteomic analyses (2, 26, 70). Long, small particle size (2 μm or less) columns with high peak capacity operated in ultra-high pressure regime (20 kpsi) can reveal 2000 proteins that vary over six orders of magnitude in concentration in a single experiment (71– 73). Elevated temperature (65◦ C) UHPLC further improves separation of intact proteins (59, 74, 75).

3.5. Multidimensional Separation

To address limited peak capacity (76), RPLC can be integrated with other separation technologies as part of a multidimensional separation approach. There are particularly useful applications such as found for the high-complexity, large-scale proteomic samples found in the CF interactome or the diseased cell/plasma proteome that can contain thousands of proteins ranging five to six orders of magnitude in abundance. Shotgun proteomic samples further increase the complexity, given that protease-digested sample yields multiple peptide products (see later). In essence, the multidimensional separation approach simply combines multiple separation techniques to improve the resolving power of the separation based on the orthogonality of the individual separation methods. Here, each dimension uses different (orthogonal) physical properties of molecules to improve separation. There are many recent review papers that cover historical and theoretical aspects of multidimensional separation (i.e. (68, 77),). The use of strong cation exchange (SCX) resin followed by RPLC has become a popular method for shotgun proteomics known as multidimensional protein identification technology (MudPIT) (26). Here, a sample loaded onto an SCX column is eluted in a series of steps with increasing salt concentration. Each fraction is either loaded onto an RP column off-line or directly eluted into the ESI source with non-polar buffer. Because

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ESI is incompatible with high detergent and salt concentrations, MudPIT utilizes specific approaches to circumvent this drawback and improve sensitive and recovery (26, 74, 78, 79). Materials that can also be used as first dimension are size exclusion, anion exchange, and the mixed-bed approach (80, 81). 3.6. Affinity-Based Chromatography

An important category of chromatographic techniques to reduce sample complexity is affinity chromatography. Affinity approaches are important to capture a sufficient level of low-abundance molecules such as CFTR to analyze the composition of specific complexes involved in many different stages of trafficking. This approach was used in combination with MudPIT to first identify the CFTR interactome in a cell-based heterologous expression system. This study revealed the importance of the Hsp90 system in CFTR folding in the endoplasmic reticulum (2). A second example is the use of affinity approaches to enrich for posttranslationally modified (PTM) proteins and peptides mentioned earlier to levels that are detectable by mass spectrometers. Phosphoproteomics is geared toward identification and quantification of phosphorylated proteins and identification of phosphorylation sites (82). Enrichment techniques take advantage of the negative charge of the phosphate group to bind to immobilized metal cations such as immobilized metal affinity chromatography or IMAC (83). Here, immobilized Fe3+ ions are used to selectively bind phosphorylated peptides. IMAC is quite versatile as selectivity and specificity can be changed by varying the pH, salt concentration (84), buffer composition, and presence of detergents (85). Metals such as Zr4+ (86) and Ga3+ (87) as well as metal oxide affinity resins such as TiO2 (88), Fe3 O4 (89), and ZrO2 (90) can be used with IMAC, altering the specificity and improving the phosphoproteome coverage (91). Anion exchange chromatography (92), mixed-bed (80), and hydrophobic-interaction chromatography (HILIC) (93) offer additional strategies along with non-chromatography-based enrichment techniques. In addition to phosphoproteomics, glycoproteomics is a new and expanding area where affinity chromatography is applicable (94–96). N-linked glycosylated peptides can be bound to solid supports and subsequently enzymatically released by specific glycosidases. N-linked glycopeptides can also be immobilized using lectin binding chemistry (97–99). Enzymatic release combined with H18 O enzymatic labeling leads to the isotope-coded glycosylation site-specific tagging (IGOT) (100, 101). Lectin chemistry can also be used to capture O-linked glycoproteins using a technique referred to as serial lectin affinity chromatography (SLAC) (102). Finally, the acetylome has recently attracted the attention of MS technologies (103–106). An understanding of acetylation profiles on proteins is likely to contribute significantly to an understanding of CF disease (107, 108).

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In general, affinity chromatography is usually a part of the multidimensional separation scheme that is performed off-line or directly coupled to the RP column for front-end loading of the mass spectrometer to reduce complexity and improve recovery of relevant protein species to the question(s) at hand.

4. Application of Proteomic Methodologies to Study CF

4.1. Bottom-Up Versus Top-Down

It should be apparent that a variety of technologies are available for the study of CF. The application of these technologies will reflect the pending question to be answered. Experiments should be hypothesis driven – the most valuable mass spectrometer results will come from carefully designed goals and the difference in proteins recovered in the “normal” control and the new condition being examined (i.e., in response to treatment with a drug). The first goal of any study will be to reduce sample complexity prior to mass analysis. The second goal will be to establish the reproducibility and robustness by repeating experiments at least three independent times to eliminate false-negative and false-positive results. A third consideration is the use of follow-up experiments to validate any insights gained from the mass spectrometry data sets. Mass spectrometric data acquisition is generally approached in a data-dependent manner, particularly in the bottom-up approach. Here, information from a current mass spectrometric scan determines the parameters of subsequent scans. Proteomic analysis for CF can make extensive use of tandem mass spectrometry where mass analysis is carried out on intact molecular ions (full scan MS) or fragmented precursor ions (MSn scans). In most cases full scans produce masses of the proteins or peptides, and fragmentation scans yield the primary sequence information. Most bottom-up applications require tandem data acquisition where peptides are subjected to collision-activated dissociation (CAD or CID). A typical proteomic analysis begins with the sample preparation step where proteins are either enzymatically digested into peptides (bottom-up analysis (109, 110)) or analyzed intact (topdown analysis (26, 51)). The bottom-up approach is very useful for tackling high-complexity samples in a high-throughput fashion. This has been referred to as “shotgun proteomics” (26, 41). In bottom-up proteomics, proteins are digested by proteases to generate peptide population prior to mass analysis. The ensuing peptide masses and sequences provide the basis for identifying corresponding proteins in the database. The most widely used

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method of the bottom-up tandem mass spectrometry data identification is the database search (26). Here, in programs such as SEQUEST (111), experimental MSn data are compared to the predicted in silico generated fragmentation patterns of peptides. In addition to SEQUEST (111), many methods have been developed to improve this process given the challenges associated with bottom-up proteomics including probabilistic scoring schemes (26, 112–117), implementing additional search criteria (26, 118, 119), and using identified spectra to bootstrap the database search (120). Although currently not available, public repositories of proteomic data are in the planning stage and will help to promote data format standardization and increased data availability for additional analysis by non-mass spectrometry experts. Given that many proteins in the CF proteome/interactome, including CFTR, are post-translationally modified, the bottomup approach provides the opportunity of chemical modification of peptides to improve quantification. ICAT (121, 122), O18 labeling (123), and Hamon tandem mass tags (124) are particularly conducive techniques for peptide-based methodologies such as MudPIT. Advantages of the bottom-up approach include (1) better front-end separation of peptides compared to proteins and (2) higher sensitivity than the top-down method. Problems associated with the bottom-up approach may involve limited protein sequence coverage by the identified peptides, the loss of labile post-translational modifications, and ambiguity of identification of isoforms or conserved domains found in many proteins due to the multiple origins of identified peptides. Top-down methods use intact protein mass and their fragments for identification. Fragmentation reactions including electron capture dissociation (ECD) and electron transfer dissociation (ETD) yield a more complete backbone sequencing and retain labile PTMs (4). These are the preferred fragmentation methods of the top-down approach which, of course, does not use an off-line upfront protease digestion protocol as found in bottomup approaches. Data analysis utilizes the expressed sequence tag (EST) or the de novo methods (3). Advantages of the top-down approach include higher sequence coverage of target proteins and more accurate characterization of the post-translational modifications (125, 126). The more extensive sequence coverage of the top-down approach reduces the problems associated with peptide-to-protein mapping and improves isoform identification, an issue that can be a problem for bottom-up approaches (127, 128). Top-down approaches also have improved reliability of protein quantification (129–131) where intact protein abundances are measured directly. While the top-down approach is seemingly very attractive, technological limitations prevent it from emerging as the technique of choice relative to the current popularity of bottom-up approaches. Front-end separation of intact proteins is

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particularly challenging, requiring larger quantities of protein and higher mass accuracy instruments (FTMS and LTQ-Orbitrap) for analysis. This largely limits the top-down approach to analysis of single proteins and simple protein mixtures, although recent studies (132, 133) have used the top-down approach for complex mixture analysis. 4.2. Quantitative Methods for Assessing the CF Proteome

Whether a bottom-up or top-down approach is used, an important advantage of large-scale proteomic approaches for systems biology questions is the capability to quantify multiple interactions in a single pass, e.g., a snapshot of concentrations of proteins associated with different states (i.e., a time course). Two broad groups of quantitative methods are used in mass spectrometrybased proteomics using both in vivo and in vitro protocols. These are relative quantitative proteomics and absolute quantitative proteomics. Relative quantitative proteomics compares two or more samples either by stable isotope labeling methods in vivo or by stable isotope tagging in vitro or with the label-free methods. In contrast, absolute quantitative proteomics utilizes stable isotope-labeled peptide and recombinant protein standards that are added to a sample to determine precise concentration of a protein. For relative quantitation, isotope labels can be introduced metabolically, chemically, or enzymatically. Metabolic labeling in vivo involves generating proteins with stable isotope of elements (15 N) or amino acids (heavy Arg, Lys, Leu, Ile), for example, growing yeast in 15 N-enriched cell culture media. Model organisms including Caenorhabditis elegans, Drosophila melanogaster (134), and rat (135) in vivo have been labeled using 15 Ncontaining medium. Relative abundance ratio of peptides is experimentally measured by comparing heavy/light peptide pairs. The protein levels are inferred from statistical evaluation of the peptide ratios. SILAC approach generates proteins with one or more “heavy” amino acids: Leu (136), Arg, Lys (137), and Tyr (138) (see Chapter 13 for a detailed description of a SILAC methodology) (4). SILAC-labeled peptides are quantified from full scan mass spectra. Many studies have applied SILAC to studying dynamic changes in response to stimuli, a problem particularly relevant to, for instance, understanding the effects of pharmacophores in CF (139, 140). SILAC has been applied to labeling of primary cells (141) and even whole organisms (142). SILAC accuracy requires complete incorporation of the labeled amino acids, although metabolic conversion of arginine to proline results in tryptic peptides also containing heavy prolines (143). Both experimental and bioinformatics solutions are used to minimize interference from incompletely labeled peptides (144–146).

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Post-cell lysis labeling technologies include ICAT (isotopecoded affinity tags – labeling of free cysteine) (147) and iTRAQ (isobaric tags for relative and absolute quantification – labeling of free amines) (148). Such chemical derivatization procedures work for any sample and are applicable to both bottom-up and top-down protocols (3). Enzymatic labeling can be used to incorporate 18 O either during or post-protease digestion. Absolute measurements of protein concentrations can also be achieved with spiked synthetic (AQUA) peptides (149), artificial proteins derived from detected peptides as in QconCAT (150) and SILAC (151), or using purified isotopic-labeled recombinant protein standards. Multiplexing tagging chemistry for iTRAQ allows simultaneous work-up of four to eight samples (152). Peptide levels are inferred from MS/MS spectra. Pulsed Q dissociation (PQD) (153) facilitates detection of iTRAQ reporter ions, bridging the gap between the linear ion trap with PQD and a quadrupole TOF instrument (40, 154, 155) quantification with an ETD-enabled LTQ-Orbitrap. When isotopic labeling is not available (e.g., cells cannot be grown or labeled in specialized isotope labeling medium), labelfree techniques are the method of choice for abundance-based proteomics. Given the sensitivity of CFTR trafficking to perturbation and the need to assess CFTR function in human primary cells and tissues, this is a method highly applicable to study of CF. Label-free methods utilize spectral counting and/or peptide signal intensity to estimate protein abundance (4, 45), with spectral sampling being directly proportional to the relative abundance of the protein in a mixture (156). Comparison of spectral counting methods to 14 N/15 N metabolic labeling demonstrates the high utility of spectral counting for quantitative proteomics by MudPIT (4, 157).

5. Software Applications for Quantification of Complex Proteomes Found in CF

As is evident given the complexity of the data sets, quantification of complex proteomes necessitates automated software solutions (4, 158). Census is such a software tool (146) that can handle data from 15 N, SILAC, iTRAQ, as well as label-free experiments. Census is capable of achieving protein quantification en masse in high complexity samples analyzed with MudPIT. In the case of isotopic-labeled experiments, Census employs an algorithm that extracts individual isotopes using a mass accuracy tolerance, a method that is very effective in reducing noise peaks leading to a high correlation of tracking chromatograms. Census calculates peptide ion intensity ratios for each peptide pair using a linear

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least squares correlation (i.e., slope of the line) and closeness of fit (i.e., correlation coefficient (r)) between data points of labeled and unlabeled ion chromatograms. Census determines protein ratios by calculating a weighted average of all peptide ratios quantified for a specific protein. Weights are determined by considering the errors associated with each peptide ratio measurement, more precisely the inverse square of the standard deviation of the measurement. Census removes statistical outliers for proteins with more than three quantified peptides. Standard deviations are calculated for all proteins using their respective peptide ratio measurements. Finally the Grubbs test (159) is applied with a userdefined p-value to remove outlier peptides.

6. Outlook for the Role of Mass Spectrometry in Understanding CF

The above overview of the evolving mass spectrometry technologies and methodologies illustrates the versatility of the approach for addressing many questions posed by CF disease at both the basic and clinical levels. The striking improvement in technologies related to accuracy and throughput when coupled to quantitative approaches will undoubtedly have a level of impact equivalent to immunoblotting, but in a high-throughput fashion with quantitative insight into CF proteomes and interactomes. The challenge will be to develop mechanisms that make these specialized technologies available to the CF investigator through either simplification of instrumentation and streamlining of methods or integrative, collaborative centers that can effectively channel questions posed by individual CF investigators that are relevant to disease into high-quality experiments. Mass spectrometry and proteomics provide a unique opportunity to understand CF at a systems level – a level of understanding that is likely to be critical for understanding and developing robust therapeutics for disease.

References 1. Riordan, J. R. (2008) CFTR function and prospects for therapy. Annu Rev Biochem 77, 701–726. 2. Wang, X., Venable, J., LaPointe, P., Hutt, D. M., Koulov, A. V., Coppinger, J., et al. (2006) Hsp90 cochaperone Aha1 downregulation rescues misfolding of CFTR in cystic fibrosis. Cell 127, 803–815. 3. Kumar, C., and Mann, M. (2009) Bioinformatics analysis of mass spectrometrybased proteomics data sets. FEBS Lett 583, 1703–1712.

4. Yates, J. R., Ruse, C. I., and Nakorchevsky, A. (2009) Proteomics by mass spectrometry: approaches, advances, and applications. Annu Rev Biomed Eng 11, 49–79. 5. Davezac, N., Tondelier, D., Lipecka, J., Fanen, P., Demaugre, F., Debski, J., et al. (2004) Global proteomic approach unmasks involvement of keratins 8 and 18 in the delivery of cystic fibrosis transmembrane conductance regulator (CFTR)/deltaF508CFTR to the plasma membrane. Proteomics 4, 3833–3844.

Mass Spectrometry in Cystic Fibrosis 6. Roxo-Rosa, M., Davezac, N., Bensalem, N., Majumder, M., Heda, G. D., Simas, A., et al. (2004) Proteomics techniques for cystic fibrosis research. J Cyst Fibros 3, 85–89. 7. Singh, O. V., Pollard, H. B., and Zeitlin, P. L. (2008) Chemical rescue of deltaF508CFTR mimics genetic repair in cystic fibrosis bronchial epithelial cells. Mol Cell Proteomics 7, 1099–1110. 8. Pollard, H. B., Eidelman, O., Jozwik, C., Huang, W., Srivastava, M., Ji, X. D., et al. (2006) De novo biosynthetic profiling of high abundance proteins in cystic fibrosis lung epithelial cells. Mol Cell Proteomics 5, 1628–1637. 9. Singh, O. V., Vij, N., Mogayzel, P. J., Jr., Jozwik, C., Pollard, H. B., and Zeitlin, P. L. (2006) Pharmacoproteomics of 4phenylbutyrate-treated IB3-1 cystic fibrosis bronchial epithelial cells. J Proteome Res 5, 562–571. 10. Pollard, H. B., Ji, X. D., Jozwik, C., and Jacobowitz, D. M. (2005) High abundance protein profiling of cystic fibrosis lung epithelial cells. Proteomics 5, 2210–2226. 11. Penque, D. (2007) Proteomic biomarker discovery for the monogenic disease cystic fibrosis. Expert Rev Proteomics 4, 199–209. 12. Gomes-Alves, P., Imrie, M., Gray, R. D., Nogueira, P., Ciordia, S., Pacheco, P., et al. (2010) SELDI-TOF biomarker signatures for cystic fibrosis, asthma and chronic obstructive pulmonary disease. Clin Biochem 43, 168–177. 13. Gharib, S. A., Vaisar, T., Aitken, M. L., Park, D. R., Heinecke, J. W., and Fu, X. (2009) Mapping the lung proteome in cystic fibrosis. J Proteome Res 8, 3020–3028. 14. Chang, D. W., Hayashi, S., Gharib, S. A., Vaisar, T., King, S. T., and Tsuchiya, M. (2008) Proteomic and computational analysis of bronchoalveolar proteins during the course of the acute respiratory distress syndrome. Am J Respir Crit Care Med 178, 701–709. 15. Fu, X., Gharib, S. A., Green, P. S., Aitken, M. L., Frazer, D. A., Park, D. R., et al. (2008) Spectral index for assessment of differential protein expression in shotgun proteomics. J Proteome Res 7, 845–854. 16. Gray, R. D., MacGregor, G., Noble, D., Imrie, M., Dewar, M., Boyd, A. C., et al. (2008) Sputum proteomics in inflammatory and suppurative respiratory diseases. Am J Respir Crit Care Med 178, 444–452. 17. MacGregor, G., Gray, R. D., Hilliard, T. N., Imrie, M., Boyd, A. C., Alton, E. W., et al. (2008) Biomarkers for cystic fibrosis lung disease: application of SELDI-TOF mass spec-

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21.

22.

23.

24.

25.

26.

27.

28.

29.

241

trometry to BAL fluid. J Cyst Fibros 7, 352–358. Nicholas, B. L., O’Connor, C. D., and Djukanovic, R. (2009) From proteomics to prescription-the search for COPD biomarkers. COPD 6, 298–303. Nicholas, B., and Djukanovic, R. (2009) Induced sputum: a window to lung pathology. Biochem Soc Trans 37, 868–872. Nicholas, B., Skipp, P., Mould, R., Rennard, S., Davies, D. E., O‘Connor, C. D., et al. (2006) Shotgun proteomic analysis of human-induced sputum. Proteomics 6, 4390–4401. Lau, A. T., and Chiu, J. F. (2009) Biomarkers of lung-related diseases: current knowledge by proteomic approaches. J Cell Physiol 221, 535–543. Thelin, W. R., Chen, Y., Gentzsch, M., Kreda, S. M., Sallee, J. L., Scarlett, C. O., et al. (2007) Direct interaction with filamins modulates the stability and plasma membrane expression of CFTR. J Clin Invest 117, 364–374. Gomes-Alves, P., Neves, S., Coelho, A. V., and Penque, D. (2009) Low temperature restoring effect on F508del-CFTR misprocessing: a proteomic approach. J Proteomics 73, 218–230. Gomes-Alves, P., Couto, F., Pesquita, C., Coelho, A. V., and Penque, D. (2010) Rescue of F508del-CFTR by RXR motif inactivation triggers proteome modulation associated with the unfolded protein response. Biochim Biophys Acta 1804, 856–865. Jiang, H., Ramos, A. A., and Yao, X. (2010) Targeted quantitation of overexpressed and endogenous cystic fibrosis transmembrane conductance regulator using multiple reaction monitoring tandem mass spectrometry and oxygen stable isotope dilution. Anal Chem 82, 336–342. Yates, J., Ruse, C. I., and Nakorchevsky, A. (2009) Proteomics by mass spectrometry: approaches, advances, and applications. Annu Rev Biomed Eng 11, 49–79. Hillenkamp, F., and Karas, M. (1990) Mass spectrometry of peptides and proteins by matrix-assisted ultraviolet laser desorption/ionization. Methods Enzymol 193, 280–295. Tanaka, K. (2003) The origin of macromolecule ionization by laser irradiation (Nobel Lecture). Angew Chem Int Ed Engl 42, 3860–3870. Fenn, J. B., Mann, M., Meng, C. K., Wong, S. F., and Whitehouse, C. M. (1989) Electrospray ionization for mass spectrometry of large biomolecules. Science 246, 64–71.

242

Balch and Yates III

30. Silvertand, L. H., Torano, J. S., de Jong, G. J., and van Bennekom, W. P. (2008) Improved repeatability and matrixassisted desorption/ionization – time of flight mass spectrometry compatibility in capillary isoelectric focusing. Electrophoresis 29, 1985–1996. 31. Zheng, J., Li, N., Ridyard, M., Dai, H., Robbins, S. M., and Li, L. (2005) Simple and robust two-layer matrix/sample preparation method for MALDI MS/MS analysis of peptides. J Proteome Res 4, 1709–1716. 32. Chen, Y., Wall, D., and Lubman, D. M. (1998) Rapid identification and screening of proteins from whole cell lysates of human erythroleukemia cells in the liquid phase, using non-porous reversed phase highperformance liquid chromatography separations of proteins followed by matrix-assisted laser desorption/ionization mass spectrometry analysis and sequence database searching. Rapid Commun Mass Spectrom 12, 1994–2003. 33. Shen, Y., Zhao, R., Belov, M. E., Conrads, T. P., Anderson, G. A., Tangm, K., et al. (2001) Packed capillary reversed-phase liquid chromatography with high-performance electrospray ionization Fourier transform ion cyclotron resonance mass spectrometry for proteomics. Anal Chem 73, 1766–1775. 34. Laiko, V. V., Baldwin, M. A., and Burlingame, A. L. (2000) Atmospheric pressure matrix-assisted laser desorption/ionization mass spectrometry. Anal Chem 72, 652–657. 35. Merchant, M., and Weinberger, S. R. (2000) Recent advancements in surface-enhanced laser desorption/ionization-time of flightmass spectrometry. Electrophoresis 21, 1164–1177. 36. Felitsyn, N., Peschke, M., and Kebarle, P. (2002) Origin and number of charges observed on multiply-protonated native proteins produced by ESI. Int J Mass Spectrom 219, 39–62. 37. Shen, Y., Moore, R. J., Zhao, R., Blonder, J., Auberry, D. L., Masselon, C., et al. (2003) High-efficiency on-line solid-phase extraction coupling to 15-150-microm-i.d. column liquid chromatography for proteomic analysis. Anal Chem 75, 3264–3273. 38. Shen, Y., and Smith, R. D. (2002) Proteomics based on high-efficiency capillary separations. Electrophoresis 23, 3106–3124. 39. Edmond de Hoffmann, V. S. (2007) Mass Spectrometry, 3rd ed. Wiley, London, p. 489. 40. Han, X., Aslanian, A., and Yates, J. R., 3rd. (2008) Mass spectrometry for proteomics. Curr Opin Chem Biol 12, 483–490.

41. Yates, J. R., 3rd. (2004) Mass spectral analysis in proteomics. Annu Rev Biophys Biomol Struct 33, 297–316. 42. Liu, T., Belov, M. E., Jaitly, N., Qian, W. J., and Smith, R. D. (2007) Accurate mass measurements in proteomics. Chem Rev 107, 3621–3653. 43. Perry, R. H., Cooks, R. G., and Noll, R. J. (2008) Orbitrap mass spectrometry: instrumentation, ion motion and applications. Mass Spectrom Rev 27, 661–699. 44. Brancia, F. L. (2006) Recent developments in ion-trap mass spectrometry and related technologies. Expert Rev Proteomics 3, 143–151. 45. Domon, B., and Aebersold, R. (2006) Mass spectrometry and protein analysis. Science 312, 212–217. 46. Hager, J. W. (2003) Product ion spectral simplification using time-delayed fragment ion capture with tandem linear ion traps. Rapid Commun Mass Spectrom 17, 1389–1398. 47. Hardman, M., and Makarov, A. A. (2003) Interfacing the orbitrap mass analyzer to an electrospray ion source. Anal Chem 75, 1699–1705. 48. Hu, Q., Noll, R. J., Li, H., Makarov, A., Hardman, M., and Graham Cooks, R. (2005) The orbitrap: a new mass spectrometer. J Mass Spectrom 40, 430–443. 49. Makarov, A., Denisov, E., Lange, O., and Horning, S. (2006) Dynamic range of mass accuracy in LTQ orbitrap hybrid mass spectrometer. J Am Soc Mass Spectrom 17, 977–982. 50. Syka, J. E., Coon, J. J., Schroeder, M. J., Shabanowitz, J., and Hunt, D. F. (2004) Peptide and protein sequence analysis by electron transfer dissociation mass spectrometry. Proc Natl Acad Sci USA 101, 9528–9533. 51. Breuker, K., Jin, M., Han, X., Jiang, H., and McLafferty, F. W. (2008) Top-down identification and characterization of biomolecules by mass spectrometry. J Am Soc Mass Spectrom 19, 1045–1053. 52. Shevchenko, A., Chernushevich, I., Ens, W., Standing, K. G., Thomson, B., Wilm, M., et al. (1997) Rapid “de novo” peptide sequencing by a combination of nanoelectrospray, isotopic labeling and a quadrupole/time-of-flight mass spectrometer. Rapid Commun Mass Spectrom 11, 1015–1024. 53. Collings, B. A., Campbell, J. M., Mao, D., and Douglas, D. J. (2001) A combined linear ion trap time-of-flight system with improved performance and MS(n) capabilities. Rapid Commun Mass Spectrom 15, 1777–1795.

Mass Spectrometry in Cystic Fibrosis 54. Douglas, D. J., Frank, A. J., and Mao, D. (2005) Linear ion traps in mass spectrometry. Mass Spectrom Rev 24, 1–29. 55. Schwartz, J. C., Senko, M. W., and Syka, J. E. (2002) A two-dimensional quadrupole ion trap mass spectrometer. J Am Soc Mass Spectrom 13, 659–669. 56. Yates, J. R., Cociorva, D., Liao, L., and Zabrouskov, V. (2006) Performance of a linear ion trap-Orbitrap hybrid for peptide analysis. Anal Chem 78, 493–500. 57. Macek, B., Waanders, L. F., Olsen, J. V., and Mann, M. (2006) Top-down protein sequencing and MS3 on a hybrid linear quadrupole ion trap-orbitrap mass spectrometer. Mol Cell Proteomics 5, 949–958. 58. Frank, A. M., Pesavento, J. J., Mizzen, C. A., Kelleher, N. L., and Pevzner, P. A. (2008) Interpreting top-down mass spectra using spectral alignment. Anal Chem 80, 2499–2505. 59. Bakalarski, C. E., Elias, J. E., Villén, J., Haas, W., Gerber, S. A., Everley, P. A., et al. (2008) The impact of peptide abundance and dynamic range on stable-isotope-based quantitative proteomic analyses. J Proteome Res 7, 4756–4765. 60. Schenk, S., Schoenhals, G. J., Souza, G. D., and Mann, M. (2008) A high confidence, manually validated human blood plasma protein reference set. BMC Med Genomics 1, 41–75. 61. Junqueira, M., Spirin, V., Balbuena, T. S., Thomas, H., Adzhubei, I., Sunyaev, S., et al. (2008) Protein identification pipeline for the homology-driven proteomics. J Proteomics 71, 346–356. 62. DiMaggio, P. A., Jr., Floudas, C. A., Lu, B., and Yates, J. R., 3rd. (2008) A hybrid method for peptide identification using integer linear optimization, local database search, and quadrupole time-of-flight or OrbiTrap tandem mass spectrometry. J Proteome Res 7, 1584–1593. 63. Lu, B., Motoyama, A., Ruse, C., Venable, J., and Yates, J. R., 3rd. (2008) Improving protein identification sensitivity by combining MS and MS/MS information for shotgun proteomics using LTQ-Orbitrap high mass accuracy data. Anal Chem 80, 2018–2025. 64. Herbert, B. R., Harry, J. L., Packer, N. H., Gooley, A. A., Pedersen, S. K., and Williams, K. L. (2001) What place for polyacrylamide in proteomics? Trends Biotechnol 19, S3–S9. 65. Monteoliva, L., and Albar, J. P. (2004) Differential proteomics: an overview of gel and non-gel based approaches. Brief Funct Genomic Proteomic 3, 220–239.

243

66. Braun, R. J., Kinkl, N., Beer, M., and Ueffing, M. (2007) Two-dimensional electrophoresis of membrane proteins. Anal Bioanal Chem 389, 1033–1045. 67. Cooper, J. W., Wang, Y., and Lee, C. S. (2004) Recent advances in capillary separations for proteomics. Electrophoresis 25, 3913–3926. 68. Fournier, M. L., Gilmore, J., Martin-Brown, S. A., and Washburn, M. P. (2007) Multidimensional separations-based shotgun proteomics. Chem Rev 107, 3654–3686. 69. Shen, Y., Zhao, R., Berger, S. J., Anderson, G. A., Rodriguez, N., and Smith, R. D. (2002) High-efficiency nanoscale liquid chromatography coupled on-line with mass spectrometry using nanoelectrospray ionization for proteomics. Anal Chem 74, 4235–4249. 70. Shen, Y., Strittmatter, E. F., Zhang, R., Metz, T. O., Moore, R. J., Li, F., et al. (2005) Making broad proteome protein measurements in 1–5 min using high-speed RPLC separations and high-accuracy mass measurements. Anal Chem 77, 7763–7773. 71. Shen, Y., and Smith, R. D. (2005) Advanced nanoscale separations and mass spectrometry for sensitive high-throughput proteomics. Expert Rev Proteomics 2, 431–447. 72. Anspach, J. A., Maloney, T. D., Brice, R. W., and Colon, L. A. (2005) Injection valve for ultrahigh-pressure liquid chromatography. Anal Chem 77, 7489–7494. 73. Anspach, J. A., Maloney, T. D., and Colon, L. A. (2007) Ultrahigh-pressure liquid chromatography using a 1–mm id column packed with 1.5-microm porous particles. J Sep Sci 30, 1207–1213. 74. Motoyama, A., Venable, J. D., Ruse, C. I., and Yates, J. R., 3rd. (2006) Automated ultra-high-pressure multidimensional protein identification technology (UHP-MudPIT) for improved peptide identification of proteomic samples. Anal Chem 78, 5109–5118. 75. Chi, A., Huttenhower, C., Geer, L. Y., Coon, J. J., Syka, J. E., Bai, D. L., et al. (2007) Analysis of phosphorylation sites on proteins from Saccharomyces cerevisiae by electron transfer dissociation (ETD) mass spectrometry. Proc Natl Acad Sci USA 104, 2193–2198. 76. Delahunty, C. M., and Yates, J. R., 3rd. (2007) MudPIT: multidimensional protein identification technology. Biotechniques 43, 563–567. 77. Stoll, D. R., Wang, X., and Carr, P. W. (2008) Comparison of the practical resolving power of one- and two-dimensional highperformance liquid chromatography analy-

244

78.

79.

80.

81.

82.

83.

84.

85.

86.

87.

88.

Balch and Yates III sis of metabolomic samples. Anal Chem 80, 89. Li, K. W., and Jimenez, C. R. (2008) Synapse proteomics: current status and quan268–278. titative applications. Expert Rev Proteomics 5, Guzzetta, A. W., and Chien, A. S. (2005) 353–360. A double-vented tetraphasic continuous column approach to mudpit analysis on 90. Zhou, M., and Veenstra, T. D. (2007) Proteomic analysis of protein complexes. Prolong capillary columns demonstrates supeteomics 7, 2688–2697. rior proteomic coverage. J Proteome Res 4, 91. Cantin, G. T., et al. (2008) Combining 2412–2419. protein-based IMAC, peptide-based IMAC, Shen, Y., Toli´c, N., Masselon, C., Pasa-Toli´c, and MudPIT for efficient phosphoproteomic L., Camp, D. G., 2nd., Lipton, M. S., et al. analysis. J Proteome Res 7, 1346–1351. (2004) Nanoscale proteomics. Anal Bioanal 92. Han, G., et al. (2008) Large-scale phosphoChem 378, 1037–1045. proteome analysis of human liver tissue by Motoyama, A., Xu, T., Ruse, C. I., enrichment and fractionation of phosphoWohlschlegel, J. A., and Yates, J. R., 3rd. peptides with strong anion exchange chro(2007) Anion and cation mixed-bed ion matography. Proteomics 8, 1346–1361. exchange for enhanced multidimensional separations of peptides and phosphopeptides. 93. McNulty, D. E., and Annan, R. S. (2008) Hydrophilic interaction chromatography Anal Chem 79, 3623–3634. reduces the complexity of the phosphoproDowell, J. A., Frost, D. C., Zhang, J., teome and improves global phosphopeptide and Li, L. (2008) Comparison of twoisolation and detection. Mol Cell Proteomics dimensional fractionation techniques for 7, 971–980. shotgun proteomics. Anal Chem 80, 94. Zaia, J. (2008) Mass spectrometry and the 6715–6723. emerging field of glycomics. Chem Biol 15, Macek, B., Mann, M., and Olsen, J. V. 881–892. (2009) Global and site-specific quantitative phosphoproteomics: principles and appli- 95. Tissot, B., et al. (2009) Glycoproteomics: past, present and future. FEBS Lett 583, cations. Annu Rev Pharmacol Toxicol 49, 1728–1735. 199–221. Ficarro, S. B., McCleland, M. L., Stuken- 96. Wei, X., and Li, L. (2009) Comparative glycoproteomics: approaches and applications. berg, P. T., Burke, D. J., Ross, M. M., Brief Funct Genom Proteomic 8, 104–113. Shabanowitz, J., et al. (2002) Phosphoproteome analysis by mass spectrometry and its 97. Dai, Z., Zhou, J., Qiu, S. J., Liu, Y. K., and Fan, J. (2009) Lectin-based glycoproapplication to Saccharomyces cerevisiae. Nat teomics to explore and analyze hepatocelluBiotechnol 20, 301–305. lar carcinoma-related glycoprotein markers. Tsai, C. F., et al. (2008) Immobilized metal affinity chromatography revisited: pH/Acid Electrophoresis 30, 2957–2966. control toward high selectivity in phospho- 98. Yue, T., and Haab, B. B. (2009) Microarrays proteomics. J Proteome Res 7, 4058–4069. in glycoproteomics research. Clin Lab Med Linding, R., Jensen, L. J., Ostheimer, G. J., 29, 15–29. van Vugt, M. A., Jørgensen, C., Miron, 99. Ito, S., Hayama, K., and Hirabayashi, J. I. M., et al. (2007) Systematic discovery of (2009) Enrichment strategies for glycopepin vivo phosphorylation networks. Cell 129, tides. Methods Mol Biol 534, 195–203. 1415–1426. 100. Atwood, J. A., 3rd., et al. (2006) GlycoproFeng, S., et al. (2007) Immobilized zircoteomics of trypanosoma cruzi trypomastignium ion affinity chromatography for speotes using subcellular fractionation, lectin cific enrichment of phosphopeptides in phosaffinity, and stable isotope labeling. J Prophoproteome analysis. Mol Cell Proteomics 6, teome Res 5, 3376–3384. 1656–1665. 101. Yue, G., Luo, Q., Zhang, J., Wu, S. L., Sykora, C., Hoffmann, R., and Hoffmann, and Karger, B. L. (2007) Ultratrace LC/MS P. (2007) Enrichment of multiphosphoryproteomic analysis using 10-microm-i.d. lated peptides by immobilized metal affinity Porous layer open tubular poly(styrenechromatography using Ga(III)- and Fe(III)divinylbenzene) capillary columns. Anal complexes. Protein Pept Lett 14, 489–496. Chem 79, 938–946. Pinkse, M. W., Uitto, P. M., Hilhorst, M. J., 102. Durham, M., and Regnier, F. E. (2006) Ooms, B., and Heck, A. J. (2004) Selective Targeted glycoproteomics: serial lectin affinisolation at the femtomole level of phosphoity chromatography in the selection of peptides from proteolytic digests using 2DO-glycosylation sites on proteins from the NanoLC-ESI-MS/MS and titanium oxide human blood proteome. J Chromatogr 1132, precolumns. Anal Chem 76, 3935–3943. 165–173.

Mass Spectrometry in Cystic Fibrosis 103. Spange, S., Wagner, T., Heinzel, T., and Kramer, O. H. H. (2009) Acetylation of nonhistone proteins modulates cellular signalling at multiple levels. Int J Biochem Cell Biol 4, 185–198. 104. Norris, K. L., Lee, J. Y., and Yao, T. P. (2009) Acetylation goes global: the emergence of acetylation biology. Sci Signal 2, 76–83. 105. Smith, K. T., and Workman, J. L. (2009) Introducing the acetylome. Nat Biotechnol 27, 917–919. 106. Choudhary, C., et al. (2009) Lysine acetylation targets protein complexes and coregulates major cellular functions. Science 325, 834–840. 107. Hutt, D. M., et al. (2010) Reduced histone deacetylase 7 activity restores function to misfolded CFTR in cystic fibrosis. Nat Chem Biol 6, 25–33. 108. Hutt, D. M., Powers, E. T., and Balch, W. E. (2009) The proteostasis boundary in misfolding diseases of membrane traffic. FEBS Lett 583, 2639–2646. 109. McDonald, W. H., and Yates, J. R., 3rd. (2003) Shotgun proteomics: integrating technologies to answer biological questions. Curr Opin Mol Ther 5, 302–309. 110. Chait, B. T. (2006) Chemistry. Mass spectrometry: bottom-up or top-down? Science 314, 65–66. 111. Eng, J., McCormack, A., and Yates, J. (1994) An approach to correlate tandem mass spectral data of peptides with amino acid sequences in a protein database. J Am Soc Mass Spectrom 5, 976–989. 112. Anderson, D. C., Li, W., Payan, D. G., and Noble, W. S. (2003) A new algorithm for the evaluation of shotgun peptide sequencing in proteomics: support vector machine classification of peptide MS/MS spectra and SEQUEST scores. J Proteome Res 2, 137–146. 113. Keller, A., Nesvizhskii, A. I., Kolker, E., and Aebersold, R. (2002) Empirical statistical model to estimate the accuracy of peptide identifications made by MS/MS and database search. Anal Chem 74, 5383–5392. 114. MacCoss, M. J., et al. (2002) Shotgun identification of protein modifications from protein complexes and lens tissue. Proc Natl Acad Sci USA 99, 7900–7905. 115. Perkins, D. N., Pappin, D. J., Creasy, D. M., and Cottrell, J. S. (1999) Probability-based protein identification by searching sequence databases using mass spectrometry data. Electrophoresis 20, 3551–3567. 116. Sadygov, R., and Yates, J. R., 3rd. (2003) A hypergeometric probability model for protein identification and validation using tan-

117.

118.

119.

120.

121.

122. 123.

124.

125.

126.

127.

128.

245

dem mass spectral data and protein sequence databases. Anal Chem 75, 3792–3798. Tabb, D. L., McDonald, H. W., and Yates, J. R., III (2002) DTASelect and contrast: tools for assembling and comparing protein identifications from shotgun proteomics. J Proteome Res 1, 21–36. Keller, L. C., Romijn, E. P., Zamora, I., Yates, J. R., 3rd., and Marshall, W. F. (2005) Proteomic analysis of isolated chlamydomonas centrioles reveals orthologs of ciliary-disease genes. Curr Biol 15, 1090–1098. Moore, R. E., Young, M. K., and Lee, T. D. (2000) Method for screening peptide fragment ion mass spectra prior to database searching. J Am Soc Mass Spectrom 11, 422–426. Frewen, B., and MacCoss, M. J. (2007) Using bibliospec for creating and searching tandem MS peptide libraries. Curr Protoc Bioinformatics 13 13, 17. Gygi, S. P., et al. (1999) Quantitative analysis of complex protein mixtures using isotopecoded affinity tags. Nat Biotechnol 17, 994–999. Bettmer, J., et al. (2009) The emerging role of ICP-MS in proteomic analysis. J Proteomics 72, 989–1005. Schnolzer, M., Jedrzejewski, P., and Lehmann, W. D. (1996) Protease-catalyzed incorporation of 18O into peptide fragments and its application for protein sequencing by electrospray and matrix-assisted laser desorption/ionization mass spectrometry. Electrophoresis 17, 945–953. Thompson, A., et al. (2003) Tandem mass tags: a novel quantification strategy for comparative analysis of complex protein mixtures by MS/MS. Anal Chem 75, 1895–1904. Siuti, N., and Kelleher, N. L. (2007) Decoding protein modifications using topdown mass spectrometry. Nat Methods 4, 817–821. Zabrouskov, V., et al. (2006) Stepwise deamidation of ribonuclease A at five sites determined by top down mass spectrometry. Biochemistry 45, 987–992. Hawkridge, A. M., et al. (2005) Quantitative mass spectral evidence for the absence of circulating brain natriuretic peptide (BNP-32) in severe human heart failure. Proc Natl Acad Sci USA 102, 17442–17447. Uttenweiler-Joseph, S., et al. (2008) Toward a full characterization of the human 20 s proteasome subunits and their isoforms by a combination of proteomic approaches. Methods Mol Biol 484, 111–130.

246

Balch and Yates III

129. Pesavento, J. J., Mizzen, C. A., and Kelleher, N. L. (2006) Quantitative analysis of modified proteins and their positional isomers by tandem mass spectrometry: human histone H4. Anal Chem 78, 4271–4280. 130. Du, Y., Parks, B. A., Sohn, S., Kwast, K. E., and Kelleher, N. L. (2006) Top-down approaches for measuring expression ratios of intact yeast proteins using Fourier transform mass spectrometry. Anal Chem 78, 686–694. 131. Waanders, L. F., Hanke, S., and Mann, M. (2007) Top-down quantitation and characterization of SILAC-labeled proteins. J Am Soc Mass Spectrom 18, 2058–2064. 132. Sharma, S., et al. (2007) Proteomic profiling of intact proteins using WAX-RPLC 2-D separations and FTICR mass spectrometry. J Proteome Res 6, 602–610. 133. Bunger, M. K., Cargile, B. J., Ngunjiri, A., Bundy, J. L., and Stephenson, J. L., Jr. (2008) Automated proteomics of E. coli via top-down electron-transfer dissociation mass spectrometry. Anal Chem 80, 1459–1467. 134. Krijgsveld, J., et al. (2003) Metabolic labeling of C. elegans and D. melanogaster for quantitative proteomics. Nat Biotechnol 21, 927–931. 135. Wu, C. C., MacCoss, M. J., Howell, K. E., Matthews, D. E., and Yates, J. R., 3rd. (2004) Metabolic labeling of mammalian organisms with stable isotopes for quantitative proteomic analysis. Anal Chem 76, 4951–4959. 136. Ong, S. E., et al. (2002) Stable isotope labeling by amino acids in cell culture, SILAC, as a simple and accurate approach to expression proteomics. Mol Cell Proteomics 1, 376–386. 137. Ong, S. E., and Mann, M. (2005) Mass spectrometry-based proteomics turns quantitative. Nat Chem Biol 1, 252–262. 138. Ibarrola, N., Molina, H., Iwahori, A., and Pandey, A. (2004) A novel proteomic approach for specific identification of tyrosine kinase substrates using [13C]tyrosine. J Biol Chem 279, 15805–15813. 139. Gruhler, A., Schulze, W. X., Matthiesen, R., Mann, M., and Jensen, O. N. (2005) Stable isotope labeling of arabidopsis thaliana cells and quantitative proteomics by mass spectrometry. Mol Cell Proteomics 4, 1697–1709. 140. Gruhler, A., et al. (2005) Quantitative phosphoproteomics applied to the yeast pheromone signaling pathway. Mol Cell Proteomics 4, 310–327. 141. Spellman, D. S., Deinhardt, K., Darie, C. C., Chao, M. V., and Neubert, T. A. (2008) Stable isotopic labeling by amino acids in cultured primary neurons: application to brain-derived neurotrophic factor-

142.

143.

144.

145.

146.

147.

148.

149.

150.

151.

152.

153.

154.

dependent phosphotyrosine-associated signaling. Mol Cell Proteomics 7, 1067–1076. Kruger, M., et al. (2008) SILAC mouse for quantitative proteomics uncovers kindlin-3 as an essential factor for red blood cell function. Cell 134, 353–364. Ong, S. E., Foster, L. J., and Mann, M. (2003) Mass spectrometric-based approaches in quantitative proteomics. Methods 29, 124–130. Bendall, S. C., et al. (2008) Prevention of amino acid conversion in SILAC experiments with embryonic stem cells. Mol Cell Proteomics 7, 1587–1597. Van Hoof, D., et al. (2007) An experimental correction for arginine-to-proline conversion artifacts in SILAC-based quantitative proteomics. Nat Methods 4, 677–678. Park, S. K., Venable, J. D., Xu, T., and Yates, J. R., 3rd. (2008) A quantitative analysis software tool for mass spectrometry-based proteomics. Nat Methods 5, 319–322. Gygi, S. P., et al. (1999) Quantitative analysis of complex protein mixtures using isotopecoded affinity tags. Nat Biotechnol 17, 994–999. Ross, P. L., et al. (2004) Multiplexed protein quantitation in saccharomyces cerevisiae using amine-reactive isobaric tagging reagents. Mol Cell Proteomics 3, 1154–1169. Gerber, S. A., Rush, J., Stemman, O., Kirschner, M. W., and Gygi, S. P. (2003) Absolute quantification of proteins and phosphoproteins from cell lysates by tandem MS. Proc Natl Acad Sci USA 100, 6940–6945. Beynon, R. J., Doherty, M. K., Pratt, J. M., and Gaskell, S. J. (2005) Multiplexed absolute quantification in proteomics using artificial QCAT proteins of concatenated signature peptides. Nat Methods 2, 587–589. Hanke, S., Besir, H., Oesterhelt, D., and Mann, M. (2008) Absolute SILAC for accurate quantitation of proteins in complex mixtures down to the attomole level. J Proteome Res 7, 1118–1130. Choe, L., et al. (2007) 8-plex quantitation of changes in cerebrospinal fluid protein expression in subjects undergoing intravenous immunoglobulin treatment for Alzheimer’s disease. Proteomics 7, 3651–3660. Schwartz, J., Syka, J., and Quarmby, S. (2005) Improving the fundamentals of MSn on 2D linear ion traps: new ion activation and isolation techniques. Am Soc Mass Spectrom 54, 67–76. Griffin, T. J., et al. (2007) iTRAQ reagentbased quantitative proteomic analysis on a linear ion trap mass spectrometer. J Proteome Res 6, 4200–4209.

Mass Spectrometry in Cystic Fibrosis

247

peptide ion chromatograms and spectrum 155. Phanstiel, D., Zhang, Y., Marto, J. A., and counting for quantitative proteomic analysis Coon, J. J. (2008) Peptide and protein quanusing stable isotope labeling. Anal Chem 77, tification using iTRAQ with electron trans6218–6224. fer dissociation. J Am Soc Mass Spectrom 19, 158. Mueller, L. N., Brusniak, M. Y., Mani, D. 1255–1262. R., and Aebersold, R. (2008) An assessment 156. Liu, H., Sadygov, R. G., and Yates, J. R., of software solutions for the analysis of mass 3rd. (2004) A model for random sampling spectrometry based quantitative proteomics and estimation of relative protein abundata. J Proteome Res 7, 51–61. dance in shotgun proteomics. Anal Chem 76, 159. Everley, P. A., et al. (2006) Enhanced analy4193–4201. sis of metastatic prostate cancer using stable 157. Zybailov, B., Coleman, M. K., Florens, L., isotopes and high mass accuracy instrumenand Washburn, M. P. (2005) Correlation tation. J Proteome Res 5, 1224–1231. of relative abundance ratios derived from

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Chapter 15 Functional Genomics Assays to Study CFTR Traffic and ENaC Function Joana Almaça, Shehrazade Dahimène, Nicole Appel, Christian Conrad, Karl Kunzelmann, Rainer Pepperkok, and Margarida D. Amaral Abstract As several genomes have been sequenced, post-genomic approaches like transcriptomics and proteomics, identifying gene products differentially expressed in association with a given pathology, have held promise both of understanding the pathways associated with the respective disease and as a fast track to therapy. Notwithstanding, these approaches cannot distinguish genes and proteins with mere secondary pathological association from those primarily involved in the basic defect(s). New global strategies and tools identifying gene products responsible for the basic cellular defect(s) in CF pathophysiology currently being performed are presented here. These include high-content screens to determine proteins affecting function and trafficking of CFTR and ENaC. Key words: Cystic fibrosis, CFTR, secretory traffic, ENaC, high-content screens, siRNA, functional genomics.

