Methods in Enzymology Vol 461: Chemokines, Part B

METHODS IN ENZYMOLOGY Editors-in-Chief

JOHN N. ABELSON AND MELVIN I. SIMON Division of Biology California Institute of Technology Pasadena, California, USA Founding Editors

SIDNEY P. COLOWICK AND NATHAN O. KAPLAN

Academic Press is an imprint of Elsevier 525 B Street, Suite 1900, San Diego, CA 92101-4495, USA 30 Corporate Drive, Suite 400, Burlington, MA 01803, USA 32 Jamestown Road, London NW1 7BY, UK First edition 2009 Copyright # 2009, Elsevier Inc. All Rights Reserved. No part of this publication may be reproduced, stored in a retrieval system or transmitted in any form or by any means electronic, mechanical, photocopying, recording or otherwise without the prior written permission of the publisher Permissions may be sought directly from Elsevier’s Science & Technology Rights Department in Oxford, UK: phone (+44) (0) 1865 843830; fax (+44) (0) 1865 853333; email: permissions@ elsevier.com. Alternatively you can submit your request online by visiting the Elsevier web site at http://elsevier.com/locate/permissions, and selecting Obtaining permission to use Elsevier material Notice No responsibility is assumed by the publisher for any injury and/or damage to persons or property as a matter of products liability, negligence or otherwise, or from any use or operation of any methods, products, instructions or ideas contained in the material herein. Because of rapid advances in the medical sciences, in particular, independent verification of diagnoses and drug dosages should be made For information on all Academic Press publications visit our website at elsevierdirect.com ISBN: 978-0-12-374907-9 ISSN: 0076-6879 Printed and bound in United States of America 09 10 11 12 10 9 8 7 6 5 4 3 2 1

CONTRIBUTORS

Ronen Alon Department of Immunology, The Weizmann Institute of Science, Rehovot, Israel Isabel Alves Department of Chemistry, Universite Pierre et Marie Curie, Paris, France Shirley Appelbe Neuroscience and Molecular Pharmacology, University of Glasgow, Glasgow, Scotland, United Kingdom Tione Buranda Department of Pathology and Cancer Center, University of New Mexico Health Science Center, Albuquerque, New Mexico, USA Gabriele S. V. Campanella Center for Immunology and Inflammatory Diseases, Division of Rheumatology, Allergy and Immunology, Massachusetts General Hospital, Harvard Medical School, Charlestown, Massachusetts, USA Jonathan J. Cannon Department of Computer Science and Engineering, Washington University in St. Louis, St. Louis, Missouri, USA Percy H. Carter Research & Development, Bristol-Myers Squibb Company, Princeton, New Jersey, USA Jenna L. Cash Sir William Dunn School of Pathology, University of Oxford, Oxford, United Kingdom Hyeryun Choe Department of Pediatrics, Harvard Medical School, Perlmutter Laboratory, Children’s Hospital, Boston, Massachusetts, USA John Dempster University of Strathclyde, Institute for Pharmacy & Biomedical Sciences, Glasgow, Scotland, United Kingdom Michael Farzan Department of Microbiology and Molecular Genetics, Harvard Medical School, New England Primate Research Center, Southborough, Massachusetts, USA xi

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David R. Greaves Sir William Dunn School of Pathology, University of Oxford, Oxford, United Kingdom Damon J. Hamel Skaggs School of Pharmacy and Pharmaceutical Science, University of California, San Diego, La Jolla, California, USA Tracy M. Handel Skaggs School of Pharmacy and Pharmaceutical Science, University of California, San Diego, La Jolla, California, USA Richard Horuk Department of Pharmacology, UC Davis, Davis, California, USA Victor Hruby Department of Chemistry, and Department of Biochemistry and Molecular Biophysics, University of Arizona, Tucson, Arizona, USA Ariane Jansma Skaggs School of Pharmacy and Pharmaceutical Science, University of California, San Diego, La Jolla, California, USA Pia C. Jensen Department of Neuroscience and Pharmacology, Laboratory for Molecular Pharmacology, The Panum Institute, University of Copenhagen, Copenhagen, Denmark Francis Lin Center for Molecular Biology and Medicine, Veterans Affairs Palo Alto Health Care System, Palo Alto, California, USA, and Laboratory of Immunology and Vascular Biology, Department of Pathology, School of Medicine, Stanford University, Stanford, California, USA, and Department of Physics and Astronomy, University of Manitoba, Winnipeg, Manitoba, Canada Tina Y. Liu Department of Biochemistry, Medical College of Wisconsin, Milwaukee, Wisconsin, USA Tamara Loos Laboratory of Molecular Immunology, Rega Institute for Medical Research, Leuven, Belgium Andrew D. Luster Center for Immunology and Inflammatory Diseases, Division of Rheumatology, Allergy and Immunology, Massachusetts General Hospital, Harvard Medical School, Charlestown, Massachusetts, USA Mario Mellado Department of Immunology and Oncology, Centro Nacional de Biotecnologı´a/ CSIC, Madrid, Spain

Contributors

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Mark J. Miller Washington University School of Medicine, Department of Pathology and Immunology, St. Louis, Missouri, USA Graeme Milligan Neuroscience and Molecular Pharmacology, University of Glasgow, Glasgow, Scotland, United Kingdom Anneleen Mortier Laboratory of Molecular Immunology, Rega Institute for Medical Research, Leuven, Belgium Laura Martinez Mun˜oz Department of Immunology and Oncology, Centro Nacional de Biotecnologı´a/ CSIC, Madrid, Spain Christopher M. Overall Departments of Biochemistry and Molecular Biology, University of British Columbia, and Oral Biological and Medical Sciences, Centre for Blood Research, Life Sciences Institute, Vancouver, British Columbia, Canada Ian Parker Departments of Neurobiology and Behavior, and Physiology and Biophysics, University of California, Irvine, California, USA Francis C. Peterson Department of Biochemistry, Medical College of Wisconsin, Milwaukee, Wisconsin, USA Robert Pless Department of Computer Science and Engineering, Washington University in St. Louis, St. Louis, Missouri, USA Paul Proost Laboratory of Molecular Immunology, Rega Institute for Medical Research, Leuven, Belgium Amanda E. I. Proudfoot Merck Serono Geneva Research Centre, Geneva, Switzerland Jose´ Miguel Rodrı´guez-Frade Department of Immunology and Oncology, Centro Nacional de Biotecnologı´a/ CSIC, Madrid, Spain Mette M. Rosenkilde Department of Neuroscience and Pharmacology, Laboratory for Molecular Pharmacology, The Panum Institute, University of Copenhagen, Copenhagen, Denmark

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Antal Rot MRC Centre for Immune Regulation, Institute of Biomedical Research, University of Birmingham, UK Zdzislaw Salamon Department of Biochemistry and Molecular Biophysics, University of Arizona, Tucson, Arizona, USA Ziv Shulman Department of Immunology, The Weizmann Institute of Science, Rehovot, Israel India Sielaff Merck Serono Geneva Research Centre, Geneva, Switzerland Larry A. Sklar Department of Pathology and Cancer Center, University of New Mexico Health Science Center, Albuquerque, New Mexico, USA Amanda E. Starr Departments of Biochemistry and Molecular Biology, University of British Columbia, Centre for Blood Research, Life Sciences Institute, Vancouver, British Columbia, Canada Andrew J. Tebben Research & Development, Bristol-Myers Squibb Company, Princeton, New Jersey, USA Gordon Tollin Department of Chemistry, and Department of Biochemistry and Molecular Biophysics, University of Arizona, Tucson, Arizona, USA Brian F. Volkman Department of Biochemistry, Medical College of Wisconsin, Milwaukee, Wisconsin, USA Gemma E. White Sir William Dunn School of Pathology, University of Oxford, Oxford, United Kingdom David L. Wokosin Northwestern University, Department of Physiology, Chicago, Illinois, USA Yang Wu Department of Pathology and Cancer Center, University of New Mexico Health Science Center, Albuquerque, New Mexico, USA Bernd H. Zinselmeyer Washington University School of Medicine, Department of Pathology and Immunology, St. Louis, Missouri, USA

PREFACE

Secreted signaling molecules like chemokines facilitate complex intercellular communication by means of interactions with cell membrane–spanning receptors. There are approximately 50 identified mammalian chemokines, and all share a common monomeric fold. There are also approximately 20 chemokine receptors, all having the seven transmembrane domain topology of G-protein–coupled receptors. Despite this apparent homogeneity, the variety of signals sent and received by them defies simple explanation. Clearly, the devil is in the details, and the structure/function relationships that govern these seemingly similar interactions are sure to be subtle and nuanced, requiring thoughtful experimentation to tease them apart. With this in mind, we have focused Volume 461 of the Methods in Enzymology series on methods to probe the physical characteristics, dynamics, modifications, and interactions of chemokines and chemokine receptors. These proteins have presented researchers with many hurdles, from the difficulty in preparing functional receptors, to the complex posttranslational modifications, to the disparity in in vitro and in vivo functionality of some chemokine variants. Hence, the topics presented herein run the gamut of biochemical disciplines, from in vitro nuclear magnetic resonance and plasmon resonance methods, to receptor modeling in silico, to model systems for measuring and even simulating in situ cell migration. In 1997 Richard Horuk edited volumes 287 and 288 in the Methods in Enzymology series on chemokines and chemokine receptors, putting together the first comprehensive practical guide to studying these molecules. Volume 461 is part two of two new editions on chemokines and their receptors. The previous volume 460 focused on studying the roles of chemokines and chemokine receptors in disease states, atypical chemokine receptors, chemokine signaling, and chemokine-related proteins from pathogens. Compilations like this are assembled by the immense efforts of many individual researchers, and we enthusiastically offer our thanks and gratitude to all of the authors who contributed to making these volumes a reality. We would also like to thank the incredible staff at Elsevier, and especially Delsy Retchagar and Tara Hoey, for valiantly trying to keep us on track and on time. We could not have done it without you. DAMON J. HAMEL AND TRACY M. HANDEL xv

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VOLUME I. Preparation and Assay of Enzymes Edited by SIDNEY P. COLOWICK AND NATHAN O. KAPLAN VOLUME II. Preparation and Assay of Enzymes Edited by SIDNEY P. COLOWICK AND NATHAN O. KAPLAN VOLUME III. Preparation and Assay of Substrates Edited by SIDNEY P. COLOWICK AND NATHAN O. KAPLAN VOLUME IV. Special Techniques for the Enzymologist Edited by SIDNEY P. COLOWICK AND NATHAN O. KAPLAN VOLUME V. Preparation and Assay of Enzymes Edited by SIDNEY P. COLOWICK AND NATHAN O. KAPLAN VOLUME VI. Preparation and Assay of Enzymes (Continued) Preparation and Assay of Substrates Special Techniques Edited by SIDNEY P. COLOWICK AND NATHAN O. KAPLAN VOLUME VII. Cumulative Subject Index Edited by SIDNEY P. COLOWICK AND NATHAN O. KAPLAN VOLUME VIII. Complex Carbohydrates Edited by ELIZABETH F. NEUFELD AND VICTOR GINSBURG VOLUME IX. Carbohydrate Metabolism Edited by WILLIS A. WOOD VOLUME X. Oxidation and Phosphorylation Edited by RONALD W. ESTABROOK AND MAYNARD E. PULLMAN VOLUME XI. Enzyme Structure Edited by C. H. W. HIRS VOLUME XII. Nucleic Acids (Parts A and B) Edited by LAWRENCE GROSSMAN AND KIVIE MOLDAVE VOLUME XIII. Citric Acid Cycle Edited by J. M. LOWENSTEIN VOLUME XIV. Lipids Edited by J. M. LOWENSTEIN VOLUME XV. Steroids and Terpenoids Edited by RAYMOND B. CLAYTON xvii

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VOLUME XVI. Fast Reactions Edited by KENNETH KUSTIN VOLUME XVII. Metabolism of Amino Acids and Amines (Parts A and B) Edited by HERBERT TABOR AND CELIA WHITE TABOR VOLUME XVIII. Vitamins and Coenzymes (Parts A, B, and C) Edited by DONALD B. MCCORMICK AND LEMUEL D. WRIGHT VOLUME XIX. Proteolytic Enzymes Edited by GERTRUDE E. PERLMANN AND LASZLO LORAND VOLUME XX. Nucleic Acids and Protein Synthesis (Part C) Edited by KIVIE MOLDAVE AND LAWRENCE GROSSMAN VOLUME XXI. Nucleic Acids (Part D) Edited by LAWRENCE GROSSMAN AND KIVIE MOLDAVE VOLUME XXII. Enzyme Purification and Related Techniques Edited by WILLIAM B. JAKOBY VOLUME XXIII. Photosynthesis (Part A) Edited by ANTHONY SAN PIETRO VOLUME XXIV. Photosynthesis and Nitrogen Fixation (Part B) Edited by ANTHONY SAN PIETRO VOLUME XXV. Enzyme Structure (Part B) Edited by C. H. W. HIRS AND SERGE N. TIMASHEFF VOLUME XXVI. Enzyme Structure (Part C) Edited by C. H. W. HIRS AND SERGE N. TIMASHEFF VOLUME XXVII. Enzyme Structure (Part D) Edited by C. H. W. HIRS AND SERGE N. TIMASHEFF VOLUME XXVIII. Complex Carbohydrates (Part B) Edited by VICTOR GINSBURG VOLUME XXIX. Nucleic Acids and Protein Synthesis (Part E) Edited by LAWRENCE GROSSMAN AND KIVIE MOLDAVE VOLUME XXX. Nucleic Acids and Protein Synthesis (Part F) Edited by KIVIE MOLDAVE AND LAWRENCE GROSSMAN VOLUME XXXI. Biomembranes (Part A) Edited by SIDNEY FLEISCHER AND LESTER PACKER VOLUME XXXII. Biomembranes (Part B) Edited by SIDNEY FLEISCHER AND LESTER PACKER VOLUME XXXIII. Cumulative Subject Index Volumes I-XXX Edited by MARTHA G. DENNIS AND EDWARD A. DENNIS VOLUME XXXIV. Affinity Techniques (Enzyme Purification: Part B) Edited by WILLIAM B. JAKOBY AND MEIR WILCHEK

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VOLUME XXXV. Lipids (Part B) Edited by JOHN M. LOWENSTEIN VOLUME XXXVI. Hormone Action (Part A: Steroid Hormones) Edited by BERT W. O’MALLEY AND JOEL G. HARDMAN VOLUME XXXVII. Hormone Action (Part B: Peptide Hormones) Edited by BERT W. O’MALLEY AND JOEL G. HARDMAN VOLUME XXXVIII. Hormone Action (Part C: Cyclic Nucleotides) Edited by JOEL G. HARDMAN AND BERT W. O’MALLEY VOLUME XXXIX. Hormone Action (Part D: Isolated Cells, Tissues, and Organ Systems) Edited by JOEL G. HARDMAN AND BERT W. O’MALLEY VOLUME XL. Hormone Action (Part E: Nuclear Structure and Function) Edited by BERT W. O’MALLEY AND JOEL G. HARDMAN VOLUME XLI. Carbohydrate Metabolism (Part B) Edited by W. A. WOOD VOLUME XLII. Carbohydrate Metabolism (Part C) Edited by W. A. WOOD VOLUME XLIII. Antibiotics Edited by JOHN H. HASH VOLUME XLIV. Immobilized Enzymes Edited by KLAUS MOSBACH VOLUME XLV. Proteolytic Enzymes (Part B) Edited by LASZLO LORAND VOLUME XLVI. Affinity Labeling Edited by WILLIAM B. JAKOBY AND MEIR WILCHEK VOLUME XLVII. Enzyme Structure (Part E) Edited by C. H. W. HIRS AND SERGE N. TIMASHEFF VOLUME XLVIII. Enzyme Structure (Part F) Edited by C. H. W. HIRS AND SERGE N. TIMASHEFF VOLUME XLIX. Enzyme Structure (Part G) Edited by C. H. W. HIRS AND SERGE N. TIMASHEFF VOLUME L. Complex Carbohydrates (Part C) Edited by VICTOR GINSBURG VOLUME LI. Purine and Pyrimidine Nucleotide Metabolism Edited by PATRICIA A. HOFFEE AND MARY ELLEN JONES VOLUME LII. Biomembranes (Part C: Biological Oxidations) Edited by SIDNEY FLEISCHER AND LESTER PACKER

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VOLUME LIII. Biomembranes (Part D: Biological Oxidations) Edited by SIDNEY FLEISCHER AND LESTER PACKER VOLUME LIV. Biomembranes (Part E: Biological Oxidations) Edited by SIDNEY FLEISCHER AND LESTER PACKER VOLUME LV. Biomembranes (Part F: Bioenergetics) Edited by SIDNEY FLEISCHER AND LESTER PACKER VOLUME LVI. Biomembranes (Part G: Bioenergetics) Edited by SIDNEY FLEISCHER AND LESTER PACKER VOLUME LVII. Bioluminescence and Chemiluminescence Edited by MARLENE A. DELUCA VOLUME LVIII. Cell Culture Edited by WILLIAM B. JAKOBY AND IRA PASTAN VOLUME LIX. Nucleic Acids and Protein Synthesis (Part G) Edited by KIVIE MOLDAVE AND LAWRENCE GROSSMAN VOLUME LX. Nucleic Acids and Protein Synthesis (Part H) Edited by KIVIE MOLDAVE AND LAWRENCE GROSSMAN VOLUME 61. Enzyme Structure (Part H) Edited by C. H. W. HIRS AND SERGE N. TIMASHEFF VOLUME 62. Vitamins and Coenzymes (Part D) Edited by DONALD B. MCCORMICK AND LEMUEL D. WRIGHT VOLUME 63. Enzyme Kinetics and Mechanism (Part A: Initial Rate and Inhibitor Methods) Edited by DANIEL L. PURICH VOLUME 64. Enzyme Kinetics and Mechanism (Part B: Isotopic Probes and Complex Enzyme Systems) Edited by DANIEL L. PURICH VOLUME 65. Nucleic Acids (Part I) Edited by LAWRENCE GROSSMAN AND KIVIE MOLDAVE VOLUME 66. Vitamins and Coenzymes (Part E) Edited by DONALD B. MCCORMICK AND LEMUEL D. WRIGHT VOLUME 67. Vitamins and Coenzymes (Part F) Edited by DONALD B. MCCORMICK AND LEMUEL D. WRIGHT VOLUME 68. Recombinant DNA Edited by RAY WU VOLUME 69. Photosynthesis and Nitrogen Fixation (Part C) Edited by ANTHONY SAN PIETRO VOLUME 70. Immunochemical Techniques (Part A) Edited by HELEN VAN VUNAKIS AND JOHN J. LANGONE

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VOLUME 71. Lipids (Part C) Edited by JOHN M. LOWENSTEIN VOLUME 72. Lipids (Part D) Edited by JOHN M. LOWENSTEIN VOLUME 73. Immunochemical Techniques (Part B) Edited by JOHN J. LANGONE AND HELEN VAN VUNAKIS VOLUME 74. Immunochemical Techniques (Part C) Edited by JOHN J. LANGONE AND HELEN VAN VUNAKIS VOLUME 75. Cumulative Subject Index Volumes XXXI, XXXII, XXXIV–LX Edited by EDWARD A. DENNIS AND MARTHA G. DENNIS VOLUME 76. Hemoglobins Edited by ERALDO ANTONINI, LUIGI ROSSI-BERNARDI, AND EMILIA CHIANCONE VOLUME 77. Detoxication and Drug Metabolism Edited by WILLIAM B. JAKOBY VOLUME 78. Interferons (Part A) Edited by SIDNEY PESTKA VOLUME 79. Interferons (Part B) Edited by SIDNEY PESTKA VOLUME 80. Proteolytic Enzymes (Part C) Edited by LASZLO LORAND VOLUME 81. Biomembranes (Part H: Visual Pigments and Purple Membranes, I) Edited by LESTER PACKER VOLUME 82. Structural and Contractile Proteins (Part A: Extracellular Matrix) Edited by LEON W. CUNNINGHAM AND DIXIE W. FREDERIKSEN VOLUME 83. Complex Carbohydrates (Part D) Edited by VICTOR GINSBURG VOLUME 84. Immunochemical Techniques (Part D: Selected Immunoassays) Edited by JOHN J. LANGONE AND HELEN VAN VUNAKIS VOLUME 85. Structural and Contractile Proteins (Part B: The Contractile Apparatus and the Cytoskeleton) Edited by DIXIE W. FREDERIKSEN AND LEON W. CUNNINGHAM VOLUME 86. Prostaglandins and Arachidonate Metabolites Edited by WILLIAM E. M. LANDS AND WILLIAM L. SMITH VOLUME 87. Enzyme Kinetics and Mechanism (Part C: Intermediates, Stereo-chemistry, and Rate Studies) Edited by DANIEL L. PURICH VOLUME 88. Biomembranes (Part I: Visual Pigments and Purple Membranes, II) Edited by LESTER PACKER

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VOLUME 89. Carbohydrate Metabolism (Part D) Edited by WILLIS A. WOOD VOLUME 90. Carbohydrate Metabolism (Part E) Edited by WILLIS A. WOOD VOLUME 91. Enzyme Structure (Part I) Edited by C. H. W. HIRS AND SERGE N. TIMASHEFF VOLUME 92. Immunochemical Techniques (Part E: Monoclonal Antibodies and General Immunoassay Methods) Edited by JOHN J. LANGONE AND HELEN VAN VUNAKIS VOLUME 93. Immunochemical Techniques (Part F: Conventional Antibodies, Fc Receptors, and Cytotoxicity) Edited by JOHN J. LANGONE AND HELEN VAN VUNAKIS VOLUME 94. Polyamines Edited by HERBERT TABOR AND CELIA WHITE TABOR VOLUME 95. Cumulative Subject Index Volumes 61–74, 76–80 Edited by EDWARD A. DENNIS AND MARTHA G. DENNIS VOLUME 96. Biomembranes [Part J: Membrane Biogenesis: Assembly and Targeting (General Methods; Eukaryotes)] Edited by SIDNEY FLEISCHER AND BECCA FLEISCHER VOLUME 97. Biomembranes [Part K: Membrane Biogenesis: Assembly and Targeting (Prokaryotes, Mitochondria, and Chloroplasts)] Edited by SIDNEY FLEISCHER AND BECCA FLEISCHER VOLUME 98. Biomembranes (Part L: Membrane Biogenesis: Processing and Recycling) Edited by SIDNEY FLEISCHER AND BECCA FLEISCHER VOLUME 99. Hormone Action (Part F: Protein Kinases) Edited by JACKIE D. CORBIN AND JOEL G. HARDMAN VOLUME 100. Recombinant DNA (Part B) Edited by RAY WU, LAWRENCE GROSSMAN, AND KIVIE MOLDAVE VOLUME 101. Recombinant DNA (Part C) Edited by RAY WU, LAWRENCE GROSSMAN, AND KIVIE MOLDAVE VOLUME 102. Hormone Action (Part G: Calmodulin and Calcium-Binding Proteins) Edited by ANTHONY R. MEANS AND BERT W. O’MALLEY VOLUME 103. Hormone Action (Part H: Neuroendocrine Peptides) Edited by P. MICHAEL CONN VOLUME 104. Enzyme Purification and Related Techniques (Part C) Edited by WILLIAM B. JAKOBY

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VOLUME 105. Oxygen Radicals in Biological Systems Edited by LESTER PACKER VOLUME 106. Posttranslational Modifications (Part A) Edited by FINN WOLD AND KIVIE MOLDAVE VOLUME 107. Posttranslational Modifications (Part B) Edited by FINN WOLD AND KIVIE MOLDAVE VOLUME 108. Immunochemical Techniques (Part G: Separation and Characterization of Lymphoid Cells) Edited by GIOVANNI DI SABATO, JOHN J. LANGONE, AND HELEN VAN VUNAKIS VOLUME 109. Hormone Action (Part I: Peptide Hormones) Edited by LUTZ BIRNBAUMER AND BERT W. O’MALLEY VOLUME 110. Steroids and Isoprenoids (Part A) Edited by JOHN H. LAW AND HANS C. RILLING VOLUME 111. Steroids and Isoprenoids (Part B) Edited by JOHN H. LAW AND HANS C. RILLING VOLUME 112. Drug and Enzyme Targeting (Part A) Edited by KENNETH J. WIDDER AND RALPH GREEN VOLUME 113. Glutamate, Glutamine, Glutathione, and Related Compounds Edited by ALTON MEISTER VOLUME 114. Diffraction Methods for Biological Macromolecules (Part A) Edited by HAROLD W. WYCKOFF, C. H. W. HIRS, AND SERGE N. TIMASHEFF VOLUME 115. Diffraction Methods for Biological Macromolecules (Part B) Edited by HAROLD W. WYCKOFF, C. H. W. HIRS, AND SERGE N. TIMASHEFF VOLUME 116. Immunochemical Techniques (Part H: Effectors and Mediators of Lymphoid Cell Functions) Edited by GIOVANNI DI SABATO, JOHN J. LANGONE, AND HELEN VAN VUNAKIS VOLUME 117. Enzyme Structure (Part J) Edited by C. H. W. HIRS AND SERGE N. TIMASHEFF VOLUME 118. Plant Molecular Biology Edited by ARTHUR WEISSBACH AND HERBERT WEISSBACH VOLUME 119. Interferons (Part C) Edited by SIDNEY PESTKA VOLUME 120. Cumulative Subject Index Volumes 81–94, 96–101 VOLUME 121. Immunochemical Techniques (Part I: Hybridoma Technology and Monoclonal Antibodies) Edited by JOHN J. LANGONE AND HELEN VAN VUNAKIS VOLUME 122. Vitamins and Coenzymes (Part G) Edited by FRANK CHYTIL AND DONALD B. MCCORMICK

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VOLUME 123. Vitamins and Coenzymes (Part H) Edited by FRANK CHYTIL AND DONALD B. MCCORMICK VOLUME 124. Hormone Action (Part J: Neuroendocrine Peptides) Edited by P. MICHAEL CONN VOLUME 125. Biomembranes (Part M: Transport in Bacteria, Mitochondria, and Chloroplasts: General Approaches and Transport Systems) Edited by SIDNEY FLEISCHER AND BECCA FLEISCHER VOLUME 126. Biomembranes (Part N: Transport in Bacteria, Mitochondria, and Chloroplasts: Protonmotive Force) Edited by SIDNEY FLEISCHER AND BECCA FLEISCHER VOLUME 127. Biomembranes (Part O: Protons and Water: Structure and Translocation) Edited by LESTER PACKER VOLUME 128. Plasma Lipoproteins (Part A: Preparation, Structure, and Molecular Biology) Edited by JERE P. SEGREST AND JOHN J. ALBERS VOLUME 129. Plasma Lipoproteins (Part B: Characterization, Cell Biology, and Metabolism) Edited by JOHN J. ALBERS AND JERE P. SEGREST VOLUME 130. Enzyme Structure (Part K) Edited by C. H. W. HIRS AND SERGE N. TIMASHEFF VOLUME 131. Enzyme Structure (Part L) Edited by C. H. W. HIRS AND SERGE N. TIMASHEFF VOLUME 132. Immunochemical Techniques (Part J: Phagocytosis and Cell-Mediated Cytotoxicity) Edited by GIOVANNI DI SABATO AND JOHANNES EVERSE VOLUME 133. Bioluminescence and Chemiluminescence (Part B) Edited by MARLENE DELUCA AND WILLIAM D. MCELROY VOLUME 134. Structural and Contractile Proteins (Part C: The Contractile Apparatus and the Cytoskeleton) Edited by RICHARD B. VALLEE VOLUME 135. Immobilized Enzymes and Cells (Part B) Edited by KLAUS MOSBACH VOLUME 136. Immobilized Enzymes and Cells (Part C) Edited by KLAUS MOSBACH VOLUME 137. Immobilized Enzymes and Cells (Part D) Edited by KLAUS MOSBACH VOLUME 138. Complex Carbohydrates (Part E) Edited by VICTOR GINSBURG

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VOLUME 139. Cellular Regulators (Part A: Calcium- and Calmodulin-Binding Proteins) Edited by ANTHONY R. MEANS AND P. MICHAEL CONN VOLUME 140. Cumulative Subject Index Volumes 102–119, 121–134 VOLUME 141. Cellular Regulators (Part B: Calcium and Lipids) Edited by P. MICHAEL CONN AND ANTHONY R. MEANS VOLUME 142. Metabolism of Aromatic Amino Acids and Amines Edited by SEYMOUR KAUFMAN VOLUME 143. Sulfur and Sulfur Amino Acids Edited by WILLIAM B. JAKOBY AND OWEN GRIFFITH VOLUME 144. Structural and Contractile Proteins (Part D: Extracellular Matrix) Edited by LEON W. CUNNINGHAM VOLUME 145. Structural and Contractile Proteins (Part E: Extracellular Matrix) Edited by LEON W. CUNNINGHAM VOLUME 146. Peptide Growth Factors (Part A) Edited by DAVID BARNES AND DAVID A. SIRBASKU VOLUME 147. Peptide Growth Factors (Part B) Edited by DAVID BARNES AND DAVID A. SIRBASKU VOLUME 148. Plant Cell Membranes Edited by LESTER PACKER AND ROLAND DOUCE VOLUME 149. Drug and Enzyme Targeting (Part B) Edited by RALPH GREEN AND KENNETH J. WIDDER VOLUME 150. Immunochemical Techniques (Part K: In Vitro Models of B and T Cell Functions and Lymphoid Cell Receptors) Edited by GIOVANNI DI SABATO VOLUME 151. Molecular Genetics of Mammalian Cells Edited by MICHAEL M. GOTTESMAN VOLUME 152. Guide to Molecular Cloning Techniques Edited by SHELBY L. BERGER AND ALAN R. KIMMEL VOLUME 153. Recombinant DNA (Part D) Edited by RAY WU AND LAWRENCE GROSSMAN VOLUME 154. Recombinant DNA (Part E) Edited by RAY WU AND LAWRENCE GROSSMAN VOLUME 155. Recombinant DNA (Part F) Edited by RAY WU VOLUME 156. Biomembranes (Part P: ATP-Driven Pumps and Related Transport: The Na, K-Pump) Edited by SIDNEY FLEISCHER AND BECCA FLEISCHER

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VOLUME 157. Biomembranes (Part Q: ATP-Driven Pumps and Related Transport: Calcium, Proton, and Potassium Pumps) Edited by SIDNEY FLEISCHER AND BECCA FLEISCHER VOLUME 158. Metalloproteins (Part A) Edited by JAMES F. RIORDAN AND BERT L. VALLEE VOLUME 159. Initiation and Termination of Cyclic Nucleotide Action Edited by JACKIE D. CORBIN AND ROGER A. JOHNSON VOLUME 160. Biomass (Part A: Cellulose and Hemicellulose) Edited by WILLIS A. WOOD AND SCOTT T. KELLOGG VOLUME 161. Biomass (Part B: Lignin, Pectin, and Chitin) Edited by WILLIS A. WOOD AND SCOTT T. KELLOGG VOLUME 162. Immunochemical Techniques (Part L: Chemotaxis and Inflammation) Edited by GIOVANNI DI SABATO VOLUME 163. Immunochemical Techniques (Part M: Chemotaxis and Inflammation) Edited by GIOVANNI DI SABATO VOLUME 164. Ribosomes Edited by HARRY F. NOLLER, JR., AND KIVIE MOLDAVE VOLUME 165. Microbial Toxins: Tools for Enzymology Edited by SIDNEY HARSHMAN VOLUME 166. Branched-Chain Amino Acids Edited by ROBERT HARRIS AND JOHN R. SOKATCH VOLUME 167. Cyanobacteria Edited by LESTER PACKER AND ALEXANDER N. GLAZER VOLUME 168. Hormone Action (Part K: Neuroendocrine Peptides) Edited by P. MICHAEL CONN VOLUME 169. Platelets: Receptors, Adhesion, Secretion (Part A) Edited by JACEK HAWIGER VOLUME 170. Nucleosomes Edited by PAUL M. WASSARMAN AND ROGER D. KORNBERG VOLUME 171. Biomembranes (Part R: Transport Theory: Cells and Model Membranes) Edited by SIDNEY FLEISCHER AND BECCA FLEISCHER VOLUME 172. Biomembranes (Part S: Transport: Membrane Isolation and Characterization) Edited by SIDNEY FLEISCHER AND BECCA FLEISCHER

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VOLUME 173. Biomembranes [Part T: Cellular and Subcellular Transport: Eukaryotic (Nonepithelial) Cells] Edited by SIDNEY FLEISCHER AND BECCA FLEISCHER VOLUME 174. Biomembranes [Part U: Cellular and Subcellular Transport: Eukaryotic (Nonepithelial) Cells] Edited by SIDNEY FLEISCHER AND BECCA FLEISCHER VOLUME 175. Cumulative Subject Index Volumes 135–139, 141–167 VOLUME 176. Nuclear Magnetic Resonance (Part A: Spectral Techniques and Dynamics) Edited by NORMAN J. OPPENHEIMER AND THOMAS L. JAMES VOLUME 177. Nuclear Magnetic Resonance (Part B: Structure and Mechanism) Edited by NORMAN J. OPPENHEIMER AND THOMAS L. JAMES VOLUME 178. Antibodies, Antigens, and Molecular Mimicry Edited by JOHN J. LANGONE VOLUME 179. Complex Carbohydrates (Part F) Edited by VICTOR GINSBURG VOLUME 180. RNA Processing (Part A: General Methods) Edited by JAMES E. DAHLBERG AND JOHN N. ABELSON VOLUME 181. RNA Processing (Part B: Specific Methods) Edited by JAMES E. DAHLBERG AND JOHN N. ABELSON VOLUME 182. Guide to Protein Purification Edited by MURRAY P. DEUTSCHER VOLUME 183. Molecular Evolution: Computer Analysis of Protein and Nucleic Acid Sequences Edited by RUSSELL F. DOOLITTLE VOLUME 184. Avidin-Biotin Technology Edited by MEIR WILCHEK AND EDWARD A. BAYER VOLUME 185. Gene Expression Technology Edited by DAVID V. GOEDDEL VOLUME 186. Oxygen Radicals in Biological Systems (Part B: Oxygen Radicals and Antioxidants) Edited by LESTER PACKER AND ALEXANDER N. GLAZER VOLUME 187. Arachidonate Related Lipid Mediators Edited by ROBERT C. MURPHY AND FRANK A. FITZPATRICK VOLUME 188. Hydrocarbons and Methylotrophy Edited by MARY E. LIDSTROM VOLUME 189. Retinoids (Part A: Molecular and Metabolic Aspects) Edited by LESTER PACKER

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VOLUME 190. Retinoids (Part B: Cell Differentiation and Clinical Applications) Edited by LESTER PACKER VOLUME 191. Biomembranes (Part V: Cellular and Subcellular Transport: Epithelial Cells) Edited by SIDNEY FLEISCHER AND BECCA FLEISCHER VOLUME 192. Biomembranes (Part W: Cellular and Subcellular Transport: Epithelial Cells) Edited by SIDNEY FLEISCHER AND BECCA FLEISCHER VOLUME 193. Mass Spectrometry Edited by JAMES A. MCCLOSKEY VOLUME 194. Guide to Yeast Genetics and Molecular Biology Edited by CHRISTINE GUTHRIE AND GERALD R. FINK VOLUME 195. Adenylyl Cyclase, G Proteins, and Guanylyl Cyclase Edited by ROGER A. JOHNSON AND JACKIE D. CORBIN VOLUME 196. Molecular Motors and the Cytoskeleton Edited by RICHARD B. VALLEE VOLUME 197. Phospholipases Edited by EDWARD A. DENNIS VOLUME 198. Peptide Growth Factors (Part C) Edited by DAVID BARNES, J. P. MATHER, AND GORDON H. SATO VOLUME 199. Cumulative Subject Index Volumes 168–174, 176–194 VOLUME 200. Protein Phosphorylation (Part A: Protein Kinases: Assays, Purification, Antibodies, Functional Analysis, Cloning, and Expression) Edited by TONY HUNTER AND BARTHOLOMEW M. SEFTON VOLUME 201. Protein Phosphorylation (Part B: Analysis of Protein Phosphorylation, Protein Kinase Inhibitors, and Protein Phosphatases) Edited by TONY HUNTER AND BARTHOLOMEW M. SEFTON VOLUME 202. Molecular Design and Modeling: Concepts and Applications (Part A: Proteins, Peptides, and Enzymes) Edited by JOHN J. LANGONE VOLUME 203. Molecular Design and Modeling: Concepts and Applications (Part B: Antibodies and Antigens, Nucleic Acids, Polysaccharides, and Drugs) Edited by JOHN J. LANGONE VOLUME 204. Bacterial Genetic Systems Edited by JEFFREY H. MILLER VOLUME 205. Metallobiochemistry (Part B: Metallothionein and Related Molecules) Edited by JAMES F. RIORDAN AND BERT L. VALLEE

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VOLUME 206. Cytochrome P450 Edited by MICHAEL R. WATERMAN AND ERIC F. JOHNSON VOLUME 207. Ion Channels Edited by BERNARDO RUDY AND LINDA E. IVERSON VOLUME 208. Protein–DNA Interactions Edited by ROBERT T. SAUER VOLUME 209. Phospholipid Biosynthesis Edited by EDWARD A. DENNIS AND DENNIS E. VANCE VOLUME 210. Numerical Computer Methods Edited by LUDWIG BRAND AND MICHAEL L. JOHNSON VOLUME 211. DNA Structures (Part A: Synthesis and Physical Analysis of DNA) Edited by DAVID M. J. LILLEY AND JAMES E. DAHLBERG VOLUME 212. DNA Structures (Part B: Chemical and Electrophoretic Analysis of DNA) Edited by DAVID M. J. LILLEY AND JAMES E. DAHLBERG VOLUME 213. Carotenoids (Part A: Chemistry, Separation, Quantitation, and Antioxidation) Edited by LESTER PACKER VOLUME 214. Carotenoids (Part B: Metabolism, Genetics, and Biosynthesis) Edited by LESTER PACKER VOLUME 215. Platelets: Receptors, Adhesion, Secretion (Part B) Edited by JACEK J. HAWIGER VOLUME 216. Recombinant DNA (Part G) Edited by RAY WU VOLUME 217. Recombinant DNA (Part H) Edited by RAY WU VOLUME 218. Recombinant DNA (Part I) Edited by RAY WU VOLUME 219. Reconstitution of Intracellular Transport Edited by JAMES E. ROTHMAN VOLUME 220. Membrane Fusion Techniques (Part A) Edited by NEJAT DU¨ZGU¨NES, VOLUME 221. Membrane Fusion Techniques (Part B) Edited by NEJAT DU¨ZGU¨NES, VOLUME 222. Proteolytic Enzymes in Coagulation, Fibrinolysis, and Complement Activation (Part A: Mammalian Blood Coagulation Factors and Inhibitors) Edited by LASZLO LORAND AND KENNETH G. MANN

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VOLUME 223. Proteolytic Enzymes in Coagulation, Fibrinolysis, and Complement Activation (Part B: Complement Activation, Fibrinolysis, and Nonmammalian Blood Coagulation Factors) Edited by LASZLO LORAND AND KENNETH G. MANN VOLUME 224. Molecular Evolution: Producing the Biochemical Data Edited by ELIZABETH ANNE ZIMMER, THOMAS J. WHITE, REBECCA L. CANN, AND ALLAN C. WILSON VOLUME 225. Guide to Techniques in Mouse Development Edited by PAUL M. WASSARMAN AND MELVIN L. DEPAMPHILIS VOLUME 226. Metallobiochemistry (Part C: Spectroscopic and Physical Methods for Probing Metal Ion Environments in Metalloenzymes and Metalloproteins) Edited by JAMES F. RIORDAN AND BERT L. VALLEE VOLUME 227. Metallobiochemistry (Part D: Physical and Spectroscopic Methods for Probing Metal Ion Environments in Metalloproteins) Edited by JAMES F. RIORDAN AND BERT L. VALLEE VOLUME 228. Aqueous Two-Phase Systems Edited by HARRY WALTER AND GO¨TE JOHANSSON VOLUME 229. Cumulative Subject Index Volumes 195–198, 200–227 VOLUME 230. Guide to Techniques in Glycobiology Edited by WILLIAM J. LENNARZ AND GERALD W. HART VOLUME 231. Hemoglobins (Part B: Biochemical and Analytical Methods) Edited by JOHANNES EVERSE, KIM D. VANDEGRIFF, AND ROBERT M. WINSLOW VOLUME 232. Hemoglobins (Part C: Biophysical Methods) Edited by JOHANNES EVERSE, KIM D. VANDEGRIFF, AND ROBERT M. WINSLOW VOLUME 233. Oxygen Radicals in Biological Systems (Part C) Edited by LESTER PACKER VOLUME 234. Oxygen Radicals in Biological Systems (Part D) Edited by LESTER PACKER VOLUME 235. Bacterial Pathogenesis (Part A: Identification and Regulation of Virulence Factors) Edited by VIRGINIA L. CLARK AND PATRIK M. BAVOIL VOLUME 236. Bacterial Pathogenesis (Part B: Integration of Pathogenic Bacteria with Host Cells) Edited by VIRGINIA L. CLARK AND PATRIK M. BAVOIL VOLUME 237. Heterotrimeric G Proteins Edited by RAVI IYENGAR VOLUME 238. Heterotrimeric G-Protein Effectors Edited by RAVI IYENGAR

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VOLUME 239. Nuclear Magnetic Resonance (Part C) Edited by THOMAS L. JAMES AND NORMAN J. OPPENHEIMER VOLUME 240. Numerical Computer Methods (Part B) Edited by MICHAEL L. JOHNSON AND LUDWIG BRAND VOLUME 241. Retroviral Proteases Edited by LAWRENCE C. KUO AND JULES A. SHAFER VOLUME 242. Neoglycoconjugates (Part A) Edited by Y. C. LEE AND REIKO T. LEE VOLUME 243. Inorganic Microbial Sulfur Metabolism Edited by HARRY D. PECK, JR., AND JEAN LEGALL VOLUME 244. Proteolytic Enzymes: Serine and Cysteine Peptidases Edited by ALAN J. BARRETT VOLUME 245. Extracellular Matrix Components Edited by E. RUOSLAHTI AND E. ENGVALL VOLUME 246. Biochemical Spectroscopy Edited by KENNETH SAUER VOLUME 247. Neoglycoconjugates (Part B: Biomedical Applications) Edited by Y. C. LEE AND REIKO T. LEE VOLUME 248. Proteolytic Enzymes: Aspartic and Metallo Peptidases Edited by ALAN J. BARRETT VOLUME 249. Enzyme Kinetics and Mechanism (Part D: Developments in Enzyme Dynamics) Edited by DANIEL L. PURICH VOLUME 250. Lipid Modifications of Proteins Edited by PATRICK J. CASEY AND JANICE E. BUSS VOLUME 251. Biothiols (Part A: Monothiols and Dithiols, Protein Thiols, and Thiyl Radicals) Edited by LESTER PACKER VOLUME 252. Biothiols (Part B: Glutathione and Thioredoxin; Thiols in Signal Transduction and Gene Regulation) Edited by LESTER PACKER VOLUME 253. Adhesion of Microbial Pathogens Edited by RON J. DOYLE AND ITZHAK OFEK VOLUME 254. Oncogene Techniques Edited by PETER K. VOGT AND INDER M. VERMA VOLUME 255. Small GTPases and Their Regulators (Part A: Ras Family) Edited by W. E. BALCH, CHANNING J. DER, AND ALAN HALL VOLUME 256. Small GTPases and Their Regulators (Part B: Rho Family) Edited by W. E. BALCH, CHANNING J. DER, AND ALAN HALL

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VOLUME 257. Small GTPases and Their Regulators (Part C: Proteins Involved in Transport) Edited by W. E. BALCH, CHANNING J. DER, AND ALAN HALL VOLUME 258. Redox-Active Amino Acids in Biology Edited by JUDITH P. KLINMAN VOLUME 259. Energetics of Biological Macromolecules Edited by MICHAEL L. JOHNSON AND GARY K. ACKERS VOLUME 260. Mitochondrial Biogenesis and Genetics (Part A) Edited by GIUSEPPE M. ATTARDI AND ANNE CHOMYN VOLUME 261. Nuclear Magnetic Resonance and Nucleic Acids Edited by THOMAS L. JAMES VOLUME 262. DNA Replication Edited by JUDITH L. CAMPBELL VOLUME 263. Plasma Lipoproteins (Part C: Quantitation) Edited by WILLIAM A. BRADLEY, SANDRA H. GIANTURCO, AND JERE P. SEGREST VOLUME 264. Mitochondrial Biogenesis and Genetics (Part B) Edited by GIUSEPPE M. ATTARDI AND ANNE CHOMYN VOLUME 265. Cumulative Subject Index Volumes 228, 230–262 VOLUME 266. Computer Methods for Macromolecular Sequence Analysis Edited by RUSSELL F. DOOLITTLE VOLUME 267. Combinatorial Chemistry Edited by JOHN N. ABELSON VOLUME 268. Nitric Oxide (Part A: Sources and Detection of NO; NO Synthase) Edited by LESTER PACKER VOLUME 269. Nitric Oxide (Part B: Physiological and Pathological Processes) Edited by LESTER PACKER VOLUME 270. High Resolution Separation and Analysis of Biological Macromolecules (Part A: Fundamentals) Edited by BARRY L. KARGER AND WILLIAM S. HANCOCK VOLUME 271. High Resolution Separation and Analysis of Biological Macromolecules (Part B: Applications) Edited by BARRY L. KARGER AND WILLIAM S. HANCOCK VOLUME 272. Cytochrome P450 (Part B) Edited by ERIC F. JOHNSON AND MICHAEL R. WATERMAN VOLUME 273. RNA Polymerase and Associated Factors (Part A) Edited by SANKAR ADHYA VOLUME 274. RNA Polymerase and Associated Factors (Part B) Edited by SANKAR ADHYA

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VOLUME 275. Viral Polymerases and Related Proteins Edited by LAWRENCE C. KUO, DAVID B. OLSEN, AND STEVEN S. CARROLL VOLUME 276. Macromolecular Crystallography (Part A) Edited by CHARLES W. CARTER, JR., AND ROBERT M. SWEET VOLUME 277. Macromolecular Crystallography (Part B) Edited by CHARLES W. CARTER, JR., AND ROBERT M. SWEET VOLUME 278. Fluorescence Spectroscopy Edited by LUDWIG BRAND AND MICHAEL L. JOHNSON VOLUME 279. Vitamins and Coenzymes (Part I) Edited by DONALD B. MCCORMICK, JOHN W. SUTTIE, AND CONRAD WAGNER VOLUME 280. Vitamins and Coenzymes (Part J) Edited by DONALD B. MCCORMICK, JOHN W. SUTTIE, AND CONRAD WAGNER VOLUME 281. Vitamins and Coenzymes (Part K) Edited by DONALD B. MCCORMICK, JOHN W. SUTTIE, AND CONRAD WAGNER VOLUME 282. Vitamins and Coenzymes (Part L) Edited by DONALD B. MCCORMICK, JOHN W. SUTTIE, AND CONRAD WAGNER VOLUME 283. Cell Cycle Control Edited by WILLIAM G. DUNPHY VOLUME 284. Lipases (Part A: Biotechnology) Edited by BYRON RUBIN AND EDWARD A. DENNIS VOLUME 285. Cumulative Subject Index Volumes 263, 264, 266–284, 286–289 VOLUME 286. Lipases (Part B: Enzyme Characterization and Utilization) Edited by BYRON RUBIN AND EDWARD A. DENNIS VOLUME 287. Chemokines Edited by RICHARD HORUK VOLUME 288. Chemokine Receptors Edited by RICHARD HORUK VOLUME 289. Solid Phase Peptide Synthesis Edited by GREGG B. FIELDS VOLUME 290. Molecular Chaperones Edited by GEORGE H. LORIMER AND THOMAS BALDWIN VOLUME 291. Caged Compounds Edited by GERARD MARRIOTT VOLUME 292. ABC Transporters: Biochemical, Cellular, and Molecular Aspects Edited by SURESH V. AMBUDKAR AND MICHAEL M. GOTTESMAN VOLUME 293. Ion Channels (Part B) Edited by P. MICHAEL CONN

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VOLUME 294. Ion Channels (Part C) Edited by P. MICHAEL CONN VOLUME 295. Energetics of Biological Macromolecules (Part B) Edited by GARY K. ACKERS AND MICHAEL L. JOHNSON VOLUME 296. Neurotransmitter Transporters Edited by SUSAN G. AMARA VOLUME 297. Photosynthesis: Molecular Biology of Energy Capture Edited by LEE MCINTOSH VOLUME 298. Molecular Motors and the Cytoskeleton (Part B) Edited by RICHARD B. VALLEE VOLUME 299. Oxidants and Antioxidants (Part A) Edited by LESTER PACKER VOLUME 300. Oxidants and Antioxidants (Part B) Edited by LESTER PACKER VOLUME 301. Nitric Oxide: Biological and Antioxidant Activities (Part C) Edited by LESTER PACKER VOLUME 302. Green Fluorescent Protein Edited by P. MICHAEL CONN VOLUME 303. cDNA Preparation and Display Edited by SHERMAN M. WEISSMAN VOLUME 304. Chromatin Edited by PAUL M. WASSARMAN AND ALAN P. WOLFFE VOLUME 305. Bioluminescence and Chemiluminescence (Part C) Edited by THOMAS O. BALDWIN AND MIRIAM M. ZIEGLER VOLUME 306. Expression of Recombinant Genes in Eukaryotic Systems Edited by JOSEPH C. GLORIOSO AND MARTIN C. SCHMIDT VOLUME 307. Confocal Microscopy Edited by P. MICHAEL CONN VOLUME 308. Enzyme Kinetics and Mechanism (Part E: Energetics of Enzyme Catalysis) Edited by DANIEL L. PURICH AND VERN L. SCHRAMM VOLUME 309. Amyloid, Prions, and Other Protein Aggregates Edited by RONALD WETZEL VOLUME 310. Biofilms Edited by RON J. DOYLE VOLUME 311. Sphingolipid Metabolism and Cell Signaling (Part A) Edited by ALFRED H. MERRILL, JR., AND YUSUF A. HANNUN

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VOLUME 312. Sphingolipid Metabolism and Cell Signaling (Part B) Edited by ALFRED H. MERRILL, JR., AND YUSUF A. HANNUN VOLUME 313. Antisense Technology (Part A: General Methods, Methods of Delivery, and RNA Studies) Edited by M. IAN PHILLIPS VOLUME 314. Antisense Technology (Part B: Applications) Edited by M. IAN PHILLIPS VOLUME 315. Vertebrate Phototransduction and the Visual Cycle (Part A) Edited by KRZYSZTOF PALCZEWSKI VOLUME 316. Vertebrate Phototransduction and the Visual Cycle (Part B) Edited by KRZYSZTOF PALCZEWSKI VOLUME 317. RNA–Ligand Interactions (Part A: Structural Biology Methods) Edited by DANIEL W. CELANDER AND JOHN N. ABELSON VOLUME 318. RNA–Ligand Interactions (Part B: Molecular Biology Methods) Edited by DANIEL W. CELANDER AND JOHN N. ABELSON VOLUME 319. Singlet Oxygen, UV-A, and Ozone Edited by LESTER PACKER AND HELMUT SIES VOLUME 320. Cumulative Subject Index Volumes 290–319 VOLUME 321. Numerical Computer Methods (Part C) Edited by MICHAEL L. JOHNSON AND LUDWIG BRAND VOLUME 322. Apoptosis Edited by JOHN C. REED VOLUME 323. Energetics of Biological Macromolecules (Part C) Edited by MICHAEL L. JOHNSON AND GARY K. ACKERS VOLUME 324. Branched-Chain Amino Acids (Part B) Edited by ROBERT A. HARRIS AND JOHN R. SOKATCH VOLUME 325. Regulators and Effectors of Small GTPases (Part D: Rho Family) Edited by W. E. BALCH, CHANNING J. DER, AND ALAN HALL VOLUME 326. Applications of Chimeric Genes and Hybrid Proteins (Part A: Gene Expression and Protein Purification) Edited by JEREMY THORNER, SCOTT D. EMR, AND JOHN N. ABELSON VOLUME 327. Applications of Chimeric Genes and Hybrid Proteins (Part B: Cell Biology and Physiology) Edited by JEREMY THORNER, SCOTT D. EMR, AND JOHN N. ABELSON VOLUME 328. Applications of Chimeric Genes and Hybrid Proteins (Part C: Protein–Protein Interactions and Genomics) Edited by JEREMY THORNER, SCOTT D. EMR, AND JOHN N. ABELSON

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VOLUME 329. Regulators and Effectors of Small GTPases (Part E: GTPases Involved in Vesicular Traffic) Edited by W. E. BALCH, CHANNING J. DER, AND ALAN HALL VOLUME 330. Hyperthermophilic Enzymes (Part A) Edited by MICHAEL W. W. ADAMS AND ROBERT M. KELLY VOLUME 331. Hyperthermophilic Enzymes (Part B) Edited by MICHAEL W. W. ADAMS AND ROBERT M. KELLY VOLUME 332. Regulators and Effectors of Small GTPases (Part F: Ras Family I) Edited by W. E. BALCH, CHANNING J. DER, AND ALAN HALL VOLUME 333. Regulators and Effectors of Small GTPases (Part G: Ras Family II) Edited by W. E. BALCH, CHANNING J. DER, AND ALAN HALL VOLUME 334. Hyperthermophilic Enzymes (Part C) Edited by MICHAEL W. W. ADAMS AND ROBERT M. KELLY VOLUME 335. Flavonoids and Other Polyphenols Edited by LESTER PACKER VOLUME 336. Microbial Growth in Biofilms (Part A: Developmental and Molecular Biological Aspects) Edited by RON J. DOYLE VOLUME 337. Microbial Growth in Biofilms (Part B: Special Environments and Physicochemical Aspects) Edited by RON J. DOYLE VOLUME 338. Nuclear Magnetic Resonance of Biological Macromolecules (Part A) Edited by THOMAS L. JAMES, VOLKER DO¨TSCH, AND ULI SCHMITZ VOLUME 339. Nuclear Magnetic Resonance of Biological Macromolecules (Part B) Edited by THOMAS L. JAMES, VOLKER DO¨TSCH, AND ULI SCHMITZ VOLUME 340. Drug–Nucleic Acid Interactions Edited by JONATHAN B. CHAIRES AND MICHAEL J. WARING VOLUME 341. Ribonucleases (Part A) Edited by ALLEN W. NICHOLSON VOLUME 342. Ribonucleases (Part B) Edited by ALLEN W. NICHOLSON VOLUME 343. G Protein Pathways (Part A: Receptors) Edited by RAVI IYENGAR AND JOHN D. HILDEBRANDT VOLUME 344. G Protein Pathways (Part B: G Proteins and Their Regulators) Edited by RAVI IYENGAR AND JOHN D. HILDEBRANDT VOLUME 345. G Protein Pathways (Part C: Effector Mechanisms) Edited by RAVI IYENGAR AND JOHN D. HILDEBRANDT

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VOLUME 346. Gene Therapy Methods Edited by M. IAN PHILLIPS VOLUME 347. Protein Sensors and Reactive Oxygen Species (Part A: Selenoproteins and Thioredoxin) Edited by HELMUT SIES AND LESTER PACKER VOLUME 348. Protein Sensors and Reactive Oxygen Species (Part B: Thiol Enzymes and Proteins) Edited by HELMUT SIES AND LESTER PACKER VOLUME 349. Superoxide Dismutase Edited by LESTER PACKER VOLUME 350. Guide to Yeast Genetics and Molecular and Cell Biology (Part B) Edited by CHRISTINE GUTHRIE AND GERALD R. FINK VOLUME 351. Guide to Yeast Genetics and Molecular and Cell Biology (Part C) Edited by CHRISTINE GUTHRIE AND GERALD R. FINK VOLUME 352. Redox Cell Biology and Genetics (Part A) Edited by CHANDAN K. SEN AND LESTER PACKER VOLUME 353. Redox Cell Biology and Genetics (Part B) Edited by CHANDAN K. SEN AND LESTER PACKER VOLUME 354. Enzyme Kinetics and Mechanisms (Part F: Detection and Characterization of Enzyme Reaction Intermediates) Edited by DANIEL L. PURICH VOLUME 355. Cumulative Subject Index Volumes 321–354 VOLUME 356. Laser Capture Microscopy and Microdissection Edited by P. MICHAEL CONN VOLUME 357. Cytochrome P450, Part C Edited by ERIC F. JOHNSON AND MICHAEL R. WATERMAN VOLUME 358. Bacterial Pathogenesis (Part C: Identification, Regulation, and Function of Virulence Factors) Edited by VIRGINIA L. CLARK AND PATRIK M. BAVOIL VOLUME 359. Nitric Oxide (Part D) Edited by ENRIQUE CADENAS AND LESTER PACKER VOLUME 360. Biophotonics (Part A) Edited by GERARD MARRIOTT AND IAN PARKER VOLUME 361. Biophotonics (Part B) Edited by GERARD MARRIOTT AND IAN PARKER VOLUME 362. Recognition of Carbohydrates in Biological Systems (Part A) Edited by YUAN C. LEE AND REIKO T. LEE

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VOLUME 363. Recognition of Carbohydrates in Biological Systems (Part B) Edited by YUAN C. LEE AND REIKO T. LEE VOLUME 364. Nuclear Receptors Edited by DAVID W. RUSSELL AND DAVID J. MANGELSDORF VOLUME 365. Differentiation of Embryonic Stem Cells Edited by PAUL M. WASSAUMAN AND GORDON M. KELLER VOLUME 366. Protein Phosphatases Edited by SUSANNE KLUMPP AND JOSEF KRIEGLSTEIN VOLUME 367. Liposomes (Part A) Edited by NEJAT DU¨ZGU¨NES, VOLUME 368. Macromolecular Crystallography (Part C) Edited by CHARLES W. CARTER, JR., AND ROBERT M. SWEET VOLUME 369. Combinational Chemistry (Part B) Edited by GUILLERMO A. MORALES AND BARRY A. BUNIN VOLUME 370. RNA Polymerases and Associated Factors (Part C) Edited by SANKAR L. ADHYA AND SUSAN GARGES VOLUME 371. RNA Polymerases and Associated Factors (Part D) Edited by SANKAR L. ADHYA AND SUSAN GARGES VOLUME 372. Liposomes (Part B) Edited by NEJAT DU¨ZGU¨NES, VOLUME 373. Liposomes (Part C) Edited by NEJAT DU¨ZGU¨NES, VOLUME 374. Macromolecular Crystallography (Part D) Edited by CHARLES W. CARTER, JR., AND ROBERT W. SWEET VOLUME 375. Chromatin and Chromatin Remodeling Enzymes (Part A) Edited by C. DAVID ALLIS AND CARL WU VOLUME 376. Chromatin and Chromatin Remodeling Enzymes (Part B) Edited by C. DAVID ALLIS AND CARL WU VOLUME 377. Chromatin and Chromatin Remodeling Enzymes (Part C) Edited by C. DAVID ALLIS AND CARL WU VOLUME 378. Quinones and Quinone Enzymes (Part A) Edited by HELMUT SIES AND LESTER PACKER VOLUME 379. Energetics of Biological Macromolecules (Part D) Edited by JO M. HOLT, MICHAEL L. JOHNSON, AND GARY K. ACKERS VOLUME 380. Energetics of Biological Macromolecules (Part E) Edited by JO M. HOLT, MICHAEL L. JOHNSON, AND GARY K. ACKERS VOLUME 381. Oxygen Sensing Edited by CHANDAN K. SEN AND GREGG L. SEMENZA

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VOLUME 382. Quinones and Quinone Enzymes (Part B) Edited by HELMUT SIES AND LESTER PACKER VOLUME 383. Numerical Computer Methods (Part D) Edited by LUDWIG BRAND AND MICHAEL L. JOHNSON VOLUME 384. Numerical Computer Methods (Part E) Edited by LUDWIG BRAND AND MICHAEL L. JOHNSON VOLUME 385. Imaging in Biological Research (Part A) Edited by P. MICHAEL CONN VOLUME 386. Imaging in Biological Research (Part B) Edited by P. MICHAEL CONN VOLUME 387. Liposomes (Part D) Edited by NEJAT DU¨ZGU¨NES, VOLUME 388. Protein Engineering Edited by DAN E. ROBERTSON AND JOSEPH P. NOEL VOLUME 389. Regulators of G-Protein Signaling (Part A) Edited by DAVID P. SIDEROVSKI VOLUME 390. Regulators of G-Protein Signaling (Part B) Edited by DAVID P. SIDEROVSKI VOLUME 391. Liposomes (Part E) Edited by NEJAT DU¨ZGU¨NES, VOLUME 392. RNA Interference Edited by ENGELKE ROSSI VOLUME 393. Circadian Rhythms Edited by MICHAEL W. YOUNG VOLUME 394. Nuclear Magnetic Resonance of Biological Macromolecules (Part C) Edited by THOMAS L. JAMES VOLUME 395. Producing the Biochemical Data (Part B) Edited by ELIZABETH A. ZIMMER AND ERIC H. ROALSON VOLUME 396. Nitric Oxide (Part E) Edited by LESTER PACKER AND ENRIQUE CADENAS VOLUME 397. Environmental Microbiology Edited by JARED R. LEADBETTER VOLUME 398. Ubiquitin and Protein Degradation (Part A) Edited by RAYMOND J. DESHAIES VOLUME 399. Ubiquitin and Protein Degradation (Part B) Edited by RAYMOND J. DESHAIES VOLUME 400. Phase II Conjugation Enzymes and Transport Systems Edited by HELMUT SIES AND LESTER PACKER

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VOLUME 401. Glutathione Transferases and Gamma Glutamyl Transpeptidases Edited by HELMUT SIES AND LESTER PACKER VOLUME 402. Biological Mass Spectrometry Edited by A. L. BURLINGAME VOLUME 403. GTPases Regulating Membrane Targeting and Fusion Edited by WILLIAM E. BALCH, CHANNING J. DER, AND ALAN HALL VOLUME 404. GTPases Regulating Membrane Dynamics Edited by WILLIAM E. BALCH, CHANNING J. DER, AND ALAN HALL VOLUME 405. Mass Spectrometry: Modified Proteins and Glycoconjugates Edited by A. L. BURLINGAME VOLUME 406. Regulators and Effectors of Small GTPases: Rho Family Edited by WILLIAM E. BALCH, CHANNING J. DER, AND ALAN HALL VOLUME 407. Regulators and Effectors of Small GTPases: Ras Family Edited by WILLIAM E. BALCH, CHANNING J. DER, AND ALAN HALL VOLUME 408. DNA Repair (Part A) Edited by JUDITH L. CAMPBELL AND PAUL MODRICH VOLUME 409. DNA Repair (Part B) Edited by JUDITH L. CAMPBELL AND PAUL MODRICH VOLUME 410. DNA Microarrays (Part A: Array Platforms and Web-Bench Protocols) Edited by ALAN KIMMEL AND BRIAN OLIVER VOLUME 411. DNA Microarrays (Part B: Databases and Statistics) Edited by ALAN KIMMEL AND BRIAN OLIVER VOLUME 412. Amyloid, Prions, and Other Protein Aggregates (Part B) Edited by INDU KHETERPAL AND RONALD WETZEL VOLUME 413. Amyloid, Prions, and Other Protein Aggregates (Part C) Edited by INDU KHETERPAL AND RONALD WETZEL VOLUME 414. Measuring Biological Responses with Automated Microscopy Edited by JAMES INGLESE VOLUME 415. Glycobiology Edited by MINORU FUKUDA VOLUME 416. Glycomics Edited by MINORU FUKUDA VOLUME 417. Functional Glycomics Edited by MINORU FUKUDA VOLUME 418. Embryonic Stem Cells Edited by IRINA KLIMANSKAYA AND ROBERT LANZA

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Isolation, Identification, and Production of Posttranslationally Modified Chemokines Tamara Loos,*,1 Anneleen Mortier,*,1 and Paul Proost* Contents 1. Introduction 2. Isolation and Stimulation of Peripheral Blood Mononuclear Cells (PBMC) 3. Concentration of Isolated Proteins 4. Affinity Chromatography 5. Specific Sandwich Enzyme-Linked Immunosorbent Assay (ELISA) 6. Sodium Dodecyl Sulfate-Polyacrylamide Gel Electrophoresis (SDS-PAGE) 7. Ion Exchange Chromatography 8. Reverse-Phase High-Pressure Liquid Chromatography (RP-HPLC) 9. Ion Trap Mass Spectrometry 10. Edman Degradation 11. Total Protein Quantification Methods 12. Illustration: Isolation and Identification of Natural Posttranslationally Modified CXCL8 Isoforms 13. Solid-Phase Peptide Synthesis 13.1. Synthesis of the peptide chain 13.2. Deprotection of the synthesized peptide chain 13.3. Folding of the raw protein 14. Citrullination of Chemokines 15. Identification of Enzymes Generating the Natural Posttranslationally Modified Chemokines, as Exemplified by Aminopeptidase N(APN)/CD13 16. Comparison of the Heparin-Binding Properties of Chemokine Isoforms Acknowledgments References

* 1

4 5 6 7 7 8 9 10 10 11 12 13 14 15 19 19 21

23 24 25 25

Laboratory of Molecular Immunology, Rega Institute for Medical Research, Leuven, Belgium Both authors contributed equally

Methods in Enzymology, Volume 461 ISSN 0076-6879, DOI: 10.1016/S0076-6879(09)05401-9

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2009 Elsevier Inc. All rights reserved.

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Abstract Chemokines attract cells during the development of lymphoid tissues, leukocyte homing, and pathologic processes such as cancer and inflammation. Limited posttranslational modification of chemokines may significantly alter the glycosaminoglycan and/or receptor binding properties and signaling potency of these chemotactic proteins. To compare the in vitro and in vivo biologic activities of posttranslationally modified chemokine isoforms, considerable amounts of pure chemokine isoforms are required. This chapter describes a number of chromatographic techniques that are useful for the isolation of natural, posttranslationally modified chemokines from primary human cell cultures. In addition, combination of immunologic assays and biochemical techniques such as automated Edman degradation and mass spectrometry are used for the identification of modifications. Alternate methods for the generation of specific chemokine isoforms are discussed such as modification of chemokines by specific enzymes and total chemical syntheses and folding of chemokine isoforms. In particular, in vitro processing of chemokines by the protease aminopeptidase N/CD13 and citrullination or deamination of chemokines by peptidyl arginine deiminases (PAD) are described as methods for the confirmation or generation of posttranslationally modified chemokine isoforms.

1. Introduction Chemokines are crucial proteins for the directed migration of leukocytes during the development of lymphoid tissue, leukocyte homing, and inflammation (Springer, 1994). The regulation of chemokine activity is a crucial event for the outcome of the immune response. Posttranslational modifications were reported to regulate chemokine activity in addition to regulation of chemokine and chemokine receptor expression levels, the production of ‘‘decoy’’ or ‘‘scavenging’’ chemokine receptors, presentation of chemokines on glycosaminoglycans, and synergistic activity between chemokines and other chemotactic factors (Colditz et al., 2007; Gouwy et al., 2005; Johnson et al., 2005; Mantovani et al., 2006; Mortier et al., 2008). Since the discovery of the first inflammatory chemokines, proteolytic processing or glycosylation was detected on inflammatory chemokines such as CXCL8/interleukin-8 (IL-8), CXCL7/NAP-2 (neutrophil-activating peptide-2), and CCL2/MCP-1 (monocyte chemotactic protein-1) (Brandt et al., 1991; Furutani et al., 1989; Jiang et al., 1990; Robinson et al., 1989; Van Damme et al., 1989b; Walz et al., 1990). Recently, deaminated or citrullinated natural chemokines were also identified (Loos et al., 2008; Proost et al., 2008). Although for some chemokines, such as CXCL7, the importance of posttranslational processing for the regulation of

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chemokine activity was evidenced even before the identification of chemokine receptors, the presence and biologic consequences of other modifications were only recently resolved. For others (e.g., glycosylation of CCL2) the biologic consequences are still to be determined. The limited availability of the posttranslationally modified chemokines was and often remains an obstacle for detailed biochemical and biologic characterization. Gene regulation studies revealed that the chemokine production pattern depends much on the cell type and inducers used (Loos et al., 2006; Proost et al., 2003, 2004b). Moreover, the abundance of different posttranslationally modified isoforms of a particular chemokine varies within cell sorts (Gimbrone et al., 1989; Schro¨der et al., 1990; Van Damme et al., 1989a; Yoshimura et al., 1989). In an attempt to isolate novel CXCL8 and CXCL10/IP-10 (interferon-gamma–inducible protein-10) isoforms, induction experiments were performed on peripheral blood–derived mononuclear cells (PBMC) followed by a four-step purification procedure (Loos et al., 2008; Proost et al., 2008). First, the conditioned medium was concentrated to controlled pore glass or silicic acid, followed by the purification to homogeneity by heparin affinity, ion exchange, and reverse-phase high-pressure liquid chromatography (RP-HPLC). Immunoreactivity, quantity, and purity of the chemokine-containing fractions between each step were analyzed with specific enzyme-linked immunosorbent assays (ELISA) and sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE). Finally, ion trap mass spectrometry and Edman degradation were applied to identify posttranslational modifications. Protein quantification was performed with the Bradford or bicinchoninic acid (BCA) total protein assays. Alternatively, posttranslationally modified chemokines were chemically synthesized or recombinant chemokines were enzymatically processed in vitro to verify or generate modified isoforms.

2. Isolation and Stimulation of Peripheral Blood Mononuclear Cells (PBMC) Freshly isolated buffy coats (Blood Transfusion Center Red Cross, Leuven, Belgium) are treated with one volume of hydroxyethyl-starch (Plasmasteril, Fresenius, Bad Homburg, Germany) and one volume of Dulbecco’s phosphate-buffered saline (DPBS; 0.0095 M phosphate buffer, pH 7.35, without Ca2þ and Mg2þ) for 30 min at 37  C, resulting in the sedimentation of most erythrocytes (Van Damme et al., 1997, 2000). After centrifugation of the supernatant at 200g for 10 min, the pellet is washed with 50 ml PBS. Next, the resuspended pellet is loaded on top of three volumes of Ficoll-sodium metrizoate (Lymphoprep, Nycomed, Oslo, Norway), and mononuclear cells and granulocytes are segregated by

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gradient centrifugation at 400g for 30 min (without brakes). The PBMC appearing in the transition layer are removed and washed twice with PBS. Finally, the pellet is resuspended in RPMI 1640 enriched with 2% fetal calf serum (FCS) at an appropriate concentration (typically 2.106 to 5.106 cells/ ml) and stimulated with cytokines and/or Toll-like receptor (TLR) ligands. Serum is a very rich and complex source of growth factors and other proteins. This increases the chemokine production yield, although an addition of more then 2% FCS severely complicates purification of chemokines to homogeneity. After 24 to 96 h of culture at 37  C in the presence of 5% CO2, the conditioned medium is harvested, centrifuged at 200g, subsequently at 1000g, and finally stored at 20  C until purification to homogeneity. Because of the minute amounts of chemokines produced (typically ng/ml range), liters of conditioned medium are required if an amount of chemokine needs to be purified sufficient for subsequent biologic characterization.

3. Concentration of Isolated Proteins A tenfold concentration of the proteins present is obtained by adsorption to controlled pore glass (CPG) (Proost et al., 2004a; Struyf et al., 2000; Wuyts et al., 1997). During the production process of the CPG, the borosilicate base is heated until the borate is released from the silicate and pores are formed (particle size: 120 to 200 mesh; pore size: 35 nm; Serva, Heidelberg, Germany). These pores increase the surface of the matrix, the yield, and the purity of the proteins. The rather expensive CPG beads may be regenerated chemically by cleaning with concentrated nitric acid that degrades the proteins that are still present on the CPG beads after the elution procedure. Therefore, the use of silicic acid is often preferred (Matrex silica, particle size: 35 to 70 mm; pore size: 10 mm; Amicon, Beverly, MA). The binding to CPG (30 ml/L conditioned medium) and silicic acid (10 g/L) should be performed at neutral pH and 4  C for 2 h to acquire proper ionic interactions between the negatively charged silica and the positively charged proteins. Next, the CPG or the silicic acid is washed for 30 min with 10 mM glycine, pH 3.5, or DPBS containing 1 M NaCl, pH 7.4, respectively. The proteins are eluted from the CPG beads by adding 300 mM glycine, pH 2.0, to destroy the ionic interactions and hydrogen bonds. The elution from the silicic acid is performed by adding DPBS, pH 7.4, containing 1.4 M NaCl, breaking ionic interactions, and 50% ethylene glycol, splitting hydrogen bonds. An additional step of 300 mM glycine, pH 2.0, can be introduced to remove remaining proteins and thereby improve the yield. If acid-stable proteins need to be purified, this step may be implemented immediately. Finally, the eluate is neutralized and desalted through dialysis with a 3.5-kDa cutoff membrane against 50 mM TRIS and 50 mM NaCl,

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pH 7.4. During the last dialysis step, 15% polyethylene glycol (PEG) (average molecular mass, 20,000) may be added to concentrate the preparation to a smaller volume before subjection to affinity chromatography.

4. Affinity Chromatography Because chemokines are characterized by a high affinity for heparin, bulk impurities are removed with heparin affinity chromatography ( Janson and Ryden, 1989; Wuyts et al., 1997). The dialyzed eluate recovered from CPG or silicic acid adsorption is loaded on a heparin-Sepharose CL 6B column (GE Healthcare, Diegem, Belgium) in equilibration buffer (50 mM TRIS, pH 7.4, containing 50 mM NaCl). Elution from the column is performed at a flow rate of 20 ml/h (60 ml bed volume) by administrating an increasing NaCl gradient starting from 50 mM to 2 M in equilibration buffer, hereby first eluting the low-affinity proteins because of competition with Naþ ions for interaction with heparin. The column is regenerated by rinsing with 0.1 M TRIS, pH 8.5, containing 50 mM NaCl and subsequently with 0.1 M NaAc, pH 5.0, containing 0.5 M NaCl. Alternately, if a certain chemokine is aspired, specific antibody affinity chromatography can be applied (Wuyts et al., 1997). Purified antichemokine antibody is coupled to CNBr-activated Sepharose 4B (GE Healthcare). The amount of Sepharose required (1 g/3.5 ml final gel volume) is weight out and washed with 1 mM HCl on a sintered glass filter resulting in it swelling and forming a gel suspension. The antibody (5 to 10 mg/ml final gel) is dissolved in coupling buffer consisting of 0.1 M NaHCO3, pH 8.3, containing 0.5 M NaCl before mixing end-over-end with the Sepharose gel for 2 h at room temperature or overnight at 4  C. The remaining active groups on the Sepharose beads are blocked by adding 0.2 M glycine, pH 8.0, for 2 h at room temperature or overnight at 4  C. The excess antibody is washed away with coupling buffer alternating with a 0.1 M acetate buffer, pH 4.0, containing 0.5 M NaCl. Finally, the empty column is packed with the antibody-bound Sepharose. In analogy with heparin affinity chromatography, the chemokine preparation is equilibrated in DPBS, pH 7.5, before loading onto the column, and stepwise elution is obtained by administrating a 0.1 M NaCl buffer containing 0.1 M citrate, pH 2.0, at a flow rate of 40 ml/h.

5. Specific Sandwich Enzyme-Linked Immunosorbent Assay (ELISA) Fractions containing immunoreactivity are detected by specific sandwich enzyme-linked immunosorbent assays (ELISA). A 96-well ELISA plate is coated overnight at 4  C with a specific primary antibody reconstituted

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in DPBS. Unbound proteins are washed away with DPBS containing 0.05% Tween-20 (v/v) that decreases the surface tension. Next, empty regions on the plastic are blocked with 0.1% casein (w/v) in DPBS containing 0.05% Tween-20 for 1 h at 37  C. Samples are diluted in the same blocking buffer, and appropriate antigen binds to the primary antibody in the course of 2 h at 37  C. Subsequently, a secondary specific antibody originating from a different organism is added for 1 h at 37  C. Then, the plate is washed and the secondary antibody is targeted by a horseradish peroxidase (HRP)– labeled tertiary antibody for 30 min at 37  C. Alternately, the secondary antibody can be tagged with biotin recognized by HRP-labeled streptavidin. The chromogen 3,30 ,5,50 -tetramethylbenzidine (TMB; 0.42 mM; SigmaAldrich, St. Louis, MO) reconstituted in 0.1 M NaAc and 0.1 M citrate, pH 4.9, supplemented with 0.004% H2O2 (v/v) is added to the wells. The H2O2 is reduced into water by peroxidase, causing the colorless TMB chromogen to oxidize into a blue product. This reaction is stopped by adding an equal volume of 1 M H2SO4, resulting in development of a yellow color. The intensity of the yellow color is proportional to the amount of HRP and hence to the amount of bound chemokine. The optical density is measured at 450 nm with a spectrofluorometer (Titertek, Huntsville, Al). The concentration of bound antigen can be determined by implementing a dilution series of a chemokine standard.

6. Sodium Dodecyl Sulfate-Polyacrylamide Gel Electrophoresis (SDS-PAGE) The purity of the chemokine preparations is evaluated by SDS-PAGE ( Janson and Ryden, 1989; Kinter et al., 2000; Wuyts et al., 1997). To detect 5- to 20-kDa proteins, TRIS/Tricine gels consisting of three layers differing in acrylamide versus bisacrylamide composition (% T and % C) are used according to Eqs. (1.1) and (1.2) (Schagger et al., 1987).

% T ¼ ½acrylamide ðgÞ þ bisacrylamide ðgÞ  100=100ml

ð1:1Þ

% C ¼ bisacrylamide ðgÞ  100=½acrylamide ðgÞ þ bisacrylamide ðgÞ ð1:2Þ The upper layer, also called the ‘‘stacking’’ gel, contains the largest pores and concentrates the sample (5% T and 5% C). The ‘‘spacer’’ gel is the middle layer, separating the small proteins from the bulk (10% T and 3.3% C). The third and lowest layer is the ‘‘separating’’ layer, consisting of smaller pore sizes, resolving proteins in individual bands (13% T and 5% C). All gels are prepared in 3 M TRIS, pH 8.5, containing 0.3% SDS. N,N,N0 ,

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N0 -tetramethyl ethylenediamine (TEMED) (0.066%) and ammonium persulfate (0.66%) are added to initialize polymerization. The separating gel also contains 10% glycerol to avoid mixture with the spacer gel. Isobutanol is deposited on top of the spacer gel to avoid interference of oxygen that oxidizes radicals and, therefore, may prevent polymerization. Samples are loaded in 50 mM TRIS, pH 6.8, containing 4% SDS, 12% glycerol, 2% b-mercaptoethanol, 0.01% Brilliant Blue G (tracking dye; Bio-Rad Laboratories, Hercules, CA), and denaturation is performed by heating at 95  C for 5 min before loading onto the stacking gel. The anode buffer in the electrophoresis system contains 0.2 M TRIS, pH 8.9, whereas the upper cathode buffer consists of 0.1 M TRIS, pH 8.2, 0.1 M Tricine, and 0.1% SDS. Proteins are visualized by silver staining (Guevara Jr et al., 1982). To decrease background noise, the SDS-PAGE components are removed by resting the gel for 1 h in 20% ethanol, 5% acetic acid, and 2.5% sulfosalicylic acid, followed by three washes with 20% ethanol. The shrunk gel is then placed in silver staining solution. A solution of 1g AgNO3 in 10 ml degassed water is prepared and added dropwise to a mixture containing 2.1 ml 14.8 M NH4OH, 0.35 ml NaOH (32% w/v), and 40 ml ethanol in 150 ml degassed water. After 1 h, the gel is washed three times with 20% ethanol and developed in 20% ethanol, 0.01% citric acid, and 0.037% formaldehyde, which oxidizes Ag ions bound to protein clusters. Reduction of these oxidized Ag ions by citric acid results in the deposition of Ag. Development is stopped by treatment with 20% ethanol and 0.5% acetic acid. The gel is then washed for 30 min in water and stored overnight in 50% ethanol. Subsequently, gels and a small volume of 50% ethanol (to prevent the gels from drying) may be packed between sealed plastic sheets and stored for weeks in the dark at 4  C. Evaluation of the relative molecular mass (Mr) and the amount of proteins can be achieved by comparison with a standardized mixture of proteins (100 ng each) containing myosin (200 kDa), b-galactosidase (116.3 kDa), phosphorylase B (97.4 kDa), bovine serum albumin (66.3 kDa), glutamic dehydrogenase (55.4 kDa), lactate dehydrogenase (36.5 kDa), carbonic anhydrase (31 kDa), trypsin inhibitor (21.5 kD), lysozyme (14.4 kDa), aprotinin (6 kDa), and insulin B chain (3.5 kDa) (Bio-Rad Laboratories).

7. Ion Exchange Chromatography Most chemokines have a high pI. Therefore, chemokines may be separated with cation exchange chromatography ( Janson and Ryden, 1989; Wuyts et al., 1997). The cation exchanger applied consists of small, perfectly spherical MonoBeads based on a 10-mm beaded hydrophilic polystyrene/divinyl benzene resin substituted with methyl sulfonate groups

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(Mono S, GE Healthcare). The advantages of MonoBeads are its chemical (pH range from 2 to 12; resistance to organic solvents) and physical stability and high-resolution separating capacity. Affinity chromatography–purified samples are dissolved in 50 mM formate, pH 4.0, and proteins are eluted from the column in a 0 to 1 M NaCl gradient in 50 mM formate, pH 4.0, in 30 min at a flow rate of 1 ml/min.

8. Reverse-Phase High-Pressure Liquid Chromatography (RP-HPLC) In a final step, the difference in hydrophobicity between chemokines is exploited to purify chemokines to homogeneity by reverse-phase highpressure liquid chromatography (RP-HPLC) ( Janson and Ryden, 1989; Wuyts et al., 1997). A silica-based matrix with octyl C8 n-alkyl hydrocarbon derivatives is used (2.1  220-mm Brownlee C8 Aquapore RP-300 column, Perkin-Elmer, Norwalk, CT). This matrix is especially suitable for the purification of hydrophobic molecules and for the separation of closely related proteins. Because certain chemokines only elute from C18 columns at high solvent concentrations, C8 columns are preferred. Proteins that eluted from cation exchange columns in a salt gradient at pH 4.0 are loaded on the column. Columns are washed with 0.1% trifluoroacetic acid (TFA) and eluted by applying an acetonitrile gradient (0 to 80%) in 0.1% TFA at a flow rate of 0.4 ml/min (for columns with an internal diameter of 2.1 mm). Detection is performed by ultraviolet (UV) adsorption at 214 nm and/or electrospray ion trap mass spectrometry after splitting the eluate (1/150) online.

9. Ion Trap Mass Spectrometry Mass spectrometry is a powerful technique to identify the Mr of a compound on the basis of the ratio mass/charge (m/z). Here, electrospray ionization is combined with an ion trap mass analyzer (Esquire LC, Bruker Daltonics, Bremen, Germany). The sample is either diluted in 50% acetonitrile in 0.1% acetic acid and manually injected at a flow rate of 300 ml/h or online analyzed from the split outlet of the HPLC system (at a flow rate of 160 ml/h). A small diameter needle subjected to high voltage then sprays the sample. The protons from the acid render the proteins in the droplets positively charged, causing them to move toward the negatively charged instrument. By applying heat (300  C) and a flow of heated nitrogen, the droplets evaporate during the spray until the gas phase is reached. The major advantage of electrospray ionization in acidic conditions is the compatibility

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with RP-HPLC and its tendency to protonate at basic sites, which results in multiply charged ions with a proton for the NH2-terminus and for several basic residues present in the peptide (M þ nHþ). The use of detergents such as SDS should be avoided, because they render peptides negative, making them less detectable, and modify the surface tension, interfering with the evaporation of the charged droplet (Kinter and Sherman, 2000). Chemokines diluted in 0.1% acetic acid or 0.1% TFA will produce ions carrying typically 5 to 15 positive charges. Although use of acetic or formic acid results in a higher sensitivity on the mass spectrometer, TFA is often used when mass spectrometry is preceded by RP-HPLC, because gradients in TFA result in sharper elution profiles for proteins from RP-HPLC columns. A data analysis program (Bruker Daltonics) deconvolutes the spectrum and calculates the molecular mass of the uncharged protein from the multiple charged ions.

10. Edman Degradation Automated amino acid sequence analysis (Procise 491 cLC protein sequencer, Applied Biosystems, Foster City, CA) is based on the Edman degradation reaction (Edman, 1949; Edman et al., 1967; Hunkapiller et al., 1978; Kinter et al., 2000). The NH2-terminal amino acid is quantitatively coupled to phenylisothiocyanate (PITC), forming a phenylthiocarbamoyl (PTC)-derivative in the presence of N-methyl piperidine at 48  C. After removing the excess PITC with n-heptane and ethyl acetate, 100% TFA is added, resulting in the cleavage of the peptide bond between the first two NH2-terminal amino acids, leaving the second amino acid available for a new Edman degradation cycle. The PTC derivative of the NH2-terminal amino acid is released as an anilinothiazolinone (ATZ) derivative and, after extraction with 1-chlorobutane and transfer to a conversion chamber, is rapidly converted into a more stable phenylthiohydantoin (PTH) derivative in the presence of 25% TFA at 64  C. Next, the PTH derivative is loaded onto a Procise cLC PTH RP-HPLC column (0.8  250 mm) and eluted in a gradient of solvent A (3.5% tetrahydrofuran in water supplemented with 15 ml/L Premix buffer, Applied Biosystems) and solvent B (12.5% v/v isopropanol in acetonitrile) at 55  C, and UV absorbance of the PTH-amino acids is detected at 270 nm. After comparing the observed elution time with known eluting positions of a standardized mixture of PTH amino acids, the released NH2-terminal amino acid can be identified. Some chemokines are obstructed by an NH2-terminal modification, such as pyroglutamic acid for the CC chemokines CCL2, CCL7, and CCL8. PITC is unable to couple to these modified NH2-termini, which renders these proteins resistant to Edman degradation. If these proteins contain Asp-Pro sequences (which is the case for a number of chemokines), formic acid (75% at 37  C for 48 to 72 h)

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cleaves these proteins, specifically between Asp and Pro, making the released COOH-terminal peptide accessible to Edman degradation.

11. Total Protein Quantification Methods Although protein concentration can be estimated by comparison with an internal benchmark with a specific sandwich ELISA, SDS-PAGE, mass spectrometry, or Edman degradation, a chemokine preparation purified to homogeneity can also be quantified with total protein detection assays such as the Bradford or BCA assay. The Bradford protein assay uses the binding properties of the dye Coomassie brilliant blue G-250 (Bio-Rad Laboratories) (Bradford, 1976). When the unbound red/brown dye binds to proteins, a conformational change occurs in its structure resulting in a spectral shift from an absorption maximum of 465 nm (green) to 595 nm (blue). The optimal wavelength to measure the blue color from the Coomassie dye-protein complex is 595 nm, because the difference between the two forms of the dye is then greatest. However, the Coomassie dye is incompatible with surfactants, excluding the technique for samples reconstituted with solubilizing detergent. In practice, sample dilutions and dilution series of bovine serum albumin (BSA) are prepared in a 96-well plate (100 ml/well) and 200 ml of Coomassie dye (1/5 diluted in DPBS) is added. Absorption can be measured immediately at 595 nm. In addition, the bicinchoninic acid (BCA) assay is prevalently used, a method based on the biuret reaction (Smith et al., 1985). In alkaline medium, peptides of 3 amino acids or larger reduce Cu2þ into Cu1þ forming a blue-colored chelated complex. Such complex is formed between one Cu1þ ion and four to six nearby peptides bonds, which is proportional to the intensity of the color. BCA selectively and with high sensitivity recognizes these Cu1þ ions, resulting in a purple color complex. The optimal wavelength is 562 nm, where a strong linearity exists between the absorbance and the protein concentration. Dilution series of BSA, starting at a concentration of 2 mg/ml, and chemokines are prepared in a volume of 25 ml in a 96-well plate. Next, 200 ml of dye (1/50 reagent B/A) (Pierce, Thermo Fischer Scientific) is added to each well. After 30 min of incubation at 37  C, the absorbance is measured at 562 nm. Because colorimetric development in most assays is related to the amino acid composition of the protein, it is advisable to apply multiple quantification methods in parallel to avoid misinterpretation. In the BCA assay, the presence of cysteine, cystine, tyrosine, and tryptophan can influence the outcome of the assay, whereas in the Bradford assay, the relative abundance of the amino acids arginine, lysine, and histidine is important.

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12. Illustration: Isolation and Identification of Natural Posttranslationally Modified CXCL8 Isoforms PBMC from 24 buffy coats were pooled (11.4  109 cells) and induced at 5  106 cells/ml with 10 mg/ml of the TLR3 ligand and double-stranded RNA polyriboinosinic: polyribocytidylic acid (polyrI:rC) and 20 ng/ml interferon-g (IFN-g) in RPMI 1640 containing 2% FCS. CXCL8 was isolated from the conditioned medium by described four-step purification method. After adsorption to silicic acid, the eluate was subjected to heparin Sepharose chromatography (GE Healthcare) (Fig. 1.1A). Besides CXCL8 protein, other chemokines were also detected such as CCL2, CCL7, CCL8, CXCL4, CXCL9, CXCL10, and CXCL11 as evidenced by specific sandwich ELISA (data not shown). Heparin Sepharose column fractions 7 to 9, which contain the most CXCL8 immunoreactivity, were pooled and loaded on a Mono S cation exchange column (GE Healthcare). CXCL8 eluted from the column at approximately 0.75 M NaCl after 63 min, as evidenced by ELISA (Fig. 1.1B). Fractions 64 to 66 (elution time 63 to 66 min) (Fig. 1.1C) and 67 to 70 (elution time 66 to 70 min) (data not shown) recovered from the ion exchange column were loaded on a 2.1  220-mm Brownlee C8 Aquapore RP-300 HPLC column (PerkinElmer) in 0.1% TFA. CXCL8 isoforms eluted from the column at approximately 31% acetonitrile and were collected in 1-min fractions. Online mass spectrometry showed the presence of three major proteins eluting from the RP-HPLC column after 55 to 61 min (Fig. 1.1D). Deconvolution of the spectra resulted in the detection of three CXCL8 isoforms in fraction 56 that were differently processed at their NH2-terminus (i.e. CXCL8[2 to 77], CXCL8[1 to 77], and CXCL8[6 to 77]). Additional analysis of the proteins in fraction 56 by Edman degradation resulted in the detection of a modified Arg in position 5 for CXCL8(1 to 77) (Fig. 1.2). Because the experimentally determined Mr of CXCL8 was not significantly different from the expected Mr, modification of Arg to citrulline (Cit) was considered. Cit is only 1 mass unit larger than Arg, and on the total Mr of CXCL8, this would fall within the accuracy of the mass spectrometer. L-Cit was subjected to Edman degradation, and PTH-Cit was found to elute at exactly the same position as the modified Arg (i.e. in between PTH-Thr and PTH-Gly). Analysis of the other RPHPLC fractions that contained CXCL8 immunoreactivity (fractions 56 to 61) resulted in the identification of several citrullinated and/or NH2terminally truncated CXCL8-forms (Fig. 1.3). Citrullination was only detected on Arg5 and not on other Arg in natural CXCL8 (Proost et al., 2008).

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Tamara Loos et al.

250 200

2500

100 50

0 <2.5

0

5

10

15

20

0

25

[NaCl] (M) (---)

5000

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10,000

CXCL8 (ng/ml) (

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10,000

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<25 0

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Retention time (min)

% acetonitrile (---)

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Intensity ⫻ 106

)

20

D

C

U.V.214 nm(mAU) (

10

8380.9 Mr (A) CXCL8 (6−77)

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1.0

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)

)

2

)

B

>12,500

[NaCl] (M) (---)

A

8800

9200

0.4 0.2 0.0

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Mr

Retention time (min)

Figure 1.1 Purification, isolation, and identification of CXCL8 isoforms. PBMC from 24 buffy coats were pooled (11.4 109 cells) and induced at 5 106 cells/ml with 10 mg/ml of polyrI:rC and 20 ng/ml IFN-g in RPMI 1640 containing 2% FCS. (A) After adsorption to silicicacid,theeluatewassubjectedtoheparinSepharosechromatography(GEHealthcare). Proteins eluted from the column by applying a NaCl gradient. Total protein (mg/ml) was measuredwiththeBradfordassay.CXCL8proteinconcentrationwasevaluatedbyaspecific sandwich ELISA. (B) Fractions 7 to 9 that eluted from the heparin Sepharose column were loaded on a Mono Scation exchange column (GE Healthcare) in 50 mM HCOOH. CXCL8 eluted from the column at approximately 0.75 M NaCl after 63 min, as evidenced by ELISA. (C) Fractions 64 to 66 recovered from the ion exchange chromatographic step were loaded on a RP-HPLC column (2.1  220-mm Brownlee C8 Aquapore RP-300 column, PerkinElmer) in 0.1% TFA. CXCL8 isoforms eluted from the column at approximately 31% acetonitrile. (D) Online mass spectrometry showed the presence of three proteins eluting from the RP-HPLC column after 55 min. The deconvoluted mass spectra corresponded to the Mr of the isoforms CXCL8(2 to 77), CXCL8(1 to 77), and CXCL8 (6 to 77).

13. Solid-Phase Peptide Synthesis To study the characteristics of natural posttranslationally modified chemokines, the availability of sufficient and pure material is an obvious requirement. Because natural sources, in general, do not supply sufficient amounts and because some natural chemokine isoforms cannot be easily separated by conventional chromatography, other approaches were mandatory to obtain sufficient material for biologic assays. One option is solidphase peptide synthesis of chemokines, which provides a good alternative

15

Posttranslational Modification of Chemokines

A E

5 4

Q

D N

3

A

TG

Y

V PM

W

F

IK L

R

H

S

2

U.V.270 nm (mAU)

B

1 (AA) 4 L

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5 4

3 P

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V

KL 3

E

1 A

C 5 4 3 2 1 0

Cit

6

8

10

12 14 16 Retention time (min)

18

20

Figure 1.2 Identification of naturally citrullinated CXCL8 by Edman degradation. (A) RP-HPLC chromatogram detected at 270 nm (mAU, milli absorption units) of the 19 PTH-amino acids (indicated by their one letter code). (B) Natural CXCL8 was subjected to Edman degradation. Overlays demonstrate PTH-derivatives detected after 3, 4, and 5 cycles of Edman degradation, revealing the amino acid sequences -KEL-from CXCL8 (6 to 77), -AVL- from CXCL8 (2 to 77), and -LPX- from CXCL8 (1 to 77) with X assigned to an unidentified amino acid. (C) L-Cit was loaded on the reaction vessel of the protein sequencer and the PTH-derivative was analyzed by RP-HPLC. PTH-Cit eluted in between PTH-Thr and PTH-Gly, at exactly the same position as the unidentified amino acid (X) in natural CXCL8.

for the time-consuming production by recombinant expression. Moreover, recombinant proteins are more likely to be contaminated with other potent proinflammatory molecules of biologic origin such as the TLR ligands. Moreover, incorporation of amino acids that are not encoded by DNA (e.g., citrulline, hydroxyproline,. . .) or chemical groups is impossible.

13.1. Synthesis of the peptide chain During solid-phase peptide synthesis, the peptide is assembled from the COOH-terminus towards the NH2-terminus. The a-carboxyl group of the COOH-terminal amino acid is attached to a stable and solid support

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Tamara Loos et al.

125

Arg5 Cit5

100 75 50

56 57 58 59 60 61

56 57 58 59 60 61

CXCL8 (1−77)

56 57 58 59 60 61

CXCL8 (−2−77)

56 57 58 59 60 61

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25 56 57 58 59 60 61

CXCL8 (pmol)

150

CXCL8 (2−77)

CXCL8 (6−77)

CXCL8 (8−77)

CXCL8 (9−77)

RP-HPLC fraction number

Figure 1.3 Abundance of CXCL8 isoforms in PBMC. Edman degradation on RP-HPLC fractions 56 to 61 (Fig.1.1C) lead to the identification of the CXCL8 isoforms CXCL8(2 to 77), CXCL8(1 to 77), CXCL8(2 to 77), CXCL8(6 to 77), CXCL8(8 to 77), and CXCL(9 to 77). Moreover, posttranslational modification of Arg5 into Cit5 was discovered on part of the CXCL8(2 to 77), CXCL8(1 to 77), and CXCL8(2 to 77) proteins (filled histograms). Histograms indicate the amount of each CXCL8 isoform in the individual RP-HPLC fractions.

(i.e., HMP-resin [4-hydroxymethyl-phenoxy-methyl-polystyrene, crosslinked by 1% divinylbenzene]), and they remain coupled during chain assembly. In this manner, the peptide can be easily separated from used reagents and solvents by simple filtration and washing. One by one the consecutive amino acids are coupled to the growing peptide chain, according to the amino acid sequence of the desired protein. The a-amino group of these amino acids is protected from inappropriate binding by a fluorenylmethoxy carbonyl–(Fmoc) protecting group (Atherton and Sheppard, 1989). Moreover, such a protecting group destroys the amino acid’s zwitterionic character. Instead of the base-labile Fmoc protecting group, an acid-labile tertiary-butoxycarbonyl (tBoc) is also widely used (Clark-Lewis et al., 1997). Although successful chemokine synthesis has been achieved with this strategy, the use on the synthesizer of concentrated TFA for the removal of tBoc groups and strongly corrosive hydrofluoric acid during final cleavage and deprotection reactions make it less attractive (Clark-Lewis et al., 1991). Because the side chains of some amino acids also contain chemically reactive groups, hindering clear-cut peptide bond formation, they need to be blocked by protecting groups as well (Atherton and Sheppard, 1989). The choice of the side chain–protecting group relies on the kind of amino acid and the synthesis strategy. The side chain–protecting groups used in our laboratory are t-butyloxycarbonyl for lysine; tert-butyl for serine, threonine, and tyrosine; 2,2,7,8-pentamethylchroman-6-sulfonyl for arginine; tert-butyl-ester for aspartic acid and glutamic acid; and trityl for histidine, cysteine, asparagine, and glutamine (Proost et al., 1995). During peptide synthesis, a portion of the peptide resin can be taken away and stored, while synthesis proceeds on the remaining peptide-resin complexes. This allows for the generation of different NH2-terminally

Posttranslational Modification of Chemokines

17

modified analogs with a common COOH-terminal sequence. Conversely, analogs with a different COOH-terminus have to be synthesized separately. Detailed synthesis protocol Initially, a threefold molar excess (compared with the amount of active groups on the resin) of the COOH-terminal amino acid of the desired protein is activated by 1 M N,N0 -dicyclohexylcarbodiimide in N-methyl pyrrolidone (DCC/NMP) generating an activated ester and subsequently added to the resin in the reaction vessel together with the basic esterification catalyst dimethyl aminopyridine (DMAP; 0.1 M in dimethylformamide [DMF]). Accordingly, the carboxyl group of the COOH-terminal amino acid is coupled to a hydroxyl group of the HMP resin by a symmetric anhydride binding. To prevent coupling of HBTU-activated amino acids at a later stage to unloaded hydroxyl groups, remaining hydroxyl groups are capped with benzoic anhydride, again with DMAP as a catalyst. Subsequently, the succeeding amino acids are coupled one by one to the growing peptide chain (0.1 mmol to 0.25 mmol of peptide resin) (Fig. 1.4). As a first step of chain assembly, the Fmoc protection group must be removed from the resin-coupled amino acid. Deprotection is carried out by fourfold treatment with piperidine (20%) in NMP, which results in the removal of the Fmoc group on the basis of a b-elimination reaction. After each deprotection step, the resin particles in the reaction vessel are washed with NMP to remove the remaining piperidine. The penultimate Fmocprotected amino acid, which needs to be coupled to the resin-bound amino acid, is activated by 2-1H-benzotriazol-1yl-1,1,3,3-tetramethylureniumhexafluorophosphate (HBTU 0.45 M )/1-hydroxybenzotriazole (HOBt 0.45 M ) in DMF. Subsequently, N,N-diisopropyl ethylamine (DIEA; 2 M in NMP) is added, and the HBTU-activated amino acid (1 mmol; 4- to 10-fold excess) is transferred to the reaction vessel to form a peptide bond with the amino acid–resin complex. Because coupling is never 100% complete, the remaining free a-amino groups of the first amino acid residues are capped with acetic anhydride (0.5 M in NMP containing 0.125 M DIEA and 0.015 M HOBt) to prevent them from being coupled to amino acids added during one of the following cycles, which would result in the synthesis of proteins internally lacking one or more amino acids. Finally, the resin particles are washed four times with NMP. These deprotection and coupling steps are repeated for every single amino acid until the entire peptide chain has been completed. In the end, the resincoupled peptide chain is treated once again with piperidine to remove the final Fmoc group from the NH2-terminal amino acid (Fig. 1.4). As the peptide chain grows, interchain and intrachain interactions are more likely to occur. As a result, the NH2-terminus of the peptide may be buried and less accessible, obviously making it harder to achieve efficient deprotection and coupling. Removal of the Fmoc group can be monitored

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O

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-H2N-CH-C-...-NH-CH-C-NH-CH-C-O - resin Rn

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R1 X TFA + thioanisole, water, 1,2-ethanedithiol and crystalline phenol O O

H2N-CH-C-...-NH-CH-C-NH-CH-C-OH Rn

R2

R1

Figure 1.4 General protocol for solid-phase peptide synthesis. During solid-phase peptide synthesis, the COOH-terminal amino acid is stably attached to the HMP-resin. Both the a-amino group and reactive side chains of amino acids are blocked by protecting groups. After loading the resin with the COOH-terminal amino acid, the Fmoc group is removed from the a-amino group by treatment with piperidine, allowing for coupling of the next amino acid. HBTUsolution is added to a cartridge containing the next amino acid. Activated Fmoc-amino acid is formed almost instantaneously and transferred to the reaction vessel, where a peptide bond is formed with the resin-coupled amino acid. Afterwards, uncoupled free a-amino groups are capped by acetic anhydride.This cycle is repeated for each of the following amino acids until the last amino acid has been coupled. The base-labile Fmoc group of the NH2 -terminal amino acid is removed by a final treatment with piperidine, whereas the acid-labile side chain protecting groups and peptide^ resin bond are cleaved withTFA.Water, ethane dithiol, thioanisole, and crystalline phenol are used as scavengers, limiting modifications of the side chains. Rx represents a random amino acid side chain. X,Y, and Z stand for side chain protecting groups.

Posttranslational Modification of Chemokines

19

by UV or conductivity measurements after every piperidine treatment. Hence, if removal of the Fmoc group does not pass very efficiently, the deprotection is automatically prolonged by conditional deprotection modules (Fig. 1.5). Moreover, these conditional deprotection modules are followed by double, instead of single, coupling. An extra amount of amino acid (1 mmol) is activated and transferred to the reaction vessel for prolonged coupling to increase the coupling yield.

13.2. Deprotection of the synthesized peptide chain After synthesis, the resin and the side chain–protecting groups are to be cleaved from the synthetic peptide (Fig. 1.4). Therefore, the peptide is incubated during 1.5 to 2.5 h in a mixture of 10 ml TFA, 0.5 ml thioanisole, 0.5 ml deionized water, 0.25 ml 1,2-ethanedithiol, and 0.75g crystalline phenol under continuous shaking. TFA cleaves the peptides from the resin and removes the side chain–protecting groups, whereas ethane dithiol, thioanisole, water, and phenol are added to keep the side chains of Trp, Tyr, Met, and Cys from being modified by released protecting groups (King et al., 1990). Afterwards, the resin particles are eliminated by filtering the TFA solution through a Biospin filter (Bio-Rad laboratories). The proteins in the filtrate are precipitated in 30 ml cold diethyl ether. After centrifugation, the protein-containing pellet is washed several times with diethyl ether to remove remaining chemicals. The precipitate is dissolved in H2O, lyophilized, and redissolved in 0.1% TFA and purified by RP-HPLC (Source 5 RPC column; GE Healthcare). Proteins are detected by online UV (l ¼ 220 nm) and ion trap mass spectrometry (Esquire LC, Bruker Daltonics). Fractions containing the intact raw protein were lyophilized before the folding procedure.

13.3. Folding of the raw protein To obtain disulfide bridges, the intact linear protein is incubated in 150 mM TRIS (tris[hydroxymethyl]) aminomethane], pH 8.6, containing 3 mM EDTA (ethylenediamine tetraacetic acid), 0.3 mM reduced glutathione, 3 mM oxidized glutathione, and 1 M guanidinium chloride. After acidification, the folded material is purified by RP-HPLC with a C8-Aquapore RP-300 column (2.1  220 mm; PerkinElmer) combined with online detection by mass spectrometry. Finally, Edman degradation on a 491 Procise cLC protein sequencer (Applied Biosystems) and ion trap mass spectrometry are used to confirm the NH2-terminal sequence and the Mr of the folded chemokine. The concentration of the synthesized chemokine is determined with the bicinchoninic acid assay and the yield of the individual amino acids after Edman degradation.

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Tamara Loos et al.

Piperidine deprotection Deprotection Deprotection Deprotection Deprotection

1 2 3 – U.V./conductivity 4 – U.V./conductivity

Difference > threshold = inefficient deprotection Difference < threshold = efficient deprotection

Inefficient deprotection

Efficient deprotection

Fifth deprotection

Extended deprotection

Activation of amino acid

Transfer

Coupling

Inefficient deprotection Extended coupling

Activation of additional amino acid Efficient deprotection Transfer

Extended coupling

Acetic anhydride capping

Figure 1.5 Incorporation of conditional modules in the general protocol of automated solid-phase peptide synthesis. During peptide chain synthesis, amino acids are coupled one by one to the growing peptide chain, directed from COOH- to NH2 -terminus. Each amino acid (except for the COOH-terminal amino acid) is coupled following the same procedure as described in this scheme. Some modules are conditional, meaning that they are only turned on/off under user-defined conditions.Whether or not the conditional modules become active is determined by UVor conductivity measurements on the deprotection solutions after piperidine treatment. When the UV or conductivity

Posttranslational Modification of Chemokines

21

Special remarks considering undesired side reactions 

Attention needs to be paid to the synthesis of proteins carrying a proline at their COOH terminus. Fmoc-proline can be loaded to HMP resin, but a potential diketopiperazine side reaction occurs during the chain assembly that can drastically reduce the yield of final peptide resin (Gisin et al., 1972; Proost et al., 1995).  Proteins bearing a DG sequence are prone to undergo base-mediated aspartimide formation during the repetitive piperidine treatments (Do¨lling et al., 1994; Lauer et al., 1994; Nicola´s et al., 1989; Yang et al., 1994). On nucleophilic attack by water or piperidine these aspartimides readily undergo ring opening, resulting in the generation of either a- and b-aspartyl peptides or N-aspartyl piperidine. We observed this side reaction during the synthesis of CXCL8 (Fig. 1.6). Verifying the Mr of the synthesized CXCL8(6 to 77) by mass spectrometry revealed a difference of 67 mass units with the theoretical molecular weight. This problem can be overcome by use of the preformed dipeptide Fmoc-Asp(OtBu)(Dmb)Gly-OH (Novabiochem, EMD Chemicals, Gibbstown, NJ), which masks the Asp-Gly amide bond, protecting it against aspartimide formation (Mergler et al., 2003; Packman, 1995).

14. Citrullination of Chemokines Citrullination is an irreversible reaction in which peptidyl arginine is deiminated and subsequently hydrolyzed into peptidyl citrulline, resulting in a mass increase of one mass unit and the loss of one positive charge. The enzymes responsible for this conversion are the calcium-dependent peptidyl arginine deiminases (PAD) (Vossenaar et al., 2003). Calcium ions bind to the enzyme, and a conformational change occurs. Consequently, it is speculated that the central cysteine residue in the catalytic domain becomes accessible and its thiol group attacks the guanidino group of arginine, releasing ammonia and forming a tetraheder intermediate. This intermediate structure is then hydrolyzed by water into citrulline (Arita et al., 2004). Chemokine citrullination was recently discovered on natural CXCL8 and CXCL10 and was shown to severely affect the biologic activities of chemokines (Loos et al., 2008; Proost et al., 2008). Chemokines may be measurement after the third deprotection step differs by more than a threshold value (typically 2.5% or 5%) from the UV or conductivity measurement after the fourth deprotection step, conditional modules are switched on. Thus, in case of inefficient deprotections, the conditional modules (underlined) are activated, aiming at higher deprotection and coupling efficiencies and a higher synthesis yield.

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Tamara Loos et al.

A

Intensity x 106

10+ 846.3 1.50

11+ 769.4

Intensity ⫻ 106

1.25

9+ 940.2

4 3 2 1

1.00

0

12+ 705.5

0.75

8453.3

5

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8+ 1057.8

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7+ 1208.3

13+ 0.25 651.2

0.00 700

800

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1300

1400 m/z

B 11+ 763.4 2.0

8386.0 Intensity ⫻ 106

10+ 839.6

12+ 699.9

Intensity ⫻ 106

1.5 9+ 932.7

8 6 4 2 0

8300 8350

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8450

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1.0 13+ 646.1 8+ 1049.2

0.5

7+ 1198.8

6+ 1398.6

0.0 700

800

900

1000

1100

1200

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1400 m/z

Figure 1.6 N-aspartyl piperidine formation of the DG sequence during synthesis of CXCL8(6 to 77) can be overcome by use of the preformed dipeptide Fmoc-Asp (OtBu)-(Dmb)Gly-OH. CXCL8, a chemokine bearing an internal Asp-Gly sequence, was synthesized on a solid-phase peptide synthesizer with Fmoc chemistry. (A) Ion trap mass spectrum of purified TFA-deprotected CXCL8(6 to 77), synthesized following the conventional method with Fmoc-Gly and Fmoc-Asp(OtBu). The Mr of the synthetic proteins is calculated by deconvolution of the multiply charged ions in the raw spectrum and is shown as an insert. The Mr of the synthesized CXCL8(6 to 77) in this case differs by 67 mass units from the expected theoretical Mr of unfolded CXCL8(6 to 77)

Posttranslational Modification of Chemokines

23

citrullinated in vitro by enzymatic treatment to investigate the biologic implications of chemokine citrullination. Citrullination is performed by incubating proteins with PAD in 40 mM TRIS, pH 7.4, supplemented with 2 mM CaCl2 at 37  C. Deimination is stopped with 0.1% TFA, because PAD activity is pH dependent (pH 6 to 9) (Nakayama-Hamada et al., 2005). Next, the citrullinated proteins are purified by RP-HPLC (1  50-mm Brownlee C8 Aquapore RP-300 column, PerkinElmer). To reveal the appropriate incubation period, kinetic studies can be performed. For example, 100 pmol CXCL8 (PeproTech, Rocky Hill, NJ) was incubated with rabbit PAD (Sigma-Aldrich) or with human PAD2 or PAD4 (ModiQuest Research, Nijmegen, The Netherlands) at an enzyme-substrate molar ratio (E/S) of 1:20 or 1:200 for different time periods. After ending deimination, samples were split and desalted on C4 ZipTip (Millipore) before mass spectrometry or in parallel spotted on PVDF membranes (ProSorb; Applied Biosystems) before Edman degradation.

15. Identification of Enzymes Generating the Natural Posttranslationally Modified Chemokines, as Exemplified by Aminopeptidase N(APN)/CD13 To uncover which enzymes may be involved in the generation of certain naturally purified proteolytically processed chemokines, chemokines can be incubated in vitro with potential candidate enzymes, followed by analysis with mass spectrometry. Indeed, incubation of CD26-processed CXCL11(3 to 73) with APN/CD13 generated the same CXCL11 isoforms as purified from natural sources (i.e. CXCL11[4,5,6 to 73]) (Proost et al., 2001, 2007). APN/CD13 is a metalloprotease that removes NH2-terminal amino acids one by one, except for proline, which is resistant to APN/CD13 cleavage (Ashmun et al., 1990; Breljak et al., 2003; Riemann et al., 1999). To investigate in vitro processing by APN/CD13, CXCL11(3 to 73) was incubated for 2 h at 37  C in phosphate-buffered saline (DPBS) with porcine kidney purified microsomal APN/CD13 (Sigma-Aldrich) at an enzymesubstrate molar ratio of 1:4 or 1:25. To prevent CXCL11 from sticking to the plastic tube, the nonionic detergent octyl-b-glucopyranoside (0.1%) was (Mr ¼ 8386 Da). This is due to aspartimide formation during piperidine deprotection, whereupon a nucleophilic attack by piperidine leads to the generation of an N-aspartyl piperidine. (B) The mass spectrum of TFA-deprotected CXCL8(6 to 77) synthesized with the preformed dipeptide Fmoc-Asp(OtBu)-(Dmb)Gly-OH. This spectrum demonstrates that on use of the preformed DG dipeptide, a protein with the correct Mr is synthesized, and no N-aspartyl piperidine formation is observed.

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Tamara Loos et al.

added. The enzymatic reaction was stopped by the addition of 0.1% TFA. Samples were desalted and concentrated with C4 Zip Tips (Millipore) and analyzed by ion trap mass spectrometry. Mass spectrometric analysis after incubation unexpectedly revealed NH2-terminal and COOH-terminal processing of CXCL11. However, when the serine protease inhibitors phenylmethylsulfonyl fluoride (PMSF; 30 mM) or benzamidine (5 mM) were included, COOH-terminal cleavage was blocked, pointing toward the presence of contaminating serine proteases in the commercially available APN/CD13 (Proost et al., 2007). Therefore, it is recommended to add a serine protease-inhibitor, such as PMSF or benzamidine, to the reaction mixture.

16. Comparison of the Heparin-Binding Properties of Chemokine Isoforms Chemokines play a prominent role in directing selective leukocyte recruitment during inflammation and normal immune surveillance. In addition to chemokine receptors, glycosaminoglycans (GAG) are key players in this process. They may drive transcytosis of chemokines across the endothelial cell layer, immobilize chemokines on the luminal surface of the endothelium, and form an immobilized gradient directing leukocytes to the site of inflammation (Colditz et al., 2007; Johnson et al., 2005; Middleton et al., 2002; Parish, 2006). Cell-surface GAG may also induce polymerization of chemokines, increasing their local concentration and, therefore, enhancing their effects on high-affinity receptors within the local environment (Hoogewerf et al., 1997). Hence, besides binding to and signaling through seven-transmembrane-spanning G protein–coupled receptors, inducing well-known effects such as an increase in the intracellular calcium concentration and chemotaxis, chemokine-GAG interaction is important for the in vivo biologic activity of chemokines. The chemokineGAG interaction has been thought to be based on electrostatic interactions between the highly negatively charged sulfated polysaccharides and the largely basic COOH terminus of the chemokine. However, further investigation revealed that this does not completely explain chemokine-GAG interactions (Handel et al., 2005). Because chemokine-GAG interaction seems to play a significant role in in vivo leukocyte migration, studying the effect of posttranslational modifications on this interaction might be very interesting. A technique for the identification or characterization of heparin-binding proteins has been developed recently (Mahoney et al., 2004); 96-well plates are treated by plasma polymerization with allylamine that leads to a change in the surface of microtiter plates, allowing heparin to be immobilized without being modified

Posttranslational Modification of Chemokines

25

(Heparin binding plates; BD, Franklin Lakes, NY). This constitutes the main advantage of this technique. Because there is no need to modify the GAG molecule, it can fully retain its ability to interact with other biomolecules. The assay for the characterization of binding of molecules to the immobilized heparin is similar to an ELISA. To immobilize heparin molecules on the plasma-polymerized coating, each well is incubated overnight with 100 ml of a low molecular weight heparin solution (25 mg/ml in DPBS; Sigma-Aldrich) at room temperature (protected from light). After three wash steps with standard assay buffer (SAB; 100 mM NaCl, 50 mM NaAc, 0.2% [v/v] Tween-20, pH 7.2) to remove unbound heparin, 250 ml of SAB enriched with 0.2% (w/v) gelatin (blocking solution) is added to each well and the plate is blocked at 37  C for 1 h. Chemokine-solutions (100 ml, diluted in blocking solution) are added and allowed to interact with heparin for 2 h at 37  C. Unbound chemokine is removed by washing the plate 3 times with SAB. Bound chemokine is detected by adding 100 ml of a specific biotinylated antichemokine antibody in blocking solution for 1 h at 37  C. The plate is washed three times with SAB, and 100 ml of HRP-labeled streptavidin ( Jackson ImmunoResearch Laboratories, West Grove, PA) is added. After 30 min, unbound streptavidin is removed by washing the plate 3 times with SAB. To produce a visible signal quantifying the peroxidase activity, 100 ml of a chromogenic HRP-substrate solution is added (cf. ELISA). Used biotinylated antibodies need to be checked for equal recognition of the native chemokine as well as the posttranslationally modified chemokines. Percentage binding was calculated by subtracting the mean OD of the negative control (blocking buffer) from the measured OD of the sample, subsequent division with the average OD of the highest concentration of intact chemokine and finally multiplying by 100. This calculation grants a 100% binding to the highest concentration of intact chemokine and 0% binding to the negative control.

ACKNOWLEDGMENTS This work was supported by the Center of Excellence (Credit no. EF/05/15) of the K. U. Leuven, the Concerted Research Actions (G.O.A./2007/15) of the Regional Government of Flanders, the Fund for Scientific Research of Flanders (F.W.O.-Vlaanderen), the Interuniversity Attraction Poles Program-Belgian Science Policy (I.A.P.), and the European Union 6FP EC contract INNOCHEM (grant LSHB-CT-2005-518167). A. M. is a research assistant of the F.W.O.-Vlaanderen.

REFERENCES Arita, K., Hashimoto, H., Shimizu, T., Nakashima, K., Yamada, M., and Sato, M. (2004). Structural basis for Ca(2þ)-induced activation of human PAD4. Nat. Struct. Mol. Biol. 11, 777–783.

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C H A P T E R

T W O

Homo- and Hetero-Oligomerization of Chemokines Ariane Jansma, Tracy M. Handel, and Damon J. Hamel Contents 1. Introduction 2. Methods to Detect and Quantify Oligomerization 2.1. Analytical ultracentrifugation (AUC); sedimentation equilibrium 2.2. Pulsed-field gradient diffusion by NMR 2.3. Dynamic light scattering 2.4. Fluorescence polarization 2.5. FT-ICR mass spectrometry 2.6. Other methods 3. Methods for Collecting Residue-Specific Information on Chemokine Oligomers 3.1. NMR: Heteronuclear single quantum correlation (HSQC) spectroscopy 3.2. NMR: Detection of nuclei in close proximity by means of the nuclear Overhauser effect (NOE) 4. Conclusions Acknowledgments References

32 35 35 39 40 41 42 42 43 43 44 47 47 47

Abstract Chemokines function in cell migration by binding and activating seven transmembrane G protein–coupled receptors (GPCRs) on leukocytes and many other diverse cell types. The extracellular binding event stabilizes specific conformations of the receptor that trigger cascades of intracellular signaling pathways involved in cell movement and activation (Baggiolini, 1998; Baggiolini et al., 1997; Charo and Ransohoff, 2006; Hartley et al., 2003; Kunkel and Butcher, 2002; Loetscher and Clark-Lewis, 2001). Although the current consensus is that monomeric forms of chemokines are necessary for receptor binding to induce

Skaggs School of Pharmacy and Pharmaceutical Science, University of California, San Diego, La Jolla, California, USA Methods in Enzymology, Volume 461 ISSN 0076-6879, DOI: 10.1016/S0076-6879(09)05402-0

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cell migration, oligomeric states of chemokines may be associated with other complex functional roles such as regulation, haptotactic gradient formation, protection from proteolysis, and signaling related to processes distinct from migration. Accordingly, diverse biophysical methods have been used to identify and characterize the details of these quaternary interactions. This chapter aims to summarize these methods and to provide guidelines for their application in future studies.

1. Introduction Chemokines are small (
8 to 12 kDa) secreted proteins that have been classified into four subfamilies (CC, CXC, CX3C, and C) on the basis of the relative position of their conserved N-terminal cysteine residues. All chemokines share a highly conserved monomeric structure consisting of a disordered N-terminal region, followed by an irregular ‘‘N-loop’’, three antiparallel b-strands, and a C-terminal a-helix (Fig. 2.1A) (Blain et al., 2007; Czaplewski et al., 1999; Fernandez and Lolis, 2002; Jin et al., 2005). Chemokine quaternary structure is more varied. Two primary structural

Figure 2.1 Examples of chemokine structures. (A) CCL2/MCP-1 monomer (PDB code 1DOL). (B) CCL2 dimer, an example of a ‘‘CC dimer’’ (PDB code 1DOM). The interface is composed of a small antiparallel b-sheet formed from residues at the N-terminus of both subunits. (C) IL-8/CXCL8 dimer, an example of a ‘‘CXC dimer’’ (PDB code 1IL8).The interface is formed by the first beta strand in each subunit, as well as interactions between the C-terminal end of the helix of one subunit and the b-sheet of the opposing subunit. (D) The lymphotactin/XCL1 dimer contains a unique allb-sheet structure that exists in equilibrium with a canonical chemokine monomer (PDB code 2JP1). (E) The CCL2 tetramer has characteristics from both CC and CXC dimer interfaces (adapted from PDB code 1DOL). (F) H-form of IP-10/CXCL10 tetramer associating through the third b-strands forming a 12-stranded antiparallel b-sheet with a sharp kink in the middle (PDB code1O80).

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types of dimers have been observed: CC dimers that interact by means of a two-stranded antiparallel b-sheet near the N-terminus, and CXC dimers formed by the first strand of the b-sheet from each monomer (Fig. 2.1B, C) (Blain et al., 2007; Czaplewski et al., 1999; Fernandez and Lolis, 2002; Jin et al., 2005). More recently, a third type of dimer was identified for the C chemokine, lymphotactin/XCL1, that consists of an all-b-sheet arrangement with no similarity to other known protein structures and that rapidly interconverts with the canonical monomeric chemokine fold (Fig. 2.1D) (Tuinstra et al., 2008 and chapter 3 by Brian Volkman). In addition, whereas the known quaternary structure of dimers are similar among members of each subfamily, some chemokines (e.g., MPC-1/CCL2, PF4/CXCL4, IP-10/CXCL10) have been shown to form tetramers that in some cases have both CC and CXC interfaces (Czaplewski et al., 1999), whereas others adopt completely novel folds (e.g., IP-10/CXCL10) (Fig. 2.1E, F) (Swaminathan et al., 2003). Finally, several chemokines form heterodimers, and it has been shown that heterodimerization can occur within members of a given subfamily, as well as between subfamilies (Crown et al., 2006; Paoletti et al., 2005; von Hundelshausen et al., 2005). Although, the current understanding of the functional relevance of these various oligomeric forms is far from complete, there is ample evidence suggesting that oligomerization is important to the overall mechanism of cell migration. Previous studies have shown that mutant forms of chemokines that are unable to oligomerize are generally still fully functional with respect to receptor binding and cell migration in vitro, suggesting that receptor binding occurs through the monomeric form (Czaplewski et al., 1999; Lowman et al., 1997; Paavola et al., 1998; Proudfoot et al., 2003). Nevertheless, these monomeric mutants are inactive in vivo when tested in an intraperitoneal recruitment assay (Campanella et al., 2006; Proudfoot et al., 2003, and see Chapter 18 by A. Luster). The prevailing explanation for these apparently anomalous results is related to the fact that as part of the mechanism for providing directional cues, chemokines are maintained near sites of production by localization on cell surfaces through interactions with glycosaminoglycans (GAGs). These interactions often involve oligomerization of chemokines on the GAGs. Indeed, biochemical and biophysical studies indicate that some chemokine: GAG interactions are facilitated by chemokine oligomerization and also that chemokine oligomerization can be facilitated by interactions with GAGs (Hoogewerf et al., 1997; Lau et al., 2004; Proudfoot et al., 2003). Furthermore, chemokine variants that are incapable of binding GAGs can also be functional in vitro but not in vivo in much the same way as mutants that are unable to oligomerize (Proudfoot et al., 2003). The functional coupling between GAG binding and oligomerization is perhaps best exemplified by the [44AANA47]-RANTES/CCL5 mutant, which is unable to bind GAGs and blocks the activity of the WT protein through a dominant negative effect by forming nonfunctional

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heterodimers with the WT protein ( Johnson et al., 2004; Lau et al., 2004). Although chemokine: GAG interactions are not discussed further here, many reviews are available on this topic (Allen et al., 2007; Fermas et al., 2008; Handel et al., 2005; Imberty et al., 2007; Johnson et al., 2005; Kuschert et al., 1999; Lau et al., 2004; Witt and Lander, 1994; Yu et al., 2005, and chapter 4 in this volume present various methods for characterizing these interactions). In addition to playing a role in cell migration, oligomerization may also contribute to the functional regulation of chemokines. For example, the disordered N-termini are the key signaling domains in all chemokines, and thus proteolytic processing of the N-terminus represents a natural mechanism for modulating chemokine function (Fox et al., 2006). Most frequently, agonist activity is reduced or abolished completely on N-terminal proteolysis; however, there are examples of increased activity, and even alterations in receptor-binding specificity with N-terminal processing (Fox et al., 2006; Homey et al., 2002). Although interactions with GAGs have clearly been shown to protect chemokines from proteolysis (Ellyard et al., 2007; Vives et al., 2002), in principle, oligomerization alone could also be protective, both directly and indirectly, by facilitating interactions with GAGs. Finally, oligomerization has been shown to influence cellular signaling. In some cases, oligomerization promotes additional signaling pathways not induced by the monomeric chemokine. For example, although a nonaggregating variant of RANTES/CCL5 was able to induce chemotaxis by means of Gi coupling, it was unable to activate T cells, monocytes, and neutrophils through protein tyrosine kinase (TK) pathways; this contrasts with wildtype (WT) CCL5, which forms large oligomers nucleated by a CC-like dimer, and induces TK proinflammatory pathways (Czaplewski et al., 1999). Oligomerization can also inhibit signaling as demonstrated by an obligate SDF-1/CXCL12 dimer, which was engineered by introduction of an intermolecular disulfide. It was shown to flux calcium but, unlike WT CXCL12, could not induce all of the pathways required for chemotaxis; instead, it blocked migration of cells to the WT chemokine (Veldkamp et al., 2008). Recently, several chemokines have been shown to heterodimerize with other chemokines, and in some cases, such as MCP-1/CCL2 and MCP-2/CCL8, their presence could be correlated with altered or amplified functional responses relative to signaling by only one of the chemokines (Crown et al., 2006; Dudek et al., 2003; Nesmelova et al., 2008). Although the relevance of oligomerization is now well established as the preceding examples suggest, there are 50 human chemokines, and little is known about the vast majority. Clearly, determining whether chemokines oligomerize and the structural details of the oligomers are crucial to understanding the mechanisms of chemokine-mediated processes. Furthermore, nonoligomerizing forms can have therapeutic value as demonstrated for a

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monomeric form of MCP-1/CCL2 that had antiinflammatory properties in animal models of experimental autoimmune encephalomyelitis and arthritis (Handel et al., 2008; Shahrara et al., 2008). This chapter will, therefore, discuss several approaches for studying chemokine oligomerization. The first step in this process is to decide what questions need to be addressed. Is residue-specific information needed to map subunit interfaces, solve oligomeric structures, or drive mutagenesis studies to create nonoligomerizing variants? Or, will simple confirmation and quantitation of oligomerization suffice? Often it is necessary to combine a variety of approaches to gain the most comprehensive understanding (Table 2.1). Furthermore, with all of these approaches, it is usually necessary to follow-up with mutagenesis or in vivo experiments to establish functional relevance (Campanella et al., 2006; Proudfoot et al., 2003).