1. Introduction The information of complete genome sequences and the identification and systematic cloning of human cDNAs provide the challenging opportunity to analyse the complexity of biological processes on a large scale. Systematic approaches, such as organelle proteomics or yeast two-hybrid screening, have attempted to identify structural and regulatory components of membrane

J. Almaça and S. Dahimène contributed equally to this work

M.D. Amaral, K. Kunzelmann (eds.), Cystic Fibrosis, Methods in Molecular Biology 742, DOI 10.1007/978-1-61779-120-8_15, © Springer Science+Business Media, LLC 2011

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traffic with the goal of reaching a more complete description of its molecular regulation. However, these techniques have limitations, not least of which is their lack of demonstrating a functional involvement of the molecules identified. Recent advances in automated fluorescence scanning microscopy and image processing allow the application of complete genome knowledge in large-scale screening applications with so far unmatched functional information at the single-cell or the sub-cellular level. Indeed, in combination with genomewide/high-content (HC) small-interference RNA (siRNA) or cDNA over-expression strategies, such microscopy-based applications hold promise to help revealing comprehensively the regulatory networks underlying several cellular processes, such as membrane traffic, in intact cells. These techniques, providing single-cell or even sub-cellular resolution, are thus of superior quality and far more informative than conventional highthroughput (HT) plate reader cell-based fluorescence analyses. For higher efficiency in dealing with HC siRNA/cDNA libraries, microscopy-based approaches can employ a ‘reverse transfection’ method, by which hundreds/thousands of siRNAs (or cDNAs) are pre-spotted on glass chambered slides and subsequently overlaid with cells which are thus locally ‘reverse transfected’ (1). Critical in this development is, however, demonstration of robustness and scalability, two essential prerequisites for large-scale HC functional screens to be conducted. Functional microscopy-based assays in living or fixed cells, coupled with large-scale genomic tools, have been recently developed and applied to solve problems in trafficking of membrane proteins (2–6), similar to that associated with F508del-CFTR (7). Such platform was demonstrated as suitable to perform genomewide siRNA screens addressing the question of which genes are required for transport of the temperature-sensitive variant of vesicular stomatitis virus glycoprotein (ts-O45-G) from the ER to the plasma membrane (3). Here, we describe how to apply cutting-edge HC microscopy-based screening technology to study traffic and function of two CF-related membrane proteins, namely the cystic fibrosis transmembrane conductance regulator (CFTR) and the sodium (Na+ ) epithelial channel (ENaC). 1.1. Secretomics of CFTR

The method described here was developed to be used in HC microscopy-based assays to monitor the traffic of wt-CFTR and F508del-CFTR in order to identify relevant intervenients in this process. To this end, two novel CFTR constructs (wt and F508del) were generated, namely bearing both an N terminusfused fluorescent tag (mCherry) and a Flag epitope tag located at CFTR 4th extracellular loop (8) (Fig. 15.1a). The Flag tag allows to quantify the CFTR that is exclusively localized at the cell surface by usage of an antibody applied extracellularly without cell

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Fig. 15.1. (A) Scheme of the novel CFTR constructs (wt and F508del) generated, with both an N-terminus-fused fluorescent tag (mCherry) and a Flag-tag located at CFTR 4th extracellular loop and example of microscopy images obtained from the stable A549 cells expressing the mCherry–Flag–wt-CFTR (B) or F508del-CFTR (C) constructs under a Tet-ON promoter, after induction with 1 μg/ml of doxycycline and 10 mM of sodium butyrate. The images to detect mCherry intracellular signal were obtained using the 661 nm laser (left panels). The images to detect the Flag staining performed without cell permeabilization to label exclusively protein at the plasma membrane were obtained using the 633-nm laser (right panels). Images were acquired using confocal microscope (LSM710, Zeiss). The pinhole opening was 4.5 μm. Scale bar = 10 μm.

permeabilization. On the other hand, usage of the fused mCherry tag (9) allows for quantification of the total amount of CFTR protein expressed by each individual cell assessed by the microscope in the screens. Together, these two tags allow to determine on each individual cell the fraction of expressed CFTR which is residing in the cell membrane in the trafficking assay. For the

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synchronized expression of CFTR and monitoring of its traffic through the secretory pathway, these two CFTR constructs (wt and F508del) were used in the establishment of stable human epithelial respiratory cell lines (A549 cells) under a tetracyclineinducible (Tet-ON) promoter. A549 cells are adenocarcinomic human alveolar basal epithelial cells, and they do not express CFTR endogenously. The presence of both tags (mCherry and Flag) does not impede trafficking of wt-CFTR to the plasma membrane, as shown by staining with the anti-flag antibody without cell permeabilization (Fig. 15.1b, right panel). Moreover, functional experiments showed that the mCherry–flag–wt-CFTR is still functional. It produced a cAMP-activated whole cell conductance (42 ± 3.2 nS; n = 11) that was comparable to that of non-tagged CFTR (37.3 ± 2.8 nS; n = 9). In contrast, F508del-CFTR is not detected at the plasma membrane in A549 cells but is retained in the intracellular compartment, plausibly in the endoplasmic reticulum (ER), as indicated by the mCherry signal (Fig. 15.1c, left panel), thus also recapitulating what is widely known for this mutant in several other cellular systems (7). The assays and image processing algorithms developed for the ts-O45-G screen (5) were the basis for the assays developed for wt-CFTR and F508del-CFTR described hereunder. 1.2. Functional Genomics of ENaC

For ENaC, a functional live-cell assay was selected, based on the activity of ENaC as sodium channel, which uses the FLIPR membrane potential (FMP) voltage-sensitive fluorescent (blue) dye in combination with the specific ENaC blocker amiloride (Fig. 15.2a). The negatively charged FMP dye enters the cells depending on their membrane voltage. If the cell membrane voltage is depolarized (less negative) due to active/open Na+ channels, which allows transport of Na+ ions into the cell, more FMP dye will be taken up by the cell and thus the fluorescence signal will be enhanced. Upon inhibition of ENaC with the specific inhibitor amiloride, cells become hyperpolarized (i.e. more negative) and FMP fluorescence is quenched, since less FMP dye is moving into the cell (for examples of results, see Fig. 15.4a). This assay can be applied to automatic microscopy screens of HC siRNA libraries spotted onto 384-spot chambered slides (Fig. 15.2b). The ‘primary’ assays described here, once being applied in the context of HT screens using HC siRNA/cDNA libraries, generate ‘hits’, which are genes/proteins affecting the traffic or function of CFTR and ENaC. These should nevertheless be validated by independent siRNAs targeting the same gene. Then, such validated ‘primary hits’ can constitute a basis for the development

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of more focussed ‘secondary’ assays specifically investigating particular aspects or specific pathways or the trafficking/function of (wt and mutant) CFTR and ENaC.

2. Materials 2.1. Reagents 2.1.1. Spotting of siRNAs

1. siRNA oligonucleotides (Ambion): Lyophilized siRNAs are dissolved with Milli-Q water to a final concentration of 30 μM. 2. Lipofectamine 2000 (Invitrogen, Cat. no 11668-019). 3. Sucrose (USB, Cat. no. 21938). 4. Gelatin (Sigma-Aldrich, Cat. no. G-9391). 5. Fibronectin, human (Sigma-Aldrich, Cat. no. F0895) (only required for spotting). 6. Drying pearls, orange – heavy metal free (Fluka, Cat. no. 94098).

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7. One-well or eight-well LabTek chambered glass slides (Nalge Nunc International, Cat. no 177372 or 177402, respectively) or 384-well, low-volume plates (Nalge Nunc International, Cat. no. 264360). 8. Sterile filters, 0.45 μm (Millipore, Cat. no. SCHVU01RE). Prepare the following solutions: 1. 0.2% (w/v) gelatin: Weigh 0.2 g gelatin and dissolve it in 100 ml water, heat this solution to 56◦ C for 20 min for dissolving. Let it cool down before use. For spotting (not for coating), add 10 μg/ml fibronectin to the 0.2% gelatin solution (this is the gelatin/fibronectin stock solution). Filter the solution with 0.45-μm pore filter (see Note 1). 2. Sucrose/OptiMEM solution (0.4 M sucrose): Weigh 1.37 g of sucrose and dissolve in 10 ml OptiMEM without shaking (see Note 1). 3. Transfection stock solution for liquid handler: 18 μl OptiMEM containing 0.4 M sucrose + 21 μl Lipofectamine 2000. 2.1.2. Traffic Assay for CFTR

1. OptiMEM I + GlutaMAX I (Gibco, Cat. no. 51985026). 2. DMEM/F12 supplemented with 10% foetal calf serum (FCS) and 2 mM glutamine. 3. Cell lines: Lung carcinoma cell line A549 (ATCC, Cat. no. CCL-185) stably transduced with lentivirus encoding for mCherry–flag–wt-CFTR or F508del-CFTR under Tet-ON promoter (generated by ADV Bioscience LLC, Birmingham, AL, USA). 4. Doxycycline (Sigma). 5. Sodium butyrate (Sigma). 6. Phosphate buffered solution (PBS). 7. Hoechst dye solution 33342 (Sigma, Cat. no. B2261). 8. Paraformaldehyde (PFA). 9. BSA (Sigma-Aldrich, Cat. no. A9056). 10. Monoclonal anti-flag M2 antibody produced in mouse (1 mg/ml; Sigma). 11. Cy5-conjugated anti-mouse secondary antibody (Molecular Probes).

2.1.3. Functional Assay for ENaC

1. OptiMEM I + GlutaMAX I (Gibco, Cat. No. 51985-026). 2. Mix of insulin/transferrin/selenium (Gibco, Cat. no. 41400-045). 3. Dexamethasone (Sigma, D4902).

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4. Human alveolar type 2 epithelial A549 cells (ATCC, Cat. no. CCL-185). 5. FLIPR membrane potential-sensitive (FMP) kit (Molecular Probes, Cat. no. R8042). 6. Amiloride hydrochloride (Sigma, A7410). 1. Growth medium: DMEM/F12 with 4.5 g/L D-glucose, supplemented with 10% (v/v) heatinactivated foetal calf serum (FCS), 2 mM glutamine, insulin/transferrin/selenium (1/100) and 100 nM dexamethasone. 2. Ringer solution: 145 mM NaCl, 0.4 mM KH2 PO4 , 1.6 mM K2 HPO4 , 5 mM glucose, 1 mM MgCl2 , and 1.3 mM Cagluconate (pH 7.4) (all chemicals are from Sigma). 3. FMP staining stock solution: Dissolve the powder from one vial of FMP (kit component A) in 10 ml of assay buffer (kit component B) (see Note 2). 2.2. Equipment 2.2.1. Spotting of siRNAs

1. Concentrator (MiVac, GeneVac). 2. Automated liquid handling robot (Microlab Star, Hamilton), equipped with 96-channel head and coolable carrier blocks for multi-well plates. 3. Heraeus Multifuge 3S (Kendro, Cat. No. 75004361). 4. Contact printers, ChipWriter (Compact and Pro; Bio-Rad Laboratories). 5. Temperature-controlled plate. 6. Solid pins (Point Technologies, Cat. no. PTS 600). 7. Gel drying box for storage of printed LabTeks (The Stewart Company).

2.2.2. Traffic Assay for CFTR

1. Confocal microscope (LSM 710, Zeiss) 63× objective. 2. Scanning microscope (Scan∧ R; Olympus Biosystems). 3. Filters: ET HQ TRITC/DsRED filter set (Ex: 545/30, Em: 620/60) to detect mCherry signal and filter set F36-523 (Ex: 628/40, Em: 692/40) to detect Flag staining (Cy5conjugated secondary antibody). 4. 10× objective (Olympus, Cat. no UPSLAPO 10×).

2.2.3. Functional Assay for ENaC

1. Scanning microscope (Scan∧ R; Olympus Biosystems). 2. Filter ET HQ TRITC/DsRED sputtered filter set (exciter: ET545/30; emitter: ET620/60; beam splitter: T570lp). 3. 10× objective (Olympus, Cat. No. UPSLAPO 10×). 4. Automated liquid dispenser (developed at EMBL).

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3. Methods 3.1. Spotting of siRNAs

Spotting of the siRNA libraries was performed as described before (10, 11) (see Note 3). 1. Put 3 μl of sucrose solution (0.4 M) in OptiMEM into a micro-centrifuge tube. 2. Add 1.75 μl Lipofectamine 2000 to the same tube and then 1.75 μl of water, mix thoroughly. 3. Add to the same tube 0.5 μl of siRNA (stock solution, 30 μM). Add 4.5 μl (or 4.0 μl, if you added two siRNAs) of water, so as to have a final volume of 11.5 μl, mix thoroughly (see Note 4). 4. Incubate for 20 min at room temperature (20–25◦ C) to allow the lipid–siRNA complexes to form. 5. Add 7.25 μl of the gelatin (± fibronectin) solution and mix thoroughly (see Note 5). 6. Transfer 18 μl of each transfection mix into each well of a 384-well plate with the same final desired layout of the LabTek (see Notes 6 and 7). 7. Dry the LabTek using a concentrator (MiVac, GeneVac) for 1 h at 37◦ C. 8. Store the coated LabTeks in a box with drying pearls (see Note 8).

3.2. Traffic Assay for CFTR

To identify proteins affecting CFTR trafficking, the strategy used was to knock down endogenous proteins with siRNAs. As positive controls for the assay, siRNAs for CFTR and joint (double) for COPII components (sec23Aa and sec23Ba) were used. Also ‘scrambled’ siRNA was employed as a negative control. Hereunder, is the step-by-step protocol adopted for the knock-down assay with control siRNAs performed using the reverse transfection method. For this assay, eight-well LabTeks coated with these control siRNAs are used.

3.2.1. Cell Seeding onto Pre-coated LabTeks

Stably inducible (Tet-ON) A549 cells expressing mCherry–flag– wt-CFTR or F508del-CFTR (see above) are maintained in DMEM/F12 supplemented with 10% FCS and 2 mM glutamine is seeded onto eight-well LabTeks pre-coated with siRNAs as described below: 1. Split almost confluent (∼90%) A549 cells 24 h prior to their seeding onto siRNA pre-coated LabTeks (see Note 9). 2. Trypsinize and count the cells on early log phase. 3. Seed at 5 × 103 cells/well onto siRNA pre-coated eight-well LabTeks (with ‘scrambled’, CFTR, and sec23Aa/sec23Ba siRNAs).

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4. Incubate the cells for 48 h in a growth medium at 37◦ C with 5% CO2 . 5. Induce CFTR expression by incubating the cells with 1 μg/ml doxycycline and 10 mM sodium butyrate for another 18 h. 3.2.2. Immunostaining of Cells on Chambered Slides

The protocol below is used to detect CFTR solely present at the plasma membrane. It is performed on non-fixed cells and uses an anti-flag antibody to detect the Flag epitope which is only externally accessible if the protein is at the membrane (see Note 10). 1. Rinse the LabTek three times with cold PBS. 2. Incubate the cells with the mouse anti-flag antibody (1:500) in PBS supplemented with 1% bovine serum albumin for 1 h at 4◦ C. 3. Rinse the LabTek three times with cold PBS. 4. Fix the cells with 4% paraformaldehyde for 20 min at room temperature. 5. Wash with PBS. 6. Incubate with rabbit anti-mouse Cy5-conjugated secondary antibody (1:500). 7. Rinse three times with PBS. 8. Incubate the cells with Hoechst dye (1/1000) for 15 min to stain the nuclei. 9. Wash the cells with PBS.

3.2.3. Image Acquisition 3.2.3.1. High-Resolution Images Acquired by Confocal Microscopy

Prior to the automatic image acquisition, high-resolution images (such as those shown in Fig. 15.1b, c) can be acquired with a confocal microscope (e.g. LSM710, Zeiss) to observe in detail the results from the assay.

3.2.3.2. Automatic Image Acquisition

Functional assays by gene downregulation by siRNA were performed on a widefield Scan∧ R microscopy system (Olympus), which allows to automatically acquire images at different positions of the well. 1. Set up the auto-focus based on the nuclei on the DAPI channel. 2. Choose exposure time and filter sets according to dye; in this assay DAPI, Cy3 and Cy5 channels that allow visualizing nuclei, mCherry and Flag staining signals were, respectively, used. 3. Choose the number of positions in each well to nine images per well. 4. Set up the first position. 5. Start automated data acquisition.

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Figure 15.3a shows examples of images acquired automatically by this approach. Cells treated with CFTR siRNA (middle row) show a reduced number of cells expressing mCherry, in comparison to cells transfected with ‘scrambled’ siRNA (top row), thus indicating that the siRNA transfection is efficient and that CFTR siRNAs are a good control to monitor siRNA transfection in these experiments. The double knock-down of COPII (bottom row) greatly inhibits CFTR trafficking to the plasma membrane as indicated by the decrease in the Flag signal (but not in the Cherry signal), in comparison to cells transfected with ‘scrambled’ siRNA (top row). This shows that these two siRNAs knocking down COPII constitute a good positive control to abolish wt-CFTR traffic in this kind of experiment. This assay can be scaled up to high-throughput screening microscopy on siRNA arrays to downregulate hundreds of genes. 3.2.4. Image Processing and Data Analysis

The goal of this assay is to measure the ratio of total CFTR at the plasma membrane (assessed by the Flag tag) vs total CFTR protein expressed (assessed by the mCherry tag) in order to identify proteins affecting CFTR transport. To do so, image processing is performed using Labview-based script as described below: 1. The images are first segmented in the Cy3 channel to identify single cells by their respective mCherry signal. 2. After background correction, the intensity of total CFTR expressed (measured by mCherry signal) and CFTR detected at the plasma membrane (assessed by a fluorescently labelled monoclonal antibody, flag–Cy5) is measured for each individual cell. 3. The intensity corresponding to the protein that is transported to the plasma membrane is divided by the intensity of the total protein in the cytoplasmic area (mCherry). 4. The median of the ratios is calculated per individual image and then a mean of these ratios is determined for the nine images of the same well.

 Fig. 15.3. (A) Example of A549 cells reverse-transfected with scrambled siRNA (top row), CFTR (middle row) or sec23Aa and sec23Ba siRNAs (bottom row). Forty-eight hours after reverse transfection, mCherry–flag–wt-CFTR expression was induced with 1 μg/ml of doxycycline and 10 mM of sodium butyrate for another 18 h. The intracellular localization was obtained using Cy3 filter (Ex: 545/30, Em: 620/60) to detect mCherry signal (middle column). Flag staining was performed without cell permeabilization (right row) and visualized using Cy5 filter (Ex: 628/40, Em: 692/40). The nuclei (left column) stained with Hoechst using DAPI filter (Ex: 350/50, Em: 460/50). Images were acquired with automated Scan∧ R system (Olympus). Scale bar = 30 μm. Summary of quantification of two independent experiments normalized to the scrambled values (18 images for each condition). (B) Bar graphs representing the mean of the ratio of cells expressing mCherry– flag–wt-CFTR treated with scrambled siRNA, CFTR or sec23Aa/Ba siRNAs as indicated vs total cells present under the same conditions (given by the stained nuclei). (C) Bar graphs representing the mean of the ratio of Flag Cy5 (total CFTR expressed at the plasma membrane) vs total CFTR expressed (mCherry). ∗ P < 0.05 vs scrambled siRNA.

Relative transport of Wt-CFTR (flag, Cy5 vs mCherry signal)

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5. Data are presented as means ± SEM and are analysed for significant differences using a standard Student’s t-test. Quantification of automatically acquired images (like those in Fig. 15.3a) by this approach can provide data on the proportion of cells expressing mCherry-CFTR vs the total number of cells present or the relative transport of wt-CFTR (Fig. 15.3b, c, respectively). 3.3. Functional Assay for ENaC

3.3.1. Cell Seeding onto Pre-coated LabTeks

The microscopy assay described here for ENaC is a functional assay, based on the activity of ENaC as a sodium channel. This is a live-cell assay and uses the FLIPR membrane potential (FMP) voltage-sensitive fluorescent (blue) dye, in combination with the specific ENaC blocker amiloride (Fig. 15.2a). The assay uses a human epithelial cell line, human alveolar type 2 epithelial A549 cell line, which expresses ENaC endogenously, being thus appropriate to detect variations in amiloride-sensitive currents (Fig. 15.4a). 1. Culture human alveolar type 2 epithelial A549 cells in DMEM/F12 supplemented with 10% FCS, glutamine, insulin/transferrin/selenium and 100 nM dexamethasone for several passages (at least for 5 days). 2. Trypsinize A549 cells on early log phase and seed them at 1 × 105 cells/ml on pre-spotted one-well LabTek chambered cover glass where 384 different human siRNAs had been spotted. 3. Allow reverse transfection to occur for 48 h in the CO2 incubator at 37◦ C.

3.3.2. Microscopy-Based Screening Assay

1. Pre-warm the microscope chamber to 37◦ C, turn on CO2 and the fluorescence lamp and the other Scan∧ R microscope components. 2. Dilute the FMP staining stock solution five times with Ringer solution (see Note 11) and add to half of it amiloride to obtain FMP/Ringer/amiloride (amil, final concentration 30 μM). Incubate both solutions at 37◦ C for 10 min. 3. Add this diluted FMP solution (no amil) to the cell array (chambered slide; LabTek) and incubate in the microscope chamber (at 37◦ C) for 10 min before imaging. 4. Start imaging each spot in the Scan∧ R microscope with a 10× objective in the Cy3 channel, with an exposure time of 25 ms and a gradient-based auto-focus, until spot 384th has been imaged (one image per spot is acquired). This is the first cycle of acquisition. 5. Replace the FMP solution by new FMP solution containing 30 μM amiloride, using an automatic liquid dispenser

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Fig. 15.4. (A) Example of the FMP assay for cells grown on spotted slides with control siRNAs. Images show A549 cells incubated with FMP and acquired before and after the addition of amiloride. As a positive control for the inhibition of ENaC transport, an siRNA targeting one of the subunits of the COPI coat proteins (ßCOP–siRNA) was used, whereas an siRNA targeting INCENP was used as a transfection control and polynucleated cells can be seen (see Note 12). (B) Bar graph representing the mean ± SEM (n = 4) of normalized amiloride-sensitive fluorescence ratios for cells grown on scrambled, ßCOP– and ßENaC–siRNA spots. The normalization applied was (spot fluorescence ratio – mean scrambled fluorescence ratio)/(2 × SD scrambled fluorescence ratio). ∗ represents a significant difference when compared to scrambled normalized ratios (unpaired t-test).

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adapted to the microscope stage (if available), or manually by carefully using an automatic pipette. 6. Three minutes after incubation with amiloride, start image acquisition of each spot, by the same order as in the first cycle, avoiding auto-focusing. This is the second cycle of acquisition (see Note 11). Figure 15.4a shows an example of the FMP assay for cells grown on spotted slides with control siRNAs. 3.3.3. Data Quantification

Quantify the intensity of FMP fluorescence per cell before and after the incubation with amiloride. A ratio between these two values can be used as a measure of the amount of ENaC that is expressed and active. The images acquired are processed and quantified using a Labview-based software by performing the steps indicated below: 1. Identify the correct pair of images per spot (each corresponding exactly to the same cells before and after amiloride addition). 2. After background correction, segment each cell using the corresponding FMP fluorescence in each image before amiloride addition and quantification of the signal (a ‘mask’ is created). 3. Apply the same ‘mask’ to the second image of each spot (after amiloride) and quantify the signal. 4. Calculate the amiloride-sensitive fluorescence ratio for each cell by applying the following formula:

Ratio =

Ibefore − Iafter × 100 Ibefore

where Ibefore is the intensity of FMP fluorescence before amiloride addition and Iafter is the same parameter after amiloride addition. 1. Calculate the median fluorescence ratio per spot taking into account each cell in every spot. 2. Normalize the median fluorescence ratio of each spot to the data obtained for the scrambled siRNA spots in the same LabTek. Quantification of automatically acquired images (like those in Fig. 15.4a) by this approach provides normalized ratios of median fluorescence ratio per siRNA taking into account each cell in every spot and different spots for the same siRNA in different LabTeks (Fig. 15.4b).

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4. Notes 1. Prepare the gelatin and OptiMEM (containing 0.4 M sucrose) solutions freshly. 2. The FMP stock solution can be diluted with Ringer solution, and the cells are still efficiently stained. If stored at –20◦ C, it can be used for 1 week. 3. The procedure here described refers to applying 384 spots onto a LabTek, but it may be adapted to siRNA coating of 384-microplate or eight-well LabTeks. 4. The siRNAs mix diluted in water is instable; the transfer of the diluted mix into spotting device should be performed quickly. 5. To coat an eight-well LabTeks, transfer 18 μl of each transfection mix into 400 μl of water and then add another 400 μl of water and mix thoroughly. 6. To coat an eight-well LabTek, transfer 100 μl of the diluted mix to each LabTek. 7. The contact printer will start in the first well of the plate and print the first row of spots in the LabTek and will continue like this. 8. LabTeks may be kept for several years stored in a box with drying pearls at room temperature, provided the pearls are changed regularly (as soon as they turn white). 9. Split almost confluent (∼90%) cell cultures of A549 cells 24 h prior to their seeding on the dried siRNA LabTek to have an actively growing cell population to facilitate siRNA uptake. 10. Detection of CFTR expressed at the plasma membrane is performed on non-fixed cells because we observed that cell fixation alters the Flag staining probably by masking Flag epitope. 11. The time of incubation with the FMP staining solution with and without amiloride is critical and should be the same between different experiments. Longer incubations with the FMP solution might lead to an increase in fluorescence, which may reflect changes in ionic strength due to activity of endogenous ion channels. The effect of amiloride is reversible and the second cycle of image acquisition should not take longer than 10–15 min.

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12. INCENP is an inner centromere protein, a component of the chromosomal passenger complex (CPC) that acts as a key regulator of mitosis. The CPC complex has essential functions at the centromere in ensuring correct chromosome alignment and segregation and is required for chromatin-induced microtubule stabilization and spindle assembly. The siRNA targeting INCENP can work as control for transfection and spot alignment since the polynucleated phenotype can be easily detected.

Acknowledgements This work is supported by TargetScreen2 (EU-FP6-LSH2005-037365) grant. J.A. is recipient of Ph.D. fellowship SFRH/BD/29134/2006 (FCT, Portugal). The authors wish to thank Beate Neumann and Jutta Bulkescher (Advanced Light Microscopy Core Facility, EMBL) for their expert technical advice. References 1. Erfle, H., Neumann, B., Liebel, U., Rogers, P., Held, M., Walter, T., et al. (2007) Reverse transfection on cell arrays for high content screening microscopy. Nat Protoc 2, 392– 399. 2. Starkuviene, V., Liebel, U., Simpson, J. C., Erfle, H., Poustka, A., Wiemann, S., et al. (2004) High-content screening microscopy identifies novel proteins with a putative role in secretory membrane traffic. Genome Res 14, 1948–1956. 3. Starkuviene, V., and Pepperkok, R. (2007) Differential requirements for ts-O45-G and procollagen biosynthetic transport. Traffic 8, 1035–1051. 4. Pepperkok, R., Simpson, J. C., Rietdorf, J., Cetin, C., Liebel, U., Terjung, S., et al. (2005) Imaging platforms for measurement of membrane trafficking. Methods Enzymol 404, 8–18. 5. Simpson, J. C., Cetin, C., Erfle, H., Joggerst, B., Liebel, U., Ellenberg, J., et al. (2007) An RNAi screening platform to identify secretion machinery in mammalian cells. J Biotechnol 129, 352–365. 6. Simpson, J. C., Mateos, A., and Pepperkok, R. (2007) Maturation of the mammalian secretome. Genome Biol 8, 211.

7. Denning, G. M., Ostedgaard, L. S., and Welsh, M. J. (1992) Abnormal localization of cystic fibrosis transmembrane conductance regulator in primary cultures of cystic fibrosis airway epithelia. J Cell Biol 118, 551–559. 8. Schultz, B. D., Takahashi, A., Liu, C., Frizzell, R. A., and Howard, M. (1997) FLAG epitope positioned in an external loop preserves normal biophysical properties of CFTR. Am J Physiol 273, C2080–C2089. 9. Shaner, N. C., Campbell, R. E., Steinbach, P. A., Giepmans, B. N., Palmer, A. E., et al. (2004) Improved monomeric red, orange and yellow fluorescent proteins derived from Discosoma sp. red fluorescent protein. Nat Biotechnol 22, 1567–1572. 10. Erfle, H., and Pepperkok, R. (2007) Production of siRNA- and cDNA-transfected cell arrays on noncoated chambered coverglass for high-content screening microscopy in living cells. Methods Mol Biol 360, 155–161. 11. Erfle, H., Neumann, B., Rogers, P., Bulkescher, J., Ellenberg, J., and Pepperkok, R. (2008) Work flow for multiplexing siRNA assays by solid-phase reverse transfection in multiwell plates. J Biomol Screen 13, 575–580.

Chapter 16 New Lipidomic Approaches in Cystic Fibrosis Mario Ollero, Ida Chiara Guerrera, Giuseppe Astarita, Daniele Piomelli, and Aleksander Edelman Abstract Lipid analysis has been a crucial source of information in cystic fibrosis (CF). New methodologies for qualitative and quantitative lipidomics allow evaluation of a large number of samples, of special interest in patient screening for diagnostic and prognostic biological markers, as well as in cell physiology. In this chapter, two new complementary approaches are described: matrix-assisted laser desorption coupled to time of flight (MALDI-TOF-ClinProToolsTM ) and liquid chromatography coupled to ion trap mass spectrometry (LC-MSn ). MALDI-TOF-ClinProToolsTM offers a large unbiased screening for the discovery of potential lipid alterations in diseased patients. LC-MSn represents a state-of-the-art lipidomic tool for the identification and quantification of such alterations. The combination of both may open new perspectives in the quest for lipids participating in CF pathogenesis, therapy targets, and biomarkers. Key words: Lipidomics, biomarkers, mass spectrometry, MALDI, electrospray.

1. Introduction Lipid alterations in cystic fibrosis (CF) patients have been extensively reported since the advent of analytical techniques in the 1960s. These observations have arisen from partial lipidomic approaches, which mainly consisted of either fatty acid profiling or targeted analysis of individual lipid species (lipid methods in the context of CF reviewed in (1, 2)). The recent development of mass spectrometry (MS) techniques has given rise in parallel to a series of lipidomic applications of outstanding potential in the search for novel diagnostic or prognostic biomarkers in CF. In this case the goal is not necessarily the finding of a specific molecule or to identify a differentially M.D. Amaral, K. Kunzelmann (eds.), Cystic Fibrosis, Methods in Molecular Biology 742, DOI 10.1007/978-1-61779-120-8_16, © Springer Science+Business Media, LLC 2011

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displayed compound, but to determine complex molecular signatures that correlate with a particular pathologic status. The drawbacks of current lipidomic approaches are the slowness of analysis, the complexity of data interpretation, the lack of a database for an easy identification, and the problems associated with quantification. In this chapter we describe a novel lipidomic strategy for biomarker discovery in CF, which uses two complementary techniques: matrix-assisted laser desorption, coupled to time of flight/time of flight (MALDI-TOF/TOF-ClinProToolsTM ) together with liquid chromatography coupled to ion trap mass spectrometry (LC-MSn ) (Fig. 16.1). MALDI-TOF/TOF-ClinProToolsTM (3) provides a fingerprint of the molecular species present in biological samples with high level of accuracy and resolution. Therefore, this technique is particularly suitable for molecular profiling, and it has been proven useful in the search for protein signatures associated with a number of disorders (4–10). Roughly, lipid extracts are separated by solid phase extraction and then analyzed by MALDI-TOF/TOF. The data obtained by MALDI-TOF/TOF analysis are subjected to a thorough statistical analysis with the ClinProToolsTM software, which determines those lipid species able to significantly segregate two or more populations (i.e., healthy individuals from patients or patients at different severity status of the disease).

Fig. 16.1. Experimental flowchart. Numbers “1” and “2” denote the ClinProToolsTM -MALDI-TOF/TOF and LC-MSn methods, respectively. The discontinuous arrow indicates the possibility of bypassing identification when the primary goal of screening is to obtain significant signatures. In this case a MALDI-TOF/TOF instrument may be used and identification, if desired, can be performed on an equivalent sample by ESI-MSn . SPE, solid phase extraction; LC, liquid chromatography; ESI, electrospray ionization.

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LC-MSn is used to obtain structural information and quantify lipid species in complex biological matrices (11, 12). Briefly, lipid species are chromatographically separated by LC and ionized by either electrospray ionization (ESI) or atmospheric pressure chemical ionization (APCI). The molecular ions generated in the ion source are then fragmented by MSn into a set of diagnostic fragments, which are used for the chemical characterization and quantification of the lipid species.

2. Materials 2.1. Biological Material

2.2. Organic Extraction and SPE

These techniques can be applied to the study of cell lines, animal tissues, human tissues, and body fluids. CF cell models, such as those stably transfected with CFTR/F508del-CFTR (e.g., HeLa, HEK, FRT), immortalized cells derived from CF patients (e.g., HBEo-, CFBEo-), cells derived from adenocarcinoma and expressing large amounts of CFTR (e.g., Calu-3, T84, HT29, Caco), are suitable for lipidomic analysis. Adherent or nonadherent cells must be devoid of incubation medium and washed several times in either water or saline solution (PBS), by sequential centrifugations at 800×g. The final pellet must be resuspended in water (ideally 0.5 ml) and maintained at 4◦ C. Tissues must be homogenized in PBS or water. Blood plasma and serum are ideally diluted in water to a final volume of 0.5 ml. The suggested initial volume is 0.1 ml. Other fluids may be used, but their lipid content is likely to be very limited. – Solvents must be at least of HPLC quality (CHROMASOLV, Sigma-Aldrich, Lyon, France). The following solvents are used: chloroform, methanol (some butylated hydroxytoluene is added to the methanol stock, see Note 1), isopropanol, diethyl ether, acetic acid, sodium acetate, and hexane. Mixtures of solvents are prepared freshly before use to avoid changes in volume proportions due to accidental evaporation, which may occur during storage. The following mixtures are used: 1. Chloroform–methanol (2:1, v/v) 2. Chloroform–isopropanol (2:1, v/v) 3. Diethyl ether–acetic acid (98:2, v/v) 4. Chloroform–methanol–0.8 N sodium acetate in water (60:30:4.5, v/v/v). – Glassware and glass tubes must be used in all cases. Ten milliliter conical tubes with phenolic screw caps are recommended (Kimble, Vineland, NJ, USA).

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– For SPE extraction, a vacuum device is recommended (Varian). Alternatively, compressed air can be applied to accelerate elution. SPE is performed on direct phase aminopropyl columns (Supelclean LC-NH2-SPE, Supelco, Bellefonte, PA, USA). – For sample evaporation, prior to SPE and to mass spectrometry analysis, a vacuum apparatus can be used (Savant SC210A SpeedVac concentrator). Alternatively, a stream of nitrogen gas can be applied. 2.3. Matrix and Calibrants for MALDI-TOF

Matrix must be prepared freshly before use. Dihydroxybenzoic acid (DHB) (Sigma-Aldrich) is suggested as a universal matrix for lipid ionization. Nevertheless, it favors the ionization of PC vs. other phospholipid moieties (13): 1. DHB matrix is prepared as a 0.5 M solution in methanol. Trifluoroacetic acid (0.1%) (TFA, Sigma-Aldrich) is added as a counter ion. 2. Calibrant mixture: peptide calibration Mix5 (LaserBio Labs, Sophia Antipolis, France). The mixture covers the mass range of 500–2000 Da. It contains bradykinin (aminoacids 1–5), bradykinin (aminoacids 1–7), bradykinin, angiotensin I human, and neurotensin. Thaw a stock aliquot (10×) before use and dilute 1/10 in matrix solution.

2.4. Instruments for MALDI-TOFClinProToolsTM

All materials and instruments are from Bruker Daltonics (Bremen, Germany): 1. AutoFlex III or UltraFlex MALDI-TOF/TOF mass spectrometers. These instruments allow the study of ion fragments by MS/MS and subsequently the determination of molecular structure and ulterior identification of some molecules. 2. ClinProToolsTM and FlexControl software packages. 3. MALDI target.

2.5. Equipment for LC/MS n Analysis

1. Agilent 1200-LC system (with autosampler) coupled to IonTrap XCT detector interfaced with ESI or APCI (Agilent Technologies). 2. Gas: ultra-high purity compressed helium (for MS fragmentation) and high-purity N2 (for drying samples and for atmospheric pressure ionization functioning).

2.6. Reagents

A representative list of internal standards used to quantify endogenous lipid species may include the following lipids: 1. Fatty acyls: – Fatty acids and eicosanoids: heptadecanoic acid from Nu-Chek Prep (Elysian, MN, USA); d8-arachidonic

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acid from Cayman Chemicals (Ann Arbor, MI, USA); prostaglandin: d4-prostaglandin E2 from Cayman Chemicals. – Fatty acid ethanolamide: heptadecenoylethanolamide (synthesized as previously reported (11)). 2. Glycerolipids: – Triacylglycerol: trinonadecenoin from Nu-Chek Prep. – Diacylglycerol: dinonadienoyl-sn-glycerol from Nu-Chek Prep. – Monoacylglycerol: monoheptadecanoyl-sn-glycerol from Nu-Chek Prep; d8-2-arachidonoyl-sn-glycerol from Cayman Chemicals. 3. Glycerophospholipids (all from Avanti Polar Lipids, Alabaster, AL, USA): – Phosphatidylethanolamine: 1,2-diheptadecanoyl-sn-glycero-3-phosphoethanolamine. – Phosphatidylglycerol: 1,2-diheptadecanoyl-sn-glycero-3phosphoglycerol. – Phosphatidylcholine: 1,2-diheptadecanoyl-sn-glycero-3phosphocholine. – Phosphatidylserine: phosphoserine.

1,2-diheptadecanoyl-sn-glycero-3-

– Phosphatidylinositol: 1,2-dipalmitoyl-sn-glycero-3-phosphoinositol. 4. Sphingolipids (from Avanti Polar Lipids): – Ceramide: N-lauroyl-ceramide. – Sphingomyelin: N-lauroyl-sphingomyelin. 5. Sterol lipids (from Avanti Polar Lipids): – Cholesterol: d7-cholesterol. 6. Solvents and chemicals for HPLC mobile phases: water, methanol, chloroform (HPLC grade) are purchased from Thermo Fisher Scientific (Somerset, NJ, USA). Acetic acid and ammonium acetate are from Sigma (St Louis, MO, USA). 2.7. Supplies (All from Agilent Technologies)

1. LC columns: – Zorbax XDB Eclipse C-18 (50 × 4.6 mm i.d., 1.8 μm particle size, 80 Å of porous diameter). – Poroshell 300SB C-18 (2.1 × 75 mm i.d., coating layer of 0.25 μm on total particle diameter of 5 μm, 300 Å of porous diameter). 2. Glass vials (1.5 ml for autosampler and LC analysis). 3. Caps with teflon liner. 4. Conical insert for reducing the volume of autosampler vials.

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3. Methods 3.1. MALDI-TOF/TOFClinProToolsTM 3.1.1. Lipid Extraction

1. Based on Folch’s method (14), extraction is performed under the principle of addition of six volumes of chloroform–methanol (2:1, v/v) to a liquid or semi-liquid sample. The latter can be a body fluid, a cell suspension, or a tissue homogenate (see Section 2.1). The optimal volume of sample is 0.5 ml, but smaller volumes down to 0.2 ml can be easily handled. 2. The mixture is vortexed for at least 10 s and centrifuged at 800×g for 5 min at 4◦ C. After centrifugation, two phases can be distinguished: an aqueous phase (upper) containing polar molecules, an organic phase (lower) containing hydrophobic molecules, and an interphase where proteins remain as a solid precipitate. 3. The lower phase (organic) is transferred to a disposable glass tube. 4. Alternatively, to increase extraction efficiency, 1.5 ml of chloroform–methanol (2:1, v/v) is added to the remaining upper phase and step 2 is repeated. Both lower phases are combined (see Note 3). 5. Samples can be stored at –20◦ C until further processing (see Note 2). If so, fill tubes with either CO2 or nitrogen (see Note 1).

3.1.2. SPE Fractionation

This methodology was described by Kaluzny et al. (15). More than a purification method it represents a rapid way of reducing the complexity level of lipid samples: 1. Total extracts are evaporated either under a stream of nitrogen gas or by means of a vacuum apparatus (see Note 4). 2. The aminopropyl column (1 ml) is conditioned with two volumes (2 ml) of hexane. The elution speed is adjusted to 2–4 ml/min. 3. Two hundred microliters of chloroform is added to each dry sample residue. The solution is vortexed for 10 s. 4. Vacuum is broken and the dissolved extract is loaded onto the column. The extract penetrates the column by gravity. The solvent level is allowed to reach the top of the column. 5. Two column volumes of chloroform–isopropanol (2:1, v/v) are loaded. Vacuum is applied and this allows the elution of non-polar lipids (cholesterol; cholesteryl esters;

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mono-, di-, and tri-glycerides). This fraction is collected and named as fraction I. 6. Two column volumes of 2% acetic acid in diethylether are loaded under vacuum. This allows elution and collection of free fatty acids (fraction II). 7. Two column volumes of methanol are loaded under vacuum. This allows elution of neutral phospholipids, such as phosphatidylcholine (PC), phosphatidylethanolamine (PE), and sphingomyelin (SM) (fraction III). 8. Two column volumes of chloroform–methanol–0.8 N sodium acetate (60:30:4.5, v/v/v) are loaded under vacuum. This allows elution of acidic phospholipids, such as phosphatidylserine (PS), phosphatidylglycerol (PG), phosphatidic acid (PA), and phosphatidylinositol (PI) (fraction IV). 9. Sodium acetate of fraction IV can interfere with analysis. To eliminate this salt, fraction IV must be evaporated either under a nitrogen stream or by a concentrator. Three milliliters of chloroform–methanol (2:1, v/v) is added to the extract, followed by 0.5 ml of water. The mixture is vortexed for 10 s and centrifuged at 800×g for 3 min. The lower phase is aspirated and transferred to a new glass tube. 10. Fractions can be stored at –20◦ C until further processing (see Note 2). If so, fill tubes with CO2 (see Note 1). 3.1.3. MALDI-TOF/TOF

1. On the day of the analysis, fraction extracts are dried and resuspended in 10 μl of chloroform–methanol (1:1, v/v) by vortexing and sonicated with 3 × 10 s pulses in a sonication bath (see Note 5). One microliter is thoroughly mixed with 1 μl of matrix solution in a separate Eppendorf, and 0.5 μl of the mixture is spotted on a classical MALDI target (Bruker). Ideally the same sample should be spotted three times to obtain technical triplicates. The spotting has to be fast because of the hydrophobic nature of the target surface and the fast rate of evaporation of this small volume. When the spot is dry the sample is ready to be analyzed by MALDITOF/TOF MS. It is necessary to add blank spots containing a 1:1 (v/v) mixture of chloroform–methanol (1:1, v/v) and the matrix solution (mixed and spotted as described for samples). 2. The MALDI profiling is done in reflectron mode over a detection range of 0–2000 Da, or less, according to the class of lipids analyzed. The spectra can be acquired in both positive and negative modes. The laser power is chosen to guarantee the best signal to noise ratio and it must be kept at

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the same intensity throughout the experiment. For the best reproducibility, the spectra are acquired in automatic mode, using FlexControl 3.0 (Bruker), accumulating only spectra with the resolution or the most intense peak higher than 4000. 3. Calibrants mixed with the matrix (1:1, v/v) are also spotted along the sample and their spectra acquired in automated mode using the same parameters. The spectra obtained allow an external calibration which can assure a mass precision within 200 ppm. In order to refine the mass precision to 50 ppm, an additional internal calibration is performed using the signal from the matrix present in the sample spectrum. Both calibrations are performed using FlexAnalysis 3.0 (Bruker). 3.1.4. ClinProToolsTM Analysis

Randomly acquired spectra are grouped into classes of patients before being subjected to statistical analysis by ClinProt Tools 2.0 (Bruker). Higher versions of this software can be used when available. Spectra are automatically processed when opened. They undergo baseline subtraction, normalization to the corresponding TIC (total ion current), and finally recalibration. The spectra that do not contain most of the reference masses used for recalibration are automatically excluded. Parameters of peak picking have to be reset to adjust to the detection range and resolution. Further manual elimination of isotopic isoforms for the same compound is necessary because the software is developed for proteins/peptides acquired in linear mode, therefore with a much lower non-isotopic resolution. Different classes of patients can simultaneously be compared with the controls. The statistical analysis chosen is a univariate sorting algorithm (QC). The results can be displayed by a 2D plot using the two most discriminant peak intensities in all classes (Fig. 16.2). However, a complete Excel list, containing the mass value, the intensity, and the ANOVA p-value for each peak, can also be exported. Raw relative abundance values can also be exported in an Excel file. Once the list of relevant peaks is obtained, it is important to eliminate those that are present in the blank spectrum, which correspond to either contaminants or matrix ions (see Notes 5 and 6). Identification of relevant peaks can be performed either by ion fragmentation using the MALDITOF/TOF apparatus (see Note 7) or by LC/MSn analysis (see Section 3.2).

3.2. LC/MS n Analysis 3.2.1. Sample Preparation

Lipid samples are prepared as described in Section 3.1.1, with the addition of a mixture of internal standards into the chloroform–methanol solution before the extraction process.

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Fig. 16.2. ClinProToolsTM 2D peak distribution diagrams corresponding to a couple of ions (m/z 808 and m/z 782) able to segregate two populations of samples (circles and crosses). Ellipses correspond to 95% confidence intervals. The values represented correspond to arbitrary units of relative intensity.

Internal standards are constituted by non-endogenous lipid species representative of each lipid class (see Section 2.6). Lipid molecular species are quantified by normalizing the individual molecular ion peak intensity with an internal standard for each lipid class. These internal standards allow the lipid levels to be normalized for both extraction efficiency and instrument response. 3.2.2. Chromatographic and Intrasource Ionization Separation of Lipid Molecules

In order to simplify the analysis in biological tissues, lipids are schematically divided into three main classes: (a) small lipids, defined here as molecules containing one aliphatic group such as fatty acids and their derivatives (amides, esters, oxygenated compounds); (b) large lipids, molecules containing two or more aliphatic groups, such as phospholipids, diacylglycerols, triacylglycerols, sphingolipids; and (c) sterol lipids, molecules containing a rigid four-ring backbone such as cholesterol and its derivatives. To identify and quantify the different classes of lipids by LC/MS, two separate chromatographic approaches are applied, using different reversed-phase C-18 stationary phases. A chromatographic separation of lipid species helps reduce the isotopic effects, which affect the actual mass abundance allowing a more accurate quantification. Furthermore, ESI set in either positive or negative mode and APCI set in positive mode are used to separate the lipid classes on the basis of different ionization efficiencies of their functional groups. The combination of chromatographic resolving power in conjunction with ionization source selection and mass detection allows the identification and quantification of lipid species present at very low concentration.

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3.2.2.1. Small Lipids

To separate lipids containing one fatty acyl group, a reversedphase C-18 column packed with conventional porous silica particles of small spherical diameter (sub-2 μm) is used. Fatty acyl species are separated both by chain length and by degree of unsaturation of their fatty acid chains. Generally, in positive ESI mode small lipids are detected as protonated molecular ions or sodium and ammonium adducts. In contrast, in negative mode small lipids are detected as deprotonated molecular ions. Mobile phase A consists of methanol containing 0.25% acetic acid and 5 mM ammonium acetate; mobile phase B corresponds to water containing 0.25% acetic acid and 5 mM ammonium acetate. Small lipids are identified based on their retention times and MSn properties. 1. Fatty acyls: Fatty acyls are separated using a reversed-phase Zorbax XDB Eclipse C-18 column. Lipids are eluted using a linear gradient from 90% A to 100% B in 2.5 min at a flow rate of 1.5 ml/min with column temperature at 40◦ C. ESI is in the negative mode, capillary voltage is set at –4 kV, and fragmentor voltage is 100 V. N2 is used as drying gas at a flow rate of 13 l/min and a temperature of 350◦ C. Nebulizer pressure is set at 60 psi. We use commercially available fatty acyls as reference standards. Fatty acids are analyzed monitoring the mass-to-charge ratio (m/z) of the deprotonated molecular ions [M–H]– in selected-ion monitoring mode. Detection and analysis are controlled by Agilent Chemstation and Bruker Daltonics softwares.

3.2.2.2. Large Lipids and Sterol Lipids

To separate large (glycerolipids, glycerophospholipids, and sphingolipids) lipids and sterol lipids, a reversed-phase C-18 column packed with superficially porous particles is used. This allows for fast flow rates and good peak shape for large lipid molecules. Although lipids are separated when differing in a single fatty acyl chain, their combinatorial nature makes only a partial separation of the isomeric species possible. Therefore, to obtain more information on the lipid structure, LC separation is coupled with MSn fragmentation data. Generally, large lipids are detected in the positive ESI mode as sodium or ammonium adducts or as deprotonated molecular ions in the negative mode. For sterol lipids, which are highly hydrophobic and hard to ionize, APCI is used in positive mode and the protonated molecular ions are detected after loss of water. 1. Glycerolipids, glycerophospholipids, and sphingolipids: Large lipid molecules are separated using a reversed-phase Poroshell 300SB C-18 column. A linear gradient is applied from 85% A to 100% B in 5 min at a flow rate of 1.0 ml/min with column temperature set at 50◦ C. MS detection is performed both in the positive and in the negative ionization modes. The capillary voltage is set at 4.0 kV and skimmer

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voltage at 40 V. N2 is used as drying gas at a flow rate of 10 l/min, temperature at 350◦ C, and nebulizer pressure at 60 psi. Helium is used as collision gas, and fragmentation amplitude is set at 1.2 V. Ion charge control is on, smart target set at 50,000, maximum accumulation time at 50 ms, scan range of 100–1500 amu, 26,000 m/z per second. Lipids are identified based on their retention times and MSn properties (Fig. 16.3). Detection and quantitative analysis are controlled by Agilent Chemstation and Bruker Daltonics software. 2. Sterol lipids: Sterol lipid molecules are separated using a reversed-phase Poroshell 300SB C-18 column. Lipids are separated using a linear gradient from 75% A to 100% B in 4-min period at a flow rate of 1.0 ml/min with column temperature at 50◦ C. APCI is set in positive mode. Drying gas is set at 350◦ C and a flow rate of 8 l/min. Nebulizer gas pressure is set at 30 psi and vaporizer temperature at 475◦ C. Capillary voltage is set at 300 V with the corona current set at 5 μA. Lipids are identified based on their retention times and MSn properties (Fig. 16.3). Detection and quantitative analysis are controlled by Agilent Chemstation and Bruker Daltonics software.

Fig. 16.3. Identification of 1-palmitoyl,2-arachidonoyl phosphatidylcholine (PC) (m/z 840.6) in biological samples. Representative extracted LC/MS3 chromatogram (panel A) and fragmentation pattern in MS2 (panel B) and MS3 (panel C) using an ion trap instrument. PC species are detected as acetate adducts of the molecular ions using ESI set in the negative mode. The MS2 fragmentation pattern is characterized by neutral loss of the acetate adduct of the N-methyl group (panel D). MS3 of the ion with m/z 766.5 yields the lysophospholipid with neutral loss of ketene in combination with the sn–1 and sn–2 carboxylate anions (panels C and D). Abbreviations: R1 = sn–1 aliphatic chain; R2 = sn–2 aliphatic chain.

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4. Notes 1. Peroxidation is the major cause of degradation of lipid extracts, particularly those containing high amounts of unsaturated chains. It is recommended to use butylated hydroxytoluene (BHT) (Sigma) as antioxidant. This is added to the methanol stock. Other actions conducted to minimize peroxidation are to perform all work on ice, fill tubes with either CO2 or nitrogen to eliminate molecular oxygen, and store extracts at low temperature (see Note 2). Although nitrogen is a more inert gas, CO2 presents the advantage of being heavier than air and remains in the interior of the tube. 2. Storage of extracts: Lipid extracts and SPE fractions can be stored before evaporation at –80◦ C for several months. Higher temperatures –20◦ C are acceptable for shorter storage times (up to 2 weeks). In general, long storage is not recommended. Shipping of extracts or samples must be assured in dry ice. 3. For MALDI-TOF/TOF-ClinProToolsTM analysis, normalization is automatically performed to total ion current by the software and there is no need for internal standards, which may also interfere with the MS detection of isomeric endogenous lipids, as no previous separation is performed. 4. Sample evaporation must be performed in the absence of molecular oxygen to minimize lipid oxidation. Nitrogen or any other inert gas is an acceptable option. Nevertheless, vacuum concentrators provide a cleaner preparation, as the lipid extract is better confined to the bottom of the tube. 5. Specificity of MALDI analysis: Some matrices favor the detection of particular lipid classes. DHB is especially indicated in the analysis of neutral phospholipids (PC, SM) in the positive mode. Other matrices can be used in the negative mode. A drawback of MALDI is the interference of matrix peaks with lipid signals. DHB is particularly noisy in the negative mode and it is not recommended for the analysis of fatty acids (see (13) for review). 6. Plastic contaminants: Long-term storage of body fluids in plastic vials may result in the presence of polymer contaminants in the sample. These contaminants are extracted by organic solvents and may be found as ghost peaks in spectra. They can be recognized as a regular sequence of peaks differing in 44 m/z. The use of plastic vials and the length of storage should be minimized. 7. Identification by MALDI-TOF/TOF: Relevant ions resulting from ClinProToolsTM analysis can be identified by

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tandem MS using the LIFT application integrated in the FlexControlTM (Bruker) software associated with the MALDI-TOF/TOF apparatus. For most lipid classes, analysis of fragmentation patterns, as described in Fig. 16.3 for ESI-MSn , allows molecular structure determination. At present, the most comprehensive general database of lipid mass spectra is that of the Lipid Maps initiative (http:// lipidmaps.org/data/databases.html). Search engines compatible with MS/MS data are also available (http:// lipidmaps.org/tools/index.html; Lipid MS Predictor software), but a manual analysis of the fragmentation spectra is needed to assure identification.

Acknowledgments This work was supported by NEUPROCF (FP6, European Commission to A.E.) and EICOCF (Association Nationale de la Recherche to A.E.), the associations Vaincre la Mucoviscidose and ABCF2 Protéines, and Legs Poix-University of Paris 5. The authors thank the Agilent Technologies/University of California Irvine Analytical Discovery Facility, the Center for Drug Discovery, and the Agilent Technologies Foundation. References 1. Freedman, S. D., Blanco, P. G., Shea, J. C., and Alvarez, J. G. (2002) Analysis of lipid abnormalities in CF mice. Methods Mol Med 70, 517–524. 2. Ollero, M. (2004) Methods for the study of lipid metabolites in cystic fibrosis. J Cyst Fibros 3 Suppl 2, 97–98. 3. Guerrera, I. C., Astarita, G., Jais, J. P., Sands, D., Nowakowska, A., Colas, J., et al. (2009) A novel lipidomic strategy reveals plasma phospholipid signatures associated with respiratory disease severity in cystic fibrosis patients. PLoS One 4, e7735. 4. Alagaratnam, S., Mertens, B. J., Dalebout, J. C., Deelder, A. M., van Ommen, G. J., den Dunnen, J. T., et al. (2008) Serum protein profiling in mice: identification of Factor XIIIa as a potential biomarker for muscular dystrophy. Proteomics 8, 1552–1563. 5. Chang, J. T., Chen, L. C., Wie, S. Y., Chen, Y. J., Wang, H. M., Liao, C. T., et al. (2006) Increase diagnostic efficacy by com-

bined use of fingerprint markers in mass spectrometry – plasma peptidomes from nasopharyngeal cancer patients for example. Clin Biochem 39, 1144–1151. 6. Freed, G. L., Cazares, L. H., Fichandler, C. E., Fuller, T. W., Sawyer, C. A., Stack, B. C., Jr., et al. (2008) Differential capture of serum proteins for expression profiling and biomarker discovery in pre- and posttreatment head and neck cancer samples. Laryngoscope 118, 61–68. 7. Gianazza, E., Mainini, V., Castoldi, G., Chinello, C., Zerbini, G., Bianchi, C., et al. (2010) Different expression of fibrinopeptide A and related fragments in serum of type 1 diabetic patients with nephropathy. J Proteomics 73, 593–601. 8. Ketterlinus, R., Hsieh, S. Y., Teng, S. H., Lee, H., and Pusch, W. (2005) Fishing for biomarkers: analyzing mass spectrometry data with the new ClinProTools software. Biotechniques Jun Suppl, 37–40.

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9. Kojima, K., Asmellash, S., Klug, C. A., Grizzle, W. E., Mobley, J. A., and Christein, J. D. (2008) Applying proteomic-based biomarker tools for the accurate diagnosis of pancreatic cancer. J Gastrointest Surg 12, 1683–1690. 10. Solassol, J., Jacot, W., Lhermitte, L., Boulle, N., Maudelonde, T., and Mangé, A. (2006) Clinical proteomics and mass spectrometry profiling for cancer detection. Expert Rev Proteomics 3, 311–320. 11. Astarita, G., Ahmed, F., and Piomelli, D. (2008) Identification of biosynthetic precursors for the endocannabinoid anandamide in the rat brain. J Lipid Res 49, 48–57. 12. Astarita, G., and Piomelli, D. (2009) Lipidomic analysis of endocannabinoid metabolism in biological samples. J Chro-

matogr B Anal Technol Biomed Life Sci 877, 2755–2767. 13. Schiller, J., Suss, R., Arnhold, J., et al. (2004) Matrix-assisted laser desorption and ionization time-of-flight (MALDITOF) mass spectrometry in lipid and phospholipid research. Prog Lipid Res 43, 449–488. 14. Folch, J., Lees, M., and Sloane Stanley, G. H. (1957) A simple method for the isolation and purification of total lipids from animal tissues. J Biol Chem 226, 497–509. 15. Kaluzny, M. A., Duncan, L. A., Merritt, M. V., and Epps, D. E. (1985) Rapid separation of lipid classes in high yield and purity using bonded phase columns. J Lipid Res 26, 135–140.

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Chapter 17 Introduction to Section III: Resources for CFTR Research Margarida D. Amaral Abstract This section of Cystic Fibrosis Protocols and Diagnosis focuses on resources available to facilitate the activities of the research community in the field of cystic fibrosis (CF). An overview of the protocols and resources described in subsequent chapters of this book section is provided, as well as how they can accelerate research in this area. Key words: Cystic fibrosis, CFTR, resources.

A major obstacle to more rapid progress in any research area is the lack of adequate resources widely available to investigators. In biomedical research, these resources include good “reagents” (antibodies, cDNA and other constructs, purified proteins), physiologically relevant cellular systems, and appropriate animal models. The previous edition of this book (1) described already existing resources in the CF field. Also, at the European level (through the FP5-funded CF-Network, coordinated by JeanJacques Cassiman, University of Leuven, Belgium) a unique series of ~160 “Consensus Protocols for CFTR Expression and Function Research” was made accessible and is still available at the European Working Group on CFTR Expression Web site (2) and resulted in a collection of 38 articles entirely dedicated to CF-related methodologies and resources published as a special supplement of the Journal of Cystic Fibrosis (3). The aim of including this section in the current edition of Cystic Fibrosis Protocols and Diagnosis is to provide an update on this previous initiative so that these novel resources are known and used to reduce effort and time of all researchers working in this and related fields.

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The first chapter within this section (Chapter 18) by Randell et al. describes how primary human airway epithelial cells recapitulate in vivo morphology and key physiologic processes when grown in vitro on porous supports at an air–liquid interface (ALI). These cultures are useful for numerous studies, including basic (patho)biology of the respiratory tract and testing of new therapies aimed at correcting the basic defect underlying CF. This chapter gives protocols enabling the generation of well-differentiated primary CF and non-CF airway epithelial cell cultures with non-proprietary reagents. The authors also discuss the production of retroviral and lentiviral vectors, reporter gene assays, and the evolving science of gene overexpression and knockdown in these ALI primary airway epithelial cultures. However, since cellular systems cannot encompass the complexity of this devastating disorder, we need to study its model organisms so as to fully understand its impact. In Chapter 19, Engelhardt et al. describe how animal models in the context of CF are critical for dissecting mechanisms of pathophysiology and developing therapies. They explain how mouse models have been the dominant species to study CF in vivo for the past two decades and their limitations and major advances in our current knowledge on CF. Such limitations include the inability of mice lacking functional CFTR in spontaneously recapitulating CF-like lung disease. These authors then describe emerging new animal models, like the CF pig and CF ferret, generated to fulfil the need for additional species on which to study CF. These new larger animal models have phenotypes that appear to closely resemble CF disease seen in human newborns, and efforts to characterize their adult phenotypes are ongoing. This chapter also comparatively reviews the lung cell biology and CFTR biology among mice, pigs, and ferrets and their implications for CF disease modelling in these species, also describing the most relevant methodological approaches. Given the complexity of the methods available to the CFTR research community and the multitude of reagents required, it is difficult, if at all possible, to have such expertise concentrated in every CF lab or even at a single institution. This was the rationale for the US CF Foundation to establish the CFTR Folding Consortium (CFC). Chapter 20 is co-authored by a significant number of groups well established in the CF research and led by Frizzell. This chapter provides a description of the current methods and reagents made available through this consortium. A primary goal of the CFC is the development and distribution of reagents as well as assays designed to better understand the mechanistic basis of mutant CFTR (namely, F508del-CFTR). Such reagents made available by the CFC include antibodies, cell lines, constructs, and proteins and their summarized description is provided in Chapter 20. Here, the systematic collection of assays

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(ranging from purified protein to well-differentiated human airway primary cultures), the “CFC roadmap,” is also explained. Up to now, ∼20 years after the cloning of the CFTR gene, over 1,800 sequence variants in the CFTR gene have been reported to the CF Mutation Database (4). The major proportion of these has never been characterized by clinical studies and/or functional assays (only about 25 mutations have been well characterized so far). Thus, it becomes imperative to identify the molecular and cellular consequences associated with a significant number of these CFTR mutations with unclear or unknown effects. Indeed, only in this way can we have better predictions of clinical impact (disease liability) on the CF patients bearing them. To address this very basic question, another initiative of the CFF (USA), the “CFTR2” project, is described in Chapter 21 but again with the input of several groups across the world. The CFTR2 project aims to cover this major gap in the CF field, by assessing the molecular and cellular impacts of a significant number of CF-causing mutations in a novel collection of isogenic and physiologically relevant cell lines expressing such CFTR variants. The expected results will have implications for diagnosis, therapy selection, and counselling for patients and families carrying a thus far uncharacterized CFTR mutation. Chapter 21 describes the status of this ongoing approach which assesses the disease implications of CFTR mutations from multiple sources: clinical data, literature, laboratory experiments, as well as by bioinformatics. References 1. Skach, W. R. (ed.) (2002) Cystic Fibrosis Methods and Protocols. Series in Methods in Molecular Medicine. Humana Press, Totowa, NJ, pp. 1–631. 2. The European Working Group on CFTR Expression website (2003) http://central. igc.gulbenkian.pt/cftr/vr/index.html

3. Amaral, M. D. (ed.) (2004) An Online Repository of Methods for Cystic Fibrosis and CFTR Research, produced by the European Working Group on CFTR Expression and Function. J Cyst Fibros 3S2, 1–250. 4. (Accessed in 2010) http://www.sickkids.on. ca/cftr

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Chapter 18 Primary Epithelial Cell Models for Cystic Fibrosis Research Scott H. Randell, M. Leslie Fulcher, Wanda O’Neal, and John C. Olsen Abstract When primary human airway epithelial (hAE) cells are grown in vitro on porous supports at an air–liquid interface (ALI), they recapitulate in vivo morphology and key physiologic processes. These cultures are useful for studying respiratory tract biology and diseases and for testing new cystic fibrosis (CF) therapies. This chapter gives protocols enabling creation of well-differentiated primary CF and non-CF airway epithelial cell cultures with non-proprietary reagents. We also discuss the production of retroviral and lentiviral vectors, the derivation of hAE cell lines, reporter gene assays, and the evolving science of gene overexpression and knockdown in ALI hAE cultures. Key words: Respiratory tract, differentiation, physiology, pathogenesis, therapy, adenovirus, lentivirus.

1. Introduction 1.1. Primary Human Airway Epithelial (hAE) Cell Cultures

In cystic fibrosis (CF) lack of functioning CF transmembrane conductance regulator (CFTR) protein in airway epithelial cells impairs innate defense mechanisms, causing the infection diathesis. Human airway epithelial (hAE) cell cultures are key for basic and applied studies of airway biology, disease, and therapy related to CF. Heterologous CFTR expression systems and airway epithelial cell lines are important for CF research and development. However, well-differentiated primary hAE cultures grown on porous supports at an air–liquid interface (ALI) recapitulate the characteristic pseudostratified mucociliary morphology and key physiologic functions and are a quantum leap toward the

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in vivo biology. The cultures serve as a critical milestone test of biological relevance. Verification of efficacy in this model is a rational step for advancement of potential therapies, and peer reviewers for scientific journals and granting agencies often require its use. Although primary hAE cultures have been created for over 25 years (1) and have been used for numerous studies, expense, technical complexity, and experimental limitations inhibit their full application. From 1984 to 2009, The University of North Carolina Cystic Fibrosis Center Tissue Procurement and Cell Culture Core has prepared cells from more than 6970 human tissue specimens, adopting new technologies and extending research capabilities. The current chapter distills and updates our prior detailed description (2), enabling others to employ this relevant cell culture model. The procedures detailed below are based on the original methods of Lechner and LaVeck (3) and Gray et al. (4), as currently employed in our laboratory. 1.2. Production of Retroviral and Lentiviral Vectors

Retroviral and lentiviral vectors are key components of the hAE research toolbox and their production by individual laboratories is within reach for many investigators. They are used extensively for creation of cell lines and for gene expression or knockdown as described in Sections 1.3 and 1.5. In Sections 2.2 and 3.2 we describe production of retroviral and lentiviral vectors for infection of undifferentiated hAE cells on plastic culture dishes. Both vectors are produced in human 293T cells, which are easily transfected with the necessary plasmids.

1.3. Creation of Airway Epithelial Cell Lines

When employed properly, airway epithelial cell lines are a valuable complement to primary cultures. They have been derived from human lung cancers (5, 6), produced by mutagenesis (7), created by introduction of oncogenes, with (8, 9) or without (10, 11) cointroduction of human telomerase reverse transcriptase (hTERT) or by gene expression that suppresses senescence (12). Cell lines found useful for CF research were previously reviewed (13). We focus in Sections 2.3 and 3.3 on two approaches for cell line creation (1) transformation with the potent viral oncogene Simian Virus 40 Early Region (SV40ER) in combination with hTERT and (2) growth extension using the mammalian oncogene Bmi-1 plus hTERT. In our experience, the viral oncogene plus hTERT approach produces rapidly growing, immortal, and genetically unstable aneuploid cell lines that lose the ability to polarize or undergo mucociliary differentiation after multiple passages, while Bmi-1 plus hTERT produces slowly dividing, growth-enhanced diploid cells that are not immortal, but are capable of polarizing and differentiating into mucous secretory and occasional ciliated cells up to passage 15 (8, 14).

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1.4. Reporter Gene Assays in ALI hAE Cells

Reporter gene assays are widely employed and highly useful in modern cell biology, including high-throughput screening, mechanistic studies and promoter analysis. Typical assays rely on cellular expression of a reporter activity driven by a specific promoter indicative of pathway activation, which is normalized to a second, constitutively expressed reporter. There are multiple formats, including fluorescence imaging and biochemical assays of secreted or cell-associated enzymes. Changes in response to stimuli are typically measured as an increase in reporter activity and effects of chemical inhibitors/stimulators can be evaluated. Additionally, a gene, a dominant negative or small hairpin RNA (shRNA) construct, or a control can be co-transfected, in excess over the reporter, to evaluate effects on baseline or stimulated promoter activity. When using appropriate protocols, tissue culture cells (3T3, 293, HeLa, A549, etc.) on plastic are easily transfectable with plasmid vectors. However, hAE cells even on plastic are transfection resistant and well-differentiated cells at an ALI are notoriously difficult. Replication-deficient adenoviral vectors are highly efficient for transient expression in tissue culture cells on plastic and, when coupled with permeabilization of the apical plasma membrane, are reasonably efficient in ALI hAE cells (15). Below (see Sections 2.4 and 3.4), we describe the use of an adenovirus expressing NF-κB-driven firefly luciferase (fLuc) to examine pathway activation in hAE cells at an ALI (Fig. 18.1). A constitutively expressed LacZ gene (β-galactosidase protein, β-gal) controls for transduction efficiency. In one example, co-transduction with dominant negative construct of the interleukin-1 receptorassociated kinase 1 indicated its key role in the ALI hAE cell response to Pseudomonas aeruginosa (16). Although time and expense can be substantial, replication-deficient adenoviruses are robust and adaptable and can be used for analysis of other pathways for which cognate promoters are available. Production of adenoviruses is beyond the scope of this chapter and can be subcontracted to a Vector Core (see Note 1) or created in the end user laboratory using the AdEasy system ((17); see also http:// www.coloncancer.org/adeasy.htm).

1.5. Protein Expression or Knockdown in ALI hAE Cells

Experiments employing expression of a protein or a mutant version of the protein, or knockdown of a specific mRNA and thus protein, can provide valuable mechanistic and functional insights. Transgenic gene expression or knockout by homologous recombination is often used in mice or other organisms for this purpose. Tissue culture cells on plastic can be genetically manipulated by plasmids and/or siRNA oligonucleotides, but standard techniques for introduction of genetic material are not efficient in well-differentiated ALI hAE cells. In Section 1.4., we illustrated

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Fig. 18.1. Overview of the method for adenovirus (Ad) reporter gene assays in welldifferentiated ALI hAE cells, employing co-transduction of a gene modifying the cell response. The panel below indicates the expected results with co-transduction of a control (Con.) or a construct that potentiates (Pot.) or inhibits (Inhib.) the baseline and stimulated reporter gene activity.

the strategy of adenovirus transduction and reporter gene assays. This approach typically results in expression of 5–30% of the total cells in an ALI hAE culture, thus limiting or precluding “whole culture” biochemical or functional analyses. However, the use of retro/lentiviral vectors, followed by selection and subculture, is a viable method for evaluating gene function in well-differentiated ALI hAE cells at the whole culture level (Fig. 18.2). This approach can be performed using viral vector constructs directing constitutive expression of proteins (18) or shRNA. Such vectors may not be feasible if the genetic manipulation inhibits cell growth and/or differentiation. In this case, inducible expression can be employed (19). Both of these approaches were used by our group to successfully knock down amiloride-sensitive epithelial sodium channel (ENaC) activity in passage 2, well-differentiated, ALI hAE cells by expressing shRNA targeting the alpha subunit gene (SCNN1A) (20) (see Note 2).

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Fig. 18.2. Overview of the method for retroviral/lentiviral vector genetic manipulation of well-differentiated ALI hAE cells.

2. Materials 2.1. Primary Human Airway Epithelial (hAE) Cell Cultures 2.1.1. Tissue Procurement

Airway epithelial cells can be extracted from excess surgical pathology or autopsy specimens procured through cooperating surgeons and pathologists using protocols in accordance with relevant regulations. These include nasal turbinates or polyps not requiring histopathologic examination; lung tissue after lobectomy, pneumonectomy, or transplantation (surgical pathology); and trachea/lungs (autopsy) after examination and release by a pathologist. A useful source of normal tissue is the donor’s lower trachea, carina, and mainstem bronchi left over after transplantation. These are transported to the laboratory in an appropriate container on wet ice in a physiologic solution (sterile saline, PBS, lactated Ringer’s solution, or tissue culture medium). Lungs from potential organ donors are frequently unsuitable for transplantation but are useful for research. These can be obtained via establishing protocols with the agencies that normally oversee organ donation or from non-profit organizations that provide human biomaterials for research (e.g., in the USA – National Disease Research Interchange, www.ndri.com). Criteria for specimen acceptability are discussed in Note 3. Finally, non-CF hAE cells

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are now available from a variety of commercial suppliers, circumventing the need for tissue procurement. 2.1.2. Media

Two closely related media are employed. Bronchial epithelial growth medium (BEGM) is used when plating initial cell harvests on type I/III collagen-coated plastic dishes or to expand passaged cells on plastic. Air–liquid interface (ALI) medium is used to support growth and differentiation on porous supports. Composition of BEGM and ALI medium is given in Table 18.1 and the differences between BEGM and ALI medium are illustrated in Table 18.2. The base media (LHC basal; Invitrogen, Carlsbad, CA, Cat. #12677, and DMEM-H; Invitrogen, Cat. #11995-065) can be purchased commercially and additives are made as specified below.

2.1.3. Stock Additives for ALI Medium and BEGM

Additives are 0.2 μM filtered (unless all components are sterile) and aliquots are stored at –20◦ C for up to 3 months unless otherwise specified. 1. Bovine serum albumin 300× (150 mg/mL): Add PBS to BSA (Sigma-Aldrich, St. Louis, MO, Cat. #A7638) at a concentration of >150 mg/mL, gently rock or stir at 4◦ C for 2–3 h until dissolved, and adjust volume to yield 150 mg/mL. 2. Bovine pituitary extract (BPE) (dilution depends on lot, typically 125×): BPE is available from Sigma-Aldrich (Cat. #P1476) and is used at a final concentration of 10 μg/mL. Check the protein concentration per milliliter of the specific lot to determine the dilution factor. 3. Insulin 1000× (5 mg/mL; 0.87 mM): Dissolve insulin (Sigma-Aldrich, Cat. #I6634) in 0.9 N HCl. 4. Transferrin 1000× (10 mg/mL; 0.125 mM): Reconstitute human holo transferrin (Sigma-Aldrich, Cat. #T0665) in PBS. 5. Hydrocortisone 1000× (0.072 mg/mL; 0.21 mM): Reconstitute hydrocortisone (Sigma-Aldrich, Cat. #H0396) in distilled water (dH2 O). 6. Triiodothyronine 1000× (0.0067 mg/mL; 0.01 mM): Dissolve triiodothyronine (Sigma-Aldrich, Cat. #T6397) in 0.001 M NaOH. 7. Epinephrine 1000× (0.5 mg/mL; 2.7 mM): Dissolve epinephrine (Sigma-Aldrich, Cat. #E4250) in 0.01 N HCl. 8. Epidermal growth factor 1000× for BEGM, 50,000× for ALI medium (25 μg/mL; 4 μM): Dissolve human recombinant, culture-grade EGF (Invitrogen, Cat. #PHG0313) in PBS.

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Table 18.1 BEGM and ALI medium composition Additive

Final concentration in media

Company

Cat. #

Bovine serum albumin

0.5 mg/mL

Sigma-Aldrich

A7638

Bovine pituitary extract

10 μg/mL

Sigma-Aldrich

P1476

Insulin

0.87 μM

Sigma-Aldrich

I6634

Transferrin

0.125 μM

Sigma-Aldrich

T0665

Hydrocortisone

0.21 μM

Sigma-Aldrich

H0396

Triiodothyronine

0.01 μM

Sigma-Aldrich

T6397

Epinephrine

2.7 μM

Sigma-Aldrich

E4250

Epidermal growth factor

25 ng/mL – BEGM 0.50 ng/mL – ALI medium

Invitrogen

PHG0313

Retinoic acid

5 × 10–8 M

Sigma-Aldrich

R2625

Phosphorylethanolamine

0.5 μM

Sigma-Aldrich

P0503

Ethanolamine

0.5 μM

Sigma-Aldrich

E0135

Zinc sulfate

3.0 μM

Sigma-Aldrich

Z0251

Penicillin G sulfate

100 U/mL

Sigma-Aldrich

P3032

Streptomycin sulfate

100 μg/mL

Sigma-Aldrich

S9137

Gentamicina

50 μg/mL

Sigma-Aldrich

G1397

Amphotericina Stock 4

Trace elements

0.25 μg/mL

Sigma-Aldrich

A2942

Ferrous sulfate

1.5 × 10–6 M

Sigma-Aldrich

F8048

Magnesium chloride

6 × 10–4 M

J.T Baker

2444

Calcium chloride

1.1 × 10–4 M

Sigma-Aldrich

C3881

Selenium

30 nM

Sigma-Aldrich

S5261

Manganese

1 nM

Sigma-Aldrich

M5005

Silicone

500 nM

Sigma-Aldrich

S5904

Molybdenum

1 nM

Sigma-Aldrich

M1019

Vanadium

5 nM

Sigma-Aldrich

398128

Nickel sulfate

1 nM

Sigma-Aldrich

N4882

Tin

0.5 nM

Sigma-Aldrich

S9262

a Not in ALI medium

9. Retinoic acid (concentrated stock = 1 × 10–3 M in absolute ethanol, 1000× stock = 5 × 10–5 M in PBS with 1% BSA): Retinoic acid (RA) is soluble in ethanol and is light sensitive. Dissolve 0.3125 mg of RA (Sigma-Aldrich, Cat. #R2625) per mL in 100% ethanol. Store in foilwrapped tubes at –70◦ C for up to 2 weeks. To prepare the 1000× stock, first confirm the RA concentration of

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Table 18.2 Differences between ALI medium and BEGM Base media Base antibiotics

ALI medium

BEGM

LHC basal:DMEM-H 50:50

LHC basal 100%

Penicillin/streptomycin (100 U/mL/100 μg/mL)

Penicillin/streptomycin (100 U/mL/100 μg/mL) Gentamicin 50 μg/mL Amphotericin 0.25 μg/mL

EGF

0.50 ng/mL

25 ng/mL

CaCl2

1.0 mM

0.11 mM

the ethanol stock by diluting it 1:100 in absolute ethanol. Read the absorbance at 350 nm using a spectrophotometer and a 1-cm light path quartz cuvette, blanked on 100% ethanol. The molar extinction coefficient of RA in ethanol equals 44,300 M–1 cm–1 at 350 nm. Thus, the absorbance of the diluted stock should equal 0.44. RA with absorbance readings below 0.18 should be discarded. If the absorbance equals 0.44, add 3 mL of 1 × 10–3 M ethanol stock solution to 53 mL PBS and add 4.0 mL of BSA 150 mg/mL stock (see step 1). For absorbance values less than 0.44, calculate the needed volume of ethanol stock as 1.35/absorbance unit and adjust the PBS volume appropriately. 10. Phosphorylethanolamine 1000× (0.07 mg/mL; 0.5 mM): Phosphorylethanolamine (Sigma-Aldrich, Cat. #P0503) is dissolved in PBS. 11. Ethanolamine 1000× (0.03 μL/mL; 0.5 mM): Dilute ethanolamine (Sigma-Aldrich, Cat. #E0135) in PBS. 12. Stock 11 1000× (0.863 mg/mL; 3 mM): Dissolve zinc sulfate (Sigma-Aldrich, Cat. #Z0251) in dH2 O. Store at room temperature. 13. Penicillin–streptomycin 1000× (100,000 U/mL and 100 mg/mL): Dissolve penicillin-G sodium (SigmaAldrich, Cat. #P3032) and streptomycin sulfate (SigmaAldrich, Cat. #S9137) in dH2 O for a final concentration of 100,000 U/mL and 100 mg/mL, respectively. 14. Gentamicin 1000× (50 mg/mL): Sigma-Aldrich, Cat. #G1397. Store at 4◦ C. 15. Amphotericin B 1000× (250 μg/mL): Sigma-Aldrich, Cat. #A2942. 16. Stock 4 1000×: Combine 0.42 g ferrous sulfate (SigmaAldrich, Cat. #F8048), 122.0 g magnesium chloride (J.T.

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Table 18.3 Stock solutions for trace elements Sigma-Aldrich, Cat. #

Component

Amount/100 mL

Molarity

Selenium (NaSeO3 )

S5261

520 mg

30.0 mM

Manganese (MnCl2 •4H2 O)

M5005

20.0 mg

1.0 mM

Silicone (Na2 SiO3 •9H2 O)

S5904

14.2 g

500 mM

Molybdenum [(NH4)6 Mo7 O24 •4H2 O]

M1019

124.0 mg

1.0 mM

Vanadium (NH4 VO3 )

398128

59.0 mg

5.0 mM

Nickel (NiSO4 •6H2 O)

N4882

26.0 mg

1.0 mM

Tin (SnCl2 •2H2 O)

S9262

11.0 mg

500 μM

Baker, Phillipsburg, NJ, Cat. #2444), 16.17 g calcium chloride dihydrate (Sigma-Aldrich, Cat. #C3881), and 800 mL dH2 O in a volumetric flask. Add 5.0 mL concentrated HCl. Stir to dissolve and bring volume to 1 L. 17. Trace elements 1000×: Prepare seven separate 100 mL stock solutions (see Table 18.3). Fill a 1-L volumetric flask to the 1 L mark with dH2 O. Remove 8 mL of dH2 O. Add 1.0 mL of each stock solution and 1.0 mL of concentrated HCl. Store at room temperature. 2.1.4. BEGM and ALI Medium

We describe here production of 500 mL or 1 L batches, which are assembled in the reservoir of a 0.2-μm bottle top filter. Larger quantities (e.g., > 6 L) can be prepared in a volumetric flask and sterilized by peristaltic pumping (e.g., Masterflex pump; Cole-Parmer Instruments, Vernon Hills, IL, Cat. #EW77910-20) through a cartridge filter (Pall, Ann Arbor, MI, Cat. #12991). To clean tubing, rinse with dH2 O, then ethanol followed again by dH2 O. 1. BEGM: Dispense thawed additives into 100% LHC basal medium (Invitrogen, Cat. #12677) in a bottle top filter unit. Note that some additives are not 1000×. Add amphotericin after filtering. Store media at 4◦ C. 2. ALI medium: The ALI base is 50:50 DMEM-H (e.g., Invitrogen, Cat. #11995-065) and LHC basal (Invitrogen, Cat. #12677). Thaw and dispense additives as above. Note that some additives are not 1000×. ALI medium contains low EGF and omits gentamicin and amphotericin. To prepare low endotoxin medium, use low endotoxin BSA (SigmaAldrich, Cat. #A2058).

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2.1.5. Antibiotics

2.1.6. Assorted Reagents and Solutions

Primary human tissues, even from non-CF sources, frequently contain yeast, fungi, or bacteria. Media for passage 0 cultures should be supplemented with at least gentamicin (50 μg/mL) and amphotericin (0.25 μg/mL) for the first 3–5 days. Less contamination will result by increasing the amphotericin concentration to 1.25 μg/mL and adding ceftazidime (100 μg/mL), tobramycin (80 μg/mL), and vancomycin (100 μg/mL). When processing tissues from CF patients, additional antibiotics are used as described in a prior publication (21). If no information is available, and assuming P. aeruginosa contamination, consider adding ciprofloxacin (20 μg/mL), meropenem (100 μg/mL), and colymycin (5 μg/mL). CF lungs infected with Alcaligenes xylosoxidans, Burkholderia sp., or Stenotrophomonas maltophilia may require a different spectrum of antibiotics including sulfamethoxazole/trimethoprim (80 μg/mL), chloramphenicol (5 μg/mL), minocycline (Sigma-Aldrich, Cat. #M9511, 4 μg/mL), tigecycline (2 μg/mL), or moxifloxacin (20 μg/mL). For fungus or yeast contamination, nystatin (Sigma-Aldrich, Cat. #N1638, 100 U/mL) and diflucan (25 μg/mL) can be added. Antibiotics listed above without sources are from the hospital pharmacy. Sterile liquids for injection may be added directly to media, whereas powders contain a given amount of antibiotic and unknown quantities of salts and buffers – purity of powders is determined by comparing the total vial powder weight to the designated antibiotic content and adjusting the micrograms per milliliter accordingly. A 25× concentrated antibiotic cocktail can be stored at 4◦ C and used within 1–2 days. Note that nystatin and amphotericin are suspensions and cannot be filter sterilized. All non-sterile solutions are filter sterilized and stored at –20◦ C unless otherwise noted: 1. Ham’s F-12 medium with 1 mM L-glutamine: Mediatech, Manassas, VA, Cat. #10-080. Store at 4◦ C. 2. Cell freezing solution: Combine 2 mL of 1.5 M HEPES (pH 7.2), 10 mL of fetal bovine serum (Sigma-Aldrich, Cat. #F6178), and 78 mL Ham’s F-12 medium. Gradually add 10 mL DMSO (Sigma-Aldrich, Cat. #D2650). 3. 1% Protease XIV with 0.01% DNase (10× stock): Dissolve protease XIV (Sigma-Aldrich, Cat. #P5147) and DNase (Sigma-Aldrich, Cat. #DN25) in desired volume of PBS and stir. A 1:9 dilution in JMEM (see step 6) is used for cell dissociation. 4. Soybean trypsin inhibitor (1 mg/mL): Dissolve soybean trypsin inhibitor (Sigma-Aldrich, Cat. #T9128) in Ham’s F-12. Store at 4◦ C.

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5. 0.1% Trypsin with 1 mM EDTA in PBS: Dissolve trypsin type III powder (Sigma-Aldrich, Cat. #T4799) in PBS. Add EDTA from concentrated stock for a final concentration of 0.1% trypsin with 1 mM EDTA. Adjust pH of the solution to 7.2–7.4. 6. Joklik minimum essential medium (JMEM): Sigma-Aldrich, Cat. #M8028. Store at 4◦ C. R (Advanced BioMatrix, San 7. Type I/III collagen: Purecol Diego, CA, Cat. #5005). Store at 4◦ C.

2.1.7. Porous Supports

There are multiple porous support options for ALI cultures. Ideal supports are optically clear, facilitate attachment and long-term growth, and are amenable to downstream analyses. However, in our experience, there have been problems with membrane consistency and quality control. We strongly recommend coating all porous supports with human type IV placental collagen (see Section 3.1.3). R , 0.4 μM pore size (Corn1. Recommended: Transwell-Clear R ing, Inc., Cat. #’s 3450, 3460, and 3470) or Snapwell (Corning, Inc., Cat. #3801) membranes. 2. We have also had recent success with Millipore IsoporeTM membrane (polycarbonate) (Millipore Corporation, Billerica, MA, Cat. #PIHP01250) but these are not optically clear and thus not amenable to direct visualization on an inverted microscope.

2.2. Materials for Production of Retroviral and Lentiviral Vectors

1. Human 293T embryonic kidney cells (ATCC, Manassas, VA, Cat. #CRL-11268, see Note 4) are cultured in DMEM with 4500 mg/L glucose, sodium pyruvate, and L-glutamine (Invitrogen, Cat. #11995-065) supplemented with 10% FBS. 2. Both retroviral and lentiviral vectors are produced using three-plasmid co-transfection. For production of HIV-1based lentiviral vectors, pCMVdeltaR8.74 (22) and pCIVSV-G (23), which encode HIV-1 Gag-Pol and the VSVG envelope, respectively, provide necessary helper functions. A third plasmid, which carries the transgene of interest (promoter plus the transgene open reading frame), also contains HIV-1 sequences necessary for encapsidation and a single round of replication. For production of murine leukemia virus (MLV)-based retrovirus vectors, the necessary helper functions are provided for by the pCI-GPZ GagPol expression vector (23) and pCI-VSV-G (23). As before, a third plasmid encodes the gene of interest as well as MLV sequences permitting encapsidation and replication. Plasmid DNA is purified using an endotoxin-free plasmid purifica-

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tion kit (Qiagen, Valencia, CA, Cat. #12362). The DNA concentration for transfection is determined by agarose gel electrophoresis and comparing the supercoiled DNA band to a mass standard run in a parallel lane (High DNA Mass Ladder; Invitrogen, Cat. #10496-016) (see Note 5). 3. 2× HBS (HEPES buffered saline, 500 mL): Dissolve 6 g HEPES (4-{2-hydroxyethyl}-1-piperazine ethanesulfonic acid) (Boehringer Mannheim, Indianapolis, IN) and 7.3 g NaCl in dH2 O to a final volume of 480 mL. Add 5 mL of 150 mM Na2 PO4 . Adjust pH to 7.10 ± 0.03 with 3 N NaOH and filter (0.2 μm) (see Note 6). 4. 2 M CaCl2 : Dissolve 29.4 g CaCl2 •2H2 O in dH2 O to a final volume of 0.1 L and filter (0.2 μm). 5. 150 mM Na2 HPO4 : Dissolve 4.02 g Na2 HPO4 •7H2 O in dH2 O to a final volume of 100 mL and filter (0.2 μm). 6. 500 mM Sodium butyrate: Dissolve 0.55 g (Alfa Aesar, Ward Hill, MA, Cat. #A11079-22) in dH2 O to a final volume of 10 mL and filter (0.2 μm). Store at –20◦ C. 7. PBS: Mediatech, Cat. #21-040. 2.3. Materials for Creation of Airway Epithelial Cell Lines

1. Frozen aliquots of retro- or lentiviruses expressing SV40ER, Bmi-1, and hTERT as prepared in Section 3.2. The Bmi-1, hTERT, and SV40ER containing HIV-1-based gene transfer vectors were obtained from Patrick Salmon (24). We typically use undiluted producer cell line supernatants instead of concentrated or purified virus. For purified virus, dilutions must be determined empirically. A multiplicity of infection (MOI) of 1–5 is typical. 2. Polybrene (Sigma-Aldrich, Cat. #H9268, 4.0 mg/mL in dH2 O). Filtered (0.2 μm) and aliquots stored at –20◦ C. 3. Passage 0 or 1 primary hAE cells on plastic at less than 40% confluence (our example is for cells growing on 100-mm tissue culture dishes – mathematically adjust volume for other formats). 4. Selection agent as appropriate for viral construct (geneticin, 100 μg/mL; puromycin, 1.0 μg/mL; hygromycin, 0.1 μg/mL; see Note 7).

2.4. Materials for Reporter Gene Assays in ALI hAE Cells

Reagents are stored at room temperature unless otherwise specified: 1. Adenovirus constitutively expressing LacZ (Ad.CMV-lacZ (25), aliquots stored at –80◦ C) (see Note 1). 2. Adenovirus expressing NF-κB-responsive firefly luciferase (Ad.NF-κB-fLuc (25), aliquots stored at −80◦ C) or other promoter-fLuc reporter construct of interest (see Note 1).

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3. Control, overexpression, dominant negative, or shRNA construct of interest cloned into a suitable shuttle vector and made into adenovirus by a vector core or using the AdEasy system (aliquots stored at −80◦ C). 4. 30 mM Sodium caprate (C10, capric acid, sodium decanoate; Sigma-Aldrich, Cat. #C4151) in PBS, filter sterilized, and aliquots stored at −20◦ C. 5. Passive lysis buffer, 5× (Promega, Madison, WI Cat. #E194A); aliquots stored at −20◦ C. 6. Luciferase assay buffer, stored in single-use aliquots at −20◦ C: to make 25 mL, combine 2.5 mL of 0.25 M glycylglycine (Sigma-Aldrich, Cat. #G1002, 25 mM final) in dH2 O, pH 7.8; 3.75 mL of 0.1 M potassium phosphate buffer (15 mM final), pH 7.8; 3.75 mL of 0.1 M MgSO4 (15 mM final) in dH2 O; 1.0 mL of 0.1 M EGTA in dH2 O (pH 8.0 to dissolve, 4 mM final); 0.5 mL of 0.1 M ATP (Sigma-Aldrich, Cat. #A3377, 2 mM final) in 5 mM Tris, pH 7.5 (stored in single-use aliquots at −20◦ C); 0.25 mL of 0.1 M dithiothreitol in dH2 O (1 mM final, stored in single-use aliquots at −20◦ C); and 13.5 mL dH2 O. 7. D-Luciferin solution, stored in single-use aliquots at −80◦ C (protect from light): To make 90 mL, add 5.0 mg D-luciferin (Sigma-Aldrich, Cat. #L9504, 0.2 mM final); 9.0 mL 0.25 M glycylglycine (Sigma-Aldrich, Cat. #G1002, 25 mM final) in dH2 O, pH 7.8; 9.0 mL of 0.1 M dithiothreitol in dH2 O (10 mM final, stored in single-use aliquots at −20◦ C) to 72 mL dH2 O. 8. β-gal assay buffer, make fresh: To 20 mL PBS, add 10 μL of 0.5 M chlorophenol red-β-D-galactoside (CPRG, SigmaAldrich, Cat. #59767, 0.25 mM final) in dH2 O, aliquots stored at −20◦ C, 0.2 mL of 0.1 M MgSO4 (1.0 mM final) in dH2 O, and 27 μL β-mercaptoethanol (19.3 mM final). 9. Luminometer (procedure illustrated is for a Turner BioSystems Veritas 96-well luminometer). 10. 96-Well optical plate reader. 2.5. Materials for Protein Expression or Knockdown in ALI hAE Cells

1. Frozen aliquots of retro- or lentiviruses expressing the constitutive or inducible protein, mutant protein, shRNA (see Note 2), or control (see Notes 5, 8, and 9) construct of interest prepared as described below in Section 3.2. We have used pSIREN- (http://www.clontech.com) and pSLIK (19)-based constructs for constitutive and inducible expression, respectively. Undiluted virus producer cell line supernatants or empirically determined dilutions of concentrated or purified virus, enabling adequate cell survival after selection, are necessary.

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2. Polybrene (see Section 2.3, step 2). 3. Passage 0 or 1 primary hAE cells on plastic (see Section 3.1.6). Enough cells should be available to accommodate the experimental treatment and all necessary controls. 4. Selection agent (see Section 3.3, step 11). 5. Induction agent, depending on vector and construct (we use 1 μg/mL doxycycline in media, filter sterilized, for the pSLIK vector system).

3. Methods 3.1. Primary Human Airway Epithelial (hAE) Cell Cultures 3.1.1. Primary Cell Culture Overview

Primary hAE cells can be obtained from nasal, tracheal, or lung tissue specimens and can be seeded directly onto porous supports for passage 0 air–liquid interface cultures or can be first grown on plastic for cryopreservation and/or sub-culture of passage 1 or passage 2 cells to porous supports (Fig. 18.3).

3.1.2. Type I/III Collagen Coating of Plastic Dishes

Passage 0 and freshly thawed, cryopreserved cells are plated on collagen-coated plastic dishes, whereas cells passaged without freezing do not require coated dishes. Add 3.0 mL of 1:75 diluR (see Section 2.1.6, step 7) in dH2 O per 100tion of Purecol mm dish. Incubate for 2–24 h at 37◦ C. Aspirate remaining liquid and expose open dishes to UV in a laminar flow hood for 30 min. Plates can be stored for up to 8 weeks at 4◦ C.

3.1.3. Type IV Collagen Coating of Porous Supports

There are multiple porous support options for ALI cultures. See Section 2.1.7 for a description of the various porous supports for collagen coating: 1. Re-suspend 10 mg of collagen powder (Sigma-Aldrich Type VI, Cat. #C7521) in 20 mL dH2 O and add 50 μL of concentrated acetic acid. Incubate for 30 min at 37◦ C until dissolved. Filter the solution using a syringe filter (0.2 μm) (Pall, Cat. #PN4192) and store aliquots at –20◦ C. 2. Thaw frozen stock and dilute 1:10 with dH2 O. Add 100 or 400 μL per 12- and 24-mm insert, respectively, and dry in a laminar flow hood overnight. Expose to UV in a laminar flow hood for 30 min, wrap dishes with parafilm, and store at 4◦ C for up to 1 month.

3.1.4. Isolating Primary hAE Cells

Primary hAE cells originate from nasal turbinates, nasal polyps, trachea, and bronchi. When handling human tissues, always follow locally prescribed safety precautions to prevent potential blood-borne pathogen exposure. Tissue is transported to the

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Fig. 18.3. Overview of the process for creating well-differentiated air–liquid interface (ALI) cultures of primary human airway epithelial (hAE) cells. P, passage.

laboratory in sterile containers containing sterile-chilled lactated Ringer’s (LR) solution, JMEM, F12, or another physiologic solution. Nasal tissue samples are usually processed without further dissection but whole lungs require dissection as described below: 1. Assemble in a laminar flow hood: a. Absorbent bench covering (many suppliers). b. Large plastic sterile drape (3M Health Care, St. Paul, MN, Cat. #1010). c. Ice bucket containing sterile specimen cups (many suppliers) filled with LR solution. d. Use instrument sterilizer (Fine Science Tools, Foster City, CA, Cat. #18000-45) or preautoclaved instruments. Suggested tools include curve-tipped scissors, delicate 4.5 in. (Fisher Scientific, Cat. #08-951-10); heavy scissors, straight, sharp, 11.5 cm (Fine Science Tools, Cat. #14058-11); forceps, blunt-pointed, straight, 15 cm (Fine Science Tools, Cat. #11008-15); rat-tooth forceps 1 × 2, 15.5 cm (Fine Science Tools, Cat. #11021-15);

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scalpels, #10 (many suppliers); sterile 4-in. × 4-in. cover sponges (many suppliers). 2. Dissect airways by removing all excess connective tissue and cutting into 5–10-cm segments. Clean tissue segments, removing any additional connective tissue and lymph nodes, and rinse by “dipping” in LR solution. Slit segments longitudinally and cut into 1 cm × 2 cm portions. Transfer to specimen cup containing chilled LR solution. 3. Since human tissue samples are likely to contain yeasts, bacteria, or fungi, begin antibiotic exposure as soon as possible. Prepare 250 mL of “wash media” – JMEM plus desired antibiotics (see Section 2.1.5). Aspirate LR solution and add “wash media,” swirl, and repeat three times. Transfer washed tissue to 50-mL conical tubes containing 30 mL “wash media” plus 4 mL protease/DNase solution. (Approximate tissue-to-fluid ratio of 1:10, final volume 40 mL.) Place tubes on platform rocker (50–60 cycles/min) at 4◦ C for 24 h. 4. CF tissues or others with abundant mucus are soaked in dithiothreitol (DTT, 0.5 mg/mL; Sigma-Aldrich, Cat. #D0632) and DNase (10 μg/mL; Sigma-Aldrich, Cat. #DN25) plus supplemental antibiotics (see Section 2.1.5). To prepare “soak solution,” add 65 mg DTT and 1.25 mg DNase to 125 mL of “wash media” and filter sterilize. Aspirate LR solution, add 40 mL “soak solution,” swirl, soak for 5 min, repeat, then rinse tissue three times in “wash media.” Transfer tissue to 50-mL tubes containing 30 mL “wash media” plus 4 mL protease/DNase (final volume 40 mL). Place tubes on platform rocker (50–60 cycles/min) at 4◦ C for 24 h. 5. Nasal turbinates, polyps, and small bronchial specimens can be dissociated in 4–24 h, depending on the size of the tissue, in 15-mL tube containing 9 mL “wash media” plus 1 mL protease solution. 3.1.5. Harvesting Cells

Follow standard sterile tissue culture techniques in a laminar flow hood: 1. End dissociation by pouring contents of 50-mL tubes into a 150-mm tissue culture dish; add fetal bovine serum (SigmaAldrich) to a final concentration of 10% (v/v). 2. Gently scrape epithelial surface with a #10 scalpel blade. Rinse tissue and plate surface with PBS, collect and pool solutions, and distribute into 50-mL conical tubes. 3. Centrifuge at 500×g for 5 min at 4◦ C. Aspirate supernatant and add 12 mL of declumping solution (2 mM EDTA, 0.05 mg/mL DTT (Sigma-Aldrich, Cat. #D0632), 0.25 mg/mL collagenase (Sigma-Aldrich, Cat. #C6885),

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0.75 mg/mL calcium chloride (Sigma-Aldrich, Cat. #C3881), 1 mg/mL magnesium chloride (Sigma-Aldrich, Cat. #M8266), and 10 μg/mL DNase in PBS). Incubate for 15 min to 1 h at 37◦ C, visually monitoring clump dissociation. Add FBS to a final concentration of 10% (v/v), centrifuge at 500×g for 5 min, remove supernatant, and resuspend pellet in F12 for counting using a hemocytometer. 3.1.6. Plating Cells

Culture dissociated P0 hAE cells directly on porous supports in ALI medium with additional antibiotics (see Section 2.1.5) at a density of 0.1–0.25 × 106 cells per cm2 (0.8–2.0 × 105 cells per 12-mm support or 0.7–1.75 × 106 cells per 24-mm support, see Note 10). To generate P1 or P2 cells, plate cells in antibioticsupplemented BEGM on type I/III collagen-coated plastic dishes at a concentration of 2–6 × 106 cells per 100-mm dish. Change media at 24 h and every 2–3 days as needed to prevent acidification.