2. Methods to Detect and Quantify Oligomerization Many variables, including protein concentration, salt concentration, and pH, affect the oligomeric equilibrium of chemokines (Veldkamp et al., 2005). Assessing the oligomeric state of a chemokine under varying conditions provides valuable data on which conditions facilitate or inhibit oligomerization. This knowledge is especially useful before structure determination by crystallography or NMR for understanding how to handle and store chemokines to preserve maximal functionality. The methods are also useful in the design and characterization of chemokine variants with reduced or enhanced propensities for oligomerization. The following section provides details and specific examples of methods that focus on determining the oligomerization state of chemokines and soluble proteins in general.

2.1. Analytical ultracentrifugation (AUC); sedimentation equilibrium In AUC experiments, one subjects a protein sample to a high centrifugal force in an analytical ultracentrifuge. One can then optically measure the distribution of the protein along the radius of the sample cell as a function of time or at equilibrium to determine shape and size distributions of proteins, as well as the equilibrium constant of oligomerization (Balbo et al., 2007). As such, this method has many applications in terms of analyzing chemokine oligomerization and the effects of solution composition and additives like GAGs. Although several types of experiments can be done by AUC, the method most commonly applied to chemokines is sedimentation

Table 2.1 Summary of various methods to study chemokine oligomerization. Advantages, disadvantages, and representative publications are listed Method

Advantages

Global detection of oligomerization Determination of Analytical equilibrium ultracentrifugation constant (AUC) PFG NMR (DOSY)

Rapid, easy analysis

Dynamic light scattering (DLS)

Fast and simple

Easy determination of dissociation constants FT-ICR mass spec. Can detect homo and heterodimerization Residue-specific information HSQC analysis Identification of residues at dimer interface NOE analysis Possible identification of residues at dimer interface Filtered NOEs Identification of residues at dimer interface Fluorescence polarization

Disadvantages

Examples

Expensive equipment, long length of experiments, analysis can be tricky

CXCL8 (Lowman et al., 1997), CCL4 ( Jin et al., 2007), CCL5 (Czaplewski et al., 1999) CXCL12 (Veldkamp et al., 2005), CCL27 CXCL12 (Holmes et al., 2001)

Very expensive equipment, limited to concentrations above
50 mM Large oligomers dominate signal, difficult to determine equilibrium constant Observe only small changes in chemokines

CXCL12 (Veldkamp et al., 2005)

Gas phase detection, no Kd determination

CCL2 and CCL8 (Crown et al., 2006)

Chemical shifts can also reflect change in conformation

CCL4 (Laurence et al., 2000), CCL2/CCL8 (Crown et al., 2006) CCL8 (Clore et al., 1990)

Difficult to distinguish intra- from inter-molecular NOEs, difficult data collection and analysis Low sensitivity, difficult data collection and analysis

CCL2 (Handel and Domaille, 1996), CXCL12 (Veldkamp et al., 2005)

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equilibrium, which is done at moderate centrifugal forces compared with the nonequilibrium method called sedimentation velocity. In the sedimentation equilibrium experiment, sedimentation of the protein by centrifugal force is counterbalanced by back diffusion of the protein along its concentration gradient. After equilibrium is achieved between these two forces, one measures the radial concentration gradient of the protein along the cell, which provides information on molecular mass, and for interacting systems, the dissociation constants. Lowman et al. (1997) determined the dimerization constants of several mutants of IL-8/CXCL8 designed to destabilize dimerization. They were able to identify mutants with significantly lower affinities for dimerization, yet showed that the mutants maintained WT potencies in several functional assays, suggesting that the monomeric form is the relevant form to induce migration. They also showed that dimerization was highly sensitive to solution conditions of ionic strength, pH, and temperature, and that high affinity could be achieved by adjustment of these parameters, suggesting that dimerization may have functional consequences despite the fact that only monomers are effective in activating the receptor (Lowman et al., 1997). Similarly, Paavola et al. (1998) identified a nondimerizing mutant of MCP-1/CCL2 that retained WT binding affinity and ability to promote cell migration. Jin et al. (2007) used AUC in conjunction with NMR to confirm both the molecular mass and correct folding of an engineered dimeric form of MIP-1b/CCL4. In contrast to studies with the disulfide-stabilized dimeric SDF-1/CXCL12 (Veldkamp et al., 2008), this study demonstrated that the disulfide-linked CCL4 dimer was not able to bind to its receptor CCR5, again confirming that CCL4 binds and activates CCR5 as a monomer ( Jin et al., 2007). Finally, Czaplewski et al. (1999) used AUC in parallel with mutagenesis and identified residues D26 and E66 in MIP-1a/CCL3 as critical for the formation of high molecular weight aggregates. They went on to demonstrate that homologous residues in CCL4 and CCL5 also inhibited aggregation, yet all three mutant chemokines maintained the ability to activate CCR1 and CCR5 in vitro (Czaplewski et al., 1999). The major advantage of sedimentation equilibrium is that it allows for the calculation of the molecular weight and dimerization constant(s) for a given system. Protein and protein complexes with masses in the range from <103 to >106 Daltons, and associating systems characterized by KD values between 104 and 108 M1 can be studied by AUC (Balbo et al., 2007). However, one caveat to this method is that it is time-consuming, taking 1 to 2 days per run. Furthermore, the data can be difficult to fit, particularly when there are issues with nonequilibrium aggregation, which plagues some chemokines (e.g., CCL5). One must also consider buffer conditions, because most chemokines are highly basic proteins. For example, it is important to avoid extremely low ionic strengths, because electrostatic interactions can become a significant force in addition to diffusion and

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sedimentation, complicating the analysis. Typically addition of 100 mM salt is sufficient to avoid nonideal behavior, but salt also commonly influences the oligomerization behavior. Primarily because of limitations on the sensitivity of the optical detection, protein concentrations are limited to the micromolar to submillimolar range (O.D. <1 for the highest sample concentration, which for chemokines is approximately 0.1 to 0.2 mM when measuring at 280 nm). Nevertheless, for chemokines, these concentration ranges are generally adequate to define the oligomerization state and/or KD for self-association. Figure 2.2 shows an example of the use of AUC A 0.02 0.00 −0.02 0.2

Residuals

B

−0.2

C

0.2

0.0

0.0 −0.2 D

Absorbance

1.2

0.8

0.4

0.0 6.6

6.7

6.8 6.9 7.0 Radius (cm)

7.1

7.2

Figure 2.2 Sedimentation equilibrium of SDF-1a. SDF-1a (200 mM) was centrifuged at 25,000 rpm, 4  C, until equilibrium was attained. Data were fit to various association state models. Residuals are plotted as the deviation from the best-fit line versus radial position for (A) an interacting monomer^dimer, (B) a monomer only, and (C) a dimer only. (D) Representative data are shown with the best-fit line for the interacting monomer^dimer model. Reprinted from ‘‘Protein Expression and Purification, 2001 Apr, 21(3):367^77, Solution studies of recombinant human stromal-cell^derived factor-1, Holmes, C. D.; Consler, T. G.; Dallas, W. S.; Rocque, W. J.; Willard, D. H.’’ with permission from Elsevier.

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to demonstrate that SDF-1/CXCL12 self-associates and that under the solution conditions used is in equilibrium between a monomer and dimer. In general, sedimentation equilibrium is accepted as the method of choice for studying oligomerization because of the highly quantitative information it provides. Many laboratories combine it with sedimentation velocity as a more rapid (hours) initial experiment to obtain information on the number of species in a sample (e.g., monomer, dimer, tetramer), but sedimentation velocity is less accurate in deriving equilibrium constants. For an excellent detailed description of the method, see Balbo et al. (2007).

2.2. Pulsed-field gradient diffusion by NMR Pulsed-field gradient (PFG) diffusion, effectively measures the average distance traveled by solute molecules in an NMR sample during a fixed period of time. The method relies on the use of pulse-field gradients to spatially encode the NMR signals such that their effective position in the NMR tube can be monitored (Altieri, 1995). Measuring the signal attenuation in successive proton spectra, as a function of increasing gradient field strength, enables calculation of the self-diffusion coefficient, Ds, which is directly related to the hydrodynamic radius of the protein in solution by means of the Stokes Einstein relationship (Altieri, 1995; Veldkamp et al., 2005, 2008). A relatively slowly decaying signal corresponds to a smaller value of Ds, which equates to a larger apparent molecular weight and vice versa. By accurately calibrating gradient strengths with solvents of known Ds, one can obtain an accurate measurement of the Ds of the protein of interest. Alternately, one can use known proteins of known molecular weight and oligomerization pattern as standards for Ds values. There are several interesting applications of PFG diffusion to the study of chemokine oligomerization. The Ds values may be compared at different protein concentrations to chart a chemokine oligomerization profile (Fig. 2.3) and can also be used to determine which solvent conditions affect the oligomerization state. Veldkamp et al. (2005) used this approach to study solvent conditions that promote dimerization SDF-1/CXCL12. By determining Ds as a function of concentration, it was possible to determine a value of KD, which was in good agreement with AUC measurements. Once this ‘‘oligomerization profile’’ has been determined for the WT chemokine, it can be compared with variants of the chemokine of interest to identify residues necessary for oligomerization and to generate mutants that remain monomeric at high concentrations. For example, Paavola et al. (1998) used such a method to determine mutations in the chemokine MCP-1/CCL2 that inhibited dimerization. Figure 2.3 shows a theoretical PFG diffusion profile for a 10-kDa chemokine forming a stable dimer. As the concentration increases, one would expect to see the Ds values rapidly decrease to a

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Ds (⫻10−06 cm2s−1)

1.5 1.4 1000 mM 1.3 100 mM

1.2 10 mM 1.1 1

0

0.2

0.4

0.6 0.8 1.0 1.2 1.4 [Chemokine] (mM)

1.6

1.8

2.0

Figure 2.3 Theoretical PFG diffusion curve showing values for Ds and concentration that would be expected for a typical chemokine of 10 kDa forming a stable dimer.These values are based on previous studies performed on chemokines and standard proteins of known molecular weight and oligomerization (Altieri,1995;Veldkamp et al., 2005).

value corresponding to approximately twice the molecular weight of the monomer and then stabilize as the concentration continues to increase. The ability to evaluate oligomerization at high concentration (millimolar range) is an important advantage of NMR, because these concentrations are not amenable to AUC. In addition, gradient diffusion experiments are rapid and easy to analyze. However, one must have access to the relevant NMR instrumentation. We favor the use of the PFG diffusion technique to screen the behavior of chemokines under different concentrations and buffer conditions. These data can then be used to identify a more limited set of conditions to characterize with the more time-consuming AUC method should this be deemed necessary. Relative to other NMR methods, PFG diffusion is fairly straight-forward to implement, and automated procedures, such as diffusion ordered spectroscopy (DOSY), are available for data processing and analysis in NMR vendor software packages such as Bruker Biospin TopSpin.

2.3. Dynamic light scattering Dynamic light scattering (DLS) is a well-established technique for studying protein oligomerization and is often used by crystallographers to determine a protein’s propensity to aggregate in solution. DLS measures intensity fluctuations in scattered, monochromatic light through a sample in solution and ultimately allows the calculation of the diffusion coefficient and from there the hydrodynamic radius. A good example of DLS applied to chemokines is a study done by Holmes et al. (2001) to determine the

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monomer–dimer equilibrium of recombinant SDF-1/CXCL12. They used DLS to calculate the apparent mass of CXCL12 at six different concentrations and determined the monomer–dimer equilibrium constant to be 114 mM. This value was verified by sedimentation equilibrium, which showed a similar equilibrium constant of 180 mM. DLS has the advantage of speed and requires less technical expertise than many of the other methods described. Typically DLS is less accurate for observing the presence of small oligomers and determining equilibrium constants than sedimentation equilibrium. However, it is especially good for detecting broad distributions of species with very different molecular masses such as native proteins and protein aggregates, which could be useful for chemokines that exhibit such behavior (e.g., RANTES/CCL5).

2.4. Fluorescence polarization Fluorescence polarization (FP) has been used to determine the dependence of the dissociation constant for dimerization of SDF-1a/CXCL12 on solution conditions, including pH, salt, and the presence of heparin (Veldkamp et al., 2005). FP is measured after excitation of a fluorophorecontaining molecule with linearly polarized light that causes ‘‘photoselection’’ of fluorophores with their absorption dipoles aligned parallel to the vector of the polarized light. The FP value depends on the reorientation rate of the fluorophore, which in turn depends on the size of the molecule it is attached to. Small molecules rotate rapidly, causing rapid randomization of the originally polarized light and low FP. By contrast, large molecules rotate slowly and have higher FP values compared with lower molecular weight, faster tumbling counterparts. The dependence on size makes FP a viable method for measuring oligomerization. In the study by Veldkamp et al. (2005) the fluorescence was derived from tryptophan residues that are highly conserved in chemokines. On oligomerization of the chemokine, the FP value increases, and when done as a function of chemokine concentration, the curves can be fit to determine dissociation constants for oligomerization. Given the size of chemokines, only small changes in FP are observed for monomer–dimer equilibria, but they are still sufficient for reasonably accurate affinity determinations. The quantum yield of Trp is also sufficient for the concentration ranges needed for chemokine oligomerization. In principle, sensitivity could be increased by covalent attachment of fluorophores with higher quantum yields. The measurements are rapid and easy both in terms of data collection and analysis. Access to the appropriate instrumentation is generally not difficult. Thus FP is certainly a method to consider for studying oligomerization, especially when comparing effects of mutations and/or solution conditions.

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2.5. FT-ICR mass spectrometry Fourier-transform ion cyclotron resonance (FT-ICR) mass spectrometry is a useful method for studying noncovalent chemokine: GAG interactions as well as oligomerization of chemokines (Crown et al., 2006; Yu et al., 2005, 2006). This method is facilitated by electrospray ionization (ESI), which enables transfer of intact noncovalent complexes from solution to gas phase (Crown et al., 2006). FT-ICR has very high mass accuracy and can be used to determine the molecular weight of complexes, stoichiometry, etc., and previous experiments have yielded results that at least qualitatively correspond to AUC and NMR (Yu et al., 2005, 2006). It is particularly useful for examining heterodimerization, which would not be possible by any of the previously described methods. With FT-ICR, Crown et al. analyzed the ability of the MCP-1 ligands (MCP-1/CCL2, MCP-2/CCL8, MCP-3/ CCL7, MCP-4/CCL13) and eotaxin/CCL11 to homo- and heterodimerize (Crown et al., 2006). CCL2 and CCL8 showed a high propensity to heterodimerize, whereas heterodimers between CCL2 and CCL11, CCL2 and CCL13, and CCL8 and CCL13 were weaker, and no ligand heterodimerized with CCL7. In addition, they demonstrated that in the case of CCL2/CCL8, heterodimerization formed at the expense of homodimerization, suggesting functional relevance (Crown et al., 2006). FT-ICR measurements can be done quite rapidly and, therefore, are useful for screens of this nature. However, because the measurements are done in the gas phase, it remains to be seen how quantitative the method is. Nevertheless, use of FT-ICR in combination with NMR for quantitation (see later), can be quite powerful. Chapter 4 in this volume describes the use of FT-ICR for analyzing chemokine: GAG interactions.

2.6. Other methods 2.6.1. Size exclusion chromatography Size exclusion chromatography (SEC) is a classic method for determining molecular size. It works by determining the volume of solvent required to elute a protein sample over a column containing porous beads. The beads have a defined distribution of pore sizes that control the size or ‘‘fractionation range’’ of proteins that can be separated from each other. The elution volume is relative and must be calibrated with known protein standards, and it is important to realize that molecules are separated according to both mass and shape. However, we mention it here as being one of the least desirable of the methods primarily because it is a nonequilibrium measurement, and dissociation of interacting species will occur during the experiment. Although SEC has been used to analyze chemokine oligomerization (Holmes et al., 2001; Hoogewerf et al., 1997), it is only applicable for very

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tightly bound complexes, which is typically not characteristic of chemokine oligomerization, with some exceptions like RANTES/CCL5. 2.6.2. 15N Heteronuclear relaxation by NMR 15N T1, T2, and heteronuclear 1H–15N NOE relaxation measurements from NMR experiments give information on protein dynamics and are generally interpreted with respect to several time scales: picosecond to nanosecond internal motions within the protein, overall global rotational tumbling of the protein (nanosecond), and microsecond to millisecond time scale motions indicative of chemical exchange such as monomer–dimer equilibrium (Ishima and Torchia, 2000). Baryshnikova and Sykes (2006) evaluated the concentration dependence of NMR relaxation parameters of CXCL12 at different concentrations to determine the binding constant for dimerization. They also demonstrated that regions from CXCL12 involved in the dimer interface in structures previously determined by crystallography are involved in slow time scale motions. Thus information on oligomerization is obtainable with these methods; however, they are not as accurate as methods like AUC. Therefore, this approach is not recommended except for the NMR aficionado, because the experimental data collection and analysis are technically quite involved, extremely time-consuming (many days), and the experiments require the production of multimilligram quantities of 15N-labeled protein.

3. Methods for Collecting Residue-Specific Information on Chemokine Oligomers NMR is a powerful technique for studying protein structures in solution. Several different methods have been applied to chemokines to specifically detect sites of interactions, such as the dimer interface and interactions with GAGs and with receptor fragments (Crown et al., 2006; McCornack et al., 2003; Nesmelova et al., 2008; Veldkamp et al., 2008). These methods all require fully assigned proton-nitrogen and/or proton-carbon correlation spectra for the protein under study and thus require considerable data collection and analysis times, as well as isotopically labeled protein.

3.1. NMR: Heteronuclear single quantum correlation (HSQC) spectroscopy Changes in chemical shift observed in heteronuclear single quantum coherence (HSQC) spectra could be used to determine which residues are involved in forming a dimer interface and potentially to calculate a binding constant. NMR signals corresponding to each backbone 15N-1H residue

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may shift frequency on the basis of changes in the local magnetic environment caused by dimerization. These changes or perturbations can be monitored as a function of concentration to study oligomerization. For example, chemical shift perturbations were used in conjunction with AUC to determine that the residues Phe13 and Pro8 are essential for the dimerization of CCL4/MIP-1b (Laurence et al., 2000). Crown et al. (2006) also used chemical shift perturbations to study the heterodimerization of MCP-1/ CCL2 and MCP-2/CCL8. By titrating increasing amounts of unlabeled CCL8 into a sample of 15N-labeled CCL2, they were able to monitor changes in chemical shifts of CCL2 1H-15N resonances, indicating that the chemokines were heterodimerizing and forming CC-like dimer structures (Crown et al., 2006). The near complete loss of signals for the CCL2 dimer on the addition of stoichiometric amounts of CCL8 indicated that heterodimer formation was favored over homodimer formation, similar to results from FT-ICR. The use of the HSQC was particularly important for this study, because most other methods described in the previous section, with the exception of FT-ICR, would not be able to distinguish homodimer formation from heterodimer formation. HSQC analysis is relatively rapid (minute to hours), although it requires the production and prior assignment of isotopically labeled protein. It is important to note, however, that because chemical shift perturbations can be caused by intermolecular interactions or by conformational rearrangements, these analyses do not unambiguously define the oligomeric interface but rather point to a general region on the basis of a consensus of chemical shift changes mapped onto a structure.

3.2. NMR: Detection of nuclei in close proximity by means of the nuclear Overhauser effect (NOE) The nuclear Overhauser effect (NOE) is used to determine nuclei within close proximity to each other and can include through-space signals both within a monomer (intramolecular) and between two subunits of a dimer (intermolecular). The NOE signal is inversely proportional to the sixth power of the distance between two nuclei and, therefore, is only observable ˚ apart. This distance constraint allows these experibetween nuclei <
6 A ments to define residues at the interface of dimers. For example, Clore et al. (1990) used NOEs to solve the dimer structure of the chemokine IL-8/ CXCL8 and determined that the interface is primarily stabilized by an antiparallel b-sheet formed between the first b-strands of each subunit (a classic ‘‘CXC’’ dimer, Fig. 2.1C), as well as several important sidechain interactions. The notable caveat to this method is the difficulty in distinguishing between intramolecular and intermolecular NOE signals. In many instances there is sufficient signal overlap to make this determination

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virtually impossible. This caveat has led to the development of filtered experiments that, in principle, select only for intermolecular NOEs. 3.2.1. Filtered NOE experiments The problem of distinguishing between intramolecular and intermolecular signals may be addressed with a combination of isotope-filtered and isotopeedited NOE experiments on complexes formed from mixtures of asymmetrically labeled chemokine monomers to break the magnetic symmetry and directly determine intersubunit NOEs (Breeze, 2000; Handel and Domaille, 1996; Jin et al., 2007; Veldkamp et al., 2008). For example, Handel and Domaille (1996) generated a sample of a 50:50 mixture of 15N-labeled and 13C-labeled MCP-1/CCL2 and used a filtered NOE experiment that selectively detects intersubunit signals between 15N-1H and 13C-1H pairs across the dimer interface. One advantage of this (HC)NH-NOE experiment is that magnetization is filtered through two different magnetically active nuclei (as opposed to other filters that record 13C-1H to 12C-1H), allowing additional suppression of intramonomer NOE signal (Handel and Domaille, 1996). Figure 2.4 shows an example of such an experiment compared with the assigned 1H-15N HSQC (Handel and Domaille, 1996). With this experiment, it was possible to assign 65 intersubunit NOEs, which characterized the dimer interface as an antiparallel b-sheet between the N-termini of the subunits. These results were used as additional restraints to solve the CCL2 dimer structure, which was determined to be what is now known as a CC dimer. More recently, Veldkamp et al. used a similar filtered NOE experiment on a mixed-label sample of SDF-1a/CXCL12 to study the interaction between an engineered covalent dimer and the sulfated N-terminal fragment of the CXCR4 receptor (Veldkamp et al., 2008). Their results suggest that receptor sulfation may enhance ligand affinity and stabilize the bound chemokine dimer. Filtered NOE experiments have been used successfully in evaluating other chemokine dimer interfaces; however, not all chemokines may be amenable to this approach. The NOE signal is relatively weak to begin with, and this is exacerbated by the fact that only 50% of the sample will correspond to a mixed-label dimer between 15N and 13C-labeled monomers (25% will be 15N-only and 25% will be 13C only). In addition, the NOE depends on dipolar coupling being the dominant relaxation mechanism. Any other competing relaxation mechanism, such as unfavorable dynamics associated with oligomerization, may make it impossible to obtain sufficient signal for analysis. These experiments and their analysis also require a great deal of experimental sophistication, making them less routinely used. The NMR methods just listed are useful tools for studying chemokine dimerization under physiologic conditions. However, larger order oligomers such as tetramers have not been successfully studied by NMR because of a number of physical and spectroscopic issues that are beyond the scope of this chapter. Fortunately, the structural details of chemokine tetramers have

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A

15N- 1H

HSQC

114

15N

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116 118 120 122 124

10

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7

(HC) NH-NOE 14N

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15F 66H 65D 14N

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57Q

23Q 70Q

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9V 68D

11C 40A

30R

122

39E 124

76T 16R 4A

52C 17N 10

19K

7A

38K 47V

9 1H

8 (ppm)

7

Figure 2.4 (A) 2-D 15N HSQC of uniformly labeled CCL2/MCP-1. (B) 2-D 1H-15N plane of the (HC)NH NOE experiment on a 50:50 mixture of (15N þ 13C)^labeled CCL2. The observed cross-peaks in the 2-D 15N HSQC unambiguously establish the backbone and side chain amide residues involved in the dimerization interface and were used by Handel et al. to solve the dimer structure of CCL2 (Handel and Domaille,1996).

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been solved by the complementary technique of X-ray crystallography as demonstrated for CCL2, IP-10/CCL10, and PF-4/CCL4 (Baldwin et al., 1991; Barinka et al., 2008; Blain et al., 2007; Lubkowski et al., 1997; Ryu et al., 2007; Shaw et al., 2004; Swaminathan et al., 2003).

4. Conclusions Chemokines are involved with many different interactions–with their receptors, with GAGs, and with other chemokines through both homoand hetero-oligomerization. In addition, the chemokine network is complex, with many chemokines interacting with multiple receptors and vice versa, yet many chemokines maintain tissue specificity. Understanding the structural characteristics and mechanisms of chemokine oligomerization is a crucial step in determining details of these different interactions. As this review shows, a wide variety of methods can be used to study chemokine oligomerization, both residue-specific and more generalized. It is often necessary to use these methods in combination with each other or in conjunction with other techniques such as mutagenesis to obtain the most complete picture possible. Although we know that many chemokines dimerize, the importance of higher order oligomerization and heterodimerization is less defined. Correlating these oligomeric states with function remains an important endeavor for fully understanding the role that structural plasticity plays in chemokine functional diversity and regulation.

ACKNOWLEDGMENTS This work was funded by the NIH through the Molecular Biophysics Training Grant (GM08326) awarded to A. J., NRSA postdoctoral fellowship F32GM083463 awarded to D. J. H., and by the Lymphoma Research Foundation, the Department of Defense (USAMRAA W81XWH0710446) and NIH (RO1-AI37113) awards to T. M. H.

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oligomerization for chemokine activity in vivo Inhibition of monocyte chemoattractant protein-1 ameliorates rat adjuvant-induced arthritis. J. Leukoc. Biol. 84, 1101–1108. Hartley, O., Dorgham, K., Perez-Bercoff, D., Cerini, F., Heimann, A., Gaertner, H., Offord, R. E., Pancino, G., Debre, P., and Gorochov, G. (2003). Human immunodeficiency virus type 1 entry inhibitors selected on living cells from a library of phage chemokines. J. Virol. 77, 6637–6644. Holmes, W. D., Consler, T. G., Dallas, W. S., Rocque, W. J., and Willard, D. H. (2001). Solution studies of recombinant human stromal-cell-derived factor-1. Protein Expr. Purif. 21, 367–377. Homey, B., Alenius, H., Mu¨ller, A., Soto, H., Bowman, E. P., Yuan, W., McEvoy, L., Lauerma, A. I., Assmann, T., Bu¨nemann, E., Lehto, M., Wolff, H., et al. (2002). CCL27CCR10 interactions regulate T cell-mediated skin inflammation. Nat. Med. 8, 157–165. Hoogewerf, A. J., Kuschert, G. S., Proudfoot, A. E., Borlat, F., Clark-Lewis, I., Power, C. A., and Wells, T. N. (1997). Glycosaminoglycans mediate cell surface oligomerization of chemokines. Biochemistry 36, 13570–13578. Imberty, A., Lortat-Jacob, H., and Perez, S. (2007). Structural view of glycosaminoglycanprotein interactions. Carbohydr. Res. 342, 430–439. Ishima, R., and Torchia, D. A. (2000). Protein dynamics from NMR. Nat. Struct. Biol. 7, 740–743. Jin, H., Hayes, G. L., Darbha, N. S., Meyer, E., and LiWang, P. J. (2005). Investigation of CC and CXC chemokine quaternary state mutants. Biochem. Biophys. Res. Commun. 338, 987–999. Jin, H., Shen, X., Baggett, B. R., Kong, X., and LiWang, P. J. (2007). The human CC chemokine MIP-1beta dimer is not competent to bind to the CCR5 receptor. J. Biol. Chem. 282, 27976–27983. Johnson, Z., Kosco-Vilbois, M. H., Herren, S., Cirillo, R., Muzio, V., Zaratin, P., Carbonatto, M., Mack, M., Smailbegovic, A., Rose, M., Lever, R., Page, C., et al. (2004). Interference with heparin binding and oligomerization creates a novel anti-inflammatory strategy targeting the chemokine system. J. Immunol. 173, 5776–5785. Johnson, Z., Proudfoot, A. E., and Handel, T. M. (2005). Interaction of chemokines and glycosaminoglycans: A new twist in the regulation of chemokine function with opportunities for therapeutic intervention. Cytokine Growth Factor Rev. 16, 625–636. Kunkel, E. J., and Butcher, E. C. (2002). Chemokines and the tissue-specific migration of lymphocytes. Immunity 16, 1–4. Kuschert, G. S., Coulin, F., Power, C. A., Proudfoot, A. E., Hubbard, R. E., Hoogewerf, A. J., and Wells, T. N. (1999). Glycosaminoglycans interact selectively with chemokines and modulate receptor binding and cellular responses. Biochemistry 38, 12959–12968. Lau, E. K., Paavola, C. D., Johnson, Z., Gaudry, J. P., Geretti, E., Borlat, F., Kungl, A. J., Proudfoot, A. E., and Handel, T. M. (2004). Identification of the glycosaminoglycan binding site of the CC chemokine, MCP-1: Implications for structure and function in vivo. J. Biol. Chem. 279, 22294–22305. Laurence, J. S., Blanpain, C., Burgner, J. W., Parmentier, M., and LiWang, P. J. (2000). CC chemokine MIP-1 beta can function as a monomer and depends on Phe13 for receptor binding. Biochemistry 39, 3401–3409. Loetscher, P., and Clark-Lewis, I. (2001). Agonistic and antagonistic activities of chemokines. J. Leukoc. Biol. 69, 881–884. Lowman, H. B., Fairbrother, W. J., Slagle, P. H., Kabakoff, R., Liu, J., Shire, S., and Hebert, C. A. (1997). Monomeric variants of IL-8: Effects of side chain substitutions and solution conditions upon dimer formation. Protein Sci. 6, 598–608. Lubkowski, J., Bujacz, G., Boque, L., Domaille, P. J., Handel, T. M., and Wlodawer, A. (1997). The structure of MCP-1 in two crystal forms provides a rare example of variable quaternary interactions. Nat. Struct. Biol. 4, 64–69. McCornack, M. A., Cassidy, C. K., and LiWang, P. J. (2003). The binding surface and affinity of monomeric and dimeric chemokine macrophage inflammatory protein 1 beta for various glycosaminoglycan disaccharides. J. Biol. Chem. 278, 1946–1956.

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C H A P T E R

T H R E E

Lymphotactin Structural Dynamics Brian F. Volkman, Tina Y. Liu, and Francis C. Peterson Contents 1. 2. 3. 4. 5. 6. 7.

Introduction Production of Biologically Active Lymphotactin Ltn Folds into Two Unrelated Native State Structures Kinetics of Interconversion in the Ltn Conformational Equilibrium Engineering Conformationally Restricted Lymphotactin Variants Functional Analysis of Distinct Ltn Native State Conformations GAG Binding Residues are Linked to the Ltn Conformational Equilibrium 8. Conclusions References

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Abstract Lymphotactin/XCL1, the defining member of the C class of chemokines, undergoes a conformational change that involves the complete restructuring of all stabilizing interactions. Other chemokines are restricted to a single conformation by a pair of conserved disulfide crosslinks, one of which is absent in lymphotactin. This structural interconversion is entirely reversible, and the two-state equilibrium is sensitive to changes in temperature and ionic strength. One species adopts the conserved chemokine fold as a monomer and functions as an agonist for XCR1, the specific G-protein–coupled receptor for lymphotactin. Rearrangement to the other conformation produces a novel four-stranded sheet that dimerizes to form a beta sandwich with high affinity for cell-surface glycosaminoglycans. We developed methods for resolving the two species and investigated the dynamics of human lymphotactin structural interconversion with NMR spectroscopy, heparin affinity chromatography, and time-resolved fluorescence on the wild-type protein and a panel of amino acid–substituted lymphotactin variants. Our results show that the lymphotactin structural rearrangement occurs at a rate of
1/s and that mutation of residues required for glycosaminoglycan binding shifts the conformational equilibrium toward the chemokine-like fold. We speculate that charge repulsion between arginines 23 and 43 destabilizes the chemokine fold and promotes conversion to the novel Department of Biochemistry, Medical College of Wisconsin, Milwaukee, Wisconsin, USA Methods in Enzymology, Volume 461 ISSN 0076-6879, DOI: 10.1016/S0076-6879(09)05403-2

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2009 Elsevier Inc. All rights reserved.

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lymphotactin dimer, whereas binding of chloride or another anion stabilizes the chemokine fold by neutralizing the repulsive effect.

1. Introduction Lymphotactin (Ltn) is a chemokine that recruits T and NK cells and is produced mainly by activated CD8þ T cells and activated NK cells. Like other chemokines, Ltn induces intracellular calcium mobilization and chemotaxis by binding a specific G-protein–coupled receptor (GPCR) (Yoshida et al., 1998). When it was originally cloned from a mouse progenitor T cell cDNA library in 1994 (Kelner et al., 1994), comparisons with other chemokines highlighted two novel structural features in the Ltn sequence. At 93 residues in length, the mature, secreted form of Ltn contains a C-terminal extension of
25 amino acids relative to the CXC and CC chemokines. Moreover, it lacks the first and third of four conserved cysteine residues found in all other chemokines, and thus possesses only a single disulfide bond. Although the CXC and CC chemokine genes cluster on human chromosomes 4 and 17, respectively (Modi and Chen, 1998; Naruse et al., 1996), human lymphotactin is located on chromosome 1 (Kelner et al., 1994). On the basis of these distinctions, lymphotactin was taken to define a novel type of chemokine, the ‘‘C’’ family (Kelner et al., 1994), and given the systematic designation XCL1. Ltn binds the GPCR XCR1 with low nanomolar affinity to induce CD8þ T cell and NK cell chemotaxis and chemoattracts CD4þ T cells with lower efficiency (Kelner et al., 1994). This may be due in part to the ability of Ltn to costimulate the apoptosis of CD4þ T cells but not CD8þ T cells (Cerdan et al., 2001). Ltn is produced mainly through T cell receptor activation in CD4þ and CD8þ T cells (Kelner et al., 1994; Tikhonov et al., 2001) but also by NK cells (Kelner et al., 1994) and gd T cells (Boismenu et al., 1996). Together, the data suggest that Ltn produced by T cells can regulate or modulate T cell–mediated immune responses. Lymphotactin expression or activity is associated with a number of T cell–mediated disease states. Data from rheumatoid arthritis patients (Blaschke et al., 2003) and animal models for acute allograft rejection (Wang et al., 1998), Crohn’s disease (Scheerens et al., 2001), and glomerulonephritis (Natori et al., 1998) are consistent with an immunomodulatory role for Ltn. Inhibitors or mimics of this chemokine may, therefore, have therapeutic value in the context of autoimmune and inflammatory diseases. In fact, Ltn has already been used in the development of novel cancer immunotherapies. A number of animal studies have shown that Ltn can recruit T cells to the site of a tumor (Dilloo et al., 1996; Huang et al., 2005), and combined expression of Ltn and interleukin-2 in a neuroblastoma

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tumor vaccine induced measurable antitumor immune responses, including complete remission in two patients (Rousseau et al., 2003). Chemokines share a highly conserved tertiary structure consisting of a flexible N-terminus, three-stranded b-sheet, and C-terminal a-helix, stabilized by two disulfide bonds (Clore and Greonenborn, 1995). Despite its small size (<10 kDa), the surface of each chemokine must support specific high-affinity binding to two different targets to function in vivo. In addition to specifically recognizing and activating a GPCR on the target cell, chemokines also bind glycosaminoglycans (GAGs) immobilized in the extracellular matrix (Proudfoot, 2003, 2006). Although the fundamental structural features of the family are now well established, novel aspects of chemokine structure and recognition continue to be revealed. The ability to form homodimers may also be essential for chemokine function (Campanella et al., 2006; Proudfoot et al., 2003), and chemokine heterodimers have recently been characterized (Crown et al., 2006; Nesmelova et al., 2008). No chemokine receptor structures have yet been solved, but sulfotyrosine modifications in the GPCR N-terminus enhance their recognition by chemokine ligands (Bannert et al., 2001; Farzan et al., 2002; Fong et al., 2002; Seibert et al., 2002, 2008), as illustrated recently for a complex between SDF-1/CXCL12 and its receptor CXCR4 (Veldkamp et al., 2006, 2008). Unlike all other chemokines, lymphotactin is constrained by only one disulfide bond, permitting it to access two completely different native state structures. A series of NMR studies showed that Ltn is conformationally heterogeneous in solution (Kuloglu et al., 2001), interconverting between the conserved chemokine fold (Kuloglu et al., 2002) and an unrelated dimeric structure (Tuinstra et al., 2008). This metamorphic folding behavior is unlike any previously described protein conformational rearrangement (Murzin, 2008). The chemokine-like Ltn conformation is a functional XCR1 agonist but has no high-affinity glycosaminoglycan (GAG)-binding site. In contrast, the alternative structure binds GAGs with high affinity but fails to activate XCR1. Because each structural species displays only one of the two functional properties essential for activity in vivo, the conformational equilibrium is likely to be essential for the biologic activity of lymphotactin. Despite its ability to orchestrate T cell–mediated immune responses, a specific biologic role for lymphotactin remains obscure. Some investigators have reported difficulty obtaining reproducible lymphotactin activity, and these challenges may derive from its unusual conformational plasticity. We investigated the dynamics of the native state equilibrium with a number of different methods as described in this chapter, with the ultimate goal of understanding how interconversion between two distinct lymphotactin structures contributes to its functional role in the immune system.

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2. Production of Biologically Active Lymphotactin Despite the challenge associated with large-scale production of disulfide-containing proteins, many biologically active chemokines have been prepared by chemical synthesis or bacterial expression (Clark-Lewis et al., 1997). A key consideration is to mimic the mature protein secreted from mammalian cells after processing of an amino terminal signal peptide, because like most chemokines, lymphotactin can be inactivated by any modifications to the amino terminal sequence (Tuinstra et al., 2007). Amino acid sequences for human lymphotactin and its orthologs are shown in Fig. 3.1A. We have used two different approaches for bacterial expression of Ltn for structural and functional studies. Our original expression system used Factor Xa cleavage of an N-terminal fusion protein to release Ltn with the native N-terminus (Kuloglu et al., 2001). This material was biologically active in assays that measure XCR1 activation by chemotaxis or intracellular calcium flux, but nonspecific proteolysis of the Ltn C-terminus led us to develop a more robust method based on cyanogen bromide (CNBr) cleavage of an N-terminal Hexa histidine tag. CNBr cleaves the peptide bond following methionine residues, but human Ltn contains two nonconserved Met residues (M63 and M73) that we changed to valine and alanine, respectively (Tuinstra et al., 2007). Ltn proteins produced by the two methods are indistinguishable in terms of structure and biologic activity (Tuinstra et al., 2007, 2008). Final purification of chemokines is typically achieved by reverse-phase HPLC after disulfide formation in an oxidation/folding step. Lymphotactin refolding can be achieved either in solution or with an on-column buffer exchange process to catalyze disulfide formation (Veldkamp et al., 2007). Oncolumn refolding is considerably faster and can improve the yield of protein with the correct disulfide pattern for some chemokines. However, because Ltn contains only a single disulfide bond, solid-phase refolding presents no particular advantage, and we typically perform disulfide oxidation in solution as previously described (Peterson et al., 2004). An unusual feature of the lymphotactin structure is glycosylation of the extended C-terminus in a portion of the protein purified from cultured mammalian cells (Dorner et al., 1997). Investigations into the functional significance of glycosylation used Ltn synthesized with carbohydrate modifications (Marcaurelle et al., 2001) or expressed in insect cells with a baculovirus system (Dong et al., 2005). Glycosylation had no detectable effect on XCR1 activation (Marcaurelle et al., 2001), and our own measurements confirm that the Ltn C-terminus (residues 73 to 93) is dispensable for both calcium-flux (Tuinstra et al., 2007) and T cell chemotaxis

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Figure 3.1 Lymphotactin adopts two unrelated folds in equilibrium. (A) Alignment of Ltn sequences from human, mouse, rat, cow, and chicken. (B) 1H-15N HSQC spectra acquired for wild-type human Ltn at 37  C and (C) 10  C in 20 mM sodium phosphate (pH 6.0) containing 200 mM sodium chloride. (D) Structure of wild-type Ltn at 10  C showing that under these solution conditions Ltn adopts the canonical chemokine fold, subsequently referred to as Ltn10. Unstructured residues (1 to 7, 76 to 93) were omitted for clarity. (E) 1H-15N HSQC spectrum of wild-type Ltn at 40  C acquired in 20 mM sodium phosphate (pH 6.0) in the absence of salt. (F) Structure of wild-type Ltn at 40  C (Ltn40) adopts a novel four-stranded antiparallel b-sheet that self-associates as a head-to-tail dimer. Disordered N- and C-termini (1 to 7, 56 to 93) were omitted for clarity.

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(S. Kutlesa, F. C. Peterson, and B. F. Volkman, unpublished results). A purpose for Ltn glycosylation thus remains unknown, and the functional role of the novel C-terminal sequence is a focus of our ongoing studies.

3. Ltn Folds into Two Unrelated Native State Structures NMR spectroscopy provided the first evidence of conformational duality in the lymphotactin structure. A 2-D 1H-15N HSQC spectrum acquired in typical conditions for protein NMR (20 mM sodium phosphate buffer, 200 mM NaCl, pH 6.0, 37  C) contains roughly twice the number of peaks expected for a stably folded 93-residue protein (Fig. 3.1B). Intense signals in a narrow 1H chemical shift range (
7 to 8 ppm) suggested that some of the protein was unfolded, whereas other more dispersed peaks corresponded to one or more folded states, but the spectrum was otherwise uninterpretable. We verified the identity, purity, and disulfide oxidation state by analytical HPLC and electrospray ionization mass spectrometry and reproduced the same 1H-15N HSQC spectrum in multiple preparations. Initially, we varied sample pH, temperature, and buffer composition with no obvious improvement in the HSQC spectrum; however, larger changes in temperature and solution ionic strength had a surprisingly dramatic effect. After systematic NMR screening of both parameters, we obtained a vastly simplified HSQC spectrum at 10  C in 200 mM NaCl (Fig. 3.1C) and solved the NMR structure under those conditions (Kuloglu et al., 2001). We refer to the conformation observed in low-temperature/high-salt conditions as Ltn10 (Fig. 3.1D), a monomeric state that closely resembles other chemokines with the addition of a highly flexible C-terminal extension consisting of residues 70 to 93. A very different HSQC pattern was observed at higher temperature in low ionic strength buffer (Fig. 3.1E) (Kuloglu et al., 2002). Analytical ultracentrifugation revealed that the Ltn structure at 40  C in the absence of salt (Ltn40) is dimeric with a Kd in the low micromolar range, but the structure of the Ltn40 dimer proved difficult to resolve. Our initial NMR studies of Ltn40 revealed a dramatic change from the typical pattern of secondary structure elements observed in the chemokine-like Ltn10 structure. Nuclear Overhauser effect (NOE) cross peaks identified longrange contacts between a new b-strand comprised of residues 11 to 14 (b0) and the b3 strand and showed that the a-helix had become disordered with the rest of the C-terminal domain (residues 53 to 93), but they failed to identify the Ltn40 dimer interface (Kuloglu et al., 2002). In an effort toward selective detection of intermolecular NOEs linking aliphatic protons from one subunit to amide protons of the other subunit, we acquired a F1

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13C-edited/F3 15N-edited

3D NOESY-HSQC spectrum on a equimolar mixture of [U-15N]-Ltn and [U-13C]-Ltn, but it was devoid of signals. Heteronuclear filtering can be technically difficult in protein NMR spectroscopy, particularly the 13C filtering of proton signals exhibiting a wide range of 1H-13C coupling constants. We successfully detected unambiguous intermolecular NOEs only after implementing an F1 13C/15Nfiltered/F3 13C-edited 3D NOESY-HSQC pulse sequence originally described by Palmer and coworkers (Stuart, 1999). Their pulse scheme compensates for the normal variations in 1H-13C scalar couplings in proteins and, most importantly, is both robust and simple to use, requiring no complex pulse calibrations or empirical optimizations. We routinely use this filtered NOESY experiment to solve structures for homodimer (Peterson et al., 2006) and heterodimer (Veldkamp et al., 2008) complexes. A total of 31 intermolecular NOEs were assigned in the filtered NOESY spectrum of Ltn40, each of which gave rise to a pair of symmetry-related intermolecular distance restraints. These restraints enabled us to solve the structure of the Ltn40 dimer (Tuinstra et al., 2008), which adopts a novel b-sandwich fold with four strands in each monomer subunit and no helices (Fig. 3.1F). Although the b1-, b2-, and b3-strands may seem unchanged, the rearrangement from Ltn10 to Ltn40 creates a completely different pattern of b-sheet hydrogen bonding and hydrophobic packing as described previously (Kuloglu et al., 2002; Tuinstra et al., 2008). Thus, Ltn folds into two distinct, unrelated structures, depending on temperature and solution conditions.

4. Kinetics of Interconversion in the Ltn Conformational Equilibrium For both native state Ltn structures to contribute to its chemokine activity in vivo, we postulated that individual molecules must be capable of converting from the Ltn10 state to the Ltn40 state and vice versa. A series of HSQC spectra collected on a single sample from 10 to 40  C confirmed that the Ltn10–Ltn40 transition is fully reversible, and spectra at intermediate temperatures contain distinct signals for each conformational state (Kuloglu et al., 2002; Tuinstra et al., 2007). Thus, changes in the Ltn conformational equilibrium induced by temperature, ionic strength, mutations, or binding interactions can be monitored by 1-D 1H and 2-D 1H-15N NMR spectroscopy. It is also of interest to measure the kinetics of conformational exchange, and the choice of technique depends on the time scale. The presence of distinct HSQC signals for the two species in equilibrium indicates that the frequency of Ltn10–Ltn40 interconversion is significantly lower than the observed chemical shift differences (
50 to 100 Hz).

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We initially tried to assess the rate of structural interconversion by monitoring amide H/D exchange rates. We reasoned that because the conformational rearrangement breaks every hydrogen bond and replaces it with a different one (Kuloglu et al., 2002), the lifetime of the Ltn10 and Ltn40 species would set an upper limit on the protection factor of all amide hydrogens. If the interconversion is very slow (minutes or longer), the observed H/D exchange rates would be dominated by this rate. We acquired 1-D 1H and 2-D 1H-15N HSQC spectra on a sample of lyophilized Ltn dissolved in 100% D2O. Regardless of pH, temperature, or salt concentration, we failed to detect any amide 1H signals in the first spectrum, which was acquired less than 5 min after dissolving the sample. Knowing that the interconversion rate was on the order of seconds (not milliseconds or minutes), we measured 2-D longitudinal 15N zz-exchange spectra (Farrow et al., 1994) to detect exchange peaks that appear at the intersection of 1H and 15N shifts for the same residue in the Ltn10 and Ltn40 conformations. We acquired a series of 2-D exchange spectra with different exchange mixing periods at 37  C in low salt buffer conditions where Ltn40 is more abundant than Ltn10 but both species are present at detectable levels (Fig. 3.2A) (Tuinstra et al., 2008). No exchange cross peaks were detected until the mixing time exceeded 50 msec with maximal intensities observed at
350 msec. Nonlinear fitting to equations accounting for a two-state exchange and 15N T1 relaxation (Tollinger et al., 2001) yielded rate constants for the forward (kforward = 0.4 s1) and reverse (kreverse = 1.2 s1) reactions consistent with an overall exchange rate, kex, of
1.5 s1. The single tryptophan in Ltn, W55, is another useful sensor of the Ltn10–Ltn40 conformational equilibrium (Kuloglu et al., 2002; Tuinstra et al., 2008). Transfer of the W55 side chain from a constrained environment in the Ltn10 hydrophobic core to a mobile, solvent-exposed state in Ltn40 shifts the tryptophan fluorescence emission maximum to a longer wavelength and reduces the intensity as illustrated in Fig. 3.2B (Kuloglu et al., 2002). Thus, changes in the conformational equilibrium can be detected by monitoring the fluorescence intensity at
335 nm. We speculated that time-resolved optical spectroscopy could be used to monitor the response of an Ltn10/Ltn40 mixture to an increase in salt concentration or the addition of a glycosaminoglycan like heparin. To demonstrate the feasibility of this approach, we performed a series of salt-jump experiments with the intrinsic fluorescence emission of W55. Although monitoring the emission at 335 nm, we injected buffer, concentrated NaCl, or low molecular weight heparin into a sample of 15 mM Ltn (Fig. 3.2C). The jump in NaCl concentration from 0 to 250 mM produced an increase in fluorescence intensity consistent with a shift toward Ltn10. In contrast, injection of heparin produced a decrease in intensity that we interpreted as an increase in the relative concentration of Ltn40.

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Figure 3.2 Spectroscopic detection of structural interconversion. (A) Exchange peaks between the Ltn10 and Ltn40 1H-15N resonances of Gly44 were detected with a 2-D 15 N zz-exchange spectrum acquired on 250 mM wild-type Ltn in 20 mM sodium phosphate, pH 6.0, 150 mM NaCl. Exchange spectra were measured with mixing times of 50, 150, 200, 250, 300, 350 (shown), 400, 500, 750, and 900 msec. Intensities of the peaks were fit to a two-state exchange model yielding rates of 0.4 and 1.2 s1 for the forward (Ltn40 ! Ltn10) and reverse (Ltn10 ! Ltn40) reactions, respectively. (B) Tryptophan emission spectrum of wild-type Ltn (15 mM) at 30  C in 0 mM NaCl, where the Ltn10:Ltn40 ratio is roughly 1:1. Arrows indicate how fluorescence intensity increases and the emission maximum shifts to lower wavelengths as the tryptophan is buried in the Ltn10 core, whereas increased solvent exposure and flexibility in Ltn40 decreases the intensity and causes a red shift. (C) Time-dependent fluorescence intensity at 335 nm for Ltn samples (15 mM, 30  C, 0 mM NaCl) injected at time 0 with buffer (), 15 mM low molecular weight heparin (▲), or 200 mM NaCl (e). Equilibration curves were fit to a simple exponential decay with ProFit software yielding Ltn40 ! Ltn10 and Ltn10 ! Ltn40 exchange rates of 0.22 and 0.73 s1, respectively.

As described in the following, this result is consistent with a model in which cell-surface GAGs bind preferentially to the Ltn40 species. Rates for the Ltn40 ! Ltn10 and Ltn10 ! Ltn40 reactions at 30  C (0.22 and 0.73 s1, respectively) obtained from nonlinear fitting are slightly lower than those measured by 2-D exchange NMR at 37  C. Although the fluorescence approach may be improved by use of a stopped flow apparatus with a shorter dead time for sample mixing, the general agreement of the preliminary results from fluorescence titrations and 2-D exchange NMR validates both methods for kinetic analysis of the Ltn conformational change. Future studies of the

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temperature dependence of kex will permit us to define the height of the energetic barrier (activation energy, Ea) separating the Ltn10 and Ltn40 species.

5. Engineering Conformationally Restricted Lymphotactin Variants Conveniently, the Ltn structure is highly sensitive to variations in temperature and salt concentration within the ranges typically used for biophysical measurements on proteins (e.g., 10 to 45  C, 0 to 200 mM NaCl), and this allowed us to resolve the two conformations present at physiologic conditions. However, assays for biologic activity with animals or cell cultures impose constraints on the buffer composition and temperature. These limited our ability to assign specific functional roles to the Ltn10 and Ltn40 species, because both would be present in significant amounts when attempting to measure intracellular calcium flux, chemotaxis, or cell recruitment in vivo. To solve this problem, we generated a panel of Ltn variants designed to favor either the Ltn10 or Ltn40 structure and prevent interconversion. Although the 3-D structure of Ltn40 had yet not been solved, its secondary structure was known (Kuloglu et al., 2002), and we used the structures of Ltn10 and the chemokine HCC-2 to design two different disulfide crosslinks that would prevent the rearrangement to Ltn40 as described previously (Tuinstra et al., 2007). Amino acid substitutions corresponding to the CC1-Ltn and CC3-Ltn variants are shown in Fig. 3.3. We took a different approach in designing an Ltn40-restricted variant: selectively destabilize the Ltn10 fold. Because residues 52 to 93 are disordered in Ltn40, we identified W55 as an essential hydrophobic core

Figure 3.3 Ltn variants stabilize either the Ltn10 or Ltn40 structure. The introduction of a second disulfide bond to stabilize the Ltn10 conformation was based on alignment of Ltn10 with CC chemokines. Construction of CC1-Ltn (T10C þ dipeptide insertion G32-AC-S33) is based on alignment with the first disulfide with RANTES, whereas the positions of the cysteine substitutions in CC3-Ltn (V21C/V59C) mimic the unusual third disulfide in HCC-2. Stabilization of the Ltn40 conformation is accomplished by introducing an aspartate or alanine point mutation at W55. Loss of the tryptophan side chain disrupts the hydrophobic core and destabilizes the Ltn10 conformation. Mutated residues are shown in white or black outline.

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residue in Ltn10 that makes no contribution to the Ltn40 structure and changed it to an alanine or aspartic acid (Fig. 3.3) (Tuinstra et al., 2008). All of the mutants were successfully expressed and purified, and we examined their 2-D 1H-15N HSQC spectra. For an objective measure of their similarity to one structure or the other we plotted the 1H and 15N shifts for each mutant against those of Ltn10 and Ltn40 (Fig. 3.4A). The W55D mutant matches the Ltn40 shifts very closely and shows a poor correlation with Ltn10, and HSQC spectra of the mutant proteins acquired at different temperatures show no evidence of interconversion to the other conformation (Fig. 3.4B), and similar results were obtained for the W55A mutant (not shown). Conversely, the nearly perfect correlation with Ltn10 shifts for the CC1 and CC3 variants show convincingly that the disulfide-locked proteins retain the chemokine-like fold, and we confirmed this by solving the NMR structure of CC3 (Fig. 3.4C) (Tuinstra et al., 2007). We next used the CC3-Ltn and W55D-Ltn proteins in a series of functional studies designed to assign functional roles to the Ltn10 and Ltn40 states.

6. Functional Analysis of Distinct Ltn Native State Conformations Chemokine function depends on dual biochemical activities, GAG binding, and GPCR activation. In the case of lymphotactin, the two functional roles may be segregated by a conformational barrier corresponding to the activation energy for Ltn10 $ Ltn40 interconversion. Treating the CC3 and W55D variants described previously as ‘‘pure’’ versions of Ltn10 and Ltn40, respectively, we compared their ability to activate the Ltn receptor XCR1 stably expressed on the surface of HEK293 cells (generously provided by Joseph Hedrick, Schering-Plough Research Institute) (Shan et al., 2000). As detailed by Tuinstra et al. (2007), changes in intracellular calcium levels in response to each protein at a concentration of 200 nM were monitored with cells loaded with the Fluo-3-AM dye at 37  C with a PTI spectrofluorometer. CC3-Ltn and wild-type Ltn induced similar calcium flux responses (Tuinstra et al., 2007), whereas W55D-Ltn was completely inactive (Tuinstra et al., 2008). To compare relative GAG binding activity for the Ltn10 and Ltn40 species, we eluted CC3-Ltn and W55D-Ltn from a heparin-Sepharose column with a sodium chloride concentration gradient (Tuinstra et al., 2008). Wild-type Ltn elutes in two broad fractions at
450 and 700 mM NaCl (Fig. 3.5 and Table 3.1), suggesting that the two conformations bind heparin with significantly different affinities. CC3-Ltn elutes at a single sharp peak at 450 mM NaCl, whereas the broader W55D-Ltn elution resembles the high-affinity fraction of wild-type Ltn with a peak at 750 mM NaCl.

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CC1 140

A

5.0

CC3 9.0

7.0

5.0

W55D

7.0

9.0

5.0

7.0

9.0 9.0

1HN 15

120

100

140 100 120 15N chemical shift

10 ⬚C

100

120

7.0

140

(ppm)

45 ⬚C

C Native disulfide bond

120 125 125

120

W55D

115 110 15N chemical

shift (ppm)

CC3

115

110

B

140

5.0

100

W55

1H

9.0

140

5.0

100

7.0

120 120

D58 G32

chemical shift (ppm)

Ltn10 Ltn40

H

9.0

8.0 1H

7.0

6.0

9.0

8.0

7.0

Engineered disulfide bond M73

6.0

chemical shift (ppm)

Figure 3.4 CC3-Ltn and W55D-Ltn are structurally indistinguishable from Ltn10 and Ltn40. (A) Amide chemical shifts for CC1-, CC3-, and W55D-Ltn plotted against the corresponding values for wild-type Ltn at 10 and 40  C. The excellent correlation of the Ltn10 chemical shifts with CC1-Ltn and CC3-Ltn compared with the poor correlation with the Ltn40 chemical shifts suggests that CC1-Ltn and CC3-Ltn adopt the chemokine-like fold. The converse is true for W55D-Ltn, demonstrating its similarity to Ltn40. Outliers in each plot are labeled and correspond to residues at or adjacent to the mutated positions in the amino acid sequence. (B) 1H-15N HSQC spectra of CC3-Ltn and W55D-Ltn acquired at 10 and 45  C in 20 mM sodium phosphate (pH 6.0). Comparison of the low- and high-temperature spectra indicates that CC3-Ltn only adopts the Ltn10 conformation and W55D-Ltn only adopts the Ltn40 conformation. (C) Ribbon diagram of CC3-Ltn showing the canonical chemokine fold. The structure was determined at 25  C in 20 mM sodium phosphate, a solution condition that normally contains a mixed population of the two Ltn conformers. The disulfide bond incorporated to restrict the conformation is shown.

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Lymphotactin Structural Dynamics

CC3

1.0

1

WT 2

W55D

R65S

R23A

2 1 1

R43A

R43A

1

2

0.25

2

R23A

0.5

K66A

2 R23A/R43A

0.75

R23A/R43A

Fractional population

K66A R65S

1

0 300

400

500 600 [NaCl] (mM)

700

800

Figure 3.5 Dual Ltn conformations bind heparin with different affinities. Elution of wild-type Ltn from a heparin-Sepharose column yields a biphasic profile with a lowand high-salt peak. In contrast, CC3-Ltn and W55D-Ltn elute as a single fraction corresponding to the low- and high-salt wild-type Ltn peaks, respectively. Alanine substitution of two arginines involved in GAG binding, R23 and R43, shifts the elution of the high-affinity (Ltn40) fraction. The high/low affinity peak ratio for R43A is skewed toward the Ltn10 conformation. This effect was more pronounced in the R23A/R43A double mutant, favoring the Ltn10 conformation by a ratio of 2:1. In contrast, mutation of residues that do not participate in heparin binding (R65A and K66S) had a minimal effect on the elution profiles or peak ratios when compared with wild-type Ltn.

Table 3.1 Elution from heparin-sepharose and relative intensities for lymphotactin variants

Ltn mutant

WT CC3 W55D R23A R43A R23A/ R43A R65S K66A

Peak 1 elution (mM NaCl)

Peak 2 elution (mM NaCl)

Fractional population peak 1

Fractional population peak 2

452 430 N.D. 382 376 309

694 N.D. 753 557 458 344

40 100 0 41 53 71

60 0 100 59 47 29

415 408

658 659

29 38

71 62

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9.8

9.4

9.0

8.6

9.4 9.8 9.0 8.6 1H chemical shift (ppm)

9.8

9.4

9.0

chemical shift (ppm)

1:1 W55D:CC3 250 mM heparin

15N

1:1 W55D:CC3 50 mM heparin

1:1 W55D:CC3 No heparin

128 127 126 125 124 123

Not surprisingly, our results showed that only the chemokine-like Ltn10 structure is capable of XCR1 signaling, and we learned that the Ltn40 dimer encodes tight GAG binding, whereas the Ltn10 species binds heparin with low but detectable affinity. To show that cell surface GAGs interact preferentially with Ltn40, we attempted to use 2-D NMR as the equivalent of a pull-down or coprecipitation assay. Initially, we added low molecular weight heparin to an NMR sample of [U-15N]-wild-type Ltn at conditions where both conformations are present, expecting to see an effect on the Ltn40 peaks only. Instead, HSQC signals for both species diminished and disappeared with increasing amounts of heparin. As illustrated by fluorescence spectroscopy in Fig. 3.2C, the addition of heparin to an equilibrium mixture of Ltn10 and Ltn40 causes a shift toward the Ltn40 state. At NMR concentrations, heparin forms insoluble complexes with Ltn40 and probably shifts the conformational equilibrium until all the protein has precipitated. To allow for selective heparin binding to either the Ltn10 or Ltn40 species without the potential for interconversion, we performed the same titration on a mixture of 15N-labeled CC3-Ltn and W55D-Ltn (Tuinstra et al., 2008). HSQC spectra of wild-type Ltn and the CC3/W55D mixture HSQC are virtually identical, but on addition of a heparin tetrasaccharide to the mixed sample, only the Ltn40 signals were lost (Fig. 3.6). Collectively, these studies support a model for lymphotactin activity in which the native state is coupled to two different binding equilibria, either of which can alter the Ltn10–Ltn40 conformational equilibrium (Fig. 3.7). In this model, cell surface GAGs can inhibit Ltn activity by shifting the equilibrium toward the

8.6

Figure 3.6 Selective heparin binding monitored by 2-D NMR. HSQC spectra recorded on an NMR sample containing 250 mM each of CC3-Ltn and W55D-Ltn at 37  C in 20 mM sodium phosphate (pH 6.0). Before the addition of heparin tetrasaccharide (left panel), 1H-15N HSQC signals are observed for W55D-Ltn (gray, Ltn40 conformation) and CC3-Ltn (black, Ltn10 conformation). Addition of heparin tetrasaccharide results in broadening (center panel) and disappearance of the W55D-Ltn resonances (right panel), whereas the CC3-Ltn resonances are unaffected.

65

Keq < 1 ΔG ⬚ = 0

XCR1 Ltn40

Lymphocyte

Ltn10

Ltn40

Keq < 1 ΔG ⬚ < 0

Ltn10

Keq < 1 ΔG ⬚ > 0 Ltn40

Cell-surface GAGs

Lymphotactin Structural Dynamics

Ltn10

Figure 3.7 Functional relevance of the Ltn conformational equilibrium. Under physiologic conditions, Ltn partitions equally between the Ltn10 and Ltn40 conformations. The conformational equilibrium may shift in response to interactions with cell-surface GAGs or XCR1. Cell-surface GAGs stabilize Ltn40 relative to Ltn10, whereas XCR1 binding may shift the equilibrium toward the Ltn10 conformer.

Ltn40 state and reducing the concentration of Ltn10 available for XCR1 activation. Presumably, there must be a mechanism for shifting the equilibrium toward the Ltn10 state when conditions require XCR1-mediated signaling and T cell chemotaxis. Whether the XCR1 receptor can shift the conformational equilibrium directly has not been investigated, and other factors that alter the Ltn10–Ltn40 balance may be identified in future in vivo studies of lymphotactin function.