3.1.7. Cell Culture Maintenance

1. P0 cells on plastic: Assess attachment after 24 h of plating P0 cells; if few clumps of floating cells are present, wash with PBS and feed with BEGM plus antibiotics (see Section 2.1.5). Rescue floating clumps of cells by washing dishes with PBS, harvesting into 50-mL conical tubes, pelleting at 500×g for 5 min, and repeating the “declumping” procedure (see Section 3.1.5, step 3). 2. Passaging primary cells on plastic: Passage primary cultures at 70–90% confluence. Harvest hard to detach cells, while minimizing trypsin exposure of cells that release quickly using “double trypsinization.” Rinse cells with PBS, add 3 mL of trypsin/EDTA per 100-mm dish, and incubate for 5–10 min at 37◦ C. Gently tap dish to detach cells, rinse with PBS, and harvest into 50-mL conical tube containing 3 mL STI solution on ice. Add another 3 mL of trypsin/EDTA to the dish and repeat, visually monitoring detachment. Pool harvested cells and centrifuge at 500×g for 5 min at 4◦ C. Aspirate supernatant and re-suspend cells in media for counting. 3. Media change in ALI cultures: For P0, P1, or P2 hAE cells grown on collagen-coated porous supports, remove apical media and rinse the apical surface with PBS. Prior to confluence, replace apical and basolateral media volumes as specified for the porous support, but after confluence, do not add media apically. During periods of rapid cell growth, cells on R inserts in the standard configuration will acidTranswell ify the media rapidly and require daily changes. We have R inserts devised Teflon adapters to enable 12-mm Transwell to be kept in six-well plates with a 2.5-mL basolateral reservoir, which decreases media change frequency. The 24-mm R insert may be kept in “Deep-Well Plates” (BD Transwell

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Bioscience, Bedford, MA, Cat. #355467) with 12.5 mL media. 3.1.8. Cryopreservation of Cells

1. Trypsinize P0 hAE cells from plastic dishes (now P1 cells) and cryopreserve for long-term storage in liquid nitrogen. Re-suspend cells in Ham’s F-12 media at a concentration of 2–6 × 106 cells/mL. 2. Keep cells on ice and slowly add an equal amount of freezing media (see Section 2.1.6, step 2) to the cell suspension. 3. Place cryovials in Nalgene cryofreezing container R Labware, Rochester, NY, Cat. #5100) and (Nalgene ◦ place in –80 C freezer for 4–24 h. 4. Transfer vial(s) from the –80◦ C freezer to liquid N2 (–196◦ C) for long-term storage.

3.1.9. Thawing Cells

1. Thaw the cryovial at 37◦ C and wipe outside with 70% ethanol. Transfer cells to a 15-mL conical tube. 2. Dilute the cell suspension by slowly filling the tube with Ham’s F-12. Centrifuge at 500×g for 5 min at 4◦ C. 3. Gently re-suspend cells in media, count, and assess viability.

3.2. Production of Retroviral and Lentiviral Vectors

1. Culture human 293T embryonic kidney cells in DMEM with 4500 mg/L glucose, sodium pyruvate, and Lglutamine supplemented with 10% FBS. Grow cells on plastic dishes or flasks at 37◦ C in a 5% CO2 incubator and split 1:8 every 3 days. For routine splitting (100-mm plates), remove and discard media, rinse cell layer briefly with PBS, and add 3 mL of trypsin/EDTA solution to plates until the cell layer is dispersed (usually within 5 min). Add 6–8 mL of complete growth medium and aspirate cells by gently pipetting. Add appropriate aliquots of cells to new culture vessels. 2. Seed 293T cells at 4.5 × 106 cells/100-mm tissue culture dish to obtain ∼80% confluence the next day. Incubate overnight at 37◦ C in a humidified incubator with 5% CO2 . 3. In polystyrene tubes, mix 15 μg gene transfer vector, 15 μg Gag-Pol expression vector, and 9 μg VSV-G expression vector to give a final volume of 262.5 μL. Add 37.5 μL of 2 M CaCl2 . 4. For each transfection, aliquot 300 μL of 2× HBS solution into a polystyrene tube. To this add the 300 μL DNA/CaCl2 mixture dropwise (but somewhat rapidly) and then mix gently. Incubate for 10 min at room temperature. 5. Remove medium from cells and replace with 6 mL fresh growth medium. Next add 600 μL plasmid sample, prepared

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as above, to the cells dropwise. Swirl the plate gently to mix and incubate overnight at 37◦ C. 6. Remove the medium and replace with 6 mL of fresh growth medium per plate containing 10 mM sodium butyrate (see Note 11). Incubate cells with sodium butyrate for 8–10 h. Remove medium and replace with 7 mL fresh medium (without sodium butyrate) containing 2% FBS and return cells to incubator. Incubate for 16–24 h. 7. The next day, swirl the plates gently, then remove virus, and filter through a 0.2-μm polyethersulfone (PES) filter. Store virus in 1 mL aliquots at –80◦ C. Just prior to use, thaw the virus in a water bath at 37◦ C. 3.3. Creation of Airway Epithelial Cell Lines

1. Employ specified personal protective equipment (lab coat, double gloves, safety glasses, and particle mask) and secure the cell culture area (post notice and close the door to limit non-essential access). Experiments involving human cells and recombinant viral vectors require Biological Safety Level 2 containment. Consult your local Institutional Biosafety Committee for advice on safe working practices when using these materials. 2. Prepare 20% chlorine bleach solution in a suitable beaker and place in tissue culture hood (all virus-contaminated items are to be bleached for at least 30 min). 3. Transfer cells (one cell type at a time, see Note 12) to hood, aspirate media, and add room-temperature PBS. 4. Thaw polybrene (need 2 μL/mL of virus-containing media). 5. Rapidly thaw virus by swirling vial in 37◦ C water, record vial identification on culture dish lid and notebook, and clean outside of vial with 70% ethanol. 6. Aspirate PBS. 7. Add 1.5 mL of SV40ER or Bmi-1 virus supernatant and 1.5 mL of hTERT virus supernatant per 100-mm diameter dish (i.e., one oncogene plus hTERT, in 3 mL total). 8. Add 6 μL of polybrene (see Section 2.3, step 2) and gently swirl in a figure eight pattern to distribute evenly. 9. Incubate for 3 h at 37◦ C and gently swirl every hour. 10. Remove virus-containing media, wash with PBS, and add growth media. 11. Initiate appropriate selection (if desired; see Note 13) for 7 days beginning 48 h after infection and change media every 2–3 days, preventing acidification.

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12. When cells reach 70–90% confluence, trypsinize and cryopreserve an aliquot (see Sections 3.1.7, step 2 and 3.1.8). Passage the remainder for expansion. 13. Cryopreserve cells at regular intervals during passaging. 3.4. Reporter Gene Assays in ALI hAE Cells

1. Use well-differentiated ALI hAE cultures in replicates of 3–4 wells per experimental group (see Note 14). 2. Soak apical surface with PBS (100 μL for each 10–12-mm insert) for 20 min 24 h prior to adenovirus exposure and rinse one more time with PBS to remove excess mucus. 3. On the day of adenovirus exposure, wash the apical surface once with PBS and aspirate the residual liquid. 4. Prepare adenovirus solution in ALI media (room temp.). Optimal concentrations should be determined by titration but are typically in the range of 0.5 × 107 CFU/mL for the reporter viruses (10× greater for co-transduction with test constructs of interest when used). 5. Add 30 mM sodium caprate in PBS to the apical surface only, 50 μL per 10–12-mm insert, for 3 min. Aspirate and wash the apical surface once with PBS (see Note 15). 6. Infect cells by applying adenovirus to both the apical and the basolateral surfaces in volumes needed for the specific culture format (50 μL apically and 1 mL basolaterally for a 10–12-mm insert in a 12-well plate). Perform equivalent maneuvers, but without virus in duplicate control wells. Place in 37◦ C, 5% CO2 incubator for 2 h. 7. Aspirate apical and basolateral media. 8. Replace basolateral media without virus; cells are ready for challenge and assay 24–48 h later. 9. Eight hours after challenge (if needed, as per the experimental design), lyse cells by removing media, transferring to a Petri dish, and adding 100 μL of 1× passive lysis buffer while pressing down on the insert and scraping cells with a rubber policeman. Repeat 1× per well for a total of 200 μL pooled sample. Assay fLuc and β-gal on the day of harvest or freeze in aliquots and store at –20◦ C, avoiding repeated freeze–thaw cycles. Handle all samples to be directly compared identically (including assays below). 10. Assay fLuc as per the luminometer format. Samples may need dilution, determined empirically, if very high activity. For automated 96-well format (e.g., Turner Veritas luminometer), add 90 μL luciferase assay buffer per well of an opaque 96-well plate and add 20 μL of lysate supernatant (14,000×g spin for 2 min) per well. Program the luminometer: one injector, no plate read before injection, 40 μL of luciferin solution per well, 0 s delay time, and

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5 s integration time. Prime the injector with luciferin solution (requires 500 μL). Perform reading. Reverse purge the injector 3X dH2 O, 3X 70% ethanol, 3X dH2 O, 3X air. 11. Assay β-gal by adding 180 μL of β-gal assay buffer per well of 96-well flat-bottomed clear plate. Add 20 μL of lysate supernatant (14,000×g spin for 2 min) per well, using nontransfected cell lysate as a control. Use adhesive 96-well plate tape and shake for 5 min. Incubate at 37◦ C until color develops, typically 10 min to 3 h. Read at 575 nm; values from 0.12 to 1.8 are within the linear range. 12. Express data as fLuc light units (arbitrary units) divided by β-gal OD 575 (- blank). 3.5. Protein Expression or Knockdown in ALI hAE Cells

1. Using protocols described in Sections 1.2 and 3.2, primary hAE cells on plastic are transduced with retroviral or lentiviral vectors and selected. 2. Selected cells are trypsinized, counted, and passaged to porous supports as in Sections 3.1.6 and 3.1.7, see Note 16. 3. For most studies, cultures are allowed to grow and differentiate at an ALI. Studies of protein function can be conducted at any time if a constitutive promoter is being used, but generally, differentiated cells are preferred (∼ 3 weeks). 4. If induction is required, the relevant induction agent is added once the cells have reached the preferred differentiation state. In a 48–72 h time frame after induction (or longer), changes in mRNA and/or protein expression can be determined by quantitative RT-PCR or Western blots, respectively, using routine protocols which are beyond the scope of this chapter (see Note 17). Functional changes induced by the genetic manipulation are examined as per the experimental purpose.

4. Notes 1. The Ad.CMV-lacZ and Ad.NF-κB-fLuc viruses described herein (25) were originally created in the University of Iowa Vector Core (http://www.uiowa.edu/~gene/) and amplified in the University of North Carolina Vector Core (http://genetherapy.unc.edu/jvl.htm); these cores and others (e.g., http://www.med.upenn.edu/gtp/vector_ core.shtml) provide services for external investigators. 2. Although results will vary across genes and shRNA sequences, we have obtained 60–70% mRNA knockdown in well-differentiated hAE cells with effective shRNA

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sequences, employing either constitutive or inducible expression systems with a corresponding, or somewhat greater, decrease in protein expression and function. 3. In our experience, autopsy specimens must be procured within approximately 8 h of time of death, but surgical pathology specimens can be stored for up to 3 days at 4◦ C. To protect personnel, do not accept specimens posing a known infection risk for HIV, Hep B and C, or tuberculosis. Samples from individuals on long-term immunosuppressive therapy may pose increased risk. All human tissue samples must be treated as a potential biohazard and handled using standard precautions. Steps for specimen procurement may breach sterility and/or tissues (especially CF) are likely infected with bacteria or fungi, thus appropriate antibiotics are necessary (see Section 2.1.5). A range of clinical data (laboratory values including blood gases, Xray, and bronchoscopy findings) can guide acceptability of sub-transplant quality donor lungs. There are no hard and fast rules, but an arterial PO2 of greater than 100 mmHg on 100% inspired oxygen is a reasonable lower limit for acceptance. 4. 293T cells obtained from different sources have variable properties and optimal cell numbers for maximum vector production may need to be determined empirically. We have found it useful to single-cell clone 293T cells from a trusted source and to test clonal cell lines for their ability to be transfected at high efficiency (95–100%) and their ability to produce vectors at high titer (>106 infectious units/mL) (23). Clonally derived cells with the desired properties can be cryopreserved and thawed when needed. After thawing, cells usually retain their vector-producing properties for at least 1–2 months before they need to be replaced. 5. Retroviral/lentiviral gene transfer vectors are available from a number of sources. For constitutive expression of a target gene as well as an antibiotic selection marker, we have had good success using the murine leukemia virus-based Retro-X Q Vectors from Clontech. The pSIREN-RetroQ gene transfer vector is a murine leukemia virus-based vector (Clontech, Cat. #PT3737-5) used for constitutively expressing small hairpin RNA (shRNA). The pSLIK vectors (ATCC, Cat. #MBA-268) are HIV-1-based gene transfer vectors used for inducible shRNA expression (19). On occasion, plasmids purified using the Qiagen methods are contaminated with insoluble material (most likely residue from the column). In such cases, the plasmid DNA is clarified by centrifugation (10,000×g, 5 min), and the DNA in the supernatant is transferred to a new tube.

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6. The pH of the 2× HBS solution is critical for obtaining efficient transfection. We usually make up several 2× HBS solutions that vary in pH between 7.05 and 7.2 and then test to see which 2× HBS solution yields the best vector production. 2× HBS can be stored for several months at room temperature. 7. The selection agent concentrations are based on our experience with passage 0–2 primary hAE cells. Densely growing cells are more resistant to selection agents. Maintaining selection for at least 7 days and passaging dense cells into media with selection agent (if necessary) is recommended. 8. Screening short RNA sequences for effective knockdown is critical. We typically screen four commercially supplied siRNA sequences in cell lines that express the protein of interest (16HBE (13) or UNCN3T (14) cells) followed by quantitative RT-PCR, or Western blot if antibodies are available. We have had good results with the Amaxa cell transfection system (Lonza, Walkersville, MD). Effective sequences (typically 1–2 out of 4 are found) are cloned into the vector of choice using appropriate methods. Screening with siRNAs may not be possible for genes/proteins not expressed in cell lines on plastic (e.g., ciliated cell-specific genes), in which case multiple shRNA vectors and empirical testing on the hAE cells will be necessary to identify active sequences. 9. Appropriate controls are essential, especially for shRNAs potentially having off-target and/or non-target effects (e.g., interferon response). Empty vector, scrambled shRNA, and/or shRNAs to irrelevant genes are good choices. Rescue by expression of an shRNA-resistant point mutant protein is the gold standard (26). 10. Seeding densities: Primary human airway epithelial cells are mortal and require sufficient seeding density. Attachment and growth of cells from different individuals and preparations may vary. Generous seeding densities of passage 0 cells on porous supports (>1.5 × 105 cells/cm2 ) are required to obtain consistent, confluent, well-differentiated ALI cultures. Although it is tempting to expand primary cells on plastic, “overexpansion” should be avoided. Passage 0 cells first grown on plastic dishes should be seeded at not less than 1 × 106 , and preferably 2–6 × 106 , cells per 100-mm collagen-coated dish (or as calculated mathematically for other dish sizes). Under these conditions, the cells should grow to >70% confluence within 5–7 days – if a longer period is required, subsequent growth may be impaired. Cells at >70% confluence, but not >95%

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confluence, should be trypsinized for cryopreservation or subpassage to a porous support or expanded one more round to passage 2 by seeding >1 × 106 cells per 100 mm tissue culture dish. Passage 1 and 2 cells seeded on porous supports at ∼1.5 × 105 cells/cm2 (∼170,000 and ∼0.7 R membranes, × 106 cells per 12- and 24-mm Transwell respectively) should result in confluence within 3–5 days after seeding, at which point an ALI should be established. Lower seeding densities may be fully successful with some specimens, which can be determined empirically with aliquots of frozen cells, but is not possible when plating passage 0 cells, and greater variability is anticipated between different preparations. 11. Production of retroviral/lentiviral vectors from most sources of 293T cells is enhanced up to fivefold by treatment with sodium butyrate. An alternate method of treatment is to leave the sodium butyrate-containing medium with 2% FBS on the cells overnight prior to harvesting the virus the next day. The brief exposure of hAE cells to sodium butyrate in the resulting virus stock does not appear to affect their growth and differentiation properties. 12. Cross-contamination of cell lines is an important concern and it is a good policy to work with only one cell line at a time in the culture hood. 13. The decision to employ a vector system enabling selection is up to the investigator. Selection ensures more uniform and higher level transgene expression in the cell population. However, resistance to selection agents may limit cell downstream utility or options, e.g., in gene expression or knockdown experiments requiring selection. When seeded at the recommended density, the selected cells should be 70–90% confluent by day 6 or 7 but may take longer if the efficiency of infection is low as indicated by abundant cell death occurring during selection. If the cells are not confluent within 10–12 days, they may not be able to differentiate well at an ALI. To achieve adequate infection efficiencies, it is recommended that the minimum titer of retroviral/lentiviral vectors is 2 × 105 infectious units/mL. 14. It is important that ALI cultures are confluent and healthy in order to withstand caprate permeabilization. Access of caprate to the basolateral solution in non-confluent cultures will result in cell exfoliation. 15. We recommend performing pilot experiments with 30 mM sodium caprate exposure to verify that it will not cause excess cell cytotoxicity and cell exfoliation of a given set of wells, and reducing the exposure time if necessary.

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16. Having nearly equivalent viral titers for control and experimental vectors and equivalent survival during selection (determined by cell counting) is an important factor. If cell survival differs greatly, then cell growth and differentiation after subculture to an ALI may be different, causing differences in expression or function independent of the specifically introduced changes, thus confounding the interpretation. As always, replication of studies is necessary to reduce the likelihood of misinterpretation. 17. Although we have demonstrated functional knockdown of ENaC using the pSLIK inducible system, GFP-reporter gene expression using this system was not uniform in different cell types in well-differentiated ALI hAE cultures and was predominantly found in columnar, non-ciliated, non-basal cells. Variations in expression among cells likely result from different levels of construct integration as well as the potential for cell-type-specific preferential expression or silencing. Evidently, the CMV enhancer promoters in the pSLIK vector are silenced in ciliated cells. At this point, further studies are needed to comprehensively determine vector backbone and promoter elements resulting in uniform expression in well-differentiated ALI hAE cells. Thus, initial experiments with the vector system to be employed, using a reporter gene such as GFP, are strongly recommended to determine whether there is appropriate expression in the differentiated cell types of interest. References 1. Lechner, J. F., Haugen, A., McLendon, I. A., and Pettis, E. W. (1982) Clonal growth of normal adult human bronchial epithelial cells in a serum-free medium. In Vitro 18, 633–642. 2. Fulcher, M. L., Gabriel, S., Burns, K. A., Yankaskas, J. R., and Randell, S. H. (2005) Well-differentiated human airway epithelial cell cultures. Methods Mol Med 107, 183–206. 3. Lechner, J. F., and LaVeck, M. A. (1985) A serum-free method for culturing normal human bronchial epithelial cells at clonal density. J Tiss Cult Methods 9, 43–48. 4. Gray, T. E., Guzman, K., Davis, C. W., Abdullah, L. H., and Nettesheim, P. (1996) Mucociliary differentiation of serially passaged normal human tracheobronchial epithelial cells. Am J Respir Cell Mol Biol 14, 104–112. 5. Gazdar, A. F., and Minna, J. D. (1996) NCI series of cell lines: an historical perspective. J Cell Biochem Suppl 24, 1–11.

6. Boers, J. E., Ambergen, A. W., and Thunnissen, F. B. (1998) Number and proliferation of basal and parabasal cells in normal human airway epithelium. Am J Respir Crit Care Med 157, 2000–2006. 7. Stoner, G. D., Katoh, Y., Foidart, J. M., Myers, G. A., and Harris, C. C. (1980) Identification and culture of human bronchial epithelial cells. Methods Cell Biol 21A, 15–35. 8. Lundberg, A. S., Randell, S. H., Stewart, S. A., Elenbaas, B., Hartwell, K. A., Brooks, M. W., et al. (2002) Immortalization and transformation of primary human airway epithelial cells by gene transfer. Oncogene 21, 4577– 4586. 9. Zabner, J., Karp, P., Seiler, M., Phillips, S. L., Mitchell, C. J., Saavedra, M., et al. (2003) Development of cystic fibrosis and noncystic fibrosis airway cell lines. Am J Physiol 284, L844–L854. 10. Gruenert, D. C., Basbaum, C. B., Welsh, M. J., Li, M., Finkbeiner, W. E., and Nadel, J. A. (1988) Characterization of human tracheal

310

11.

12.

13.

14.

15.

16.

17.

18. 19.

Randell et al. epithelial cells transformed by an origindefective simian virus 40. Proc Natl Acad Sci USA 85, 5951–5955. Masui, T., Lechner, J. F., Yoakum, G. H., Willey, J. C., and Harris, C. C. (1986) Growth and differentiation of normal and transformed human bronchial epithelial cells. J Cell Physiol Suppl 4, 73–81. Ramirez, R. D., Sheridan, S., Girard, L., Sato, M., Kim, Y., Pollack, J., et al. (2004) Immortalization of human bronchial epithelial cells in the absence of viral oncoproteins. Cancer Res 64, 9027–9034. Gruenert, D. C., Willems, M., Cassiman, J. J., and Frizzell, R. A. (2004) Established cell lines used in cystic fibrosis research. J Cyst Fibros 3 Suppl 2, 191–196. Fulcher, M. L., Gabriel, S. E., Olsen, J. C., Tatreau, J. R., Gentzsch, M., Livanos, E., et al. (2009) Novel human bronchial epithelial cell lines for cystic fibrosis research. Am J Physiol Lung Cell Mol Physiol 296, L82–L91. Coyne, C. B., Kelly, M. M., Boucher, R. C., and Johnson, L. G. (2000) Enhanced epithelial gene transfer by modulation of tight junctions with sodium caprate. Am J Respir Cell Mol Biol 23, 602–609. Wu, Q., Lu, Z., Verghese, M. W., and Randell, S. H. (2005) Airway epithelial cell tolerance to Pseudomonas aeruginosa. Respir Res 6, 26. Luo, J., Deng, Z. L., Luo, X., Tang, N., Song, W. X., Chen, J., et al. (2007) A protocol for rapid generation of recombinant adenoviruses using the AdEasy system. Nat Protoc 2, 1236–1247. Cockrell, A. S., and Kafri, T. (2007) Gene delivery by lentivirus vectors. Mol Biotechnol 36, 184–204. Shin, K. J., Wall, E. A., Zavzavadjian, J. R., Santat, L. A., Liu, J., Hwang, J. I., et al. (2006) A single lentiviral vector platform for microRNA-based conditional RNA interference and coordinated transgene

20.

21.

22.

23.

24.

25.

26.

expression. Proc Natl Acad Sci USA 103, 13759–13764. Jones, L. C., Wonsetler, R. L., Olsen, J., Davis, W. C., Randell, S. H., Stutts, M., and O’Neal, W. K. (2008) Short hairpin RNA knockdown in well-differentiated human bronchial epithelial cells: A method for querying gene function relevant to cystic fibrosis. Pediatr Pulmonol Suppl 31, 284. [Abstract]. Randell, S. H., Walstad, L., Schwab, U. E., Grubb, B. R., and Yankaskas, J. R. (2001) Isolation and culture of airway epithelial cells from chronically infected human lungs. In Vitro Cell Dev Biol Anim 37, 480–489. Dull, T., Zufferey, R., Kelly, M., Mandel, R.J., Nguyen, M., Trono, D., et al. (1998) A third-generation lentivirus vector with a conditional packaging system. J Virol 72, 8463– 8471. Johnson, L. G., Mewshaw, J. P., Ni, H., Friedmann, T., Boucher, R. C., and Olsen, J. C. (1998) Effect of host modification and age on airway epithelial gene transfer mediated by a murine leukemia virus-derived vector. J Virol 72, 8861–8872. Salmon, P., Oberholzer, J., Occhiodoro, T., Morel, P., Lou, J., and Trono, D. (2000) Reversible immortalization of human primary cells by lentivector-mediated transfer of specific genes. Mol Ther 2, 404–414. Sanlioglu, S., Williams, C. M., Samavati, L., Butler, N. S., Wang, G., and McCray, P. B., Jr. et al. (2001) Lipopolysaccharide induces Rac1-dependent reactive oxygen species formation and coordinates tumor necrosis factor-alpha secretion through IKK regulation of NF-kappa B. J Biol Chem 276, 30188–30198. Cullen, B. R. (2006) Enhancing and confirming the specificity of RNAi experiments. Nat Methods 3, 677–681.

Chapter 19 Comparative Biology of Cystic Fibrosis Animal Models John T. Fisher, Yulong Zhang, and John F. Engelhardt Abstract Animal models of human diseases are critical for dissecting mechanisms of pathophysiology and developing therapies. In the context of cystic fibrosis (CF), mouse models have been the dominant species by which to study CF disease processes in vivo for the past two decades. Although much has been learned through these CF mouse models, limitations in the ability of this species to recapitulate spontaneous lung disease and several other organ abnormalities seen in CF humans have created a need for additional species on which to study CF. To this end, pig and ferret CF models have been generated by somatic cell nuclear transfer and are currently being characterized. These new larger animal models have phenotypes that appear to closely resemble human CF disease seen in newborns, and efforts to characterize their adult phenotypes are ongoing. This chapter will review current knowledge about comparative lung cell biology and cystic fibrosis transmembrane conductance regulator (CFTR) biology among mice, pigs, and ferrets that has implications for CF disease modeling in these species. We will focus on methods used to compare the biology and function of CFTR between these species and their relevance to phenotypes seen in the animal models. These cross-species comparisons and the development of both the pig and the ferret CF models may help elucidate pathophysiologic mechanisms of CF lung disease and lead to new therapeutic approaches. Key words: Lung biology, tracheal xenograft, CFTR processing, pig, ferret, mouse.

1. Introduction Animal models that reproduce the human cystic fibrosis (CF) disease phenotypes are required to effectively develop methods to treat the disease. These models also serve to increase our understanding of disease pathophysiology, cystic fibrosis transmembrane conductance regulator (CFTR) processing and channel function, testing of therapeutic molecules, and development M.D. Amaral, K. Kunzelmann (eds.), Cystic Fibrosis, Methods in Molecular Biology 742, DOI 10.1007/978-1-61779-120-8_19, © Springer Science+Business Media, LLC 2011

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of gene therapy approaches. It would be ideal if a single model was available that completely modeled the human disease (see Table 19.1); however, species differences are clearly apparent in the three CF models generated to date. As has been the case for CF mouse models, differences in the severity of various aspects of CF organ disease in the pig and ferret models will likely inform new biologic discoveries about CFTR functions in organ physiology and how dysfunction of these processes lead to disease in humans. The purpose of this chapter is to briefly review the general phenotypes of the CF mouse, pig, and ferret models, and to provide methods for comparative analysis of CFTR biology between these models. More detailed reviews of CF mouse models have been reported elsewhere (1–5), and the methods of construction of the CF pig and ferret models have also been previously reported (6, 7) and will not be a focus of the chapter. Comparative differences and similarities among these models will greatly enhance our understanding of the disease and accelerate the development of a cure for CF. It is important to emphasize that differences among species in their ability to model CF (see Table 19.2) will likely help to educate the field on what factors influence phenotypic variability seen in CF patients. 1.1. The Murine Models of CF

Murine models of CF have existed since the early 1990s, contributing invaluably to the current understanding of CF. To our knowledge, at least 14 mouse models of CF exist, including null and mutant forms of CFTR (8–21). The degree to which these models recapitulate various organ pathologies seen in human CF disease varies. Generally, the severity of the phenotypes in each of these models varies slightly based on the levels of CFTR mRNA, as a result of the gene targeting method used and the genetic background of the mouse (1, 4, 5). Briefly, most of the models display one or more of the following phenotypes including severe abnormalities in the gastrointestinal tract, failure to thrive, decreased rates of survival due to intestinal complications, and hyperinflammatory responses in the airway. Furthermore, most of these CF mouse models retain defects in cAMP-inducible chloride permeability in the nasal epithelium as seen in humans. Though not extensively studied in each model, reports have suggested decreased mucociliary clearance (22–24), reduced fertility (25, 26), mild pancreatic dysfunction (27–29), and liver abnormalities (28). However, these models thus far lack the development of significant spontaneous lung disease as observed in humans with CF. Furthermore, gut obstruction phenotypes seen in CF mice at weaning are clinically different from meconium ileus seen in newborn CF infants and suggest some level of biologic differences in the developmental control of chloride movement in the gut by CFTR between mice and humans.

1480

1476

1482

1484

∼80 kg

∼25 g

∼90 kg

∼2–3 kg

Human

Mouse

Pig

Ferret

91

92

78

100

a Protein sequence identity compared to the human CFTR sequence

AA, amino acid; SMG, submucosal gland

CFTR AA No.

Avg. mass

Species

CFTR identitya (%)

Table 19.1 General species characteristics of CFTR

42

114

21

280

Days of gestation

8

10

6

1

Avg. litter size

4–6 months

6–8 months

6–8 weeks

10–16 years

Sexual maturation

8–10

10–15

2

∼78

Abundant

Abundant

Rare

Abundant

Avg. life expectancy (years) SMG abundance

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None

Adult: severe (40)

Newborn: frequent (39) Adult: severe (unpublished)

Mouse

Pig

Ferret

Birth: 100% ADD 0% EPD (39)

Birth: 100% EPD (38, 64)

Birth: none Adult: mild ADDa (4, 61)

Birth: ∼72–90% ADD ∼3% EPD Adult: ∼83% EPD (41, 42, 50)

Exocrine pancreas

Birth: 75% MI 100% MA (39)

Birth: 100% ELFTs (39)

Birth: 20% FBC (38, 64)

Birth: normal Adult: mild FBCa (4,61, 63)

Birth: OB at weaninga Adult: MAa (4,61, 62) Birth: 100% MI (38, 64)

Birth: ∼50% ELFTs Adult: ∼10–20% FBC (56, 57)

Liver

Birth: ∼10–15% MI ∼80% MA Adult: MA, OB (51–55)

Gastrointestinal

Birth: normal (39)

Birth: 100% (38, 64)

Birth: normal

Birth: ∼23% (52, 58)

Micro-gallbladder

CBAVD: present at birth (39)

CBAVD: variable at birth (40, 40a)

Reduced female fertilitya (26)

Male infertility: ∼95% CBAVD (59, 60)

Fertility

MI, meconium ileus; TBD, to be determined; ADD, mild lesions associated with exocrine acinar duct dilatation; EPD, severe lesions associated with exocrine pancreas destruction; ELFTs, elevated liver function tests; FBC, focal biliary cirrhosis; MA, malabsorption; OB, intestinal obstruction; CBAVD, congenital bilateral absence of vas deferens a Observed only on certain background strains and/or CFTR genotypes

Birth: infrequent Adult: severe (49)

Spontaneous lung infections

Human

Species

Table 19.2 Cystic fibrosis phenotype across species

314 Fisher, Zhang, and Engelhardt

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Although the nasal bioelectric defects seen in the CF mouse models appear to closely resemble those in the human nasal epithelium (5), the bioelectric characteristics in the tracheal airways of mice and humans diverge significantly with murine models demonstrating cAMP-inducible changes in chloride permeability despite the absence of CFTR (30, 31). Potential explanations for this observation include differences in airway cell biology (i.e., different types of secretory cells are found in the proximal airway of humans [goblet cells] and mice [Clara cells]), differences in the distribution of submucosal glands (i.e., throughout the cartilaginous airways in humans and located only to the proximal regions of the trachea in mice), and the presence of alternative non-CFTR chloride channels in mice capable of activation in response to cAMP that are not found in humans (5, 30). Much effort has been placed to develop methods capable of studying bacterial clearance defects in CF mouse lung (2, 4, 32, 33). Many groups with variable success have attempted inoculation of these CF mouse models with bacteria, mainly Pseudomonas aeruginosa, to reproduce the human lung disease phenotype. A variety of inoculation methods have been attempted from aerosolization of free bacteria to insertion of bacteria-laden agar beads. Some studies report decreased survival of the CF mice compared to their littermates, while others indicate no difference in clearance between genotypes (2, 4). However, some groups have reproducibly observed excessive inflammatory response and higher mortality to inoculation of the CF mouse lung with bacteria-laden agar beads, despite no differences in bacterial clearance (32, 33). Another interesting model recently reported by Hodges and colleagues (21, 34) is the development of a conditional CFTR knockout mouse model. This model is being used to direct tissue-specific deletion of CFTR following crossing with transgenic mice that directs Cre recombinase expression under tissuespecific promoters. This system will allow for a systematic and directed evaluation of CFTR function at the level of individual organs. 1.2. New Methods for Generating Larger Animal Models of CF Disease

Given the observed phenotype in CF mouse models, it is clear that additional larger animal models of CF would be of utility to the field. Several parameters influence the choice of alternative species to model CF including (1) the types of cells in the airway in comparison to human (2), the distribution of submucosal glands which are thought to play an important role in CF airway disease (3), conservation of CFTR structure and function (4), the composite of alternative chloride channels in the airway, and (5) the reproductive parameters of the species which will make it feasible to rapidly perform research studies. Generation of larger CF

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animal models such as pig (35), ferret (36), and sheep (37) has been considered, but the technology to manipulate the genomes of these animals has lagged behind until recently. Recently, methods for generating both pig and ferret CF models have been developed using recombinant adeno-associated virus (rAAV)mediated gene targeting of exon 10 (6, 7). The phenotypes of newborn CFTR knockout pigs and ferrets have also recently been described (38, 39) and will be discussed in more detail below. 1.2.1. The Porcine Models of CF

Generation of the CFTR–/– and F508 alleles was accomplished by rAAV gene targeting of male porcine fetal fibroblasts (7). The targeted nuclei were subsequently used for somatic cell nuclear transfer, and CFTR+/– male piglets were born and bred to homozygosity. Due to the lack of reports on the heterozygous F508 piglets, this section will focus mostly on the CFTR–/– piglets. Rogers et al. (38) recently reported a detailed description of the newborn CFTR–/– piglet phenotype. In summary, these pigs were born with near-Mendelian ratios of 1:2:1 with no differences in the newborn birth weight or in appearance between genotypes. CFTR-deficient piglets lacked CFTR mRNA and therefore expressed no protein. Nasal transepithelial potential difference (TEPD) displayed a lack of cAMP-inducible chloride permeability and an elevated baseline TEPD in the CFTR–/– piglets similar to that seen in CF humans and mice lacking functional CFTR. All of the CFTR-deficient piglets developed meconium ileus (MI) and atretic microcolon distal to the obstruction, resulting in failure to pass stool and gain weight after birth. If untreated by surgery, the MI was lethal in 100% of the CFTR–/– animals. To live beyond the first few days after birth, all animals required an ileostomy bypassing the obstruction. Rogers et al. also reported adipose infiltration of the pancreas and complete exocrine pancreatic insufficiency (or destruction) at birth in all CFTR–/– animals. These CFTR-deficient piglets also presented with focal biliary cirrhosis and developed a mucus- and bile-filled micro-gallbladder. No overt abnormalities were seen in the lungs, airways, submucosal glands, male reproductive tract, and other non-CF-related organs. Encouraging to the CF field was the recent report that aged (>2 months) CFTR–/– and CFTR–/F508 piglets developed a CF-like lung phenotype (40). We anticipate future reports describing the lung phenotype of F508/F508 homozygous pigs.

1.2.2. The Ferret Model of CF

The generation of CFTR null ferrets was described in detail by Sun et al. (6). rAAV was used to introduce a stop codon and a neomycin cassette into exon 10 of the CFTR gene in primary ferret fibroblasts. Infected fibroblasts were cloned and selected by serial dilution into G418 followed by PCR screening for the targeting events. Due to early senescence of gene-targeted primary

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ferret fibroblasts (not an issue with the generation of the CF pig models), it was necessary to rejuvenate gene-targeted fibroblast clones by somatic cell nuclear transfer. Primary fibroblasts were then expanded from 21-day fetuses and used for a second round of somatic cell nuclear transfer. Using this process, eight CFTR+/– male ferret founders were obtained and expanded to generate CFTR+/– breeder pairs. Similar to the CF piglets, there was no prenatal lethality associated with CFTR deficiency in ferret kits. Newborn CFTRdeficient newborn ferrets (kits) failed to thrive compared to their wild-type and heterozygous littermates. Approximately 75% of the CFTR-deficient kits failed to pass meconium due to MI and died within the first 36–48 h of life due to intestinal perforation and sepsis (39). Interestingly, this variable penetrance of MI seen in the CF kits is significantly different than the CF porcine model in which 100% of piglets presented with MI (see Table 19.2). Interestingly, the CFTR-deficient kits that passed stool (∼25%) also failed to thrive and died within the first week of life, despite the fact that their intestinal tract was grossly and microscopically normal. The reason for death of these animals appeared to be due to malabsorption, demonstrating a histologic depletion of fat stores and progressive decline in blood cholesterol with age that was not corrected by pancreatic enzyme replacement. CFTRdeficient kits histologically demonstrated mild pancreatic disease at birth, presenting with exocrine acinar ducts that were swollen with inspissated secretions. Such findings are more similar to the human CF pancreatic phenotype at birth (41, 42) and contrasted with the CF pig model in which nearly complete exocrine pancreatic destruction was reported (38). CF kits also demonstrated early signs of functional liver disease (as evident by elevated liver function tests) despite liver histology not overtly different from controls. Unlike the CF pig model, CF newborn ferrets had a histologically normal gallbladder and the majority of kits that escaped MI presented with bronchopulmonary pneumonia at the time of death. It is currently unclear if the bronchopulmonary pneumonia seen in nutritionally compromised CF kits was secondary to their compromised health status and the inability to clear aspirated material from the lung. Based on the clinical blood chemistries seen in CFTR-deficient kits, drug and nutritional therapy to enhance fat absorption by the intestine was undertaken and significantly improved weight gain and survival (39). This treatment involved oral gavages with ursodeoxycholic acid (to treat apparent liver disease indicated by elevated liver enzymes in the blood), omeprazole (to raise gastrointestinal track pH), and elemental diet. This treatment regime improved liver function tests and raised serum cholesterol. Despite improved weight gain using these treatments, CF kits still often developed lung infections within the first four weeks of life that where characterized

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predominantly by steptococcus and staphylococcus infections. Rearing animals on antibiotics has also been used to enhance survival during the preweaning period. Although the adult CF ferret lung phenotype remains under investigation, a slow progressive and fatal lung disease has been shown to occur in this model (unpublished data). The finding that CFTR-deficient ferrets are susceptible to lung infections both early and late in life is encouraging. 1.3. Future Directions for Larger CF Animal Models

The creation of ferret and pig CF models will undoubtedly enhance CF research for decades to come. Comparative aspects of disease between CF mouse, ferret, and pig models should enlighten mechanisms of CFTR function and CF pathophysiology responsible for diverse disease phenotypes seen in CF patients. Despite the promise that comes with the new CF ferret and pig models, there remain significant barriers to their widespread use in research. Foremost among these barriers are the severe intestinal phenotypes at birth in both models. In the CF pig, the requirement for surgery to treat MI will significantly impair the use of this model for the average researcher. Similarly, since 75% of CF ferrets also present with a lethal MI phenotype at birth, the cost of implementing this model will be quite high until this problem can be solved. Two approaches are currently under investigation to reduce the severity of MI in these models. In the context of the ferret, the variable penetrance of MI suggests that there may be heritable influences on the severity of early intestinal disease in this model. To this end, the CF ferret model is being bred into different genetic lines in an effort to determine if a colony of CF ferrets with reduced penetrance of MI can be generated. Second, gut-corrected transgenic CFTR–/– ferrets that express ferret CFTR under the rat fatty acid-binding protein (FABP) promoter have been generated and shown to correct MI in newborn CF kits (39). This has proven feasibility that a transgenic complementation approach combined with somatic cell nuclear transfer can further improve both the CF ferret and pig models. This approach has been used successfully in CF mouse models to prevent intestinal obstruction at weaning (12). Future development of the gut-corrected CF ferret model will require regenerating the model on a heterozygous background for breeding expansion. A second intriguing aspect of future ferret and pig models of CF pertains to the ability of a particular species to model certain mutations of CFTR. As discussed in more detail below, analysis of pig F508-CFTR demonstrates that this protein is partially processed to the apical membrane of airway epithelia where it retains some level of function (43, 44). These findings suggest that the pig may not be the best model on which to study the F508CFTR mutation. It is currently unclear if ferret F508-CFTR will retain similar processing defects as seen with the human

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319

mutant protein and a conclusive answer to this question in a ferret F508-CFTR model is in progress (45). Three methods useful in evaluating CF animal models will be discussed in this chapter. The first area will review methods for evaluating TEPD in tracheal xenografts. The second area will review antibodies that are suitable for studying alternative species of CFTR. The last area will review methods for studying species-specific processing of CFTR by metabolic pulse-chase labeling. We will use ferret as a model for most of the methods discussed, since other species have already been published elsewhere. 1.4. Cross-Species Analysis of Tracheal TEPD in a Tracheal Xenograft Model

Analysis of the bioelectric properties of cAMP-inducible chloride channels in the airway is critical to characterizing the ability of a particular species to model CF. TEPD measurements are an effective method to study chloride channel defects and have been extensively used in human and mouse models to study CF. Typically, this assay has been performed on the nasal epithelium since it is readily accessible in a live host. However, given the fact that the CF mouse retains nasal but not tracheal chloride transport defects seen in CF humans, methods to directly assess the bioelectric properties of the trachea in CF animal models are needed. Tracheal TEPD measurements can be obtained ex vivo in a tracheal xenograft model. Freshly excised tracheas cannulated with flexible plastic tubing and inserted subcutaneously in athymic Nu/Nu mice have allowed analysis of tracheal bioelectric properties in a vascularized airway free from infection. This system has been extremely useful in characterizing TEPD in these models due to the early intestinal complications in the newborn ferret and pig CF models. Perfusion of pharmacological ion channel agonists and antagonists allows for a systematic measurement of the bioelectric properties in these new models. This chapter will focus on the protocol for making tracheal TEPD measurements using this ex vivo system. Xenograft cassette design, implantation of xenografts, and maintenance of the xenografts will not be discussed in detail because these general methods have been detailed in an earlier edition of this book (46).

1.5. Cross-Species Analysis of CFTR Processing

As new CF models are developed with specific CFTR mutations, a clear understanding of comparative CFTR biology is paramount. Topics relevant to modeling CFTR mutations in a new species include how closely each of the following resembles that of the human mutant CFTR : (1) the efficiency of folding, (2) the efficiency of detection by endoplasmic reticulum associated protein degradation (ERAD), (3) the stability at the plasma membrane, and (4) the activity of the channel at plasma membrane. Reports have already shown that F508-CFTR processing differences exist among mice, pigs, and humans (43, 44, 47). CFTR is

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composed of five structural domains, including two membranespanning domains, two nucleotide-binding domains, and a regulatory domain. With the exception of the regulatory domain, the other two domains are highly conserved between most model species and humans, more so in pigs and ferrets than in mice. Differences in the primary protein structure among species may dictate the ability of these species to correctly model the CF disease seen in humans. The mouse, pig, and ferret CFTRs are 77, 92, and 91 identical to the human CFTR, respectively (Table 19.1). The identification of species-specific differences in CFTR processing may also help to inform new approaches to enhance processing of human mutant CFTR, by identifying molecular targets responsible for variation among species (i.e., differences in chaperone interactions). This section will focus on CFTR antibody optimization across species and comparative metabolic pulse-chase experiments.

2. Materials 2.1. TEPD Measurements in a Tracheal Xenograft Model

1. Tracheal xenograft at least 4 weeks post-transplantation (see Note 1). 2. Ketamine (100 mg/kg) and xylazine (20 mg/kg) in PBS. 3. Multi-range, variable-rate infusion pump (Orion Research, Cat. no. 001967). 4. pH/mV meter (Fisher Scientific, Cat. no. 13-636-AB15P). 5. Calomel reference electrodes (Fisher Scientific, Cat. no. 13-620-51). 6. 21-Gauge × 0.75-in. butterfly infusion set (Abbott Laboratories, Cat. no. 4492). 7. Computer with data acquisition software (CyberComm Pro 2.3; Fisher Scientific) for recording PD in millivolts. 8. 10-mL Disposable syringes with 21-gauge × 1.5-in. needles. 9. Manifold pump tubing (PVC Solvent Flexible tubing; Fisher, Cat. no. 14-190-139). 10. Silicone tubing (Bio-Rad Laboratories, Cat. no. 7318211). 11. Agar Nobel (Difco Laboratories, Detroit, MI, Cat. no. 0142-01). 12. 1 M KCl. 13. Hemostat. 14. HEPES phosphate-buffered Ringer’s (HPBR) solution: 10 mM HEPES (pH 7.4), 140 mM NaCl, 5 mM KCl,

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1.2 mM MgSO4 , 1.2 mM Ca gluconate, 2.4 mM K2 HPO4 , and 0.4 mM KH2 PO4 . 15. Chloride-free HPBR solution: 10 mM HEPES (pH 7.4), 140 mM Na gluconate, 5 mM K gluconate, 1.2 mM MgSO4 , 1.2 mM Ca gluconate, 2.4 mM K2 HPO4 , and 0.4 mM KH2 PO4 . 16. Ham’s F12 medium. 17. PD buffer sequence: a. HPBR solution, 100 μM 4,4 -diisothiocyanatostilbene2,2 -disulfonic acid (DIDS). b. HPBR solution, 100 μM DIDS, 100 μM amiloride. c. Chloride-free HPBR solution, 100 μM DIDS, 100 μM amiloride. d. Chloride-free HPBR solution, 100 μM DIDS, 100 μM amiloride, 200 μM 8-cpt-cAMP. e. Chloride-free HPBR solution, 100 μM DIDS, 100 μM amiloride, 200 μM 8-cpt-cAMP, 50 μM CFTRINH GlyH-101. 2.2. Cross-Species Analysis of CFTR Processing Requires Antibodies that Efficiently Bind Across Species

1. Immunoprecipitation. 2. In vitro phosphorylation: a. PKA phosphorylation buffer (per sample): 50 mM KH2 PO4 (pH 6.8), 2 μg BSA, 2 μg protein kinase A (PKA; Calbiochem, La Jolla, CA) diluted to 20 μL using ddH2 O. b. ATP phosphorylation buffer (per sample): 50 mM KH2 PO4 (pH 6.8), 4 μg BSA, 10 mM MgCl2 , and 3.6 μCi (6000 Ci/mmol) [γ–32 P]-ATP (Perkin Elmer, Waltham, MA) diluted to 40 μL using ddH2 O. c. Thermal-controlled shaker.

2.3. Cross-Species Analysis of the Processing Efficiency and Stability of CFTR by [35 S]Methionine Pulse Chase

1. Starvation media, DMEM lacking methionine and cysteine (Invitrogen, Cat. no. 21013024). 2. [35 S]Methionine and [35 S]cysteine EasyTag Express 35 S protein labeling mix (Perkin Elmer, Cat. no. NEG772007MC). 3. Activated charcoal-loaded syringe. 4. Chase media, DMEM containing 10% FBS, 1% penicillin and streptomycin, and 2 mM cold methionine and cysteine. 5. Ice-cold PBS. 6. RIPA buffer (150 mM NaCl, 20 mM Tris–HCl, 1% Triton X-100, 0.1% SDS, 0.5% deoxycholate, pH 8.0) containing protease inhibitors (Roche, Cat. no. 34342). 7. Refrigerated tabletop centrifuge.