7. GAG Binding Residues are Linked to the Ltn Conformational Equilibrium In a previous study, we substituted most of the lysine and arginine residues in Ltn with alanine and used surface plasmon resonance (SPR) to measure heparin binding affinities. We identified R23 and R43 as the residues that contributed most to GAG binding, because each alanine substitution reduced the affinity for heparin by
30-fold (Peterson et al., 2004). R23 and R43 are adjacent in the Ltn10 structure (Fig. 3.1C), but as described earlier, heparin-Sepharose binding studies showed that Ltn40 supplies the GAG binding function. Because SPR measurements provide no information on the relative affinities of the two Ltn structural species, we ran the panel of arginine and lysine mutants over the heparin column and noted the elution of the high- and low-affinity fractions. The results are illustrated schematically in Fig. 3.5 and summarized in Table 3.1. For substitutions that have little or no effect on GAG binding (e.g., R65S and K66A), the position and relative intensities of the two peaks are similar to wild type. As expected, the high-affinity fractions of R23A and R43A elute at significantly lower salt concentrations (557 and 458 mM NaCl, respectively) than wild-type Ltn40 (694 mM NaCl). Interestingly, the peak

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ratio for R43A was skewed toward the low affinity fraction compared with wild-type Ltn (Table 3.1), and the effect was even more pronounced for the R23A/R43A double mutant, which favored the low-affinity fraction by a ratio of more than 2:1. Elimination of key residues for high-affinity GAG binding seems to shift the conformational equilibrium toward Ltn10, but this could simply reflect a diminished capacity for heparin to stabilize Ltn40 and shift the equilibrium in the opposite direction. To determine whether substitutions at R23 and R43 alter the relative stabilities of Ltn10 and Ltn40 independent of heparin, we compared the HSQC spectra of wild-type Ltn and the R23A, R43A, and R23A/R43A mutants. Except for signals from the substituted residues, the HSQC spectrum of each mutant is superimposable with the spectrum of wild-type Ltn, thus the tertiary structure is unchanged. As shown in Fig. 3.8, wild-type Ltn readily converts from Ltn10 to Ltn40 as the temperature is increased from 10 to 45  C. However, substitution of either R23 or R43 with alanine seems to stabilize the Ltn10 species and shift the Ltn40 transition to higher temperatures (data not shown). The effect is more

A

B

45 ⬚C

9.0

8.0

chemical shift (ppm)

7.0

6.0

0.2 0.0 1.0

LTN40 0

10

20

30

40

50

30

40

50

LTN10

0.8 0.6

120

Fractional population

115 120 125 1H

6.0

chemical shift (ppm)

110 7.0

0.4

0.4

125

115 8.0

LTN10

0.6

15N

WT R23A/R43A 9.0

1.0 0.8

110

10 ⬚C

0.2 0.0

LTN40 0

10

20

Temperature (⬚C)

Figure 3.8 Mutation of GAG binding residues alters the Ltn10–Ltn40 equilibrium. Alanine substitution of R23 and R43 stabilize the Ltn10 conformer. (A) 1H-15N HSQC spectra of wild-type and R23A/R43A-Ltn acquired at 10 and 45  C in 20 mM sodium phosphate (pH 6.0). Comparison of the low- and high-temperature HSQCs indicates that the R23A/R43A double mutant stabilizes the Ltn10 conformation in the absence of salt. (B) Relative intensities of the W55 1He1 peak in the Ltn10 and Ltn40 conformations is plotted as a function of temperature. The plots indicate the equilibrium midpoint for wild-type Ltn is
25  C. In contrast, the equilibrium midpoint for R23A/R43A is shifted to
50  C under conditions that typically favor the Ltn40 conformation.

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Lymphotactin Structural Dynamics

+ R23 R23 +

R23 +

Cl−

R43

+

R43

+

R43

+

Figure 3.9 Ionic strength dependence in the Ltn structural equilibrium. Electrostatic repulsion in Ltn10 is relieved by salt or conversion to Ltn40 conformer. In the Ltn10 ˚ ) for their guanidinyl groups to conformation R23 and R43 are close enough (<8A coordinate a chloride ion (left panel). In the absence of salt, electrostatic repulsion between the positively charged side chains destabilizes the Ltn10 conformation (center panel). Alternately, the R23-R43 repulsion can be eliminated by conversion to the Ltn40 conformer (right panel).

pronounced for the R23A/R43A double mutant that remains predominantly in the Ltn10 form even at 45  C (Fig. 3.8). How does alanine substitution of one or two solvent-exposed loop residues affect the conformational equilibrium so dramatically? A recent molecular dynamics study suggests the close proximity of R23 and R43 in the Ltn10 conformation may be a destabilizing factor in low ionic strength solution. In a 14-nsec MD simulation performed at 45  C in the presence of 200 mM NaCl, Cui and coworkers found that the positively charged R23 and R43 side chains coordinate a chloride ion that also forms hydrogen bonds with the T41 hydroxyl and backbone amides from the 40’s loop (Formaneck et al., 2006). Chloride association with R23, R43, and the 40’s loop persisted for the last 5 nsec of the simulation, illustrating a specific protein–ion interaction that would favor the Ltn10 conformation. In the absence of a stabilizing anion, electrostatic repulsion between the nearby R23 and R43 side chains is relieved by the Ltn10 ! Ltn40 rearrangement ˚ which separates the two positively charged residues by a distance of
20 A (Fig. 3.9). Replacement of either R23 or R43 reduces the repulsive effect, diminishing the need for anion stabilization and favoring the Ltn10 structure relative to Ltn40.

8. Conclusions Unique features of the lymphotactin sequence distinguish it from other chemokines. Structural analysis revealed an unprecedented nativestate interconversion between two unrelated structures, each of which contributes to the biologic activity of Ltn. In this work, we showed that

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the Ltn10 and Ltn40 structures interconvert with a frequency of
1 s1 with fluorescence and NMR experiments. Data from mutagenesis, heparin affinity chromatography, and NMR interpreted in the context of published MD simulations suggested that electrostatic repulsion in the Ltn10 structure between key GAG-binding residues could be stabilized by anion binding in solutions of high ionic strength. Our long-term goals are to understand each step in the process of structural interconversion between the Ltn10 and Ltn40 states and to relate this unusual conformational equilibrium to lymphotactin activity in vivo. The experimental approaches and results described here serve as a foundation for more detailed studies of lymphotactin dynamics with a combination of mutagenesis, optical and NMR spectroscopy, and MD simulations.

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and oligomerization are essential for the in vivo activity of certain chemokines. Proc. Natl. Acad. Sci. USA 100, 1885–1890. Rousseau, R. F., Haight, A. E., Hirschmann-Jax, C., Yvon, E. S., Rill, D. R., Mei, Z., Smith, S. C., Inman, S., Cooper, K., Alcoser, P., Grilley, B., Gee, A., et al. (2003). Local and systemic effects of an allogeneic tumor cell vaccine combining transgenic human lymphotactin with interleukin-2 in patients with advanced or refractory neuroblastoma. Blood 101, 1718–1726. Scheerens, H., Hessel, E., de Waal-Malefyt, R., Leach, M. W., and Rennick, D. (2001). Characterization of chemokines and chemokine receptors in two murine models of inflammatory bowel disease: IL-10/ mice and Rag-2/ mice reconstituted with CD4þCD45RBhigh T cells. Eur. J. Immunol. 31, 1465–1474. Seibert, C., Cadene, M., Sanfiz, A., Chait, B. T., and Sakmar, T. P. (2002). Tyrosine sulfation of CCR5 N-terminal peptide by tyrosylprotein sulfotransferases 1 and 2 follows a discrete pattern and temporal sequence. Proc. Natl. Acad. Sci. USA 99, 11031–11036. Seibert, C., Veldkamp, C. T., Peterson, F. C., Chait, B. T., Volkman, B. F., and Sakmar, T. P. (2008). Sequential tyrosine sulfation of CXCR4 by tyrosylprotein sulfotransferases. Biochemistry 47, 11251–11262. Shan, L., Qiao, X., Oldham, E., Catron, D., Kaminski, H., Lundell, D., Zlotnik, A., Gustafson, E., and Hedrick, J. A. (2000). Identification of viral macrophage inflammatory protein (vMIP)-II as a ligand for GPR5/XCR1. Biochem. Biophys. Res. Commun. 268, 938–941. Stuart, A. C., Borzilleri, K. A., Withka, J. M., and Palmer, A. G., 3rd., (1999). Compensating for variations in 1H-13C scalar coupling constants in isotope-filtered NMR experiments. J. Am. Chem. Soc. 121, 5346–5347. Tikhonov, I., Kitabwalla, M., Wallace, M., Malkovsky, M., Volkman, B., and Pauza, C. D. (2001). Staphylococcal superantigens induce lymphotactin production by human CD4þ and CD8þ T cells. Cytokine 16, 73–78. Tollinger, M., Skrynnikov, N. R., Mulder, F. A., Forman-Kay, J. D., and Kay, L. E. (2001). Slow dynamics in folded and unfolded states of an SH3 domain. J. Am. Chem. Soc. 123, 11341–11352. Tuinstra, R. L., Peterson, F. C., Elgin, E. S., Pelzek, A. J., and Volkman, B. F. (2007). An engineered second disulfide bond restricts lymphotactin/XCL1 to a chemokine-like conformation with XCR1 agonist activity. Biochemistry 46, 2564–2573. Tuinstra, R. L., Peterson, F. C., Kutlesa, S., Elgin, E. S., Kron, M. A., and Volkman, B. F. (2008). Interconversion between two unrelated protein folds in the lymphotactin native state. Proc. Natl. Acad. Sci. USA 105, 5057–5062. Veldkamp, C. T., Peterson, F. C., Hayes, P. L., Mattmiller, J. E., Haugner, J. C., 3rd., de la Cruz, N., and Volkman, B. F. (2007). On-column refolding of recombinant chemokines for NMR studies and biological assays. Protein Expr. Purif. 52, 202–209. Veldkamp, C. T., Seibert, C., Peterson, F. C., De la Cruz, N. B., Haugner, J. C., 3rd., Basnet, H., Sakmar, T. P., and Volkman, B. F. (2008). Structural basis of CXCR4 sulfotyrosine recognition by the chemokine SDF-1/CXCL12. Sci. Signal. 1, ra4. Veldkamp, C. T., Seibert, C., Peterson, F. C., Sakmar, T. P., and Volkman, B. F. (2006). Recognition of a CXCR4 sulfotyrosine by the chemokine stromal cell-derived factor1alpha (SDF-1alpha/CXCL12). J. Mol. Biol. 359, 1400–1409. Wang, J. D., Nonomura, N., Takahara, S., Li, B. S., Azuma, H., Ichimaru, N., Kokado, Y., Matsumiya, K., Miki, T., Suzuki, S., and Okuyama, A. (1998). Lymphotactin: A key regulator of lymphocyte trafficking during acute graft rejection. Immunology 95, 56–61. Yoshida, T., Imai, T., Kakizaki, M., Nishimura, M., Takagi, S., and Yoshie, O. (1998). Identification of single C motif-1/lymphotactin receptor XCR1. J. Biol. Chem. 273, 16551–16554.

C H A P T E R

F O U R

Interactions of Chemokines with Glycosaminoglycans Damon J. Hamel,* India Sielaff,† Amanda E. I. Proudfoot,† and Tracy M. Handel* Contents 1. Introduction 2. Methods to Detect, Quantify, and Characterize Chemokine: Gag Interactions 2.1. Biochemical and in vivo methods 2.2. In vivo cellular recruitment 3. Biophysical Methods 3.1. Isothermal fluorescence titration 3.2. Surface plasmon resonance (SPR) 3.3. Sedimentation equilibrium analytical ultracentrifugation 3.4. NMR: Heteronuclear single quantum correlation (HSQC) spectroscopy 3.5. Fourier-transform ion cyclotron resonance mass spectrometry (FT-ICR MS) 3.6. Mass spectrometry methods for characterizing GAG-binding epitopes on chemokines: Proteolytic footprinting 3.7. Emerging mass spectrometry methods for characterizing protein:GAG interactions: Hydrogen deuterium exchange and radiolytic oxidation 4. Summary Acknowledgments References

72 80 80 85 87 87 88 90 91 93 95

96 97 98 98

Abstract Many proteins require interactions with cell surface glycosaminoglycans (GAGs) to exert their biologic activity. The effect of GAG binding on protein function ranges from essential roles in development, organogenesis, cell growth,

* {

Skaggs School of Pharmacy and Pharmaceutical Science, University of California, San Diego, La Jolla, California, USA Merck Serono Geneva Research Centre, Geneva, Switzerland

Methods in Enzymology, Volume 461 ISSN 0076-6879, DOI: 10.1016/S0076-6879(09)05404-4

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2009 Elsevier Inc. All rights reserved.

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cell adhesion, inflammation, tumorigenesis, and interactions with pathogens. A classic example is the role of GAGs in the interaction of fibroblast growth factors with their receptors, where GAGs play a role in specificity determination and control of receptor-ligand engagement. The other well-studied example involves the binding of antithrombin to heparin/heparan sulfate, which results in the inactivation of the coagulation cascade. In view of their specialized activity in cellular recruitment, chemokines interact with GAGs, minimally as a mechanism for localization of chemokines to specific anatomical spaces enabling them to act as directional signals for migrating cells. The biological relevance of these interactions has been recently demonstrated by functional characterization of mutants that are deficient in GAG binding. These mutants bind receptor normally in vitro but are unable to recruit cells in vivo. Observations like this have motivated investigations to identify GAG-binding epitopes on chemokines, the specificity and affinity of chemokines for different GAGs, the oligomerization of chemokines on GAGs, and the efficacy of GAG-binding mutants in the context of in vivo cell recruitment and animal models of disease. To this end, several techniques have been developed to measure the interactions of chemokines with GAGs. In this chapter we describe these various assays with particular reference to those that have been used to assess the binding of chemokines to GAGs and to define their epitopes. In the end, we believe both in vitro and in vivo characterization are absolutely necessary for understanding these interactions and their biologic relevance in the context of the whole organism.

1. Introduction In the past several years, it has become increasingly apparent that to function properly, chemokines require interaction not only with G protein– coupled receptors (GPCRs) but also with the carbohydrate moieties (glycosaminoglycans or GAGs) of proteoglycans on endothelial cells and the extracellular matrix (Handel et al., 2005; Johnson et al., 2005). The biological relevance of GAG interactions was first convincingly demonstrated with engineered variants of chemokines (RANTES/CCL5, MCP-1/CCL2, and MIP1b/CCL4) that had mutations which inhibited their ability to bind to heparin, yet minimally perturbed their ability to bind to their respective receptors and promote cell migration in vitro. Nevertheless, these mutants were ineffective in inducing cell migration in vivo, in contrast to their WT counterparts, demonstrating the importance of the GAG interaction (Proudfoot et al., 2003). Since these studies, related experiments with GAG-binding mutants of MCP-3/CCL7 (Ali et al., 2005) and Lymphotactin/XCL1 (Peterson et al., 2004) have also demonstrated the requirement of GAG interactions for chemokine-induced cell migration in vivo. Minimally, these interactions are thought to provide a mechanism for the localization

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and concentration of chemokines on cell surfaces, which in turn provides guidance cues for migrating cells; in the absence of such interactions, rapid diffusion of chemokines would occur, especially in the presence of blood flow, dissipating directional gradients and resulting in chemokine concentrations below the threshold required to activate their receptors. The importance of these interactions has been further underscored by the ability of GAG-binding mutants of chemokines to block the action of wild type chemokines both in normal and pathological states. For example, [44AANA47]-RANTES, a GAG-binding mutant of CCL5/RANTES, was shown to be a dominant negative inhibitor of cell recruitment by the WT protein, both by preventing higher order oligomerization and by forming nonfunctional heterodimers with WT RANTES wherein only some of the subunits in the hetero-oligomer have intact GAG epitopes ( Johnson et al., 2004). This same mutant also attenuated atherosclerotic plaque formation in LDLr
/
mice by inhibiting leukocyte recruitment into plaques, producing a less inflammatory and more stable plaque phenotype (Braunersreuther et al., 2008). A GAG-binding mutant of MCP-3/CCL7 similarly has been shown to inhibit chemokine-mediated recruitment in murine air pouches and to inhibit the chemotactic activity of synovial fluid from patients with rheumatoid arthritis (Ali et al., 2005). Studies of viral mechanisms of immunomodulation also underscore the importance of GAG interactions. Many viruses produce chemokine-binding proteins (CBPs) that inhibit the activity of chemokines; for example, the murine poxvirus pathogen, ectromelia virus E163, secretes a 31-kDa glycoprotein that selectively binds a number of CC and CXC chemokines with high affinity, and in the case of SDF-1a/CXCL12 and IP-10/CXCL10, functions by blocking their GAG-binding epitopes (Ruiz-Arguello et al., 2008). Advantageously, E163 also binds directly to GAGs with high affinity, allowing it to remain in the vicinity of sites of viral infection, ready to interfere with the function of locally secreted chemokines. Other promiscuous CBPs include T7 from the myxoma rabbit poxvirus, which blocks GAG interactions of chemokines from the CXC, CC, and C families (Lalani et al., 1997), whereas M3 is a murine herpesvirus CBP that binds and inactivates chemokines from all four families (van Berkel et al., 2000). M3 is particularly effective in neutralizing chemokine function; in the case of the CC chemokine, MCP-1/CCL2, it blocks the GAG-binding epitopes and the receptorbinding epitopes of the chemokine and interferes with the ability of CCL2 to oligomerize (Alexander et al., 2002) (another functionally important interaction of chemokines described later and in Chapter 2). More details of virally encoded chemokine-binding proteins and methods for their study are given in Chapters 9 and 10 in volume 460. The interaction of chemokines with GAGs is unsurprising from a structural point of view, because almost all chemokines are highly basic proteins with many Arg, Lys, and His residues on their surfaces, whereas

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GAGs are acidic, sulfated linear polysaccharides that typically bind proteins rich in these amino acids. Interestingly, the two chemokines that are acidic, MIP-1a/CCL3 and MIP-1b/CCL4, both bind GAGs, albeit less strongly than basic chemokines. Linear epitopes for GAG binding have been defined on chemokine surfaces such as XBBXBX and XBBBXXBX motifs (where B represents a basic amino acid), suggesting common features of proteinGAG recognition; however, chemokines are known to oligomerize on GAGs, thereby spatially diversifying the nature of the binding epitopes (Handel et al., 2005). Figure 4.1 shows the distribution and diversity of GAG-binding epitopes on the surfaces of dimeric structures of several chemokines. Adding to the complexity, Fig. 4.2 shows the distribution of GAG-binding epitopes on three different tetrameric forms of a single chemokine, IP-10/CXCL10, which may allow this chemokine to Chemokine

GAG-binding

Residues

MCP-1/CCL2

R18, K19, R24, K49, K58, H66

MIP-1a /CCL3

R18, K45, R46, K48

Rantes/CCL5

R44, K45, R47

SDF-1a/CXCL12

K24, H25, K27, R41, K43

IL-8/CXCL8

K20, R60, K64, K67, R68

Lymphotactin/XCL1

R23, R43

Figure 4.1 Illustration of GAG-binding epitopes of chemokines defined by mutagenesis coupled with many of the assays outlined in this chapter. This figure shows surface topology models of chemokine homodimers. The GAG-binding epitopes, as defined by mutagenesis, are shown in black and listed on the right. They are taken from the following references: MCP-1/CCL2) (Hemmerich et al., 1999; Jarnagin et al., 1999), MIP-1a/CCL3 (Koopmann and Krangel, 1997), RANTES/CCL5 (Proudfoot et al., 2001), SDF-1/CXCL12 (Amara et al., 1999; Sadir et al., 2001), 1L-8/CXCL8 (Kuschert et al., 1998), and Lymphotactin/XCL1 (Peterson et al., 2004). Images were generated with PyMol.

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Figure 4.2 Different tetrameric structures of IP-10/CXCL10 have been solved and are suggested to be associated with differential GAG binding. Left, Human IP-10 M form with MCP-1/PF4 like quaternary structure. Middle, Human IP-10 H form. Right, Murine IP-10. The top row contains backbone traces plus the secondary structure of each form. The middle row contains a surface representation in the same orientation as the top row, with GAG-binding epitopes in black. The bottom row has been rotated 180 about the X-axis. PDB entries are listed below the name of each tetrameric form. Images were generated with PyMol.

selectively interact with different types of GAGs. This variability in the nature of the binding sites suggests that in addition to providing mechanisms for localization of chemokines, the GAG interaction may add to the specificity of chemokine function (Handel et al., 2005; Hoogewerf et al., 1997; Johnson et al., 2005; Webb et al., 1993). For example, although many chemokines bind and activate the same receptor, GAG interactions may selectively recruit specific chemokines to cell surfaces and tissues to fine tune the immune response. Indeed, cells can alter their GAG coats in the context of pathological states like cancer, possibly to selectively recruit certain chemokines, cytokines, and growth factors to modulate phenotype (Sasisekharan et al., 2002). The biologic importance of chemokine-GAG interactions and the discovery that GAG-deficient chemokines can have therapeutic potential has motivated many studies to define the GAG-binding epitopes on chemokines and to characterize the structure, affinity, and specificity of these interactions. However, these studies are technically challenging for many reasons. Unlike proteins or nucleic acids, which are fairly homogeneous, GAGs are exceptionally heterogeneous polymers with respect to both length and composition. Considering composition alone, it has been

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suggested that more than 12 billion sequences are possible for an oligosaccharide of six disaccharide units, representing 100 times the variation of a hexapeptide and 2 million times that of a nucleic acid hexamer (Shriver et al., 2002). This diversity derives from the nontemplate nature of GAGs and the fact that the GAG biosynthetic reactions do not always proceed to completion. These same characteristics also make them difficult to produce recombinantly and to characterize them analytically and structurally compared with nucleic acids and proteins. The six major classes of GAGs include heparin, heparan sulfate (HS), chondroitin sulfate (CS), dermatan sulfate (DS), keratin sulfate (KS), and hyaluronic acid (HA). However, most studies use heparin as a model system (and to a lesser extent heparan sulfate), because it is more easily obtained and cheaper than other GAGs. As an interesting side note, heparin is more highly sulfated than heparan sulfate, the most abundant GAG expressed on virtually every cell in the body. Heparin (and HA) are also soluble GAGs, whereas HS, DS, KS, and CS are usually covalently attached to a protein core, forming an overall structure referred to as proteoglycan. Traditional dogma suggests that the GAG chains are the functional ligand-binding units of proteoglycans. However, there is emerging evidence that the core proteins can also impact ligand binding through interactions that are both direct and indirect (i.e., the spacing of the GAG chains on the protein) (Herndon et al., 1999). Thus the use of ‘‘model reagents’’ is a major caveat of studies of chemokine-GAG interactions and may be limiting the ability of investigators to truly get at issues of specificity and binding affinity for example. Nevertheless, the use of heparin as a representative GAG has been quite successful in defining GAG-binding epitopes on chemokines (Ali et al., 2005; Amara et al., 1999; Campanella et al., 2003; Koopmann et al., 1999; Koopmann and Krangel, 1997; Lau et al., 2004b; Peterson et al., 2004; Proudfoot et al., 2001). Bearing in mind that the use of heparin is not always optimal, in this chapter, we describe many of the assays and techniques that have been used to characterize chemokine-GAG interactions, along with their advantages and disadvantages (Table 4.1). These include both biochemical and biophysical methods. With respect to the biochemical assays, in our experience, it seems that some assays are better than others for rank ordering GAG-binding hotspots and determining chemokine:GAG affinities, and where appropriate we comment on this and offer plausible explanations for discrepancies. In general, we have found that the use of several assays in combination is best for obtaining consensus results, with the ultimate test of biologic relevance being the use of in vivo cell migration experiments to evaluate carefully designed GAG-binding–deficient mutants compared with WT chemokines. The biophysical assays, described in the second section, are generally more demanding and require sophisticated equipment and expertise. However, these methods, and extensions not included here,

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Table 4.1 Summary of various methods described in this chapter to study chemokine: GAG interactions, listing advantages and disadvantagesa Method

Advantages

Disadvantages

Heparin affinity chromatography

Rapid and easy; little protein required

Equilibrium competition binding

Fast and very reliable; IC50 and Kd determinations are feasible; can be used to determine binding epitopes on chemokines; competitors can be chemokines or GAGs; one can observe GAGinduced oligomerization Fast and simple; not biased toward charged amino acids for identification of GAG-binding epitopes on chemokines in contrast to the heparin affinity assay Easy; little protein required; no specialized equipment needed; can customize binding surface with GAG of interest so the assay is not limited to heparin

True affinities are not measured; results are biased toward identifying charged amino acids as binding epitopes Requires radioactively labeled chemokine

Tritiated heparin binding assay

Enzyme-linked immunosorbent saturation binding assay

Requires radioactively labeled GAGs; less reliable than other assays like equilibrium competition

Provides relative affinities rather than true affinities

(continued)

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Table 4.1 (continued) Method

Advantages

Disadvantages

In vivo cellular recruitment

Provides the only assay of biologic relevance in vivo; can be used to prioritize the importance of GAGbinding epitopes; can be used to test chemokine or GAGbased inhibitors in competition studies Easy and no labeled material is required; good for relative ranking of chemokine mutants

Minimal quantitative data

Isothermal fluorescence titration

Surface plasmon resonance (SPR)

Sedimentation equilibrium analytical ultracentrifugation

Can get kinetic rates of association and disassociation in addition to equilibrium constants; can get information on oligomerization; in principle, one can customize the sensor chip with the GAG of interest Provides information on stoichiometries, equilibrium constants; can discriminate quite well between different models of chemokine:GAG interaction

Consumes a fair amount of protein; Kd’s are apparent because of oligomerization; chemokine:GAG aggregation can be problematic Experimental execution and data analysis can be quite complicated; expertise required

Experimental execution and especially data analysis can be complicated; a common problem with chemokine: GAG complexes is time-dependent aggregation

x

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Table 4.1 (continued) Method

Advantages

Disadvantages

Heteronuclear single quantum correlation (HSQC) spectroscopy

Provides amino acid resolution information on GAG-binding epitopes on chemokines.

Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS)

A very powerful and emerging technique for studies of chemokine:GAG complexes; it is possible to detect many different complexes in terms of stoichiometries and compositions caused by the mass accuracy of the technique; can be used to select highaffinity GAGs and determine their composition A powerful method to relatively quickly identify GAG binding epitopes on chemokines; little protein is required

Limited to studies with size and compositionally defined GAGs caused by NMR issues with heterogeneity; with longer GAGs, solubility can be problematic Not quantitative; requires very expensive equipment and significant expertise

Proteolytic footprinting coupled with mass spectrometry

a

Low resolution unless effort is taken to use multiple proteases; expensive equipment and expertise is required

All methods suffer from reagent limitations resulting in the fact that most studies use heparin. Radiolytic oxidation and HDMS are not included in the table because they have not yet been used to characterize chemokine: GAG interactions.

particularly involving mass spectrometry, represent important future directions for the chemokine:GAG field. Indeed, a burning issue is to understand how much specificity is really encoded by chemokine:GAG interactions. For this we must be able to identify and isolate or synthesize high-affinity ligands from complex GAG mixtures so that we can move beyond studies with heparin.

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2. Methods to Detect, Quantify, and Characterize Chemokine: Gag Interactions 2.1. Biochemical and in vivo methods 2.1.1. Heparin affinity chromatography A commonly used method to determine the relative ‘‘affinity’’ of chemokines for GAGs is to determine the amount of salt needed for elution of the chemokine from a heparin sepharose column. For example, a comparison of several chemokines showed the following rank order of affinities for heparin Sepharose: RANTES/CCL5 > I-TAC/CXCL11 > SDF-1/CXCL12 > IL-8/CXCL8 > MCP-1/CCL2 > MIP-1a/CCL3 > MIP-1b/CCL4 (Handel et al., 2005). To determine the contribution of specific residues of a given chemokine to its GAG-binding epitope, the salt concentration required for elution of alanine point mutants are compared with that of the WT protein, yielding per residue values for D[NaCl]H. Often, these measurements are done in parallel with determining the amount of salt required to elute mutants from a nonspecific S-sepharose column (D[NaCl]S) and compared with the elution from the heparin sepharose column. This provides a measure of the specificity of the protein-heparin interaction by accounting for nonspecific electrostatics. The specificity index is related to DDNaCl as calculated from the formula that follows, where the superscripts H and S refer to elution from heparin sepharose or S-sepharose column, respectively (Kuschert et al., 1998; Lau et al., 2004a,b).

DD½NaCl ¼ D½NaClH
D½NaClS where D[NaCl]H ¼ D[NaCl]H WT
D [NaCl]H mutant and D[NaCl]S ¼ DNaCl]S WT
D[NaCl]S mutant For example, in the preceding rank order for binding to heparin sepharose, although RANTES required the highest concentration of NaCl for elution, the order when bound to S-sepharose was I-TAC/CXCL11 > SDF-1/CXCL12 > RANTES/CCL5 > IL-8/CXCL8 > MCP-1/CCL2 > MIP-1a/CCL3 > MIP-1b/CCL4, placing RANTES in third place. However, when converted to the specificity index, the results indicate the highest specificity of RANTES for this GAG (Handel et al., 2005). An advantage of the heparin affinity chromatography method is that it is fast, inexpensive and uses relatively small amounts of protein. However, it is not a true measure of affinity. Because salt is used for elution, the method is primarily useful for identifying amino acids involved in electrostatic interactions (although the electrostatic component is accounted for, at least in part, by determining the specificity index for a given amino acid). Nevertheless, this approach has been successfully used to characterize the

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GAG-binding epitopes of several chemokines including CXCL8 (Kuschert et al., 1998), CCL2, (Lau et al., 2004b), CCL5 (Proudfoot et al., 2001), and MIP-1a (Koopmann and Krangel, 1997), and when compared with other methods such as heparin competition binding (described later), it seems to give consistent results (Lau et al., 2004b). This method could be adapted to characterizing interactions with other GAGs besides heparin, although such columns are not commercially available at the present time. 2.1.2.1. Materials and methods This assay only requires a chromatography system, a conductivity meter, heparin sepharose and cation exchange columns, recombinant chemokine, and standard laboratory buffers. The amount of chemokine depends on the detection limit of UV absorbance at 280 nm, but reliable results are obtained with 50 to 100 mg on a standard FPLC system. The amounts of protein can be reduced if detection is conducted at 214 nm. The protein is applied to the heparin sepharose column, previously equilibrated in the buffer of choice (typically 50 mM TRIS/HCl, pH 7.5), and eluted with a linear gradient of 0 to 2 M NaCl in the same buffer. The salt concentration at which the protein elutes is measured with a conductivity meter. An equivalent amount of chemokine is treated under the same conditions with a cation exchange column. The amount of salt needed for elution of protein from both columns is compared, and the difference is the heparin specificity index as defined in the previous equations.

2.1.3. Equilibrium competition binding To determine more accurate affinities of chemokines for GAGs compared with the heparin affinity chromatography assay, classical equilibrium competition–binding assays can be used. These assays also use an immobilized heparin format. Heparin sepharose beads are incubated with the radioactively labeled chemokine of interest and are competed off with increasing concentrations of the GAG (Kuschert et al., 1999). Alternately, it is also possible to use unlabeled chemokine instead of GAG as the competitor. In both cases, one would expect to observe that addition of competitor would simply compete off the radiolabeled chemokine, and this is exactly what is observed with GAG as competitor. However, such assays with chemokines as competitors often cause the recruitment of additional radiolabeled chemokine onto the immobilized heparin because of oligomerization of chemokines on GAGs (Hoogewerf et al., 1997) as shown in Fig. 4.3 (Handel et al., 2008). This assay, therefore, serves not only as a good method for determining binding affinities of different chemokines for heparin and the relative ability of different types of GAGs to compete for chemokine binding to heparin, but it is also an excellent qualitative screen of GAG-induced chemokine oligomerization.

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% Hot ligand bound

200

150

100

50

0 −12

−11

−10

−9

−8

−7

−6

−5

−4

Log [cold ligand]

Figure 4.3 Equilibrium competition binding of MCP-1/CCL2 (open circles) and a nonoligomerizing variant [P8A]-MCP-1 (closed circles) on immobilized heparin. 125Ilabeded MCP-1 was incubated with heparin Sepharose beads, and unlabeled MCP-1 or [P8A]-MCP-1 was added. The increase in bound 125I- labeled MCP-1 on addition of WT MCP-1 is diagnostic of oligomerization, whereas only competitive inhibition is observed with [P8A]-MCP-1. Reprinted with permission from: ‘‘Journal of Leukocyte Biology, 2008 84:1101–8; An engineered monomer of CCL2 has anti-inflammatory properties emphasizing the importance of oligomerization for chemokine activity in vivo; Handel, T. M., Johnson, Z., Rodrigues, D. H., Dos Santos, A. C., Cirillo, R., Muzio, V., Riva, S., Mack, M., De´ruaz, M., Borlat, F., Vitte, P. A., Wells, T. N., Teixeira, M. M., Proudfoot, A. E.’’

A disadvantage of this method is the use of radioactively labeled material, which is expensive and needs a specifically designated working space. However, the method is fast and quite reliable and is, therefore, a frequently used strategy. For example, it was used to define the GAG binding site of RANTES (Proudfoot et al., 2001) and then to demonstrate that interference with heparin binding and with oligomerization presents a novel anti-inflammatory strategy ( Johnson et al., 2004). This method has also been used to demonstrate the presence of an unusually high affinity GAG-binding site for I-TAC/CXCL11 (Sielaff et al., 2009). Overall, we find that the equilibrium competition–binding assay is a straightforward and useful assay for characterizing chemokine:GAG interactions for many applications. 2.1.3.1. Materials and methods This assay requires laboratory equipment routinely used for equilibrium competition–binding assays with iodinated tracers such as a shaker to accommodate 96-well plates, a vacuum filtration apparatus for 96-well plates, and a Microbeta Scintillation Counter for 96-well plates. Required reagents include 125I-labeled chemokine, heparin-sepharose beads, 96-well filter plates, nonprotein adsorbing 96-well plates, the desired competitors such as soluble GAGs or unlabeled chemokine, and standard laboratory buffers.

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A dilution series of competitor (unlabeled chemokine or GAG) is prepared in binding buffer (50 mM TRIS, pH 7.5, 1 mM CaCl2, 5 mM MgCl2, 0.5% BSA), ideally in threefold dilutions spanning 4 to 5 orders of magnitude to achieve 12 data measurements in a nonprotein binding 96-well plate; 25 ml of the dilutions is transferred to a filter plate in triplicate (NB: if RANTES/CCL5 is used in the assay, the binding buffer must be supplemented with 0.15 M NaCl to prevent oligomerization). To achieve a final assay volume of 100 ml, 25 ml of binding buffer is added to each well. The iodinated chemokines are generally obtained with a specific activity of 2000 Ci/mmol. We recommend reconstituting them in 500 ml of water to obtain a 23 nM stock, which is diluted in binding buffer to 0.4 nM so that the addition of 25 ml of the solution to each well of the filter plate results in a final concentration of 0.1 nM radiolabeled chemokine. 1 g of heparin sepharose beads is rehydrated in 10 ml of water and left at room temperature for 60 min. The beads are then diluted 400-fold with binding buffer and 25 ml is added to each well. The plates are then incubated for 4 h at room temperature. To remove unbound ligand, the plates are washed three times with 200 ml wash buffer (binding buffer supplemented with 0.15 M NaCl or 0.5 M NaCl in the case of RANTES/CCL5) in a 96-well plate filter device. After the addition of 50 ml of scintillation liquid per well, the radioactivity is determined with a calibrated Microbeta Scintillation Counter (Perkin Elmer). 2.1.4. Tritiated heparin binding assay The tritiated heparin assay is a commonly used biochemical assay that measures the binding of the protein of interest to soluble tritiated heparin. The radioactive heparin is incubated with increasing concentrations of protein in 96-well plates fitted with protein binding cellulose phosphate paper. The wells are washed to remove unbound GAG and the amount of radioactivity retained in the filter is determined. Compared with the heparin affinity chromatography assay, which only accounts for the electrostatic interactions, this assay has the advantage that it reflects the overall binding capacity for heparin of a protein or protein mutant. This method is often used in conjunction with alternative methods to obtain a more complete profile of protein-GAG interactions, for example for the identification of the GAG binding site of MCP-1/CCL2 (Lau et al., 2004b) or for the determination of GAG binding to monomeric chemokine variants (Proudfoot et al., 2003). However, large amounts of protein are required for the assay, and the results can be somewhat variable. Furthermore, inconsistencies compared with the heparin sepharose affinity assay and an isothermal fluorescence titration assay (described later) have been observed (Lau et al., 2004b) that may reflect the varying efficiencies of different protein mutants to bind to the filter.

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2.1.4.1. Materials and methods The assay requires a Microbeta Scintillation Counter (Perkin Elmer), a shaker, and a vacuum filtration system to accommodate 96-well plates. The required reagents include the sodium salt of 3H-heparin, recombinant chemokines, nonprotein adsorbing 96-well plates, protein-adsorbing P-81 Whatman 96-well filter plates, scintillation liquid, and phosphate-buffered saline (PBS). A dilution series of the unlabeled chemokines is prepared in PBS in a nonprotein adsorbing 96-well plate in triplicate, spanning 4 to 5 orders of magnitude. Each well should contain the same volume, ideally 50 ml; 50 ml of 3H-heparin solution in PBS is then added to each well. 3H-heparin sodium salt is supplied by Perkin Elmer at a specific activity of 0.2 to 1.0 mCi/mg in aliquots of 1 mCi. This amount is dissolved in 500 ml H2O and subsequently diluted 1:600 in PBS for use in the assay. The plate is then incubated at 37  C for 1 h. After incubation, 20 ml from each well is transferred into the corresponding wells of a P-81 Whatman filter plate. The filter plate is washed three times with PBS with a vacuum system, and 50 ml of scintillation fluid is added per well. The radioactivity is then determined with a calibrated Microbeta Scintillation Counter.

2.1.5. Enzyme-linked immunosorbent saturation binding assay A more recently developed assay is the saturation binding assay with EpranEx plates. The plates have a special coating that binds heparin or other GAGs such as heparin sulfate (HS). Because of the inability of heparin to adhere to the surface of conventional polystyrene microplates, the development of high-throughput ELISA-like assays that use surface immobilized heparin had previously been hampered. The Plasso EpranExTM plate provides a surface onto which heparin can be immobilized, and the immobilized heparin is then capable of capturing heparin-binding proteins. The principle of this assay is similar to an ELISA. The GAG solution is incubated overnight in the plate and, after a wash step, the protein of interest is added. Detection of binding is achieved with a primary antibody to the protein and a secondary antibody labeled with horseradish peroxidase (HRP), or with a biotinylated primary antibody, followed by ExtrAvidin detection. The assay uses relatively small amounts of protein and GAGs, it is easy to perform, and no specialized equipment is required. It has been increasingly reported in the recent literature, for example, to demonstrate the selectivity of Eotaxin/CCL11 for heparin over other GAGs (Ellyard et al., 2007) and the reduced affinity toward GAGs of citrullinated IL-8/CXCL8 (Proost et al., 2008). A significant advantage of this assay is the ability to investigate interactions with different types of GAGs because of the ability to prepare custom-coated plates. Furthermore, it is amenable to inhibition studies with soluble GAGs as competitor. The assay allows determinations of relative affinities, for example, to study chemokine mutants to identify the GAG

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binding site. Although KD determinations are possible in principle, the exact amount of immobilized GAG, presented in the correct active orientation, cannot be determined. 2.1.5.1. Materials and methods This assay requires standard laboratory equipment, namely a microplate reader and a shaker to accommodate 96-well plates. The necessary reagents are: EpranEx plates (Plasso, Sheffield, UK), GAG (e.g., heparin, recombinant chemokines, a biotinylated primary antibody, ExtrAvidin solution [Sigma]), and NaCl, NaOAc, Tween 20, gelatin, and nonprotein binding 96-well plates. For the coating of the EpranEx plate with GAG, 200 ml of a 25 mg/ml heparin (or other GAG) solution in PBS is added to each well, and the plate is then incubated overnight at room temperature in the dark. The liquid is then discarded and the plate washed three times with standard assay buffer (SAB, 100 mM NaCl, 50 mM NaOAc, 0.2 % (v/v) Tween 20; pH7.2); 250 ml of blocking solution (0.2 % [w/v] gelatin in SAB) is then added to each well, the plate is incubated for 1 h at room temperature and then washed three times with SAB as before. A dilution series of chemokine in SAB, spanning 4 to 5 orders of magnitude, is prepared in a nonprotein binding 96-well plate; 100 ml of the dilution series is transferred in triplicate to the EpranEx plate, and the plate is incubated for 2 h at room temperature. The wells are then washed three times with SAB. To detect the amount of bound chemokine, 200 ml of an antibody in blocking solution is added to each well (diluted according to instructions for ELISA). The plate is incubated for 1 h and washed three times with SAB; 200 ml of ExtrAvidin-AP in blocking solution (1:10,000) is added to each well, the plate is incubated for 30 min at room temperature, and washed three times with SAB; 200 ml of developing reagent is added per well, the plate is incubated for 40 min at room temperature, and the absorbance is measured at 405 nm in a microplate reader. As an alternative to the ExtrAvidin solution, streptavidin-conjugated horseradish peroxidase may be used for detection (Kadi et al., 2006). Furthermore, it is possible to use this assay for competition experiments using a dilution series of competitor, such as heparin or other GAGs, and a constant amount of chemokine.

2.2. In vivo cellular recruitment Use of the preceding biochemical assays with mutants of chemokines has allowed the identification of potential GAG-binding epitopes on the chemokines. However, none of these assays prove whether GAG binding or the identified GAG-binding epitopes are biologically relevant. Thus a common strategy has been to couple the in vitro assays with in vivo assays.

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Chemokines have been used to induce cellular recruitment into different cavities in vivo: an artificially created air pouch (Ramos et al., 2003), the pleural cavity (Pinho et al., 2007), or the joint (Deruaz et al., 2008). We have used a fairly simple approach involving a chemokine-induced peritoneal cellular recruitment assay (Proudfoot et al., 2003). Although the details may vary with chemokine, a typical procedure involves the following: (1) inject chemokine or saline control into the peritoneal cavity of mice, (2) sacrifice mice after a few to several hours, and (3) lavage the cavity and count the number of recruited cells. Parameters to optimize include the duration between injecting and sacrificing the mice, the amount of chemokine, and whether the mice are presensitized (Sielaff et al., 2009). One can also coinject GAG-mutants with wild-type chemokine; this approach has revealed that a GAG mutant of RANTES acts as a dominant negative inhibitor of cell recruitment of the WT protein ( Johnson et al., 2004). In addition, GAGs themselves can be used as competitors, and such experiments provide additional information on GAG specificity (Ellyard et al., 2007). These experiments have the advantage over in vitro experiments in that they provide a readout of biological relevance and can be used to rank order the importance of different chemokine epitopes on GAG binding, as long as mutation of the epitopes do not, or minimally affect, receptor binding. Otherwise, impaired cell migration in response to GAG-binding mutants may be due to effects on GAG binding, receptor binding, or both. A significant disadvantage of in vivo assays is the requirement for large amounts of chemokine, and thus the ability to produce recombinant protein is advised over use of commercially available material. Other in vivo assays have been used to address the relevance of GAG binding such as the murine air pouch assay (Ali et al., 2005; Das et al., 1998; Ellyard et al., 2007). For example, Ali and coworkers used this assay to demonstrate that a GAGbinding mutant of MCP-3/CCL7 could inhibit migration not only to WT CCL3, but also to a receptor sharing chemokine, RANTES/CCL5, and the nonreceptor sharing chemokine, SDF-1/CXCL12 (Ali et al., 2005). 2.2.1. Materials and methods We describe here the method for chemokine-induced peritoneal recruitment. For this assay recombinant chemokines are required, and we have used 8- to 12-week-old female Balb/c mice. 0.1 to 100 mg of chemokine or mutant diluted in 0.2 ml of sterile, lipopolysaccharide-free 0.9% NaCl solution is injected i. p. If used in the experiment, antagonists are administered either i.v. or s.c. The mice are sacrificed after 4 to 18 h by CO2 asphyxiation, depending on the choice of chemokine stimulant. The peritoneal cavity is washed three times with 5 ml PBS, and the washes are pooled. The resulting solution of peritoneal cells is centrifuged at 1500 rpm for 5 min and the cells are resuspended in 1 ml of PBS and counted.

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3. Biophysical Methods This section describes biophysical approaches for characterizing chemokine: GAG interactions. Because several of these methods are technically involved and require more optimization and expertise than the biochemical assays described previously, protocols are not provided for some of these techniques. However, references are provided as guides.

3.1. Isothermal fluorescence titration The simplest of the biophysical methods for characterizing chemokine: GAG interactions is the isothermal fluorescence titration assay (Goger et al., 2002). In this assay, one monitors the change in fluorescence intensity from a Trp residue, which is highly conserved in most chemokines, on addition of GAG. If the protein of interest does not possess a Trp, one can generally replace a Phe or Tyr with a Trp, provided that the mutation does not affect biological activity (Sielaff et al., 2009). The form of the data is a binding isotherm from which an apparent binding constant can be determined as illustrated in Fig. 4.4. Comparison of different mutants in this assay allows one to define residues that contribute to the GAG-binding epitopes, the role of oligomerization on GAG-binding affinity, and the effect of different GAGs on binding affinity (Lau et al., 2004b). The assay is very straightforward, relatively rapid and reproducible, and access to the requisite fluorescence equipment is generally not an issue. This is a recommended approach for affinity measurements because of its simplicity in both execution and interpretation, with the proviso that the measurements are deemed ‘‘apparent,’’ because they can be complicated by changes in avidity caused by concentration-dependent oligomerization of the chemokine. 3.1.1. Materials and methods This assay requires a fluorescence spectrophotometer, heparin, or other GAG, recombinant chemokine, and standard laboratory buffers. The sensitivity is limited by the fluorescence emission at 340 nm, which is quenched on addition of GAG, but dissociation constants between 20 nM and 750 mM have been reported (Goger et al., 2002; Lau et al., 2004b). In previous studies of IL-8/CXCL8, different concentrations of chemokine were used to bias the chemokine to a monomeric (50 nM ) versus dimeric (700 nM) form (Goger et al., 2002), whereas in a study of MCP-1/CCL2, a 1 mM solution of chemokine in PBS was used (Lau et al., 2004b). High-concentration GAG stocks are required to minimize dilution when added to the chemokine solution, and the concentration is calculated from the average molecular weight for the GAG under study (another less

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Figure 4.4 Isothermal fluorescence titration of heparin with WT MCP-1/CCL2 compared with the monomeric variant P8A-MCP-1 and the GAG-binding deficient mutant K18A/R19A MCP-1. The data show the effect of oligomerization on GAGbinding affinity and identify a double mutant with significantly impaired ability to bind heparin. Reprinted from: ‘‘Journal of Biological Chemistry, 2004 279:22294–22305; Identification of the glycosaminoglycan binding site of the CC chemokine, MCP-1: implications for structure and function in vivo; Lau, E. K., Paavola, C. D., Johnson, Z., Gaudry, J. P., Geretti, E., Borlat, F., Kungl, A. J., Proudfoot, A. E., Handel, T. M.’’ with permission from ASBMB.

accurate parameter). The GAG solution is titrated into a fixed concentration of chemokine, and the fluorescence emission is recorded with excitation and emission wavelengths of 282 and 340 nm, respectively, and a 290-nm cutoff filter. The resulting binding isotherms are then fit by nonlinear regression to an equation describing a bimolecular (or other) association reaction, as described in Goger et al. (2002). Again, we refer to the resulting number as an apparent affinity because of the assumptions made in curve fitting to a bimolecular reaction when changes in aggregation state may occur.

3.2. Surface plasmon resonance (SPR) A powerful tool for the study of protein-protein and protein-ligand interactions is an evanescent biosensor technology referred to as surface plasmon resonance (SPR). The technology is based on an optical phenomenon that enables detection of unlabeled binding partners in real time (Schuck, 1997). Effectively, the technique depends on the refractive index of the sample within the evanescent field above the sensor surface. Adsorption or

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desorption of macromolecules at the sensor surface change the local refractive index and produce a shift in the measured resonance angle that, to a good approximation, is proportional to the surface concentration of macromolecules. Operationally, one binding partner is immobilized on a chip. A solution containing the putative binding partner is then flowed over the chip at a constant rate, and the association kinetics of the two binding partners is detected by the change in mass as a function of time. Then in a dissociation phase, buffer is used instead, and the time course of complex dissociation is monitored. In this way it is possible to determine the association/dissociation kinetics of the complex, and from these, an equilibrium dissociation constant can be calculated. This method has been used in several studies for the characterization of chemokine-GAG interactions (Alexander-Brett and Fremont, 2007; Amara et al., 1999; Kawashima et al., 2003; Vives et al., 2002). In the study by Vives et al., SPR was used to analyze the interaction between an N-terminally truncated form of CCL5/RANTES ([9 to 68]-RANTES) and heparin sulfate immobilized on the chip surface (Vives et al., 2002). Although a monomer in solution, the results demonstrated a complex binding model involving dimerization of [9 to 68]-RANTES on heparin sulfate, with positive cooperativity such that the first CCL5 molecule associated with HS with an affinity of 398 nM followed by a second CCL5 molecule with an affinity of 84 nM, even though [9 to 68]-RANTES is a monomer in solution. These results suggest that the chemokine:GAG interaction is facilitated by oligomerization and vice versa, which seems to be a characteristic of many chemokines. The immobilzation of a protein on a surface bears the risk of abolishing partly or completely its binding ability, and the immobilization chemistry must, therefore, be carefully considered. GAGs, however, are readily immobilzed on streptavidin SA sensor chips surfaces (Biacore, GE Healthcare) by biotinylation (Osmond et al., 2002). The immobilzation of GAGs on the surface should not alter their binding characteristics, because they are often attached to cell surfaces by means of proteoglycans in vivo. An advantage of the method is that small amounts of material are needed, and labeling is not required for the protein whose binding is to be detected. Furthermore, it is possible to detect the association or competition with a third binding partner. For example, SPR has been used to examine the competition of the viral chemokine decoy receptor M3 with chemokines binding to heparin (Alexander-Brett and Fremont, 2007). However, one must have access to the requisite expensive Biacore (GE Healthcare) equipment. 3.2.1. Materials and methods For this assay a Biacore instrument is needed. The reagents used are recombinant chemokines, GAGs, biotinylation reagent, streptavidin sensor chips (SA chips), HEPES-buffered saline (HBS), and glycine buffers at

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pH 2 (both from Biacore, GE healthcare) and NaCl. Note: other buffers may be recommended for certain Biacore instruments. The GAGs are biotinylated as previously described (Osmond et al., 2002), dissolved in HBS buffer at 1 to 50 mg/ml and immobilized on the streptavidin chip by flowing the solution over the chip at 10 ml/min to achieve at least 500 to 1000 RU units. The chip is then ready for binding experiments. The chemokines are dissolved at 1 mg/ml and flowed over the chip at 30 ml/ml. Regeneration of the chip is achieved by flowing glycine buffer, pH2, containing 0.5 to 1.0 M NaCl at 30 ml/min over the chip.

3.3. Sedimentation equilibrium analytical ultracentrifugation Analytical ultracentrifugation (AUC), specifically the sedimentation equilibrium technique, is a powerful method for determining the mass of a protein or protein complex in solution and can be used for characterizing associating systems, including subunit stoichiometries and equilibrium constants for the assembly process. AUC is extensively described in Chapter 2 on methods for characterizing chemokine oligomerization, and, therefore, the reader is referred to that chapter for a more detailed summary of the physical basis of the technique. A sample is subject to high centrifugal force in an analytical ultracentrifuge. One then optically measures the distribution of the protein along the radius of the sample cell at equilibrium, from which one can extract molecular mass, and for interacting systems, the dissociation constant (Balbo et al., 2007b). Protein and protein complexes with masses in the range from <103 to >106 Daltons, and associating systems characterized by KD values between 10
4 to 10
8 M
1 can be studied by AUC (Balbo et al., 2007a). Although this method has most frequently been used to characterize chemokine oligomerization and the effect of mutations (Laurence et al., 2000; Paavola et al., 1998), it can also be used to characterize the interaction of chemokines with GAGs. In the case of MCP-1/ CCL2, AUC and NMR studies have shown that this chemokine exists as a dimer in solution (Handel and Domaille, 1996). However, the addition of heparin octasaccharide very clearly induces the chemokine to form tetramers, consistent with a crystal structure form (Lau et al., 2004b; Lubkowski et al., 1997). By contrast, an engineered monomeric mutant, [P8A]-MCP-1 did not oligomerize in the presence of the GAG, even though it still bound GAG (Lau et al., 2004b). These structural properties were correlated with the ability of the WT chemokine but not the monomeric variant to induce cell migration in vivo because of the requirement of both oligomerization and GAG-binding for in vivo function (Proudfoot et al., 2003). One caveat to AUC is that it is time consuming, taking 1 to 2 days per run. Furthermore, the data can be difficult to fit, particularly when there are issues with nonequilibrium aggregation or precipitation, which often occurs in the presence of larger GAGs (hexasaccharides and larger). For example,

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the addition of heparin octasaccharide to Eotaxin/CCL11 causes the timedependent formation of large aggregates that gradually fall out of solution (Handel, unpublished data). When solubility is favorable, as for MCP-1, one must still be careful to calculate the partial specific volume of the complex, and the dissociation constants must be such that one can assume 100% binding, or a concentration series must be collected and fit. Nevertheless, for many chemokines, the relevant concentration ranges (high nanomolar to submicromolar) are generally adequate for these purposes. Fig. 4.5 shows an example of the use of AUC that revealed that CCL2 forms tetramers in the presence of an octasaccharide. It also illustrates how the goodness of the fit, reflected by the residuals, can be used to discriminate between different models of assembly. Access to the appropriate equipment, such as a Beckman Optima XL-A ultracentrifuge and associated curvefitting software, is the basic requirement for conducting these studies.

3.4. NMR: Heteronuclear single quantum correlation (HSQC) spectroscopy Heteronuclear single quantum coherence (HSQC) spectroscopy is an NMR method in which one detects 1H nuclei and their attached 13C or 15N heteronuclei. A 2-dimensional HSQC spectrum thus provides a ‘‘fingerprint’’ of the protein in the way of chemical shifts or cross peaks from 1H-15N atoms from the backbone amides and side chain NH groups 2 (in a 1H-15N HSCQ) or of the 1H-13C groups from both the backbone and side chains (1H-13C HSCQ) in a protein. Fig. 2.4A in Chapter 2 shows an example of a 1H-15N HSCQ, where each cross peak corresponds to an NH (or NH2) group from a different amino acid in the protein. The power of the use of HSQC spectra to monitor interactions of chemokines and GAGs is that the position of the cross peaks (i.e., the chemical shifts) are exquisitely sensitive to the magnetic environment, and perturbations caused by GAG binding can be readily identified by changes in chemical shift. Such changes can, therefore, provide residue specific information on the region of the protein surface where the GAG is binding. This method has been used quite frequently to monitor interactions of chemokines with small saccharides to identify binding sites on the chemokine and to identify features of the GAG, like the presence and position of sulfate groups, which are important for the interaction. For example, titrating different GAGs into IL-8/CXCL8 revealed a heparin-binding site that includes the C-terminal a-helix and a proximal loop encompassing residues 18 to 23 (Kuschert et al., 1998). Similarly, with differentially sulfated disaccharides, it was possible to show the dependence of the interaction on the composition of the GAG on binding and amino acids involved in the binding surface (McCornack et al., 2003), which agreed well with prior studies based on mutagenesis (Laurence et al., 2001).

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A limitation of this method is that one must use GAGs that have defined composition and size, and because these are generally only available for small saccharides, studies have been limited to the use of small GAGs. Compositional and size heterogeneity usually causes exchange broadening and makes the spectra uninterpretable. Longer GAGs can also cause precipitation at the concentrations (50 mM and above) used for NMR. However, because chemokines tend to prefer binding to larger GAGs as indicated by experiments with isothermal calorimetry ([Kuschert et al., 1999], another technique only mentioned here), the use of small GAGs will not capture a picture of the entire binding surface and, instead, may identify nonspecific interactions. Nevertheless, these methods are useful. Isotopically labeled protein is also required, but making labeled protein has been straightforward for chemokines. The experiments are quite easy to collect and interpret, although they require prior assignment of the spectra, which may be complicated for the nonexpert. However, many chemokine structures have already been solved by NMR, and assignments are available in the PDB that can serve as a starting point for such studies. Looking toward the future, as methods for making compositionally defined GAGs improve, these types of NMR experiments and others (Zhuang et al., 2006) will become increasingly more powerful for characterizing chemokine: GAG interactions.

3.5. Fourier-transform ion cyclotron resonance mass spectrometry (FT-ICR MS) Fourier-transform ion cyclotron resonance (FT-ICR) mass spectrometry is a useful method for studying noncovalent chemokine:GAG interactions as well as oligomerization of chemokines (Crown et al., 2006; Yu et al., 2005). As described in Chapter 2, which is focused on the oligomerization of chemokines, this method is facilitated by electrospray ionization (ESI), which enables transfer of intact noncovalent complexes from solution to the gas phase. FT-ICR has very high mass accuracy and can be used to Figure 4.5 Sedimentation equilibrium of MCP-1/CCL2 in the absence (top left) and presence (top right) of a heparin octasaccharide at a 1:1 stoichiometry. Below the data sets, a comparison is shown of residual plots for different models generated from the þoctasaccharide data set. The best fit is determined by the randomness of the distribution of residuals and by minimization of the variance. Here, the monomer-tetramer equilibrium seems to be the best model to describe the data, because the other models exhibit residuals with systematic nonrandom deviations, indicative that they are inaccurate. Reprinted from: ‘‘Journal of Biological Chemistry, 2004 279:22294–22305; Identification of the glycosaminoglycan binding site of the CC chemokine, MCP-1: implications for structure and function in vivo; Lau, E. K., Paavola, C. D., Johnson, Z., Gaudry, J. P., Geretti, E., Borlat, F., Kungl, A. J., Proudfoot, A. E., Handel, T. M.’’ with permission from ASBMB.

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determine the molecular weight of complexes, stoichiometry, etc. With FT-ICR, Crown et al. analyzed the ability of the MCP-1 ligands (MCP-1/ CCL2, MCP-2/CCL8, MCP-3/CCL7, MCP-4/CCL13) and eotaxin/ CCL11 to homo- and hetero-dimerize and the influence of GAGs on this process (Crown et al., 2006). Figure 4.6 shows an example of a spectrum of a sample containing MCP-1/CCL2 þ MCP-2/CCL8 þ the pentasaccharide Arixtra. The high mass accuracy allows easy identification of all of the species, and although exact quantitation is an issue because measurements are done in the gas phase, the intensities of the various species usually reflect the relative population in solution. In these studies, it was possible to show that interaction with GAGs typically promoted hetero-oligomerization. For example, MCP-3/CCL11 does not interact with MCP-2/CCL8 in the absence of GAG, whereas a strong heterodimer complex with one bound pentasaccharide (Arixtra) was observed when the GAG was added. In related studies it was also shown that FT-ICR MS could be used in combination with affinity purification to select and identify chemokine-binding octasaccharides from complex mixtures (Schenauer et al., 2007). Thus this method has great potential for identifying determinants of chemokine: GAG specificity and affinity focused on the composition of the GAG. FT-ICR measurements can be done quite rapidly, and the method requires very little protein and GAG. However, in addition to the previously mentioned issues with quantitation, access to the appropriate and very [CCL2 + CCL2 + arixtra]8+ [CCL2 + CCL8 +arixtra]9+ [M(CCL2)]5+ M4+/D8+(CCL2) [M(CCL8)]5+ [CCL2+ CCL8]8+ [M(CCL2)]6+ [CCL2 + CCL8]9+ [M(CCL8)]6+

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Figure 4.6 ESI-FTICR mass spectra of 10 mM MCP-1/CCL2 plus 10 mM MCP-2/ CCL8 plus 10 mM of the defined pentasaccharide, Arixtra, in 100 mM NH4OAc (pH 6.8). M refers to the monomer species and D to the dimer species. For example, [M(CCL8)]6þ is the þ6 ion of the MCP-2/CCL8 monomer, [CCL2þCCL8]9þ is the þ9 ion of the CCL2/CCL8 heterodimer and [CCL2 þ CCL8 þ Arixtra]8þ is the þ8 ion of the CCL2/CCL8 heterodimer in complex with Arixtra pentasaccharide. Reprinted from: ‘‘Journal of Biological Chemistry, 2006 281:25438–46; Heterodimerization of CCR2 chemokines and regulation by glycosaminoglycan binding; Crown, S. E., Yu, Y., Sweeney, M. D., Leary, J. A., Handel, T. M.’’ with permission from ASBMB.

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expensive instrumentation and the need for mass spectrometry expertise are barriers to routine use of this technique. However, mass spectrometry is emerging as the most powerful method for analytical characterization of carbohydrates that bind with high affinity to chemokines.

3.6. Mass spectrometry methods for characterizing GAGbinding epitopes on chemokines: Proteolytic footprinting Apart from understanding whether proteins interact with GAGs and defining their corresponding affinities, it is often useful to know which regions of a protein form the binding site(s). This information is crucial for understanding, and potentially modulating, protein:GAG interactions. Most methods described previously can be used for this purpose by analyzing point mutants of chemokines; however, although powerful, mutagenesis is a labor-intensive approach. Proteolytic footprinting is a sophisticated method that allows for the identification of regions of a protein that bind to GAGs without the absolute requirement for mutagenesis. The protein of interest, complexed to a GAG of interest, is subjected to digestion with trypsin. The resulting peptides are subsequently analyzed by mass spectrometry and compared with those obtained after a digest of the free protein (Falsone et al., 2007). Regions that are complexed with the GAG are protected from digestion and are thus identified compared with digests in the absence of heparin (or other GAG). This method was used to confirm the GAG binding site of I-TAC/CXCL11 as being principally located in a region encompassing the 50’s loop (53CLNPKSKQAR62), because this region was digested in the absence of heparin but remained intact in the presence of heparin (Sielaff et al., 2009). Although this technique enables the rapid identification of general GAG-binding regions on the chemokine, it does not provide amino acid resolution. The use of additional proteases in addition to trypsin, however, can improve the resolution. 3.6.1. Materials and methods For this assay a nanoHPLC-MS/MS instrument is required. It also requires recombinant chemokine, heparin, or other GAGs, trypsin, NH4HCO3 buffer, NaCl, and formic acid. For the GAG-footprinting experiments, chemokines are proteolytically digested with trypsin for 1 h at 20  C, in an enzyme to substrate ratio of 1:10 (w/w). The digestion is performed in the presence and in the absence of a 10 molar excess of heparin or another GAG in 50 mM NH4HCO3, pH 8.0, containing 150 mM NaCl to suppress nonspecific interactions. Proteolytic cleavage is carried out at 37  C for 18 h. The digest is then stopped by adjusting the pH to 2.5 with formic acid. The resulting peptide fragments are subsequently identified by nanoHPLC-MS/MS as described previously

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(Falsone et al., 2007). Potential GAG-binding epitopes on the chemokine are identified as undigested (protected) peptides in the presence of heparin that are digested in the absence of heparin.

3.7. Emerging mass spectrometry methods for characterizing protein:GAG interactions: Hydrogen deuterium exchange and radiolytic oxidation Footprinting methods related to the proteolysis approach described above include hydrogen deuterium (H/D) exchange and radiolytic oxidation mapping (Takamoto and Chance, 2006; Xu and Chance, 2007). These methods have not yet been applied to chemokine:GAG interactions let alone many other protein:GAG interactions. However, they are emerging methods and, therefore, worth mentioning. In hydrogen/deuterium amide exchange mass spectrometry (HDMS or DXMS), protein is buffer-exchanged from a medium containing H2O to the same buffer containing D2O (Mandell et al., 2005). The labile hydrogen atoms of the backbone amides exchange with solvent at a rate dependent on several parameters, including solvent accessibility and involvement in H-bonds, and the time-dependent rate of exchange can be measured by a shift in mass of 1 Dalton per amide group with mass spectrometry. Regions of higher stability or burial will be characterized by more slowly exchanging amides compared with regions of low stability and exposure. Therefore, if a region of a protein is protected by a GAG, the reduced solvent accessibility should result in protection from exchange compared with the free protein. The experiment is conducted as follows: protein alone or protein and GAG is rapidly diluted into a D2O buffer for various amounts of time. At the end of a given exchange period, the sample is then ‘‘quenched’’ to low pH to terminate the reaction and prevent further exchange during subsequent steps. The samples are then subject to proteolysis with enzymes that work at low pH, like pepsin and fungal protease. One then determines the rate of incorporation of the deuterium into the peptides as a function of time with mass spectrometry. The resolution of the method is, therefore, defined by the peptide coverage, and the use of different proteases, therefore, increases resolution. This method was used to characterize the Link module from human tumor necrosis factor stimulated gene-6 (Link_TSG6) and hyaluronan (HA) oligosaccharides (Seyfried et al., 2007). Although promising, and widely used for protein-protein interactions, this study points out a major caveat. In this study, amides distal to the GAG-binding site were protected because of allosteric effects; thus one must be able to distinguish protection caused by conformational changes versus those caused by ligand binding. A general technical issue with the use of H/D exchange is to avoid back exchange of the deuterium off the protein during sample processing.

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Radiolytic oxidation, another relatively new mass spectrometry technique, does not suffer from this complication (Takamoto and Chance, 2006). This technique is also based on the principle of increased amino acid protection in the presence of ligand/protein/GAG, but in this case, the protection is from hydroxyl radicals that oxidize amino acid side chains. Although we know of only one report of the application to characterizing a carbohydrate binding protein (Charvatova et al., 2008), the method seems to have several advantages over HDMS. First, the modifications are covalent, which facilitates analysis without the worry of back exchange. Second, the oxidation seems to be directly related to solvent accessibility and thus unless major conformational arrangements occur, the results should readily reflect ligand binding epitopes without complications from allostery. All side chains are subject to oxidation, and the reactivities are reasonably well characterized; thus the method in principle has amino acid resolution. Finally, side chain interactions seem most important for binding GAGs, and these are probed in the radiolytic approach, whereas only backbone atoms are probed by HDMS, because the labile side chain atoms exchange much too fast for detection. At this point, the method has been applied to characterize the dimer interface of the carbohydrate-binding protein, galectin-1, but not yet with GAG bound. However, one can anticipate future applications to mapping protein-carbohydrate surfaces as the technique matures. One of the main issues will be the availability of software for the identification of the modifications that occur on hydroxyl radical oxidation, access to the appropriate mass spectrometry equipment, and further understanding of the underlying chemistry of oxidation.

4. Summary Interactions between chemokines and glycosaminoglycans have been proven to be critical for their biological function. Moreover, GAG-binding deficient mutants, engineered to test the relevance of GAG binding in vivo, have been shown to interfere with cell migration induced by the wild-type proteins and to be effective in animal models of disease, suggesting that such mutants could be effective protein therapeutics. These findings represent major advances in the chemokine field, yet there is much to be discovered. What really is the extent of the specificity encoded by interactions of these proteins with GAGs? For chemokines, these interactions could significantly influence their spatial localization on cells and thus function. To answer these questions, further development of methods beyond those outlined here will be necessary, and the chemokine field will likely benefit from emerging technologies involving glycan arrays, glycomics, sequencing by mass spectrometry, and methods for routine synthesis of carbohydrates and

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carbohydrate analogs. Beyond characterizing the interactions between chemokines and GAGs, which is largely the focus of the methods covered in this chapter, we also need to obtain a better understanding of the full significance of their functional roles in vivo.

ACKNOWLEDGMENTS This work was funded by an NRSA postdoctoral fellowship F32GM083463 awarded to D. J. H., and by the Lymphoma Research Foundation, the Department of Defense (USAMRAA W81XWH0710446), and NIH (RO1-AI37113 and R21AI076961) awards to T. M. H. and a European Union FP6 INNOCHEM award (LSHB-CT-2005-518167) to A. E. I. Proudfoot.

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C H A P T E R

F I V E

Multiple Approaches to the Study of Chemokine Receptor Homo- and Heterodimerization Jose´ Miguel Rodrı´guez-Frade, Laura Martinez Mun˜oz, and Mario Mellado Contents 1. Introduction 2. Biochemical Techniques to Measure Chemokine Receptor Oligomerization 2.1. Western blot and immunoprecipitation 2.2. Colocalization assays 2.3. Fluorescence labeling of antibodies 2.4. Construction of fluorescence-labeled receptors 3. Resonance Energy Transfer (RET) Techniques 3.1. Bioluminiscence resonance energy transfer (BRET) techniques 3.2. Fluorescent resonance energy transfer (FRET) techniques 4. Sequential BRET-FRET (SRET) Technology 5. Conclusion Acknowledgments References

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Abstract Chemokines belong to a family of structurally related chemoattractant proteins that bind to specific seven-transmembrane receptors linked to G proteins. They are implicated in a variety of biologic responses ranging from cell polarization, movement, immune and inflammatory responses, as well as prevention of HIV-1 infection and cancer metastasis. Recent evidence indicates that chemokine receptors can adopt several conformations at the cell membrane. Chemokine receptor homo- and heterodimers preexist on the cell surface, even in the absence of ligands. Chemokine binding stabilizes specific receptor conformations and activates distinct signaling cascades. Analysis of the conformations

Department of Immunology and Oncology, Centro Nacional de Biotecnologı´a/CSIC, Madrid, Spain Methods in Enzymology, Volume 461 ISSN 0076-6879, DOI: 10.1016/S0076-6879(09)05405-6

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adopted by the receptors at the membrane and their dynamics is crucial for a complete understanding of the function of these inflammatory mediators. We focus here on conventional biochemical and genetic methods, as well as on new imaging techniques such as those based on resonance energy transfer, discussing their advantages, disadvantages, and possible complementarity in the analysis of chemokine receptor dimerization.

1. Introduction The family of low molecular weight proinflammatory cytokines termed chemokines were originally described as specific mediators of leukocyte directional movement (Mackay, 2001). Current views nonetheless implicate these molecules in the movement of several cell types, because they participate in functions such as lymphocyte trafficking (Baggiolini, 1998), regulation of T cell differentiation (Sallusto et al., 1998), HIV-1 infection (Berger et al., 1999), angiogenesis (Belpario et al., 2000), development (Raz, 2003), and tumor metastasis (Mu¨ller et al., 2001). Today, scientists refer to the nearly 50 known chemokines as either constitutive chemokines, which are usually regulated during development, or as inducible chemokines, whose expression is regulated mainly by inflammatory mediators (Proudfoot, 2002). In addition, certain viruses encode highly selective chemokine receptor ligands that can serve as agonists or antagonists and may, thus, have a role in viral dissemination or evasion of host immune response (Alcami, 2003). On the basis of their broad range of functions, it is easy to deduce that chemokines must be central to a variety of diseases that are characterized by inflammation and cell infiltration. They have become a major focus of interest as therapeutic targets, because there is a clear correlation between the expression of specific chemokines and the orchestrated recruitment of cell populations during the course of some disease processes (Proudfoot, 2002). The chemokines act by binding to class A rhodopsin–like, seventransmembrane G-protein–coupled receptors (GPCR) (Horuk, 2001). The 20 receptors characterized to date are classified as CCR, CXCR, CX3CR, and XCR on the basis of their ligand specificity (Rossi and Zlotnik, 2000). Another group of receptors (D6, DARC, and CCXCKR) that can interact with several chemokines were recently denominated ‘‘silent’’ receptors, because they are unable to activate signal transduction events that lead to cell chemoattraction (Borroni et al., 2008). Most chemokine receptors are able to interact with more than one chemokine (shared receptors), although there are some examples of specific chemokine-receptor pairs (specific receptors) (Horuk, 2001). Expression of these receptors is finely regulated by factors that include cytokines,

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growth factors, and cell cycle status (Loetscher et al., 1996; Papadopoulus et al., 1999; Parks et al., 1998). It is, therefore, not surprising that cells respond differently to a chemokine, depending on the microenvironment in which they are found. As the chemokine receptors integrate numerous signaling pathways (Soriano et al., 2003; Thelen and Stein, 2008), the chemokine-mediated signaling cascade is more complex than was originally thought. Although initially considered a cytokine habit (Thelen and Baggiolini, 2001), various studies have demonstrated the existence of chemokine receptor homo- and heterodimers and have speculated on the functional relevance of these conformations (Mellado et al., 2001a,b; Percherancier et al., 2005; Vila-Coro et al., 2000; Wang et al., 2006). The difficulties in detecting these complexes with immunoprecipitation methods suggest conformational instability in the absence of ligand, but resonance energy techniques clearly show that chemokine receptor dimers form spontaneously in the absence of ligand (Hernanz-Falco´n et al., 2004; Wilson et al., 2005). A number of questions remain to be answered, however, including the dynamic nature of these receptor complexes and the role of distinct ligands in promoting the conformational changes that trigger function. This is particularly important in the case of chemokines, because there is a relative lack of selectivity in ligand binding, with many receptors showing high affinity for more than one chemokine (Tian et al., 2004) and simultaneous expression of several receptors on the same cell. Although biochemical technologies were classically used to analyze protein-protein interactions, our current knowledge has been supplemented by new approaches on the basis of energy transfer between fluorochromes followed by confocal microscopy. These methods exploit important technologic advances such as laser light sources, fluorescent probes, and improvements in computer science that allow digital imaging and image analysis. Independently of the technique used, the cell system being used must be characterized in detail before attempting analysis of chemokine receptor dimerization. This includes routine testing such as analysis of cell cycle status, cell surface receptor expression, and determination of receptor number and affinity constants, especially when cells are transfected with mutant or fluorescently labeled receptors.

2. Biochemical Techniques to Measure Chemokine Receptor Oligomerization Until recently, most assays used to demonstrate receptor oligomerization were based on biochemical approaches such as immunoprecipitation or crosslinking. Alternately, dominant negative receptor mutants were used to

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abrogate wild-type receptor functions by forming nonfunctional complexes (Rodriguez-Frade et al., 1999). Because any single method alone has intrinsic limitations, most should be used in concert with others to obtain meaningful results.

2.1. Western blot and immunoprecipitation Although the general protocol for immunoprecipitation assays is very similar, lysis buffer compositions vary, and cell number should be adjusted for each case. Cells (1
107 cells/ml), unstimulated or stimulated with the appropriate chemokine, are diluted immediately with 1 ml cold PBS to terminate stimulation. Cells are centrifuged (800g, 5 min, 4  C), washed with cold PBS, resuspended in 200 ml lysis buffer (10 mM triethanolamine, pH 8, 150 mM NaCl, 1 nM EDTA, 10% glycerol, 2% digitonin), and incubated (30 min, 4  C, with continuous rocking). Other lysis buffers can be also used; however, detergents can alter receptor interactions and must be evaluated carefully. A preclearing step is essential to reduce nonspecific binding to the immunoprecipitating antibody (Ab). For this step, incubate the supernatant containing solubilized proteins with antiimmunoglobulin Ab (antibody against immunoglobulin of the animal species from which the immunoprecipitating Ab is derived) coupled to agarose and incubate (30 min, 4  C). Then add the immunoprecipitating Ab (90 min, 4  C), followed by anti-Ig coupled to agarose (without washing; 60 min, 4  C). After extensive washing and centrifugation, resolve the pellets by SDS-PAGE. To adjust the percentage of the acrylamide solution, remember that the predicted molecular weight of chemokine receptors is in the 30- to 50-kDa range. Transfer the gel to nitrocellulose membranes and develop Western blot as described elsewhere (Rodriguez-Frade et al., 1999). The immunoprecipitation technique is based on the use of chemokine receptor-specific Ab and depends greatly on their characteristics (specificity, affinity). This method is useful for evaluation of receptor heterodimers, in which case one receptor should appear in the immunoprecipitates of the other receptor. Alternately, it can be applied to analyze homodimerization, although in this case the receptors must be tagged appropriately. Receptor labeling bypasses the need to raise antibodies specific for target receptors and has been used successfully to demonstrate homodimerization of CCR2 and in the case of other GPCR, such as b2Ars, GABAB, mGluR5, d-opioid, m3-muscarinic, and Ca2þ receptors (Angers et al., 2002; Rodriguez-Frade et al., 1999). Selection of an appropriate tag and its location in the receptor are both important factors. Amino acids added to the extracellular region might alter ligand binding, whereas modification of intracellular domains can disturb the coupling of signaling molecules. Both ligand affinity and receptor distribution should first be evaluated to ensure that the behavior of the tagged receptor is similar to that of the wild-type receptor. FLAG, myc,

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HA, GST, His, GFP, and GAL are among the tags for which there are commercially available antibodies that immunoprecipitate and recognize the tagged receptor in Western blot. Homemade epitopes can also be designed and included into the receptor cDNA sequence with standard PCR techniques (Rodriguez-Frade et al., 1999). Immunoprecipitation methods can be complemented with crosslinking assays with bifunctional reagents such as disuccinimidyl suberate (DSS). Before lysis, cells should be resuspended in 1 ml cold PBS with 10 ml 100 mM DSS and incubated (10 min, 4  C). Care must be taken in cell handling before the lysis step, because the presence of nonintact cells increases the background of nonspecific protein crosslinking. Prepare the DSS reagent just before use. Continue with lysis, immunoprecipitation, and Western blot analysis as described previously. In this case, Western blot analysis with specific Ab will develop the band corresponding to the monomeric receptor, as well as the high molecular weight dimeric, trimeric and oligomeric species.

2.2. Colocalization assays Modern optical microscopy allows us not only to visualize organelles and molecules but also to study their function. In living cells, we can analyze how a molecule moves, changes location, or associates with other molecules. Such phenomena were originally evaluated with colocalization assays, which detect light from two different fluorophores and evaluate a digital image for the presence of the same pixel in two distinct channels. Signal colocalization indicates adjacency of fluorophores, and thus of the molecules they label (Fig. 5.1). A high-numerical aperture microscope lens permits resolution near 300 nm, sufficient to locate molecules in different cell compartments but not to demonstrate molecular association. The technique requires fluorescence-labeled antibodies or receptors coupled to fluorescent proteins. To determine colocalization between chemokine receptors, plate cells on coverslips coated with poly-L-lysine (20 mg/ml, 1 h, 37  C) and culture them (24 h, 37  C, 5% CO2). After washing, fix the cells with 4% paraformaldehyde (10 min, room temperature [RT]). To avoid nonspecific binding, treat the cells with PBS supplemented with 1% BSA, 0.1% goat serum and 50 mM NaCl (1 h, 37  C). Add the receptor-specific Ab (30 min, RT). To facilitate the procedure, use antibodies of distinct species origin (i.e., mouse, rabbit, rat, hamster) to stain the two receptors. If prelabeled Abs are available, their use precludes the need for secondary antibodies. Otherwise, add the mixture of prelabeled secondary Ab (20 min, RT). If both primary Abs are of the same origin and isotype, add one of these Abs, followed by its fluorochrome-labeled secondary antibody. Wash and incubate the cells with undiluted serum from the same species as the primary Ab (30 min, RT). Now stain the cells with the specific Ab for the second receptor as

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A Cy

3

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Figure 5.1 Chemokine receptors colocalize at the cell membrane.(A) Scheme of the colocalization experiment. Chemokine receptors can be fused to fluorescent proteins (left) or immunostained with fluorochrome-labeled specific antibodies (right). (B) In a representative experiment, CCR2/CCR5 stably transfected L1.2 cells were fixed and costained with anti-CCR2 (anti-CCR2-Cy3) and -CCR5 mAb (anti-CCR5-Cy2).The merged image is also shown; arrows indicate colocalization areas (yellow). All images are overlaid on the DIC (differential interference contrast) image.

previously, followed by its secondary antibody labeled with a different fluorochrome (20 min, RT). Evaluate fluorescence on a confocal microscope with filters appropriate for the fluorochromes used.

2.3. Fluorescence labeling of antibodies Although commercially available Ab can be used for these purposes, antibodies can also be labeled in the laboratory. Given their intense fluorescence and low hydrophobicity, the Cy dyes are efficient tags for fluorescence labeling. In the standard labeling procedure, the contents of a commercial vial (‘‘to label 1 mg of protein’’) of Cy2, Cy3, or Cy5 are dissolved in 50 ml dimethylsulfoxide (DMSO). The antibody is dissolved to 1 mg/ml in buffer (100 mM NaCl and 35 mM H3BO3, pH 8.3). Mix 10 ml of dye/DMSO mixture with 200 ml antibody solution and incubate (30 min, 25  C, in the dark). Separate unbound dye by adding 300 ml of 100 mM NaH2PO4, incubate (30 min, 25  C), and load the sample on a PD-10 column preequilibrated with 100 mM NaCl, 50 mM NaH2PO4, 1 mM EDTA

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(pH 7.5). Elute the labeled protein with 2 ml of distilled H2O. The labeled antibody should be titrated against the chemokine receptor before use.

2.4. Construction of fluorescence-labeled receptors For rapid, easy visualization of chemokine receptors, fluorescent proteinbased constructs and microscopy techniques are very helpful. The constructs are typically used in colocalization analysis and energy transfer techniques. Receptors are cloned with standard molecular biology methods into commercially available vectors bearing fluorescent proteins. Insertion of the fluorescent probe in the C-terminal region of the receptor involves elimination of the receptor stop codon, whereas insertion in the N-terminal region requires elimination of the fluorescent protein stop codon. Transfected cells should be analyzed for receptor expression and function.

3. Resonance Energy Transfer (RET) Techniques Newer methods to determine chemokine receptor oligomerization are based on resonance energy transfer (RET). These techniques are also useful for determining conformation dynamics, the role of ligand and receptor levels, and for defining the dimerization site within the cell (Harrison and van der Graaf, 2006). There are two main types of RET, bioluminescence resonance energy transfer (BRET) and fluorescence resonance energy transfer (FRET). In the former, the donor molecule is luminescent (Pfleger and Eidne, 2006); in the latter, the donor fluorochrome transfers energy to an acceptor fluorochromes (Cardullo, 2007). Both techniques require generation of fusion proteins between the receptor and the fluorescent/luminescent donor and acceptor proteins, as well as the use of transfected cells (Boute et al., 2002). Controls must, therefore, be included to rule out alterations in receptor distribution between the cells and to avoid differences in receptor-mediated cell function. Although BRET has been used at the single cell level (Coulon et al., 2008), it is, in fact, an approach for cell suspensions (Pfleger et al., 2006). It allows measurement of energy transfer between receptors independently of their expression pattern and permits quantitation. In contrast, FRET imaging techniques use confocal or wide-field microscopy, allowing measurements in single cells and identification of cell locations at which FRET is detected.

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3.1. Bioluminiscence resonance energy transfer (BRET) techniques BRET makes use of nonradiative energy transfer between a light donor and a fluorescent acceptor. The bioluminescent energy resulting from the catalytic degradation of a substrate by luciferase is transferred to an acceptor fluorophore, which in turn emits a fluorescent signal (McVey et al., 2001). This transfer takes place when there is an effective range of 10 nm between donor and acceptor, which allows at least 50% of the energy to excite the acceptor molecule. For maximum spectral overlap, the acceptor fluorophore (YFP or GFP2) varies depending on the substrate oxidized (coelenterazine or its derivative DeepBlueC, respectively). Because of their small size and their hydrophobicity, coelenterazines cross the cell membrane easily. For BRET measurements, at 48 h posttransfection, wash cells once with PBS. Add coelenterazine H (Nanolight Technology) to a final concentration of 5 mM in PBS, and take readings with a multidetector plate reader that allows the sequential integration of signals detected in the 480  20 nm and 530  20 nm windows for luciferase and YFP light emission, respectively. The BRET signal is determined by calculating the ratio of the light intensity emitted by receptor-YFP to the light intensity emitted by receptor-RLuc. The values are corrected by subtracting the background BRET signal as measured in the same cells expressing the receptor-RLuc or the receptorYFP construct alone. For acquisition of full BRET spectra, cells are transfected with different amounts of receptor-YFP for a given quantity of receptor-RLuc. Cells are detached and resuspended in HBSS containing 0.1% (w/v) glucose. Cells (2
105) expressing different acceptor/donor (YFP/RLuc) ratios are seeded in 100 ml HBSS in a clear-bottom 96-well plate, and a BRET scan is performed by reading luminescence between 400 and 600 nm, immediately after coelenterazine addition. YFP fluorescence is determined in the same cells with a black 96-well plate. For BRET titration experiments, net BRET ratios are expressed as a function of the acceptor/donor ratio. These BRET saturation curves provide an idea of the maximum BRET signal. They also allow evaluation of BRET50, which is proposed to indicate the ability of two partners to interact (Audet et al., 2008); nonetheless, this would only be the case if the association between the receptors is reversible, which has not yet been demonstrated. Total fluorescence and luminescence are used as relative measures of total acceptor and donor protein expression, respectively. Total fluorescence is determined with an excitation filter at 485 nm and an emission filter at 535 nm. Total luminescence is measured 5 to 10 min after coelenterazine addition, in the absence of the emission filter. Because BRET-based experiments do not permit subcellular analysis, results can be altered, for example, by random collisions because of

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accumulation of chemokine receptors in intracellular membranes. To define receptor oligomers, experiments must be performed with several acceptor/donor ratios at a fixed surface density and a number of expression levels at a defined acceptor/donor ratio. Under these conditions, nonspecific interactions are independent of BRET efficiency and of acceptor/ donor ratios. Finally, it is very useful to include positive controls such as the donor genetically fused to the acceptor and, when possible, a known interacting receptor pair whose characteristics resemble those studied. Although the ideal negative control is a noninteracting protein similar to that analyzed, the acceptor protein is normally used alone.

3.2. Fluorescent resonance energy transfer (FRET) techniques In FRET, donor excitation energy is transferred to the acceptor by means of an induced dipole-dipole interaction; efficiency depends on the distance between and orientation of donor and acceptor fluorophores (Sekar and Periasami, 2003). Ideal dyes are photostable, have little intensity fluctuation, and are relatively small in size to minimize perturbation of the chemokine receptor. For all FRET methods, donor/acceptor choice is critical. Donor emission spectra should ideally have maximum overlap with acceptor absorption spectra, although acceptor and donor emissions should be clearly separable to minimize background interference. Fluorochrome incorporation into the protein must also be considered, because FRET sometimes requires the generation of chimeric constructs in which each chemokine receptor is fused to a different, modified form of green fluorescent protein (GFP). Some donor/acceptor combinations are blue (BFP)/GFP, CFP/YFP, green (GFP)/dsREd, GFP2/YFP, and YFP/dsRed. The most frequently used is, nonetheless, the CFP/YFP combination, because both are extremely bright, and this combination offers few technical problems (Pollok and Heim, 1999). BFP is a poor donor, because it is not especially bright, making FRET between BFP and GFP difficult to detect. dsRed is a poor acceptor, because it has a broad absorption spectrum and excites the same wavelength as the donor (GFP or YFP). FRET is sometimes evaluated on intact receptors with specific Ab conjugated to appropriately selected fluorescent dyes. Some common dyes are Alexa488, FITC, Cy3 or Cy2 as donor, and rhodamine-2, Alexa555, Cy3, or Cy5 as acceptor. Although Cy3 (donor) and Cy5 (acceptor) form a suitable fluorochrome pair, the Cy2 donor/Cy3 acceptor pair is often more convenient, because it allows use of the widely available 488-nm argon laser line. Secondary antibodies are occasionally needed, although the increased distance between fluorophores complicates FRET detection; this can be

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resolved with dye-labeled F(ab0 ) fragments. Because FRET depends on fluorochrome distance and orientation, low FRET efficiency values do not necessarily correlate with lack of dimerization. Several methods are used to determine and quantify FRET. The first is sensitized acceptor fluorescence, in which the donor fluorescent dye is excited and the acceptor signal is measured (Fig. 5.2). Another possibility is acceptor photobleaching, a method based on quenching donor fluorescence. Some donor photons are used to excite the acceptor, decreasing the emission energy detected. Photobleaching of the acceptor abolishes FRET, increasing donor light emission (Fig. 5.3). This method cannot be used for living cells, however, because exposure to extended laser energy is thought to damage the cell. Finally, fluorescence lifetime imaging microscopy (FLIM) measures a chromophore’s fluorescence lifetime, allowing spatial resolution of biochemical processes. The fluorescence lifetime of a donor dye decreases under FRET conditions, independently of fluorophore concentration (Periasami et al., 2002). To develop FRET assays by photobleaching with the CFP/YFP pair, plate HEK-293T cells (3.5
104 cells/ml) on poly-L-lysine–coated coverslips (20 mg/ml, 1 h, 37  C) and incubate (24 h, 37  C, 5% CO2). Cotransfect receptor combinations at a 1:1 ratio (one YFP- and one CFP-labeled receptor) and incubate (48 h, 37  C, 5% CO2); confirm equal levels of each receptor at the cell surface with standard flow cytometry analysis. Wash cells in PBS and fix with 4% formaldehyde (4 min, RT). Wash in A YFP emission

YFP

CFP

CFP emission B CFP

YFP

FRET

Figure 5.2 Analysis of chemokine receptor dimerization by the sensitized acceptor fluorescence method for FRET. (A) Scheme illustrating the sensitized acceptor fluorescence method. CFP is excited with a 405-nm laser line and YFP emission detected at 530 nm. Alternately, a decrease in CFP emission can be detected at 460 to 500 nm. (B) Unstimulated HEK-293Tcells were transiently cotransfected with CCR2-CFP and CCR5-YFP, fixed, and FRETdetermined by detection of YFP emission. Images show CFP staining (left),YFP staining (middle), and FRET (right).

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Figure 5.3 Analysis of chemokine receptor dimerization by the photobleaching method in FRET. (A) Schematic representation of the photobleaching method. Some donor energy is used to excite the acceptor, decreasing detectable donor emission (left). Photobleaching of the acceptor abolishes FRET, increasing donor emission (right). (B) FRET evaluation of chemokine receptor heterodimerization with the acceptor photobleaching method. Unstimulated HEK293T cells were transiently cotransfected with a 1:1 combination of CCR2-CFP and CCR5-YFP, fixed, and FRET was determined. The image shows CFP staining before (CFP-pre) and after (CFP-post) photobleaching, as well as a false color merged image (FRET) and a zoom image of FRETat the photobleached area (insets).The DIC image is also included (left).

PBS and mount coverslips onto slides with PBS (pH 7.0) containing 80% glycerol. Evaluate fluorescence on a confocal microscope with appropriate filters for the fluorochrome. In a FRET assay, an image of the cell region of interest is taken with standard spectroscopic settings. CFP and YFP are excited by separate sweeps of the 405-nm (laser diodo [25 mW]) and 515-nm lines (three-line argon laser [45 mW]), respectively, and directed to the cell by means of a 405- to 440/515-nm dual dichroic mirror. The emitted fluorescence is split by a 510-nm dichroic mirror for CFP and directed to a spectral detector adjusted to the 460- to 500-nm range. For YFP, fluorescence is directed to a spectral detector adjusted to the 530- to 570-nm range. Confocal fluorescence intensity data (ICFPpre and IYFPpre) are recorded, with a pinhole of 100, as the average of four line scans per pixel and digitized at 12 bits. Repeated scans with 515 nm maximum light intensity are used to photobleach YFP, which requires 5 to 30 sec at maximal scan rates and a 100-pinhole aperture. After 60 to 90% of YFP bleaching, fluorescence intensity (ICFPpost and IYFPpost) is measured with identical parameters. With ImageJ 1.40g software (NIH), FRET efficiency is determined on a pixel-by-pixel basis (E) and calculated in percent as E = (1  FDpre/FDpost)
100%, where FDpre and FDpost are the background-corrected CFP fluorescence intensities before

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and after YFP photobleaching, respectively (Kenworthy, 2001; Zimmermann, 2002). As a negative control, FRET should be determined in transiently transfected HEK-293T cells with a chemokine receptor-CFP and in a region of the cotransfected cells without photobleaching. FRET efficiency should be calculated from several independent determinations, with at least 50 images from each. Recall that FRET provides meaningful data when determined with cells that have been evaluated individually for similar CFP and YFP fluorescence intensities. An alternative based on the sensitized acceptor fluorescence method allows FRET evaluation in cell populations (Carriba et al., 2008). HEK-293T cells are transiently transfected with vectors encoding the chemokine receptors of interest, coupled to CFP or GFP2 (donor) and YFP (acceptor). At 48 h posttransfection, distribute cell suspensions (20 mg protein/well) into 96-well microplates and read them in a fluorimeter equipped with a highenergy xenon flash lamp, with a 10-nm bandwidth excitation filter at 430 nm (CFP) or 400 nm (GFP2) and 10-nm bandwidth emission filters for 495 nm (CFP), 510 nm (GFP2), and 530 to 535 nm (YFP). To avoid spectral mixing, use identical gain settings for all experiments to maintain a constant relative contribution of the fluorophores to the detection channels. It is critical to measure the contribution of donor and acceptor alone to each detection channel in experiments with cells expressing only one of the proteins; these values are normalized to the sum of the signal obtained in the two detection channels. To exclude an effect on FRET efficiency because of the acceptor/ donor ratio and to be able to compare dimerization efficiency between receptor pairs, generate a FRET curve with constant expression levels of the receptor coupled to the donor and increasing amounts of the receptor coupled to the acceptor. This curve yields the FRETmax, which is not informative of interaction specificity, as well as the FRET50 (the acceptor/donor value at half-maximal FRET), which indicates the propensity of the interacting partners to associate and thus reflects differences in the relative affinity of these two partners. FRET efficiency is determined as previously (Zimmermann, 2002). FRET-based experiments can also be designed to determine the dynamics of receptor conformation at the cell membrane (Pello et al., 2008). If the role of the ligand is being studied, cells should be stimulated before they are fixed. The influence of a given receptor, R1, on R2:R2 homodimers can be determined by measuring photobleaching FRET in HEK-293T cells transiently cotransfected with CFP-R2 and YFP-R2 and comparing the result with FRET in HEK-293T cells transiently cotransfected with these two receptors plus R1. To facilitate analysis, R1 is expressed in a pIRES2AcGFP1-Nuc vector (Clontech). Only R1-expressing cells will be GFP-labeled in the nucleus and will be used to determine FRET. These experiments can also be modified to measure FRET between receptor heterodimers. In all cases, R1 expression in GFPþ cells should be controlled by flow cytometry and the CFP/YFP ratio determined by separate

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measurement of fluorescence levels. Controls should also include evaluation of the effect of R1 on R2 expression. For a complete analysis, the effect of the unlabeled receptor on FRET saturation curves assays should be measured; determine sensitized acceptor FRET in cells coexpressing a constant donor amount and increasing acceptor levels alone or in the presence of the unlabeled specific or unspecific receptors. FLIM is the most powerful FRET technique, because it is independent of transfection levels, although it requires complex equipment. In a typical FLIM determination, cells are plated on a chamber coverglass and transfected as described previously. Avoid fixing to allow in vivo measurements. FLIM is measured with a confocal microscope with a High Speed Lifetime Module and a 60
PlanApo 1.4 objective, or equivalent equipment. Fluorescence lifetime is determined after excitation with a pulsed laser (picosecond pulses) and a bandpass emission filter appropriate for the fluorochrome used and is quantitated with LIMO (Nikon) or similar software. Avoid the use of mounting solutions, which increase autofluorescence. The fluorescence lifetime of a donor is a constant parameter in specific experimental conditions (Fig. 5.4). A reduction in donor lifetime is due to a A

Pulsed laser

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Figure 5.4 Analysis of chemokine receptor dimerization by FLIM. (A) Scheme showing the FLIM method. The fluorescence lifetime of CFP after pulsed laser excitation (440 nm) (left) decreases under FRETconditions (right). (B) CFP fluorescence lifetime images (calculated from the phase shift) of HEK-293 cells expressing CCR5-CFP (left) or CCR5-CFP/CCR2-YFP (right). The pseudocolor scale ranges from 0 (black) to 4.0 nanosec (white).

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quenching effect triggered by the acceptor and is, therefore, indicative of chemokine receptor dimerization. Positive and negative controls as in BRET or in other FRET methods should also be included. Pay careful attention to variations in pH, temperature, and ionic strength in the medium, because these parameters cause alterations in FLIM measurements. Mycoplasma infection of the cells will also cause artifacts.

4. Sequential BRET-FRET (SRET) Technology Although BRET and FRET techniques are widely used to demonstrate homo- and heterodimers in living cells, they are inadequate for evaluating high-order complexes; that is, complexes involving more than two molecules. A new BRET-FRET–based technique called sequential BRET-FRET (SRET) was recently described (Carriba et al., 2008). SRET uses cells expressing a protein fused to RLuc, a protein fused to a BRET acceptor (GFP2 or YFP), and a protein fused to a FRET acceptor (YFP or DsRed). Addition of a RLuc substrate promotes acceptor excitation by BRET and subsequent energy transfer to the FRET acceptor (Fig. 5.5). We use suspensions of transiently cotransfected HEK-293T cells (20 mg protein/well) distributed in 96-well microplates, read in a fluorimeter equipped with a high-energy xenon flash lamp and a series of 10-nm bandwidth excitation and emission filters appropriate for the receptor-fused protein; this allows detection of BRET and FRET acceptor emission. These experiments require quantitation of receptor-fluorochrome expression, separation of the relative contribution of each fluorophore to the detection channels, quantitation of receptor-RLuc expression by determining luminescence, and, finally, SRET determination after addition of the RLuc substrate. The exact proportion of each fluorophore

RLuc 400 nm BRET

dsRED

YFP 530 nm FRET

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0n

m

Colenterazine

Figure 5.5 Sequential resonance energy transfer technique (SRET). Cell coexpressing chemokine receptors, each fused to RLuc, to YFP, or to dsRED. Addition of the RLuc substrate (coelenterazine) triggers luciferase light emission at 485 nm. In consequence, the excited donor FRET (YFP) emits at 530 nm, which excites the FRET acceptor (dsRED). dsRED emission is then detected at 590 nm. This technique is used to study oligomerization.

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in the cell population is thus established, which indicates the receptor ratio used. These experiments measure FRET in cell populations, as for BRET; analyses, therefore, cannot be restricted to a specific cell area. All the general considerations and controls described for BRET and FRET are also applicable for these assays.

5. Conclusion Chemokines are the principal chemotactic factors implicated in the regulation of leukocyte traffic, both to inflammation sites and for establishing lymphoid organ architecture. Chemokines mediate their function by interacting with specific members of the seven-transmembrane, G-protein–coupled receptor family, which are expressed on the cell surface. Much information is available on the biochemical pathways activated by this large receptor family. Recent experiments, including those based on the application of resonance energy transfer (RET) technology, have, nonetheless, revealed an unexpected degree of complexity in chemokine receptor dynamics at the plasma membrane. In addition to the known promiscuity between ligands and receptors, the chemokine receptors can adopt a variety of conformations at the cell surface. These homo- and heterodimeric, and possibly oligomeric conformations, might be modulated by the levels of chemokine receptors or of other GPCR, as well as by chemokine expression. To explain the precise role of ligands and receptors in these dynamics, the classical biochemical techniques such as crosslinking, immunoprecipitation, and Western blot must be complemented by new technologies such as those based on RET and microscopy analysis. For these procedures, methodologic questions will need to be clarified, including use of different cell types, protein overexpression, and use of chemical inhibitors that can alter in vitro distribution, availability, and/or function of chemokine receptors compared with their in vivo behavior. Correctly used, these techniques will clearly be of value in unraveling the complexities of chemokines, their receptors, and their signals. Improved understanding of receptor homoand heterodimerization is changing our view of chemokine receptor structure and activation, which is likely to have substantial influence on drug development and screening.

ACKNOWLEDGMENTS We thank the members of the DIO chemokine group, who contributed to some of the work described in this review. We also thank C. Bastos and C. Mark for secretarial support and helpful editorial assistance, respectively. This work was partially funded by grants from the EU (Innochem LSHB-CT-2005-518167 and Molecular Imaging LSHG-CT-2003-503259),

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the Spanish Ministry of Science and Innovation (SAF2005-03388), and the Madrid Regional Government. The Department of Immunology and Oncology was founded and is supported by the Spanish National Research Council (CSIC) and by Pfizer.

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C H A P T E R

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Plasmon Resonance Methods in Membrane Protein Biology: Applications to GPCR Signaling Zdzislaw Salamon,* Gordon Tollin,*,† Isabel Alves,‡ and Victor Hruby*,† Contents 124 125 125 126 129 131 132 136 138 141 144 144 144

1. Introduction 2. Plasmon Spectroscopy 2.1. Description of surface plasmons 2.2. Varieties of surface plasmon resonances 3. Sensor Construction and Sample Deposition 4. Lipid Bilayer Deposition 5. Spectral Data Analysis 6. Membrane Protein Insertion 7. Ligand and G-Protein Binding by GPCRs 8. Conclusions Conflicts of Interests Acknowledgments References

Abstract Plasmon waveguide resonance (PWR) spectroscopy, a variant of surface plasmon resonance (SPR) spectrometry, allows one to examine changes in conformation of anisotropic structures such as membranes and membrane-associated proteins such as G-protein–coupled receptors (GPCRs). The binding and resulting structural changes that accompany interactions of membrane protein with ligands (agonists, antagonists, inverse agonist, etc.), G-proteins, and other effectors and modulators of signaling can be directly examined with this technique. In this chapter we outline the instrumentation used for these studies, the experimental methods that allow determination of the structural changes, and thermodynamic and kinetic parameters that can be obtained from these studies.

* { {

Department of Biochemistry and Molecular Biophysics, University of Arizona, Tucson, Arizona, USA Department of Chemistry, University of Arizona, Tucson, Arizona, USA Department of Chemistry, Universite Pierre et Marie Curie, Paris, France

Methods in Enzymology, Volume 461 ISSN 0076-6879, DOI: 10.1016/S0076-6879(09)05406-8

#

2009 Elsevier Inc. All rights reserved.

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1. Introduction Examination of the structures of integral membrane proteins and of the structural changes that accompany their interactions with biologically important ligands such as agonists, antagonists, inverse agonists, partial agonists, allosteric modulators, and other integral membrane proteins has been very difficult. This is due to their relatively low abundance in membranes, the highly anisotropic properties of cellular membranes, the relative lack of biophysical and analytical methods that can directly probe integral membrane protein structure, and the difficulty of purifying and crystallizing integral membrane proteins in their biologically active forms. The use of radioactive and fluorescent probes on the ligands for integral membrane protein, fluorescent, and other physical probes on the integral membrane proteins and on the membranes has allowed the development of binding assays (thermodynamic and kinetic information can be obtained) and the evaluation of certain intermolecular interactions at the membrane surface in response to ligands, but there often are difficulties of interpretation and of evaluating artifacts because of the structural modifications that have occurred by addition of the probes and reporter groups, fluorescent proteins, dyes, etc. Clearly there is a need for better biophysical methods that can directly probe these biologic systems. In this chapter, we will discuss a relatively new biophysical method, plasmon-waveguide resonance (PWR) spectroscopy (Salamon and Tollin, 1999a,b; Salamon et al., 1997a,b,c, 1999a) that allows one to directly examine structural changes of integral membrane proteins that result from their interactions with ligands or other proteins on the membrane surface. Anisotropic properties can be directly probed, as can thermodynamic and kinetic properties that result from these interactions, without the need for any chemical modifications. In this chapter, we will illustrate the uses and power of this new method with G-protein–coupled receptors (GPCRs) as an example of an integral membrane protein. GPCRs are the largest class of integral membrane proteins, in fact the largest class of proteins in the human genome with more than 1000 different proteins now known. They are absolutely essential for most aspects of intercellular communication in complex biologic multicellular systems such as human beings and are the targets of most hormones and neurotransmitters that modulate behavior and metabolism. Furthermore, they are directly involved in many diseases. In fact, they are the targets of approximately 50% of all current drugs. In this chapter, we will examine the use of PWR to monitor and provide thermodynamic and kinetic information in regard to ligand binding, information transduction by G-proteins, GTP-GDP exchange occurring as a consequence of receptor activation, effects of membrane composition, and other aspects of GPCR action that can be directly examined by PWR spectroscopy.

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2. Plasmon Spectroscopy 2.1. Description of surface plasmons The concept of surface plasmons (Salamon and Tollin, 1999a; Salamon et al., 1997b) originates from the plasma formulation of Maxwell’s theory of electromagnetism, where the free electrons of a metal are treated as a high-density liquid (plasma). Plasma oscillations in metals are collective longitudinal excitations of the electrons, and plasmons are the quanta representing these charge-density oscillations. The spreading electron density fluctuations generate a surface-localized electromagnetic wave that propagates along the plane interface between the metal and an adjacent dielectric medium (e.g., air or water), with the electric field normal to this interface and decreasing exponentially with distance from both sides of the interface. These characteristics of the electromagnetic field also describe the guided surface waves (also known as evanescent waves) generated optically under total internal reflection conditions when all of the incident light is reflected at the boundary of the incident and emerging media. Surface plasmon excitation is a resonance phenomenon that occurs when energy and momentum conditions between incident light photons and surface plasmons are matched according to the following equation (Salamon et al., 1999a): 1=2

kSP ¼ kph ¼ ðo=cÞe0 sin a0 ;

ð6:1aÞ

kSP ¼ ðo=cÞðe1 e2 =e1 þ e2 Þ1=2 :

ð6:1bÞ

where

kSP is the longitudinal component of the surface plasmon wave vector, kph is the component of the exciting light wave vector parallel to the active (metal) medium surface, o is the frequency of the surface plasmon excitation wavelength (l), c is the velocity of light in vacuo, e0, e1, and e2 are the complex dielectric constants for the incident, surface active and dielectric (or emerging) media, respectively, and a0 is the incident coupling (resonance) angle. To satisfy this relationship in a conventional resonator assembly (Salamon and Tollin, 1999b; Salamon et al., 1997c), plasmon excitation must occur through an evanescent wave generated by p-polarized incident light (electric vector perpendicular to the surface). This plasmon excitation geometry turns out to be ideal for application as a biomedical sensor, because the excitation light is totally separated from the emergent medium

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(e.g., a biologic fluid to be analyzed). This allows the assay of such fluids regardless of their optical transparency (including, for example, blood, urine, cell suspensions, etc.). The resonance conditions mentioned previously can be fulfilled by changing the incident light angle, a, at a constant value of photon energy (i.e., wavelength) (Salamon and Tollin, 1999a; Salamon et al., 1997b). At resonance, the surface plasmons are generated at the expense of the energy of the excitation light leading to significant alterations of the totally reflected light intensity. Thus, a plot of the reflected light intensity versus incident angle is a quantitative measure of the resonance and constitutes a surface plasmon resonance spectrum (Salamon and Tollin, 1999b, 2000; Salamon et al., 1997c, 1999a ). Furthermore, any alteration in the optical properties of the metal/dielectric medium interface (such as, for example, immobilization of material) will affect the surface plasmon wave vector and, therefore, change the resonance characteristics, leading to changes in both the position and shape of the resonance curve. As can be seen from Eq. (6.1), these optical properties are fully described by the complex dielectric constant, e, which contains the refractive index, n, and the extinction coefficient, k (i.e., e ¼ nik) as well as the thickness, t, of a layer of material deposited at the interface. The sensitivity (Salamon and Tollin, 1999b, 2000), S, of measurements of such alterations can be defined as the change in reflectance (dR), measured at a specific angle, a1, within the range of the resonance curve, divided by the change in one of the three optical parameters (dn, dk, and dt), i.e.,

Sa1 ¼ ½dRðaÞ =dn dk dta1

ð6:2Þ

In general, the magnitude of changes in the experimental value of R are controlled by two factors: the shift of the position and the shape of the resonance spectrum. Both of these factors are related to the sharpness of the spectrum (i.e., its half-width); this defines the optical resolution (i.e., the smallest changes that can still be resolved as two different readings). Therefore, the overall sensitivity of a plasmon resonator will depend on both the magnitude of the electromagnetic field at the resonator surface and the optical resolution.

2.2. Varieties of surface plasmon resonances 2.2.1. Conventional surface plasmon resonance (SPR) In the most straightforward case, for which the hypotenuse of a right angle prism is coated with a single high-performance metal layer (usually Ag or Au, although gold is often used in biosensors because of its resistance to corrosion), one can generate surface plasmons on the outer surface of the

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Distance from the prism surface, nm

Normalized electric field amplitude

0

200

400

600

3 s

PWR (Ag, SiO2)

2 p

1

SPR (Au)

0 SiO2 layer Metal layer (Ag,Au)

Figure 6.1 Calculated electric field amplitudes for SPR and PWR resonators with excitation light wavelength 632.8 nm.The sensitivity of the resonator is proportional to the amplitude of the field at the external surface (gold layer in the case of SPR and silica layer in the case of PWR).

metal with visible light (typically 500 to 700 nm), as indicated in Fig. 6.1 for either a 55-nm Ag or a 48-nm Au layer (which are the optimal thicknesses for these metals) (Salamon and Tollin, 1999a,b; Salamon et al., 1997b,c). The electromagnetic wave created as a result of surface plasmon excitation is characterized by several important properties, which are very relevant in biosensor applications. First, there is an enormous increase in the intensity of the electromagnetic field generated by surface plasmons compared with that at the incident surface. It is also important to note that the energy of the field is proportional to the square of the electromagnetic wave intensity. This property further increases the sensitivity of the measurement. Second, the magnitude of the increase in the electromagnetic field intensity depends on the optical properties of the metal layer used to generate plasmons. Thus, as the calculation presented in Fig. 6.1 demonstrates, silver produces approximately a twofold higher intensity, which results in a fourfold higher overall sensitivity than gold.

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2.2.2. Plasmon-waveguide resonance (PWR) In 1997 we developed (Salamon and Tollin, 2001a, 2002; Salamon et al., 1997, 1999b) a variant of SPR that involves more complex assemblies in which surface plasmon resonances in a thin metal film are coupled with guided waves in a dielectric overcoating, resulting in excitation of both plasmon and waveguide resonances. We termed this phenomenon coupled plasmon-waveguide resonance (CPWR [Salamon and Tollin, 1999a,b; Salamon et al., 1999a]; later shortened to PWR). We constructed a spectrometer based on this technology, which we have applied to the study of biologic membrane systems (Hruby and Tollin, 2007; Salamon and Tollin, 2001b; Salamon et al., 1999a). We also licensed this technology to Proterion Corp., who developed and patented a PWR instrument (Anafi et al., 2004), which we have also used successfully in the study of biomembrane systems. A plasmon-waveguide resonator contains a metallic layer (as in a conventional SPR assembly), which is deposited on either a prism or a grating and is overcoated with either a single dielectric layer or a system of dielectric layers; these layers are characterized by appropriate optical parameters so that the assembly is able to generate surface resonances on excitation by both p- and s-polarized light components (Fig. 6.1). The addition of such a dielectric layer (or layers) to a conventional SPR assembly plays several important roles. First, it enhances the spectroscopic capabilities (because of excitation of resonances with both p- and s-polarized light components), which results in the ability to directly measure anisotropies in refractive index and optical absorption coefficient in a thin film immobilized onto the surface of the overcoating (Salamon and Tollin, 2001c). This allows one to obtain information regarding structural changes in the analyte, providing the material is oriented uniaxially at the interface. Second, it functions as an optical amplifier that significantly increases electromagnetic field intensities at the dielectric surface compared with conventional SPR, as illustrated by Fig. 6.1. This results in an increased sensitivity and spectral resolution (the latter caused by decreased resonance line widths, as also shown in Fig. 6.2). Usually these two resonances ( p- and s-) have different sensitivities resulting from different evanescent electrical field intensity distributions (Fig. 6.1). In the simplest PWR sensor comprised of silver covered with silica, the s-polarization is significantly more sensitive (fivefold to 10-fold) than that of p-polarization. It is important to note that both of these resonances are much more sensitive than conventional SPR. The latter resonators are usually based on a gold metal film. As noted previously, such a sensor is approximately four- to fivefold less sensitive than a silver-based one. The simplest PWR sensor described previously further increases the sensitivity by a factor of 4 (for p-polarization) or 10 (for s-polarization), resulting in an overall 20- to 50-fold increase in sensitivity compared with a conventional gold-based SPR sensor. It should also be noted that the PWR sensitivity could be

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Normalized reflectance

1.0

SPR (Au) 0.5

p

s

PWR (Ag, SiO2) 0.0 65

70 Incident angle, deg

75

80

Figure 6.2 Calculated resonance curves for SPR and PWR resonators shown in Fig. 6.1.

further amplified by modifying the simplest two-layered (silver and silica) sensor with more complex arrangements of dielectric layers. Such systems have been developed in our laboratory to be able to distinguish between different microdomains in lipid bilayer membranes (Salamon et al., 2005). These latter systems are characterized by an overall sensitivity at least two orders of magnitude higher that that obtained with conventional gold-based sensors. A third important characteristic of PWR is that the dielectric overcoating also serves as a mechanical and chemical shield for the thin metal layer. This allows reactive metals such as silver to be used in an aqueous environment, the latter being crucial for biosensor applications. It also provides a surface that can take advantage of the wide range of chemistries developed for the covalent immobilization of materials.

3. Sensor Construction and Sample Deposition Figure 6.3 shows a view of the sample compartment and sensor of a Proterion PWR instrument (Anafi et al., 2004). The sensor prism is pressed against a Teflon block containing a sample chamber (aqueous volume approx. 0.5 ml) and a reference compartment (aqueous volume approx. 0.1 ml) and sits adjacent to a solid-state detector that monitors the incident polarized CW laser light intensity reflected through the prism from the

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Flow manifold

Prism block

To computer

Teflon block Sample chamber

Detector connector

Bare reference chamber Cam clamp (closed position) Coated side

(Bare glass portion)

Detector

Prism

Prism block removed

Prism detail

Sample deposited here

Cam clamp (open position)

CW laser

SiO2 layer (~50 nm) Silver layer (~500 nm) Bare glass

Used for angle and amplitude calibration

Figure 6.3 Diagram of the prism holder and sample compartment of a Proterion PWR instrument.

backside of the sensor surface. The sample and reference chambers can be accessed through ports in the Teflon block holder. The sensor prism surface is partially coated with thin layers of silver and SiO2 on which the sample to be characterized is deposited. The laser beam can be positioned so that it is incident either on the sample region or on the bare glass region; the latter is used for incident angle and light intensity calibration purposes (the critical angle for total internal reflection is used as a reference point). This entire unit is mounted on a rotating table that allows the incident angle of the laser beam to be continuously varied with 1 mdeg resolution so as to obtain a computer readout of the angular dependence of the reflected light intensity (see Fig. 6.4). It is important to point out that the thickness and the quality (uniformity, purity, etc.) of the prism coatings are extremely important, because these control the angular position and the line width of the resonance signal. For a sample to influence the PWR resonance spectra obtained with a sensor prism in contact with an aqueous solution, it is desirable for it to be

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Detector Computer Prism Plasmon generating film (Ag + SiO2) Sample Aqueous medium Polarizer CW Laser Rotating table

Figure 6.4

Diagram of a typical PWR spectrometer.

immobilized within a distance from the surface corresponding to less than one wavelength of the monitoring light. This influence will diminish exponentially as one moves away from this surface. A variety of methods can be used for this purpose, including covalent attachment to the silica or physicochemical adsorption to the surface. Inasmuch as one of the main interests of our laboratory has been the characterization of membrane proteins, we will focus here on the use of lipid bilayers for immobilization.

4. Lipid Bilayer Deposition With the orifice in the sample compartment of the Teflon block as a support, it is possible to create a self-assembled single lipid bilayer on the silica surface of the resonator that is attached by a Gibbs border of lipid solution (Salamon et al., 1994, 1996a), in much the same way as was done across an orifice in a Teflon sheet separating two aqueous phases in the classical Mueller-Rudin experiment (Mueller et al., 1962). Such an annulus of lipid solution not only anchors the bilayer but also acts as a reservoir of lipid molecules. Bilayer formation is accomplished by depositing a small amount of a lipid solution (typically at a concentration of approximately 10 mg/ml of lipid in a mixture of squalene and butanol; 0.15:10, v/v) on the hydrated surface of the sensor prism and then filling the chamber with aqueous buffer. The hydrophilic surface of the silica attracts the polar head groups of the lipid molecules, thus forming a lipid monolayer deposited on a layer of adsorbed water, with the hydrocarbon chains oriented toward the droplet of excess lipid solution. Filling the cell with the

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1.0

Reflectance

0.8

0.6

0.4 Buffer: p-polarization Buffer: s-polarization Bilayer: p-polarization Bilayer: s-polarization

0.2

0.0 64

65 Incident angle (mdeg)

66

Figure 6.5 Typical PWR spectra obtained with a Proterion instrument from a silver/ silica sensor in contact with an aqueous buffer before and after deposition of an egg phosphatidylcholine bilayer.

appropriate aqueous solution initiates the second step, which involves a thinning process with the formation of both the second monolayer and the Gibbs border that attaches the bilayer film to the Teflon spacer, allowing the excess of lipid and solvent to move out of the orifice (Salamon and Tollin, 1999a,b). This typically occurs in 20 to 40 min and creates a very stable, highly flexible, bilayer into which integral membrane proteins can be inserted and onto which peripheral membrane proteins can be bound by electrostatic forces (see Figure 6.5). A variety of lipid compositions can be used to form such bilayers, and the aqueous environment can also be varied over a large range. This allows one to investigate microenvironmental effects on bilayer formation and protein immobilization.

5. Spectral Data Analysis As noted previously, the optical properties of a system can be described by three parameters: refractive index (n), extinction coefficient (k), and thickness (t). It is important to note that only thickness is a scalar quantity, whereas both n and k are tensors and, therefore, in general, they

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have different values along the different measurement axes. The refractive index is a macroscopic quantity and is related to the properties of individual molecules through the molecular polarizability tensor, as well as to the environment in which these molecules are located (e.g., packing density and internal organization). Similarly, the extinction coefficient is related to the molecular optical transition tensor (Salamon and Tollin, 2001b,c; Salamon et al., 2005). The distinction between thickness and the two other optical parameters is especially important when the molecules to be investigated are located in a matrix (such as a biomembrane or lipid bilayer membrane or any thin film) that has nonrandom organization and thus possesses long-range spatial molecular order. Such molecular ordering creates an optically anisotropic system, usually having a uniaxial optical axis resulting in two different principal refractive indices: ne (also denoted as nII or np) and n0 (also referred to as n or ns), and two different extinction coefficients: kp, and ks (Salamon and Tollin, 2001b). The first of these indices is associated with a linearly polarized light wave in which the electric vector is polarized parallel to the optical axis. The second one is observed with light in which the electric vector is perpendicular to the optical axis. This is the fundamental basis on which measurement of the optical properties of anisotropic systems can lead to the evaluation of their structural parameters. In the simplified case in which a molecular shape can be approximated by a rodlike structure and the molecules are ordered such that their long axes are parallel (e.g., phospholipid molecules in a lipid bilayer membrane), one has an optically anisotropic system whose optical axis is perpendicular to the plane of the lipid bilayer (Salamon and Tollin, 2001). The values of the refractive indices and extinction coefficient measured with two light polarizations (i.e., parallel, np and kp, and perpendicular, ns and ks, to the optical axis) will describe the optical (An) and extinction coefficient (Ak) anisotropies, as follows:




An ¼ ðnp Þ  ðns Þ  Ak ¼ ðkp  ks Þ kav 2

2




ðnav Þ2 þ 2



ð6:3aÞ ð6:3bÞ

where nav and kav are the average values of the refractive index and extinction coefficient. For a uniaxial system, in which the optical axis is parallel to the membrane normal, one has the following equations for the average values:


i1=2 2 2 nav ¼ 1=3 ðnp Þ þ 2ðns Þ h

kav ¼ ðkp þ 2ks Þ=3

ð6:4aÞ ð6:4bÞ

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Furthermore, as can be seen from the Lorentz-Lorenz relation for the refractive index and the Lambert-Beer relationship for the extinction coefficient, nav is also directly related to the mass surface density (Cuypers et al., 1983; Salamon and Tollin, 2001b):



  2 ðnav Þ2 þ 2 m ¼ 0:1M=N t ðnav Þ  1

ð6:5aÞ

whereas kav is also related to the surface concentration of chromophore:

C ¼ ð4p=lÞðkav =bÞ

ð6:5bÞ

where M is molecular weight, N is molar refractivity, t is the thickness of the membrane, C the molar concentration of chromophore, and b the molar absorptivity. For lipid molecules a reasonable approximation of M/N is 3.6 (Cuypers et al., 1983). Thus, from the refractive indices and extinction coefficients measured with two polarizations (np, ns, kP, and ks), and the thickness of the membrane (t), one can calculate the following parameters describing the physical characteristics of the membrane: (1) the surface mass density (or molecular packing density), i.e., mass per unit surface area (or number of moles per unit surface area) (Salamon and Tollin, 2001b,c), which reflects the surface area occupied by a single molecule; (2) the optical anisotropy (An), which reflects the spatial mass distribution created by both the anisotropy in the molecular polarizability and the degree of long-range order of molecules within the system (Salamon and Tollin, 2001c); (3) the surface chromophore density; and (4) the spatial distribution of chromophores. As noted previously, the experimental PWR spectra can be described by three parameters: spectral position, spectral width, and resonance depth. In the case of lipid bilayers, these features depend on such physical properties as the surface mass and/or chromophore density, the spatial mass and/or chromophore distribution, and the membrane thickness. Thin-film electromagnetic theory based on Maxwell’s equations provides an analytical relationship between the experimental spectral parameters and the optical properties (Salamon and Tollin, 1999a,b; Salamon et al., 1997c, 1999a). This allows evaluation of the n, k, and t parameters from which the membrane physical properties can be assessed. The fact that there are three experimentally measured spectral parameters and three optical parameters allows, in principle, a unique determination of the n, k, and t values by fitting a theoretical resonance curve to the experimental one. We have demonstrated such an approach by applying a nonlinear least-square fitting procedure to describe the structural consequences of the interaction of the human d-opioid receptor with some of its ligands

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(Salamon et al., 2000). With this approach we demonstrated that significantly different structural changes are induced in the d-opioid receptor on binding to different ligands. We were also able to quantify these differences and to propose a model representing changes in conformation and mass distribution of lipid and receptor molecules during interaction of the receptor with either agonist or antagonist molecules. Although such an approach to analysis of experimental data works well and is able to generate enhanced understanding of both the mass and structural alterations induced by molecular interactions within a thin film, in some cases another approach is necessary. In general, this arises from three principal reasons: (1) molecular interactions leading to a complex spectrum where it is no longer possible to obtain a unique determination of the optical parameters (e.g., they occur in a heterogeneous film), resulting in a final spectrum that represents a mixed population; (2) rapid conclusions about the interactions is required, which precludes a tedious and often difficult analysis; and (3) the resonance spectra are not good enough to be fitted by the theoretical curves (poorly resolved spectra usually are good enough to do some comparative experiments, but they cannot be used to quantify them by fitting procedures). In these cases there are two other approaches available: (1) spectral simulation (Alves et al., 2005a; Salamon et al., 2005), or (2) graphical analysis (Salamon and Tollin, 2004). The spectral simulation procedure is based on the same principle as the fitting approach described previously, but is quicker and easier to apply. We have used this method to characterize the lateral segregation of lipids and proteins into microdomains (rafts) in solidsupported bilayers. We were able to measure and simulate the PWR spectra of membranes formed from a single component lipid, as well as from a mixture of lipids. Iteration in such simulations was performed by manual variation of the optical parameters until an appropriate agreement with the experimental spectra was obtained. Application of this method of data analysis allowed us to assess the most important structural parameters of a lipid membrane, such as thickness, average surface area occupied by one lipid molecule (or molecular packing density), and degree of longrange molecular order. Furthermore, we were able to characterize segregated microdomains and demonstrate preferential association of protein molecules with one type of microdomain (Salamon et al., 2005). The graphical analysis procedure (Salamon and Tollin, 2004) is based on the following consideration. PWR spectra are determined by two physical properties of a thin film such as a lipid membrane: (1) an average surface mass density, and (2) the spatial distribution of mass within the system that results from the structure of the deposited film. The separation of mass changes from those caused by structure is achieved by transforming the measured spectral changes (e.g., changes in the position of the spectra obtained either with p- or s-polarized exciting light) from an (s-p)

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orthogonal coordinate system into one reflecting (mass-structure). To perform such a transformation one must be able to place mass and structural axes within the orthogonal (s-p) coordinate system. This can be done if one knows the following two properties of the measurement system: (1) the mass sensitivity of the p- and s-axes in the (s-p) coordinate system (i.e., the sensor must be calibrated either theoretically or experimentally); (2) the optical symmetry of the measured system (i.e., whether the system is optically isotropic or anisotropic). For an anisotropic system, one must assume the direction of the optical axis (i.e., whether the optical axis is parallel to the p- or to the s-polarization direction). The axes of a new (mass/structure) coordinate system can then be scaled with the original (s/p) coordinates. Each point on the mass axis (Dm) can be expressed by changes of the original coordinates (Ds) and (Dp) as

ðDm Þ ¼ ½ðDs Þ2m þ ðDp Þ2m 1=2

ð6:6aÞ

and on the structural axis:

ðDstr Þ ¼ ½ðDs Þ2str þ ðDp Þ2str 1=2

ð6:6bÞ

In this way the contribution of structural changes and mass alterations are expressed in terms of angular shifts.

6. Membrane Protein Insertion Integral membrane protein insertion into the solid-supported bilayers can be accomplished by detergent dilution methods. Care must be taken in the choice of the detergent used so that the detergent is both able to maintain the protein in its native state and is sufficiently mild so that it does not perturb the lipid bilayer. Octylglucoside, in our experience, is able to satisfy both conditions, although in certain cases dodecyl maltoside was able to maintain the receptor active for longer periods of time. However, because dodecyl maltoside greatly perturbs the lipid bilayer, the detergent was exchanged with octylglucoside before addition to the PWR sample cell. By injecting small aliquots of a solution of a protein in an octylglucoside-containing buffer into the sample compartment, in which the detergent is above the critical micelle concentration (CMC), thereby diluting the detergent to below the CMC, spontaneous incorporation into the bilayer occurs, usually over a period of minutes. Lipid molecules that are displaced by such insertion can be transferred into the Gibbs border. Similarly, the bilayer is flexible enough so that even large extramembrane

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segments can be accommodated. It should be noted that not all the protein that is injected into the PWR sample compartment is inserted into the bilayer. Indeed, from spectral analysis we have determined that only a small amount of protein is properly reconstituted in the bilayer (approximately 5% in the case of the d-opioid receptor) (Alves et al., 2005a). Because PWR is a very sensitive technique, the insertion of picomole quantities of protein is usually sufficient to obtain a good signal. The remaining protein, which is most probably deposited into the bottom of the PWR cell, is washed from the cell compartment by flowing buffer through the system. It should be pointed out that if one wants to compare the spectral changes induced by ligand and/or G-protein binding to the lipid bilayer, one has to either incorporate similar amounts of receptor (as judged by comparable spectral shifts) or to normalize the data so that the amount of incorporated receptor is taken into account. In Fig. 6.6 are presented the PWR spectra obtained for the incorporation of a GPCR, the human d-opioid receptor (hDOR) into an egg PC bilayer. Note that the incorporation of the receptor into the bilayer leads to anisotropic increases in the resonance angle position (190 mdeg shift for the p- and 130 mdeg for the s-polarized resonance) and in the spectral depth, that are the result of an increase in the mass and the thickness of the bilayer. Because the receptor protrudes from both sides of the lipid bilayer, one should expect the bilayer to become thicker on

A

B 1.2 1.0 Reflectance

Reflectance

1.0

0.8

0.8

0.6 0.6 0.4 63.5

63.9 64.3 64.7 Incident angle, deg

67.2

67.4 67.6 Incident angle, deg

67.8

Figure 6.6 PWR spectra obtained for lipid bilayer formation and receptor incorporation with p-polarized (A) and s-polarized (B) light excitation. Solid curves represent the buffer spectra (10 mM TRIS buffer (pH 7.3), 0.5 mM EDTA, and 10 mM KCl) before bilayer formation; dotted curves correspond to PWR spectra obtained after the formation of a lipid bilayer composed of 75:25 mol% egg PC/POPG; dashed curves are PWR spectra obtained after addition of an octylglucoside-containing buffer solution of hDOR; final concentration in the cell sample compartment 0.4 nM.