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8. 1.5- and 2.0-mL Eppendorf tubes. 9. Anti-CFTR antibodies M3A7 and MM13-4 (Millipore, Cat. nos. 05-581 and 05-533, respectively) and anti-HA high-affinity antibody (Roche, Cat. no. 11867431001). R and separation magnet (Invitro10. Protein G DynaBeads gen, Cat. nos. 100.04D and 123.21D).

11. 7.5% SDS-PAGE gels. 12. Gel fixative solution (10% glacial acetic acid, 25% isopropanol, and 65% ddH2 O). 13. Amplify fluorographic reagent (GE Healthcare, Cat. no. NAMP100). 14. Gel dryer. 15. Phosphoscreen, phosphoimager, and image analysis software (ex. ImageJ. or ImageQuant).

3. Methods 3.1. TEPD Measurements in a Tracheal Xenograft Model

Newborn tracheas from CF and non-CF pigs and ferrets are obtained at birth sterilely and connected to flexible tubing through a series of adapters and stents to keep the trachea extended to normal length. These cassettes are then implanted subcutaneously into the flanks of athymic Nu/Nu mice (a host that will not reject the tissue). A schematic view of this ex vivo tracheal xenograft model is shown in Fig. 19.1. Importantly, these grafts become vascularized by 2–3 weeks and have ports that allow for lumenal access for TEPD measurements. Details on the methods for generating these cassettes and for the surgical implantation are described elsewhere (46). TEPD measurements of the xenografted tracheal airways can be used to assess changes in the permeability to various ions in response to antagonists and agonists of epithelial ion channels such as the epithelial sodium channel (ENaC) and CFTR. 1. After 4–5 weeks post-transplantation, the xenografts are fully differentiated and ready for TEPD analysis using the equipment shown in Fig. 19.2. The xenograft-bearing mouse (typically with two xenografts) is anesthetized by intraperitoneal injection of ketamine (100 mg/kg) and xylazine (20 mg/kg) in PBS. Once anesthetized, the mouse is placed on a sterile drape and the chrome wire caps from the xenograft exit ports are removed using sterile forceps. 2. The xenograft is gently flushed with 1 mL of Ham’s F12 medium using a 1-mL syringe and a butterfly needle.

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Fig. 19.1. Tracheal xenograft design and transplantation. (a) The cassette is composed of flexible plastic tubing, freshly excised newborn pig or ferret trachea, and chrome wire plugs (see Note 1). The trachea is fastened to the tubing using silk sutures. (b) The xenograft cassettes are inserted subcutaneously into the flanks of Nu/Nu athymic mice. The xenografts vascularize within 2–3 weeks and continue to mature and develop until ready for bioelectric characterization by measuring PD (4–5 weeks). PD recordings are made weekly until 8–9 weeks post-transplantation. Usually a CFTR–/– xenograft is transplanted in parallel to either a CFTR+/– or a CFTR+/+ xenograft.

Fig. 19.2. Potential difference instrumentation and setup. Measuring TEPD in this ex vivo model requires the following equipment: computer with data acquisition software, pH/mV meter, calomel electrodes, and syringe pump. The pH/mV is connected to the calomel electrodes that are connected to the anesthetized mouse by means of butterfly electrodes (see Note 2). The positive electrode is inserted into the perfusion tubing (black arrows) allowing access to the luminal surface of the trachea, while the negative electrode is inserted subcutaneously (white arrows).

3. The Ham’s F12 medium is removed by flushing the xenograft with air. This is done by removing the syringe from the butterfly needle, refilling it with air, returning the syringe to the butterfly needle, and gently forcing the air through the xenograft. 4. The syringe is removed and the butterfly needle is left on the distal port as a drain for the perfused TEPD buffer solutions.

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5. 10-mL syringes are filled with TEPD buffers and fitted on the syringe pump. A length of manifold pump tubing, which is to be placed on the needle of the first syringe, is first fitted onto the medial port of the xenograft by means of a shortened pipette tip (20–200 μL). 6. Calomel electrodes, immersed in 1 M KCl, are connected to the pH/mV meter and to the butterfly electrodes. 7. Butterfly electrodes are prepared by filling 21-gauge butterfly tubing with 5% noble agar in 1 M KCl (see Note 2). The positive butterfly electrode is inserted into the perfusion tubing just external to the xenograft port. This is done by directly inserting the 21-gauge needle through the tubing. The negative electrode is inserted subcutaneously in the back of the mouse. 8. Millivolt recordings are obtained from the pH/mV meter and data linked directly to a computer, equipped with data acquisition software. Measurements are taken every second. Example TEPD recordings and histological sections for ferret CFTR–/– and CFTR+/+ xenografts are depicted in Fig. 19.3. 9. Typically, the xenograft is sequentially perfused with 2 mL of each of the TEPD buffers through the syringe pump at a flow rate of 200 μL/min (10 min, see Notes 3 and 4). 10. After recording is complete, the xenograft is gently flushed with 1 mL of Ham’s F-12 medium using a butterfly needle and a 1-mL syringe. The syringe is then disconnected from the xenograft. The syringe is refilled with air by gently forcing air through the xenograft, restoring an air–liquid interface. The chrome wire inserts are replaced into the tubing ports. 11. Steps 1–10 are repeated (optional) on the xenograft on the other side of the animal if two xenografts are implanted. 12. Xenografts can be routinely measured up to two times per week and are typically irrigated with F12 media, followed by air, the day before each measurement to remove excess mucous. 3.2. Cross-Species Analysis of CFTR Processing Requires Antibodies that Efficiently Bind to Conserved Epitopes Between Species

When comparing biologic properties among different species of CFTR, it is imperative that the antibodies used react similarly across the species. This can be achieved by screening available antibodies against each species of CFTR to be compared and/or adding a common epitope tag such as HA to the fourth extracellular loop (which has not been shown to affect CFTR function). Summarized in Table 19.3 are results of an antibody screen for comparative studies between human and ferret CFTRs using Western blotting and immunoprecipitation. This section

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Fig. 19.3. TEPD analysis of ferret CF and non-CF tracheal xenografts. (a) Representative TEPD tracings of newborn ferret CFTR+/+ (dark line) and CFTR–/– (light line) tracheal xenografts. The buffer conditions change with ion channel agonists and antagonists are indicated above the tracing. (b) Reproducibility of sequential TEPD measurements taken in the same ferret CFTR+/+ and CFTR–/– xenografts at week intervals as indicated. Buffer conditions were the same as shown in (a) with the buffer number marked arrowheads. (c) Histological H&E sections of ferret CFTR+/+ (top) and CFTR–/– (bottom) xenografts. Note the intact pseudostratified ciliated epithelium (empty arrows) and the presence of submucosal glands (solid arrows) in both genotypes.

will focus on our methods of immunoprecipitation of CFTR using R and the subsequent detection by phosphorylation of DynaBeads CFTR with protein kinase A (PKA) and [γ–32 P]ATP as previously described with modifications (43, 48). A brief description of our Western blot protocol is contained in Note 5. 1. Immunoprecipitation a. Total protein (1 mg), from cell lysate derived from cells transiently transfected with human or ferret CFTR or EGFP expression plasmid (see Note 6), is aliquoted to a 2-mL Eppendorf tube and diluted to 1 mL using RIPA buffer containing freshly added protease inhibitors. Tween 20 is then added to a final concentration of 0.1%.

R&D Systems

CFC

Santa Cruz

24–1

Mr. Pink

H-182

N-Term

NBD1

C-Term

R Domain

Pre-NBD1

NBD1

NBD1

R Domain

NBD2

NBD1

R Domain

C-Term

N-Term

CFTR region

1:200

1:500

1:1000

1:1000

1:1000

1:500

1:1000

1:1000

1:1000

1:500

1:1000

1:1000

1:1000

WB dilution

+

+

+

+

++

++

++

+++

+++

+++

+++

+++

+++

WB human

+

+

+

+

++

–

++

+++

+++

+++

++

++

+++

WB ferret

+++

2 μg/mL

ND ND

7.5 μL ND

ND

ND ND

ND

ND +++

2 μg/mL

++

10 μg/mL ND

ND

ND

ND

ND

ND

ND

ND

+++

2 μg/mL ND

IP human

IP dilution

ND

ND

ND

ND

+++

ND

++

ND

ND

ND

ND

+++

+++

IP ferret

WB, Western blot; IP, immunoprecipitation; CFFT, cystic fibrosis foundation therapeutics; CFC, CFTR folding consortium; ND, not determined; –, no interaction; +, weak binding; ++, moderate binding; +++, strong binding. All WB and IPs came from a large pool of cell lysate derived from HT1080 cells expressing either human or ferret CFTR

R&D Systems

13–1

CFC

3G11

CFC

CFFT

570

Millipore

CFFT

596

L12B4

CFFT

660

10B6.2

Millipore

CFFT

MM13-4

Millipore

M3A7

217

Source

Name

Table 19.3 Human and ferret CFTR antibody optimization

326 Fisher, Zhang, and Engelhardt

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b. Primary antibody is incubated with the dilution specified in Table 19.3 for at least 2 h at 4◦ C with rotation. R (50 μL) is added to the Washed protein G DynaBeads solution and the mixture is incubated overnight at 4◦ C (see Notes 7 and 8). c. The beads are washed three times with PBS containing 0.1% Tween 20, placing the tube on a magnet between each wash to remove the supernatant. 2. In vitro phosphorylation of CFTR: a. Prepare PKA and ATP phosphorylation buffers. b. The beads from the finished IP protocol are washed once with PBS and the supernatant is removed by placing the tube on the magnet. c. The beads are resuspended in 20 μL of the PKA phosphorylation buffer. d. Add 40 μL of the ATP phosphorylation buffer and shake for 30 min at 30◦ C (see Note 9). e. The beads are washed four times with PBS containing 0.1% Tween 20. f. Beads, antibody, and CFTR are dissociated by adding 2× SDS-PAGE loading buffer, incubating at 37◦ C with continual shaking. g. Place the tube in the magnet and load the supernatant on a 7.5% SDS-PAGE gel. h. Resolve by electrophoresis (see Note 10). i. Fix the gel by transferring the gel to a disposable plastic container filled with fixative solution (10% glacial acidic acid, 25% isopropanol, and 65% ddH2 O) and gently agitate for 30 min. j. Dry the gel by transferring to a piece of filter paper, cover with plastic wrap, and dry on a vacuum gel drier at 80◦ C for 45 min. k. Expose to a pre-cleared phosphoscreen and scan several days later using a phosphoimager. 3.3. Cross-Species Analysis of the Processing Efficiency and Stability of CFTR by [35 S]Methionine and Cysteine Pulse Chase

The glycosylation characteristics of CFTR serve as an excellent endpoint for assessing the processing CFTR. The immature form of CFTR resides in the endoplasmic reticulum (ER) and is called band B (∼150 kDa), while the fully glycosylated mature protein resides at the plasma membrane and is called band C (∼170– 180 kDa). Note that the migratory apparent molecular weight of CFTR can vary slightly across species and may be due to slightly altered glycosylation. Metabolic pulse-chase experiments using radioactive amino acids, [35 S]methionine and [35 S]cysteine,

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Fig. 19.4. Metabolic [35 S]methionine pulse chase of ferret CFTR processing. (a) HT1080 cells transiently expressing ferret CFTR were starved of methionine and cysteine (30 min), labeled with [35 S]methionine and [35 S]cysteine (15 min), and chased with media containing cold methionine and cysteine for the given time points as described under Section 3.3. (b) Densitometric quantification of (a) Empty points representing band BT /band B0 × 100. Solid data points representing band CT /band B0 × 100 (see Note 13).

serve as an excellent method to characterize the rate, stability, and efficiency of processing from band B to C of wild-type and mutant CFTRs across species. An example of a metabolic pulsechase autoradiograph and quantification thereof for ferret wildtype CFTR is shown in Fig. 19.4. 1. Depletion of intracellular pools of methionine and cysteine: Gently wash the cells expressing CFTR two times with warm starvation media. Incubate the cells at 37◦ C for 30 min in starvation media (2 mL). 2. Metabolic labeling of CFTR: Gently aspirate the starvation media. Transfer cells to an area designated for the use of radioactive materials (see Note 9). Add 2 mL of starvation media containing 0.2 mCi/mL of [35 S]methionine and cysteine. Incubate at 37◦ C for 15 min. 3. Metabolic chase of labeled CFTR: Aspirate the labeling media and place the cells on ice. Wash three times in cold PBS. Add warm chase media (4 mL) and incubate at 37◦ C for the desired amounts of time (see Note 11). 4. Harvesting the cells: Place cells on ice and remove the chase media by aspiration. Proceed to gently wash the cells three times with ice-cold PBS (1 mL). Lyse the cells on ice in 1 mL of RIPA buffer containing protease inhibitors for 5–30 min. Transfer the lysate to a 1.5-mL Eppendorf tubes and spin at 16,000×g for 10 min at 4◦ C (see Note 12). Freeze the samples until last chase time point has been harvested.

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5. Immunoprecipitation of labeled CFTR: Thaw lysate and add Tween 20 to a final concentration of 0.1%. Then add 2 μg of anti-CFTR antibodies M3A7, L12B4, and MM13-4 and rotate for 3–5 h at 4◦ C. Wash 50 μL (30 μg/mL) of R with PBS containing 0.1% Tween 20, pelletDynaBeads ing between each wash. Resuspend the beads in the original volume and add to the antibody/antigen containing lysate. Rotate at 4◦ C overnight. Wash the lysate with PBS (0.1% Tween 20) six times. Dissociate the protein and antibody by adding 2× SDS loading buffer (30 μL) and shake at 37◦ C for 30 min. 6. Electrophoresis and autoradiography: Load the lysate on 7.5% SDS-PAGE gels and electrophorese overnight (30 V). Fix the gel for 30 min by gently shaking at room temperature in the fixative solution. Replace the fixative solution with Amplify and incubate for 30 min at room temperature with gentle shaking. Dry the gel using a gel dryer and expose to a phosphoscreen for several days. Develop/scan the phosphoscreen using a phosphoimager and imaging software. 7. Densitometric analysis: Quantify the total CFTR signal for bands B and C for each of the experimental time points (see Note 13).

4. Notes 1. Freshly isolated trachea from newborn ferret or pig is cannulated to the previously described xenograft cassette (46). In brief, the cassette consists of a combination of silastic (Dow Corning, Midland, MI) and Teflon (Thomas Scientific, Swedesboro, NJ) tubing attached to barb-to-barb connectors (Bio-Rad Laboratories, Hercules, CA). The trachea is ligated to the connectors and the tubing ports capped with chromel A steel wire (Hoskins MFG, Novi, MI). These cassettes are inserted subcutaneously into the flanks of male Nu/Nu athymic mice. 2. Butterfly electrodes are made by dissolving the agar noble (5%) in 1 M KCl by heating. The butterfly needle/tubing is filled with this hot solution by negative pressure generated by a 30-mL syringe. These electrodes are submerged in 1 M KCl in a 100-mm dish for up to 1 year at 4◦ C. 3. To accurately calculate changes in potential difference between buffers, it is important to wait for a stable millivolt reading before switching to the next buffer. This usually occurs within 10 min but depends upon the xenograft.

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4. It is critical that the fluid-filled tubing and the xenograft are devoid of any air bubbles. The manifold tubing is therefore clamped with a hemostat when changing buffers. The hemostat is removed once the tubing is attached to the next buffer. Failure to keep air from the system will result in moments of infinite TEPD spikes as the air moving through the xenograft disrupts the electrical conductivity. 5. Equal amounts of protein from cellular lysate from cells expressing human or ferret CFTR (see Note 6) were resolved electrophoretically on 6% SDS-PAGE gels. The protein was transferred to nitrocellulose membranes and the membrane blocked in PBS containing 0.1% casein and 0.2% Tween 20. CFTR primary antibodies were then added at the dilution indicated in Table 19.3 and incubated for 1 h at room temperature. The blots were washed, probed with secondary antibodies conjugated to an IR dye, and imaged using an Odyssey IR scanner. 6. Transient expression of human and ferret CFTRs in HT1080 cells was achieved by electroporation using the BTX-830/630B system (Harvard Apparatus, Holliston, MA). The following electroporation conditions were used for HT1080 (4 pulses, 230 mV, 1 ms interval) and BHK21 (1 pulse, 260 mV, 1 ms interval) cell lines. R 7. Incubation of the antigen/antibody and the DynaBeads for 2 h at room temperature is also sufficient. It is also critR be maintained in a 0.01–0.1% ical that the DynaBeads Tween 20 solution to avoid bead clumping.

8. Alternatively, one can prebind the CFTR antibodies and R by incubating with rotation for 30 min at the DynaBeads room temperature. The unbound antibody is then washed R can be directly away and the antibody-bound DynaBeads added to the cell lysate and rotated for 2 h at room temperature. 9. From this step forward, everything must be carried out in the radiation room according to manufacturer’s guidelines. Everything must be discarded appropriately and appropriate personal protective equipment used. 10. To achieve adequate separation between bands B and C on a 7.5% mini gel, we run the ladder off to 100 kDa. This is done by running the gel at 120 V for ∼3 h or 30 V overnight. 11. It is recommended that several time points from 0 to 12 h be included to adequately study the rate of disappearance of band B and appearance and disappearance of band C. It may be helpful to also include time points up to 48 h to ascertain differences in protein stability.

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12. To avoid non-specific pull down of other labeled proteins, keep the lysis time less than 30 min and spin the lysate at 4◦ C. This avoids protein degradation and lysis of nuclei in the sample. 13. Quantify the lane background using two regions for each lane (below band B and above band C). Subtract the lane background from the regions representing bands B and C. To analyze the disappearance of band B, measure the percentage of band B over time divided by the initial amount of band B (band BT /band B0 ). To analyze the appearance/disappearance of the higher molecular weight, fully processed band C, it is important to measure the intensity of band C over time divided by the initial band B labeling intensity (band CT /band B0 ). Due to background issues throughout the lane at time 0 of the chase (likely due to undegraded fragments of CFTR generated during the labeling process), band C0 is set to 0.

Acknowledgments This work was supported by grants from the NHLBI (RC1HL099516), NIDDK (P30DK054759, R37DK047967), NHLBI (HL091842) and the Cystic Fibrosis Foundation (ENGELH08XX0), as well as by the Roy J. Carver Chair in molecular medicine. We also gratefully acknowledge Drs Christine Blaumueller and Monali Sawai for editorial contributions. References 1. Davidson, D. J., and Dorin, J. R. (2001) The CF mouse: an important tool for studying cystic fibrosis. Expert Rev Mol Med 3, 1–27. 2. Davidson, D. J., and Rolfe, M. (2001) Mouse models of cystic fibrosis. Trends Genet 17, S29–S37. 3. Dickinson, P., Dorin, J. R., and Porteous, D. J. (1995) Modelling cystic fibrosis in the mouse. Mol Med Today 1, 140–148. 4. Egan, M. E. (2009) How useful are cystic fibrosis mouse models? Drug Discovery Today: Disease Models 6, 35–41. 5. Grubb, B. R., and Boucher, R. C. (1999) Pathophysiology of gene-targeted mouse models for cystic fibrosis. Physiol Rev 79, S193–S214. 6. Sun, X., Yan, Z., Yi, Y., Li, Z., Lei, D., Rogers, C. S., et al. (2008) Adeno-associated

virus-targeted disruption of the CFTR gene in cloned ferrets. J Clin Invest 118, 1578–1583. 7. Rogers, C. S., Hao, Y., Rokhlina, T., Samuel, M., Stoltz, D. A., Li, Y., et al. (2008) Production of CFTR-null and CFTR-DeltaF508 heterozygous pigs by adeno-associated virus-mediated gene targeting and somatic cell nuclear transfer. J Clin Invest 118, 1571–1577. 8. Dorin, J. R., Dickinson, P., Alton, E. W., Smith, S. N., Geddes, D. M., Stevenson, B. J., et al. (1992) Cystic fibrosis in the mouse by targeted insertional mutagenesis. Nature 359, 211–215. 9. Snouwaert, J. N., Brigman, K. K., Latour, A. M., Malouf, N. N., Boucher, R. C., Smithies, O., et al. (1992) An animal model for cystic

332

10.

11.

12.

13.

14.

15.

16.

17.

18.

19.

20.

Fisher, Zhang, and Engelhardt fibrosis made by gene targeting. Science 257, 1083–1088. O’Neal, W. K., Hasty, P., McCray, P. B., Jr., Casey, B., Rivera-Perez, J., Welsh, M. J., et al. (1993) A severe phenotype in mice with a duplication of exon 3 in the cystic fibrosis locus. Hum Mol Genet 2, 1561–1569. Ratcliff, R., Evans, M. J., Cuthbert, A. W., MacVinish, L. J., Foster, D., Anderson, J. R., et al. (1993) Production of a severe cystic fibrosis mutation in mice by gene targeting. Nat Genet 4, 35–41. Zhou, L., Dey, C. R., Wert, S. E., DuVall, M. D., Frizzell, R. A., and Whitsett, J. A. (1994) Correction of lethal intestinal defect in a mouse model of cystic fibrosis by human CFTR. Science 266, 1705–1708. Colledge, W. H., Abella, B. S., Southern, K. W., Ratcliff, R., Jiang, C., Cheng, S. H., et al. (1995) Generation and characterization of a delta F508 cystic fibrosis mouse model. Nat Genet 10, 445–452. Hasty, P., O‘Neal, W. K., Liu, K. Q., Morris, A. P., Bebok, Z., Shumyatsky, G. B., et al. (1995) Severe phenotype in mice with termination mutation in exon 2 of cystic fibrosis gene. Somat Cell Mol Genet 21, 177–187. van Doorninck, J. H., French, P. J., Verbeek, E., Peters, R. H., Morreau, H., Bijman, J., et al. (1995) A mouse model for the cystic fibrosis delta F508 mutation. EMBO J 14, 4403–4411. Zeiher, B. G., Eichwald, E., Zabner, J., Smith, J. J., Puga, A. P., McCray, P. B., Jr., et al. (1995) A mouse model for the delta F508 allele of cystic fibrosis. J Clin Invest 96, 2051–2064. Delaney, S. J., Alton, E. W., Smith, S. N., Lunn, D. P., Farley, R., Lovelock, P. K., et al. (1996) Cystic fibrosis mice carrying the missense mutation G551D replicate human genotype–phenotype correlations. EMBO J 15, 955–963. Rozmahel, R., Wilschanski, M., Matin, A., Plyte, S., Oliver, M., Auerbach, W., et al. (1996) Modulation of disease severity in cystic fibrosis transmembrane conductance regulator deficient mice by a secondary genetic factor. Nat Genet 12, 280–287. Dickinson, P., et al. (1998) Generation of a CF mutant mouse possessing the G480C mutation. In 22nd European CF Conference Berlin Book of Abstracts, PS7. 14, 143. Du, M., Liu, X., Welch, E. M., Hirawat, S., Peltz, S. W., and Bedwell, D. M. (2008) PTC124 is an orally bioavailable compound that promotes suppression of the human

21.

22.

23.

24.

25.

26.

27.

28.

29.

30.

31.

CFTR-G542X nonsense allele in a CF mouse model. Proc Natl Acad Sci USA 105, 2064– 2069. Hodges, C. A., Cotton, C. U., Palmert, M. R., and Drumm, M. L. (2008) Generation of a conditional null allele for Cftr in mice. Genesis 46, 546–552. Zahm, J. M., Gaillard, D., Dupuit, F., Hinnrasky, J., Porteous, D., Dorin, J. R., et al. (1997) Early alterations in airway mucociliary clearance and inflammation of the lamina propria in CF mice. Am J Physiol 272, C853– C859. Kent, G., Iles, R., Bear, C. E., Huan, L. J., Griesenbach, U., McKerlie, C., et al. (1997) Lung disease in mice with cystic fibrosis. J Clin Invest 100, 3060–3069. Cowley, E. A., Wang, C. G., Gosselin, D., Radzioch, D., and Eidelman, D. H. (1997) Mucociliary clearance in cystic fibrosis knockout mice infected with Pseudomonas aeruginosa. Eur Respir J 10, 2312–2318. Reynaert, I., Van Der Schueren, B., Degeest, G., Manin, M., Cuppens, H., Scholte, B., et al. (2000) Morphological changes in the vas deferens and expression of the cystic fibrosis transmembrane conductance regulator (CFTR) in control, deltaF508 and knockout CFTR mice during postnatal life. Mol Reprod Dev 55, 125–135. Hodges, C. A., Palmert, M. R., and Drumm, M. L. (2008) Infertility in females with cystic fibrosis is multifactorial: evidence from mouse models. Endocrinology 149, 2790–2797. Beharry, S., Ackerley, C., Corey, M., Kent, G., Heng, Y. M., Christensen, H., et al. (2007) Long-term docosahexaenoic acid therapy in a congenic murine model of cystic fibrosis. Am J Physiol Gastrointest Liver Physiol 292, G839–G848. Durie, P. R., Kent, G., Phillips, M. J., and Ackerley, C. A. (2004) Characteristic multiorgan pathology of cystic fibrosis in a longliving cystic fibrosis transmembrane regulator knockout murine model. Am J Pathol 164, 1481–1493. Freedman, S. D., Kern, H. F., and Scheele, G. A. (2001) Pancreatic acinar cell dysfunction in CFTR(–/–) mice is associated with impairments in luminal pH and endocytosis. Gastroenterology 121, 950–957. Grubb, B. R., Paradiso, A. M., and Boucher, R. C. (1994) Anomalies in ion transport in CF mouse tracheal epithelium. Am J Physiol 267, C293–C300. Liu, X., Yan, Z., Luo, M., and Engelhardt, J. F. (2006) Species-specific differences in mouse and human airway epithelial biol-

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34. 35.

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disease and exhibit defective bacterial eradicaogy of recombinant adeno-associated virus tion at birth. Sci Transl Med 2, 29ra31. transduction. Am J Respir Cell Mol Biol 34, 40a. Pierucci-Alves, F., Akoyev, V., Stewart, J., 56–64. van Heeckeren, A. M., Schluchter, M. D., Wang, L., Schultz, B. D. (2010) CFTR–/– Xue, W., and Davis, P. B. (2006) Response pigs exhibit CBAVD phenotype at birth. to acute lung infection with mucoid Pediatr Pulmonol 45, 291. Pseudomonas aeruginosa in cystic fibrosis 41. Oppenheimer, E. H., and Esterly, J. R. mice. Am J Respir Crit Care Med 173, (1973) Cystic fibrosis of the pancreas. Mor288–296. phologic findings in infants with and without Heeckeren, A., Walenga, R., Konstan, M. diagnostic pancreatic lesions. Arch Pathol 96, W., Bonfield, T., Davis, P. B., and Ferkol, T. 149–154. (1997) Excessive inflammatory response of 42. Oppenheimer, E. H., and Esterly, J. R. cystic fibrosis mice to bronchopulmonary (1975) Pathology of cystic fibrosis review infection with Pseudomonas aeruginosa. of the literature and comparison with 146 J Clin Invest 100, 2810–2815. autopsied cases. Perspect Pediatr Pathol 2, Hodges, C. A., and Drumm, M. L. (2009) 241–278. CF: tissue by tissue. Pediatr Pulmonol 44, 43. Ostedgaard, L. S., Rogers, C. S., Dong, 188–189. Q., Randak, C. O., Vermeer, D. W., Rogers, C. S., Abraham, W. M., BrogRokhlina, T., et al. (2007) Processing and den, K. A., Engelhardt, J. F., Fisher, J. T., function of CFTR-DeltaF508 are speciesMcCray, P. B., Jr., et al. (2008) The porcine dependent. Proc Natl Acad Sci USA 104, lung as a potential model for cystic fibro15370–15375. sis. Am J Physiol Lung Cell Mol Physiol 295, 44. Liu, Y., Wang, Y., Jiang, Y., Zhu, N., Liang, L240–L263. H., Xu, L., et al. (2008) Mild processing Li, Z., and Engelhardt, J. F. (2003) Progress defect of porcine DeltaF508-CFTR suggests toward generating a ferret model of cysthat DeltaF508 pigs may not develop cystic tic fibrosis by somatic cell nuclear transfer. fibrosis disease. Biochem Biophys Res Commun Reprod Biol Endocrinol 1, 83. 373, 113–118. Williams, S. H., Sahota, V., Palmai-Pallag, 45. Yan, Z., Lei-Butters, D., Sun, X., Yi, Y., T., Tebbutt, S. J., Walker, J., and Harris, Fisher, J. T., and Engelhardt, J. F. (2009) A. (2003) Evaluation of gene targeting by Progress toward generating a F508-CFTR homologous recombination in ovine somatic cystic fibrosis ferret model. Pediatr Pulmonol cells. Mol Reprod Dev 66, 115–125. 44, 284. Rogers, C. S., Stoltz, D. A., Meyerholz, D. 46. Filali, M., Zhang, Y., Ritchie, T. C., and K., Ostedgaard, L. S., Rokhlina, T., Taft, P. Engelhardt, J. F. (2002) Xenograft model J., et al. (2008) Disruption of the CFTR gene of the CF airway. Methods Mol Med 70, produces a model of cystic fibrosis in new537–550. born pigs. Science 321, 1837–1841. 47. French, P. J., van Doorninck, J. H., Peters, Sun, X., Sui, H., Fisher, J. T., Yan, Z., Liu, X., R. H., Verbeek, E., Ameen, N. A., Marino, Cho, H. J., Joo, N. S., Zhang, Y., Zhou, W., C. R., et al. (1996) A delta F508 mutation Yi, Y., Kinyon, J. M., Lei-Butters, D. C., Grifin mouse cystic fibrosis transmembrane confin, M. A., Naumann, P., Luo, M., Ascher, ductance regulator results in a temperatureJ., Wang, K., Frana, T., Wine, J. J., Meyersensitive processing defect in vivo. J Clin holz, D. K., and Engelhardt, J. F. (2010) DisInvest 98, 1304–1312. ease phenotype of a ferret CFTR-knockout 48. Ostedgaard, L. S., Zeiher, B., and Welsh, model of cystic fibrosis. J Clin Invest 120, M. J. (1999) Processing of CFTR bear3149–3160. ing the P574H mutation differs from wildStoltz, D. A., Meyerholz, D. K., Pezzulo, type and deltaF508-CFTR. J Cell Sci 112, A. A., Ramachandran, S., Rogan, M. P., 2091–2098. Davis, G. J., Hanfland, R. A., Wohlford- 49. Vawter, G. F., and Shwachman, H. (1979) Lenane, C., Dohrn, C. L., Bartlett, J. A., Cystic fibrosis in adults: an autopsy study. Nelson, G. A. t., Chang, E. H., Taft, P. Pathol Annu 14, 357–382. J., Ludwig, P. S., Estin, M., Hornick, E. 50. Sturgess, J. M. (1984) Structural and develE., Launspach, J. L., Samuel, M., Rokhlina, opmental abnormalities of the exocrine panT., Karp, P. H., Ostedgaard, L. S., Uc, A., creas in cystic fibrosis. J Pediatr Gastroenterol Starner, T. D., Horswill, A. R., Brogden, K. Nutr 3 Suppl 1, S55–S66. A., Prather, R. S., Richter, S. S., Shilyansky, 51. Gaillard, D., Bouvier, R., Scheiner, C., NessJ., McCray, P. B., Jr., Zabner, J., and Welsh, mann, C., Delezoide, A. L., Dechelotte, P., M. J. (2010) Cystic fibrosis pigs develop lung et al. (1996) Meconium ileus and intestinal

334

52.

53.

54.

55.

56. 57. 58.

Fisher, Zhang, and Engelhardt atresia in fetuses and neonates. Pediatr Pathol Lab Med 16, 25–40. Oppenheimer, E. H., and Esterly, J. R. (1962) Observations in cystic fibrosis of the pancreas. II. Neonatal intestinal obstruction. Bull Johns Hopkins Hosp 111, 1–13. Bronstein, M. N., Sokol, R. J., Abman, S. H., Chatfield, B. A., Hammond, K. B., Hambidge, K. M., et al. (1992) Pancreatic insufficiency, growth, and nutrition in infants identified by newborn screening as having cystic fibrosis. J Pediatr 120, 533–540. Weber, A. M., Roy, C. C., Chartrand, L., Lepage, G., Dufour, O. L., Morin, C. L., et al. (1976) Relationship between bile acid malabsorption and pancreatic insufficiency in cystic fibrosis. Gut 17, 295–299. O’Brien, S., Mulcahy, H., Fenlon, H., O’Broin, A., Casey, M., Burke, A., et al. (1993) Intestinal bile acid malabsorption in cystic fibrosis. Gut 34, 1137–1141. Lindblad, A., Glaumann, H., and Strandvik, B. (1999) Natural history of liver disease in cystic fibrosis. Hepatology 30, 1151–1158. Feranchak, A. P., and Sokol, R. J. (2001) Cholangiocyte biology and cystic fibrosis liver disease. Semin Liver Dis 21, 471–488. Chaudry, G., Navarro, O. M., Levine, D. S., and Oudjhane, K. (2006) Abdominal mani-

59.

60.

61. 62.

63.

64.

festations of cystic fibrosis in children,. Pediatr Radiol 36, 233–240. Popli, K., and Stewart, J. (2007) Infertility and its management in men with cystic fibrosis: review of literature and clinical practices in the UK. Hum Fertil 10, 217–221. Oates, R. D., and Amos, J. A. (1994) The genetic basis of congenital bilateral absence of the vas deferens and cystic fibrosis. J Androl 15, 1–8. Guilbault, C., Saeed, Z., Downey, G. P., and Radzioch, D. (2007) Cystic fibrosis mouse models. Am J Respir Cell Mol Biol 36, 1–7. Hardcastle, J., Harwood, M. D., and Taylor, C. J. (2004) Absorption of taurocholic acid by the ileum of normal and transgenic deltaf508 cystic fibrosis mice. J Pharm Pharmacol 56, 445–452. Freudenberg, F., Broderick, A. L., Yu, B. B., Leonard, M. R., Glickman, J. N., and Carey, M. C. (2008) Pathophysiological basis of liver disease in cystic fibrosis employing a deltaf508 mouse model. Am J Physiol Gastrointest Liver Physiol 294, G1411–G1420. Meyerholz, D. K., Stoltz, D. A., Pezzulo, A. A., and Welsh, M. J. (2010) Pathology of gastrointestinal organs in a porcine model of cystic fibrosis. Am J Pathol 76, 1377–1389.

Chapter 20 CFTR Folding Consortium: Methods Available for Studies of CFTR Folding and Correction Kathryn W. Peters, Tsukasa Okiyoneda, William E. Balch, Ineke Braakman, Jeffrey L. Brodsky, William B. Guggino, Christopher M. Penland, Harvey B. Pollard, Eric J. Sorscher, William R. Skach, Philip J. Thomas, Gergely L. Lukacs, and Raymond A. Frizzell Abstract The CFTR Folding Consortium (CFC) was formed in 2004 under the auspices of the Cystic Fibrosis Foundation and its drug discovery and development affiliate, CFF Therapeutics. A primary goal of the CFC is the development and distribution of reagents and assay methods designed to better understand the mechanistic basis of mutant CFTR misfolding and to identify targets whose manipulation may correct CFTR folding defects. As such, reagents available from the CFC primarily target wild-type CFTR NBD1 and its common variant, F508del, and they include antibodies, cell lines, constructs, and proteins. These reagents are summarized here, and two protocols are described for the detection of cell surface CFTR: (a) an assay of the density of expressed HA-tagged CFTR by ELISA and (b) the generation and use of an antibody to CFTR’s first extracellular loop for the detection of endogenous CFTR. Finally, we highlight a systematic collection of assays, the CFC Roadmap, which is being used to assess the cellular locus and mechanism of mutant CFTR correction. The Roadmap queries CFTR structure– function relations at levels ranging from purified protein to well-differentiated human airway primary cultures. Key words: Protein folding, protein degradation, antibody generation, cell surface protein detection, research consortium, www.cftrfolding.org.

K.W. Peters and T. Okiyoneda contributed equally to this chapter

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1. Introduction 1.1. The CFTR Folding Consortium (CFC): Rationale

CFTR and many of its disease mutants are prominent substrates for endoplasmic reticulum-associated degradation (ERAD). As a multi-subunit ABC transporter protein, the biogenesis of CFTR is a complex process that involves multiple positive (pro-folding) and negative (pro-degradation) protein interactions. The common disease mutation (F508del), which results in the omission of phenylalanine at position 508 (a class II mutation), is characterized by defective biogenesis and near-complete ERAD (1). Approximately 30,000 CF patients reside in North America and more than 90% carry the F508del mutation on at least one allele; ~50% are F508del homozygotes. The F508del mutation produces severe disease, with a life expectancy of only 24 years, as opposed to 37 years in the general patient population (CF Fdn 2005 Patient Registry). Thus, among the many mutations responsible for CF, correction of the molecular defect imposed by F508del offers the maximal potential for improving the quality of life and life expectancy of CF patients. Interactions of CFTR with folding/degradation pathway components are determined by the protein’s conformation, which can be monitored by comparing the proteolytic cleavage patterns of the WT and mutant proteins. Such studies have indicated that the protease cleavage patterns are similar for immature WT and F508del proteins, whereas the digestion pattern of mature WT-CFTR is more compact, reflecting its folded state (2, 3). These data support the concept that ER-retained F508del-CFTR achieves intermediate conformation(s) that lie along the normal CFTR-folding pathway, and they suggest that misfolding arrests F508del at one or more critical checkpoints. This concept implies that F508del can be rescued from ERAD if the limiting step(s) are appropriately manipulated. Indeed, F508del-CFTR can be rescued biochemically and functionally by low temperature (4), chemical chaperones (5), chaperone manipulations (6–8), intragenic suppressor mutations (9, 10), or ER retention motif mutations (11). On this basis, and beginning approximately 10 years ago, the Cystic Fibrosis Foundation linked with biotechnology firms and academic researchers to utilize high-throughput screening (HTS) as a drug discovery platform to identify small molecules that promote F508del-CFTR trafficking to the plasma membrane (12, 13). By definition, small molecule correctors would facilitate the delivery of functional CFTR to the surface of epithelial cells. Nevertheless, HTS platforms provide end-point assays of CFTR function (e.g., anion efflux or membrane voltage) or of cell surface protein expression, which do not provide information on the

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mechanism by which additional CFTR has progressed to the cell surface. Given the complex series of interactions that may rescue mutant CFTR, knowledge of the molecular target(s) may be important in the advancement of drugs through approval processes, in the evaluation of potential off-target effects (i.e., toxicity), and in the potential development of combination therapies that would target different pathways. In addition, a byproduct of the drug discovery process is often the provision of new tools for a vertical evaluation of mechanism of action and for judging selectivity within a protein class. Compounds on the critical path for human therapy that do not define a mechanism of action do not address these important issues. Accordingly, it became apparent that furthering our understanding of the mechanisms whereby misfolded proteins can be progressed through the secretory pathway would benefit from coordinating the efforts of multiple investigators with complementary assays and areas of expertise that report on distinct aspects of CFTR biology. This CFTR Folding Consortium has now expanded to 10 academic laboratories, comprising the authorship of this chapter. Key goals of CFC include (a) the generation of new tools and assays for investigating CFTR folding and biogenesis and the means to share them with the CF scientific community and (b) the identification of cellular pathways that mediate CFTR processing as targets for the potential therapeutic manipulation of F508del-CFTR mis-processing. Accordingly, the unifying hypothesis linking these goals states that the unproductive course of F508del-CFTR biogenesis can be overcome by understanding and manipulating the intra-molecular fold and/or the rate-limiting inter-molecular interactions required for F508del trafficking to, and function at, the cell surface. 1.2. CFC Web Site

The methods and reagents developed by the CFC are made available to researchers focused on the above hypothesis through the consortium Web site: www.cftrfolding.org. In the spirit of the consortium effort, investigators who utilize these resources are asked to provide feedback on their utility and to make available any new and improved reagents or methods developed from them. Reagents available at present include antibodies (primarily to NBD1), NBD1 proteins, cell lines, and expression vectors for related proteins and shRNAs. Protocols for the use of these reagents are available from CFC investigators, and their posting on the Web site is an ongoing process.

1.3. CFTR Reagents

While there are many useful antibodies available for CFTR detection and localization, our understanding of CFTR folding would benefit from the availability of antibodies whose interaction with the protein is conformation dependent, permitting them to distinguish between wild-type CFTR and its F508del variant. Several

1.3.1. CFTR Antibodies

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CFC laboratories have been actively pursuing this goal by raising antibodies to NBD1. Currently, five NBD1 antibodies are available through the Web site, including the mouse monoclonals, 5A6.3, 10B6.2, and 7D12; the rat monoclonal, 3G11; and the rabbit polyclonal, Mr. Pink. Interestingly, the majority of the monoclonal antibodies recognize a common epitope, which lies within aa 401–410 of hNBD1, while the available polyclonal targets several NBD1 epitopes, as would be expected. Further attempts to generate antibodies sensitive to conformation continue, using CFTR domains or full-length protein as antigens. Success in this endeavor may be reflected in antibodies that recognize the folded protein in immunoprecipitation or immunofluorescence experiments but detect the unfolded protein less well in Western blots or vice versa. Such tools would permit the evaluation of conditions and agents that improve the folding of mutant CFTR. 1.3.2. CFTR Proteins

Purified mouse and human NBD1 proteins are available for distribution to investigators. Wild-type and F508del-mNBD1 and WT-hNBD1 (residues 389–673) are provided for shipping costs in aliquots of a few hundred micrograms. Requests for larger amounts can be accommodated with justification. Requests for the reagents can be placed at the Folding Consortium Web site under “Reagents.” A complete set of characterization data for each preparation (SDS-PAGE, CD spectrum, intrinsic tryptophan fluorescence spectrum, and thermal stability, as described in Chapter 20) is also included on the Web site under the “Data” tab. Identity of the expressed protein has been verified by mass spectrometry for samples of each of the preparations as well. Protocols used for the expression, purification, and characterization are also available on the Web site under the “Protocols” tab. Whereas the F508del-hNBD1 is more difficult to produce, due to decreased stability, it is not routinely available via the CFC Web site.

1.3.3. The CFC Roadmap

A goal of the Folding Consortium is to combine the diverse array of cell-based and in vitro assays available in member labs to probe diverse aspects of CFTR biogenesis and trafficking. To systematize this process, the collection of assays was overlaid on a modified scheme for the protein secretory pathway, featuring intersections that allow distinct aspects of CFTR function to be assessed. Thus, the Roadmap is basically an assay-laden decision tree that reflects the cellular fate of CFTR. The analysis of CFTR function at each of these nodes provides a fingerprint of how a specific modulator (potentiator or corrector) influences CFTR’s function at critical sites of the secretory pathway. For example, macroscopic assays of transepithelial currents across airway epithelia provide

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an indication of whether pre-incubation with a compound rescues F508del-CFTR function in the context of a relevant cellular background. Assays performed at other nodes, approximately 30 in all, determine whether this action can be attributed to increased cell surface protein expression, improved intracellular trafficking, reduced ERAD, or the folding of CFTR toward a native conformation. Depending on the outcome, in-depth assays are available to assess the pathways that are responsible for the observed effect(s). Details of the Roadmap and its attendant assays are provided in a manuscript that focuses on the analysis of CFTR modulators (14). That report summarizes the potential uses of Roadmap assays and provides a comparative analysis of the actions of available small molecule correctors, reduced temperature, and revertant mutations that improve the F508del-CFTR fold. The Modulator Roadmap provides an assay-based view of the protein secretory pathway, rather than the one found in textbooks. Due to the diversity of its assays, this analysis provides a more complete picture of mechanism than can generally be obtained by individual laboratories or biotechnology concerns, at least within a timely manner. Nevertheless, each of the map intersections is determined by pathways involving hundreds of proteins and protein interactions, requiring a more complete systems biology analysis of the actions of the most efficacious compounds. A key implication from the findings to date is that different F508del correction approaches show activity profiles that allow their distinction from one another (14). Potentially, this outcome could inform drug development by (a) identifying ratedetermining steps in the complex process of CFTR biogenesis; (b) informing structure–activity relationships by associating different drug scaffolds with activity at the same or different nodes within the Roadmap; (c) implicating compound interactions that may lead to additivity or synergy when treatments are combined; and (d) suggesting candidates for the molecular target(s) of drug action. In general, the profile of drug activity in this analysis may provide for comparisons of different CFTR correction strategies to optimize our efforts to understand and treat the most common cause of cystic fibrosis. In addition, this approach may be generally applicable to other diseases of protein folding. 1.4. Methods to Determine CFTR Membrane Expression 1.4.1. Measuring CFTR Cell Surface Density by Cell Surface ELISA

The cell surface density of CFTR can be determined by biotinylation combined with immunoprecipitation and immunoblotting (15–17). However, this experimental approach is technically demanding and time consuming and has a relatively low sensitivity. Exogenous and endogenous CFTR could also be detected at the plasma membrane by antibodies recognizing extracellular segments of the channel (e.g., the first extracellular loop)

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(18, 19). We have developed a third approach using cell surface ELISA (designated as immunoperoxidase assay) to monitor quantitatively the cell surface expression level, as well as turnover of heterologously expressed wild-type and mutant CFTR bearing an extracellular epitope tag (20, 21) (Fig. 20.1a). To this end, a 3HA epitope tag was introduced genetically into the fourth extracellular loop of CFTR (CFTR-3HA) (12, 20). CFTR variants with the 3HA tag were expressed heterologously in BHK, HEK293, HeLa, IB3, and CFBE cells. We confirmed that the

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Fig. 20.1. (a) Schematic model of the immunoperoxidase assay to measure CFTR cell surface density, internalization rate, and cell surface stability. The CFTR cell surface density is measured by the primary anti-HA and secondary HRP-conjugated antibody binding to the CFTR-3HA. The HRP activity is monitored by the fluorescence generated R Red substrate. CFTR cell surface stability and internalization rate from the Amplex are quantified by measuring the disappearance of the anti-HA antibody from the cell surface at 37◦ C following the primary antibody binding. The remaining anti-HA antibody is quantified by the immunoperoxidase assay. (b) Cell surface density of CFTR-3HA in HEK293MSR cells. Similar to previous studies (12, 20, 21), most F508del-CFTR failed to express at the cell surface. Low-temperature incubation (26◦ C, 36 h) rescued the cell surface expression of F508del-CFTR (rF). (c) Internalization rate (5 min) of the wt and rescued F508del-CFTR-3HA in HEK293MSR cells. (d) Cell surface stability of CFTR-3HA in HEK293MSR cells was measured by the immunoperoxidase assay. While the wt-CFTR was stable at the cell surface, rF508del-CFTR was rapidly internalized (c) and eliminated from the cell surface (d).

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3HA tag has minimal effect on CFTR folding, channel functioning, and trafficking (12, 20–22). The wild-type (wt) and mutant CFTR-3HA expression, as well as internalization and stability at the plasma membrane (PM), was detected by the immunoperoxidase assay using primary antiHA antibody and HRP-conjugated secondary antibody in the R Red (Invitrogen), a florescent HRP subpresence of Amplex strate. Normalization of the fluorescence signal for cell number or cellular protein permits the quantitative comparison of the channel density under various conditions, as well as the PM turnover rate of CFTR, an assay described in Section 3.1.1. CFTR internalization and cell surface stability are followed by a modified version of the immunoperoxidase assay as described in Section 3.1.2. 1.4.2. Cell Surface Detection of Native CFTR

Epitope or fluorescent protein tagging of CFTR has been remarkably successful, permitting the cell surface labeling of expressed protein for a variety of purposes, including the screening for small molecule correctors of mutant CFTR trafficking (23, 24). Nevertheless, the detection of native, untagged CFTR at the plasma or the apical membrane remains a significant goal, particularly in epithelia that express the channel endogenously. If successful, this approach would have the benefit of eliminating over-expression artifacts and cell-type dependency in the cellular handling of WT and mutant CFTR. High-affinity antibodies that recognize an extracellular epitope of endogenous CFTR would be particularly useful in preclinical studies to evaluate potential therapies to promote CFTR progression to the apical plasma membrane. However, only 4% of CFTR’s amino acids are predicted to be located at the extracellular surface, and the majority of these are likely to be shielded by glycosylation at two sites in the larger fourth extracellular loop. However, the first ECL contains 15 amino acids in a sequence predicted to be antigenic. Amino acids 107–118 were used previously to raise antibodies, and they detected CFTR in the plasma membrane of non-permeabilized cells, with amplification procedures (18, 19). They provided some of the first evidence that F508del-CFTR did not appear at the cell surface. This antibody was less efficient in immunoprecipitation experiments, perhaps because it did not detect the native conformation of ECL1 at high affinity. In anticipation of raising higher affinity antisera, we employed a conformationally constrained ECL1 peptide as antigen, in which the N and C termini were linked by a disulfide bond. Results obtained with this rabbit antibody in Western blot, immunoprecipitation, and immunofluorescence studies are described in Section 3.2.

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2. Materials 2.1. Materials for Detection of HA-CFTR

1. Cell culture medium: Use the appropriate bicarbonatecontaining medium (e.g.„ Dulbecco’s modified Eagle’s medium (DMEM) for HeLa or HEK293 cells, DMEM/F12 for BHK cells) supplemented with 10% FBS (Invitrogen) for culturing the cells in a CO2 incubator. Medium should be stored at 4◦ C. 2. PBS(+): Phosphate-buffered saline supplemented with 0.1 mM CaCl2 and 1 mM MgCl2 . 3. 0.5% Bovine serum albumin (BSA)/PBS(+). Store at 4◦ C. 4. Anti-HA11 monoclonal antibody (Covance MMS-101R). 5. HRP-conjugated anti-mouse IgG secondary antibody (GE Healthcare NA931V). R Red reagent (Invitrogen A-22177, 10 mM 6. Amplex DMSO stock, stored at –20◦ C, protect from light).

7. 30% H2 O2 (Sigma H1009). R R Red reaction mix (50 μM Amplex Red, 8. Amplex 200 μM H2 O2, 50 mM NaH2 PO4 , pH 7.4, protect from light, prepare immediately before use).

9. RIPA buffer (150 mM NaCl, 20 mM Tris, 1% Triton X100, 0.1% SDS, 0.5% sodium deoxycholate, pH 8.0). 10. BCA protein assay kit (Thermo Scientific, #23225). 2.1.1. Instrumentation

1. Tissue culture incubator at 37◦ C with 5% CO2 . 2. 24-Well tissue culture plates (BD Falcon DL-353047). 3. 96-Well black plates for fluorescence (NUNC 437111). 4. Fluorescence plate reader (POLAR star Optima, BMG LABTECH).

2.2. Materials for Detection of Native CFTR

1. Cell culture and lysis: Wild-type cystic fibrosis bronchial epithelial (wt-CFBE) (a kind gift of J.P. Clancy) cells are cultured in growth medium consisting of minimum essential medium (MEM) (Invitrogen) supplemented with 10% fetal bovine serum (FBS) (HyClone), 50 U/ml penicillin, 50 μg/ml streptomycin, 2 mM L-glutamine (Invitrogen), and 0.5 μg/ml puromycin (InvivoGen). F508delCFBE cells are cultured as wt-CFBEs but with 2 μg/ml puromycin. Parental CFBE cells (p-CFBEs) are cultured as wt-CFBEs but without puromycin. Calu-3 cells are cultured in MEM (ATCC), 15% FBS (HyClone), and 1% penicillin/streptomycin (Gibco). A 0.25% trypsin–0.53 mM EDTA solution (ATCC) is used to remove cells from plastic.

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2. 4-(2-Hydroxyethyl)-1-piperazine ethanesulfonic acid (HEPES)-buffered saline, pH 7.4–7.6 (HBS): 19 mM HEPES, 122 mM NaCl, 1 mM glucose, 6.3 mM Na2 HPO4 •7H2 O (dibasic), and 250 μl 0.5% phenol red solution. 10% Polyvinylpyrrolidone (PVP) (Sigma) is made in HBS. 3. 0.2% Ethylene glycol-bis(2-aminoethyl-ether)-N,N,N ,N tetraacetic acid (EGTA) is made in HBS. 4. Fifty milliliter of PVP/EGTA/trypsin (PET) is made with 35 ml HBS, 5 ml of 10% PVP, 5 ml of 0.2% EGTA, and 5 ml of 0.25% trypsin with Versene (Sigma). 5. Lysis buffer (RIPA): 150 mM NaCl, 50 mM Tris–HCl (pH 7.5), 1.0% Triton X-100, 1% deoxycholic acid (sodium salt), 0.1% sodium dodecyl sulfate (SDS), Complete Mini protease inhibitor tablet (PIT; Roche) (one tablet/10 ml RIPA). 2.2.1. Coupling of Peptide

1. Cognate sequence of the first extracellular loop of CFTR with three additional cysteines. R maleimide-activated mariculture keyhole limpet 2. Imject hemocyanin (mcKLH) (Pierce). R (Pierce) dialysis cassettes. 3. Slide-A-Lyzer

2.2.2. Production of Polyclonal Antibodies

1. Synthetic peptide coupled with KLH. 2. PBS (Gibco). R 3. Imject Freund’s complete adjuvant (Pierce). R Freund’s incomplete adjuvant (Pierce). 4. Imject

5. Two or three 6-week-old male rabbits. 2.2.3. Enzyme-Linked Immunosorbent Assay (ELISA)

1. Carbonate buffer: 15 mM Na2 CO3 , 35 mM NaHCO3 , 3 mM NaN3 , pH 9.6 (25). 2. Diethanolamine buffer: 1 M diethanolamine, 3 mM NaH3 , 0.5 mM MgCl2 , pH 9.8, stored in the dark. 3. Tris buffered saline (TBS): 50 mM Tris–HCl, 0.2 M NaCl, pH 7.5. 4. TBS/Tween (TBST): 50 mM Tris–HCl, 0.2 M NaCl, pH 7.5, 0.05% Tween 20. 5. TBST/bovine serum albumin (TBSTB): 50 mM Tris–HCl, 0.2 M NaCl, pH 7.5, 0.05% Tween 20, 1.0% bovine serum albumin. 6. Rabbit serum expressing antibodies of interest. 7. Alkaline phosphatase-conjugated AffiniPure goat anti-rabbit IgG (Jackson ImmunoResearch).

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2.2.4. Immunoprecipitation (IP)

1. Protein A agarose (Invitrogen) (26).

2.2.5. Immunoblot (IB)

1. Tris buffered saline (TBS): 50 mM Tris–HCl, 0.2 M NaCl, pH 7.5.

2. Sample buffer: 62.5 mM Tris–HCl (pH 6.8), 2% SDS, 10% glycerol, 0.01% bromophenol blue, and 5% β-mercaptoethanol.

2. TBS/0.1% Tween 20 (TBST). 3. TBST/5% instant non-fat dry milk (Carnation) (TBSTM). 4. Chemiluminescent reagents (GE Healthcare). 2.2.6. Immunofluorescence (IF)

1. Calu-3 cells on filters. 2. PBS. 3. Agonist: 10 ml PBS with 10 μl of 10 mM forskolin (Calbiochem) (fsk) in EtOH and 20 μl of 500 mM 3-isobutyl1-methylxanthine (IBMX) (Sigma) in dimethyl sulfoxide (DMSO). 4. PBS/0.5% bovine serum albumin (BSA)/0.15% glycine (PBSBG). 5. PBSBG/5% goat serum (PBSBG-GS).

3. Methods 3.1. Methods for Detection of Cell Surface HA-CFTR 3.1.1. Cell Surface Density Measurement of CFTR-3HA

1. Seed cells expressing CFTR-3HA on 24-well plates at least 24 h before the experiment. Prepare three or four wells of each sample so that triplicate or quadruplicate measurements could be obtained. Prepare non-transfected cells to verify the extent of the non-specific binding of the primary and the secondary antibody. By the time of the experiment cells should be at 80–90% confluence. 2. Rinse cells with ice-cold 0.5% BSA–PBS(+) (1 ml/well) gently to avoid cell loss. 3. Add ice-cold 0.5% BSA–PBS(+) (1 ml/well) and block in the same medium for 20 min on ice. 4. Bind the primary anti-HA antibody (1:1000–2000 dilution) in 0.5% BSA–PBS(+) (200 μl/well) for 1 h on ice (see Note 1). 5. Rinse the cells with ice-cold PBS(+) (1 ml/well) three times (see Note 2). 6. Bind HRP-conjugated anti-mouse IgG (1:1000–2000 dilution) in 0.5% BSA–PBS(+) (200 μl/well) for 1 h on ice.

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7. Rinse the cells with ice-cold PBS(+) (1 ml/well) 6–7 times (see Note 2). R Red reaction mix (200 μl/well) and incu8. Add Amplex bate on ice for 10–20 min in the dark (see Note 3).

9. Transfer 200 μl Amplex Red reaction mix from 24-well plates to black 96-well plates. R Red signal by a fluorescence plate 10. Read the Amplex reader (e.g., POLAR star Optima, BMG LABTECH) at 544 nm excitation and 590 nm emission wavelength.

11. Rinse the cells with 1 ml ice-cold PBS(+) once and add 70 μl RIPA buffer to lyse the cells for the BCA assay to measure the protein concentration (see Note 4). 12. Calculate the relative cell surface CFTR-3HA density based on the specific fluorescence signal. Normalize the fluorescence signal for the protein concentration of the respective well. Subtract the normalized fluorescence signal measured on non-transfected cells from the total fluorescence signal. Express the cell surface density of the CFTR variant as percentage of the wt-CFTR (Fig. 20.1b). 3.1.2. CFTR Internalization and Cell Surface Stability Measurement

Modification of the cell surface ELISA enables to determine the internalization rate and cell surface stability of CFTR-3HA (12, 20, 21). The CFTR-3HA internalization and the cell surface stability are measured by monitoring the disappearance of CFTRbound anti-HA antibody from the plasma membrane at 37◦ C. 1. Seed the cells as described in Section 3.1.1. Prepare multiple 24-well plates for different length of chase (e.g., time 0, 5, 60, and 120 min). 2. Bind the primary anti-HA antibody as described in Section 3.1.1. 3. Rinse the cells with ice-cold PBS(+) (1 ml/well) three times. 4. CFTR endocytosis is induced by the addition of the prewarmed (37◦ C) complete medium (+FBS). Incubate the cells for the desired time period to allow internalization (e.g., 2.5 and 5 min). Longer chase periods are required to measure the CFTR turnover at the plasma membrane at 37◦ C. Since CFTR appears to be less stable in HEK293 cells than in other non-polarized cells, 60- and 120-min incubation was chosen in this study. 5. After the incubation at 37◦ C, terminate the internalization by rinsing the cells with ice-cold PBS(+) (1 ml/well) two times (see Note 5). 6. Bind HRP-conjugated anti-mouse IgG as described in Section 3.1.1.

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7. Rinse the cells with ice-cold PBS(+) (1 ml/well) 6–7 times R Red signal as described in Secand measure the Amplex tion 3.1.1. 8. The CFTR internalization rate is expressed as the percentage of channel uptake after 5 min relative to the initial amount at cell surface (Fig. 20.1c). To determine the cell surface stability, the disappearance kinetics of cell surface labeled CFTR is plotted. The remaining amount of CFTR is expressed as the percentage of the initial amount. The channel turnover is indicated by the chase time that is necessary to decrease the CFTR cell surface density by 50% (Fig. 20.1d). 3.2. Methods for Detection of Native CFTR 3.2.1. Cell Culture and Lysis

1. The CFBE cells are maintained at 37◦ C in a humidified incubator containing 5% CO2 and allowed to grow until 90–95% confluent. At this point, using aseptic techniques, they are rinsed twice with HBS, rinsed with 5 ml PET, then covered with PET again, and returned to the incubator for 5 min. To the dislodged cells, 7 ml of media is added and the mixture placed in a 15-ml conical tube. Cells are pelleted gently at 10◦ C, at 800–1000 rpm in a Sorvall RT6000B refrigerated centrifuge, the media removed, cells dislodged by tapping, 4 ml of fresh media added, and 1 ml of the heterogeneous mixture added to each new T-75 flask containing 9 ml of medium. 2. Calu-3 cells are cultured in a similar manner with appropriate media and trypsin. Time for removal of these cells from plastic is longer, about 7 min. 3. Cells are lysed by rinsing the flask twice with PBS, then adding 1 ml of RIPA/PIT. Assays are performed to determine protein concentration.

3.2.2. Choice of Antigen

The predicted structure of CFTR suggests that there are six extracellular loops (27); however, four are less than five amino acids and are likely unsuitable for antibody production. The fourth loop has two consensus glycosylation sites for N-linked glycans which may mask antibody recognition of the epitope, rendering it an unsuitable candidate. The first loop has 15 amino acids:

GRIIASYDPDNKEER Several are polar, hydrophilic, and form an epitope likely accessible to antibodies. In order to restrict separation and hold the peptide into a loop, two cysteines were added at the carboxy and amino termini to form disulfide bonds and a third cysteine was added at the carboxy terminus for coupling.

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3.2.3. Synthesis of Antigen

The peptide is synthesized in solid phase on a Liberty Microwave Synthesizer (CEM Corporation, 3100 Smith Farm Road, Mathews, NC 28106) using an FMOC synthesis protocol (University of Pittsburgh Peptide Synthesis Facility). Briefly, synthesis is performed by stepwise addition of activated amino acids to the solid support (preloaded Wang resin) starting at the carboxy and proceeding to the amino terminus. Activation of amino acids is performed by DIPEA/HOBT/TBTU chemistry. For regioselective cyclization between cysteine positions 1 and 17 (carboxy to amino), trityl-protecting groups are used and the N-terminal cysteine is protected by a PMeOBZl group. At the end of synthesis, the peptide is cleaved from the resin by reagent R (90% TFA, 5% thioanisole, 3% ethanedithiol, and 2% anisole) and subjected to multiple ether extractions. The crude peptide is analyzed, characterized, and purified by gel filtration (G-25 column) and reversed-phase, high-performance liquid chromatography (RPHPLC, 486 and 600E by Waters Corporation), and later the correct mass is confirmed by MALDI-TOF mass spectroscopy (The Voyager-DE STR Biospectrometry Workstation). Cyclization of purified peptide is performed by a hydrogen peroxide method and confirmed by Elman’s test. At the end, the PMeOBZL group is removed from the N-terminal cysteine and the final product is re-purified by HPLC and confirmed by mass spectrometry.

3.2.4. Coupling of Peptide to Keyhole Limpet Hemocyanin

In order for the peptide hapten to elicit an adequate immune response in the rabbit, it is coupled with KLH, a large, foreign protein, following manufacturer’s directions (Pierce): 1. Ten milligrams of activated carrier is reconstituted in 1 ml dH2 O and 10 mg of hapten is added. This carrier/peptide solution is allowed to react for 2 h at room temperature. R dialysis cassette 2. The solution is dialyzed in a Slide-A-Lyzer ◦ (Pierce), 10,000 MWCO, at 4 C overnight, removed from cassette, aliquoted, and frozen.

3.2.5. Production of Antibodies in Rabbits

Before any treatment is commenced in rabbits, a pre-immune bleed (about 20 ml) is removed from the medial ear artery with a 21-gauge butterfly needle and the serum is harvested for use as negative controls in future experiments. To carry out this procedure, blood is allowed to clot for 1 h at room temperature, separated from the sides of the tube with the wooden end of a long, cotton-tipped applicator, then spun at 10,000×g for 10 min. The serum (supernatant) is recovered from the pellet (red blood cells), aliquoted in quantities that will not necessitate repeated freeze/thaws, and frozen at –80◦ C. To prepare for injections of antigen, an emulsion is made with equal volumes of coupled peptide (500 μg per rabbit) in PBS and R Freund’s complete adjuvant (Pierce) adjuvant. On day 1, Imject is used for the first series of 5–7 subcutaneous injections and on

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3.2.6. Enzyme-Linked Immunosorbent Assay (ELISA)

In preparation for this experiment, (a) allow diethanolamine buffer to come to room temperature and (b) make appropriate dilutions of antiserum into TBSTB in microcentrifuge tubes, e.g., start with 1:100, then proceed with progressive twofold dilutions in the remaining 11 tubes. 1. Coat 96-well microtiter plate with antigen by placing 200 μl carbonate buffer to each well and adding 50 pmol antigen to each well. Cover plate with parafilm and incubate at room temperature overnight. 2. Block the plate. Fill each well by adding TBSTB. Incubate at 37◦ C for 1 h. 3. Wash plate three times using TBST. 4. Add 100 μl antiserum into each well. Incubate at 37◦ C for 1 h covered with parafilm. 5. Wash plate three times with TBST. 6. Make a 1:5000 dilution of secondary Ab–alkaline phosphatase conjugate (goat anti-rabbit) in TBSTB and add 100 μl to each well. Incubate for 2 h at 37◦ C. 7. Wash plate three times using TBST. 8. Dissolve para-nitrophenylphosphate tablets (one 5 mg tablet/5 ml diethanolamine buffer). Add 100 μl of this substrate to each well. Incubate for 30 min at room temperature protected from light. 9. Read plate at 414 nm subtracting out nonspecific background of the plate at 650 nm. 10. Binding curves are defined at half maximal values with 50 pmol of antigen (Fig. 20.2a).

3.2.7. Immunoprecipitation

Immunoprecipitations are carried out as described by Harlow and Lane with modifications: 1. Rinse flasks twice with PBS, then remove PBS. 2. Add RIPA, scrape cells, and place lysate in a microcentrifuge tube. 3. Sonicate lysates, then rotate for 1 h at 4◦ C. 4. Centrifuge for 3 min at 13,000×g. Recover the supernatant and perform a protein assay. 5. Place 500 μg of soluble lysate in a microcentrifuge tube. Add 3 μl ECL1 antibody and rotate overnight at 4◦ C. 6. Add 50 μl protein bead slurry and rotate for 7 h or overnight.

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A

B

kDa

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Fig. 20.2. (a) Data from a quantitative ELISA for antibody recognition of the first extracellular loop of CFTR, ECL1. Fifty picomoles of ECL1 peptide was used with a repetitive series of 1:2 dilutions of the antiserum. Binding curves were half-maximal at 50 pM, at an antibody dilution of 1:100,000. (b) The ECL1 antibody effectively immunoprecipitates CFTR from CFBE cells. Lanes: 1, parental CFBE; 2, CFBE-WT; 3, CFBE-F508del; 4, CFBE-F508del following 48 h incubation at 27◦ C. Although effective for immunoprecipitation, the ECL1 antibody does not recognize denatured CFTR by immunoblot (data not shown). (c) CFTR detection by immunofluorescence in polarized Calu-3 cells. Left, peptide competition of ECL1 antibodies with synthetic peptide prior to use. Right, ECL1 staining of non-permeabilized Calu-3 monolayer using the IgG fraction. Cells cultured on Transwell filter for 1 week were imaged by confocal microscopy at the first detectable apical signal, which creates the patchy fluorescence patter due to the uneven cell layer.

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7. Centrifuge immunocomplexes and wash pellets times with 1 ml RIPA. 8. Remove RIPA, add sample buffer, and incubate at 40◦ C for 10 min. 9. Load samples onto a 6% gel for SDS-PAGE. 3.2.8. Immunoblot

1. Block membranes, into which proteins have been transferred, in TBSTM for 1 h at room temperature. 2. Incubate membrane with primary antibody at appropriate dilution (e.g., 217 monoclonal 1:5000) for 1 h at room temperature. 3. Wash three times for 5 min each in TBST. 4. Incubate membrane in appropriate peroxidase-conjugated secondary antibody at a dilution of 1:20,000 for 2 h at room temperature. 5. Wash three times for 5 min each. 6. Mix substrate chemiluminescent detection reagents one and two (GE Healthcare) in equal amounts and apply to toweldried membranes for 1 min. 7. Blot membranes dry and expose to film for optimal exposure (Fig. 20.2b).

3.2.9. Immunofluorescence

1. Seed Calu-3 cells onto filters (Snapwells with polycarbonate membrane) (Costar) and maintain until confluent. 2. Wash filters in PBS. 3. Add agonist for 10 min at room temperature. 4. From this point on, perform all steps with ice-cold buffers and keep filters on ice. 5. Wash filters three times with PBS, followed by three washes with PBSBG. 6. Block non-specific binding with PBSBG-GS for 1 h. 7. Wash three times with ice-cold PBSBG. 8. Incubate cells with primary antibody diluted 1:200 in PBSBG for 1 h. 9. Wash three times with PBSBG. 10. Incubate cells with secondary antibody, e.g., goat antirabbit CY3 1:1000 for 1 h. 11. Wash three times with PBSBG followed by three washes in PBS. 12. Cut filters from Snapwells and orient them upside down onto coverslips. Place Gelvatol onto a microscope slide, position over the filter, and press (Fig. 20.2c).

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4. Notes 4.1. Detection of HA-CFTR

1. It is recommended to optimize the antibody concentration in order to maximize the specific signal. This could be achieved by using serial dilutions of the primary and secondary antibodies on transfected and non-transfected cells in pilot studies. Incubation should be done at 4◦ C to prevent the CFTR–antibody internalization. 2. Add the solution carefully by pipetting down the sides of the wells to avoid detachment of cells. Avoid drying the cells during the washing by immediately adding the medium after aspiration. 3. If the fluorescence signal is weak, extend the incubaR tion time. If you have too strong signal (e.g., Amplex Red becomes pink in 1–2 min), you need to dilute the R Red to avoid the signal saturation. antibodies/Amplex 4. This is not necessary if the cell number in each sample is same. If the cell number is different between samples, the fluorescence signal normalization is required for protein concentration, which reflects the cell number. 5. During the 37◦ C incubation, keep the other plates on ice to prevent the CFTR–antibody complex internalization.

Acknowledgments Resources providing support for this work in the Frizzell lab include grants from the NIH (DK068196 and DK 072506) and the Cystic Fibrosis Foundation (CFF R883-CR07 and FRIZZE05XX0). Experimental work in the laboratory of Gergely Lukacs was funded by the NIH, Cystic Fibrosis Folding Consortium, CIHR, and CFI. Tsukasa Okiyoneda was supported by a postdoctoral fellowship from the Canadian Cystic Fibrosis Foundation. References 1. Cheng, S. H., Gregory, R. J., Marshall, J., Paul, S., Souza, D. W., White, G. A., et al. (1990) Defective intracellular transport and processing of CFTR is the molecular basis of most cystic fibrosis. Cell 63, 827–834. 2. Zhang, F., Kartner, N., and Lukacs, G. L. (1998) Limited proteolysis as a probe for

arrested conformational maturation of delta F508 CFTR. Nat Struct Biol 5, 180–183. 3. Du, K., Sharma, M., and Lukacs, G. L. (2005) The DeltaF508 cystic fibrosis mutation impairs domain-domain interactions and arrests post-translational folding of CFTR. Nat Struct Mol Biol 12, 17–25.

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4. Denning, G. M., Anderson, M. P., Amara, J. F., Marshall, J., Smith, A. E., and Welsh, M. J. (1992) Processing of mutant cystic fibrosis transmembrane conductance regulator is temperature-sensitive. Nature 358, 761–764. 5. Welch, W. J. (2004) Role of quality control pathways in human diseases involving protein misfolding. Semin Cell Dev Biol 15, 31–38. 6. Wang, X., Venable, J., LaPointe, P., Hutt, D. M., Koulov, A. V., Coppinger, J., et al. (2006) Hsp90 cochaperone Aha1 downregulation rescues misfolding of CFTR in cystic fibrosis. Cell 127, 803–815. 7. Zhang, Y., Nijbroek, G., Sullivan, M. L., McCracken, A. A., Watkins, S. C., Michaelis, S., et al. (2001) Hsp70 molecular chaperone facilitates endoplasmic reticulum-associated protein degradation of cystic fibrosis transmembrane conductance regulator in yeast. Mol Biol Cell 12, 1303–1314. 8. Sun, F., Mi, Z., Condliffe, S. B., Bertrand, C. A., Gong, X., Lu, X., et al. (2008) Chaperone displacement from mutant cystic fibrosis transmembrane conductance regulator restores its function in human airway epithelia. FASEB J 22, 3255–3263. 9. DeCarvalho, A. C., Gansheroff, L. J., and Teem, J. L. (2002) Mutations in the nucleotide binding domain 1 signature motif region rescue processing and functional defects of cystic fibrosis transmembrane conductance regulator delta F508. J Biol Chem 277, 35896–35905. 10. Teem, J. L., Carson, M. R., and Welsh, M. J. (1996) Mutation of R555 in CFTR-delta F508 enhances function and partially corrects defective processing. Receptors Channels 4, 63–72. 11. Chang, X. B., Cui, L., Hou, Y. X., Jensen, T. J., Aleksandrov, A. A., Mengos, A., et al. (1999) Removal of multiple arginine-framed trafficking signals overcomes misprocessing of delta F508 CFTR present in most patients with cystic fibrosis. Mol Cell 4, 137–142. 12. Pedemonte, N., Lukacs, G. L., Du, K., Caci, E., Zegarra-Moran, O., Galietta, L. J., et al. (2005) Small-molecule correctors of defective DeltaF508-CFTR cellular processing identified by high-throughput screening. J Clin Invest 115, 2564–2571. 13. Van Goor, F., Straley, K. S., Cao, D., Gonzalez, J., Hadida, S., Hazlewood, A., et al. (2006) Rescue of DeltaF508-CFTR trafficking and gating in human cystic fibrosis airway primary cultures by small molecules. Am J Physiol Lung Cell Mol Physiol 290, L1117–L1130.

14. Pyle, L. C., Balch, W. E., Lukacs, G., Braakman, I., Guggino, W. B., Thomas, P. J., et al. (2010) Developing a cellular road map for correctors of protein misfolding: a consortium approach. Nat Rev Drug Disc. (submitted). 15. Lukacs, G. L., Segal, G., Kartner, N., Grinstein, S., and Zhang, F. (1997) Constitutive internalization of cystic fibrosis transmembrane conductance regulator occurs via clathrin-dependent endocytosis and is regulated by protein phosphorylation. Biochem J 328 (Pt 2), 353–361. 16. Prince, L. S., Peter, K., Hatton, S. R., Zaliauskiene, L., Cotlin, L. F., Clancy, J. P., et al. (1999) Efficient endocytosis of the cystic fibrosis transmembrane conductance regulator requires a tyrosine-based signal. J Biol Chem 274, 3602–3609. 17. Benharouga, M., Haardt, M., Kartner, N., and Lukacs, G. L. (2001) COOH-terminal truncations promote proteasome-dependent degradation of mature cystic fibrosis transmembrane conductance regulator from postGolgi compartments. J Cell Biol 153, 957– 970. 18. Denning, G. M., Ostedgaard, L. S., Cheng, S. H., Smith, A. E., and Welsh, M. J. (1992) Localization of cystic fibrosis transmembrane conductance regulator in chloride secretory epithelia. J Clin Invest 89, 339–349. 19. Denning, G. M., Ostedgaard, L. S., and Welsh, M. J. (1992) Abnormal localization of cystic fibrosis transmembrane conductance regulator in primary cultures of cystic fibrosis airway epithelia. J Cell Biol 118, 551–559. 20. Sharma, M., Pampinella, F., Nemes, C., Benharouga, M., So, J., Du, K., et al. (2004) Misfolding diverts CFTR from recycling to degradation: quality control at early endosomes. J Cell Biol 164, 923–933. 21. Glozman, R., Okiyoneda, T., Mulvihill, C. M., Rini, J. M., Barriere, H., and Lukacs, G. L. (2009) N-glycans are direct determinants of CFTR folding and stability in secretory and endocytic membrane traffic. J Cell Biol 184, 847–862. 22. Barriere, H., Bagdany, M., Bossard, F., Okiyoneda, T., Wojewodka, G., Gruenert, D., et al. (2009) Revisiting the role of cystic fibrosis transmembrane conductance regulator and counterion permeability in the pH regulation of endocytic organelles. Mol Biol Cell 20, 3125–3141. 23. Robert, R., Carlile, G. W., Pavel, C., Liu, N., Anjos, S. M., Liao, J., et al. (2008) Structural analog of sildenafil identified as a novel corrector of the F508del-

CFTR Folding Consortium Reagents and Protocols CFTR trafficking defect. Mol Pharm 73, 478–489. 24. Carlile, G. W., Robert, R., Zhang, D., Teske, K. A., Luo, Y., Hanrahan, J. W., et al. (2007) Correctors of protein trafficking defects identified by a novel high-throughput screening assay. ChemBioChem 8, 1012–1020. 25. Voller, A., Bidwell, D., Rose, N. R., Friedman, H., and Fahey, J. L. (1986) Enzymelinked immunosorbent assay, in Manual of Clinical Laboratory Immunology, vol. 3.

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American Society of Microbiology, Washington, DC, pp. 99–109. 26. Harlow, E., and Lane, D. (1988) Immunoprecipitation, in Antibodies: A Practical Approach. 27. Riordan, J. R., Rommens, J. M., Kerem, B., Alon, N., Rozmahel, R., Grzelczak, Z., et al. (1989) Identification of the cystic fibrosis gene: cloning and characterization of complementary DNA. Science 245, 1066–1073.

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Chapter 21 Evaluation of the Disease Liability of CFTR Variants Patrick R. Sosnay, Carlo Castellani, Mary Corey, Ruslan Dorfman, Julian Zielenski, Rachel Karchin, Christopher M. Penland, and Garry R. Cutting Abstract Over 1600 novel sequence variants in the CFTR gene have been reported to the CF Mutation Database (http://www.genet.sickkids.on.ca/cftr/Home.html). While about 25 mutations are well characterized by clinical studies and functional assays, the disease liability of most of the remaining mutations is either unclear or unknown. This gap in knowledge has implications for diagnosis, therapy selection, and counseling for patients and families carrying an uncharacterized CFTR mutation. This chapter will describe a critical approach to assessing the disease implications of CFTR mutations utilizing clinical data, literature review, functional testing, and bioinformatic in silico methods. Key words: CFTR mutations, CFTR variants, CFTR polymorphisms, mutation prediction algorithms, in silico testing, bioinformatic analysis, genotype–phenotype relationship.

1. Introduction Defining disease liability: Disease liability in reference to a germline mutation refers to the capability of that allele to influence a given disease phenotype. For example, an individual with the p.Glu6Val (HbS) mutation in each beta-globin gene is expected in all cases to have sickle-cell anemia. Likewise, in the case of cystic fibrosis (CF), the full penetrance of the most common deleterious allele in the cystic fibrosis transmembrane conductance regulator gene (CFTR) (p.Phe508del, c.1521_1523delCTT) is well documented. However, unlike sickle cell anemia there are over 1600 variants in CFTR, many M.D. Amaral, K. Kunzelmann (eds.), Cystic Fibrosis, Methods in Molecular Biology 742, DOI 10.1007/978-1-61779-120-8_21, © Springer Science+Business Media, LLC 2011

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of which have been reported in one or only a few individuals. The 23 alleles included in the American College of Medical Genetics (ACMG) panel on screening for CF and a few other mutations have been identified as disease causing by evaluating patients carrying one of these mutations and p.Phe508del on the other chromosome and by functional testing (1, 2). However, the remaining CFTR variants identified in the CF Mutation Database (CFMD) have not been rigorously examined. Systematic and objective evaluation of the disease-causing potential of CFTR mutations is important as genetic testing for CFTR mutations is being performed more frequently for newborn screening, carrier screening, and CF diagnosis and for consideration of mutation-specific therapeutics (3). The lessons and experience learned from developing an algorithm to evaluate CFTR mutations should be relevant to complex diseases with a heritable component (4, 5). Challenges created by multiple CFTR variants: Individuals with CF have mutations in both copies of their CFTR gene, as expected for a recessive Mendelian disorder. The Hardy– Weinberg law establishes the relationship between the allele frequency and the genotype frequency in a population (Fig. 21.1). The most common CFTR mutation p.Phe508del accounts for 70% of CF alleles and has a frequency of approximately 2.5% in the general population (6, 7). Both of these frequencies assume a population of Caucasian European descent, though there may be remarkable differences among distinct geographical areas (7, 8). From the frequency of p.Phe508del in CF patients, one can estimate that 49% of individuals with CF have two copies of p.Phe508del allele (p2 = (0.7)2 = 0.49). The remaining individuals will have either one p.Phe508del with another CFTR mutation (2pq = 2 × 0.7 × 0.3 = 0.42) or two non-p.Phe508del alleles (q2 = (0.3)2 = 0.09). When genotyping with the ACMG panel (which accounts for 85% of the CF alleles) one can predict that 27% of individuals with CF will carry at least one non-ACMG CF mutation (2 × 0.85 × 0.15 + (0.15)2 ). If enough CFTR mutations are well characterized to account for 95% of CF alleles, then only 10% of CF patients would have an uncharacterized CFTR

Fig. 21.1. The Hardy–Weinberg equation for population genetics. CFTR has many potential variants. The frequencies that appear in the text use this equation to compare genotypes when different percentages of the alleles are characterized.

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mutation (9). The effect of increasing the fraction of CF alleles known to cause disease upon the fraction of patients with fully informative genotypes is illustrated in Fig. 21.2. Another way of looking at this challenge is demonstrated in Fig. 21.3. Mutations such as p.Phe508del and p.Met470Val occur commonly, and therefore the confidence in determination of the effect of each mutation is high. Rare mutations constitute not only a large percentage of the total variation in CFTR but also a small fraction of all CF alleles. These uncharacterized mutations are infrequently evaluated and therefore there is low confidence in any prediction of disease liability. Although we are providing population-based estimates here, the difficulty with uncharacterized CFTR mutations is acute in individual cases. For example, consider the challenge of an uncharacterized CFTR mutation in an asymptomatic child detected by a newborn screen. There are uncertain ramifications of diagnosis and a lifetime of costly therapies to consider. Determining the Effect of Variants on CFTR Function: It is reasonable to predict that each CFTR variant alters protein function in some manner along a spectrum from null (no function) to

Fig. 21.2. Percentage of CF total mutations, total alleles in CF patients, and individuals with genotypes that would be characterized based on the number of mutations evaluated. The fraction of total mutations is based on 1600 CFTR variants described in the CFMD. The percentage of total alleles is based on the worldwide CFTR2 database (Cutting, unpublished results). The percentage of individuals in which both CFTR mutations are identified uses the allele percentage and the Hardy–Weinberg law.

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Fig. 21.3. The relationship between CFTR variant disease liability and (a) the relative number of patients that carry that variant; (b) the number of variants expressed as the percentage of total variants in CFTR; (c) the confidence of our ability to determine if a variant is disease causing or neutral. Common variants or polymorphisms as well as mutations that are often seen in CF patients are frequently seen and therefore one can determine with confidence their disease liability. Infrequently seen mutations affect few patients, but these represent a large percentage of the total CFTR variation described. Because these mutations are seen less there are less rigorous evaluations and therefore the confidence about the determination of their disease liability is less.

near-wild type or even, theoretically, enhanced protein function. Disease-causing mutations (such as p.Phe508del) are expected to cause CFTR to be dysfunctional. At the other end of the spectrum are amino acid substitutions (such as p.Met470Val) that cause only minor alterations in function and are not associated with disease (10–12). For CF diagnostic purposes, one would ideally have all CFTR variants characterized as either a disease-causing mutation (like p.Phe508del) or a neutral (like p.Met470Val). The key challenge is to identify the threshold at which a reduction in protein function is enough to cause disease. Features of individuals carrying a given variant, functional evaluation of the variant in cell-based assays, or predictive evaluation of the consequences of the variant each may be used to evaluate where along the spectrum between deleterious and near wild type a given variant belongs. Correlating CFTR Genotype with CF Phenotype: The severity spectrum and threshold for CFTR differ across organ systems, illustrated in Fig. 21.4 (13). This is a result of the differing role of CFTR in pathogenesis for each of these organ systems. CF carriers may demonstrate single organ system traits seen in CF,

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Fig. 21.4. Genotype and specific organs system phenotype correlation. The relative penetrance of separate organ systems is shown relative to the degree of CFTR dysfunction. CF carriers, with only one CF causing CFTR mutation, may have some of the traits seen in CF patients. In these cases, CFTR is acting as a modifier gene interacting with other genetic and environmental predispositions, rather than the sole etiology of the organ dysfunction (ABPA = allergic bronchopulmonary aspergillosis).

but with much lower penetrance than individuals with two CFTR mutations (14–16). The male reproductive tract is the most sensitive tissue to detect CFTR dysfunction. Individuals who carry a single CFTR mutation, as well as individuals with mutations in each CFTR gene that cause only mild reductions in function, may have obstructive azoospermia without any other signs of disease (13, 14, 17, 18). Pancreatic and lung tissue require more severe disruption of CFTR function to manifest features of CF. CFTR mutations have been arranged into five functional classes by Welsh and Smith according to the defect in protein function (19). Classes 1–3 CFTR mutations which cause the most severe disruption of CFTR function are associated with pancreatic insufficient disease compared to classes 4 and 5 CFTR mutations which lead to milder impairment in CFTR function and are associated with partially retained pancreatic function (20). This categorization of CFTR mutations by their effect on pancreatic function is problematic and will be discussed below. Additionally, how well correlated the severity of organ system pathology is

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with the degree of CFTR dysfunction is different across different organ systems, is subject to different genetic and environmental modifiers for each organ system, and varies with time. These complicating factors confound researchers’ and clinicians’ ability to predict the degree of lung dysfunction that will be associated with a CFTR genotype.

2. Tools to Evaluate CFTR Variants for Disease Liability

Clinical Data: One method to assess pathogenicity is to view every CFTR mutation occurring in an individual meeting clinical diagnostic criterion for CF as disease causing. However, there are a few caveats to this approach. First, although we are attempting to assess the disease liability for the mutation, we are evaluating the mutation in the context of the recessive phenotype caused by alterations in both CFTR genes. Heterozygote carriers do not manifest CF (although they may have a predisposition to other conditions). Therefore to create a CF phenotype both copies of CFTR must be dysfunctional. It is important therefore when evaluating the disease liability of a CFTR mutation of unknown effect to analyze patients carrying a known CF-causing mutation in their other CFTR gene. The severity and commonness of p.Phe508del facilitate its use as a consistent background on which to compare novel mutations (21–23). Second, discerning the disease liability of a mutation when multiple mutations exist in the same CFTR gene can be a substantial challenge. These “complex alleles” may harbor covert point mutations in the coding or noncoding regions of the gene or a large insertion, deletion, or duplication (24, 25). For example, the variant p.Ile148Thr was initially felt to be disease causing, but further examination found that the mutation occurred at a higher rate in healthy individuals undergoing carrier screening than in CF patients (26). Subsequent studies revealed that most CF patients with p.Ile148Thr also carry the two amino acid deletion c.3067_3072del (27). The latter mutation in isolation causes CF whereas p.Ile148Thr in isolation does not. Other CFTR variants may not individually cause disease, but can cause disease when they occur in a CFTR gene with other variants. For example, the disease liability of the ACMG mutation p.Arg117His is dependent on polythymidine variants in the flanking exon (28). When this mutation is associated with the “5T” polythymidine tract, p.Arg117His has a higher penetrance for CF, whereas longer polythymidine tracts (“7T” or “9T”) are associated with obstructive azoospermia or no disease at all. For these reasons it is critical to confirm that a mutation in isolation is deleterious both by demonstrating the clinical

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traits consistent with CF in several individuals that carry the novel mutation and by demonstrating its dysfunction on a cellular level. As an additional test, variants identified in healthy carriers with a CF-causing CFTR mutation on the other chromosome must be neutral. Third, direct measures of CFTR function (sweat chloride and nasal potential differences (NPD) measurements) are not highly correlated with the morbidity and mortality of the disease. Other traits, such as lung dysfunction and airway bacterial colonization, more useful in predicting clinical outcome in CF, are usually normal at birth and only manifest over time. Furthermore, these traits show high individual variability and are influenced by genetic and environmental modifiers (29). With these limitations in mind, the effect of a CFTR mutation on an individual’s phenotype is the single most important measure of the medical relevance of that mutation. The specific features used to clinically evaluate CFTR function are described below.

3. Direct Assays of In Vivo CFTR Function

Sweat Chloride Measurement: The determination of ion concentration in sweat induced by pilocarpine administration is an objective method to differentiate CF from other diseases of the lungs or pancreas. The procedure is standardized, accurate, and highly reproducible (30, 31). In the context of a positive newborn screen or clinical symptoms of CF, individuals with a sweat chloride concentration higher than 60 mEq/L have two CF-causing CFTR mutations. This is a specific threshold as lower sweat values do not exclude two disease-causing mutations (32). However, only 3.5% of CF patients in the USA had sweat chloride concentration less than 60 mEq/L and only 1.2% had values less than 40 mEq/L (33). The thresholds for sweat chloride measurement were recently changed (>60 mEq/L: positive; 30–60 mEq/L for infants, 40–60 mEq/L for children over 6 months: intermediate; and <30 mEq/L for infants, <40 mEq/L for children over 6 months: negative) to account for changes in sweat chloride that occurs after infancy (34–36). In addition, CFTR mutations that have been described in CF but more frequently identified in males with isolated obstructive azoospermia may be associated with indeterminate (between 40 and 60 mEq/L) or even negative (less than 40 mEq/L) sweat chloride. Thus, in clinical cases where sweat chloride concentration is indeterminate, the test is repeated and other disorders associated with CFTR dysfunction need to be considered (i.e., “CFTRopathies” or CFrelated metabolic syndrome) (6, 37). The challenge of intermediate sweat chloride values is a consequence of the fact that sweat

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chloride concentrations correlate with the degree of dysfunction caused by CFTR mutations. For example, mutations associated with residual CFTR function by in vitro assay (discussed later in the chapter and elsewhere in this book) are associated with less elevated sweat chloride concentrations than mutations that result in null or minimal residual function in CFTR (38). Nasal Potential Difference Measurements (NPD): Nasal epithelial cells provide a useful surrogate for lower airway epithelium as they both display the same electrical properties of lower airway cells and also demonstrate a disease phenotype. NPD measurement is performed with a reference electrode under the skin, measuring the voltage difference across the respiratory epithelium in the nose. The exact procedure for NPD is described elsewhere in this book (Chapter 6, of Vol. I). Individuals with two deleterious mutations in CFTR will have a hyperpolarized baseline voltage difference as a result of the loss of inhibition of the epithelial sodium channel, a large decrease in voltage with the addition of amiloride, and a lack of a response to low chloride perfusate or to forskolin (39). NPD measurement may be an adjunct to sweat chloride measurements in individuals with indeterminate sweat tests or uncertain cases where an elevation in sweat chloride is seen in the absence of clinical features. NPD also has the ability to detect defects in the epithelial sodium channel which may create a CF-like phenotype without mutations in CFTR (40). The limitations of NPD are discussed in Chapter 6, of Vol. I, although theoretically the possibility for intermediate results that exist with sweat chloride is reduced. NPD can be a useful test in cases where the CF diagnosis is in question or to evaluate potential therapeutics, but the lack of availability and inconsistency make this test less useful to assess the disease liability of CFTR mutations (41).

4. Clinical Characteristics The clinical characteristics used to define CF (outlined in Table 21.1) may be used to confirm the CF phenotype in an individual with an uncertain genotype, but these features are limited in their ability to quantify the degree of dysfunction of CFTR mutations (34, 36, 42, 43). A few clinical characteristics deserve special attention. As mentioned previously males with mild CFTR mutations associated with low penetrance may have obstructive azoospermia as their only evidence of CFTR dysfunction. These individuals would meet the diagnostic criteria for CF if they also demonstrate abnormal in vivo CFTR function measured by sweat chloride or NPD. Second, the correlation described previously

Malnutrition is a clinical diagnosis, fat-soluble vitamin deficiencies may be suggested by clinical findings, must be confirmed by laboratory tests Laboratory testing

Malnutrition, fat-soluble vitamin deficiencies

Obstructive azoospermia

Reproductive

Absence of vas deferens on physical exam or ultrasound abnormalities

1. Some correlation of mutation class with pancreatic function

1. PFTs are useful objective measurement that can be used to predict prognosis

1. Pseudomonas and Cepacia have higher specificity for CF (ref) 2. Pseudomonas infection was shown to be predictive of CFTR mutation in individuals with “non-typical” CF (ref. Pubmed ID)

Comments

Modified from Rosenstein and Cutting (36) (reference # 33, 35 from text). The references associated with airway colonization and infection are (1) Burns et al. (43) (Pubmed ID 9675470) and (2) Groman et al. (42) (Pubmed ID 15970673) – these reference are all included in the text where the table is introduced.

Hyponatremic dehydration

Clinical diagnosis and laboratory findings

Elevated liver function tests, cirrhosis on imaging, or biopsy

Hepatic involvement

Diabetes mellitus

Pancreatitis diagnosed by clinical evaluation and laboratory evidence. Pancreatic insufficiency suggested by history, but diagnosed by fecal studies for fat or antibodies for fecal elastase

Pancreatitis, pancreatic insufficiency

Physical exam finding Meconium ileus is a surgical diagnosis, intestinal obstruction syndromes are a clinical diagnosis (combination of history, physical exam, and imaging)

Digital clubbing

Meconium ileus, intestinal obstruction syndromes

Physical exam, radiological evidence, or surgical diagnosis

Nasal polyps

Salt loss syndromes

Gastrointestinal and nutritional abnormalities

Presence of airway dilation on chest x-ray or CT scan Wheezing on physical exam or pulmonary function test (PFT) documentation of airway obstruction

Airway obstruction

Historical definition

Chronic cough, sputum production

Bronchiectasis

Sputum microbiology analysis showing a CF specific organism: Staphylococcus aureus, nontypeable Haemophilus influenzae, mucoid and nonmucoid Pseudomonas aeruginosa, Stenotrophomonas maltophilia, and Burkholderia cepacia

Persistent airway colonization/infection

Chronic sinopulmonary disease

Defining characteristic

Phenotypic feature

Category

Table 21.1 Phenotypic features consistent with a diagnosis of CF

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between CFTR mutation class and pancreatic status is not absolute. For example, the incidence of pancreatic insufficiency, even in those with pancreatic sufficient genotypes, has been shown to increase in older CF patients (44). Furthermore, characterization of pancreatic sufficient mutations as “mild” is misleading, as individuals with pancreatic sufficient genotypes may still have severe lung disease. Finally, lung function is the single phenotypic feature most relevant to disease progression, morbidity, and mortality. Pulmonary function tests (PFTs) to measure lung function are standardized, well referenced, and objective. However, there is high variability in lung function even among individuals with the same CFTR genotype, and lung function correlates poorly with CFTR function on an individual basis (45, 46).

5. Functional Assessment Detailed discussions of the laboratory-based assays to evaluate CFTR function are discussed elsewhere in this book (see Part II – RNA Methods to Approach CFTR Expression, Part III – CFTR Protein Biogenesis, Folding, Degradation and Traffic). Mutations in CFTR can be classified as originally described by Welsh and Smith (19). Nonsense mutations (Class 1) which introduce a premature stop codon would be expected to produce an unstable mRNA and marked reduction in protein product (47). Mutations that lead to abnormalities in processing and folding (Class 2) will produce a protein product that is incompletely glycosylated (more B-band than the fully glycosylated C-band). Other mutations allow CFTR to mature and traffic to the cell surface, but interfere with channel ion regulation or conduction (Classes 3 and 4). Finally, mutations that alter CFTR splicing may produce insufficient levels of correctly spliced mRNA leading to reduced CFTR protein and abnormal ion conductance (Class 5). Table 21.2 describes the CFTR mutation classes and what would be expected on several key assays.

6. Predictive Methods Predicted nonsense-mediated mRNA decay (NMRD): Mutations that would be expected to introduce a premature stop codon (nonsense mutations) that cause a frameshift or that alter the universal splice donor/acceptor sites, typically cause an unstable truncated mRNA that is degraded by the cell. Therefore, it

Markedly reduced or absent mRNA

No detectable CFTR protein

No detectable CFTR protein

Markedly reduced anion conductance compared to wild type. Unable to augment conductance with CFTR stimulation

RNA assessment: • mRNA assay from CFTR expressing tissue • Hybrid minigene

CFTR processing • Protein analysis (in primary or transfected cells)

CFTR localization

Anion conductance • Single channel recordings • Short circuit preparations

Class 1 Defective protein production

Markedly reduced anion conductance compared to wild type. Unable to augment conductance with CFTR stimulation

Little CFTR present, not correctly localized

Incompletely glycosylated (B band) in excess of maturely processed, fully glycosylated protein (C-band)

Normal levels of mRNA

Class 2 Defective protein production

Markedly reduced anion conductance compared to wild type. Unable to augment conductance with CFTR stimulation

CFTR present in apical or sub-apical compartment

Mix of Incompletely glycosylated (B band) and maturely processed, fully glycosylated protein (C-band)

Normal levels of mRNA

Class 3 Defective channel regulation

Table 21.2 Mutation classes and expected results on key functional assays

Reduced anion conductance compared to wild type. Possibly retained augmented conductance with CFTR stimulation

CFTR present in apical or sub-apical compartment

Normal levels of maturely processed, fully glycosylated protein (C-band)

Normal levels of mRNA

Class 4 Defective channel conductance

Reduced anion conductance compared to wild type. Retained ability to augment conductance with CFTR stimulation

CFTR present in reduced quantity vs. wild type in apical or sub-apical compartment

Normal ratio of maturely processed, fully glycosylated protein (C-band) to immaturely processed (B-band)

Populations of mRNA that are correctly and aberrantly spliced (two different length PCR products)

Class 5 Mutations causing abnormal splicing

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would be expected that these mutations would produce no functional protein and therefore be disease causing (48). Consistent with this, there are no known neutral CFTR variants of these mutation types. Individuals with a CFTR mutation predicted to cause NMRD, in trans with another CF-causing mutation, would be expected to have CF. Predicted affect on structure and function by bioinformatic in silico analysis: There is growing field of research dedicated to making predictions of the effect of an amino acid substitution on protein function (49, 50). These methodologies take into account general features about the protein structure or sequence to predict whether a given amino acid substitution is deleterious. In particular, this approach has been applied to predict the effect of non-synonymous single nucleotide polymorphisms upon genes implicated in inherited diseases, especially cancer susceptibility (49, 51–57). The bioinformatic tools PolyPhen and SIFT have been employed to evaluate amino acid changes in CFTR, but made significant errors incorrectly identifying “known” neutral polymorphisms p.Phe508Cys and p.Ile148Thr as likely to be deleterious (58, 59). An alternate bioinformatics approach that incorporates structural modeling and statistical learning has also been used to predict the effect of CFTR polymorphisms in the nucleotide-binding domains (NBDs). This method applied a random forest classifier using both amino acid sequence homology and structure-based features on a curated collection of over 8,000 amino acid changing variants annotated as “disease” or “neutral” from the UniProtKB databases (60). The classifier yielded 86% accuracy in discriminating between 59 disease and 13 neutral CFTR polymorphisms from the CFTR database (and 78% accuracy for 215 disease and 60 neutral polymorphisms from the human ABC transporter superfamily annotated in UniProtKB and CFTR databases). The structural models highlighted three disease “hot-spots” in the NBDs in which polymorphisms associated with multiple diseases were found to be enriched in eight ABC transporters, including CFTR. All in silico predictive tools will inaccurately predict the effect on function of some variants. To evaluate the utility of these predictive tools for CFTR polymorphisms and to identify variants that are predicted incorrectly, they will need to be tested systematically against variants agreed upon to be either deleterious or neutral. The large difference between the number of CFTR variants cataloged (>1600) and the number that has well-characterized disease liability remains the biggest challenge that prevents the widespread use of these bioinformatic predictors in CF. Drawing from the literature examining cancer genes, there is likely benefit in developing computational machine learners and Bayesian statistical models specifically targeted to CFTR variants. These new methods can combine various types of information (bioinformatic, functional, and clinical) (4, 61, 62). Such

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combined predictive models will also benefit from better characterization (utilizing better clinical phenotype characterization and further cell-based functional analysis) of CFTR variants that are clearly disease causing and clearly neutral. Similar predictive techniques could also be used to predict the consequence of splice mutations that do not involve canonical splice donor/acceptor sites. It will be necessary to incorporate a weighting system into these models. For example, if a mutation is seen in only three patients worldwide the strength of a call (disease causing vs. neutral) based on clinical criteria would be weaker than a mutation seen in 100 patients. Likewise there are likely trends within nucleotide substitutions or insertion/deletions that make a variant more or less likely to be disease causing and should therefore receive more weight in a predictive model. These trends may incorporate a hotspot for mutations within the sequence of the gene or may involve specific nucleotide or amino acid changes.