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receptor incorporation. Indeed, the thickness of the proteolipid system was found by spectral fitting (Salamon et al., 1997a, 2000) to increase from 5.3 nm to 6.8 nm (the latter value corresponds to the dimension of the incorporated protein molecule perpendicular to the membrane plane). A thickness of the proteolipid system of 6.8 nm correlates well with the size determined for rhodopsin from X-ray crystallography (Palczewski et al., 2000). One should note also that spectral shifts with p-polarization were larger than with s-polarization (indicating refractive index changes in the p-direction larger than for the s-direction), which is a consequence of the anisotropic structure (i.e., cylindrical shape) of the receptor molecules. This is also evidence for the incorporation of the receptor into the bilayer with the expected orientation (i.e., long axis oriented perpendicular to the lipid bilayer), rather than just adsorbed to the surface of the bilayer, clearly reflecting a corresponding increase of the average long-range molecular order in the membrane resulting from receptor-lipid interactions. The direction of receptor insertion is usually controlled by their extramembranous domains; for example, in several cases where these are known to be small (e.g., Family A of G-protein–coupled receptors) we have found that such incorporation is bidirectional (Alves et al., 2003; Salamon et al., 1996b, 2000). This is advantageous in that it allows both sides of an inserted protein to be probed; this is important when one wants to interrogate binding to both sides as is the case with ligand and G-protein binding. This will be further discussed in the following section.

7. Ligand and G-Protein Binding by GPCRs After incorporation of the receptor into the lipid bilayer, the ligandinduced receptor conformational changes can be followed both in kinetic and thermodynamic modes. For that, small aliquots of a ligand solution (usually tens of microliters) are successively introduced into the sample cell and the PWR spectral changes followed. Spectral shifts can be used to determine a thermodynamic binding constant for the ligand-protein interaction by plotting the shifts at equilibrium as a function of the concentration of ligand in the sample compartment. Because the amount of ligand bound is very much smaller than the total ligand present, as a consequence of the large difference in the volumes of the bilayer and the aqueous medium (approximately 1000-fold), the concentration of added ligand is approximately the same as the free ligand. Because the PWR shifts are directly proportional to the bound ligand concentration, KD values can be calculated from the hyperbolic dependence of such a plot. Affinity constants obtained in this manner are in good agreement with those determined by classical binding assays with radiolabel ligands, as exemplified in Table 6.1 for ligand

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Table 6.1 Affinity constants for binding of various ligands to the hDOR obtained with PWR and from previous literature with radiolabel methods KD (nM) obtained from PWR experiments Ligands

p-polarization

s-polarization

Ligand affinities obtained from literaturea (nM)

DPDPE pClDPDPE Deltorphin II SNC80 (-)tan67 TIPPPSI NTI Naloxone TMT-LTic Morphine Etorphine

14  3 2.9  0.7

18  5 3.3  0.8

16 1.6

0.88  0.05

1.2  0.3

0.7

52  8 3.2  1.2 1.1  0.1 0.025  0.001 83 2.5  0.3

57  12 3.7  1.5 1.2  0.1 0.023  0.004 81 3.2  0.2

56 6 1.22 0.028 10 9

520  30 0.3  0.1

b

1101 0.2

b

a

The references from which such binding constants have been obtained can be found in Alves et al. (2004a). s-polarized shifts were negligible for these ligands. Note: KD values were obtained from plotting the resonance minimum position (Y) for the PWR spectra as a function of ligand concentration (X) and fitting to the following hyperbolic function that describes the binding of a ligand to a receptor: Y = (BmaxX)/(KD þ X). Bmax represents the maximum concentration bound and KD is the concentration of ligand required to reach half-maximal binding. b

binding to the hDOR (Alves et al., 2004a). Moreover, contrary to classical surface plasmon resonance (SPR) methods where only mass changes can be investigated (and binding constants obtained), because these are sensitive only to p-polarized refractive index changes, with PWR the ligand-induced conformational changes of the receptor can be monitored by obtaining spectra with both polarizations. Such studies have been performed in our laboratories with several GPCRs: rhodopsin (activated by light rather than by ligand binding) (Alves et al., 2005b; Salamon et al., 1996b), the hDOR (Alves et al., 2003, 2004a), the beta-adrenergic receptor (Devanathan et al., 2004), the neurokinin receptor (Alves et al., 2006), and the cannabinoid receptor (Georgieva et al., 2008). Here, we will not go into the details of those studies but rather point out that they have provided important insights into the type and magnitude of the conformational changes of the receptors. As an example, in the case of the neurokinin 1 receptor, for which over the past 25 years there was a large controversy in the field, radiolabel binding studies have shown that the receptor possesses two binding sites (Sagan et al., 1997), although the origin of those two binding sites was unclear

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(Beaujouan et al., 2004). PWR studies performed by successive binding of one ligand to one site after the other site was occupied and seeing how the binding of the second ligand was affected led to the conclusion that the sites were distinct and non-interconvertible (Alves et al., 2006). Furthermore, careful spectral analysis and data deconvolution, as described in one of the preceding sections, allowed one to obtain detailed information on the nature of such receptor conformations (e.g., with rhodopsin and the hDOR) (Salamon et al., 1996b, 2000). These studies have confirmed the idea that GPCRs adopt a large multitude of conformations depending on the type of bound ligand, which is important to understand GPCR signaling (Alves et al., 2004a; Salamon et al., 2000). PWR has the great advantage of being able to directly monitor G-protein binding to a receptor (in the absence or presence of ligand) because: (1) contrary to classical pharmacologic methods usually used to learn about early signal transduction events, such as cAMP and GTPgS assays, PWR does not rely on downstream events; (2) it allows one to understand the contribution of each individual G-protein subtype, rather than a global response as obtained with studies in cells where several G-proteins are expressed at different levels. To establish a network of signal transduction with the G-protein subtypes that bind to a given receptor in the presence of a specific ligand, we have inserted a pre-bound receptor into the lipid bilayer and then assay its binding to a series of different G-protein subtypes (Alves et al., 2003). In view of the fact that the receptor can orient in the lipid bilayer exposing both the extracellular and intracellular faces to the aqueous side of the bilayer (the one that can be accessed), some fraction of the inserted receptor molecules have the intracellular side available for G-protein interaction. An example of this is shown in Fig. 6.7 for the binding of a G-protein mixture to the hDOR prebound to the agonist DPDPE. In this way, the hDOR has been examined for its G-protein affinities when bound to a large variety of ligands (agonists and partial agonists, antagonists, inverse agonists). We have not only determined that the affinity of the receptor for the G-protein is highly dependent on the type of bound ligand but that a high level of specificity exists in the interaction with the different G-protein subtypes (see Table 6.2 for the binding of different G-protein subtypes to ligand-bound hDOR) and that there is no relationship between the capacity of a ligand to induce G-protein binding and to activate GTPgS exchange (Alves et al., 2003). Furthermore, we were able to study the effect of having the G-protein bound to the receptor on its capacity to bind a ligand (the so-called low- and high-affinity states corresponding to the absence and presence of G-protein, respectively). In these experiments, because neither the G-protein nor the ligand is able to cross the lipid bilayer, we have chosen a different approach, with liposomes harboring both the receptor and G-protein under study that were fused with the lipid bilayer in the PWR cell (a process induced by

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60 p-polarization

Resonance position shift, mdeg

50 s-polarization 40

30 KD = 10.4 ± 0.4 nM

20

10

0 0

20

40

60

80

100

[G proteins], nM

Figure 6.7 Binding of a G-protein mixture (obtained from human brain) to the hDOR prebound to the agonist DPDPE: p-polarization (closed circles); s-polarization (open circles); solid lines correspond to hyperbolic fits to data points yielding KD value shown in figure.

calcium ions) (Alves et al., 2004b). In this way, some G-protein could be delivered to the side of the bilayer facing the prism. Subsequent ligand binding to the G-protein–receptor complex showed that the ligand affinity is greatly enhanced by the presence of G-protein bound to the receptor (Alves et al., 2004b). Such studies have provided important information on the initial signal transduction events.

8. Conclusions In this chapter we have provided a description of a novel biophysical method, plasmon-waveguide resonance (PWR) spectroscopy, that allows evaluation of the anisotropic structural properties of lipid and proteolipid bilayers, with s- and p-polarized light, as well as the structural changes that accompany perturbation of these structures by other biologically relevant molecules such as agonist and antagonist ligands, and other proteins that are involved in a biologic cascade, that directly interact with the integral membrane protein. For the first time, all of these studies, including the thermodynamic and kinetic parameters involved in these interactions, can be accomplished directly without the need for any modification of structure

Table 6.2 Binding affinities between the individual G-protein subtypes and the hDOR either unliganded or bound to various ligands and between GTPgS and the receptor–G-protein complex G-protein subtype

Goa

Polarization

p

Gia1

Gia2

Gia3

s

p

s

p

s

P

S

DPDPE bound KDG-protein (nM) 10  1 KDGTPgS (nM) 404  37

91 394  71

302  24 4.7  0.3

306  28 3.7  0.7

71 9.9  0.5

71 8.3  0.8

45  5 80  11

41  5 83  9

Unliganded receptor KDG-protein (nM) 20  1.7 KDGTPgS (nM) 1917  177

22  1.8 1883  219

79  9 *

81  8 *

598  70 *

574  70 *

95  10 *

96  10 *

45  4 880  135

36  8 89  11

31  7 96  9

298  29 1589  129

322  25 1712  135

18  3 925  139

16  3 896  145

4.8  0.4 12.5  1.9

215  33 2.2  0.4

209  33 2.4  0.3

13.1  1.1 92  13

14.2  1.1 102  15

18  2 26  3

19  2 23  3

Morphine bound KDG-protein (nM) 40  5 KDGTPgS (nM) 910  120 SNC 80 bound KDG-protein (nM) 5.2  0.5 KDGTPgS (nM) 8.9  1.8

* No PWR spectral shifts were obtained on addition of GTPgS up to 5 mM. Note: KD values were obtained from plotting the resonance minimum position for the PWR spectra as a function of G-protein concentration and fitting to the following hyperbolic function that describes the binding of a ligand to a receptor: Y = (Bmax  X)/(KD þ X). Bmax represents the maximum concentration bound and KD is the concentration of ligand required to reach half-maximal binding. The table has been obtained from Alves et al. (2004b).

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(radiolabels, fluorescent probes, dyes, etc.) that are necessary for evaluation of such interactions by other currently available biophysical and bioanalytical methods. Perhaps an even greater advantage of this new method is that it is exquisitely sensitive, requiring only femtomole quantities of integral membrane proteins. This is critical at the present time because most integral membrane proteins are not produced in large quantities naturally, and efforts to use more robust methods of molecular biology to obtain large amounts of these proteins have been only rarely successful because of the fragile stability of most integral membrane proteins and the lack of general biochemical methods to refold denatured membrane proteins to their biologically active structures. In this overview, we have illustrated the application of PWR to examine the structures of G-protein–coupled receptors (GPCRs), the largest class of integral membrane proteins in the human genome, and the targets for nearly 50% of all current drugs. We have demonstrated that we can directly evaluate the conformational changes that occur on interactions of these receptors with agonists, antagonists, partial agonists, and inverse agonists and have been able to determine the equilibrium-binding affinities of these ligands for the receptors, as well as the kinetics of these processes. Unlike SPR, the use of two polarizations to carry out these measurements allows one to obtain information about structural changes as well as changes in mass density. A possible criticism of these studies is that they are done in artificial model membrane structures, and thus the changes in structure observed, and the corresponding thermodynamic and kinetic properties obtained, may not correspond to what is happening in biologic cellular systems. We have addressed these concerns in detail previously (Hruby and Tollin, 2007). Most importantly, the binding affinities of ligands to the G-protein– coupled receptors we have examined, whether agonist, antagonist, partial agonist, or inverse agonist, have been the same in studies with PWR as those reported in the literature with membrane preparations from living systems or cellular assays (see Table 6.1). Furthermore, GTPgS assay results have been comparable to those seen in membrane and whole cell preparations from living systems. This is clear evidence that no major changes in protein conformation have occurred during the course of these measurements. On the other hand, it cannot be ruled out that the microenvironment that exists within a cell may modulate the detailed properties of the receptors. In fact, in those cases in which we have changed the lipid compositions of the bilayer, we have, indeed, observed quantitative changes in receptor thermodynamic properties (Alves et al., 2005a,b). Thus, care must be used in extrapolation of these results to in vivo systems. These studies also have far-reaching implications in a number of areas of biochemistry, pharmacology, and drug design. For example, our studies have demonstrated that GPCRs have multiple biologically relevant conformations, which are likely important for signaling. Interactions of

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agonists, antagonists, partial agonists, and inverse agonists all give different functional conformations than the unoccupied receptor. Thus, textbook depictions of the typical GPCR with a two-state model (i.e., inactive state and agonist-occupied active state) will need to be modified. Structurally, GPCRs are much more heterogeneous with respect to the structures that result from ligand-receptor interactions than implied by such a simplistic model. Indeed, in some cases peptide agonists and nonpeptide agonists for the same receptor can lead to different conformational states. Furthermore, the conformational diversity of receptor-ligand structure manifests itself in different effects on G-protein interactions with the receptor (Alves et al., 2004b; see Table 6.2). The implications of these and other observations that use PWR are still not completely clear and will require further studies. However, even at this early date it seems possible that they may provide new insights into the subclassification of some GPCRs (as for example mu1, mu2, etc. opioid receptors) based on the different structure-activity relationship of different classes of ligands. In this regard, it can be suggested that these varieties of structural changes might lead to different signaling pathways depending on the ways in which these different ligand-receptor conformations affect interactions with other signaling proteins such as adenylate cyclase, protein kinases, inositol phosphate, protein phosphatases, b-arrestins, ion channels and other proteins involved in GPCR signaling. These and other potential studies offer exciting new possibilities for the application of PWR spectroscopy to a variety of important biologic problems involving membranes, integral membrane proteins, and the biochemical machinery associated with their bioactivities.

Conflicts of Interests The authors have patents or patents pending on the instrumentation and applications of PWR spectroscopy.

ACKNOWLEDGMENTS This work was supported previously by grants from the National Science Foundation and the U. S. Public Health Service, National Institutes of Health, and National Institute of Drug Abuse.

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Tyrosine Sulfation of HIV-1 Coreceptors and Other Chemokine Receptors Hyeryun Choe* and Michael Farzan† Contents 1. Introduction 1.1. Disovery of tyrosine-sulfated peptides and proteins 1.2. Identification of the tyrosyl-protein sulfotransferases 1.3. Tyrosine sulfation of HIV-1 coreceptors 1.4. Tyrosine sulfation of other chemokine and related receptors 1.5. Tyrosine sulfation of coreceptor-binding site antibodies 1.6. Useful properties of sulfotyrosine 1.7. Approaches to studying tyrosine sulfation of chemokine receptors 2. Production and Use of Tyrosine-Sulfated Peptides Derived from Chemokine Receptors 2.1. Chemically synthesized tyrosine-sulfated peptides 2.2. Production of sulfated peptides in mammalian cells 2.3. Cell-free sulfation 2.4. Modulation of peptide sulfation 2.5. Uses of tyrosine-sulfated peptides 3. Study of Chemokine-Receptor Sulfation on the Plasma Membrane 3.1. Modulation of chemokine-receptor sulfation 3.2. Mutagenesis of candidate sulfotyrosines 4. Bacterial Expression of Tyrosine-Sulfated Peptides and Proteins 4.1. A system to introduce non-native amino acids into proteins 4.2. Advantages and uses of the system

* {

148 148 149 149 150 153 154 155 155 155 156 158 158 159 160 160 160 161 161 162

Department of Pediatrics, Harvard Medical School, Perlmutter Laboratory, Children’s Hospital, Boston, Massachusetts, USA Department of Microbiology and Molecular Genetics, Harvard Medical School, New England Primate Research Center, Southborough, Massachusetts, USA

Methods in Enzymology, Volume 461 ISSN 0076-6879, DOI: 10.1016/S0076-6879(09)05407-X

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2009 Elsevier Inc. All rights reserved.

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5. Protocols 5.1. Detection of sulfotyrosine of chemokine receptors 5.2. Metabolic labeling of peptide-Fc fusion proteins and removing the Fc domain 5.3. Inhibiting tyrosyl-protein sulfotransferae activity with smallhairpin RNAs 5.4. Cell-free sulfation of tyrosine-containing peptides 5.5. Expression of tyrosine-sulfated proteins in E. coli 6. Conclusions References

163 163 164 165 165 166 167 168

Abstract Sulfotyrosines contribute to a number of critical extracellular protein–protein interactions, including the association of the HIV-1 envelope glycoprotein with the HIV-1 coreceptor CCR5, a similar association between the Duffy binding protein of Plasmodium vivax and the Duffy antigen/receptor for chemokines, between complement components C5a and C3a and their respective receptors, and between many CC- and CXC-chemokines and their receptors. In addition, the antigen-combining regions of a number of human antibodies include sulfotyrosines that are necessary for antigen recognition. The study of sulfotyrosines requires an array of techniques, each with its advantages and limitations. These include modulation of tyrosyl-protein sulfotransferase activity in mammalian cell lines, production of tyrosine-sulfated peptides with direct chemical synthesis or enzymatic addition of sulfate to tyrosines in cell-culture or cell-free systems, and use of a novel tRNA/tRNA-synthetase pair capable of introducing sulfotyrosines at specific sites into bacterially expressed proteins. Here we describe the use of these various approaches to study the role of tyrosine sulfation of chemokine receptors in ligand binding and HIV-1 entry.

1. Introduction 1.1. Disovery of tyrosine-sulfated peptides and proteins Tyrosine sulfation was first described on fibrinopeptide B in 1954, and by the 1970s, a handful of secreted peptides had been shown to include functionally important sulfotyrosines (reviewed in Kehoe and Bertozzi [2000], Moore [2003], and Seibert and Sakmar [2008]). A greater appreciation for full extent of tyrosine sulfation came in 1982, with the observation that many proteins from mammalian cells could incorporate metabolically labeled sulfate on what amino-acid analysis showed to be tyrosines (Huttner, 1982, 1984). The first membrane protein shown to be modified by tyrosine sulfate was the P-selectin glycoprotein ligand (PSGL-1) (Pouyani and Seed, 1995; Sako et al., 1995). The flexible PSGL-1 aminoterminus includes both sulfotyrosines and adjacent O-glycosylation

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moieties. As was later shown for CCR5 and its natural ligands, these aminoterminal modifications cooperate in binding the PSGL-1 ligand, P-selectin.

1.2. Identification of the tyrosyl-protein sulfotransferases The identification of the enzymes responsible for addition of sulfate to tyrosines was a critical contribution to the study and production of sulfated proteins. Two enzymes, tyrosyl protein sulfotransferases 1 and 2 (TPST1, TPST2), mediate tyrosine sulfation in mammalian cells (Beisswanger et al., 1998; Ouyang and Moore, 1998; Ouyang et al., 1998). These enzymes, type II membrane proteins active in the trans-Gogi network, bind the universal sulfate doner 30 -phosphoadenosine 50 -phosphosulfate (PAPS) and transfer sulfate to tyrosines of exposed and flexible regions of lumenal domains of proteins (Suiko et al., 1992). The TPSTs recognize accessible tyrosines usually adjacent to several acidic residues, although in a proper context glycines or asparagines can also promote or at least permit sulfation. In contrast, glycosylated asparagines, basic residues, and phenylalanines seem to hinder sulfation and are typically not found adjacent to a sulfotyrosine (Bundgaard et al., 1997). To date, no clear specificity difference between the two TPSTs has been observed, nor has any tyrosine-specific sulfatase activity been described in mammalian cells (Moore, 2003).

1.3. Tyrosine sulfation of HIV-1 coreceptors The first chemokine receptor shown to be modified by tyrosine sulfation was the CC chemokine receptor and HIV-1 coreceptor CCR5 (Farzan et al., 1999). Figure 7.1 shows specific incorporation of sulfate into CCR5. CCR5 binds and signals in response to the CC-chemokines CCL3 (MIP1a, CCL4 (MIP-1b) and CCL5 (RANTES), and the receptor’s aminoterminal sulfotyrosines and O-linked glycosylation are essential for this association (Bannert et al., 2001). In addition, CCR5 together with the cellular receptor CD4 is essential for most primary HIV-1 isolates to enter a target T cell or macrophage (Choe et al., 1996). The HIV-1 envelope glycoprotein gp120, which with gp41 mediates the viral entry process, first binds CD4. CD4 association induces a conformational change in gp120 that permits subsequent association with CCR5 (Wu et al., 1996). After CCR5 association with gp120, gp41 mediates a large-scale structural rearrangement of the envelope glycoprotein resulting in mixing of the virion and target cell lipids and ultimately entry of the viral core into the cell. CCR5 sulfotyrosines, but not its O-glycosylation, are critical to gp120 binding and HIV-1 entry (Farzan et al., 1999). In some infected individuals, HIV-1 variants can emerge that gain the ability to enter cells by way of the chemokine receptor CXCR4 in addition to or instead of CCR5. Although tyrosine sulfation of CXCR4 is essential for association with this receptor’s

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1

2

3

4

5

6

7

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100 67 CD4 46 CCR5 30 cys/met

SO4

Figure 7.1 CCR5 incorporation of [35S]-sulfate. Cf 2Th cells (lanes 1, 3, 5, and 7) or Cf 2Th cells stably expressing CD4 and CCR5 (lanes 2, 4, 6, and 8) were incubated with [35S]-cysteine and -methionine (lanes 1 to 4) or [35S]-sulfate (lanes 5 to 8). Cells were lysed, and lysates were immunoprecipitated with the anti-CCR5 antibody 5C7 (lanes 1, 2, 5, and 6) or the anti-CD4 antibody OKT4a (lanes 3, 4, 7, and 8), and analyzed by SDSPAGE. Lanes 1 to 4 represent a 12-h film exposure, whereas lanes 5 to 8 represent the same gel exposed for 48 h. Numbers at the left of the figure indicate molecular weight in kilodaltons.

natural ligand, CXCL12 (SDF-1), this modification and, indeed, the entire CXCR4 amino-terminus play a much less pronounced role in the entry of CXCR4-using HIV-1 isolates than with CCR5-using isolates (Farzan et al., 2002a). In addition to these principal coreceptors, a number of chemokine receptors and similar proteins have been shown to support HIV-1 entry in cell-culture systems (Table 7.1). For example, the chemokine receptors CCR2b, CCR3, CCR8, CXCR6, and the related receptors gpr1, gpr15, and apj can support infection by one or more isolates (reviewed in Choe et al. [1998]). In contrast to CCR5 and CXCR4, physiologic roles for these minor coreceptors have not been described. However, their identification has highlighted biochemical properties essential for HIV-1 entry, namely the presence of an acidic and tyrosine-rich amino-terminal motif similar to CCR5 and CXCR4. In those cases that have been examined (CCR2b, CCR3, CCR5, CCR8, and CXCR4) these receptors are sulfated at their amino-terrminal tyrosines (Farzan et al., 1999, 2002a; Fong et al., 2002; Gutierrez et al., 2004; Preobrazhensky et al., 2000).

1.4. Tyrosine sulfation of other chemokine and related receptors In addition to the principal and minor HIV-1 coreceptors, a number of chemokine and related receptors rely on amino-terminal sulfotyrosines to bind their natural ligands, including CX3CR1, the C5a and C3a receptors,

Table 7.1 Sequences of amino-termini of chemokine receptors and related proteins. The amino-terminal sequences of the chemokine receptors and selected related receptors are shown. Bold receptor name indicates experimental demonstration of tyrosine sulfation. Sequences predicted or demonstrated to contain sulfotyrosines are indicated in bold. Receptors that function as principal or minor HIV-1 coreceptors are indicated with, respectively, triple or single plus signs Chemokine Receptors

ccr1 ccr2 ccr3 ccr4 ccr5 ccr6 ccr7 ccr8 ccr9 ccr10 cxcr1 cxcr2 cxcr3 cxcr4 cxcr5 cxcr6 cxcr7 cx3cr1 xcr1

HIV-1 coreceptor?

METPNTTEDYDTTTEFDYGDATPC MLSTSRSRFIRNTNESGEEVTTFFDYDYGAPC MTTSLDTVETFGTTSYYDDVGLLC MNPTDIADTTLDESIYSNYYLYESIPKPC MDYQVSSPIYDINYYTSEPC MSGESMNFSDVFDSSEDYFVSVNTSYYSVDSEMLLC MDLGKP. . .LLVIFQVCLCQDEVTDDYIGDNTTVDYTLFESLC MDYTLDLSVTTVTDYYYPDIFSSPC MTPTDFTSPIPNMADDYGSESTSSMEDYVNFNFTDFYC MGTEATEQVSWGHYSGDEEDAYSAEPLPELC MSNITDPQMWDFDDLNFTGMPPADEDYSPC MEDFNMESDSFEDFWKGEDLSNYSYSSTLPPFLLDAAPC MVLEVSDHQVLNDAEVAALLENFSSSYDYGENESDSCCTSPPC MEGISIYTSDNYTEEMGSGDYDSMKEPC MNYPLTLEMDLENLEDLFWELDRLDNYNDTSLVENHLC MAEHDYHEDYGFSSFNDSSQE MDLHLFDYSEPGNFSDISWPCNSSDCIVVDTVMC MDQFPESVTENFEYDDLAEAC MESSGNPESTTFFYYDLQSQPC

 þ þ  þþþ   þ þ     þþþ  þ    (continued )

Table 7.1 (continued) Related 7TMS receptors

TSHR DARC c5aR ccrl1 d6 chemr23 apj gpr1 gpr15

HIV-1 coreceptor?

GMGCSS. . .IGFGQELKNPQEETLQAFDSHYDYTICGDSEDMVC MGNCLH. . .LDFEDVWNSSYGVNDSFPDGDYDANLEAAAPCHSC MNSFNYTTPDYGHYDDKDTLDLNTPVD MALEQNQSTDYYYEENEMNGTYDYSQYELIC MAATASPQPLATEDADSENSSFYYYDYLDEVAFMLC MEDEDYNTSISYGDEYPDYLDSIVVLED MEEGGDFDNYYGADNQSE MEDLEETLFEEFENYSYDLDYYSLESDL MDPEETSVYLDYYYATSPNSDIR

     þ þ þ þ

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the thyroid-stimulating hormone receptor (TSHR), and the Duffy antigen/ receptor for chemokines (DARC) (Choe et al., 2005; Costagliola et al., 2002; Farzan et al., 2001; Fong et al., 2002; Gao et al., 2003). DARC, thought to be a scavanger receptor for several CC- and CXC-chemokines, mediates the invasion of reticulocytes by the malaria parasite Plasmodium vivax, and the association of DARC with the P. vivax Duffy-binding protein requires one of two sulfate groups present on DARC’s amino-terminal tyrosines (Choe et al., 2005). Table 7.1 shows tyrosine-sulfated regions of each of these seven-transmembrane segment receptors, as well as regions of related chemokine receptors also predicted to include sulfotyrosines.

1.5. Tyrosine sulfation of coreceptor-binding site antibodies Sulfotyrosines also play a necessary role in the recognition by some antibodies of a highly conserved coreceptor-binding region of the HIV-1 envelope glycoprotein (Choe et al., 2003). Tyrosine sulfate has been observed at the third complementarity detemining region (CDR3) of the heavy chain of at least five neutralizing antibodies that recognize this region (Table 7.2). However, sulfation is unlikely to be limited to antibodies of HIV-positive individuals. The heavy chain CDR3 is encoded by one of approximately 25 diversity genes, a number of which encode sequences rich in tyrosines and acidic residues. Although antibody sulfation likely requires relatively long and flexible CDR3 regions, the frequency of tyrosines and aspartic acids encoded by antibody heavy-chain diversity genes suggests that tyrosine sulfation of antibodies is not rare. Tyrosine-sulfated antibodies have become an important tool in understanding the coreceptor interaction with HIV-1 envelope glycoprotein. For example, a structure of the HIV-1 gp120 with CD4 and one such antibody has defined two gp120 Table 7.2 The heavy-chain CDR3 regions of coreceptor-binding site antibodies. The heavy-chain CDR3 regions of five tyrosine-sulfated HIV-1 neutralizing antibodies and of 17b, an antibody that recognizes the same gp120 epitope, are shown. Note that 17b is not sulfated despite the presence of an apparent sulfation motif, likely because of the inaccessibility of its tyrosines. The names of sulfated antibodies are shown in bold, as are CDR3 regions shown to include sulfotyrosines Antibody

Heavy-chain CDR3 sequence

E51 412d 47e C12 Sb1 17b

NSIAGVAAAGDYADYDGGYYYDMD PYPNDYNDYAPEEGMSWYFD GGEDGDYLSDPFYYNHGMD DVGPDWDNDDYYDRSGRGVFD RNPNEYYDENADYSTVYHYMD VYEGEADEGEYDNNGFLK

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Table 7.3 Alignment of a the CCR5 amino-terminus with a peptide derived from the heavy-chain CDR3 region of the tyrosine-sulfated HIV-1 neutralizing antibody E51. An alignment of residues suggesting that the basis of pDE51’s activity may be its homology with CCR5 in aspartic acids and sulfotyrosines that contact gp120. Homologous residues are shown in bold. The higher affinity of pDE51 for gp120 may be due to the absence of hydrophobic CCR5 residues that interact with CCR5 transmembrane regions

pDE51 CCR5

GDYA. . ..DYDGGYYYDMD MDYQVSSPIYDINYYTSEP. . .

sulfotyrosine-binding pockets that presumably bind CCR5 sulfotyrosines (Huang et al., 2007). In addition, a CCR5-mimetic peptide shown in Table 7.3 and derived from tyrosine-sulfated CDR3 region of another HIV-1 neutralizing antibody inhibits viral replication more efficiently than any CCR5-derived peptides and suggests ways in which affinity of sulfated peptides for chemokine ligands might be enhanced (Dorfman et al., 2006).

1.6. Useful properties of sulfotyrosine The observations of key roles for tyrosine sulfation in the entry processes of both HIV-1 and one of the two major forms of human malaria suggests that properties of sulfotyrosine are useful to these pathogens. One possibility is that sulfotyrosines, with a number of highly polarizable electrons distributed between the sulfate and phenyl groups, can bind specifically and with high affinity a diverse set of proteins. The specificity with which sulfotyrosinecontaining peptides bind various ligands is clear. For example HIV-1 gp120 will not bind a C5aR-derived peptide with two sulfotyrosines or a CCR5derived peptide with two phosphotyrosines, but it will associate with a CCR5-peptide with two sulfotyrosines (Cormier et al., 2000; Farzan et al., 2000). Similarly, C5a will not bind tyrosine-sulfated CCR5-derived peptides, but it will bind a C5aR peptide with the two sulfotyrosines found on the native receptor (Farzan et al., 2001). Despite this specificity, sulfotyrosines may permit a wider array of protein interactions than unmodified amino acids. The chemokine/receptor interaction is an example of this; most chemokines bind more than one receptor, and most chemokine receptors bind more than one chemokine. P. vivax and especially HIV-1 may also use this property of sulfotyrosine to modify their respective entry proteins in response to immune pressure while at the same time retaining a high affinity for their cellular receptors. Sulfate modification may have an additional function for chemokine receptors, because it distinguishes immature receptors from receptors that have passed through the trans-Golgi network, perhaps preventing intracellular association of chemokine and

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receptor in cells that produce both. A premature interaction between the HIV-1 envelope glycoprotein and CCR5 may be similarly avoided.

1.7. Approaches to studying tyrosine sulfation of chemokine receptors Despite central roles for tyrosine sulfation in many protein–protein interactions, working with sulfated peptides and proteins has proved challenging. Chemical synthesis of peptides bearing sulfotyrosines requires modification of standard synthesis protocols, is consequently of high cost, and typically limited to two sulfotyrosines on relatively short peptides. Because bacteria do not naturally sulfate proteins and because chemokine receptors, like other mammalian seven-transmembrane segment receptors, cannot be expressed in bacteria, most studies of chemokine-receptor sulfation have been performed in mammalian systems, with RNA interference or overexpression of the TPST enzymes. Cell-free systems for sulfating peptides and soluble receptor fragments have also been used, but peptide yields are typically limiting. Recently, an important contribution to the field has been made by Peter Schultz’s group (Liu and Schultz, 2006; Ryu and Schultz, 2006), who have developed a novel technology for introducing synthetic amino acids, including sulfotyrosines, into bacterially expressed proteins. The uses and limitations of each of these approaches are described below.

2. Production and Use of Tyrosine-Sulfated Peptides Derived from Chemokine Receptors 2.1. Chemically synthesized tyrosine-sulfated peptides Because chemokine receptors cannot be expressed as soluble proteins, biochemical characterization of tyrosine-sulfated peptides based on receptor amino-termini will likely play an increasingly important role in the study and inhibition of chemokine-receptor function. Building on earlier studies of secreted peptides such as gastrin and cholecystokinin, several groups investigated the potential of commercially synthesized tyrosine-sulfated peptides based on the sequence of the CCR5 amino-terminus. These peptides were useful in demonstrating the specificity of sulfotyrosine association with gp120, in clarifying the role of individiual CCR5 sulfotyrosines in this association, and in localizing the sulfate-binding region on gp120 (Cormier and Dragic, 2002; Cormier et al., 2001; Farzan et al., 2000; 2002b). They proved, however, dissappointing as inhibitors of HIV-1 entry, blocking viral replication with IC50s greater than 100 mM. There are several reasons for the poor performance of these first-generation CCR5 mimetics. First, although CCR5 has four sulfated tyrosines in its

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amino-terminus, difficulties in synthesis limited to two the number of sulfotyrosines that could be included in high-quality peptide preparations. Moreover, only shorter peptides (<25 amino acids) could be generated in this manner, and introduction of an adjacent disulfide bond proved prohibitively difficult and expensive. In addition to these problems of chemical synthesis, first-generation peptides, based directly on the CCR5 aminoterminus, retained a number of hydrophobic amino acids that do not interact with the HIV-1 envelope glycoprotein. Instead, experimental evidence suggested they interact with the remainder of the CCR5 protein, and, indeed, these peptides can mediate a interaction of a CCR5 variant lacking its amino-terminus with the HIV-1 envelope glycoprotein or with the chemokine CCL5 (Farzan et al., 2002b). It is likely that hydrophobic residues from the CCR5 amino-terminus contribute to inappropriate conformations or small-scale aggregation of these peptides in solution. Second-generation peptides, produced in mammalian cells and lacking these hydrophobic residues, are considerably more effective at blocking HIV-1 infection (Dorfman et al., 2006), although further improvements will be necessary before they can be considered as potential therapeutics. One such peptide is shown in Table 7.3 aligned with CCR5.

2.2. Production of sulfated peptides in mammalian cells The limitations and expense of chemically synthesized peptides prompted exploration of mammalian expression systems for studying the interaction between CCR5 and the HIV-1 envelope glycoprotein. To promote efficient production and secretion of these peptides, they have typically been expressed as fusion proteins with the Fc region of an antibody, usually human or mouse IgG (Fig. 7.2). Because these overexpression systems typically saturate the endogenous TPST activities of cell lines such as HEK293T cells, plasmids expressing a peptide-Fc fusion protein are cotransfected with a plasmid expressing one of the TPSTs. In our hands, TPST2 is the more efficient at sulfating CCR5-based or CCR5-like peptides. Fc-fusion proteins generated in this way can be purified on protein-A Sepharose beads with protocols standard for antibody purification. Note, however, if elution is performed with a highly acidic buffer, the eluant must be neutralized immediately. Otherwise, the acid-labile sulfates are likely to be lost. Elution with high salt, for example 3 M MgCl, can be used and may be preferable to avoid this possibility. The efficiency of sulfate incorporation can be monitored as in Fig. 7.1 by [35S]-sulfate labeling of cells in parallel, before harvesting of peptide, or through functional assays if function has already been established. If necessary, removal of the Fc domain can be accomplished through introduction of a thrombin cleavage site and incubation with thrombin (see section 5.2). Figure 7.3 shows an

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mock

patient sera

pCCR5-Ig

pE51-Ig

p47e-Ig

pC12-Ig

p17b-Ig

p412-Ig

Peptide-Fc fusion

ADA-Ig

S1-Ig

Beads alone

ADA-Ig

S1-Ig

Beads alone

DM1

CD4mim

Figure 7.2 The CDR3 regions of the sulfated antibody E51 functions as a CCR5 mimetic. Radiolabeled HIV-1 gp120 (ADA isolate) was incubated with radiolabeled supernatants from 293Tcells transfected with plasmid expressing the sulfated (412d C12, 47e, E51) or unsulfated (17b) heavy-chain CDR3 regions of the indicated antibody, or the CCR5 amino-terminus, or with patient sera. Each peptide was expressed as a fusion protein with the Fc region of human IgG1 and produced in the presence of exogenous TPST2. Mixtures of peptide-Fc and gp120 were precipitated with protein A-Sepharose and analyzed by SDS-PAGE. Numbers to the left of the panel indicate molecular weight in kilodaltons. Bands that migrate with the 67-kDa marker indicate residual dimeric forms of the peptide-Ig proteins. As shown in Table III, pE51 is highly similar to the CCR5 amino-terminus, but it lacks a number of the hydrophobic residues of CCR5 that may interfere with gp120 association.

DM1 CD4mim

8.5 3.5

Total

DM1 CD4mim Bound

Figure 7.3 A combined CCR5/CD4 mimetic peptide efficiently binds gp120. Plasmids encoding peptides formed of a 27-amino-acid CD4 mimetic peptide, with or without a 12-amino-acid CCR5 mimetic peptide, and fused to the Fc region of human IgG1were transfected into HEK293T cells, and culture supernatants were precipitated with protein-A Sepharose. CD4 mimetic and CD4/CCR5 mimetic peptides were eluted in 3 M MgCl2, dialyzed against PBS and incubated with thrombin, which cleaves a specific sequence engineered between the mimetic peptide and the Fc domain (see protocols). Free peptide was concentrated and incubated with HIV-1 gp120 and protein sera. Note that only the double CD4/CCR5 mimetic, but not the CD4 mimetic peptide, bound gp120 efficiently.

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60 min

20 min

Figure 7.4 Cell-free sulfation of a CCR5-derived peptide. Protein-A Sepharose beads bound to 200 ngTPST2 fused to the Fc region of human IgG1were incubated with 4 mCi (2 nM ) [35S]-PAPS (30 -phosphoadenosine 50 -phosphosulfate, the sulfate donor) and 2.5 mg (1 nM) unsulfated peptide derived from the first 22 amino acids of CCR5 (MDYQVSSPIYDINYYTSEPSQK) in a total volume of 100 ml for 20 or 60 min, as indicated. An aliquot of supernatant was analyze by SDS-PAGE on a 10 to 20% gradient Tricine gel. Note that longer incubation times generate more of the multiply sulfated peptides, which have greater mobility in these conditions.

example of a CCR5-mimetic peptide fused to a CD4-mimetic peptide that was prepared in this manner and precipitated with HIV-1 gp120.

2.3. Cell-free sulfation An alternative protocol for generation of sulfated peptides was orginally developed to study PSGL-1 and later applied to CCR5. Chemically synthesized or cell-produced peptides can be incubated with PAPS and a soluble form of TPST2 (see protocols). However, the cell-free TPST activity is significantly attenuated relative to TPST activity in a cell, so peptides generated in this way are usually studied in small quantities and with radiolabeling with [35S]-PAPS (Fig. 7.4). Because of the lower efficiency of cell-free TPST2, peptides with multiple tyrosines can be variably sulfated. This heterogeniety is usually not desired, but it has been useful for determining the order of sulfate addition to CCR5 and CXCR4 by mass spectrometry (Seibert et al., 2002, 2008).

2.4. Modulation of peptide sulfation With mammalian expression systems, unsulfated or partially sulfated control peptides can be generated in several ways. The first is through mutation of the sulfated tyrosines. Frequently, phenylalanine is chosen to replace the

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ST-shRNA

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ST-shRNA

Tyrosine Sulfation of Chemokine Receptors

37 scFv 25 cys/met

SO4

Figure 7.5 TPST-2 enhancement and shRNA inhibition of sulfation of a single-chain antibody E51. Plasmid encoding E51scFv was cotransfected into 293Tcells with plasmids expressing shRNAs complementary to the messages of TPST1 and TPST2 (STshRNA), with pcDNA3.1 (vector) or with a plasmid encoding TPST2.Transfected cells were divided and radiolabeled with [35S]-cysteine and -methionine or [35S]-sulfate. Radiolabeled cell supernatants were immunoprecipitated with protein L-Sepharose and analyzed by SDS-PAGE.

sulfated tyrosine, but for several reasons this may be an innappropriate choice. First, because of its greater hydrophobicity, phenylalanine led to aggregation or nonbiologic conformations of a peptide in solution. Second, when more than one sulfotyrosine is present on a peptide, and elimination of a single sulfate is desired, phenylalanine is especially inappropriate, because it will efficiently prevent sulfation of adjacent tyrosines. For these reasons, aspartic acid, which maintains peptide solubility and promotes sulfation of nearby tyrosines, can be a better choice. An alternative means by which unsulfated peptides can be generated is through the use of RNA interference targeting the cellular TPSTs (see protocols). As shown in Fig. 7.5, targeting of TPST1 and TPST2 by small hairpin RNAs 2 days before transfection of plasmid expressing an scFv or peptide-Fc fusion protein can prevent incorporation of up to 90% of the sulfate incorporated into same peptide produced in the presence of exgoneous TPST2 (Choe et al., 2003).

2.5. Uses of tyrosine-sulfated peptides Once generated, tyrosine-sulfated peptides and Fc-fusion proteins are used in a variety of assays. For example, they can block the binding of iodinated or [35S]-labeled ligand with receptor. Similarly, peptide can be used to inhibit the association of gp120/soluble CD4 complexes with CCR5 on the cell membrane, or an antibody recognizing the coreceptor-binding site of gp120. Sulfated peptides have been shown to complement a CCR5variant lacking its amino-terminus, but only in assays that can detect a transient association with receptor such as chemokine-mediated signaling

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monitered by calcium mobilization or an HIV-1 entry assay. Peptide-Fc fusion proteins can be used as antibodies to precipitate gp120, neutralize HIV-1 entry, or monitor conformational changes of the HIV-1 envelope glycoprotein expressed on the cell surface. With the introduction of structural elements such as disulfide bonds into these peptides and through elimination of hydrophobic residues that do not contribute to ligand binding, these peptides will be of further use in characterizing and inhibiting chemokine receptor and coreceptor function.

3. Study of Chemokine-Receptor Sulfation on the Plasma Membrane 3.1. Modulation of chemokine-receptor sulfation The study of tyrosine sulfation of intact chemokine receptors present an additional set of challenges, because the structure of the receptor ectodomain is determined by the transmembrane helices and cannot be manipulated in solution. These studies include binding assays with radiolabeled chemokine or gp120/CD4 complexes, signaling assays with an indicator of calcium mobilization, and HIV-1 entry assays quantified with an integrated reporter gene such as luciferase or green-fluorescent protein. Early study of tyrosine sulfate of cell-surface receptors used the TPST inhibitor chlorate to establish a functional role for tyrosine sulfation in receptor activity. However, because of its cytotoxity, chlorate can be used only in a narrow time window. Chlorate also inhibits the sulfation of O-glycosylation moieties and glycosaminoglycans, which typically promote lower affinity, low specificity interactions with chemokines and gp120. As with tyrosine sulfated peptides, a better current alternative for blocking TPST activity is the use of siRNA or shRNA targeting both sulfotransferases. As mentioned, shRNA can substantially diminish TPST activity to an extent detectable in functional assays. Because protein overexpressed in HEK293T cells can overwhelm the endogenous TPST activity of these cells, a functional role for tyrosine sulfate can also be established by comparison of receptor function in cells expressing exogenous TPST2 with shRNA or mock-transfected cells.

3.2. Mutagenesis of candidate sulfotyrosines Although these aforementioned assays can establish a role for tyrosine sulfation in chemokine receptor function, it is frequently important to know which receptor tyrosines are sulfated and which sulfotyrosines

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contribute most to function. Here mutagenesis is essential, and, as in peptide studies, alteration of tyrosine to aspartic acid is frequently preferable to alterations to phenylalanine. The extent of sulfation of wild-type and variant receptors can be quantitatively determined through comparison of [35S]cysteine and -methionine labeling to [35S]-sulfate incorporation into receptor. Functional assays of modified chemokine receptors require some means of measuring cell-surface expression, because removal of a sulfotyrsosine can have a suprisingly pronounced effect on receptor expression at the plasma membrane. Flow cytometric analysis can be used to quantify expression on the plasma membrane. This analysis can be performed with either an antibody recognizing a tag at the receptor amino-terminus, or, preferably, an antibody insensitive to chlorate treatment or to shRNA inhibition of the TPSTs. If a particular receptor variant expresses less efficiently than its wildtype counterpart, wild-type receptor expression should be varied by decreasing the amount of plasmid transfected. Although sometimes found in the literature, functional results should not be numerically normalized by dividing by expression levels, because expression and function rarely have a linear relationship.

4. Bacterial Expression of Tyrosine-Sulfated Peptides and Proteins 4.1. A system to introduce non-native amino acids into proteins A recent, major contribution to the study of tyrosine sulfation was made by Liu and Schultz (2006), who extended a novel system developed in the Schultz laboratory that permits introduction of synthetic amino acids into bacterially expressed proteins. This system uses a modified heterologous tRNA synthetase derived from Methanococcus jannashii to charge an M. jannashii amber tRNA with a nonnative amino acid. Liu and Schultz isolated a tRNA synthetase from a library of such enzymes positively selected to charge sulfotyrosine and negatively selected to avoid charging any other amino acids. The selected tRNA synthetase charges the M. jannashii amber tRNA, which then introduces sulfotyrosine during translation at any amber codon introduced into the gene. With this system, sulfotyrosine can be introduced into any site by modifying the corresponding codon to amber. To produce protein, plasmid bearing a modified gene is transformed into E. coli together with an additional plasmid encoding the heterologous tRNA/tRNA synthetase pair. Bacteria are grown in defined media in the presence of sulfotyrosine (see protocol below). As shown in Fig. 7.6, when sulfotyrosines are incorporated in this

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37 scFv 25

Figure 7.6 Bacterial expression of a tyrosine-sulfated 412d scFv. The open-reading frame of 412d scFv was cloned into bacterial expression vector pET11 (Novagen). A variant of this construct was made in which codons for two 412d heavy-chain CDR3 tyrosines were modified to amber (412d**, asterisks indicate amber-encoded sulfotyrosine). BL21(DE3) bacteria (Invitrogen) were transformed with pSUP-SY plasmid, which expresses both the M. jannashii amber suppressing tyrosyl tRNA (MjtRNATyrCUA) and the M. jannashii tyrosyl-transfer RNA synthetase (MjTyrRS) selected to charge the MjtRNATyrCUAwith sulfotyrosine. Bacteria were subsequently transformed with pET-scFv-412d or pET-scFv-412d**. Bacteria were grown overnight, diluted 1:100 in a defined media containing antibiotics and 10 mM sulfotyrosine, grown to an OD600 of 0.7, and induced with IPTG. Induction was continued for 24 h at room temperature; 15-ml aliquots of induced bacteria were lysed by boiling in SDS sample buffer, separated by SDS-PAGE, and blotted with an antibody that recognizes C9 tag at the scFv-C-terminus. Note that sulfotyrosines shift the mobility of the scFv variant and that no unsulfated scFv-412d** was detected.

manner at two sites in a single-chain antibody (scFv), the scFv expresses with comparable efficiency as the otherwise identical scFv encoding two unsulfated tyrosines.

4.2. Advantages and uses of the system This system has a number of advantages relative to chemical synthesis and mammalian expression systems for generating tyrosine-sulfated peptides and proteins. First, unlike chemical synthesis, there seems to be little limitation on number of sulfotyrosines incorporated, because peptides with as many as five sulfotyrosines express efficiently in this system. Second, in contrast to both mammalian expression and chemical synthesis, large quantities of proteins and peptides can be produced with standard bacterial expression protocols. Third, sulfotyrosine is incorporated homogenously at all desired sites. Fourth, the system does not depend on TPST activity, and it therefore allows introduction of a sulfotyrosine in amino-acid sequences that the mammalian TPSTs may not recognize. Finally, this system permits the phage-based selection of tyrosine-sulfated antibodies and peptides and has been recently used with phage display to generate de novo a tyrosine sulfated antibody that recognizes HIV-1 gp120 (Liu et al., 2008). Thus this system can begin to change the way tyrosine-sulfated proteins are produced, improved, and studied, ultimately allowing biologists to fully exploit the useful properties of sulfotyrosine.

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5. Protocols 5.1. Detection of sulfotyrosine of chemokine receptors 5.1.1. General considerations Sulfotyrosine can be detected through incorporation of radiolabeled sulfate into a chemokine receptor in which all glycosylation moieties have been removed. Removal of glycosylation is essential because carbohydrates are also frequently sulfated. Note that in conjunction with use of shRNA or exogenous TPSTs, this approach can obviate the need to show that sulfate is specifically incorporated at tyrosines with thin-layer chromotography, a more difficult and time-consuming approach (Corbeil et al., 2005). With a few exceptions it is difficult to immunoprecipitate endogenously expressed chemokine receptors from cell lysates, because few antibodies are available to do so. One exception is CXCR4, which can be precipitated from a number of cell lines, including HeLa cells, with the antibody 12G5 (R&D Systems). Generally instead a tag is added to the N- or C-terminus of the chemokine receptor. In most cases in our experience these tags do not disrupt function. Flag tag should be avoided at the amino-terminus, however, because the tag is highly acidic and its tyrosine itself is prone to sulfation. Note also that cells are lysed with sugar-based detergents such as DDM, cymal-5, or cymal-6 (Anatrace) rather than lipid-based detergents such as NP40 or Triton X100, because the former detergents permit more efficient extraction of the hydrophobic chemokine receptors. In addition, receptors are eluted off of protein A-Sepharose beads at 50 to 60  C rather than at boiling temperature to prevent aggregation and artifactual higher order bands in SDS-PAGE. 5.1.2. Radiolabeled reagents and labeling media To assess tyrosine sulfation of a given protein or peptide, we use [35S]cysteine and -methionine labeling (Perkin Elmer) to determine expression of the protein-of-interest and control proteins. Sulfate incorporation is measured with parallel labeling with [35S]-sulfate (Perkin Elmer). [35S]cysteine and -methionine labeling media is made by adding 50 mCi each of [35S]-cysteine and -methionine per ml of cysteine- and methionine-free cellculture media (Invitrogen or Sigma) containing, penicillin, streptomycin, glutamine, and 10% dialyzed fetal bovine serum (FBS, Invitrogen). [35S]sulfate labeling media is made by adding100 mCi of [35S]-sulfate per ml of sulfate-minus media (MEM, Sigma) containing 10% dialyzed FBS. Because cells need more sulfate than provided in 100 mCi [35S]-sulfate, for overnight labeling, unlabeled sodium sulfate is added to a final 1 mM concentration. Protocol: Detecting tyrosine sulfation of chemokine receptors 1. 3 to 4  106 HEK293T cells are plated onto T75 flasks. The following day, cells are transfected with a plasmid encoding tagged chemokine receptor and a plasmid encoding TPST2 at 10:1 ratio.

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2. The following day, cells are trypsinized, washed twice in phosphatebuffered saline (PBS), split at 1:5 ratio, resuspended in 1.5 ml of cysteine/ methionine-labeling media or 5 to 10 ml of sulfate-labeling media, and plated onto 1 (cysteine/methionine) or 3 (sulfate) wells of a 6-well plate. Because transfected HEK293T cells easily detach, polylysine-coated plates are recommended. 3. After overnight labeling, radioactive media is removed, and cells are either directly lysed in the wells or harvested in PBS containing 1 mM EDTA, and lysed in tubes, with 0.3 to 0.5 ml per well of 0.5% DDM or Cymal-5 (Anatrace) in PBS containing protease inhibitor cocktail (Sigma). 4. Cell debris is removed by microfuge centrifugation at 13,000 rpm for 10 min at 4  C, and tagged chemokine receptors are precipitated from the cleared lysate with anti-tag antibody and protein A-Sepharose at room temperature for 1 h. 5. Precipitates are washed three times with the same detergent used to lyse cells, once with PBS, and digested in a small volume (5 ml) containing protease inhibitor cocktail with 0.5 to 1 ml of N-glycosidase, endo F (PNGase F, New England Biolab), for 30 min at 37  C with intermittent mixing. Removal of N-glycosylation is useful, because sulfate can be associated with N- and O-glycosylation. 6. If removal of O-glycosylation is also necessary, wash N-glycosidase– digested samples once with 150 mM NaCl containing low concentration buffer (5 mM ) of neutral pH. Remove liquid completely, add a small volume (10 to 15 ml) of 1 O-glycosidase buffer containing O-glycosidase, neuraminidase, and protease inhibitor cocktail, and incubate for 1 h at 37  C with intermittent mixing. 7. At the end of digest, add reducing SDS-PAGE sample buffer directly to the samples, and incubate for 10 min at 50 to 60  C. As mentioned previously, boiling the samples will cause aggregation of chemokine receptors. 8. Resolve samples by SDS-PAGE, dry the gel, and expose it to an X-ray film. In most cases, chemical enhancing of signals is not necessary. Both [35S]-cysteine/-methionine and [35S]-sulfate signals should be detectable after overnight exposure.

5.2. Metabolic labeling of peptide-Fc fusion proteins and removing the Fc domain 5.2.1. General considerations 1. Peptide-Fc fusion proteins precipitated onto protein A-Sepharose beads are washed an additional time with 150 mM NaCl/20 mM Tris, pH 8.4. Liquid is removed completely, and 10 to 20 U of thrombin (Novagen) in a

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small volume is added into beads, and incubate at 37  C for 1 h with intermittent mixing. If protease inhibitors are used during immunoprecipitation and thrombin digestion, those of serine protease should be excluded. 2. Add 50 to 200 ml of PBS, vortex, spin beads, and transfer supernatant to a new tube. Repeat this step, combine the supernatant, and spin once again to pellet residual beads. Care should be taken not to include the beads, because they clog the membrane used in the next step. 3. Transfer this supernatant into Microcon centrifugal filter unit (Millipore) with 3 or 10 kDa molecular-weight cutoff (YM-3 or YM-10), spin in the microcentrifuge, and collect filter-through containing cleaved peptides. Thrombin and any contaminating Ig portion of the molecules are retained above the filter. The peptide can then be used in proteinbinding assays (as in Fig. 7.3) or for other functional studies.

5.3. Inhibiting tyrosyl-protein sulfotransferae activity with small-hairpin RNAs 5.3.1. General considerations The functional role of sulfotyrosines of chemokine receptors can be examined by modulating receptor sulfation or by mutating sulfated tyrosines. As shown in Fig. 7.5 for an scFv, tyrosine sulfation can be modulated with RNA interference with shRNAs, or, if the protein is overexpressed, by including exogenous TPST2. If interefering RNAs are used, cells have to be grown for at least 2 days after transfection with shRNA before they are used in functional assays to reduce the effect of previously translated TPST. In our experience, shRNA sequences derived from nucleotides 259 to 276 of the TPST1 gene (GCCATGCTGGACGCACAT) and nucloetides 73 to 92 of the TPST2 (GGACAGCAGGTGCTAGAGTG), transcribed by U6 promoter, substantially reduce TPST activities.

5.4. Cell-free sulfation of tyrosine-containing peptides 5.4.1. General considerations Tyrosine sulfation of peptides can be carried out in vitro with purified TPSTs and the sulfate donor, PAPS. Ig-fusion forms of TPST ectodomains (residues 25 through 370 of TPST1, and 25 through 396 of TPST2) can be produced efficiently and retain their enzymatic activities. Because in our hands TPST2-Ig more efficiently sulfates tyrosines on a CCR5-derived peptide than TPST1-Ig, the remainder of this protocol used TPST2-Ig. TPST2-Ig proteins are produced from transfected HEK293T cells into a serum-free media (Free-Style; Invitrogen). Figure 7.4 shows TPST2-Ig sulfation of four tyrosines on synthetic peptides derived from amino terminal 22 residues of CCR5 (MDYQVSSPIYDINYYTSEPSQK).

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Protocol: Cell-free sulfation of syntheticpeptides 1. TPST-Ig proteins produced in Free-Style media are bound to protein A-Sepharose and washed twice with 0.5 M NaCl/PBS and twice with PBS. 2. Beads containing approximately 0.2 ug of TPST-Ig, determined by analyzing an aliquot by SDS-PAGE, are mixed with 2.5 ug of peptide (1 nMoles) and 4 mCi (2 nMoles) of [35S]-PAPS (Perkin Elmer) in total volume of 100 ml, and incubated at 37  C. 3. At various time points up to 24 h, aliquots are taken, beads pelleted, and supernatants are analyzed by SDS-PAGE on a 10 to 20% gradient Tricine gel. Note that sulfation efficiency varies with sequence and number of target tyrosines.

5.5. Expression of tyrosine-sulfated proteins in E. coli 5.5.1. General considerations Although bacteria do not have a mechanism to incorporate sulfate into tyrosines, a novel system for introducing sulfotyrosines during translation in bacteria has been developed. Bacteria are sequentially transformed with two plasmids: one expressing the tRNA/tRNA synthetase pair (pSUP-SY, a generous gift from Chang Liu and Peter Schultz), and one encoding the protein-of-interest, whose gene is modified so that the amber codon (TAG) is introduced at sites where sulfotyrosine is desired. (Note that the natural stop codon should be altered if it is an amber.) Apart from supplementing culture media with sulfotyrosine (Bachem), standard bacterial expression protocols can be used. We transformed BL21(DE3) bacteria (Invitrogen) with pSUP-SY, made these transformed bacteria chemically competent, and transformed them with a pET11 vector expressing a single-chain form of the tyrosine-sulfated antibody 412d, modified to amber at sites encoding its sulfated tyrosines (pET11-scFv-412d**). A control plasmid in which the tyrosine codons are not replaced is also characterized (pET11-scFv-412d). The results are shown in Fig. 7.6. Protocol: Expression of a sulfated single-chain antibody in E. coli 1. Transform BL21(DE3) with pSUP-SY plasmid, and grow at 37  C in the presence of 30 mg/ml chloramphenicol. Wait for 2 days, because any colonies that appear within 1 day tend to have deletion of tRNA gene, because overexpressed tRNA is toxic. Also, large colonies likely have tRNA-gene deletion. 2. Expand a few colonies, extract plasmids, and sequence these to confirm that tRNA and synthetase genes are not deleted. 3. Prepare competent bacteria from a selected colony with standard methods, transform pET11 plasmid containing the gene-of-interest

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6. 7.

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bearing amber codons, and grow on plates containing 30 mg/ml of chloramphenicol and 100 mg/ml of ampicillin. A colony resistant to both antibiotics and, therefore, harboring both plasmids is grown overnight in LB containing 30 mg/ml of chloramphenicol and 100 ug/ml of ampicillin. Dilute the overnight culture 1:100 into GMML (1  M9 salt, 1% glycerol, and 0.3 mM leucine), and grow to saturation at 37  C. Dilute this culture 1:20 in GMML supplemented with up to 15 mM sulfotyrosine (Bachem), and grow with shaking at room temperature. During this step and induction, use 50 mg/ml ampicillin and 15 mg/ml chloramphenicol. At 0.6 to 0.7 of OD600, add IPTG to final 1 mM. Grow bacteria transformed with the wild-type gene for 2 h at 37  C, and those containing amber mutations for 12 to 48 h at room temperature. Check induction level by aliquoting 20 ml of bacteria suspension at various time points with and without induction. Boil these aliquots directly in reducing SDS-PAGE sample buffer, separate by SDS-PAGE, and visualize by Coomassie staining. To visualize the induced protein, the gel is transferred to PVDF membrane and blotted with an antibody that recognizes the protein or a tag. Sulfated and unsulfated proteins can be usually distinguished by their mobilities on a polyacrylamide gel; larger sulfated proteins tend to migrate more slowly (Fig. 7.6), whereas sulfated peptides tend to run faster (Fig.7.4). In both cases, this mobility shift is proportional to the number of sulfates.

6. Conclusions Despite the observation by Hutter in 1982 that the tyrosines of many proteins expressed in mammalian cells are modified by sulfate, it took a number of years to recognize the functional importance of these sulfotyrosines. Perhaps because of their unique biophysical properties, sulfotyrosines are frequently found at sites of protein–protein interactions, including interactions necessary for at least two important human pathogens. The discovery of the TPST enzymes began to make possible not just the scientific characterization but also the production and manupulation of tyrosine-sulfated proteins. The development of bacterial systems in which sulfotyrosine is genetically encoded will likely transform the way we improve, produce, and use tyrosine-sulfated peptides and proteins. This technology may make possible novel therapeutics including peptides and antibodies that control replication of pathogens or modulate inflammatory responses mediated by chemokine receptors and related proteins.

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Tyrosine-sulfated peptides functionally reconstitute a CCR5 variant lacking a critical amino-terminal region. J. Biol. Chem. 277, 40397–40402. Farzan, M., Mirzabekov, T., Kolchinsky, P., Wyatt, R., Cayabyab, M., Gerard, N. P., Gerard, C., Sodroski, J., and Choe, H. (1999). Tyrosine sulfation of the amino terminus of CCR5 facilitates HIV-1 entry. Cell 96, 667–676. Farzan, M., Schnitzler, C. E., Vasilieva, N., Leung, D., Kuhn, J., Gerard, C., Gerard, N. P., and Choe, H. (2001). Sulfated tyrosines contribute to the formation of the C5a docking site of the human C5a anaphylatoxin receptor. J. Exp. Med. 193, 1059–1066. Farzan, M., Vasilieva, N., Schnitzler, C. E., Chung, S., Robinson, J., Gerard, N. P., Gerard, C., Choe, H., and Sodroski, J. (2000). A tyrosine-sulfated peptide based on the N terminus of CCR5 interacts with a CD4-enhanced epitope of the HIV-1 gp120 envelope glycoprotein and inhibits HIV-1 entry. J. Biol. Chem. 275, 33516–33521. Fong, A. M., Alam, S. M., Imai, T., Haribabu, B., and Patel, D. D. (2002). CX3CR1 tyrosine sulfation enhances fractalkine-induced cell adhesion. J. Biol. Chem. 277, 19418–19423. Gao, J., Choe, H., Bota, D., Wright, P. L., Gerard, C., and Gerard, N. P. (2003). Sulfation of tyrosine 174 in the human C3a receptor is essential for binding of C3a anaphylatoxin. J. Biol. Chem. 278, 37902–37908. Gutierrez, J., Kremer, L., Zaballos, A., Goya, I., Martinez, A. C., and Marquez, G. (2004). Analysis of post-translational CCR8 modifications and their influence on receptor activity. J. Biol. Chem. 279, 14726–14733. Huang, C. C., Lam, S. N., Acharya, P., Tang, M., Xiang, S. H., Hussan, S. S., Stanfield, R. L., Robinson, J., Sodroski, J., Wilson, I. A., Wyatt, R., Bewley, C. A., and Kwong, P. D. (2007). Structures of the CCR5 N terminus and of a tyrosine-sulfated antibody with HIV-1 gp120 and CD4. Science 317, 1930–1934. Huttner, W. B. (1982). Sulphation of tyrosine residues-a widespread modification of proteins. Nature 299, 273–276. Huttner, W. B. (1984). Determination and occurrence of tyrosine O-sulfate in proteins. Methods Enzymol. 107, 200–223. Kehoe, J. W., and Bertozzi, C. R. (2000). Tyrosine sulfation: A modulator of extracellular protein-protein interactions. Chem. Biol. 7, R57–R61. Liu, C. C., Mack, A. V., Tsao, M. L., Mills, J. H., Lee, H. S., Choe, H., Farzan, M., Schultz, P. G., and Smider, V. V. (2008). Protein evolution with an expanded genetic code. Proc. Natl. Acad. Sci. USA 105, 17688–17693. Liu, C. C., and Schultz, P. G. (2006). Recombinant expression of selectively sulfated proteins in Escherichia coli. Nat. Biotechnol. 24, 1436–1440. Moore, K. L. (2003). The biology and enzymology of protein tyrosine O-sulfation. J. Biol. Chem. 278, 24243–24246. Ouyang, Y., Lane, W. S., and Moore, K. L. (1998). Tyrosylprotein sulfotransferase: purification and molecular cloning of an enzyme that catalyzes tyrosine O-sulfation, a common posttranslational modification of eukaryotic proteins. Proc. Natl. Acad. Sci. USA 95, 2896–2901. Ouyang, Y. B., and Moore, K. L. (1998). Molecular cloning and expression of human and mouse tyrosylprotein sulfotransferase-2 and a tyrosylprotein sulfotransferase homologue in Caenorhabditis elegans. J. Biol. Chem. 273, 24770–24774. Pouyani, T., and Seed, B. (1995). PSGL-1 recognition of P-selectin is controlled by a tyrosine sulfation consensus at the PSGL-1 amino terminus. Cell 83, 333–343. Preobrazhensky, A. A., Dragan, S., Kawano, T., Gavrilin, M. A., Gulina, I. V., Chakravarty, L., and Kolattukudy, P. E. (2000). Monocyte chemotactic protein-1 receptor CCR2B is a glycoprotein that has tyrosine sulfation in a conserved extracellular N-terminal region. J. Immunol. 165, 5295–5303.