7. Types of Databases Currently, to investigate a particular uncharacterized CFTR variant, a patient, a clinician, or a researcher have several online publicly available databases to consider. These resources are described in Table 21.3. There are clinical descriptions of patient characteristics as well as laboratory-based testing published in the literature, but it would require a sophisticated reader with a great deal of time to amass and synthesize information for any given mutation. Therefore a simple MEDLINE/PubMed search is not included in the table. Much of the published literature is summarized in the Online Mendelian Inheritance in Man (OMIM) database, published by the US National Center for Biotechnology Information. The CFMD overseen at the University of Toronto is the largest collection of CFTR variants, with over 1600. This database is maintained by voluntary submissions from CF researchers. The CFMD represents the most comprehensive collection of variation, although it allows the possibility of artifactual results. One problem is that these locus-specific databases (LSDBs) in CF are not targeted toward the general medical community or lay public. Very few of the more than 700 genes that have LSDBs accomplish this goal (63). Given the complexity of the genotype–phenotype relationship in CF, there is a considerable challenge presenting this data to a broad audience. The increase in genetic screening necessitates that a wider scope of people will need to interpret the results of genetic tests. As there is a movement toward personalized medicine and increased use of genetic testing in general, monogenic disorders such as CF can provide an

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Table 21.3 Mutation databases

Database

Description

OMIM http://www. ncbi.nlm.nih. gov/omim

Genotype– phenotype summary of disease associated with CFTR (and other genes)

HGMD http://www. hgmd.cf.ac.uk/ ac/gene.php? gene=CFTR

Number of CFTR alleles

Advantages

Disadvantages

136

Well annotated with links to references. Written so that a broad audience could use

Lags behind as it relies on published data

Mutation-based index, organized by mutation type

1385

Includes both published and unpublished data. Contains links to references

No information on phenotype or consequence of the mutation. Not accessible to most lay-users

CF mutation database http://www. genet.sickkids. on.ca/cftr/ Home.html

A locus specific database with researcher submitted entries

1602

Long history of characterizing mutations. Excellent coverage of both deleterious and neutral variants. Searchable by text and by location on the gene

Researcher submitted, so may contain incorrect information, especially with regard to clinical information. Not accessible to most lay users

Patient registries

National or regional databases of patient information

Unknown Well-described phenotype, in some cases longitudinal

Not public, may contain identifying information. Quality of information varies by registry. Information is not summarized by mutation

example of how genetic information is communicated. Therefore there is tremendous opportunity for a database that both helps to address the great number of uncharacterized variants in CFTR and also presents that information in a manner that the lay public can readily understand.

8. Summary Genetic analysis for CFTR mutations is being used more frequently for both CF diagnosis and screening. Reduction of the cost of DNA sequencing and other advances has enabled the identification of a wide array of CFTR mutations in patients.

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Fig. 21.5. Algorithm for evaluating CFTR variant. Variants are initially characterized by the clinical features of individuals carrying the variant in question in trans with another known CF-causing mutation. Those mutations that are clinically consistent with CF are then evaluated functionally. Those either predicted (mutations that cause NMRD) or confirmed (with cell-based in vitro testing) to cause CFTR dysfunction are then confirmed with both higher level predictive models and the absence of that variant in trans with a CF-causing mutation, in non-CF controls. Mutations satisfying all criteria are validated as disease-causing CF mutations.

Effective and safe use of this flood of information has two particular challenges: discriminating neutral variants from deleterious mutations and communicating this information to a broad population. Figure 21.5 outlines how clinical features of patients carrying the variant, laboratory-based testing of the consequences of the variant, and predictive algorithms may be used to evaluate the disease liability of the variant. Further refinement on how to combine these different modalities to derive a diagnostic model that can be applied to any given variant will be the focus of future bioinformatic research.

Acknowledgments The authors would like to thank Neeraj Sharma Ph.D. and Barbara Karczeski M.S., M.A. for their critical review of this manuscript. This work was supported by research grants from the US CF Foundation (CUTTING09A and SOSNAY10Q0) and from the National Institute of Health (HL68927 and DK44003).

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References 1. Grody, W. W., Cutting, G. R., Klinger, K. W., Richards, C. S., Watson, M. S., and Desnick, R. J. (2001) Laboratory standards and guidelines for population-based cystic fibrosis carrier screening. Genet Med 3, 149–154. 2. Watson, M. S., Cutting, G. R., Desnick, R. J., Driscoll, D. A., Klinger, K., Mennuti, M., et al. (2004) Cystic fibrosis population carrier screening: 2004 revision of american college of medical genetics mutation panel. Genet Med 6, 387–391. 3. Lebo, R. V., and Grody, W. W. (2007) Testing and reporting ACMG cystic fibrosis mutation panel results. Genet Test 11, 11–31. 4. Goldgar, D. E., Easton, D. F., Deffenbaugh, A. M., Monteiro, A. N., Tavtigian, S. V., and Couch, F. J. (2004) Integrated evaluation of DNA sequence variants of unknown clinical significance: application to BRCA1 and BRCA2. Am J Hum Genet 75, 535–544. 5. Mitchell, A. A., Chakravarti, A., and Cutler, D. J. (2005) On the probability that a novel variant is a disease-causing mutation. Genome Res 15, 960–966. 6. Castellani, C., Cuppens, H., Macek, M., Jr., Cassiman, J. J., Kerem, E., Durie, P., et al. (2008) Consensus on the use and interpretation of cystic fibrosis mutation analysis in clinical practice. J Cyst Fibros 7, 179–196. 7. Bobadilla, J. L., Macek, M., Fine, J. P., and Farrell, P. M. (2002) Cystic fibrosis: a worldwide analysis of CFTR mutations – correlation with incidence data and application to screening. Hum Mutat 19, 575–606. 8. Southern, K. W., Munck, A., Pollitt, R., Travert, G., Zanolla, L., Dankert-Roelse, J., et al. (2007) A survey of newborn screening for cystic fibrosis in Europe. J Cyst Fibros 6, 57–65. 9. Grody, W. W., Cutting, G. R., and Watson, M. S. (2007) The cystic fibrosis mutation “arms race”: when less is more. Genet Med 9, 739–744. 10. Pompei, F., Ciminelli, B. M., Bombieri, C., Ciccacci, C., Koudova, M., Giorgi, S., et al. (2006) Haplotype block structure study of the CFTR gene. Most variants are associated with the M470 allele in several European populations. Eur J Hum Genet 14, 85–93. 11. Bombieri, C., Giorgi, S., Carles, S., de Cid, R., Belpinati, F., Tandoi, C., et al. (2000) A new approach for identifying non-pathogenic mutations. An analysis of the cystic fibrosis transmembrane regulator gene in normal individuals. Hum Genet 106, 172–178.

12. Wei, L., Vankeerberghen, A., Jaspers, M., Cassiman, J., Nilius, B., and Cuppens, H. (2000) Suppressive interactions between mutations located in the two nucleotide binding domains of CFTR. FEBS Lett 473, 149–153. 13. Zielenski, J. (2000) Genotype and phenotype in cystic fibrosis. Respiration 67, 117–133. 14. Stuppia, L., Antonucci, I., Binni, F., Brandi, A., Grifone, N., Colosimo, A., et al. (2005) Screening of mutations in the CFTR gene in 1195 couples entering assisted reproduction technique programs. Eur J Hum Genet 13, 959–964. 15. Wang, X. J., Moylan, B., Leopold, D. A., Zeitlin, P. L., Rubenstein, R. C., Proud, D., et al. (1998) An increased frequency of CF mutations in patients with chronic sinusitis. Am J Hum Genet 63, A55. 16. Miller, P. W., Hamosh, A., Macek, M., Jr., Greenberger, P. A., MacLean, J., Walden, S., et al. (1996) Cystic fibrosis transmembrane conductance regulator (CFTR) gene mutations in allergic bronchopulmonary aspergillosis. Am J Hum Genet 59, 45–51. 17. Wilschanski, M., Dupuis, A., Ellis, L., Jarvi, K., Zielenski, J., Tullis, E., et al. (2006) Mutations in cystic fibrosis transmembrane regulator gene and in vivo transepithelial potentials. Am J Respir Crit Care Med 127, 705–710. 18. Anguiano, A., Oates, R. D., Amos, J. A., Dean, M., Gerrard, B., Stewart, C., et al. (1992) Congenital bilateral absence of the vas deferens – a primarily genital form of cystic fibrosis. J Am Med Assoc 267, 1794–1797. 19. Welsh, M. J., and Smith, A. E. (1993) Molecular mechanisms of CFTR chloride channel dysfunction in cystic fibrosis. Cell 73, 1251– 1254. 20. Kerem, E., and Kerem, B. (1995) The relationship between genotype and phenotype in cystic fibrosis. Curr Opin Pulm Med 1, 450– 456. 21. Cheng, S. H., Gregory, R. J., Marshall, J., Paul, S., Souza, D. W., White, G. A., et al. (1990) Defective intracellular transport and processing of CFTR is the molecular basis of most cystic fibrosis. Cell 63, 827–834. 22. US Cystic Fibrosis Foundation (2008) US cystic fibrosis foundation patient registry annual data report for 2007. 23. The Cystic Fibrosis Genotype-Phenotype Consortium (1993) Correlation between genotype and phenotype in patients with cystic fibrosis. The cystic fibrosis

Evaluation of CFTR Variants

24. 25.

26.

27.

28.

29.

30.

31.

32.

33. 34.

genotype-phenotype consortium. N Engl J Med 329, 1308–1313. Mickle, J. E., and Cutting, G. R. (2000) Genotype-phenotype relationships in cystic fibrosis. Med Clin North Am 84, 597–607. Taulan, M., Guittard, C., Theze, C., Claustres, M., and Georges, M. (2009) A novel double deletion underscores the importance of characterizing end points of the CFTR large rearrangements. Eur J Hum Genet 17, 1683–1687. Rohlfs, E. M., Zhou, Z., Sugarman, E. A., Heim, R. A., Pace, R. G., Knowles, M. R., et al. (2002) The I148T CFTR allele occurs on multiple haplotypes: a complex allele is associated with cystic fibrosis. Genet Med 4, 319–323. Strom, C. M., Huang, D., Buller, A., Redman, J., Crossley, B., Anderson, B., et al. (2002) Cystic fibrosis screening using the college panel: platform comparison and lessons learned from the first 20,000 samples. Genet Med 4, 289–296. Kiesewetter, S., Macek, M., Jr., Davis, C., Curristin, S. M., Chu, C.-S., Graham, C., et al. (1993) A mutation in the cystic fibrosis transmembrane conductance regulator gene produces different phenotypes depending on chromosomal background. Nature Genet 5, 274–278. Vanscoy, L. L., Lai, T., Bowers, A., and Cutting, G. R. (2006) Modifier genes may contribute substantially to variation in cystic fibrosis (cf) lung disease estimated by CFSpecific % for FEV1. Proc Am Thorac Soc 3, A408. Gibson, L. E., and Cooke, R. E. (1959) A test for concentration of electrolytes in sweat in cystic fibrosis of the pancreas utilizing pilocarpine by iontophoresis. Pediatrics 23, 545– 549. Beauchamp, M., and Lands, L. C. (2005) Sweat-testing: a review of current technical requirements. Pediatr Pulmonol 39, 507– 511. Stewart, B., Zabner, J., Shuber, A. P., Welsh, M. J., and McCray, P. B., Jr. (1995) Normal sweat chloride values do not exclude the diagnosis of cystic fibrosis. Am J Resp Crit Care Med 151, 899–903. US Cystic Fibrosis Foundation (2008) US cystic fibrosis foundation patient registry annual data report for 2007. Farrell, P. M., Rosenstein, B. J., White, T. B., Accurso, F. J., Castellani, C., Cutting, G. R., et al. (2008) Guidelines for diagnosis of cystic fibrosis in newborns through older adults: cystic fibrosis foundation consensus report. J Pediatr 153, S4–S14.

371

35. Eng, W., LeGrys, V. A., Schechter, M. S., Laughon, M. M., and Barker, P. M. (2005) Sweat-testing in preterm and fullterm infants less than 6 weeks of age. Pediatr Pulmonol 40, 64–67. 36. Rosenstein, B. J., and Cutting, G. R. (1998) The diagnosis of cystic fibrosis: a consensus statement. J Pediatr 132, 589–595. 37. Borowitz, D., Parad, R. B., Sharp, J. K., Sabadosa, K. A., Robinson, K. A., Rock, M. J., et al. (2009) Cystic fibrosis foundation practice guidelines for the management of infants with cystic fibrosis transmembrane conductance regulator-related metabolic syndrome during the first two years of life and beyond. J Pediatr 155, S106–S116. 38. Wilschanski, M., Zielenski, J., Markiewicz, D., Taui, L. C., Corey, M., Levison, H., et al. (1995) Correlation of sweat chloride concentration with classes of the cystic fibrosis transmembrane conductance regulator gene mutations. J Pediatr 127, 705–710. 39. Wilson, D. C., Ellis, L. E., Zielenski, J., Corey, M., Ip, W. F., Tsui, L. C., et al. (1998) Uncertainty in the diagnosis of cystic fibrosis: possible role of in vivo nasal potential difference measurements. J Pediatr 132, 596–599. 40. Sheridan, M. B., Fong, P., Groman, J. D., Conrad, C., Flume, P., Diaz, R., et al. (2005) Mutations in the beta subunit of the epithelial Na+ channel in patients with a cystic fibrosis-like syndrome. Hum Mol Genet 14, 3493–3498. 41. Wilschanski, M., Famini, H., StraussLiviatan, N., Rivlin, J., Blau, H., Bibi, H., et al. (2001) Nasal potential difference measurements in patients with atypical cystic fibrosis. Eur Respir J 17, 1208–1215. 42. Groman, J. D., Karczeski, B., Sheridan, M., Robinson, T. E., Fallin, M. D., and Cutting, G. R. (2005) Phenotypic and genetic characterization of patients with features of “nonclassic” forms of cystic fibrosis. J Pediatr 146, 675–680. 43. Burns, J. L., Emerson, J., Stapp, J. R., Yim, D. L., Krzewinski, J., Louden, L., et al. (1998) Microbiology of sputum from patients at cystic fibrosis centers in the United States. Clin Infect Dis 27, 158–163. 44. Wilschanski, M., and Durie, P. R. (2007) Patterns of GI disease in adulthood associated with mutations in the CFTR gene. Gut 56, 1153–1163. 45. Kerem, E., Corey, M., Kerem, B. -S., Rommens, J., Markiewicz, D., Levison, H., et al. (1990) The relation between genotype and phenotype in cystic fibrosis – analysis of the most common mutation (deltaF508). N Engl J Med 323, 1517–1522.

372

Sosnay et al.

46. McKone, E. F., Emerson, S. S., Edwards, K. L., and Aitken, M. L. (2003) Effect of genotype on phenotype and mortality in cystic fibrosis: a retrospective cohort study. Lancet 361, 1671–1676. 47. Hamosh, A., Trapnell, B. C., Zeitlin, P. L., Montrose-Rafizadeh, C., Rosenstein, B. J., Crystal, R. G., et al. (1991) Severe deficiency of CFTR mRNA carrying nonsense mutations R553X and W1316X in respiratory epithelial cells of patients with cystic fibrosis. J Clin Invest 88, 1880–1885. 48. Hamosh, A., Rosenstein, B. J., and Cutting, G. R. (1992) CFTR nonsense mutations G542X and W1282X associated with severe reduction of CFTR mRNA in nasal epithelial cells. Hum Mol Genet 1, 542–544. 49. Ng, P. C., and Henikoff, S. (2006) Predicting the effects of amino acid substitutions on protein function. Annu Rev Genomics Hum Genet 7, 61–80. 50. Thusberg, J., and Vihinen, M. (2009) Pathogenic or not? And if so, then how? Studying the effects of missense mutations using bioinformatics methods. Hum Mutat 30, 703–714. 51. Gomez Garcia, E. B., Oosterwijk, J. C., Timmermans, M., van Asperen, C. J., Hogervorst, F. B., Hoogerbrugge, N., et al. (2009) A method to assess the clinical significance of unclassified variants in the BRCA1 and BRCA2 genes based on cancer family history. Breast Cancer Res 11, R8. 52. Bao, L., and Cui, Y. (2005) Prediction of the phenotypic effects of non-synonymous single nucleotide polymorphisms using structural and evolutionary information. Bioinformatics 21, 2185–2190. 53. Bromberg, Y., and Rost, B. (2007) SNAP: predict effect of non-synonymous polymorphisms on function. Nucleic Acids Res 35, 3823–3835. 54. Karchin, R., Diekhans, M., Kelly, L., Thomas, D. J., Pieper, U., Eswar, N., et al. (2005) LS-SNP: large-scale annotation of coding non-synonymous SNPs based on

55.

56.

57.

58.

59.

60.

61.

62.

63.

multiple information sources. Bioinformatics 21, 2814–2820. Ramensky, V., Bork, P., and Sunyaev, S. (2002) Human non-synonymous SNPs: server and survey. Nucleic Acids Res 30, 3894–3900. Reumers, J., Maurer-Stroh, S., Schymkowitz, J., and Rousseau, F. (2006) SNPeffect v2.0: a new step in investigating the molecular phenotypic effects of human non-synonymous SNPs. Bioinformatics 22, 2183–2185. Yue, P., Melamud, E., and Moult, J. (2006) SNPs3D: candidate gene and SNP selection for association studies. BMC Bioinformatics 7, 166. George Priya, D. C., Rajasekaran, R., Sudandiradoss, C., Ramanathan, K., Purohit, R., and Sethumadhavan, R. (2008) A novel computational and structural analysis of nsSNPs in CFTR gene. Genomic Med 2, 23–32. Dorfman, R., Nalpathamkalam, T., Taylor, C., Gonska, T., Keenan, K., Yuan, X. W., et al. (2010) Do common in silico tools predict the clinical consequences of amino-acid substitutions in the CFTR gene? Clin Genet 77, 464–473. Kelly, L., Fukushima, H., Karchin, R., Gow, J. M., Chinn, L. W., Pieper, U., et al. (2010) Functional hot spots in human ATPbinding cassette transporter nucleotide binding domains. Protein Sci 19, 2110–2121. Goldgar, D. E., Easton, D. F., Byrnes, G. B., Spurdle, A. B., Iversen, E. S., and Greenblatt, M. S. (2008) Genetic evidence and integration of various data sources for classifying uncertain variants into a single model. Hum Mutat 29, 1265–1272. Karchin, R., Monteiro, A. N., Tavtigian, S. V., Carvalho, M. A., and Sali, A. (2007) Functional impact of missense variants in BRCA1 predicted by supervised learning. PLoS Comput Biol 3, e26. Horaitis, O., Talbot, C. C., Jr., Phommarinh, M., Phillips, K. M., and Cotton, R. G. (2007) A database of locus-specific databases. Nat Genet 39, 425.

INDEX Note: The letters ‘f ’, ‘t’ and ‘n’ following locators refer to figures, tables and notes respectively.

A

Airway surface liquid (ASL) . . . . 4f, 6–9, 53, 77–79, 78f, 99 composition/function . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77 structure/function, assessment methods . . . . . . . . . . . . 88 volume-sensing signals/systems . . . . . . . . . . . . . . . . . . . 79 See also ASL/mucus transport rates, measurement methods Alcian blue . . . . . . . . . . . . . . . . 129, 132, 135, 136f, 137–138, 140n1, 177 Almac¸a, Joana, . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 249–264 Alternative CF model . . . . . . 53, 62, 64, 215, 312, 316–319 Amaral, Margarida, . . . . . . . . . . . . . . . . . . 193–211, 249–264, 281–283 American College of Medical Genetics (ACMG) . . . . . 356 Analysis of variance (ANOVA) . . . . . . . . . . . . . 202–206, 272 Animal models ferret . . . . . 53, 55, 64, 73, 103, 282, 312–314, 316–319, 322, 324–330 mouse . . . . . . 52–53, 55, 63–64, 73, 103, 282, 312–315, 318–320, 323 pig . . . . . . . . . . 11, 53, 55, 64, 73, 94, 98, 103, 105, 282, 312–314, 316–319, 322, 329 See also CF animal models, comparative biology of Anion transport inhibitors . . . . . . . . . . . . . . . . . . . . . . . . . . . 95 ANOVA, see Analysis of variance (ANOVA) Antibiotics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 294 Antibody generation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 338 Anti-inflammatory agents. . . . . . .54–55, 62–63, 62f, 68–69 APCI, see Atmospheric pressure chemical ionization (APCI) Appel, Nicole, . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 249–264 Arginine . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 139, 218, 238 ASL, see Airway surface liquid (ASL) ASL/mucus transport rates, measurement methods ASL, composition/function of . . . . . . . . . . . . . . . . . . . . 77 ASL height, variations in normal/CF airway . . . . . . . 78 ASL and human airway cultures . . . . . . . . . . . . . . 78f ASL volume-sensing signals/systems . . . . . . . . . . . 79 XZ laser scanning confocal microscopy . . . . . . . . . 79 ASL labeling for confocal and epifluorescence microscopy . . . . . . . . . . . . . . . . . . . . . . . . . . . . 82–83 ASL structure/function, assessment methods . . . . . . . 88 fluorescent probes/dyes, choice of . . . . . . . . . . . . . . 79–82 ASL pH, mesurement of . . . . . . . . . . . . . . 81–82, 81f dextrans. . . . . . . . . . . . . . . . . . . . . . . . . . . . . .79–81, 80f mucus labeling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 82 Texas Red . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79 materials ASL height measurement with confocal microscopy . . . . . . . . . . . . . . . . . . . . . . . . . . . . 84–86 mucus transport, measurement with epifluorescent microscopy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 86

A549 cells . . . . . . 251–252, 251f, 253f, 255–256, 258f, 260, 261f, 287 Achromobacter xylosoxidans . . . . . . . . . . . . . . . . . . . 11, 144, 155 ACMG, see American College of Medical Genetics (ACMG) Adenovirus . . . . . . . . . . . . . . . . 287–288, 288f, 296–297, 304 Affinity chromatography . . . . . . . . . . . . . . . . . . . . . . . 235–236 See also Immobilized metal affinity chromatography (IMAC) Agarose–polyacrylamide gel electrophoresis . . . . . . 130–131, 135–138 Air–liquid interface (ALI) medium . . . . . . . 290, 291t–292t, 293, 301 Airway epithelia epithelium . . . . . . . . 7, 174–177, 179–180, 182–183, 362 surface liquid . . . . . . . . . . . . . . . . . . . . . . . . . . 4, 6–9, 53, 78 Airway glands species differences in rabbit, “obligate nose breather” . . . . . . . . . . . . . . . . 96 structure/distribution. . . . . . . . . . . . . . . . . . . . . . . . . 94f, 96 human trachea, components . . . . . . . . . . . . . . . . . . . 96 Airway submucosal gland secretion, measurement of agonists/inhibitors of secretion . . . . . . . . . . . . . . . . . . . 102 airway glands species differences in . . . . . . . . . . . . . . . . . . . . . . . . . . 96 structure/distribution . . . . . . . . . . . . . . . . . . . . . 94f, 96 composition/physical properties of mucus, measure of . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 98 gland mucus vs. sputum . . . . . . . . . . . . . . . . . . . . . . . . . . 96 materials equipments, see Equipments for maintaining/imaging tissues reagents. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .101–102 mechanisms of fluid secretion . . . . . . . . . . . . . . . . . . 95–96 methods, see Methods for measure of submucosal gland secretion mucus and airway sterility . . . . . . . . . . . . . . . . . . . . . 94–95 CFTR, cause of infection . . . . . . . . . . . . . . . . . . . . . 95 mucus clearance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 95 primary gland mucus . . . . . . . . . . . . . . . . . . . . . . . . . 95 mucus secretion, examination . . . . . . . . . . . . . . . . . . 93–94 human airway submucosal gland (microdissected) . . . . . . . . . . . . . . . . . . . . . . . . . . 94f from a pig trachea . . . . . . . . . . . . . . . . . . . . . . . . . . . 94f optical measurement method . . . . . . . . . . . . . . . . . . 93–94 previous methods, see Previous methods of measuring airway mucus secretion single gland optical method, advantages/ limitations . . . . . . . . . . . . . . . . . . . . . . . . . . . . 98–99

M.D. Amaral, K. Kunzelmann (eds.), Cystic Fibrosis, Methods in Molecular Biology 742, c Springer Science+Business Media, LLC 2011 DOI 10.1007/978-1-61779-120-8, 

373

CYSTIC FIBROSIS

374 Index

ASL/mucus transport rates (continued) methods ASL height measurement with confocal microscopy . . . . . . . . . . . . . . . . . . . . . . . . . . . . 86–87 fluorescent imaging of rotational mucus transport . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87–88 mucus transport rates, measurement of . . . . . . . . . 84, 85f determination of MCC . . . . . . . . . . . . . . . . . . . . . . . 84 use of PFC FC-72/FC-77 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83 XZ confocal microscopy and ASL measurement . . . 81f, 83–84 Aspergillus fumigatus . . . . . . . . . . . . . . . . . . . . . . . . . . . 144, 147 Assessment of CF proteome, quantitative methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . 238–239 enzymatic labeling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 239 label free techniques . . . . . . . . . . . . . . . . . . . . . . . . . . . . 239 metabolic labeling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 238 post-cell lysis labeling technologies . . . . . . . . . . . . . . . 239 SILAC approach . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 238 Astarita, Giuseppe, . . . . . . . . . . . . . . . . . . . . . . . . . . . . 265–277 Atmospheric pressure chemical ionization (APCI) . . . . . . . . . . . . . . . . . . . 267–268, 273–275 Automated fluorescence scanning microscopy . . . . . . . . . 250 Autopsy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 289 Azoospermia . . . . . . . . . . . . . . . . . . . . . . . . . . . . 359–362, 363t

B Bacchetta, Marc, . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 173–184 Bacterial pathogens in CF, methods of classification CF pathogen identification Koch-Henle postulates . . . . . . . . . . . . . . . . . . . . . . 144 Koch’s criteria . . . . . . . . . . . . . . . . . . . . . . . . . . 145–146 sputum culture of CF patient with P. aeruginosa lung infection . . . . . . . . . . . . . . . . . . . . . . . . . . . 146f isolation/identification from CF lung media and culture conditions . . . . . . . . . . . . . 147–149 microscopy of gram-stained specimens . . . 146–147, 148f molecular biology methods vs. conventional methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . 149–150 materials biofilm detection in sputum and tissue . . . . 151–152 DNA typing by PFGE . . . . . . . . . . . . . . . . . . 154–155 ELISA for measuring IgG/IgA antibodies . . . . . 155 recA-gene PCR/RFLP-based identification . . . . . . . . . . . . . . . . . . . . . . . 153–154 in vitro flow cell biofilm . . . . . . . . . . . . . . . . . 152–153 methods, see Methods for identification of CF pathogens microorganisms, role in pathogenesis . . . . . . . . . 143–144 visualization in sputum and lung tissue DNA probes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 150 microscopy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 150 in vitro study of biofilms . . . . . . . . . . . . . . . . . . . . 150–151 BAL, see Bronchoalveolar lavage (BAL) Balch, William . . . . . . . . . . . . . . 189–191, 227–240, 335–351 “Basal” secretion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 104 Batch effect . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 200, 202 Bayesian statistical models . . . . . . . . . . . . . . . . . . . . . . . . . . 366 BEGM, see Bronchial epithelial growth medium (BEGM) BEGM/ALI medium, composition/ differences . . . . . . . . . . . . . . . . . . . . . . . . 291t–292t Benos, Dale J., . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10, 35–49 Berdiev, Bakhrom K., . . . . . . . . . . . . . . . . . . . . . . . . . 10, 35–49

Bicarbonate-free buffers (1-HEPES and 25-HEPES) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 102 Bidimensional SDS-polyacrylamide gel electrophoresis (2D SDS-PAGE) . . . . . . . . . . . . . . . . 70, 213–214 Bilayers. . . .36, 38–40, 44n2, 45n10, 45n11, 45n12, 46n13, 46n14, 47f See also Lipid bilayers Biofilms . . . . 4, 10, 145–146, 148f, 150–151, 150–151, 153, 155–156, 157f–158f, detection in sputum and tissue . . . . . . . . . . . . . . . 151–152 formation process, stages . . . . . . . . . . . . . . . . . . . . . . . . 151 Bioinformatic(s) analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 366 tools . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 366 Biomarker discovery, techniques LC-MS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 266–267, 266f MALDI-TOF-ClinProToolsTM . . . . . . . . . . . 266, 266f Biomarkers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 229, 265–266 BioworksTM . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 60 Bjarnsholt, Thomas, . . . . . . . . . . . . . . . . . . . . . . . . . . . 143–168 Bottom-up technology . . . . . . . . . . . 230, 232–233, 236–239 advantages/limitations. . . . . . . . . . . . . . . . . . . . . . . . . . .237 SEQUEST . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 237 Boucher, R. C., . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3–12 Braakman, Ineke, . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 335–351 Brodsky, Jeffrey L., . . . . . . . . . . . . . . . . . . . . . . . . . . . . 335–351 Bronchial epithelial growth medium (BEGM) . . . . 89, 290, 291t, 292t, 293, 301 Bronchoalveolar lavage (BAL) . . . . . 53, 55–56, 62f, 64–65, 70, 229 Burkholderia cepacia . . . . .10, 144, 147, 153, 159, 162f–163f, 294, 363t

C Ca2+ . . . . . . . . . . . . . . . . . . . 7, 9–10, 21, 36–37, 79, 113–125 Calcium-activated chloride channel (CaCC) . . . . . 7–10, 96 Calcium signals in normal/CF human cultures, measurements of epithelial polarization, effect on calcium signals . . . . 114 ER Ca2+ storage expansion, mechanism . . . . . . . . . . 114 materials GPCR-dependent Ca2+ i signal, measurement of . . . . . . . . . . . . . . . . . . . . . 115–116 HBE cultures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 115 methods Ca2+ i signals, measurement of, see Measurement of calcium signals (intracellular) HBE cultures . . . . . . . . . . . . . . . . . . . . . . . . . . 116–117 and mitochondrial production of ROS, correlation . . . . . . . . . . . . . . . . . . . . . . . . . . 114–115 Calu-3 cells . . . . . . . . . . . . . . 95–96, 218, 267, 342, 344, 346, 349f, 350 cAMP . . . . . . . . . . . 10, 41, 79, 252, 312, 315–316, 319, 321 Candidate gene discovery tools ANOVA analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . 202–203 gene pattern . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 196 gene set and pathway analysis . . . . . . . . . . . . . . . 196, 203 DAVID . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 206 GeneGo MetaCore . . . . . . . . . . . . . . . . . . . . . . . . . . 206 GSEA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 205 IPA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 203–205, 204f STRING and related databases . . . . . . . . . . 206–209 Castellani, Carlo, . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 355–369 CCD, see Charge-coupled device (CCD) Cell surface protein detection . . . . . . . . . . . . . . 338–339, 341

CYSTIC FIBROSIS 375 Index Cellular networks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 190 Census software . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 239–240 CF, see Cystic fibrosis (CF) CF animal models, comparative biology of CF phenotype across species . . . . . . . . . . . . . . . . . . . . 314t cross-species analysis of CFTR processing . . . . . . . . 319 general species characteristics of CFTR . . . . . . . . . . 313t materials cross-species analysis of CFTR processing . . . . 321, 324–327 cross-species analysis of processing efficiency/stability of CFTR . . . . . . . . . . 321–322 tracheal xenograft model, cross-species analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 320–321 methods cross-species analysis of CFTR processing . . . . . . . . . . . . . . . . . . . . . . . . . . 324–327 cross-species analysis of processing efficiency/stability of CFTR . . . . . . . . . . 327–329 tracheal xenograft model, cross-species analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 322–324 methods for generating larger animal models choice of alternative species, parameters . . . . . . . 315 ferret model of CF . . . . . . . . . . . . . . . . . . . . . . 316–318 future directions . . . . . . . . . . . . . . . . . . . . . . . . 318–319 porcine models of CF . . . . . . . . . . . . . . . . . . . . . . . . 316 murine models of CF . . . . . . . . . . . . . . . . . . . . . . . 312–315 bacterial clearance defects in lungs . . . . . . . . . . . . 315 conditional CFTR knockout mouse model . . . . 315 general abnormalities . . . . . . . . . . . . . . . . . . . . . . . . 312 nasal bioelectric defects . . . . . . . . . . . . . . . . . . . . . . 315 tracheal xenograft model, cross-species analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 319–320 CFC, see CFTR Folding Consortium (CFC) CF, clinical characteristics . . . . . . . . . . . . . . . . . . . . . . 362–364 CFC methods for study of CFTR folding/correction biogenesis of CFTR ERAD . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 336 F508del mutation . . . . . . . . . . . . . . . . . . . . . . . . . . . 336 CFC web site . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 337 CFTR membrane expression determination, methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . 339–341 cell surface detection of native CFTR . . . . . . . . . 341 measuring CFTR cell surface density by ELISA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 339–341 schematic model of immunoperoxidase assay . . 340f CFTR reagents CFC Roadmap . . . . . . . . . . . . . . . . . . . . . . . . . 338–339 CFTR antibodies . . . . . . . . . . . . . . . . . . . . . . . 337–338 CFTR proteins . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 338 drug discovery process . . . . . . . . . . . . . . . . . . . . . . 336–337 goals of CFC . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 337 materials for detection of HA-CFTR . . . . . . . . . . . . . . . . . . 342 for detection of native CFTR . . . . . . . . . . . . 342–344 methods for detection of HA-CFTR . . . . . . . . . . . . . 344–346 for detection of native CFTR . . . . . . . . . . . . 346–350 CFC roadmap . . . . . . . . . . . . . . . . . . . . . . . . . . . . 283, 338–339 F508del correction approaches, impact on drug development . . . . . . . . . . . . . . . . . . . . . . . . . . . . 339 Modulator Roadmap . . . . . . . . . . . . . . . . . . . . . . . . . . . . 339 CF lipidomics . . . . . . . . . . . . . . . . . . . . . . . . . . . . 191, 265–277 biomarker discovery, techniques LC-MS . . . . . . . . . . . . . . . . . . . . . . . . . . 266–267, 266f MALDI-TOF-ClinProToolsTM . . . . . . . . 266, 266f

drawbacks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 266 materials biological material . . . . . . . . . . . . . . . . . . . . . . . . . . . 267 equipment for LC/MSn analysis . . . . . . . . . . . . . . 268 MALDI-TOF-ClinProToolsTM , instruments for . . . . . . . . . . . . . . . . . . . . . . . . . . 268 matrix and calibrants for MALDI-TOF . . . . . . . 268 organic extraction and SPE . . . . . . . . . . . . . . 267–268 reagents. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 268–269 supplies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 269 methods, see Lipidomic methods CFMD, see CF Mutation Database (CFMD) CF models animal models ferret . . . . . . . . . . . 53, 55, 64, 73, 103, 282, 312–314, 316–319, 322–326, 328–330 mouse . . . 52–53, 55, 63–64, 73, 103, 282, 312–315, 318–320, 323 pig . . . . . . . 11, 53, 55, 64, 73, 94, 98, 103, 105, 282, 312–314, 316–319, 322, 329 CF Mutation Database (CFMD) . . . . . . . . . 283, 356, 357f, 367, 368t CF pathophysiology defective ion transport and lung disease, link . . . . . . 3–4 mucociliary clearance mechanisms, normal/CF lung . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4f disease management therapies, aim/examples . . . . . . . . . . . . . . . . . . . . . . . . 5 fluid and mucus . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8–9 fluid transport impermeable/permeable fluorescent dyes, use of . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 Z stack confocal microscopy, advantage . . . . . . . . . . 8 inflammatory response, innate/acquired . . . . . . . . . 10–11 β-ENaC overexpressing mice, study . . . . . . . . . . . . 11 ceramide, role . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 identification of pathogens, methods . . . . . . . . 11–12 ion transport and airway surface liquid . . . . . . . . . . . . 6–7 CaCC pathway, treatment of CF . . . . . . . . . . . . . . . . 7 chloride secretion, routes . . . . . . . . . . . . . . . . . . . . . . . 7 fetal lung secretory process . . . . . . . . . . . . . . . . . . . 6–7 ion transport in vivo/in vitro . . . . . . . . . . . . . . . . . . . . . 7–8 human-cultured bronchial epithelial cells, development of . . . . . . . . . . . . . . . . . . . . . . . . . . 7–8 nasal PD measurements . . . . . . . . . . . . . . . . . . . . . . . . 7 localization of CFTR . . . . . . . . . . . . . . . . . . . . . . . . . . . 5–6 mechanical sensitivity (CaCC pathway) ATP mechanism . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 (Ca2+ )i , role of . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 pathway interactions (CaCC,CFTR, and ENaC) . . . 10 CF research, see HAE cell models for CF research CFTR expression . . . . . 17, 19–20, 257, 258f, 281, 285, 364 CFTR Folding Consortium (CFC) . . . . . . . . . 282, 335–351 CFTR folding/correction, study methods biogenesis of CFTR ERAD . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 336 F508del mutation . . . . . . . . . . . . . . . . . . . . . . . . . . . 336 CFC web site . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 337 CFTR membrane expression determination, methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . 339–341 cell surface detection of native CFTR . . . . . . . . . 341 measuring CFTR cell surface density by ELISA . . . . . . . . . . . . . . . . . . . . . . . . . . 339–341 schematic model of immunoperoxidase assay . . 340f CFTR reagents CFC Roadmap . . . . . . . . . . . . . . . . . . . . . . . . . 338–339

CYSTIC FIBROSIS

376 Index

CFTR folding/correction, study methods (continued) CFTR antibodies . . . . . . . . . . . . . . . . . . . . . . . 337–338 CFTR proteins . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 338 drug discovery process . . . . . . . . . . . . . . . . . . . . . . 336–337 goals of CFC . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 337 materials for detection of HA-CFTR . . . . . . . . . . . . . . . . . . 342 for detection of native CFTR . . . . . . . . . . . . 342–344 methods for detection of HA-CFTR . . . . . . . . . . . . . 344–346 for detection of native CFTR . . . . . . . . . . . . 346–350 CFTR immunostaining confocal microscopy, advantages . . . . . . . . . . . . . . . . . . . 23 endogenous CFTR expression . . . . . . . . . . . . . . . . . . . . 17 in cryosections of human tissues . . . . . . . . . . . . 23–24 in fresh well-differentiated hAE cultures . . . . 25–26 in frozen-fixed/paraffin-embedded/ well-differentiated hAE cultures . . . . . . . . . . . . 26 in formalin-fixed, paraffin-embedded human tissues . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25 heterologous CFTR expression. . . . . . . . . 17, 19–20, 19f in cell cultures using anti-CFTR antibodies . . . . . 26 of transgenic human in frozen mouse tissues . . . . . . . . 28 CFTR knockout mouse model . . . . . . . . . . . . . . . . . . . . . . 315 CFTR localization in cultured cells/tissues in freshly isolated/frozen human airway tissues . . . . . 18f in freshly isolated/frozen human tissues and airway primary cultures . . . . . . . . . . . . . . . . . . . . . . . . . . 16f materials cell cultures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20–21 frozen and paraffin-embedded primary cultures . . 21 human tissue specimens . . . . . . . . . . . . . . . . . . . . . . . 20 immunostaining reagents . . . . . . . . . . . . . . . . . . 21–22 mouse tissue specimens . . . . . . . . . . . . . . . . . . . . . . . 21 methods Extope-CFTR, visualization of . . . . . . . . . . . . 26–28 imaging of GFP-tagged CFTR . . . . . . . . . 17–19, 28 immunofluorescence staining, see CFTR immunostaining CFTR mutations . . . . . . . . . . 283, 318–319, 356–357, 357f, 359–364, 359f, 363t, 366, 368 classification . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 364 “CFTRopathies,” . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 361 CFTR polymorphisms . . . . . . . . . . . . . . . . . . . . . . . . . 358, 366 CFTR processing . . . . . . . . . . . . . 5, 311, 319, 321, 324–327, 328f, 337, 365t CFTR regulation of epithelial sodium channel CFTR and ENaC interaction b-ENaC co-immunoprecipitation with CFTR. . . . . . . . . . . . . . . . . . . . . . . . . . . . . .48f CFTR modulation of abg-ENaC in bilayers . . . . 47f materials cell culture, transient transfection . . . . . . . . . . . . . . 37 oocyte preparation and injection with cRNAs . . . 36 planar lipid bilayers . . . . . . . . . . . . . . . . . . . . . . . . . . . 36 two-electrode voltage clamp . . . . . . . . . . . . . . . . 36–37 methods bilayer incorporation . . . . . . . . . . . . . . . . . . . . . . . . . . 39 cell culture, transient transfection, co-immunoprecipitation . . . . . . . . . . . . . . . . . . . 42 planar lipid bilayer system . . . . . . . . . . . . . . . . . . 38–39 preparation and injection of xenopus oocytes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37–38 preparation of Xenopus oocyte membrane vesicles . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38 sample preparation by Western blotting . . . . . 42–43

SDS-PAGE and transfer . . . . . . . . . . . . . . . . . . . . . . 43 two-electrode voltage clamp recordings of ENaC. . . . . . . . . . . . . . . . . . . . . . . . . . . . . .40–42 two-electrode voltage clamp system . . . . . . . . . . . . 40 Western blotting for CFTR and ENaC . . . . . 43–44 CFTR trafficking, assay cell seeding onto pre-coated LabTeks . . . . . . . . 256–257 image acquisition automatic image acquisition, examples . . . 257–258, 258f confocal microscopy . . . . . . . . . . . . . . . . . . . . . . . . . 257 image processing and data analysis . . . . . . . . . . . 258–260 immunostaining of cells . . . . . . . . . . . . . . . . . . . . . . . . . 257 CFTR variants . . . . . . . . . . . . . . 190, 283, 340, 345, 355–369 See also Evaluation of disease liability of CFTR variants Chanson, M., . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8, 173–184 Chaperone systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 229 Charge-coupled device (CCD) . . . . . . . . . . . . . . . 58, 84, 105 Chemical separation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 233 Cho, Hyungju, . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93–109 Choi, Jae Young, . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93–109 Clarke, Luka A., . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 193–211 Classification of pathogens in CF CF pathogen identification Koch-Henle postulates . . . . . . . . . . . . . . . . . . . . . . 144 Koch’s criteria . . . . . . . . . . . . . . . . . . . . . . . . . . 145–146 sputum culture of CF patient with P. aeruginosa lung infection . . . . . . . . . . . . . . . . . . . . . . . . . . . 146f isolation/identification from CF lung media and culture conditions . . . . . . . . . . . . . 147–149 microscopy of gram-stained specimens . . . 146–147, 148f molecular biology methods vs. conventional methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . 149–150 materials biofilm detection in sputum and tissue . . . . 151–152 DNA typing by PFGE . . . . . . . . . . . . . . . . . . 154–155 ELISA for measuring IgG/IgA antibodies . . . . . 155 recA-gene PCR/RFLP-based identification for B.cepacia complex . . . . . . . . . . . . . . . . . . . 153–154 in vitro flow cell biofilm . . . . . . . . . . . . . . . . . 152–153 methods, see Methods for identification of CF pathogens microorganisms, role in pathogenesis . . . . . . . . . 143–144 visualization in sputum and lung tissue DNA probes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 150 microscopy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 150 in vitro study of biofilms . . . . . . . . . . . . . . . . . . . . 150–151 ClinProToolsTM software . . . . . . . . . . . . 266, 266f, 268, 272, 273f, 276n7 Clunes, Mark T., . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3–12 Co-immunoprecipitation . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48f Confocal microscopy . . . . . . . . 5, 8, 17, 22–24, 26–30, 26–30, 78f, 79, 81, 83–87, 90, 121, 257, 349 scanning laser microscopy . . . . . . . . . . . . . . . . . . . 153, 158 vs. epifluorescence microscopy . . . . . . . . . . . . . . . . . . . . 23 Conrad, Christian,. . . . . . . . . . . . . . . . . . . . . . . . . . . . .249–264 “Consensus Protocols for CFTR Expression and Function Research,” . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 281 Copenhagen criteria . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 149 Corey, Mary, . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 355–369 Cormet-Boyaka, Estelle, . . . . . . . . . . . . . . . . . . . . . . . . . 35–49 “Corrector” drugs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 Crespin, S., . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 173–184 Cuthbert, Alan W., . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93–109

CYSTIC FIBROSIS 377 Index Cutting, Garry R., . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 355–369 Cystic fibrosis bronchial epithelial (CFBE) cells . . 340, 342, 346, 349f Cystic fibrosis (CF) . . . . . . . . . . . 1–185, 187–278, 281–283, 285–309, 311–331, 336–337, 339, 342, 355–364, 366–369 infected airways microorganisms in . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 inflammation identification of pathogens, methods . . . . . . . . 11–12 issues . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 therapies traditional/antibiotic . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 See also CF animal models, comparative biology of; CF pathophysiology; Classification of pathogens in CF; Inflammation in CF, methods of evaluation Cystic Fibrosis Protocols and Diagnosis . . . . . . . . . . . . . . . . 281 Cystic fibrosis transmembrane conductance regulator (CFTR) antibodies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21 constructs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 250 expression . . . . . . . . . . . 5, 10, 15, 17–29, 41, 96, 96, 252, 257, 258f, 281–282, 285–286, 330, 339–341, 364 immunostaining . . . . . . . . 15–18, 23, 26, 28, 30–31, 257 localization . . . . . . . . . . . . . . . . . . . . . 5–6, 15–32, 337, 365 mutations . . . . . . . . . . . . . . 283, 318–319, 356–357, 357f, 359–364, 359f, 363t, 366, 368 polymorphisms . . . . . . . . . . . . . . . . . . . . . . . . . . . . 358, 366 processing . . . . . . . . . . . 5, 311, 319, 321, 324–327, 328f, 337, 365t secretomics of . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 250–252 structure of . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 346 trafficking . . . . . . . . . . . . . . . . . . . . . . . . . 19, 239, 249–264 “corrector” drugs, discovery of . . . . . . . . . . . . . . . . . . 6 F508del CFTR . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 R117H mutation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 variants . . . . . . . . . . . . . . . . . 190, 283, 340, 345, 355–369 Cytokines . . . . . 11, 52–54, 56, 60, 62–65, 73, 179, 204–206

production of polyclonal antibodies . . . . . . . . . . . 343 methods cell culture and lysis . . . . . . . . . . . . . . . . . . . . . . . . . 346 choice of antigen . . . . . . . . . . . . . . . . . . . . . . . . . . . . 346 coupling of peptide to KLH . . . . . . . . . . . . . . . . . . 347 ELISA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 348, 349f immunoblot . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 350 immunofluorescence . . . . . . . . . . . . . . . . . . . . 349f, 350 immunoprecipitation . . . . . . . . . . . . . . . . . . . . 348–350 production of antibodies in rabbits . . . . . . . . 347–348 synthesis of antigen . . . . . . . . . . . . . . . . . . . . . . . . . . 347 Detergent-resistant membranes (DRMs) . . . . . . . . 220–221 DIC, see Differential interference contrast (DIC) Differential expression . . . . . . . . . . . . . . . 202–203, 205, 205f Differential interference contrast (DIC) . . . . . . . . . . . . 30n12 Differentiation, see Differentiation of hAEC, study approaches Differentiation of hAEC, study approaches cytokine and mucin production . . . . . . . . . . . . . . . . . . 179 quantification by ELLA. . . . . . . . . . . . . . . . . . . . . . 179 immunohistochemical detection of markers . . . . . . . 178 monitoring gap junctional intercellular communication . . . . . . . . . . . . . . . . . . . . . 178–179 morphology of hAEC . . . . . . . . . . . . . . . . . . . . . . 176–177 long-term differentiation of MucilAirTM hAEC cultures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 177f Digital microscopy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 105 Disease liability . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 355 See also Evaluation of disease liability of CFTR variants DNA microarray technology . . . . . . . . . . . . . . . . . . . . . . . . 228 Dorfman, Ruslan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 355–369 Dot/slot blot . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 129, 134–135 “Double trypsinization” . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 301 DRMs, see Detergent-resistant membranes (DRMs) 2D SDS-PAGE, see Bidimensional SDS-polyacrylamide gel electrophoresis (2D SDS-PAGE) Dudez, T., . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 173–184

D

ECD, see Electron capture dissociation (ECD) ECFP, see Enhanced cyan fluorescent protein (ECFP) Edelman, Aleksander, . . . . . . . . . . . . . . . . . . . . . . . . . . 213–224 eggNOG, see Evolutionary genealogy of genes: non-supervised orthologous groups (eggNOG) Electron capture dissociation (ECD) . . . . . . . . . . . . . . . . . 237 Electron transfer dissociation (ETD) . . . . . . . . . . . . 237, 239 Electrospray ionization (ESI) . . . . . . . 75n19, 230, 266f, 267 ELLA, see Enzyme-linked lectin assay (ELLA) EMBL, see European Molecular Biology Laboratory (EMBL) ENaC, see Epithelial Na+ channel (ENaC) ENaC functional genomics assay . . . . . . . 252–253, 260–262 cell seeding onto pre-coated LabTeks . . . . . . . . . . . . . 260 data quantification . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 262 live-cell FMP-based assay . . . . . . . . . . . . . . . . . . 253f, 260 microscopy-based screening assay . . . . . . . . . . . . 260–262 Endoplasmic reticulum-associated degradation (ERAD) . . . . . . . . . . . . . . . . . . . . . . . 319, 336, 339 Endoplasmic reticulum (ER) . . . 17, 19, 113, 219, 235, 252, 319, 327, 336 Engelhardt, John F., . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 311 Enhanced cyan fluorescent protein (ECFP) . . . . . . . . . . . . 10 Enhanced yellow fluorescent protein (EYFP) . . . . . . . . . . 10 Enzymatic labeling technologies . . . . . . . . . . . . . . . . . . . . . 239 Enzyme-linked lectin assay (ELLA) . . . . . . . . . . . . . . . . . 179

Dahim`ene, Shehrazade, . . . . . . . . . . . . . . . . . . . . . . . . 249–264 Database for annotation, visualization, and integrated discovery (DAVID) . . . . . . . . . . . . . . . . . . 196, 206 DAVID, see Database for annotation, visualization, and integrated discovery (DAVID) Davis, Pamela B., . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51–75 “Declumping” process . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 301 Deep sequencing technology . . . . . . . . . . . . . . . . . . . . . . . . 194 Defective ion transport. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .3 Dehydration (airway) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 Denufosol therapy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 Detection of HA-CFTR materials . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 342 methods cell surface density measurement . . . . . . . . . 344–345 CFTR internalization/cell surface stability measurement . . . . . . . . . . . . . . . . . . . . . . . 345–346 Detection of native CFTR materials coupling of peptide . . . . . . . . . . . . . . . . . . . . . . . . . . 343 ELISA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 343 immunoblot . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 344 immunofluorescence . . . . . . . . . . . . . . . . . . . . . . . . . 344 immunoprecipitation . . . . . . . . . . . . . . . . . . . . . . . . 344

E

CYSTIC FIBROSIS

378 Index

Epithelial Na+ channel (ENaC) . . . . . . . . . . . 4–5, 7, 10–11, 35–49, 52, 89, 95, 249–264, 288, 309, 322, 362 Equipments for maintaining/imaging tissues cameras . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 100 microscopes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 100 optical chambers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 101 experimental set up . . . . . . . . . . . . . . . . . . . . . . . . . 101f physiological chambers . . . . . . . . . . . . . . . . . . . . . . . . . . 100 ER, see Endoplasmic reticulum (ER) ERAD, see Endoplasmic reticulum-associated degradation (ERAD) ESI, see Electrospray ionization (ESI) ESI technique . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 231 ETD, see Electron transfer dissociation (ETD) European Molecular Biology Laboratory (EMBL) . . . . 206 Evaluation of disease liability of CFTR variants clinical characteristics . . . . . . . . . . . . . . . . . 362–364, 363t pancreatic mutations, study . . . . . . . . . . . . . . . . . . . 364 databases, types . . . . . . . . . . . . . . . . . . . . . . . 367–368, 368f CFMD . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 367 LSDB . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 367 OMIM . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 367 direct assays of in vivo CFTR function NPD, limitations . . . . . . . . . . . . . . . . . . . . . . . . . . . . 362 sweat chloride measurement . . . . . . . . . . . . . 361–362 disease liability CFTR genotype and CF phenotype, correlation . . . . . . . . . . . . . . . . . . . . . 358–360, 359f CFTR mutations, identification of . . . . . . . . . . . . 356 characterization of genotypes based on CF mutations . . . . . . . . . . . . . . . . . . . . . 356–357, 357f definition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 355 effect of variants on CFTR function . . . . . . 357–358 example . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 355 Hardy-Weinberg law . . . . . . . . . . . . . . . . . . . 356, 356f functional assessment CFTR mutations, classification . . . . . . . . . 364, 365t mutation prediction algorithm . . . . . . . . . . . . . . . . . . . 369f predictive methods . . . . . . . . . . . . . . . . . . . . . . . . . 364–367 Bayesian statistical models, development of . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 366–367 bioinformatic in silico analysis . . . . . . . . . . . . . . . . 366 NMRD . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 364–366 tools for evaluation . . . . . . . . . . . . . . . . . . . . . . . . . 360–361 CF-causing CFTR mutation, limitations . . 360–361 Evaluation of inflammation in CF, methods assessment of BAL, meaurement of cytokines . . . . . . . . . . . . . . . . 53 bronchoscopy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53 materials animal models, stimulation, and treatment with compounds . . . . . . . . . . . . . . . . . . . . . . . . . . . 55–56 cell culture, stimulation, and treatment with compounds . . . . . . . . . . . . . . . . . . . . . . . . . . . 54–55 cytokines/chemokines secretion, measurement of . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56 gene array analyses . . . . . . . . . . . . . . . . . . . . . . . . . . . 59 histology and immunohistochemical staining . . . . 56 one/two-dimensional SDS-PAGE . . . . . . . . . . . . . 57 promoter/transcription factor activity, evaluation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 58 proteomic analyses . . . . . . . . . . . . . . . . . . . . . . . . 59–60 Western blot analysis . . . . . . . . . . . . . . . . . . . . . . 57–58 methods animal maintenance and treatments . . . . . 62f, 64–65

cell culture maintenance and treatments . . . . . . . . . . . . . . . . . . . . . . . 60f–61f, 63 cytokine production, measurement of . . . . . . . . . . . 65 gene array analysis . . . . . . . . . . . . . . . . . . . . . . . . 69–70 histological analysis of lung tissue . . . . . . . . . . . 65–66 promoter/transcription factor activity, analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67–68 proteomic analysis . . . . . . . . . . . . . . . . . . . . . . . . 70–72 Western blot analysis . . . . . . . . . . . . . . . . . . . . . . 66–67 models ferret/pig models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53 humans/mouse models . . . . . . . . . . . . . . . . . . . . 52–53 immortalized epithelial cell pair models, areas of research . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52 study levels/mechanisms . . . . . . . . . . . . . . . . . . . . . . 60–63 Evolutionary genealogy of genes: non-supervised orthologous groups (eggNOG) . . . . . . . 208–209 Exocrine secretion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 316–317 Extope-CFTR . . . . . . . . . . . . . 19f, 20–21, 23, 26–27, 31n20 Extraction methods of hAE cell cultures . . . . . . . . . . . . . 299f cryopreservation of cells . . . . . . . . . . . . . . . . . . . . . . . . . 302 isolation of hAE cells . . . . . . . . . . . . . . . . . . . . . . . 298–301 plating cells . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 301 surgical pathology/autopsy . . . . . . . . . . . . . . . . . . . . . . . 289 thawing cells . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 302 type I/III collagen coating of plastic dishes . . . . . . . . 298 type IV collagen coating of porous supports . . . . . . . 298 EYFP, see Enhanced yellow fluorescent protein (EYFP)

F FC-72 PFC. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .83, 90n5 F508del-CFTR . . . . . . . . . 19, 218, 229, 250–252, 254, 256, 267, 282, 318–319, 336–337, 339–341 Ferret, . . . 53, 55, 64, 73, 103, 282, 312–314, 316–319, 322, 324–326, 328–330 Fetal CF lungs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 Fisher, John T., . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 311–331 FLIPR membrane potential (FMP) . . . . . . . . . 252, 255, 260 Fluorescent in situ hybridization (FISH) . . . . . . . . 150–152, 155–156, 157f Fluorophore . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29n9 FMP, see FLIPR membrane potential (FMP) Folch’s method . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 270 Frizzell, Raymond A.,. . . . . . . . . . . . . . . . . . . . . . . . . .335–351 Fulcher, M. Leslie, . . . . . . . . . . . . . . . . . . . . . . . . . . . . 285–309 Functional genomics . . . . . . . . . . . . . . . . . . . . . . . . . . . 249–264 See also ENaC functional genomics assay Fura-2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9, 115–121, 120f

G Gel-forming mucins . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 127 GeneChip . . . . . . . . . . . . . . . . . . . . . . . . . . . 194–196, 200–201 GeneGo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 196, 206, 206f Gene set enrichment analysis (GSEA) . . . . . . . . . . 196, 202, 204f, 205 Genomics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 190 See also Genomics assays to study CFTR traffic and ENaC function Genomics assays to study CFTR traffic and ENaC function functional genomics of ENaC . . . . . . . . . . . . . . . 252–253 live-cell FMP-based assay . . . . . . . . . . . . . . . . . . . 252f large-scale screening applications ‘reverse transfection,’. . . . . . . . . . . . . . . . . . . . . . . . .250

CYSTIC FIBROSIS 379 Index materials equipment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 255 reagents. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .253–255 methods functional assay for ENaC . . . . . . . . . . . . . . . 260–262 spotting of siRNAs . . . . . . . . . . . . . . . . . . . . . 255–256 traffic assay for CFTR, see CFTR trafficking, assay secretomics of CFTR . . . . . . . . . . . . . . . . . . . . . . . 250–252 A549 cells expressing CFTR constructs . . . . . . . 251f systematic approaches, limitation . . . . . . . . . . . . 249–250 Genotype–phenotype relationship . . . . . 358–360, 359f, 367 Gentzsch, Martina, . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15–32 GFP, see Green fluorescent protein (GFP) Glycoproteomics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 235 See also Affinity chromatography G protein-coupled receptor (GPCR) . . . . . . . . . . . . 114–124 Green fluorescent protein (GFP) . . 17, 19f, 20, 23, 28, 48f, 49, 152–153, 159, 309 GSEA, see Gene set enrichment analysis (GSEA) Guerrera, Ida Chiara, . . . . . . . . . . . . . . . . . . . . . . . . . . 213–224 Guggino, William B., . . . . . . . . . . . . . . . . . . . . . . . . . . 335–351

H hAEC, differentiation/repair of air–liquid interface culture based models . . . . . . . . . . 174 animal-based models, issues . . . . . . . . . . . . . . . . . . . . . 174 materials equipments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 176 hAEC cultures and media . . . . . . . . . . . . . . . . . . . . 175 reagents and solutions . . . . . . . . . . . . . . . . . . . 175–176 for wounding . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 176 methods differentiation, see Differentiation of hAEC, study approaches repair, see Repair of hAEC, study approaches MucilAirTM system . . . . . . . . . . . . . . . . . . . . . . . . . . . . 174 hAE cell cultures ALI and BEGM medium . . . . . . . . . . . . . . . . . . . . . . . 293 antibiotics. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .294 assorted reagents and solutions . . . . . . . . . . . . . . 294–295 extraction methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 299f cryopreservation of cells . . . . . . . . . . . . . . . . . . . . . . 302 isolation of hAE cells . . . . . . . . . . . . . . . . . . . 298–302 plating cells . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 301 thawing cells . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 302 type I/III collagen coating of plastic dishes . . . . . 298 type IV collagen coating of porous supports . . . . 298 media . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 290 BEGM/ALI medium, differences . . . . . . . . . . . . 292t BEGM and ALI medium composition . . . . . . . 291t porous supports . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 295 stock additives for ALI medium/BEGM . . . . . 290–293, 293t tissue procurement . . . . . . . . . . . . . . . . . . . . . . . . . 289–290 hAE cell models for CF research cell line creation, approaches . . . . . . . . . . . . . . . . . . . . . 286 hAE cell cultures . . . . . . . . . . . . . . . . . . . . . . . . . . . 285–286 materials airway epithelial cell lines, creation of . . . . . . . . . 296 hAE cell cultures . . . . . . . . . . . . . . . . . . . . . . . 289–295 protein expression/knockdown in ALI hAE cells 297–298 reporter gene assays in ALI hAE cells. . . . .296–297 retroviral and lentiviral vectors, production of . . . . . . . . . . . . . . . . . . . . . . . 295–296

methods airway epithelial cell lines, creation of . . . . . 303–304 hAE cell cultures . . . . . . . . . . . . . . . . . . . . . . . 298–302 protein expression/knockdown in ALI hAE cells . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 305 reporter gene assays in ALI hAE cells. . . . .304–305 retroviral and lentiviral vectors, production of . . . . . . . . . . . . . . . . . . . . . . . 302–303 See also Extraction methods of hAE cell cultures protein expression/knockdown in ALI hAE cells 287–288 adenovirus transduction, strategy . . . . . . . . . . . . . 288 homologous recombination . . . . . . . . . . . . . . . . . . . 287 method for retroviral/lentiviral vector genetic manipulation . . . . . . . . . . . . . . . . . . . . . . . 288, 289f reporter gene assays in ALI hAE cells . . . . . . . . . . . . 287 method for adenovirus reporter gene assays . . . . 288f retroviral and lentiviral vectors, production of . . . . . . 286 See also HAE cell cultures hAEC wounding techniques . . . . . . . . . . . . . . . . . . . . 180–181 Haemophilus influenzae . . . . . . . . . . . . . . . . . . . . 11, 144, 363t Hanrahan, John W., . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93–109 Hansson, Gunnar C., . . . . . . . . . . . . . . . . . . . . . . . . . . 127–141 Hardy–Weinberg law . . . . . . . . . . . . . . . . . . . . 356, 356f–357f Harvard apparatus . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 100 High-content (HC) screening . . . . . . . . . . . . . . . . . . . . . . . 250 High-throughput (HT) screening . . . . . . . . . . . . . . . . . . . 258 ‘Hits,’ . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 252 Høiby, Niels, . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 143–168 HPLC . . . . . . . . . . 21, 59–60, 133, 216–217, 222–224, 234, 267, 269, 347 hTERT, see Human telomerase reverse transcriptase (hTERT) Huang, S., . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 173–184 Human airway submucosal gland (microdissected) . . . . . 94f Human bronchial epithelial (HBE) cells . . . . . . . . 8, 20, 54, 113–117, 113–117, 119–121, 120f, 123–125, Human mucins, antibodies in . . . . . . . . . . . . . . . . . . . . . . . 131t Human telomerase reverse transcriptase (hTERT). . . . . 286 Human trachea, components . . . . . . . . . . . . . . . . . . . . . . . . . 96 Human transplant recipient lungs . . . . . . . . . . . . . . . . . . . . 103 Hybrid instruments . . . . . . . . . . . . . . . . . . . . . . . . . . . . 231–232 Hybridization . . . . . . . . . . . . . . 17–18, 59, 69, 147, 155–156, 194, 199–201

I Ianowski, Juan, . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93–109 Ibuprofen . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52 IMAC, see Immobilized metal affinity chromatography (IMAC) Immobilized metal affinity chromatography (IMAC) . . 235 Immunoperoxidase assay, schematic model . . . . . . . . . . . 340f Immunostaining . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15 See also CFTR immunostaining INCENP . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 261f, 264n12 Inflammation . . . . . . 3–4, 10–11, 29, 51–75, 119, 124–125, 144–146, 173 See also Inflammation in CF, methods of evaluation Inflammation in CF, methods of evaluation assessment of BAL, meaurement of cytokines . . . . . . . . . . . . . . . . 53 bronchoscopy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53 materials animal models, stimulation, and treatment with compounds . . . . . . . . . . . . . . . . . . . . . . . . . . . 55–56

CYSTIC FIBROSIS

380 Index

Inflammation in CF, methods of evaluation (continued) cell culture, stimulation, and treatment with compounds . . . . . . . . . . . . . . . . . . . . . . . . . . . 54–55 cytokines/chemokines secretion, measurement of . . . . . . . . . . . . . . . . . . . . . . . . . . . 56 gene array analyses . . . . . . . . . . . . . . . . . . . . . . . . . . . 59 histology and immunohistochemical staining . . . . 56 one/two-dimensional SDS-PAGE . . . . . . . . . . . . . 57 promoter/transcription factor activity, evaluation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 58 proteomic analyses . . . . . . . . . . . . . . . . . . . . . . . . 59–60 Western blot analysis . . . . . . . . . . . . . . . . . . . . . . 57–58 methods animal maintenance and treatments . . . . . 62f, 64–65 cell culture maintenance and treatments . . . 60f–61f, 63 cytokine production, measurement of . . . . . . . . . . . 65 gene array analysis . . . . . . . . . . . . . . . . . . . . . . . . 69–70 histological analysis of lung tissue . . . . . . . . . . . 65–66 promoter/transcription factor activity, analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67–68 proteomic analysis . . . . . . . . . . . . . . . . . . . . . . . . 70–72 Western blot analysis . . . . . . . . . . . . . . . . . . . . . . 66–67 models ferret/pig models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53 humans/mouse models . . . . . . . . . . . . . . . . . . . . 52–53 immortalized epithelial cell pair models, areas of research . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52 study levels/mechanisms . . . . . . . . . . . . . . . . . . . . . . 60–63 Ingenuity pathway analysis (IPA) . . . . . . 196, 203–206, 204f In silico testing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 237, 366 Interactome . . . . . . . . . . . . . . . . . 228–229, 233–235, 237, 240 Intracellular calcium . . . . . . . . . . . . . . . . . . . . . 9–10, 113–125 See also Measurement of calcium signals (intracellular) Ion channel . . . 7, 54, 95, 114, 119, 127, 263, 319, 322, 325 transporter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 95 Ionization techniques . . . . . . . . . . . . . . . . . . . . . . . . . . 230–231 ESI . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 231 MALDI . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 230–231 Ion trap instruments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 232–233 technologies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 232–233 LC-MS/MS protein identification . . . . . . . . . . . . 232 LTQ-Orbitrap, application . . . . . . . . . . . . . . . . . . . 233 IPA, see Ingenuity pathway analysis (IPA) Irokawa, Toshiya, . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93–109 Isobaric tag for relative and absolute quantitation (ITRAQ) . . . . . . . . . . . . . . . . . . . . . . . . . . . 215, 239 ITRAQ, see Isobaric tag for relative and absolute quantitation (ITRAQ)

J Johansen, Ulla, . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 143–168 Journal of Cystic Fibrosis . . . . . . . . . . . . . . . . . . . . . . . . . . . . 281

K Karchin, Rachel, . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 355–369 Karlsson, Dr. Niclas, . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 135 Khansaheb, Monal, . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93–109 Koch–Henle postulates. . . . . . . . . . . . . . . . . . . . . . . . .144–146 Koch’s criteria . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 144 KRB, see Krebs–Ringer bicarbonate buffer (KRB) Krebs–Ringer bicarbonate buffer (KRB) . . . . . . . . . 101, 103 Kreda, Silvia, . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6

Krouse, Mauri E., . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93–109 Kunzelmann, Karl, . . . . . . . . . . . . . . . . . . . . . . . . . . . . 249–264

L Large-scale screening, see High-content (HC) screening; High-throughput (HT) screening Laser confocal microscopy . . . . . . . . 5, 22–23, 26, 29–30n11 LC-MS/MS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 72, 133, 232 Leed’s criteria . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 149 Lentivirus . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 254, 296–297 Lipid bilayers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36, 38–39 compartments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38 formation “painting” approach . . . . . . . . . . . . . . . . . . . . . . . . . . . 39 incorporation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39 Lipidomic methods LC/MSn analysis chromatographic/intrasource ionization separation of lipids . . . . . . . . . . . . . . . . . . . . . . . 273–275, 275f sample preparation . . . . . . . . . . . . . . . . . . . . . . 272–273 MALDI-TOF-ClinProToolsTM ClinProToolsTM analysis . . . . . . . . . . . . . . . 272, 273f lipid extraction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 270 MALDI-TOF/TOF . . . . . . . . . . . . . . . . . . . . 271–272 SPE fractionation . . . . . . . . . . . . . . . . . . . . . . . 270–271 Lipids large . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 273–275 small . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 273–274 sterol . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 273–275 Locus-specific databases (LSDBs) . . . . . . . . . . . . . . . . . . . 367 LSDBs, see Locus-specific databases (LSDBs) Lukacs, Gergely L., . . . . . . . . . . . . . . . . . . . . . . . . . . . . 335–351 Lung biology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 312, 315–317 Lysozyme . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 95

M MALDI, see Matrix-assisted laser desorption ionization (MALDI) MALDI-TOF, see Matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF) MALDI-TOF-ClinProToolsTM . . . . . . . . . . . . . . . . . . . . 266, 266f, 276n3 Mass analyzers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 231–232 spectrometer . . . . . . . . . . . . . 60, 133, 139, 217, 231–233, 235–236, 268 spectrometry . . . . . 11, 72, 149, 191, 213, 227–240, 228, 265–266, 268, 338, 347 2D-PAGE . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 229 MALDI . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 229 TOF . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 229 Matrix-assisted laser desorption ionization (MALDI) . . . . . . . . 72, 149, 217–218, 217–218, 223–224, 229–231, 229–234, 266, 268, 270–272, 276–277, 347 Matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF) . . 149, 229, 266, 266f, 268, 271, 276–277n7, 347 MCC, see Mucociliary clearance (MCC) MCC mechanisms, normal/CF lung . . . . . . . . . . . . . . . . . . 4f McCray, Paul B., . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 193–211 Measurement of airway submucosal gland secretion agonists/inhibitors of secretion . . . . . . . . . . . . . . . . . . . 102

CYSTIC FIBROSIS 381 Index airway glands species differences in . . . . . . . . . . . . . . . . . . . . . . . . . . 96 structure/distribution . . . . . . . . . . . . . . . . . . . . . 94f, 96 composition/physical properties of mucus, measure of . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 98 gland mucus vs. sputum . . . . . . . . . . . . . . . . . . . . . . . . . . 96 materials equipments, see Equipments for maintaining/imaging tissues reagents. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .101–102 mechanisms of fluid secretion . . . . . . . . . . . . . . . . . . 95–96 methods, see Methods for measure of submucosal gland secretion mucus and airway sterility . . . . . . . . . . . . . . . . . . . . . 94–95 CFTR, cause of infection . . . . . . . . . . . . . . . . . . . . . 95 mucus clearance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 95 primary gland mucus . . . . . . . . . . . . . . . . . . . . . . . . . 95 mucus secretion, examination . . . . . . . . . . . . . . . . . . 93–94 human airway submucosal gland (microdissected) . . . . . . . . . . . . . . . . . . . . . . . . . . 94f from a pig trachea . . . . . . . . . . . . . . . . . . . . . . . . . . . 94f optical measurement method . . . . . . . . . . . . . . . . . . 93–94 previous methods, see Previous methods of measuring airway mucus secretion single gland optical method, advantages/ limitations . . . . . . . . . . . . . . . . . . . . . . . . . . . . 98–99 Measurement of calcium signals (intracellular) . . . . 117–121 assessment of GPCR activation . . . . . . . . . . . . . . 119–120 Fluo-4 loading and assessment of GPCR . . . . activation 120–121 Fura-2 loading and assessment of GPCR activation . . . . . . . . . . . . . . . . . . . . . . . . . . 117, 120f measurement of Ca2+ i . . . . . . . . . . . . . . . . . . . . . 117–119 mitochondrial Ca2+ m measurements . . . . . . . . . . . . 122f confocal microscopic assessment of GPCR activation . . . . . . . . . . . . . . . . . . . . . . . . . . . 121–123 HBE loading with Rhod-2 . . . . . . . . . . . . . . . . . . . 121 in normal/CF human cultures . . . . . . . . . . 123–125, 124f epithelial polarization, effect on calcium signals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 114 ER Ca2+ storage expansion, mechanism . . . . . . 114 materials . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 115–116 methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 116–123 Meconium ileus (MI) . . . . . . . . . . . . . . . . . . . . . 312, 316, 363t Mendelian disorder . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 356 Metabolome . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 228, 230, 233 MetaCore . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 196, 206 Methods for identification of CF pathogens DNA typing by PFGE . . . . . . . . . . . . . . . . 163–164, 165f ELISA for measuring IgG/IgA antibodies . . . . 164–167 calculation of results . . . . . . . . . . . . . . . . . . . . 166–167 interpretation of results . . . . . . . . . . . . . . . . . . . . . . 167 limitations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 164–165 preparation of dilutions . . . . . . . . . . . . . . . . . . . . . . 166 principle . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .164 gram stain sputum . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 155 PNA FISH of tissue and sputum . . . . . . . . . . . . 155–156 P. aeruginosa biofilms surrounded by PMNs . . . 157f P. aeruginosa (3-day-old) biofilms grown in flow chambers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 160f recA-gene PCR/RFLP-based identification for B.cepacia complex . . . . . . . . . . . . . . . . . . . . . . . 162f agarose gel electrophoresis. . . . . . . . . . . . . . . . . . . .161 DNA extraction . . . . . . . . . . . . . . . . . . . . . . . . 160–161 PCR reaction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 161

RFLP analysis . . . . . . . . . . . . . . . . . . . . . . . . . . 161–162 in vitro flow cell biofilm . . . . . . . . . . . . . . . . . . . . . 156–159 experimental set up . . . . . . . . . . . . . . . . . . . . . . . . . 158f Methods for measure of submucosal gland secretion experimental manipulations . . . . . . . . . . . . . . . . . . . . . . 108 mucosal preparation . . . . . . . . . . . . . . . . . . . . . . . . 103–104 mucosal cleaning, drying, oiling. . . . . . . . . . . . . . .104 mucosal dissection and mounting . . . . . . . . . 103–104 setup and “basal” secretion . . . . . . . . . . . . . . . . . . . 104 optical measurements . . . . . . . . . . . . . . . . . . . . . . . 104–108 digital microscopy . . . . . . . . . . . . . . . . . . . . . . . . . . . 105 direct camera capture . . . . . . . . . . . . . . . . . . . . . . . . 105 image storage, analysis, and presentation . . . . . . . . . . . . . . . . . . . 105–106, 106f lighting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 104 measurement errors . . . . . . . . . . . . . . . . . . . . . 107–108 tissue acquisition and preparation human donor tracheal/bronchial scraps . . . . . . . . 103 human transplant recipient lungs. . . . . . . . . . . . . .103 mouse . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 103 sheep, pig, and ferret . . . . . . . . . . . . . . . . . . . . . . . . 103 MI, see Meconium ileus (MI) Microarray experiment data analysis, concepts . . . . . . . . . . . . . . . . . . . . . . . . . . 204f differential expression . . . . . . . . . . . . . . . . . . . . . . . . 202 normalization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 201 quality control . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 201 design considerations Affymetrix sample preparation and microarray analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 200 batch effect . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 200 confounding variables . . . . . . . . . . . . . . . . . . . . . . . . 199 NuGEN Pico/Exon method procedure . . . 200–201 unknown confounders . . . . . . . . . . . . . . . . . . . 199–200 RNA isolation mirVana miRNA isolation kit (Ambion) method . . . . . . . . . . . . . . . . . . . . . . . . 195, 198–199 sample preparation . . . . . . . . . . . . . . . . . 195, 197–198 TRIzol/TRI reagent solution methodology . . . . . . . . . . . . . . . . . . . . . . . 195, 198 Microarray hybridizations, methods . . . . . . . . . . . . . 200–201 Microarray mRNA expression profiling deep sequencing technology, benefits . . . . . . . . . . . . . 194 materials candidate gene discovery tools . . . . . . . . . . . . . . . . 196 collection and long-term storage of tissues and cells . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 195 general requirements. . . . . . . . . . . . . . . . . . . . . . . . .195 microarray experiment . . . . . . . . . . . . . . . . . . 195–196 RNA isolation/storage/clean up . . . . . . . . . . . . . . . 195 sample preparation for RNA isolation . . . . . . . . . 195 methods candidate gene discovery tools . . . . . . . . . . . 202–209 candidate gene validation, approaches . . . . . . . . . 209 collection and long-term storage of tissues/ cells . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 196–197 data analysis, general concepts . . . . . . . . . . . 201–202 microarray, see Microarray experiment RNA isolation/storage/clean up . . . . . . . . . . 198–199 sample preparation for RNA isolation . . . . . 197–198 Microbiology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 149–150 Mitochondria . . . . . . . . . . . . . . . . . . . 114–115, 121–123, 219 MLV, see Murine leukemia virus (MLV) Modulator Roadmap . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 339 Moraxella catarrhalis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 144 MOTT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 144, 147–148

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382 Index

Mouse . . . . . . . . . . . . 5, 15, 19, 21–25, 27–28, 52–53, 27–28, 52–53, 55, 63–64, 68, 73, 103, 140, 174, 206, 254, 257, 282, 312–315, 318–320, 322–324, 338, MRNA . . . . 17–18, 114, 193–211, 228, 287, 305, 312, 316, 364–365 MS application to study proteomics/interactomics in CF DNA microarray technology, limitations . . . . . . . . . . 228 MS, role in CF study. . . . . . . . . . . . . . . . . . . . . . . . . . . . 240 MS technologies applicable to CF affinity-based chromatography . . . . . . . . . . . 235–236 instrumentation . . . . . . . . . . . . . . . . . . . . . . . . 231–232 ion trap technologies . . . . . . . . . . . . . . . . . . . . 232–233 mass analyzer technologies . . . . . . . . . . . . . . . . . . . 232 multidimensional separation . . . . . . . . . . . . . 234–235 separation technologies . . . . . . . . . . . . . . . . . . 233–234 protein “interactome” network . . . . . . . . . . . . . . . . . . . 228 proteomic approaches chaperone systems, importance . . . . . . . . . . . . . . . 229 ionization techniques. . . . . . . . . . . . . . . . . . . .230–231 proteomic methodologies bottom-up versus top-down . . . . . . . . . . . . . . 236–238 quantitative methods, see Quantitative methods, assessment of CF proteome software applications . . . . . . . . . . . . . . . . . . . . . . . 239–240 Census . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 239–240 MS/MS . . . . . . 133, 217–218, 222–224, 232, 239, 268, 277 MS proteomic approaches . . . . . . . . . . . . . . . . . . . . . . 230–231 MucilAirTM , 174–175, 177, 180 Mucin expression, identification/quantification . . . . . . . 128f materials composite agarose–polyacrylamide gel electrophoresis . . . . . . . . . . . . . . . . . . . . . . 130–131 mucin preparation and solubilization. . . . . . 128–129 mucins/glycoproteins, see Mucins/glycoproteins, visualization of Slot/Dot blotting . . . . . . . . . . . . . . . . . . . . . . . . . . . . 129 trypsin digestion . . . . . . . . . . . . . . . . . . . . . . . . 132–133 methods composite agarose–polyacrylamide gel electrophoresis . . . . . . . . . . . . . . . . . 135–138, 136f mucin preparation and solubilization. . . . . . 133–134 mucins/glycoproteins, see Mucins/glycoproteins, visualization of Slot/Dot blotting . . . . . . . . . . . . . . . . . . . . . . . 134–135 mucins(major) in lungs . . . . . . . . . . . . . . . . . . . . . 127–128 Mucin preparation and solubilization . . . . . . . . . . . . . . . . . . . . . . . . . . 128–129 using chaotropic salt . . . . . . . . . . . . . . . . 128–129, 134 using protein gel sample-loading buffer . . . 129, 134 Mucins/glycoproteins, visualization of on composite gels . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 138 glycan-based detection . . . . . . . . . . . . . . . . . . . . . . . 132 imperial (coomassie) stain . . . . . . . . . . . . . . . . . . . . 138 protein-based detection . . . . . . . . . . . . . . . . . . . . . . 132 SYPRO Ruby staining . . . . . . . . . . . . . . . . . . . . . . . 137 human mucins, antibodies in . . . . . . . . . . . . . . . . . . . . 131t identification with proteomics . . . . . . . . . . 133, 139–140 on nitrocellulose membranes Alcian blue staining . . . . . . . . . . . . . . . . . . . . . 129, 138 DIG glycan detection . . . . . . . . . . . . . . . . . . . . . . . . 130 immunoblotting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 130 PAS staining . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 129 transfer to PVDF membrane . . . . . . . . . . . . . . . . 132, 138 Mucociliary clearance (MCC). . . . . . . . .4, 9, 20, 84, 93, 99, 143, 312

Mucosal innate defense . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 94 Mucosal preparation method . . . . . . . . . . . . . . . . . . . 103–104 mucosal cleaning, drying, oiling . . . . . . . . . . . . . . . . . . 104 mucosal dissection and mounting . . . . . . . . . . . . 103–104 setup and “basal” secretion . . . . . . . . . . . . . . . . . . . . . . . 104 Mucous cell . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 96, 177 Mucoviscidose, see Cystic fibrosis (CF) Mucus hurricanes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 88n1, 90n7 layer adherent . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 dehydration of, effects . . . . . . . . . . . . . . . . . . . . . . . . . . 4 secretion (examination) . . . . . . . . . . . . . . . . . . . . . . . 93–94 human airway submucosal gland (microdissected) . . . . . . . . . . . . . . . . . . . . . . . . . . 94f from a pig trachea . . . . . . . . . . . . . . . . . . . . . . . . . . . 94f vs. sputum . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 96 MudPIT . . . . . . . . . . . . . . . . . . . . . . . . . . . . 234–235, 237, 239 Multidimensional . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 234–236 See also Separation technologies Murine leukemia virus (MLV) . . . . . . . . . . . . . . . . . . 295, 306 Murine models of CF . . . . . . . . . . . . . . . . . . . . . . . . . . 312–315 Mutation prediction algorithms . . . . . . . . . . . . 356, 369, 369f Myoepithelial cell . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 98

N NanoHPLC . . . . . . . . . . . . . . . . . . 217–218, 222–223, 224n2 NanoLC . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 217–218 Nasal potential difference (NPD) . . . . . . . . 74n15, 361–362 Nielsen, Xiaohui Chen, . . . . . . . . . . . . . . . . . . . . . . . . 143–168 NMRD, see Nonsense-mediated mRNA decay (NMRD) Nomarski illumination, see Differential interference contrast (DIC) Nonsense-mediated mRNA decay (NMRD) . . . . . 364–366 Nørgaard, Lena, . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 143–168 Normalization . . . . . . . . . . . . 201, 210n13, 261f, 272, 276n3, 341, 351n4 NPD, see Nasal potential difference (NPD)

O Okiyoneda, Tsukasa, . . . . . . . . . . . . . . . . . . . . . . . . . . . 335–351 Oligohydramnios . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 Ollero, Mario, . . . . . . . . . . . . . . . . . . . . . . . 213–224, 265–277 Olsen, John C., . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 285–309 Omics biology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 190 CFTR physiology and CF pathophysiology . . . . . . . 190 CFTR as cellular network . . . . . . . . . . . . . . . . . . . . 190 CFTR, role in tissue hydration . . . . . . . . . . . . . . . 190 Mendelian genetics . . . . . . . . . . . . . . . . . . . . . . . . . . 190 protein–protein interactions . . . . . . . . . . . . . . . . . . 190 subcellular environments . . . . . . . . . . . . . . . . . . . . . 190 coupled to bioinformatics, emergence . . . . . . . . . . . . . 191 genomics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 190 metabolomics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 190 proteomics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 190 OMIM, see Online Mendelian inheritance in man (OMIM) Oncogenes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 286, 303 O’neal, Wanda, . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 285–309 Online Mendelian inheritance in man (OMIM) . . . . . . . . . . . . . . . . . . . . . . . . . . 367, 368t Organelle proteomics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 249 Oxidative stress . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 114

CYSTIC FIBROSIS 383 Index P Pathogenesis . . . . . . . . . . . . . . . . 5, 11–12, 144, 150, 213, 358 Penland, Christopher, . . . . . . . . . . . . . . . . . 335–351, 355–369 Pepperkok, Rainer, . . . . . . . . . . . . . . . . . . . . . . . . . . . . 249–264 Peptide separation by NanoLC and MS/MS analysis. . .217–218, 222–223 OFFgel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 217, 222 Perfluorocarbon (PFC) . . . . . . . . . . . . . . . . . . . . 81, 83, 85–88 Periciliary liquid layer (PCL) . . . 77, 78f, 81–82, 81f, 86–87 Peters, Kathryn W.,. . . . . . . . . . . . . . . . . . . . . . . . . . . .335–351 PFC, see Perfluorocarbon (PFC) PFTs, see Pulmonary function tests (PFTs) Phosphoproteomics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 235 See also Affinity chromatography Pig . . . . . . . . . . . 11, 53, 55, 94, 98, 103, 105, 282, 312–314, 316–319, 322, 329 Piomelli, Daniele, . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 265–277 Pollard, Harvey B., . . . . . . . . . . . . . . . . . . . . . . . . . . . . 335–351 Porcine models of CF . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 316 Post-cell lysis labeling technologies . . . . . . . . . . . . . . . . . . 239 Previous methods of measuring airway mucus secretion collection of oil-trapped secretions with Bore capillaries . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 97–98 direct collection from gland duct orifices (Nadel) . . . . 97 labeled glycoconjugates as surrogates for secretion . . . 97 other methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 98 tantalum powder . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 97 Primary gland mucus . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 95 Protease inhibitors, see Secretory leukoprotease inhibitor (SLPI); Splunc1 Protein degradation . . . . . . . . . . . . . . . . . . . . . . . . . . . 319, 331, 336 folding . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 336, 339 “interactome” network . . . . . . . . . . . . . . . . . . . . . . . . . . 228 Protein–protein interactions . . . . . . . 10, 190, 207f, 208, 228 Proteome assessment, quantitative methods . . . . . . . . . . . . 238–239 enzymatic labeling . . . . . . . . . . . . . . . . . . . . . . . . . . . 239 label free techniques . . . . . . . . . . . . . . . . . . . . . . . . . 239 metabolic labeling . . . . . . . . . . . . . . . . . . . . . . . . . . . 238 post-cell lysis labeling technologies . . . . . . . . . . . . 239 SILAC approach . . . . . . . . . . . . . . . . . . . . . . . . . . . . 238 Proteomic MS technologies . . . . . . . . . . . . . . . . . . . . . . . . . 228 Proteomics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 190 See also Proteomics (quantitative) of CF cell models by SILAC Proteomics (quantitative) of CF cell models by SILAC materials cell culture and SILAC . . . . . . . . . . . . . . . . . . . . . . 215 “in-solution” trypsin digestion. . . . . . . . . . . .216–217 microdomain protein extraction . . . . . . . . . . . . . . . 216 microsomal protein extraction . . . . . . . . . . . . . . . . 216 peptide OFFgel separation . . . . . . . . . . . . . . . . . . . 217 peptide separation by NanoLC and MS/MS analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 217–218 total protein extraction . . . . . . . . . . . . . . . . . . . . . . . 215 methods cell culture and SILAC . . . . . . . . . . . . . . . . . . . . . . 218 “in-solution” trypsin digestion . . . . . . . . . . . . . . . . 221 microdomain protein extraction . . . . . 220–221, 221f microsomal protein extraction . . . . . . . . . . . . . . . . 219 peptide OFFgel separation . . . . . . . . . . . . . . . . . . . 222 peptide separation by NanoLC and MS/MS analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 222–223 total protein extraction . . . . . . . . . . . . . . . . . . 218–219

MS-based techniques, application . . . . . . . . . . . 213–214 2D SDS-PAGE . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 213 high-throughput identification of proteins, strategies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 214 proteomic approaches, issues/solution . . . . . . . . . . . . . 214 strategy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 215f Pseudomonas aeruginosa . . . . . . . . . . 10–11, 54, 62f, 144–151, 154–156, 157f, 159, 160f, 163–164, 165f, 167, 287, 294, 315, 363t Pulmonary function tests (PFTs) . . . . . . . . . . . . . . . 363t, 364 Pulsed field gel electrophoresis (PFGE) . . . . . . . . 146f, 149, 154–155, 163–164, 165f

Q Qadri, Yawar J., . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35–49 Quality control . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19f, 201, 295 Quantitative methods, assessment of CF proteome . . . . . . . . . . . . . . . . . . . . . . . . . . . 238–239 enzymatic labeling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 239 label free techniques . . . . . . . . . . . . . . . . . . . . . . . . . . . . 239 metabolic labeling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 238 post-cell lysis labeling technologies . . . . . . . . . . . . . . . 239 SILAC approach . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 238

R RAAV, see Recombinant adeno-associated virus (rAAV) Rabbit trachea . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 96 Ramachandran, Shyam, . . . . . . . . . . . . . . . . . . . . . . . . 193–211 Randell, Scott H., . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 285–309 Reactive oxygen species (ROS) . . . . . . . . . . . . . 114–115, 123 recA-gene PCR . . . . . . . . . . . . . . . . . 153–154, 159–162, 162f Recombinant adeno-associated virus (rAAV) . . . . . . . . . 316 Repair, see Repair of hAEC, study approaches Repair of hAEC, study approaches criteria of repaired airway epithelium . . . . . . . . . . . . . 183 monitoring wound closure cell behavior . . . . . . . . . . . . . . . . . . . . . . . . . . . . 182–183 kinetics . . . . . . . . . . . . . . . . . . . . . . . . . . . 181–182, 182f wounding . . . . . . . . . . . . . . . . . . . . . . . . . . . . 180–181, 180f Reporter gene assays . . . . . . . . . . . . . 287, 296–297, 304–305 Research consortium, see CFTR Folding Consortium (CFC) Resources for CFTR research . . . . . . . . . . . . . . . . . . . 281–283 CFC, goal . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 282–283 CFTR2 project, aim . . . . . . . . . . . . . . . . . . . . . . . . . . . . 283 Respiratory infection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3, 11 Respiratory tract . . . . . . . . . . . . . . . . . . . . . 143–144, 147, 282 ‘Reverse transfection,’ . . . . . . . . . . . . . . . . . . . . . . . . . . 250, 256 Ribeiro, Carla M P., . . . . . . . . . . . . . . . . . . . . . . . . . . . 113–125 Riordan, Jack, . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 RNA deep sequencing (RNA-seq) . . . . . . . . . . . . . . . . . . . 194 ROS, see Reactive oxygen species (ROS)

S Scheetz, Todd E., . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 193 SDS-PAGE, see SDS-polyacrylamide gel electrophoresis (SDS-PAGE) SDS-polyacrylamide gel electrophoresis (SDS-PAGE) . . . . . . 43, 57, 66–67, 70–71, 214, 322, 327, 329, 338, 350 Search tool for interactions of chemicals (STITCH) . . . 208 Search tool for the retrieval of interacting genes/proteins (STRING) . . . . . . . . . . . . . 196, 206, 208, 211n14 Secretory leukoprotease inhibitor (SLPI) . . . . . . . . . . . . . . 95

CYSTIC FIBROSIS

384 Index

Secretory traffic . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 252 SELDI, see Surface-enhanced laser desorption ionization (SELDI) Separation technologies chemical separation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 233 2D-PAGE/MALDI . . . . . . . . . . . . . . . . . . . . . . . . . . . . 233 goal . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 233 HPLC. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .234 multidimensional . . . . . . . . . . . . . . . . . . . . . . . . . . 234–235 Serous cell . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18f, 95–96 “Shotgun proteomics,” see Bottom-up technology Siderocalins . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 95 SILAC, see Stable isotope labelling in cell culture (SILAC) Single gland optical method . . . . . . . . . . . . . . . . . . . . . . 98–99 siRNA . . . . . . . . . . . . . . . . . 250, 252–253, 255–263, 287, 307 Skach, William R., . . . . . . . . . . . . . . . . . . . . . . . . . . . . 335–351 Slot/Dot blotting . . . . . . . . . . . . . . . . . . . . . . . . . 129, 134–135 SLPI, see Secretory leukoprotease inhibitor (SLPI) Small hairpin RNA (shRNA) . . . . . . . . . . . . . . 287–288, 297, 305n2, 306n5, 307n8, 307n9, 337 Small molecule correctors . . . . . . . . . . . . . . . . . . . . . . . . . . . 336 Sol . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 Soo Joo, N., . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93–109 Sorscher, Eric J., . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 335–351 Sosnay, Patrick R., . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 355–369 “Specific”/“non-specific” infectious diseases . . . . . . 144–145 See also Koch-Henle postulates Spectral counting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 239 Splunc1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79, 95 Stable isotope labelling in cell culture (SILAC) . . 213–224, 238–239 Staphylococcus aureus . . . . . . . . . . . . . . . . . . . . . . . . 10, 144, 363t Stenotrophomonas maltophilia . . . . . . . . . . . 11, 144, 294, 363t Sterol lipids . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 273–275 STITCH, see Search tool for interactions of chemicals (STITCH) Streptococcus pneumoniae . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 144 STRING, see Search tool for the retrieval of interacting genes/proteins (STRING) Structure of CFTR. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .346 Subcellular environments . . . . . . . . . . . . . . . . . . . . . . . . . . . 190 Submucosal gland . . . . . . . . . . . . . . . . . . . . . 5, 18, 94, 96, 313 dysfunction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 Surface-enhanced laser desorption ionization (SELDI) 231 Surgical pathology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 289 Sweat chloride measurement . . . . . . . . . . . . . . . . . . . . 361–362 c resin. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .101 Sylgard Systems biology, see Omics biology

Thiocyanate . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 95 Thomas, Philip J., . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 335–351 Thomsson, Kristina A., . . . . . . . . . . . . . . . . . . . . . . . . 127–141 Three-plasmid co-transfection . . . . . . . . . . . . . . . . . . . . . . 295 Time-of-flight (TOF) . . . . . . . . . . . . . . . . . . . . . . . . . 229, 231 TOF, see Time-of-flight (TOF) Top-down technology . . . . . . . . . . . . . . . . 230, 233, 236–239 advantages/limitations . . . . . . . . . . . . . . . . . . . . . . 237–238 Tracheal xenograft model . . . . . . . . . . . . . . . . . 319–324, 325f design and transplantation . . . . . . . . . . . . . . . . . . . . . . 323f potential difference instrumentation and setup . . . . 323f TEPD analysis of ferret CF/non-CF tracheal xenografts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 325f Tran, Kim V., . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93–109 Transcription factors . . . . . . . . . . . 57–58, 62, 67–68, 74, 203 Transepithelial electrical resistance (TEER) . . . . . . 176, 181 Trypsin digestion . . . . . . . . . . . . . . . . 132, 214f, 216–217, 221 Two-electrode voltage clamp . . . . . . . . . . . . . . . 36–37, 40–42 Two-hybrid screening . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 249

U Unfolded protein response (UPR) . . . . . . . . . . . . . . . . . . . 114 UPR, see Unfolded protein response (UPR) Ussing chambers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8, 78, 117

V Vieu, Diane-Lore, . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 213–224

W Water transport . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3, 7, 9 Wine, Jeffrey J., . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6, 93–109 Wiszniewski, L., . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 173–184 Worthington, Erin N., . . . . . . . . . . . . . . . . . . . . . . . . . . . 77–90 Wounding techniques . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 180 Wu, Jin V., . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93–109 www.cftrfolding.org . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 337

X X-box binding protein-1 (XBP-1) . . . . . . . . . . . . . . . . . . . 114 XBP-1, see X-box binding protein-1 (XBP-1) XcaliburTM . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 60 Xenopus oocyte . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36–38, 40

Y Yates, John R. III, . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 227–240

T

Z

Tarran, Robert, . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8, 77–90 TEER, see Transepithelial electrical resistance (TEER) Therapy . . . . 5, 9, 11, 64, 145, 167, 283, 285, 306, 312, 337

Zhang, Yulong, . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 311–331 Ziady, Assem G., . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51–74 Zielenski, Julian, . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 355–369