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Ryu, Y., and Schultz, P. G. (2006). Efficient incorporation of unnatural amino acids into proteins in Escherichia coli. Nat. Methods 3, 263–265. Sako, D., Comess, K. M., Barone, K. M., Camphausen, R. T., Cumming, D. A., and Shaw, G. D. (1995). A sulfated peptide segment at the amino terminus of PSGL-1 is critical for P-selectin binding. Cell 83, 323–331. Seibert, C., Cadene, M., Sanfiz, A., Chait, B. T., and Sakmar, T. P. (2002). Tyrosine sulfation of CCR5 N-terminal peptide by tyrosylprotein sulfotransferases 1 and 2 follows a discrete pattern and temporal sequence. Proc. Natl. Acad. Sci. USA 99, 11031–11036. Seibert, C., and Sakmar, T. P. (2008). Toward a framework for sulfoproteomics: Synthesis and characterization of sulfotyrosine-containing peptides. Biopolymers 90, 459–477. Seibert, C., Veldkamp, C. T., Peterson, F. C., Chait, B. T., Volkman, B. F., and Sakmar, T. P. (2008). Sequential tyrosine sulfation of CXCR4 by tyrosylprotein sulfotransferases. Biochemistry 47, 11251–11262. Suiko, M., Fernando, P. H., Sakakibara, Y., Nakajima, H., Liu, M. C., Abe, S., and Nakatsu, S. (1992). Post-translational modification of protein by tyrosine sulfation: active sulfate PAPS is the essential substrate for this modification. Nucleic Acids Symp. Ser. 183–184. Wu, L., Gerard, N. P., Wyatt, R., Choe, H., Paralin, C., Ruffing, N., Borsetti, A., Cardosa, A. A., Desjardin, E., Newman, W., Gerard, C., and Sodroski, J. (1996). CD4-induced interactions of primary HIV-1 gp120 glycoproteins with the chemokine receptor CCR-5. Nature 184, 179–183.

C H A P T E R

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Activation Mechanisms of Chemokine Receptors Pia C. Jensen and Mette M. Rosenkilde Contents 1. 2. 3. 4.

Introduction Current Models for 7TM Receptor Activation Constitutive Activity of 7TM Receptors Activation of Chemokine Receptors by Small-Molecule Agonists 4.1. CCR8 small molecules–semiclassic pharmacophores for CC-chemokine receptors 4.2. CXCR3—small-molecule anchorage 4.3. CCR1—allosteric modulators 5. Experimental Procedures 6. IP3 Assay in Transiently Transfected COS-7 Cells 6.1. Detailed protocol References

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Abstract Chemokine receptors belong to the large family of 7-transmembrane (7TM) G-protein–coupled receptors. These receptors are targeted and activated by a variety of different ligands, indicating that activation is a result of similar molecular mechanisms but not necessarily similar modes of ligand binding. Attempts to unravel the activation mechanism of 7TM receptors have led to the conclusion that activation involves movements of the transmembrane segments VI and VII in particular, as recently gathered in the Global Toggle Switch Model. However, to understand the activation mechanism completely, more research has to be done in this field. Chemokine receptors are interesting tools in this matter. First, the chemokine system has a high degree of promiscuity that allows several chemokines to target one receptor in different ways, as well as a single chemokine ligand to target several receptors in different ways. Second, the endogenous ligands are large proteins that mainly activate their cognate receptors by interacting with various extracellular-located receptor regions.

Department of Neuroscience and Pharmacology, Laboratory for Molecular Pharmacology, The Panum Institute, University of Copenhagen, Copenhagen, Denmark Methods in Enzymology, Volume 461 ISSN 0076-6879, DOI: 10.1016/S0076-6879(09)05408-1

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It is, however, also possible to introduce agonism of simple ligands like metal ions. Thus, the chemokine system offers the possibility to test and compare the activation profiles of several chemically diverse ligands. This also brings up the interesting discussion of allosterism, because small molecules in the chemokine field often interact with allosteric receptor sites.

1. Introduction With more than 700 members, 7-transmembrane (7TM) G-protein– coupled receptors (GPCR) make up the largest superfamily of proteins in the human organism. Of the six subgroups (family A to F, based on sequence homology), family A (also known as the rhodopsin-like receptors) is by far the largest and most exploited (Gether, 2000; Schwartz, 1996). Chemokine receptors are found as a subgroup of the latter and count up to approximately 25 members (Murphy et al., 2000). 7TM receptors, in general, are activated by a diversity of endogenous chemical agents and exogenous stimuli such as peptides, ions, biogenic amines, lipids, nucleotides, odors, light, and taste (Okuno et al., 2008). Chemokines contain 70 to 80 amino acids, yet despite this (relatively) large ligand size, several nonpeptide agonists and antagonists have been identified within the chemokine system (Fig. 8.1). The huge ligand diversity within 7TM receptors indicates that receptor activation is not necessarily dependent on agonists binding to a specific set of residues in the conserved structure. That is, there is no common lock for all agonists (Schwartz and Rosenkilde, 1996a). It is, however, believed that a general activating mechanism is common for all 7TM receptors, irrespective the chemical nature of the agonist or the binding site (Schwartz and Rosenkilde, 1996b; Schwartz et al., 2006). Palczewski and colleagues (2000) published the first crystal structure of a mammalian 7TM receptor, the bovine rhodopsin in an inactive state, and in the following years the crystallization field was relatively silent. However, in 2007 and 2008 the field ‘‘exploded’’ with several convincing crystals of not only rhodopsin but also the b2- and b1-adrenergic receptors and the Adenosin A2 receptor (Hanson et al., 2008; Jaakola et al., 2008; Palczewski et al., 2000; Rasmussen et al., 2007; Warne et al., 2008). These crystals are all depicting receptors in inactive states constrained by antagonists or inverse agonists and by antibodies, T4-lysozyme fusion-constructs, or stabilizing receptor mutations (Hanson et al., 2008; Jaakola et al., 2008; Palczewski et al., 2000; Rasmussen et al., 2007; Warne et al., 2008). As a temporary climax, the first crystal structure of a 7TM receptor in a G-protein–interacting (active!!) conformation was presented in September 2008 (Scheerer et al., 2008). In this structure, the activated state of the receptor was mimicked by crystallizing opsin in complex with the main

CCR2 antagonist

CCR5 antagonists

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Pfizer UK-427,857 (Maraviroc)

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ZK 756326 (uM)

Figure 8.1 Selection of small-molecule CC-chemokine receptor antagonists and agonists. The chemical compounds share a similar pharmacophore with a centrally located amine flanked by aromatic groups (except for ZK 756326 with aromatic groups only at one side). From left, the CCR2 antagonist: RS-504393 (10-[2-(5-methyl-2-phenyloxazol-4-yl)ethyl]-6-methylspiro{4H-3,1-benzoxazine-4,40 -piperidin}2(1H)-one) (Berkhout et al., 2003; Mirzadegan et al., 2000), the CCR5 antagonists: UK-427,857 (Maraviroc or 4,4-difluoro-N-((1S)3-{(3-endo)-3-[3-methyl-5-(1-methylethyl)-4H-1,2,4-triazol-4-yl]-8-azabicyclo[3.2.1]oct-8-yl}-1-phenylpropyl)cyclohexanecarboxamide) (Dorr et al., 2005) and GSK-873140 (Aplaviroc or 4-{[4-({(3R)-1-butyl-3-[(R)-cyclohexyl(hydroxy)methyl]-2,5dioxo-1,4,9-triazaspiro[5.5] undec-9-yl}methyl)phenyl]oxy}benzoic) (Watson et al., 2005), and the CCR8 agonists: LMD-174 N-(1-(3-(2-methoxyphenoxy)benzyl) piperidin-4-yl)-1,2,3,4-tetrahydro-2-oxoquinoline-4-carboxamide, LMD-009 (8-[3-(2-methoxyphenoxy)benzyl]-1-phenethyl-1,3,8-triazaspiro[4.5]decan-4-one) ( Jensen et al., 2007) and ZK 756326 (2-[2-[4-(3-phenoxybenzyl)piperazin-1-yl]ethoxy]ethanol) (Haskell et al., 2006).

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peptide fragment of the interacting Ga-protein on the intracellular side. In comparison with previous published structures, this structure revealed outward movements of TM-VI and -VII on the intracellular side, making room for the binding of the Ga-protein (Scheerer et al., 2008), and thus mimicked the recently published opsin structure (Park et al., 2008). However, because these receptors were not coupled to an agonist, it is difficult to explain activation movements on the extracellular side. Even though the structure of an active 7TM receptor was unknown until recently, site-directed spin labeling studies combined with electron paramagnetic resonance have been a very useful tool in uncovering the helical movements during activation (Altenbach et al., 2008; Farrens et al., 1996; Hubbell et al., 2000, 2003). In accordance with the recent structure(s) of active 7TM receptor(s) (Park et al., 2008; Scheerer et al., 2008), several of these studies conclude that receptor activation involves outward movements of the helices—especially TM-VI and -VII—on the intracellular site, making space for the G-protein and/or arrestin to interfere with receptor motifs (Altenbach et al., 2008; Farrens et al., 1996; Hubbell et al., 2000, 2003). As the extracellular movements have proven difficult to explain by these methods, other techniques, such as metal-ion constrainment have been used. Metal-ions are the smallest and best understood naturally occurring 7TM receptor ligands with well-defined coordination, and reliable distance constraints can be obtained by making these ions work as potent agonists or antagonists in 7TM receptors (Elling and Schwartz, 1996; Elling et al., 2006; Holst et al., 2002; Kledal et al., 1997; Lagerstrom et al., 2003; Rosenkilde et al., 1998, 2006, 2007). Thus, by use of the b2-adrenergic receptor as a test model, Elling and coworkers introduced a metal-ion binding site in the major binding pocket (the binding crevice delimited by TM-III, -IV, -V, -VI, and -VII) to mimic the activation mechanism of the endogenous monoamines (Elling et al., 2006). The attachment point of monoamines in TM-III (Asp in position III:08) (Strader et al., 1991) was chosen as starting point for the metal-ion anchorage, and a tridentate metal-ion binding site was introduced between the TM-III, -VI and -VII (position III:08, VI:16, and VII:06) by site-directed mutagenesis (Fig. 8.3). On the basis of the X-ray structure of the inactive state of rhodopsin (Palczewski et al., 2000), computer simulations were made and distances calculated among these three positions. This model revealed that the distances between the three metalion binding residues were too long to form a binding site in the inactive conformation and that these three helices consequently approach each other during receptor activation (Elling et al., 2006). Concluding experiments in this field were recently gathered and described as a Global Toggle Switch Model (Schwartz et al., 2006). This model accommodates both the outward movements of TM-VI and -VII on the intracellular side and the inward movements of the helices on the extracellular side and provides a general activation model of class A 7TM

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receptors independent of the chemical structure or binding site of the agonists. Importantly, metal-ion site engineering in CXCR3 has confirmed this model (as described in detail later in this chapter).

2. Current Models for 7TM Receptor Activation Members of family A 7TM receptors are characterized by having highly conserved residues distributed along the transmembrane helices. Among these are the five proline residues in TM-II, -IV, -V, -VI, and -VII (Mirzadegan et al., 2003). These residues serve as helix breakers, because they, in contrast with any other naturally occurring amino acid, are unable to form the necessary a-helix stabilizing hydrogen bond to the backbone carbonyl oxygen of residue i-4 (MacArthur and Thornton, 1991). Thus, there are visible (more or less centered) kinks in the transmembrane segments that are most pronounced in TM-IV, -VI, and -VII. On the basis of the properties of these highly conserved helical kinks, the Global Toggle Switch Model describes the activation mechanism as a vertical seesaw movement of TM-VI and -VII. That is, with the proline kinks as pivots, oppositely directed movements of the two halves of TM-VI and -VII close the main binding crevice around the ligand on the extracellular side, while making space for the G-protein and/or arrestin on the intracellular side (Schwartz et al., 2006). A resting 7TM receptor is constrained through various molecular interactions that have to be broken to activate the receptor. The DRY motif (Asp, Arg, Tyr), which is highly conserved among family A receptors, is of special importance. This historically well-characterized motif is located on the intracellular side of TM-III, and is believed to work as an ionic lock in certain rhodopsin-like 7TM receptors (Ballesteros et al., 2001). In consistency with the dark-state crystal structure of rhodopsin (Palczewski et al., 2000), mutational analyses have located the ionic interaction partner of the Arg to a conserved Glu residue in the intracellular end of TM-VI (in position VI:-06 or 6.30). However, this does not sufficiently describe the activation mechanism of all 7TM receptors, because 30% of all family A receptors (including all chemokine receptors) contain a positively charged residue at the proposed site of interaction. This indicates that the inactive state of 7TM receptors is maintained by a complex network of interhelical interactions, of which the DRY motif seems to play an important role for certain receptor subgroups (Springael et al., 2007). Likewise, the Asp residue in this motif has been identified as being crucial in constraining the inactive conformation, because substitution with residues mimicking its protonated state (i.e., mimicking the activated receptor) results in agonist-independent activation (Rasmussen et al., 1999). Besides the DRY motif, sequence alignment of family A receptors has revealed a conserved NPYxxY(X)5,6F sequence that connects TM-VII to

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the intracellular helix 8 through aromatic interactions (Fritze et al., 2003). By mutational analysis of this motif, it has been shown that release of constraints results in receptor activation (Fritze et al., 2003), consistent with previous observations of helix 8 rearrangements during activation (Altenbach et al., 1999). A third important microdomain involved in receptor activation is the highly conserved CWLP motif in the center of TM-VI. In the inactive structure of rhodopsin, the Trp residue is positioned vertically toward TM-VI, possibly stabilized by hydrogen bonds in TM-III and -VII in a conformation that prevents the inward movement of TM-VI (Shi et al., 2002). NMR studies have shown that this residue changes interaction partners during activation by rotating toward TM-III and -V (Patel et al., 2004). Thus, receptor activation seems to happen by a rotametric shift of this residue, resulting in the straightening of the proline kink in TM-VI (Schwartz et al., 2006).

3. Constitutive Activity of 7TM Receptors As described previously, receptor activation is a complex matter of molecular interactions involving several microdomains and switches. The common understanding of receptor activation is that these movements are induced on binding of the agonist (induced-fit model) (Koshland, 1958). An alternate theory is that the agonist acts simply by constraining the receptor in an active conformation (conformational selection model) (Monod et al., 1965). It is, however, most likely that agonist-mediated receptor activation occurs as a combined act of induced fit and conformational selection (Schwartz, 1996; Schwartz and Rosenkilde, 1996a). It is well known that receptor activation can happen in the absence of agonists in so-called constitutively activated receptors, as described in 1982 for the first time (Koski et al., 1982) and further explained by Costa and Herz (1989). Thus, Costa and Herz discovered ligands that affected the basal GTPase activity in a negative intrinsic manner—a phenomenon known today as inverse agonism. Today it is clear that constitutive activity is an intrinsic property of most 7TM receptors. It is also evident that constitutive activity can be induced or attenuated by single point mutations, not only in the suggested ionic locks as previously described (Acharya and Karnik, 1996; Gruijthuijsen et al., 2004; Lu et al., 1997; Rosenkilde et al., 2005; Rosenthal et al., 1993; Scheer et al., 1996; Wess, 1998) but also in diverse regions of the specific subtype. In the ghrelin receptor, for example, the constitutive activity of approximately 50% has been determined by aromatic interactions between residues in the interface of the extracellular ends of TM-VI and TM-VII (Holst et al., 2004). To test the general impact of this aromatic cluster in other family A receptor subtypes, an aromatic pocket at the given

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positions was introduced in CCR8 and importantly resulted in an increase in the constitutive activity from 8% of CCR8 WT to approximately 30% ( Jensen et al., 2007). In the orphan Epstein-Barr virus–induced receptor 2 (EBI-2) a region located in the top of TM-II was recently shown to be important for the constitutive activity, because substitution of Arg87 in position II:20 to Ala and Glu totally abolished receptor activity without affecting receptor surface expression (Benned-Jensen and Rosenkilde, 2008) Importantly, the constitutive activity of the Arg-to-Glu [R87E] substitution in position II:20 could be rescued by introduction of a salt bridge from GluII:20 to position III:03 (by substitution of Ile106 to Arg, [I106R]), and thereby strengthened the importance of this region (TM-II/TM-III interface) for constitutive receptor activation (Benned-Jensen and Rosenkilde, 2008, 2009).

4. Activation of Chemokine Receptors by Small-Molecule Agonists The chemokine system plays essential roles in the development and function of the immune system-most importantly through the control of leukocyte migration and differentiation but also in developmental processes during embryogenesis (Luster, 1998). From a drug-development point of view, chemokine receptors are interesting targets for various (auto)-immune and inflammatory diseases (Ribeiro and Horuk, 2005). Therefore, the development of nonpeptide ligands against chemokine receptors has been of huge focus in many big pharmaceutical companies (such as Glaxo-Smith-Kline/ Millenneum, Merck and Novartis (Godessart, 2005)). The discovery and receptor mapping of both nonpeptide agonists and antagonists are important generalizing tools for uncovering the activation mechanism for family A 7TM receptors. It is in that respect highly interesting that chemokine receptors, which normally are targeted by large peptide ligands (70 to 80 amino acid ligands), can be activated by small-molecule agonists binding to allosteric sites. The molecular mechanisms of action of small-molecule agonists on three different chemokine receptors are described in the following, and even though the chemical nature of the ligands and their exact interaction points varies (but overlap considerably), it seems that the overall mechanism of activation is similar.

4.1. CCR8 small molecules–semiclassic pharmacophores for CC-chemokine receptors Most nonpeptide antagonists targeting chemokine receptors are characterized by being relatively elongated structures, carrying one or two centrally located positively charged amines flanked by bilateral aromatic groups (Fig. 8.1).

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These common features can be coupled to the fact that a Glu in the top of TM-VII (position VII:06) is selectively conserved among chemokine receptors (74% occurrence) in contrast to nonchemokine receptors (0.5% occurrence) (Rosenkilde and Schwartz, 2006). Several studies have proven the importance of this residue as an anchor point for the positively charged amine, thereby bridging the ligand between the minor and the major binding pocket, as reviewed in Rosenkilde and Schwartz (2006). Screening efforts for identifying CCR8 selective antagonists have proven difficult, because most small-molecule ligands turned out to be agonists. The first CCR8 targeting nonpeptide agonist ZK 756326 was reported by Haskell and coworkers (Haskell et al., 2006) (Fig. 8.1). Concomitantly, five other nonpeptide CCR8 agonists were identified, and their interaction with CCR8 was mapped ( Jensen et al., 2007). All of these agonists share similar chemical groups, because they carry a centrally located amine in the elongated structure and a biphenyl group at one side of the amine. However, whereas the initial compound ZK 756326 that activates CCR8 with micromolar potency contains an aliphatic group at the other side of the amine, the more potent (nanomolar potencies) compounds LMD-009, -584-902, -268, and 174 contain bilateral aromatic groups, which putatively increase the potencies by a deeper anchorage in the major binding pocket (Fig. 8.1). These compounds, with a structure similar to classical chemokine antagonists, targeted CCR8 with high specificity, as they neither activated nor antagonized any other known human chemokine receptors ( Jensen et al., 2007). Mutational mapping revealed that they—as expected from their structures—used GluVII:06 as an anchor point and interfered with residues in both the minor and the major binding pockets (Fig. 8.2) (i.e., similar to the proposed binding for most CC chemokine receptor antagonists) as reviewed in Rosenkilde and Schwartz (2006). One particularly interesting observation was that an Ala substitution of Phe in the top of TM-VI (position VI:16) resulted in a gain of potency, as well as efficacy of one of the agonists (LMD-009) (Fig. 8.2). Computational modeling revealed that this substitution made it possible for LMD-009 to dock deeper into the major binding pocket, which according to the Global Toggle Switch Model, could be interpreted as a gain of flexibility of TM-VI and a subsequent tighter constrainment toward TM-III (Fig. 8.2).

4.2. CXCR3—small-molecule anchorage In a recent work from our group, CXCR3 was used as an example to prove the Global Toggle Switch Model (Rosenkilde et al., 2007). The hypothesis behind the CXCR3 experiment was that a small compound could be tethered into acting as a highly efficacious agonist by anchoring and stabilizing an inward movement of TM-VI and -VII toward TM-III in CXCR3 (Rosenkilde et al., 2007).

PheVI:16

Superagonism of LMD-009 by changed binding pocket 200

[F254A]-CCR8

GluVII:06

PheVI:16 to Ala

GluVII:10

% of CCL1 activation

CCR8 WT

150

[F254]-CCR8

100 50

CCR8 WT

0 0 −10 −9 −8 −7 −6 −5 Log. conc. LMD-009 (M)

Figure 8.2 Molecular modeling of the interaction of LMD-009 with CCR8wt and [F254A]-CCR8. From left, interaction of the smallmolecule agonist LMD-009 with CCR8 wt and with the single-mutated receptor in which Phe254 was substituted with Ala [F254A]-CCR8 at positionVI:16.The curves illustrate the superagonism of LMD-009 with increases in potency, as well as efficacy introduced by the space-created mutation [F254A] at positionVI:16. COS-7 cells were transiently transfected with chemokine receptor and the promiscuous Gqi4myr, and the activity was measured as IP3 accumulation. Data redrawn from Jensen et al. (2007).

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A

B

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Zn++ Bip

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PheIII:08

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TyrVI:16

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TM-VI

TM-VI

TM-I

TM-I TM-VII

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CXCR3-Activation by metal-ion chelator complex

b2-Adrenergic receptoractivation by metal-ion alone

Figure 8.3 Molecular modeling of metal-ion/metal-ion chelator complex ending in CXCR3 and in the b2 -adrenergic receptor. Both models were built over the inactive structure of rhodopsin. In CXCR3, the metal-ion is believed to anchor between His128 and Asp186 in positions III:05 and IV:20, respectively, and the chelator interacting with Tyr271 in position VI:16, stabilized by an aromatic zipper formed by residues in TM-III (Phe131 in III:08) and in TM-VII (Tyr308 in VII:10. In the b2 -adrenergic receptor, the metal-ion binding site was built between TM-III (HisIII:08), -VI (CysVI:16) and -VII (CysVII:06). In both models, it is clear that the residues in the inactive structure cannot participate in the binding, because the distances are to long. Thus, agonism occurs only on an inward movement of TM-VI and -VII (as highlighted by yellow arrows) in accordance to the Global Toggle Switch Model. The receptor models are adapted from data in Elling et al. (2006) and Rosenkilde et al. (2007).

On the basis of the knowledge of other family A 7TM receptors, a metal-ion binding site was introduced in the major binding pocket between the top of TM-III and -IV (between HisIII:05 and the naturally occurring AspIV:20) by substitution of SerIII:05 with His [S110H]-CXCR3. The free metal ions Cu(II) or Zn(II) did not activate CXCR3, but in complex with a chelator—bipyridine or phenanthroline (which did not have any agonistic effect on their own)—they activated the receptor with high potency and efficacy. In fact, the metal-ion chelator complexes acted as superagonists with higher efficacies compared with the three endogenous chemokines CXCL9-11 (Rosenkilde et al., 2007). By site-directed mutagenesis, the Tyr in position VI:16 was identified as the second-site interaction partner stabilized by an aromatic zipper formed by residues in TM-III (Phe131 in III:08) and in TM-VII (Tyr308 in VII:10). Molecular modeling and simulations of these results supports the Global Toggle Switch Model as the aromatic zipper was formed only on inward movements of TM-VI and -VII (indicated by yellow arrows in Fig. 8.3). It is important to note that none of the mutations destroyed the ability of endogenous chemokine activation by CXCL11, thereby emphasizing that chemokine activation occurs through interactions with more extracellular interactions (like Velcro) (Allen et al., 2007; Rosenkilde et al., 2007).

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Besides supporting the expected helical movements, the experiments in CXCR3 show that the stabilization of an active conformation is not a simple event, because it—in CXCR3—depends on a second row (second-side interaction with chelator) and a third row (stabilizing aromatic zipper) interaction (Rosenkilde et al., 2007).

4.3. CCR1—allosteric modulators There are today numerous examples of allosteric compounds targeting 7TM receptors in the medicinal industry; that is, compounds targeting a topographically distinct (allosteric) binding site compared with the binding site of the endogenous ligand (at the orthosteric site). In strict terms, allosteric ligands function by modulating the binding and/or the signaling of the (orthosteric) ligands in a positive or negative manner and do not posses any activities on their own (May et al., 2007). However, numerous articles have emphasized that allosteric compounds may have efficacies on their own acting either as allosteric agonists (also suggested to be denoted ago-allosteric compounds Schwartz and Holst, 2006)) or allosteric inverse agonists (Christopoulos and Kenakin, 2002; Jakubik et al., 1996; Thomas et al., 1997). We recently described a series of small-molecule agonists with the same efficacies for CCR1 wt as the endogenous CCL3 (MIP-1a) and CCL5 (RANTES) ( Jensen et al., 2008). Interestingly, these agonists enhanced the binding of CCL3 (acted as allosteric enhancers or positive allosteric modulators of CCL3), whereas they—at the same time—inhibited the binding of CCL5 in a competitive manner (Fig. 8.4). In accordance with this binding pattern, mutational analyses revealed that the binding site for these compounds overlapped considerably with CCL5, but not with CCL3, with regard to residues pointing into the major binding pocket. Thus, this series of small-molecule agonists depicted different orthosteric binding sites for CCL3 and CCL5—a phenomenon that is extremely important to remember in drug-discovery process, because it shows for the first time that a certain compound may act with opposite effects on different endogenous ligands acting on the same 7TM receptor (Fig. 8.4) ( Jensen et al., 2008). The aforementioned examples from CXCR3, CCR8, and CCR1 illustrate that although the specific points of interaction differ (albeit with considerable overlap), the small molecules act similar in respect of the activation mechanism. The study in CCR8 shows how a classical antagonistic pharmacophore has the opposite effect in this receptor and raises the interesting question: what makes a ligand work as an agonist? In that respect it is believed that a receptor is never completely silent but instead shifts between various conformations that are targeted and stabilized by different ligands in a combined act of induced fit and conformational selection. Thus, agonists stabilize the active conformation(s) of the receptor, whereas inverse agonists (and antagonists) stabilize the inactive conformation(s). Interpretations of the

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N-term. Glu VII:06

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Me-chelator as orthosteric blocker

Distinct binding sites:

Overlapping binding sites:

MC enhances CCL3 binding by stabilizing CCL3-preferring conformations

MC displaces CCL5 - competition between partly overlapping binding sites

Receptor with two ligands

Figure 8.4 Schematic side view of the transmembrane segments of CCR1.The upper panel illustrates the inactive and active conformations of the ligand-free receptor. The middle panel illustrate the receptors incubated with one ligand, from left: CCL3, metalion chelators, and CCL5. As indicated, CCL3 binds predominantly extracellularly, whereas the N-terminus of CCL5 docks into the major binding pocket, overlapping

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metal-ion chelator studies (CXCR3 and CCR1) provide evidence that agonists are ligands that ‘‘glue’’ the upper segments of the transmembrane helices in the major binding pocket together, whereas antagonists prevent these movements either by acting deep in the binding pocket (small-molecule antagonists) or by a more superficial steric hindrance or prevention of inward movements of TM-III, VI, and VII.

5. Experimental Procedures Chemokine receptor activity can be measured in several ways. Among these is, for instance, the measurement of different second messengers. These kinds of assays have gained different appreciation, depending on the type of research and wanted outcome. Thus, methods used for highthroughput screening of potential drug compounds might not be adequate for mutational mapping of single compounds. When talking about chemokine receptor activation, chemotaxis—where the cells move toward an increasing gradient of a chemoattractant—is a natural choice. Thus, what is in nature used as homing of blood cells to sites of inflammation can be used as a measure of ligand potency in the in vitro two-chamber assay. This assay depends on high chemokine receptor expression, and purified blood cells or stably transfected cells are, therefore, preferred over transiently transfected cells. Therefore, the difficulties in the use of this assay for mutational mapping are obvious. Furthermore, the activation profile with ligand gradients seems to increase and decrease rapidly, making a classical bell-shaped curve. This makes the chemotaxis assay too complex for a direct and trustworthy result of optimal ligand-induced activation. The search for robust and reliable assays suitable for both highthroughput screening and mapping has led to the construction of promiscuous G proteins (Conklin et al., 1993; Kostenis, 2001). The rationale behind these chimeras has its origin in the search of new drugs for both orphan and 7TM receptors with known ligands. The goal was to create an overall Ga-subunit with the highest probability of coupling the maximum number of receptors to a common pathway. In 1993, Conklin and coworkers found that it was possible to shift the pathway of Gi-coupled

with the binding site of the metal-ion chelators (MCs). The lower panel illustrates the CCR1 receptor with coincubation with two ligands, from left: CCL3 coadministered with MC, which results in increased binding of CCL3, and CCL5 coadministered with MC, where a competition takes place (partly caused by overlapping binding sites) and MCs displace CCL5 from CCR1. Adapted from Jensen et al. (2008).

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Gi-coupled receptor

II II

Chimeric Ga-subunit

Gaq Gai

+

III IV V VI VII

VIII

Gas

−

+

Gaq

Gai

+

Adenylate cyclase

ATP

cAMP

+

Phospholipase C

PIP2

DAG + IP3

Figure 8.5 Simplified model of Ga-subunit^mediated response on activation. Gas stimulates adenylate cyclase to convert adenosine triphosphate (ATP) to cyclic adenosine monophosphate (cAMP), whereas Gai inhibits this process. Gaq activates phospholipase C resulting in the degradation of phosphatidylinositol bisphosphate (PIP2) to diacylglycerol (DAG) and inositol triphosphate (IP3). Cotransfection of a Gai signaling receptor with the promiscuous chimeric Ga-subunit Gqi5 (Conklin et al., 1993; Coward et al.,1999) or GD6aqi4myr (Kostenis et al.,1998) converts the signal from a Gai readout to a Gaq response, as illustrated by the long arrow.

receptors to a Gq-coupled response by substituting the five C-terminal residues of the Gaq-subunit with that of the Gai-protein (Conklin et al., 1993) (Fig. 8.5). Later, this G-protein chimera has been improved in different ways, for instance by including a myristoylation site (Kostenis, 2001). This overcomes the problem that Gi signaling (which is the preferred G-protein for chemokine receptors) inhibits adenylate cyclase and thereby results in a decrease in cAMP. In contrast to a gain of second messengers, as is the case with Gs (which stimulates adenylate cyclase) and Gq (which stimulates phospholipase C resulting in the production of inositol triphosphate [IP3] and subsequently the release of intracellular Ca2þ stores), a decrease of second messenger is a difficult measure, because it relies on the stable continuous activation of the stimulatory pathway. Thus, the chimeric G-protein is a great tool both for the screening of orphan receptors and when measuring the activation of Gi-coupled receptors in general (Fig. 8.5).

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6. IP3 Assay in Transiently Transfected COS-7 Cells Cotransfection of chemokine receptors that primarily signal through Gai with the promiscuous G-proteins described previously open up for two obvious readouts; namely Ca2þ assays and IP3 assays. Measurement of Ca2þ is widely distributed in the screening of ligands. However, the accumulation of IP3 is more robust and can be carried out on transiently transfected cells, making it ideal for mutational analysis. Furthermore, this assay makes it possible to test antagonism (by the presence of a constant concentration of an agonist) and inverse agonism in the case of constitutive receptor signaling. One important consideration is the ratio between receptor and G-protein, and especially that the concentration of the G-protein is sufficient for proper interaction with the receptors. Therefore, a 3:2 ratio of G-protein/receptor is chosen for the cotransfection. The IP3 assay relies on the incorporation of 3H-myoinositol into the cellular inositol metabolism. When the receptor is activated by an agonist, activated phospholipase C will degrade phosphatidylinositol 4,5-bisphosphat (PIP2) into diacylglycerol (DAG) and IP3 (Fig. 8.5). By incubating with a lithium buffer, the recycling pathway of IP3 is blocked, leading to accumulation of tritiated IP3.

6.1. Detailed protocol 6.1.1. Day one: Transiently calcium phosphate transfection For medium flasks (75 cm2) containing 3  106 COS-7 cells, mix 10 mg receptor DNA and 15 mg GD6aqi4myr with 30 ml 2 mM CaCl2 and TE buffer (10 mM TRIS-HCl, 1 mM EDTA, pH 7.4) to a total volume of 240 ml. Add the mixture gently and drop wise to a tube containing 240 ml 2 HBS buffer (280 mM NaCl, 50 mM HEPES, 1.5 mM Na2HPO4, pH 7.2), and let it precipitate for 45 min at room temperature. Meanwhile, change the cell medium to 5 ml. Add the precipitate drop wise to the cells, and add 150 ml (100 mM final) chloroquine (2 mg/ml) to the medium, and incubate for 5 h at 37  C, 10% CO2. Stop the transfection by adding 10 ml COS-7 growth medium and incubate overnight at 37  C, 10% CO2. 6.1.2. Day two: Seeding and incubation with 3H-myoinositol Aspirate media and loosen the cells by adding 5 ml PBS-EDTA. Spin down the cells, count, and dissolve in an appropriate volume to 5  105 cells/ml.

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Add 5 mCi/ml 3H-myoinositol. Seed the cells in 24-well plates, with 150.000 cells/well. Incubate over night at 37  C, 10% CO2. 6.1.3. Day three: IP3 assay Aspirate media and wash twice with HBSS (Hanks balanced salt solution) at room temperature. Add 200 ml 10 mM LiCl HBSS to each well and incubate at least 15 min at 37  C. Add the ligands and incubate 90 min at 37  C. Stop the reaction by aspirating the media and add 1 ml ice-cold 10 mM formic acid. Incubate 30 min on ice. Prepare the columns (Dowex 18-200, Sigma) by adding 3 ml regeneration buffer (3 M ammonium formate, 100 mM formic acid). Wash the columns twice with 5 ml Milli Q water. Add the formic acid extracts. Wash twice with 5 ml GPI buffer (60 mM sodium formate, 5 mM borax). Eluate into 20-ml scintillation vials with 3 ml elution buffer (1 M ammonium formate, 100 mM formic acid). Add 10 ml scintillation fluid to each vial and close with lids. Shake the vials thoroughly to homogenize the contents and count in a b-counter.

REFERENCES Acharya, S., and Karnik, S. S. (1996). Modulation of GDP release from transducin by the conserved Glu134-Arg135 sequence in rhodopsin. J. Biol. Chem. 271, 25406–25411. Allen, S. J., Crown, S. E., and Handel, T. M. (2007). Chemokine: Receptor Structure, Interactions, and Antagonism. Annu. Rev. Immunol. 25, 787–820. Altenbach, C., Cai, K., Khorana, H. G., and Hubbell, W. L. (1999). Structural features and light-dependent changes in the sequence 306-322 extending from helix VII to the palmitoylation sites in rhodopsin: A site-directed spin-labeling study. Biochemistry 38, 7931–7937. Altenbach, C., Kusnetzow, A. K., Ernst, O. P., Hofmann, K. P., and Hubbell, W. L. (2008). High-resolution distance mapping in rhodopsin reveals the pattern of helix movement due to activation. Proc. Natl. Acad. Sci. USA 105, 7439–7444. Ballesteros, J. A., Jensen, A. D., Liapakis, G., Rasmussen, S. G., Shi, L., Gether, U., and Javitch, J. A. (2001). Activation of the beta 2-adrenergic receptor involves disruption of an ionic lock between the cytoplasmic ends of transmembrane segments 3 and 6. J. Biol. Chem. 276, 29171–29177. Benned-Jensen, T., and Rosenkilde, M. M. (2008). Structural motifs of importance for the constitutive activity of the orphan 7TM receptor EBI2Analysis of receptor activation in the absence of an agonist. Mol. Pharmacol. 74, 1008–1021.

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The Duffy Antigen Receptor for Chemokines Antal Rot* and Richard Horuk† Contents 192 194 198 199 200 201 202 203

1. Introduction 2. Methods for the Study of DARC as a Malarial Receptor 3. Methods for the Study of DARC as a Chemokine Sink 4. Isolation of Erythrocytes and Measurement of Chemokines 5. DARC as a Chemokine Transcytosis Receptor 6. The Assay of Chemokine Transcytosis by DARC 7. Conclusions References

Abstract The Duffy blood group antigen is a serpentine protein with seven transmembrane domains that is not coupled to G-proteins or other known intracellular effectors. In addition to erythrocytes, it is also expressed in endothelial cells and neurons. In recent years the Duffy antigen has received much attention because of its diverse roles in health and disease. These include its functions as a docking receptor for the invasion of human erythrocytes by the malaria parasite Plasmodium vivax. In addition, the Duffy antigen is a binding protein for multiple inflammatory chemokines. Its expression allows erythrocytes to regulate intravascular levels of chemokines. It has also been shown recently that the Duffy antigen plays an important role in endothelial cells by facilitating chemokine transcytosis and presentation. Given these diverse functions of the Duffy antigen, this short review presents detailed methods that can be used to investigate each of these potential roles of this multifaceted protein.

* {

MRC Centre for Immune Regulation, Institute of Biomedical Research, University of Birmingham, UK Department of Pharmacology, UC Davis, Davis, California, USA

Methods in Enzymology, Volume 461 ISSN 0076-6879, DOI: 10.1016/S0076-6879(09)05409-3

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2009 Elsevier Inc. All rights reserved.

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1. Introduction The Duffy antigen was first identified as a blood group antigen that was expressed on the cell surface of human red blood cells (Cutbush et al., 1950). Following the observation that West Africans do not express the protein on their erythrocytes and that they are resistant to Plasmodium vivax– induced malaria, the Duffy antigen was identified as the major portal of entry for the malarial parasite to allow cellular invasion and infection (Miller et al., 1976). The mutation in the Duffy antigen that abolishes receptor expression is due to a T to C substitution at nucleotide-46 (Tournamille et al., 1995). This mutation impairs the promoter activity in erythroid cells by disrupting a binding site for the GATA1 erythroid transcription factor. The Duffy negative phenotype gives almost total protection against infection with P. vivax and P. knowlesi. This suggests that the survival benefit in malaria-infested regions of Africa provided the evolutionary pressure behind the widespread occurrence of this polymorphism. The Duffy antigen was cloned in 1993 (Chaudhuri et al., 1993) and shown to be a seven-transmembrane domain protein (Neote et al., 1994) (Fig. 9.1). In addition to binding malaria parasites, the Duffy antigen was shown to be a promiscuous receptor for chemokines (Horuk et al., 1993a);

Figure 9.1 Primary amino acid sequence of DARC showing its seven transmembrane domain topology. Adapted from Horuk (1994).

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originally postulated to be an intravascular ‘‘sink’’ for CXCL8 (Darbonne et al., 1991), it also binds with high affinity a number of other inflammatory CXC and CC chemokines including CXCL1, CXCL7, CCL2, and CCL5 (Horuk et al., 1993a; Neote et al., 1993). On the basis of these activities the protein was renamed Duffy Antigen Receptor for Chemokines (DARC) (Hadley et al., 1994). Interestingly, the expression of DARC is not confined to erythrocytes, and it is also found in vascular endothelial cells and cerebellar neurons (Hadley et al., 1994; Peiper and Horuk, 1996; Peiper et al., 1995). However, the overall physiologic significance of DARC has been open to question, because it does not seem to be coupled to, or regulated by, G-proteins (Horuk et al., 1993b). Nevertheless, the fact that DARC expression is preserved on the endothelial cells lining postcapillary venules of Duffy-negative individuals (Peiper et al., 1995), even in the presence of the strong negative selection from morbidity and mortality from P. vivax, raises the possibility that DARC plays a critical role in the biology of endothelial cells particularly in the context of postcapillary venules, an active site of leukocyte trafficking. Several groups investigated various epidemiologic and clinical correlates of the DARC-negative phenotype and reported on possible roles for erythrocyte DARC in physiologic and disease settings. It was shown recently that in addition to malaria infection the Duffy-negative phenotype affects HIV infection and AIDS. It is associated with a significantly increased susceptibility to HIV-1 infection; interestingly, however, it also leads to prolonged survival in HIV-1–infected subjects with AIDS (He et al., 2008). The increased incidence of asthma and atopy in individuals of African origin was shown to depend on a DARC-negative phenotype (Vergara et al., 2008). Another clinical study has suggested that there is an association of the DARC-negative phenotype with sickle cell disease, claiming that this phenotype was more strongly associated with chronic organ damage and proteinuria than in patients not expressing it (Afenyi-Annan et al., 2008). On the basis of the results of two conflicting studies the contribution of the Duffy phenotype to the delayed graft function and allograft survival of the transplanted kidney remains contentious (Akalin and Neylan, 2003). Two reports have suggested a link of the Duffy-negative phenotype to prostate cancer. In the first it was suggested that the lack of erythrocyte expression of DARC in greater than 70% of African-Americans could account in part for the greater than 60% incidence of prostate cancer and a twofold higher mortality rate in these individuals than in Caucasian men (Shen et al., 2006). This hypothesis was tested in a transgenic model of prostate cancer with DARC-deficient mice. The data indicated that in vivo, tumors from DARC-deficient mice had higher intratumor concentrations of angiogenic chemokines an increased tumor vessel density and greatly augmented prostate tumor growth. In the second study, CD82, a prostate cancer metastasis suppressor gene, whose downregulation has been found to

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be clinically associated with metastatic progression in a variety of cancers, was shown to bind DARC (Bandyopadhyay et al., 2006). This interaction leads to inhibition of tumor cell proliferation and induction of senescence. On the basis of these data, the authors suggest that DARC signals through CD82 to induce the suppression of metastasis. However, this study does not take into account the fact that, as discussed previously, the DARCnegative individuals still express this molecule in the endothelial cells, whereas whether erythrocyte DARC may have any effect on suppression of metastasis remains unknown. Several groups explored the function of DARC in inflammation with DARC knockout mice. When challenged with LPS, the DARC knockout mice had significantly increased inflammatory infiltrates in the lung and liver compared with their wild-type litter mates (Dawson et al., 2000). These results seem to support the idea that DARC can act as an intravascular regulator of chemokine concentrations. However, in addition to the chemokine ‘‘sink’’ effect, a study in DARC-deficient mice uncovered the role of erythrocyte DARC in the long-term maintenance of plasma levels of free soluble cognate chemokines (Fukuma et al., 2003). Similar observations were made in human clinical studies where Duffy-negative humans were shown to have significantly lower levels of free chemokines in plasma under normal conditions ( Jilma-Stohlawetz et al., 2001). This is because in the absence of erythrocyte, DARC chemokines disappear from circulation. Thus the function of erythrocyte DARC in chemokine homeostasis has two sides, that of a chemokine ‘‘sink’’ and that of a ‘‘reservoir’’ of chemokines in blood. Conversely, it was suggested that DARC in endothelial cells may have a different function altogether by transporting chemokines in abluminal (basal) to luminal (apical) direction (Pruenster and Rot, 2006; Rot, 2005). Such chemokine transcytosis by DARC has been recently proven experimentally in vitro and in vivo (Pruenster et al., 2008). Thus, given the potential importance of DARC, as a target for an antimalarial drug, as a binding protein that plays a role in the regulation of intravascular levels of chemokines, as well as a chemokine ‘‘interceptor’’ (Haraldsen and Rot, 2006) on endothelial cells that accomplishes chemokine transcytosis and presentation, we describe a number of methods to characterize the potential roles of this multifaceted protein.

2. Methods for the Study of DARC as a Malarial Receptor The fact that DARC is a serpentine seven-spanner highly homologous to G-protein–coupled receptors (GPCRs) and that almost 40% of all marketed medicines interact with this family of proteins (Hopkins and

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Groom, 2002), strongly suggests that DARC is an excellent target for therapeutics to treat malaria. A similar approach has already shown benefit in HIV, in which the major coreceptors for virus entry are CCR5 and CXCR4. Like DARC, CCR5 and CXCR4 belong to the chemokine receptor subfamily of GPCRs (Horuk, 1999). Pfizer has developed a small-molecule inhibitor (Maravoric) of the interaction between HIV gp120 and CCR5 that is currently a registered drug to treat HIV (Hitti, 2007), and CXCR4 inhibitors are in clinical development (Rusconi et al., 2007). We envisage that an approach to identify small-molecule inhibitors of DARC will similarly prove to be of major benefit in drastically reducing the number of cases of P. vivax malaria by treatment and reduced transmission. Such inhibitors in combination with existing therapies should also delay the emergence and spread of resistance. To achieve the goal of identifying small-molecule antagonists of DARC, a high-throughput screening assay will be required. There are several ways to achieve this. By analogy to HIV, which also uses chemokine receptors as coreceptors for invasion, we envisage that approaches that have led to the discovery of CCR5 entry inhibitors should be equally successful in identifying inhibitors that block the entry of the malarial parasite to the red blood cell. Invasion of erythrocytes requires the interaction of a P. vivax Duffy binding protein (PvDBP) with DARC (Horuk et al., 1993a; Miller et al., 1976). The binding domain of PvDBP has been mapped to an aminoterminal, cysteine-rich region referred to as P. vivax region II (PvRII) (Chitnis and Miller, 1994). Thus assays that are based on this interaction can be set up to find entry inhibitors. Methods to produce a correctly folded form of recombinant PvRII for use in an ELISA assay to study the interaction of PvRII with DARC have been described (Choe et al., 2005; Hans et al., 2005). This assay can be used to identify small molecules that block the binding of PvRII to an N-terminal peptide of DARC (Fig. 9.2). In this assay, the N-terminal 66-amino acid residues of DARC fused with human Fc is coated in ELISA plate wells and incubated with recombinant PvRII. Bound PvRII is detected with a monoclonal antibody directed against PvRII (Grimberg et al., 2007). This assay can be adapted for high-throughput screening of inhibitors that block the interaction of PvRII with DARC with small-molecule libraries. Identified hits may block by either binding to DARC or PvRII. DARC-Ig is coated onto 96-well plates by incubation at 1 mg/ml. Bacterially expressed and refolded PvR II (Singh et al., 2001) is incubated with coated plates at 0.1 mg/ ml. Bound PvRII is detected with murine anti-PvRII antibodies and quantified colorimetrically with anti-mouse IgG conjugated to horseradish peroxidase (Fig.9. 2). Again, by analogy to the development of HIV fusion inhibitors, an assay involving inhibition of chemokine binding to DARC can be used to discover small-molecule inhibitors. One such assay is a high-throughput CCL3 binding assay that was initially used by scientists at Merck to discover

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Substrate Anti mouse IgG-HRPO

Color development

Anti PvRII PvRII DARC-Ig

Figure 9.2 ELISA assay to study the interaction of PvRII with DARC; 96-well plates are coated with recombinant DARC-Fc (N-terminal extracellular 60 amino acids of DARC fused to the Fc region of human IgG). Binding of recombinant PvRII to DARC-Fc is detected quantitatively with murine anti-PvRII antibodies and antimouse IgG goat antibodies conjugated to horseradish peroxidase (anti-mouse IgG-HRPO). Adapted from Chitnis and Sharma (2008).

small-molecule inhibitors of HIV entry that use CCR5 (Dorn et al., 2001; Finke et al., 2001). Human kidney 293 cells stably expressing DARC are incubated with 1251-CCL3 and varying concentrations of CCL3 or smallmolecule inhibitors at 4
C for 1 h. The incubation is terminated by harvesting through a GF/B filter plate presoaked with 0.3% polyethylenimine and washed three times with cold wash buffer (10 mM HEPES, 0.5 M NaCl, 0.5% bovine serum albumin, pH 7.4). The radioactivity in each well is determined with a scintillation counter after the addition of 50 ml of Scint20 scintillation fluid. Nonspecific binding is assessed in competition studies with unlabeled CCL3 (100 nM ). Confirmed hits from the two screens described previously can then be examined in a low-throughput secondary assay that tests the ability of compounds to inhibit invasion of human red blood cells by the DARCdependent parasite, P. knowlesi. P. knowlesi is an accepted surrogate for P. vivax invasion, because both strains require interaction with DARC for invasion, and P. knowlesi can be cultured in vitro. This assay has been previously used to measure the ability of the chemokine CXCL1 and CXCL1 mutants to inhibit erythrocyte invasion by P. knowlesi (Hesselgesser et al., 1995). Erythrocytes (2  107 in a volume of 870 ml of RPMI containing 22 mM glucose, 29 mM HEPES, pH 7.4, and 10% fetal calf serum, per invasion) are incubated with increasing concentrations of chemokines for 1 h at room temperature. Percoll-purified P. knowlesi schizont-infected erythrocytes (2  106 in 100 ml) and 6 ml of 7.5% sodium bicarbonate are added and incubated for 6 to 7 h at 37
C, during which time the infected erythrocytes ruptured, releasing merozoites that were able to invade other erythrocytes. The cells were centrifuged through Percoll to separate the ring-infected and normal erythrocytes. A thin smear of the

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Relative invasion rate (%)

120 100 80 60 40 20 0 0.1

E6A R8A E39A K49A CXCL1

1 10 100 Ligand concentration (nM)

1000

Figure 9.3 Inhibition of erythrocyte invasion by P. knowlesi by MGSA and MGSA mutants.To study the effect of MGSA and its mutants on invasion, we preincubated erythrocytes (2  107 in a volume of 870 ml of RPMI containing 22 mM glucose, 29 mM HEPES, pH ¼ 7.4, and 10% fetal calf serum, per invasion) with increasing concentrations of these chemokines for 1 h at room temperature. Percoll-purified P. knowlesi schizont-infected erythrocytes (2  106 in 100 ml) and 6 ml of 7.5% sodium bicarbonate were added and incubated for 6 to 7 h at 37
C, during which time the infected erythrocytes ruptured, releasing merozoites that were able to invade other erythrocytes. The cells were centrifuged through Percoll to separate the ring-infected and normal erythrocytes. A thin smear of the resuspended erythrocytes was stained with Giemsa, and the percentage of erythrocytes infected with ring-stage parasites was determined. The invasion rates are expressed as a percentage of the rate of invasion in the absence of chemokines. Adapted from Horuk et al. (1993a).

resuspended erythrocytes was stained with Giemsa, and the percentage of erythrocytes infected with ring-stage parasites was determined. The invasion rates are expressed as a percentage of the rate of invasion in the absence of chemokines. Inhibition of invasion EC50 in a typical assay (Fig. 9.3) were: CXCL1 ¼ 7 nM, E6A ¼ 8.6 nM, R8A ¼ >1 mM, E39A ¼ 710 nM, K49A ¼ 96 nM. The mutants inhibited parasite invasion at ligand concentrations that were consistent with their receptor binding affinities for DARC (Hesselgesser et al., 1995). For example, the mutant E6A was almost as effective as CXCL1 with an EC50 of inhibition of invasion of 8.6 nM compared with 7 nM for wild-type CXCL1. The mutant E6A binds to DARC with high affinity and efficiently blocks parasite invasion (Fig. 9.3) but binds to CXCR2 poorly and does not activate neutrophils. This assay demonstrates the feasibility of blocking parasite invasion with inhibitors of chemokines and strongly suggests that screening for small-molecule inhibitors of parasite invasion with the assays described here could constitute a new and novel approach in the fight against P. vivax–induced malaria. Several other low-throughput assays that can measure the potential effectiveness of agents in blocking P. vivax–mediated infection have been described. Most are indirect assays, for example, like the erythrocyte rosetting assay described by Chitnis and Miller (Chitnis and Miller, 1994).

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COS7 cells transfected with PvRII are plated in 3.5-cm diameter wells and used for erythrocyte binding assays 40 to 60 h after transfection; 200 ml of a 10% erythrocyte suspension is added to 2 ml of media in wells containing the transfected cells, the plate is swirled to mix the erythrocytes well, and the erythrocytes are allowed to settle for 2 h at 37
C. The COS7 cells are then washed three times with 2 ml of PBS to remove nonadherent erythrocytes. Transfected COS7 cells with rosettes of adherent erythrocytes are then scored. The number of rosettes is scored in either 10 or 20 fields at a magnification of 40 with an inverted microscope. Binding is scored as negative when no rosettes are seen in the entire well. To study the effect of inhibitors of the interaction between DARC and PvRII the erythrocytes are first resuspended to a hematocrit of 1% in 1 ml of complete DMEM and incubated for 1 h at room temperature with the potential inhibitors at the required concentrations. The erythrocytes are then used in erythrocyte binding assays as described previously. The number of COS7 cells with rosettes of adherent erythrocytes is scored in 20 randomly chosen fields at a magnification of 40 in each well and the percent inhibition is determined as follows: percent binding ¼ 100  (no. of bound COS7 cells in the presence of inhibitors)/(no. of bound COS7 cells in absence of inhibitors); percent inhibition ¼ 100  percent binding; and percent inhibition ¼ 0 if binding (%) i > 100.

3. Methods for the Study of DARC as a Chemokine Sink Shortly after its discovery, DARC was postulated to be a ‘‘sink’’ for chemokines (Darbonne et al., 1991; Neote et al., 1993), and a study to test this concept was carried out in healthy volunteers who were given LPS intravenously to induce chemokines in the circulation (Olszyna et al., 2001). Injection of LPS was associated with increases in the erythrocyte bound levels of the chemokines CXCL1, CXCL8, and CCL2 that all bind to DARC. In contrast CCL4, which was measured as a non-DARC–binding chemokine, remained very low or undetectable in cell fractions after LPS administration. Endotoxemia and gram-negative sepsis, in which LPS plays a major role, are characterized by elevated levels of chemokines in plasma, and a recent study showed that in patients with sepsis, CXCL8 bound to erythrocytes exceeds CXCL8 concentrations in plasma (Marie et al., 1997). In another study, CXCL8 was shown to be released in the plasma of patients with acute myocardial infarction and readily binds to DARC on red blood cells (de Winter et al., 1997), resulting in only a transient rise of plasma CXCL8 and a more prolonged increase of erythrocyte-bound CXCL8. CXCL8 was shown to be transiently elevated in the serum of cancer patients undergoing

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treatment with IL-1 alpha. The erythrocyte-bound CXCL8 levels were higher than those measured in plasma and remained elevated long after the plasma levels had become undetectable (Tilg et al., 1993). Elevated plasma CXCL8 is a diagnostic marker of early-onset bacterial infection in neonates, and a recent study revealed that neonates with suspected bacterial infections had ng/ml levels of CXCL8 bound to DARC on their red blood cells compared with almost undetectable levels in healthy newborns (Orlikowsky et al., 2004). Preeclampsia is characterized by neutrophil activation, and CXCL8 is involved in the pathophysiology. A recent study revealed a correlation between a Duffy-negative phenotype, high plasma levels of CXCL8, and TNF-a in preeclamptic women compared with controls (Velzing-Aarts et al., 2002). The higher CXCL8 levels in preeclampsia may result from increased production and/or reduced clearance, related to a high frequency of a Duffy-negative phenotype. The function of DARC on red blood cells in the long-term maintenance of the levels of free chemokines in plasma has been uncovered by Jima and coworkers ( Jilma-Stohlawetz et al., 2001). Thus DARC functions as a biphasic regulator of chemokines in blood buffering them in acute situation and maintaining their levels on a longer run.

4. Isolation of Erythrocytes and Measurement of Chemokines Whole blood is centrifuged at 2000g, and the plasma is removed and saved. The packed pellet is resuspended in PBS, pH 7.4, and centrifuged over a Ficoll-Hypaque solution adjusted to a density of 1.095 to remove granulocytes, platelets, and mononuclear cells. Erythrocytes prepared in this manner are devoid of contaminating leukocytes and platelets when examined by light microscopy. The red blood cells are then washed three times by centrifugation at 180g in PBS and set aside for extraction of chemokines. To extract chemokines bound to the isolated red blood cells they are lysed by resuspension in 1% Triton X-100 in a volume corresponding to the original blood sample. The lysate is then incubated for 40 min and then stored at 80
C until assayed for chemokines. Chemokines are assayed by ELISA with kits from R and D systems. Typical instructions for measuring CXCL8 levels in plasma and in red cell lysates is taken from the manufacturer’s booklet and is given in the following. Other chemokines such as CCL5 and CCL2 can be measured with the appropriate ELISA kit. 1. Add 100 ml of assay diluent to each well. 2. Add 50 ml of standard, control, or sample per well. Securely cover with a plate sealer and incubate for 2 h at room temperature. Gently tap the plate to ensure thorough mixing.

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3. Aspirate each well and wash, repeating the process three times for a total of four washes. Wash by filling each well with wash buffer (400 ml). Complete removal of liquid at each step is essential to good performance. After the last wash, remove any remaining wash buffer by aspirating or decanting. Invert the plate and blot it against clean paper towels. 4. Add 100 ml of CXCL8 conjugate to all wells. Securely cover with a plate sealer and incubate for 1 h at room temperature. 5. Repeat the aspiration/wash as above. 6. Add 200 ml of substrate solution to each well. Incubate for 30 min at room temperature and protect from light. 7. Add 50 ml of stop solution to each well. The color in the wells should change from blue to yellow. If the color in the wells is green or if color change does not appear uniform, gently tap the plate to ensure thorough mixing. 8. Determine the optical density of each well within 30 min, with a microplate reader set to 450 nm. If wavelength correction is available, set to 540 nm or 570 nm. If wavelength correction is not available, subtract readings at 540 nm or 570 nm from the readings at 450 nm. This subtraction will correct for optical imperfections in the plate. There is very little interference in this assay from either the 1% Triton X-100 in the cell lysate or from plasma samples. The dynamic range of the assay is from 20 to 2000 pg/ml, and all samples should be diluted so that the chemokine concentration lies somewhere in the middle of the standard curve.

5. DARC as a Chemokine Transcytosis Receptor To induce leukocyte emigration, chemokines produced by tissue cells have to negotiate the endothelial cell barrier and associate with the luminal endothelial cell surface (Rot, 1992). The translocation of tissue chemokines is achieved by active endothelial cell transport leading to chemokine immobilization on the tips of the luminal microvilli and their presentation to the adherent leukocytes (Middleton et al., 1997). Until recently, glycosaminoglycans, heparan sulfate in particular, have been postulated to mediate endothelial cell transport and immobilization of chemokines (Handel et al., 2005; Wang et al., 2005). However, early studies of chemokine in situ binding in intact tissues suggested that DARC expressed by the endothelial cells of venules contributes to the chemokine interactions with these cells (Hub and Rot, 1998). Nevertheless the clear demonstration of DARC function in chemokine transcytosis was possible only in vitro. Primary endothelial cells rapidly lose their DARC expression in culture, and in vitro propagated endothelial cell lines do not express this receptor either.

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Therefore, transfected cells were used to uncover in vitro the contribution of DARC to chemokine transcytosis and apical immobilization (Pruenster et al., 2008). Here we detail the transwell-based methods to study DARCmediated chemokine transcytosis and its contribution to chemokineinduced leukocyte transmigration across the cell monolayers expressing this receptor.

6. The Assay of Chemokine Transcytosis by DARC 1. Seed DARC-transfected cells known to form tight polar monolayers (e.g., MDCK or HUVEC) on collagen-coated transwell inserts (pore size 5 mm) and grow in complete medium until confluence. To prevent the cell outgrowth below the filter, it is important to place fluid in the bottom plate only 1 day before the assay. If fluid is placed in the bottom plate simultaneously with seeding the cells, within 3 to 4 days two monolayers will grow in a transwell, one above and one below the filter. 2. Before the assay, measure electrical resistance across the monolayers and select only the wells with comparable monolayers. Anticipate attrition at this point by starting more wells than will be necessary for the assay. Diffusion across the monolayers of FITC-labeled inulin as a tracer (its molecular mass is in the range of chemokines) may confirm the low nonspecific permeability of the monolayers. 3. For transcytosis assay, select 125I-labeled cognate chemokine. Good results were obtained with CXCL8 or CCL2 (specific radioactivity approximately 2000 Ci/mmol). Test for saturability of binding and establish optimal and economical concentration to be used by initially testing different concentrations of chemokine (e.g., from 0.002 to 20 pmol). Use non-cognate chemokine (e.g., CCL19) to test for specificity of binding and transcytosis. Depending on studying basolateral to apical transcytosis or vice versa, place chemokine below or above the monolayer, respectively and incubate for 3 or 4 h as well as overnight at 37
C. Collect fluid from the bottom and top compartments and then recover the cell surface– bound chemokine by the addition of 10 saline for 3 min above the monolayers. The latter fraction is important for studying DARCmediated transcytosis, because a significant part of transported chemokine remains associated with the apical cell membrane. Previously, the fraction of membrane-associated transported chemokine was not accounted for, which explains why the direct contribution of DARC to chemokine transcytosis has not been observed by previous investigators (Lee et al., 2003). Next disrupt the cells with 0.4% Triton-X100 to obtain the intracellular chemokine.

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4. To differentiate between the radioactivity associated with intact and degraded chemokine submit the samples recovered from the different compartments of transwell to precipitation by 12.5% trichloroacetic acid (TCA) at 4
C. 5. Measure in a gamma counter the radioactivity associated with TCAsoluble fractions (degraded chemokine) and TCA-precipitable, insoluble fractions (intact chemokine) for samples obtained from each of the different compartments. The total amount of radioactivity recovered from the transwell system should be close to 100% of the input. With some chemokines that avidly bind to plastic, the amount recovered is less. Chemokine binding to transwell support and bottom well can be tested by measuring the radioactivity associated with these parts. 6. By use of the transcytosis assay as described previously, the contribution of DARC to the unidirectional chemokine transport from basolateral to apical surface of the cell monolayers was uncovered. The functional consequences of DARC-mediated transcytosis to chemokine-induced leukocyte transmigration across the monolayers can be studied as follows. Assemble the transwells as previously, except use inserts with 8-mm pores. On monolayer confluence, add to the bottom plates of transwells either buffer alone or with chemokine at different concentrations. After 1 h of equilibration, label leukocytes with carboxyfluorescein diacetate succinimidyl diester and place 5  105 cells (depending on the chemokine used either neutrophils, monocytes or lymphocytes), into the insert and allow to migrate for 4 h across the cell monolayers either expressing DARC or not. On disassembly, the cells that had migrated across the monolayers and the filters should be counted in the following distinct compartments: (1) in suspension in the bottom well (this is the traditional way of evaluating transmigration); (2) adherent to the bottom plate; as well as (3) adherent to the bottom side of the filter (in both 2 and 3 after being removed with 5 nM EDTA). The enumeration of leukocytes adherent to the bottom side of the filter is important because the expression of DARC by the monolayers disproportionately increases, for not yet clear reasons, the number of the cells in this compartment.

7. Conclusions We have described a number of methods for the experimental study of DARC that should prove to be useful for investigators aiming to analyze the molecular properties of this fascinating protein. Although DARC is an unusual receptor because it does not seem to couple to any of the known intracellular signaling pathways, it has found interest because of its role in malaria pathogenesis together with its functions in regulating chemokine

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levels in blood and their endothelial cell transport. Methods have been presented here that will allow each of these diverse roles of this protein to be further investigated.

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Hetero-Oligomerization of Chemokine Receptors Shirley Appelbe and Graeme Milligan Contents 1. Introduction 2. Coimmunoprecipitation 2.1. Coimmunoprecipitation protocol following heterologous expression of epitope-tagged chemokine receptors 3. Resonance Energy Transfer Techniques 3.1. Bioluminescence resonance energy transfer (BRET) 3.2. Single-point BRET2 protocol 3.3. Data analysis 3.4. Time-resolved FRET 3.5. FRET imaging in living cells 4. Developing Techniques References

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Abstract Although traditionally assumed to be monomeric signaling units, G-protein– coupled receptors (GPCRs) have been shown to exist as dimers/oligomers. Many chemokine receptors have been demonstrated to form homo-oligomers, and hetero-oligomerization between both pairs of chemokine receptors and chemokine receptors and other GPCRs has also been demonstrated. This chapter highlights some of the most common techniques used to investigate chemokine receptor oligomerization.

1. Introduction GPCRs were long assumed to function as monomeric signaling units. However, a large body of evidence now suggests that GPCRs exist as dimers or higher order oligomers (Milligan, 2007). The first conclusive demonstration that receptor oligomers exist in native membranes was Neuroscience and Molecular Pharmacology, University of Glasgow, Glasgow, Scotland, United Kingdom Methods in Enzymology, Volume 461 ISSN 0076-6879, DOI: 10.1016/S0076-6879(09)05410-X

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provided by atomic force microscopy images of the organization of rhodopsin in mouse rod outer segment discs (Fotiadis et al., 2003; Liang et al., 2003). These studies clearly demonstrated individual rhodopsin molecules within an oligomeric array of closely packed dimers. As members of the GPCR superfamily, potential oligomerization of various chemokine receptors has been investigated widely. An example of the potential physiologic relevance of chemokine receptor oligomerization was demonstrated following the discovery of a natural genetic mutation of the CCR5 receptor, termed ccr5–32D, which conferred resistance to HIV-1 infection. Individuals homozygous for this mutation were found to be resistant to HIV-1 infection (Liu et al., 1996). Individuals heterozygous for this allele display a delayed progression from infection with HIV-1 to the development of AIDS (Dean et al., 1996; Huang et al., 1996; Micheal et al., 1997; Samson et al., 1996). This delayed progression of infection observed in heterozygous individuals has been hypothesized to result from the homo-oligomerization of ccr5– 32D with wild-type CCR5, resulting in a reduced level of CCR5 expressed at the cell surface (Benkirane et al., 1997). Oligomerization has also been implicated in the delayed progression of HIV-1 infection to AIDS observed in individuals possessing a CCR2 receptor polymorphism CCR2V64I (Smith et al., 1997). Although CCR2 has not been shown to act as a coreceptor for HIV-1, it can form hetero-oligomers with CCR5 and CXCR4 (Mellado et al., 1999), and this is hypothesized to explain the delayed progression of the disease. Demonstration of hetero-oligomerization between both pairs of coexpressed chemokine receptors (Sohy et al., 2007) and the CXCR2 receptor and the DOP opioid receptor (Parenty et al., 2008) have also been instrumental in appreciation of ways in which ligands that lack direct affinity for a GPCR expressed in isolation can produce allosteric effects on that receptor in the presence of a second GPCR for which the ligand does have affinity, if the two GPCRs form a functional hetero-oligomer (Milligan and Smith, 2007; Springael et al., 2007). Several techniques have been developed to investigate GPCR oligomerization. Some of the most useful approaches use energy transfer technology to explore direct protein-protein interactions. Each specific technique in this area yields information on receptor oligomerization that is complementary to the data yielded by the other approaches, and when used in combination, can provide strong evidence of oligomerization.

2. Coimmunoprecipitation Coimmunoprecipitation is a technique that uses antibodies specific for two different forms of a single receptor or a pair of antibodies that identify different receptors that are coexpressed to demonstrate the presence of the

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protein targets for the antibodies in the same supramolecular complex. Although unable to distinguish between direct protein-protein interactions involving the target proteins and simply their presence within a larger protein complex, coimmunoprecipitation-based studies have been central features of many studies on GPCR oligomerization and are often the only practical biochemical approach to address this issue in native cells and tissues. The availability of well-characterized anti-chemokine receptor antibodies has allowed more widespread analysis of chemokine receptor heterooligomerization in native cells than for many other GPCRs. Despite this, even in studies on chemokine receptor oligomerization, the use of differentially epitope-tagged forms of the receptors that have been coexpressed in heterologous cell lines, and their coimmunoprecipitation by anti-epitope tag antibodies, has played an important role in exploring the molecular basis and relevance of oligomerization. Coimmunoprecipitation has been applied to demonstrate the homo-oligomerization of a variety of chemokine receptors including CCR2 (Rodriguez-Frade et al., 1999), CCR5 (Vila-Coro et al., 1999), CXCR1 (Wilson et al., 2005), and CXCR2 (Trettel et al., 2003; Wilson et al., 2005). This technique has also been used to demonstrate hetero-oligomerization between pairs of chemokine receptors including CCR2 and CCR5 (Mellado et al., 2001), CCR2 and CXCR4 (Percherancier et al., 2005), and CXCR1 and CXCR2 (Wilson et al., 2005), as well as hetero-interactions between chemokine receptors and other GPCRs, for example CXCR2 and the DOP opioid receptor (Parenty et al., 2008) and CCR5 and the MOP opioid receptor (Chen et al., 2004). Interactions consistent with the presence of chemokine receptor heterooligomers have previously been demonstrated (see Wang and Norcross 2008 for a review). For example, modification of the chemokine receptors CXCR1 and CXCR2 by the addition of Flag and c-Myc epitope tags to the N-terminal of these receptors and their coexpression in HEK293 cells allowed anti-Flag immunoprecipitation. Subsequent separation of the immunoprecipitates and detection with anti-c-Myc revealed immunoreactivity consistent with the presence of a CXCR1/CXCR2 oligomer in the transfected cells (Wilson et al., 2005) as illustrated in Fig. 10.1. An important consideration when coimmunoprecipitation is used is that because of the highly hydrophobic nature of GPCRs, there is a natural tendency for the receptors to aggregate on removal from the plasma membrane. To address this concern it is important to include appropriate controls. These include studies in which lysates from two different cell populations each expressing only one of the GPCRs under examination are mixed before the initial immunoprecipitation step. Figure 10.1 demonstrates that when such controls were performed with cell lysates individually expressing differentially epitope-tagged forms of CXCR1 and CXCR2, there was no indication of interactions between the two receptors, which could only reflect an artefact of the experimental setup.

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250 160 105 75 a myc

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Figure 10.1 Coimmunoprecipitation. HEK293 cells were mock-transfected (mock) or transfected to transiently express Flag-(human) h-CXCR1, c-Myc-h-CXCR2, or both (co-transfected). Samples containing either Flag-h-CXCR1 or c-Myc-h-CXCR2 were also mixed (mix). Confirmation of expression of the appropriate constructs was obtained by immunoblotting cell lysates with either anti-c-Myc or anti-Flag (lower panels). Cell lysates were subsequently immunoprecipitated with anti-Flag. Immunoprecipitated samples were resolved by SDS-PAGE and immunoblotted with anti c-Myc (upper panel) (adapted fromWilson et al. [2005]).

Another important practical consideration in such studies is the centrifugal force used to remove particulate material remaining after cell lysis and membrane solubilization before the immunoprecipitation step. It is vital to centrifuge for a relatively long time and at high centrifugal force. This is done to ensure removal of small membrane fragments that may remain in the ‘‘soluble’’ supernatant fraction that would result in a false-positive result being observed that, rather than oligomerization, might simply reflect the presence of copies of the two monomeric receptors within these membrane fragments. As noted earlier, coimmunoprecipitation may be exploited to investigate chemokine receptor hetero-oligomerization within native tissues if pairs of suitable and well-characterized anti-receptor antibodies are available.

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For example, Suzuki et al. (2002) used receptor-specific antibodies to demonstrate the ability of CCR5 to form hetero-oligomers with each of DOP, KOP and MOP opioid receptors in human CEMx174 lymphocytes.

2.1. Coimmunoprecipitation protocol following heterologous expression of epitope-tagged chemokine receptors Seed HEK293T cells into 10 cm2 dishes. When the cells have reached 60 to 70% confluency, transfect the cells with Lipofectamine reagent according to manufacturers’ instructions (Invitrogen, Paisley, U.K.). The differentially epitope-tagged constructs should be both expressed individually and coexpressed and a mock transfection control should also be included. Harvest cells 48 h after transfection and resuspend the cell pellet with 1 ml of 1
RIPA (radioimmune precipitation assay) buffer (100 mM HEPES, pH 7.4, 300 mM sodium chloride, 2% Triton-X 100, 1% sodium deoxycholate, and 0.2% sodium dodecyl sulfate) supplemented with 10 mM NaF, 5 mM EDTA, pH 8, 10 mM NaH2PO4, 5% ethylene glycol, and a Complete EDTA-free protease inhibitor tablet. Place the samples on a rotating wheel at 4  C for 1 h. Centrifuge the samples for 60 min at 100,000g at 4  C and transfer the supernatant to a fresh tube containing 200 ml of 1
RIPA and 50 ml of Protein G (GE Healthcare) to preclear the samples. Incubate the samples at 4  C on a rotating wheel for 1 h. Pellet the Protein G by centrifugation for 10 min at 20,800g, at 4  C. Remove the supernatant into a fresh tube and determine the protein concentration with a bicinhoninic acid (BCA) assay method. This method uses bicinhoninic acid and copper sulphate solutions in which proteins reduce the Cu (II) ions to Cu (I) ions in correlation with protein amount initiating a color change caused by BCA binding to reduced Cu (I). The absorption of the protein samples can be recorded at 562 nm and the concentration calculated by referring to a standard curve. Equalize the protein concentration of the samples to 1 mg/ml with 1
RIPA. At this stage a mixed protein control should be generated in which equal amounts of the samples each expressing a single epitope-tagged chemokine receptor construct should be present. The total protein present in this control should equal the other samples; 600 ml of each sample should be incubated overnight with 40 ml Protein G and an optimal concentration of antibody directed against the epitope of interest at 4  C on a rotating wheel. If the receptors of interest undergo marked N-glycosylation, this may hinder the binding of the antibody and it can be beneficial to include N-glycosidase F to promote deglycosylation in the pulldown step. Reserve 100 ml of the equalized supernatant to investigate protein expression in the cell lysates. Approximately 16 h after incubation, centrifuge samples at 20,800g for 1 min at 4  C and wash the pelleted Protein G

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beads with 500 ml 1
RIPA buffer. Repeat this washing step a further twice before adding 40 ml Laemmli sample buffer. Heat the samples to 85  C for 4 min to elute the proteins. Analyze both immunoprecipitated samples and cell lysates with SDS-PAGE gel electrophoresis.

3. Resonance Energy Transfer Techniques Resonance energy transfer techniques have been used extensively to demonstrate chemokine receptor and other GPCR oligomerization. The main advantage these techniques offer is the ability to demonstrate GPCR interactions in living cells. These techniques exploit the nonradiative transfer of energy between an energy donor and acceptor pair and are based on the Fo¨rster mechanism. This theory states that the energy transfer efficiency is inversely proportional to the distance between donor and acceptor molecules by the sixth power calculated by:


E ¼ 1= 1 þ ½r=Ro 6 ; (Forster, 1948). This calculation demonstrates that the extent of energy transfer between the donor and acceptor moieties is highly dependent on ˚ the proximity of the moieties with the permissive distance being <100 A apart to record significant energy transfer (Wu and Brand, 1994). Two types of energy transfer techniques are commonly used. These are termed bioluminescence resonance energy transfer (BRET) and fluorescence resonance energy transfer (FRET). The main difference between the two techniques is that in the case of FRET the donor is excited by an external light source, whereas in BRET the donor protein is luminescent. The receptors of interest can be N- or C-terminally conjugated to donor and acceptor moieties that possess overlapping donor emission and acceptor excitation wavelengths. If the donor and acceptor molecules are within a RET permissive distance, then the energy will be reemitted at a wavelength that is characteristic of the acceptor moiety. The extent of the energy transfer observed depends on several factors. The extent of the overlap between the donor emission and acceptor excitation spectra is an important factor, as is the orientation of the donor and acceptor moieties. It is possible that an interaction could be occurring that results in donor and acceptor molecules being organized into an orientation that is unfavorable to energy transfer, resulting in a false-negative result (Kroeger and Eidne, 2004; Pfleger and Eidne, 2003). In general, the acceptor and donor moieties are appended to the C-terminal tail of the GPCRs under study. This means that the acceptor and donor are located intracellularly, and signals obtained are

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not limited to those from fully mature, cell surface–located receptors and are likely to include signals from immature and incorrectly folded proteins that are destined for rapid proteasomal destruction. This may generate artefacts, particularly in studies that rely exclusively on transient expression studies.

3.1. Bioluminescence resonance energy transfer (BRET) BRET is an energy transfer technique that uses a bioluminescent donor, generally the luciferase from the sea pansy Renilla reniformis (RLuc), and a fluorescent acceptor. On addition of a luciferase substrate (e.g., h-coelenterazine) the substrate is oxidized, and light energy is released. The earliest BRET assays to be developed used enhanced YFP (eYFP), derived from the green fluorescent protein (GFP) from the jellyfish Aequoria victoria, as the acceptor molecule (Xu et al., 1999, 2003). Subsequently variants have been developed. These include the development by PerkinElmer of a modified form of GFP termed GFP2 and a modified donor substrate termed DeepBlueC to generate the system generically described as BRET2 (Ayoub et al., 2002; Ramsay et al., 2002). This offers greater spectral resolution between donor and acceptor molecules. BRET2 can also be exploited to quantify the interaction between receptor pairs. ‘‘Saturation’’ BRET curves (Ayoub et al., 2004; Mercier et al., 2002; Ramsay et al., 2004) can be constructed by expressing differing amounts of donor and acceptor conjugated receptors and mathematical analysis then yields maximal BRET and BRET50 values. The BRET50 value is the ratio of (energy acceptor)/(energy donor), yielding a half-maximal BRET signal and gives an indication of the relative affinity of the receptors for each other. An example of saturation BRET is shown in Fig.10 2. Parenty et al. (2008) used saturation BRET to demonstrate the hetero-oligomerization of the chemokine CXCR2 receptor with the DOP opioid receptor and produced data to suggest that this interaction was of higher affinity than for either CXCR2 or DOP receptor homo-oligomers. BRET has been used extensively to investigate chemokine receptor oligomerization. Homo-oligomerization of CCR2 (Issafras et al., 2002), CXCR4 (Percherancier et al., 2005), and CCR5 (Babcock et al., 2003) has been demonstrated with this technique. The hetero-oligomerization of CCR2 and CCR5 has also been explored with BRET (El-Asmar et al., 2005).

3.2. Single-point BRET2 protocol Seed HEK293T cells into 10 cm2 tissue culture dishes. When the cells have reached 60 to 70% confluency, transfect the cells with Lipofectamine reagent according to manufacturers’ instructions (Invitrogen, Paisley, U.K.). The donor-tagged receptor should be expressed alone, as well as coexpressed with the acceptor conjugate to determine bleedthrough between the channels.

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110 100 90 80 70 60 50 40 30 20 10 0 −10

h-CXCR2-RLuc : h-CXCR2-GFP2 h-CXCR2-RLuc : h-DOP-GFP2

0.0

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Figure 10.2 Saturation BRET2 studies: h-CXCR2-Renilla luciferase and h-CXCR2GFP2 (filled squares) or h-CXCR2-Renilla luciferase and h-DOP-GFP2 (open squares) were transiently coexpressed in HEK293 cells. After addition of the luciferase substrate/ BRET2 energy donor, DeepBlueC BRET measurements were made. Data were analyzed with the one site binding hyperbola equation yielding BRETMAX and BRET50 values (adapted from Parenty et al. [2008]).

Harvest the cells 48 h after transfection in 1
phosphate-buffered saline (PBS) supplemented with 1 g/L glucose. Resuspend the cell pellet in a final volume of 1 ml PBS/glucose. Dispense 160 ml of the cell slurry into a white-walled 96-well plate in triplicate. If the effects of an agonist are to be studied, add 20 ml of the agonist dilution to the wells and incubate at 37  C for a suitable time period. If no agonist is to be tested, then add 20 ml of PBS/glucose to the well. Dilute the DeepBlueC substrate 1:20 in PBS/glucose, protecting the solution from light until required. Add 20 ml of substrate per well immediately before measuring BRET2. This results in a final concentration of 10 mM DeepBlueC. Record the energy transfer immediately. 3.2.1. Saturation BRET2 protocol Seed HEK293T cells into 6-well tissue culture dishes. When the cells have reached 60 to 70% confluency, transfect the cells with Lipofectamine reagent according to manufacturers’ instructions (Invitrogen, Paisley, U.K.). Transfect cells with a constant amount of Renilla Luciferase–linked construct and varying amounts of acceptor GFP2 construct. When HEK293T cells are used do not exceed 2 mg of DNA/well.

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Harvest the cells 48 h after transfection in 1
PBS supplemented with 1 g/L glucose. Resuspend the cell pellet in a final volume of 1 ml PBS/glucose. BRET2 is then assessed as previously described for single-point BRET2 experiments. Luminescence and fluorescence measurements are obtained for the transfected samples. Dispense 50 ml of cells in duplicate for each transfectant into white-walled 96-well plates for luminescence readings and blackwalled 384-plates for fluorescence measurements. To record luminescence, add 50 ml of h-coelenterazine to the cells yielding a final concentration of 5 mM. Incubate the 96-well plate for 30 min at 37  C before reading at 410 nm. To record fluorescence, measure GFP2 with an excitation filter at 400 nm, an emission filter at 510 nm, and the following parameters: gain, 1; photo multiplicator tube, 1100 V; time, 1.0 sec. We have generally used the Mithras LB940 microplate reader (Berthold Technology, Bad Wildbad, Germany) to perform BRET2 studies, although a range of other readers may be used. Readings should be recorded with a 410 nm (bandpass 80 nm) filter corresponding to light emission resulting from luciferase catalyzing the substrate conversion to coelenteramide. Energy transfer emitted by GFP2 should be detected with a 515-nm (bandpass 30-nm) filter and a ratiometric reading obtained corresponding to the ratio of light intensity (515 nm) to light intensity (410 nm).

3.3. Data analysis BRET2 readings should be corrected for energy transfer resulting from ‘‘bleedthrough’’ of the RLuc construct expressed alone but detected in the GFP2 channel. Fluorescence readings should be corrected for the endogenous fluorescence detected for nontransfected HEK293T cell membranes. To construct saturation BRET2 graphs, calculate fluorescence readings over luminescence ([acceptor]/[donor]) and plot this against the BRET2 ratios. For acceptor and donor-linked proteins interacting directly, this should generate a hyperbolic saturation curve, reaching a plateau with increasing [acceptor]/[donor] ratio that corresponds to BRETMAX. Nonspecific interactions that reflect random collisions between the proteins are anticipated to generate BRET signals that increase in a linear manner with increasing [acceptor]/[donor] ratio (see Milligan and Bouvier [2005] for further discussion). GraphPad Prism 4 or another appropriate data fitting package can be used to analyze data with the one site binding hyperbola equation yielding BRETMAX and BRET50 values.

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3.4. Time-resolved FRET Time-resolved FRET (Tr-FRET) is a technique that uses epitope-specific antibodies that are conjugated to fluorescent moieties capable of participating in energy transfer. Given their commercial availability, anti-Flag and c-Myc tags are most commonly used, but this should not be considered to be restricted. This technique exploits the prolonged fluorescent characteristics of lanthanide compounds, permitting a short delay between excitation and detection (Bazin et al., 2002; Morrison, 1998). This delay serves to allow any short-lived autofluorescence to decay and hence yields a superior signal/noise ratio. Tr-FRET offers the advantage of facilitating the detection of GPCR oligomers present only at the cell surface in living cells. Assuming that the labeled antibodies are directed against elements on the extracellular face of the chemokine receptors of interest or against epitope tags engineered into the extracellular N-terminal domain of the receptor(s), incubation of the antibodies with intact cells should result in any energy transfer observed resulting exclusively from interactions with receptors that are present at the cell surface. The inclusion of negative controls in such experiments is vital. A negative control in which the Flag and c-Myc or otherwise-tagged chemokine receptors under study have been expressed individually and mixed before antibody incubation should give little energy transfer. This is due to the lack of hetero-oligomers present and, therefore, on antibody binding the donor and acceptor molecules will be out with permissive distance to allow energy transfer. Figure 10.3 demonstrates on coexpression of appropriately N-terminally tagged CXCR2 and DOP opioid receptors, energy transfer can be observed, whereas in the mixed cell control little energy transfer is detected. A further important control is to record that the antibodies linked to acceptor and donor species actually bind and recognize their target proteins. In a situation in which little or no energy transfer is observed, it is vital to determine whether this is due to a lack of binding or a true reflection of the lack of oligomerization of the target GPCRs. In our own experiments we have used commercially available antibodies directed against the c-Myc- and Flag-epitope tags conjugated to the donor and acceptor moieties Europium3þ (Eu3þ) and Allophycocyanin (APC), respectively, from PerkinElmer). Tr-FRET was recorded with a Victor2 multiwell plate reader that is equipped to record time resolved measurements. As for BRET studies, a number of other commercial readers are suitable for such studies. Readings should be obtained by excitation at 340 nm with emission being recorded at 615 nm, corresponding to donor, and 665 nm corresponding to the acceptor. The delay time between excitation and emission readings is 50 msec with a measurement window time of 200 msec and a 1000 msec cycle time.

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Figure 10.3 Tr-FRET. c-Myc-h-DOP and Flag-h-DOP or c-Myc-h-CXCR2 and FLAG-h-DOP were expressed individually in HEK293 cells that were then mixed (mix) or the two receptors were coexpressed (co). After addition of a combination of Eu3þ-labeled anti-c-Myc, to act as a long-lived energy donor, and APC-labeled antiFlag, to act as a potential energy acceptor, to intact cells Tr-FRET was monitored as described in 3.4 (adapted from Parenty et al. [2008]).

Tr-FRET has been used to demonstrate CXCR1/2 receptor homoand hetero-oligomerization (Wilson et al., 2005) and DOP opioid receptor hetero-oligomerization with CXCR2 (Parenty et al., 2008). Theoretically, in homo-oligomerization studies the bivalent nature of the antibodies used may result in the cross-linking and aggregation of receptors and the generation of artifactual false-positive data. This could be overcome by the use of reagents based on antibody Fab fragments and is not a significant concern in hetero-oligomerization studies. Although not yet applied to studies of chemokine receptor oligomerization, the recent development of CLIP and SNAP-tag technologies (see Section 4) may eliminate these concerns. 3.4.1. Protocol Seed HEK293T cells into 10 cm2 tissue culture dishes. When the cells have reached 60 to 70% confluency, transfect the cells with Lipofectamine reagent according to manufacturers’ instructions (Invitrogen, Paisley, U.K.). The Flag and c-Myc–tagged receptors should be expressed alone, as well as coexpressed to generate the appropriate controls.

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Harvest the cells 48 h after transfection and mix the cells that have been transfected with the tagged receptors expressed individually. This provides a ‘‘mixed’’ cell control. Resuspend the cell pellets in 200 ml of icecold PBS. Dilute the anti-c-Myc Eu3þ and anti-Flag APC antibodies in 50% newborn calf serum: 50% PBS yielding a final concentration of 5 nM and 15 nM, respectively. A dilution containing the anti-c-Myc Eu3þ antibody should also be prepared. Aliquot 250 ml of the antibody dilutions into fresh tubes and add 50 ml of resuspended cells resulting in antibody incubations containing only anti-c-Myc Eu3þ or containing both anti-c-Myc Eu3þ and anti-Flag APC antibodies for each sample. Mix the samples by gently flicking the tubes and incubate on a rotating wheel at room temperature for 2 h. The samples should be covered in aluminium foil to minimize the exposure of the fluorophores to light. Centrifuge the samples at 1000g for 1 min and aspirate the antibody mix from the cell pellet. Wash the cell pellet 2
in ice-cold PBS before resuspending the cells in 250 ml of PBS. If the effect of an agonist on energy transfer is to be investigated, transfer 90 ml of cells into a fresh tube and incubate with the chosen concentration of the agonist at 37  C To measure energy transfer 40 ml of each sample (both samples incubated with anti-c-Myc Eu3þ alone or incubated with both anti-c-Myc Eu3þ and anti-Flag APC antibodies) should be dispensed in triplicate into a blackwalled 384-well plate. Blank wells containing PBS should also be included. Record the energy transfer with a Tr-FRET protocol. The presence of anti-Flag APC binding should be determined by direct excitation of the samples at 620 nm and measurement of emission at 665 nm. 3.4.2. Data analysis Normalized FRET can be calculated with the equation:

Normalized FRET ¼ ððA665  BLKÞ=D615 Þ  C Where A665 is the fluorescent emission from the acceptor, D615 is the fluorescent emission from the donor, and BLK represents the background reading at 665 nm from the wells containing PBS. C represents the crosstalk between the donor and acceptor windows for the samples incubated with only anti-c-Myc Eu3þ and is equal to A665-BLK/D615.

3.5. FRET imaging in living cells Spectral FRET imaging provides a further method of studying receptor oligomerization in living cells. Three sets of measurements must be recorded in this technique: the sensitized fluorescence and the donor and acceptor fluorescence. Because of the close spectral overlap of the donor and

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acceptor pair, it is essential to record the degree of bleedthrough between filter sets. FRET is most commonly expressed as the ratio of bleedthrough corrected sensitized fluorescence to donor or acceptor fluorescence. The most commonly used acceptor and donor pairing to tag receptors for such studies are enhanced cyan fluorescent protein (eCFP) and eYFP, although other pairings are possible, and the development of both further spectrum-modified forms of the original GFP (Heim et al., 1994; Tsien, 1998) and of other fluorescent proteins from a variety of marine organisms (Matz et al., 1999; Shaner et al., 2005) has greatly expanded the available pairings and allowed the development of linked FRET pairings to explore the presence of more than two proteins within a multimolecular complex (Lopez-Gimenez et al., 2007). As in the other RET-based approaches, it is important to include appropriate negative controls in these studies. These may include experiments in which a chemokine receptor conjugated to eCFP and nonconjugated eYFP acceptor proteins are coexpressed. Any energy transfer observed must indicate nonspecific signals, as nonconjugated eYFP is cytoplasmic and, therefore, should not be within FRET-competent distance of a membrane inserted chemokine receptor. Figure 10.4 demonstrates the robust energy transfer observed on coexpression of CXCR1-eCFP and DOP-eYFP. The energy transfer resulting from expression of CXCR1-eCFP and eYFP is very low and suggests that 0.25

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Figure 10.4 FRET imaging. CXCR1-eCFP was transiently expressed in HEK293T cells with or without DOP-eYFP or eYFP alone and fluorescence imaged. Raw FRET and calculated normalized FRET (shown above) was then assessed as in section 3.5.2.

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the signal observed for the CXCR1-DOP opioid receptor pairing is not simply an artefact of direct interactions between the two autofluorescent proteins. FRET imaging has been used to demonstrate CXCR4 homooligomerization (Toth et al., 2004), CXCR1/2 receptor homo- and hetero-oligomerization (Wilson et al., 2005), and DOP opioid receptor and CXCR2 hetero-oligomerization (Parenty et al., 2008). In our own studies with FRET imaging, cells are visualized with a Nikon Eclipse TE2000-E fluorescence inverted microscope and images obtained individually for eYFP, eCFP, and FRET filter channels with an Optoscan monochromator (Cairn Research, Faversham, Kent, UK) and a dichroic mirror 86002v2bs (Chroma Inc., Rockingham, VT). The filter sets used were eYFP (excitation, 500/5 nm; emission, 535/30 nm), eCFP (excitation, 430/12 nm; emission, 470/30 nm), and FRET (excitation, 430/12 nm; emission, 535/30 nm). The illumination time was 250 msec and binning modes 2
2. As with other techniques described previously, other microscopes are also appropriate, and the selection of filter sets will be determined by the exact pair of FRET reporters selected for the studies. 3.5.1. Protocol Seed HEK293T cells into 6-well plates containing glass coverslips that have been coated with poly-D-lysine. When the cells have reached 60 to 70% confluency, transfect the cells with Lipofectamine reagent according to manufacturers’ instructions. The eCFP/eYFP-tagged receptor constructs should be expressed individually, as well as coexpressed to permit the calculation of the bleedthrough factor. Twenty-four hours after transfection, remove the glass coverslip and place a fragment of it into a microscope chamber containing physiologic saline solution (130 mM NaCl, 5 mM KCl, 1 mM CaCl2, 1 mM MgCl2, 20 mM HEPES, 10 mM D-glucose, pH 7.4). Visualize the cells with a fluorescence microscope and obtain images for eYFP, eCFP, and eFRET filter channels. Care should be taken to ensure that the cells are in focus to aid analysis. 3.5.2. Data analysis We use MetaMorph imaging software (Universal Imaging Corp., West Chester, PA) to successfully quantify the FRET images with the sensitized FRET method. Corrected FRET can be calculated with a pixel-by-pixel methodology with the equation:

FRETc ¼ FRET  ðcoefficient B
eCFPÞ  ðcoefficient A
eYFPÞ; where eCFP, eYFP, and FRET values correspond to background corrected images obtained through the eCFP, eYFP, and FRET channels. B and A

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correspond to the values obtained for the eCFP (donor) and eYFP (acceptor) bleedthrough coefficients, respectively, calculated with cells singly transfected with either the eCFP or eYFP protein alone. To correct the FRET levels for the varying amounts of donor (eCFP) and acceptor (eYFP) expressed, normalized FRET was calculated with the equation:

FRETn ¼ FRETc=eCFP
eYFP; where FRETc, eCFP, and eYFP are equal to the fluorescence values measured for each individual cell. FRET should be recorded for several cells within an experiment and the results combined.

4. Developing Techniques A number of alternative techniques to study GPCR oligomerization have been recently developed that, if applied to chemokine receptor oligomerization, could potentially further our understanding in the field. Technology permitting simultaneous protein labeling in living cells has recently been described by Covalys. The development of CLIP- and SNAP-tags offers the ability to detect two different fusion proteins inside the same cell or at the cell surface. These tags are derived from the O6guanine nucleotide alkyltransferase. The SNAP-tag specifically recognizes substrates based on benzyl guanine, whereas the CLIP-tag reacts with benzylcytosine derivatives permitting simultaneous labeling. The SNAPand CLIP-tags are approximately two-thirds the size of GFP and allow several applications including the study of receptor internalization and protein localization. The application of this technology to GPCR oligomerization has been described Maurel et al. (2008). The authors used N-terminally tagged Flag-GABAB2 and SNAP-GABAB1 to perform Tr-FRET experiments investigating the oligomerization of the receptors. Large Tr-FRET signals were detected after incubation with benzyl guanine conjugated to the donor fluorophore and an anti-Flag antibody conjugated to the acceptor. A major disadvantage to the traditional Tr-FRET approach is the use of antibodies that, because of their bivalent nature, could potentially stabilize large complexes giving a false-positive result. The SNAP/ CLIP tag technology eliminates the need for antibodies and so avoids this issue. Another advantage this technology offers is the ability to label only cell surface proteins, eliminating a high proportion of the ‘‘bystander’’ energy transfer observed with BRET where the luciferase substrate is cell permeable. The method can also be modified to 96- and 384-well formats that make it amenable to high-throughput adaptation.

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Bimolecular fluorescence complementation (BiFC) is another technique that has been used to investigate GPCR oligomerization (Hu et al., 2002; Shyu et al., 2006). The principle of this technique is the use of distinct N- and C-terminal fragments of eYFP, or other autofluorescent proteins, that are not fluorescent when expressed individually or coexpressed. However, if linked to proteins that dimerize, the N- and C-terminal fragments of the autofluorescent protein are able to interact and generate fluorescence. This technique offers the advantage of a stable fluorescence signal being observed without the need for additional antibodies or fluorescent agents. However, this could also be viewed as a disadvantage, because it permits no real-time detection of rapidly occurring changes in oligomerization. LopezGimenez et al. (2007) used this technology to investigate oligomerization of the a1b-adrenoceptor within the endoplasmic reticulum and, hence, at an early stage in protein synthesis and maturation. This technique has been expanded to develop multicolor BiFC that permits interactions occurring between multiple combinations of proteins within the same cell to be visualized (Hu and Kerppola, 2003). Multicolor BiFC uses the reconstitution of distinct fluorescent protein spectral variants. By fusing fragments to several potential interaction partners, the complexes formed can be visualized independently in the same cell. Vidi et al. (2008) used this approach to demonstrate the formation of A2A/D2 hetero-oligomers and A2A homooligomers and their colocalization. Recently Gandia et al. (2008) have reported a combined BRET-BiFC technique that has permitted the detection of adenosine A2A receptor oligomers and the explanation that these oligomers contain more than two promoters. In this study the authors used the reconstituted eYFP fragments to act as an acceptor in the BRET assay.

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Matz, M. V., Fradkov, A. F., Labas, Y. A., Savitsky, A. P., Zaraisky, A. G., Markelov, M. L., and Lukyanov, S. A. (1999). Fluorescent proteins from nonbioluminescent Anthozoa species. Nat. Biotechnol. 17, 969–973. Maurel, D., Comps-Agrar, L., Brock, C., Rives, M. L., Bourrier, E., Ayoub, M. A., Bazin, H., Tinel, N., Durroux, T., Prezeau, L., Trinquet, E., and Pin, J. P. (2008). Cell-surface protein-protein interaction analysis with time-resolved FRET and snap-tag technologies: Application to GPCR oligomerization. Nat. Methods 5, 561–567. Mellado, M., Rodriguez-Frade, J. M., Vila-Coro, A. J., de Ana, A. M., and Martinez, A. (1999). Chemokine control of HIV-1 infection. Nature 400, 723–724. Mellado, M., Rodriguez-Frade, J. M., Vila-Coro, A. J., Fernandez, S., Martin, D. A., Jones, D. R., Toran, J. L., and Martinez, A. (2001). Chemokine receptor homo- or heterodimerization activates distinct signaling pathways. EMBO J. 20, 2497–2507. Mercier, J. F., Salahpour, A., Angers, S., Breit, A., and Bouvier, M. (2002). Quantitative assessment of beta 1- and beta 2-adrenergic receptor homo- and heterodimerization by bioluminescence resonance energy transfer. J. Biol. Chem. 277, 44925–44931. Michael, N. L., Louie, L. G., and Sheppard, H. W. (1997). CCR5-delta 32 gene deletion in HIV-1 infected patients. Lancet 350, 741–742. Milligan, G., and Bouvier, M. (2005). Methods to monitor the quaternary structure of G protein-coupled receptors. FEBS J. 272, 2914–2925. Milligan, G. (2007). G protein-coupled receptor dimerisation: Molecular basis and relevance to function. Biochim. Biophys. Acta 1768, 825–835. Milligan, G., and Smith, N. J. (2007). Allosteric modulation of heterodimeric G-proteincoupled receptors. Trends Pharmacol. Sci. 28, 615–620. Morrison, L. E. (1988). Time-resolved detection of energy transfer: Theory and application to immunoassays. Anal. Biochem. 174, 101–120. Parenty, G., Appelbe, S., and Milligan, G. (2008). CXCR2 chemokine receptor antagonism enhances DOP opioid receptor function via allosteric regulation of the CXCR2-DOP receptor heterodimer. Biochem. J. 412, 245–256. Percherancier, Y., Berchiche, Y. A., Slight, I., Volkmer-Engert, R., Tamamura, H., Fujii, N., Bouvier, M., and Heveker, N. (2005). Bioluminescence resonance energy transfer reveals ligand-induced conformational changes in CXCR4 homo- and heterodimers. J. Biol. Chem. 280, 9895–9903. Pfleger, K. D., and Eidne, K. A. (2003). New technologies: Bioluminescence resonance energy transfer (BRET) for the detection of real time interactions involving G-protein coupled receptors. Pituitary 6, 141–151. Ramsay, D., Kellett, E., McVey, M., Rees, S., and Milligan, G. (2002). Homo- and heterooligomeric interactions between G-protein-coupled receptors in living cells monitored by two variants of bioluminescence resonance energy transfer (BRET): Heterooligomers between receptor subtypes form more efficiently than between less closely related sequences. Biochem. J. 365, 429–440. Ramsay, D., Carr, I. C., Pediani, J., Lopez-Gimenez, J. F., Thurlow, R., Fidock, M., and Milligan, G. (2004). High-affinity interactions between human alpha1A-adrenoceptor C-terminal splice variants produce homo- and heterodimers but do not generate the alpha1L-adrenoceptor. Mol. Pharmacol. 66, 228–239. Rodriguez-Frade, J. M., Vila-Coro, A. J., de Ana, A. M., Albar, J. P., Martinez, A., and Mellado, M. (1999). The chemokine monocyte chemoattractant protein-1 induces functional responses through dimerization of its receptor CCR2. Proc. Natl. Acad. Sci. USA 96, 3628–3633. Samson, M., Libert, F., Doranz, B. J., Rucker, J., Liesnard, C., Farber, C. M., Saragosti, S., Lapoumeroulie, C., Cognaux, J., Forceille, C., Muyldermans, G., Verhofstede, C., et al. (1996). Resistance to HIV-1 infection in Caucasian individuals bearing mutant alleles of the CCR-5 chemokine receptor gene. Nature 382, 722–725.

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Shaner, N. C., Steinbach, P. A., and Tsien, R. Y. (2005). A guide to choosing fluorescent proteins. Nat. Methods 2, 905–909. Shyu, Y. J., Liu, H., Deng, X., and Hu, C. D. (2006). Identification of new fluorescent protein fragments for bimolecular fluorescence complementation analysis under physiological conditions. Biotechniques 40, 61–66. Smith, M. W., Dean, M., Carrington, M., Winkler, C., Huttley, G. A., Lomb, D. A., Goedert, J. J., O’Brien, T. R., Jacobson, L. P., Kaslow, R., Buchbinder, S., Vittinghoff, E., et al. (1997). Contrasting genetic influence of CCR2 and CCR5 variants on HIV-1 infection and disease progression. Hemophilia Growth and Development Study (HGDS), Multicenter AIDS Cohort Study (MACS), Multicenter Hemophilia Cohort Study (MHCS), San Francisco City Cohort (SFCC), ALIVE Study. Science 277, 959–965. Sohy, D., Parmentier, M., and Springael, J. Y. (2007). Allosteric transinhibition by specific antagonists in CCR2/CXCR4 heterodimers. J. Biol. Chem. 282, 30062–30069. Springael, J. Y., Urizar, E., Costagliola, S., Vassart, G., and Parmentier, M. (2007). Allosteric properties of G protein-coupled receptor oligomers. Pharmacol. Ther. 115, 410–418. Suzuki, S., Chuang, L. F., Yau, P., Doi, R. H., and Chuang, R. Y. (2002). Interactions of opioid and chemokine receptors: Oligomerization of mu, kappa, and delta with CCR5 on immune cells. Exp. Cell Res. 280, 192–200. Toth, P. T., Ren, D., and Miller, R. J. (2004). Regulation of CXCR4 receptor dimerization by the chemokine SDF-1alpha and the HIV-1 coat protein gp120: A fluorescence resonance energy transfer (FRET) study. J. Pharmacol. Exp. Ther. 310, 8–17. Trettel, F., Di Bartolomeo, S., Lauro, C., Catalano, M., Ciotti, M. T., and Limatola, C. (2003). Ligand-independent CXCR2 dimerization. J. Biol. Chem. 278, 40980–40988. Tsien, R. Y. (1998). The green fluorescent protein. Annu. Rev. Biochem. 67, 509–544. Vidi, P. A., Chemel, B. R., Hu, C. D., and Watts, V. J. (2008). Ligand-dependent oligomerization of dopamine D(2) and adenosine A(2A) receptors in living neuronal cells. Mol. Pharmacol. 74, 544–551. Vila-Coro, A. J., Rodriguez-Frade, J. M., Martin, D. A., Moreno-Ortiz, M. C., Martinez, A., and Mellado, M. (1999). The chemokine SDF-1alpha triggers CXCR4 receptor dimerization and activates the JAK/STAT pathway. FASEB J. 13, 1699–1710. Wang, J., and Norcross, M. (2008). Dimerization of chemokine receptors in living cells: Key to receptor function and novel targets for therapy. Drug Discov. Today 13, 625–632. Wilson, S., Wilkinson, G., and Milligan, G. (2005). The CXCR1 and CXCR2 receptors form constitutive homo- and heterodimers selectively and with equal apparent affinities. J. Biol. Chem. 280, 28663–28674. Wu, P., and Brand, L. (1994). Resonance energy transfer: methods and applications. Anal. Biochem. 218, 1–13. Xu, Y., Piston, D. W., and Johnson, C. H. (1999). A bioluminescence resonance energy transfer (BRET) system: Application to interacting circadian clock proteins. Proc. Natl. Acad. Sci. USA 96, 151–156. Xu, Y., Kanauchi, A., von Arnim, A. G., Piston, D. W., and Johnson, C. H. (2003). Bioluminescence resonance energy transfer: Monitoring protein-protein interactions in living cells. Methods Enzymol. 360, 289–301.

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Subsecond Analyses of G-Protein Coupled-Receptor Ternary Complex Dynamics by Rapid Mix Flow Cytometry Tione Buranda, Yang Wu, and Larry A. Sklar Contents 228 228 229 229

1. Introduction 1.1. GPCR biology 2. Analysis of GPCR Function by Flow Cytometry 2.1. Introduction 2.2. Standardization of flow cytometry data with fluorescence calibration beads 3. Small-Volume Rapid Mix Device Flow Cytometry 3.1. General considerations 4. General Listing of Materials 4.1. Materials 5. Optimizing For Analysis of Molecular Assemblies by Flow Cytometry: Receptor Affinity 6. Modular Molecular Assemblies of GPCR Ternary Complexes on Beads 6.1. Materials 6.2. Solubilization of FPR 6.3. Modular assembly of ternary complexes on beads 7. Preparation of G-Protein Coated Beads (Ga
bg Beads) 7.1. Materials 7.2. Preparation of M2 beads 7.3. Preparation of G (abg) on M2 beads 7.4. Assembly of LRG (abg) on beads 8. Analysis of Modular Dissassembly of LRG Modules 8.1. Real-time spectrofluorometric measurement of the dissociation of L from R

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Department of Pathology and Cancer Center, University of New Mexico Health Science Center, Albuquerque, New Mexico, USA Methods in Enzymology, Volume 461 ISSN 0076-6879, DOI: 10.1016/S0076-6879(09)05411-1

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8.2. Real-time spectrofluorometric measurement of the dissociation of L from RG 8.3. Rapid mix measurement of guanine nucleotide–induced disassembly of ternary complexes 8.4. Real-time rapid mix measurement of the dissociation of Ga from Gbg: disassembly of module in Fig. 11.2B 8.5. Rapid mix measurement of the dissociation of R from Gabg: disassembly of modules in Fig. 11.2A,D 8.6. Rapid-mix measurement of the dissociation of LF from RGabg: disassembly of module in Fig. 11.2C 9. Summary and Outlook Acknowledgments References

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Abstract The binding of full and partial agonist ligands (L) to G-protein–coupled receptors (GPCRs) initiates the formation of ternary complexes with G-proteins (LRG complexes). We describe the assembly of detergent-solubilized LRG complexes on beads. Rapid mix flow cytometry is used to analyze the subsecond dynamics of guanine nucleotide–mediated ternary complex disassembly. Ternary complexes were assembled with three formyl peptide receptor constructs (wild type, FPR-Gai2 fusion, and FPR-GFP fusion) and two isotypes of the a subunit (ai2 and ai3) and bg dimer (b1g2 and b4g2). Experimental evidence suggests that thermodynamic stability of ternary complexes depends on subunit isotype. Comparison of assemblies derived from the three constructs of FPR and G-protein heterotrimers composed of the available subunit isotypes demonstrate that the fast step is associated with the separation of receptor and G-protein and that the dissociation of the ligand or of the a and bg subunits was slower. These results are compatible with a cell activation model involving G-protein conformational changes rather than disassembly of Gabg heterotrimer.

1. Introduction 1.1. GPCR biology G-protein–coupled receptors (GPCRs) belong to the largest family of transmembrane signaling molecules. G-proteins are comprised of 27a-, 5b-, and 13g-subunit proteins that combine to form functional heterotrimeric units (Sprang et al., 2007). The functional proclivities of the various combinations of a, b, and g heterotrimers are dictated by subunit isotype (Robishaw and Berlot, 2004). Interaction of ligand-stimulated GPCRs with specific heterotrimeric G-proteins triggers the exchange of GDP for GTP at the nucleotide binding pocket of Ga-subunits, resulting in dissociation

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(Oldham and Hamm, 2007, 2008) or rearrangement (Lohse et al., 2007a,b) of the Ga-subunit from Gbg, enabling the separated/rearranged G-proteins to interact with effectors (Oldham and Hamm, 2007, 2008). We have used rapid mix flow cytometry measurements on detergentsolubilized ternary complexes of {ligand}:{GPCR}:{nucleotide-free G-protein}, assembled on beads, to examine the differential kinetics of nucleotide-induced dissociation of components (Buranda et al., 2007; Wu et al., 2007a). The most significant aspects of this work are: (1) The fastest step associated with ternary complex disassembly is the subsecond departure of the receptor from the Ga-subunit. (2) The dissociation of Ga from Gbg occurs on a time scale (t1/2  tens of seconds) not relevant to cell signaling for Gai subunits used in this study. (3) In this system GDP was shown to initiate the disassembly of ternary complexes in a manner nearly analogous to GTP (Wu et al., 2007a). Because isolated ternary complexes lack the biochemical milieu in which cellular signaling occurs, the results of this study are insensitive to potential collateral effects of downstream contact with effectors (Sprang et al., 2007; Sunahara et al., 1997). Although it has been generally assumed that neither Gbg nor Ga can interact with effectors, before GPCR activation (Sprang et al., 2007), resting state complexes of Gaq and the effector phospholipase Cb (PLCb) (Dowal et al., 2006) have been reported before GPCR activation. It is the intent of this chapter to provide experimental details for the use of modular molecular assemblies of nucleotide-free ternary complexes on beads and rapid mix flow cytometry to examine the differential kinetics of nucleotide-induced disassembly at specific junction points of the complex. This chapter will focus on the formyl peptide receptor (Buranda et al., 2007; Wu et al., 2007a). This receptor system has been well characterized in cells, membranes, and in detergent-solubilized systems in solution and on beads. Reagents, fluorescently small molecule peptide ligands (e.g., FITC-conjugated formyl-Met-Leu-Phe-Lys; fMLFK-FITC), fluorescently labeled antibodies, GFP fusion constructs, and G-protein subunits have made this system uniquely suitable as a model system to study on beads.

2. Analysis of GPCR Function by Flow Cytometry 2.1. Introduction Flow cytometry is a well-established technique for sensitive and quantitative kinetic analysis used in cellular biochemistry involving cell activation, ligand binding, or macromolecular assembly (Seamer et al., 1999; Sklar et al., 1998, 2002). Because flow cytometers can discriminate between free and cell- or particle-bound fluorophores, homogenous analysis of

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real-time events and fixed time points can be used to assess ligand/receptor interactions, as well as receptor processing and receptor-mediated cell activation without wash steps (Nolan et al., 1999; Sklar et al., 2002). Generally, the behavior of a GPCR that is expressed on the surface of a cell or immobilized on a bead can be probed by: (1) binding of a fluoresceinated ligand, (2) cell expression (or surface coverage on a bead) of a GPCR-GFP fusion, and (3) disassembly of a ternary complex. Because of the ready availability of fluorescent ligands displaying affinities from mM to pM, the FPR is a model system in which flow cytometry has been used to study ligand binding on cells, membranes, and detergent-solubilized molecular assemblies (Buranda et al., 2007).

2.2. Standardization of flow cytometry data with fluorescence calibration beads Standard fluorescence calibration beads are used to quantify the number of receptor sites on a cell or bead and to account for day-to-day variation in bead fluorescence, changes in detector settings, and use of different flow cytometers (Wu et al., 2007b). The most common standard calibration beads are commercial standards from Bangs Labs (www.bangslabs.com) QuantumTM FITC MESF beads. These beads are optimized for fluorescein but can be used for other fluorophores being analyzed under the same excitation and detection optics as long as a suitable correction factor is applied to account for the spectroscopic differences between the fluorescein and target fluorophore (e.g., eGFP). The calibration scheme has been recently described in detail (Wu et al., 2007b). The measured fluorescence intensity of any target molecule is proportional to, I0ef%T; where I0 is the intensity of the light source, eex is the absorption coefficient of the fluorophore at the excitation wavelength, f is the quantum yield of the fluorophore, and %T is the percent fraction of fluorescence light transmitted by the 530-nm, 30-nm wide bandpass filter (up to 80% maximum transmittance) and is used to account for the spectral mismatch between the sample fluorophore and the fluorescein standard. To apply Quantum FITC MESF beads to eGFPlabeled assemblies, an appropriate correction factor (cf ) must be applied as shown in Eq. (11.1) (Wu et al., 2007b):

cf ¼

ðe488 f%TÞeGFP 56; 000  0:60  40 ¼ 0:60 ¼ ðe488 f%TÞfluorescein 85; 000  0:93  28

ð11:1Þ

Eq. (11.1) corrects for the spectroscopic mismatches in e, f, and %T between the calibration standard beads and eGFP. This formalism is accurate when samples are irradiated with a nonsaturating light source. It is

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worth noting that most fluorescein conjugates tend to have lower quantum yields than the parent molecule, where simple derivatization of fluorescein typically attenuates the yield by at least 18% (e.g., fluorescein biotin) (Buranda et al., 1999) or greater (e.g., 80% for FITC antibody conjugates) (f/p ratio 4:1) (Piyasena et al., 2004). Furthermore, the reader should also be aware of the dependence on pH of fluorescein’s extinction coefficient and quantum yield. Thus the quantum yield values used in Eq. (11.1) correspond to values measured for monomeric fluorophores under neutral pH conditions. Most spectroscopic parameters are available at the Invitrogen company web site (www.invitrogen.probes.com), through the Fluorescence SpectraViewer tool.

3. Small-Volume Rapid Mix Device Flow Cytometry 3.1. General considerations In this section we detail the essential elements of a rapid mix flow cytometer, which is used to delineate the kinetics of disassembly of the ternary complex on guanine nucleotide activation (Wu et al., 2005b). Typical kinetic flow cytometry measurements generally include a 5 to 10 sec dead time (the time interval between the start of sample mixing and the point of detection) and consume wasteful quantities of precious reagents (Wu et al., 2005b). To minimize the dead time, we have established a small-volume rapid mix flow cytometry device that is capable of: (1) limiting total dead time to 250 msec, (2) minimizing total dead volume to 14 ml and (3) optimization of the efficiency of sample mixing in the laminar flow regime. Dead volume normally includes the unusable volume of the syringes and the volume lost to the connectors and the valves, which is largely determined by the dimensions of the respective components. The dead volume in the rapid mixing device determines the limiting volume of reagent that can be analyzed. The technical details of this device have been described elsewhere (Wu et al., 2005b). The prototypical device is optimized to handle 20,000 to 27,000 particles in 35- to 45-ml aliquots, and then to mix and deliver sample to the flow cytometer with an automated rapid mixing sequence. Only 40% of the beads are actually used in the kinetic analysis; 40% of the beads are lost to dead volume in syringes and valves, and 20% are lost during the initial fast boost phase, which enable the device to overcome the effects of laminar flow to attain high enough Reynolds numbers necessary to achieve fluid turbulence for efficient mixing (Ottino, 1990; Peltier and Caulfield, 2003) (see Box 11.1).

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Box 11.1 Optimizing sample mixing and delivery to the flow cytometer under laminar flow conditions

In small volumes, under the conditions of laminar flow, mixing is largely achieved by diffusion alone and is extremely slow and not practical for subsecond kinetics. The Reynolds number (Re) is often used to determine the physical characteristics of the flow (laminar or turbulent regime) (Brody et al., 1996; Purcell, 1977). For continuous flow in circular tubes, the Reynolds number is defined as:

Re ¼ rdð4u=pd 2 Þ=m

ð11:2Þ

where u is the velocity of the fluid through the tube (ml/sec), r is the fluid density (1 g/cm3), d is the diameter of the tube; and m is the viscosity of the fluid (102 g/cm2sec). The transition from laminar to turbulent flow generally occurs for Re values between 1800 and 2300 and is strongly dependent on the geometry of the system (Ottino, 1990). Transition from laminar to turbulence at relatively low flow rates can be mediated by introducing obstacles or irregularities in the system (Ottino, 1990; Peltier and Caulfield, 2003). Three-way connecting valves used in the rapid mix device provide the necessary irregularities in the system to achieve efficient mixing. In the rapid mix device (Fig. 11.1) the passage of fluid streams bearing beads and biotin through valve Y3 was characterized by fluid flow of Re  3800 (d ¼ 0.05 cm; v ¼ 2  770 ml/sec) where the sample streams were expected to be well mixed. During the sample delivery and fast boost phases, Re ranged from 1040 to 3140 (d ¼ 0.025 to 0.075 cm; v ¼ 416.7 ml/sec). At the flow cytometer (after mixing) Re was reduced to 6 (d ¼ 0.025 cm; v ¼ 1.16 ml/sec) to match the required sheath flow rate of 1 ml/sec. The performance characteristics of the rapid mix device are periodically validated by a rapid kinetics fluorescence based biotin assay (Wu et al., 2005).

4. General Listing of Materials 4.1. Materials Plastic ware was from VWR (West Chester, PA), and all chemicals and reagents were from Sigma (St. Louis, MO) except where otherwise noted; 6.2-mm diameter streptavidin-coated polystyrene beads (0.5% w/v) were purchased from Spherotech Inc. (Libertyville, IL). ai2 and ai3 G-protein subunits were purchased from Calbiochem (La Jolla, CA) and were used

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To waste

Mixing valve2 Delay line, 60 mL

To flow cytometer

Mixing valve 1

Washing buffer

Syringe1 LRG

Syringe2 GTP

Washing buffer

Syringe3

Buffer loading

Y-valve3

Buffer syringe 500 mL

Y-valve1

“Double barrel” (cell/ligand) syringes 1000 mL

Syringe4

Sample loading

Sample loading Y-valve2

Driving screw

Washing buffer

Motor

Internal syringe 2500 mL

Figure 11.1 Schematic of small volume rapid mix device. Mixing and delivery of fluid samples to the flow cytometer are initiated with the three syringes labeled ‘‘buffer’’ and‘‘double barrel’’ (syringes1and 2 define cell/bead and ligand/reagent loading, respectively).The volumes shown refer to the maximum capacity of the syringes. Samples are loaded into syringes1and 2 through the sample-loading paths of the loading‘‘Y’’connectors. The buffer syringe 3 is used to push samples from the delay line into the flow cytometer. A computer program is used to control the sequence in which syringe pumps and valves are activated. Syringe 4 is used to clean the delay line without affecting the loaded samples in the double-barrel syringes after each run. Two three-way Teflon solenoid, mixing valves (1 and 2) are used to isolate the delay line from the rest of the sample lines. Mixing valve 1 is used to switch flow between the double-barrel syringes and the buffer syringe. A 13.2-cm (60 ml) delay line is used to carry the mixed samples. Mixing valve 2 is positioned at the end of the delay line and is used to direct sample flow either into the flow cytometer or to waste.

without further purification. FLAG-his tagged bg -subunits (b1g2 or b4g2) were prepared and purified as described previously (McIntire et al., 2001; Simons et al., 2003a). The subunits were stored at 80  C in 2- to 5-ml volume aliquots depending on stock concentration (3 to 7 mM ). Membrane fractions from U937 cells expressing FPR (R), FPR-GFP (RF), or FPRGai2 fusion protein (R-Gai2) were prepared as described elsewhere (Simons et al., 2003a) and used without further purification. The following buffers were used: HPSM (pH7.5, 30 mM HEPES, 100 mM KCl, 20 mM NaCl, 1 mM MgCl2), DHPSM (HPSM with 0.1% n-dodecyl-b-D-maltoside, DOM), G-buffer (HPSM with 0.1% DOM and 1 mM dithiothreitol, DTT), and AMF solution (20 mM AlCl3, 10 mM MgCl2, and 10 mM NaF).

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5. Optimizing For Analysis of Molecular Assemblies by Flow Cytometry: Receptor Affinity To establish a rational approach to molecular assemblies on cells or beads, it is important to determine the affinity of the fluorophore-derivatized ligand. Affinity measurements are typically measured by generating equilibrium binding curves, which, if necessary, can be augmented by kinetic measurements of binding and dissociation rate constants (Buranda et al., 2007). Poor affinities (Kd values greater than approximately 50 nM ) and high reagent concentration can lead to excessive background (nonspecific) fluorescence signals. The ability of the flow cytometer to discriminate between bound and free ligands may be compromised when the concentration of soluble ligand exceeds >100 nM. Nonspecific binding or fluorescent ligand dissociation is determined by incubating the cells or beads with a large excess (i.e., 100 to 1000  Kd) of site-saturating nonfluorescent ligand. Alternately, nonspecific binding can be analyzed by incubation of the parental cells, which lack the transfected receptor, or beads, which lack the cognate receptor, in the presence of fluoresceinated peptide alone (Gilbert et al., 1999; Simons et al., 2003c). Affinity measurements can also be quantitatively evaluated by spectrofluorometry, for FPR (Simons et al., 2003a; Sklar et al., 1981, 1985). The determination of FPR ligand affinities can be accomplished through a soluble ligand competition assay as described in Simons et al. (2003a).

6. Modular Molecular Assemblies of GPCR Ternary Complexes on Beads 6.1. Materials Frozen cell membranes (500-ml aliquots), HPSM buffer, syringe with 25-gauge needle, and 25% DOM. The cloning of the FPR, its expression in U937 cells, generation of FPRGai2, and FPR-GFP fusion constructs and membrane preparations have been described elsewhere (Simons et al., 2003a). Wild-type FPR receptors and fusion constructs are over expressed (up to 500,000 receptors/cell) in U937 cells. Expression levels are optimized by sorting on the flow cytometer. The cells are lysed by nitrogen cavitation, and crude postnuclear membrane preparations are stored at 80  C in aliquots of 500 ml, corresponding to 108 cell equivalents.

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6.2. Solubilization of FPR A typical membrane solubilization preparation involves the following steps: Add 700 ml of HPSM buffer to an aliquot of thawed membranes. Centrifuge sample in a microcentrifuge tube for 15 min and remove supernatant, and resuspend the pellet in 220 ml of HPSM with a syringe attached to a 25-gauge needle. Add 25 ml of 10% dodecyl maltoside, and 2.5 ml of 100 protease inhibitor cocktail (Calbiochem, San Diego, CA) to the membrane suspension, and gently mix for 2 h at 7  C. Remove the unsolubilized material by centrifugation at 135,000g for 15 min, yielding a supernatant of solubilized FPR at 4  108 cell equivalents/ml (5 mg/ml protein), which must be used within 6 h of preparation for best results, otherwise samples can be stored at 80  C. Solubilization may yield up to 100% of receptors harvested from the membranes. It cannot be assumed that DOM allows binding activity to be retained in other GPCR systems, although it has been confirmed for b2-adrenegic receptor. The typical yield of receptors ranges from 100 to 300 nM, depending on receptor expression levels. The initial number of receptors/cell is usually determined by flow cytometry measurements, which are based on the analysis of bound fluorescent ligands used at saturating concentrations or GFP fluorescence, where applicable (cf. section on Standard calibration beads).

6.3. Modular assembly of ternary complexes on beads In cells, the ternary complex of ligand, GPCR, and heterotrimeric G-proteins is expected to have a very short lifetime, which is regulated by the kinetics of nucleotide exchange between the inactive GDP-bound form and the active GTP-bound form (Hamm, 1998, 2001). The exchange is initiated by the contact between the heterotrimeric G-protein and a ligandactivated GPCR. The ternary complex thus survives for the short duration of the dissociative interchange between GDP and GTP under rapid mass transfer considerations where intracellular [GTP] >> [GDP] and can thus more readily replace GDP. Under our experimental conditions, stable LRG assemblies on beads are created in circumstances in which the contact between the GPCR and G beads causes the ejection of GDP from the Ga nucleotide pocket with little to no chance of rebinding, because of the negligible concentrations of soluble nucleotides (GDP or GTPgS), in solution. The nucleotide pocket remains empty until the addition of excess nucleotides, which triggers the disassembly of ternary complexes during the rapid mix experiments.

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7. Preparation of G-Protein Coated Beads (Ga
bg Beads) 7.1. Materials FLAG tagged subunits (Gb1g2 or Gb4 g 2), Gai2, Gai3, etc, (N.B. the variety of subunits isotypes is only limited by availability), G buffer. We have typically used streptavidin-coated beads (Spherotech), where the typical stock concentration is 40,000 beads/ml (Buranda et al., 2001). The concentration of beads (beads/ml) is determined by counting on a hemocytometer or a flow cytometer. To use a flow cytometer, the rate at which sample is consumed (i.e., flow rate) must be defined. The typical flow rate on our BD flow cytometers is set at 1 ml/sec on ‘‘high-flow’’ setting. Therefore one needs to simply run a sample for a desired time while the cytometers’ ‘‘event count’’ readout function in CellQuest software is turned on. At present, biotin functionalized antiFLAG M2 antibodies (bioM2) purchased from Sigma need to be purified of up to millimolar levels of biotin impurities, by several washes in YM-30 Microcon centrifugal filter devices (Millipore Corp. Bedford, MA) (Buranda et al., 2001). Sample purity can be checked by assaying for biotin in successive filtrate solutions with a simple biotin assay (Wu et al., 2005a). The assay is based on the kinetic analysis of the enhancement of fluorescence of streptavidin/fluorescein biotin complexes in the presence of biotin. The kinetic response of fluorescence enhancement is proportional to the concentration of biotin.

7.2. Preparation of M2 beads We have previously used titration binding curves to show that Spherotech beads are surface-saturated with 4 to 4.5 million bioM2 molecules (Buranda et al., 2001; Wu et al., 2007b). The number of bioM2 antibodies/bead can be assessed by use of a fluorescently labeled FLAG peptide (Kd  8.0 nM ) in a centrifugation assay (Buranda et al., 2001). A centrifugation assay involves the determination of absolute numbers of bead-associated ligands from the analysis of fluorescence of residual supernatant solutions after the removal of beads by centrifugation. Paired samples (ligand binding samples and samples blocked with excess biotin) of beads are allowed to equilibrate before centrifugation. The difference in the fluorescence intensity of residual supernatant solutions of binding samples and blocked samples is used to determine the quantity of bound samples. The solution measurements are, in turn, correlated to a parallel analysis of bead-associated fluorescence by flow cytometry (Buranda et al., 1999). For routine preparations of M2 beads, a simple 50% stoichiometric excess of bioM2 is sufficient to saturate the bead sites because of the very tight multivalent binding of streptavidin and the 3 biotins/bioM2.

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The M2 beads are washed twice and resuspended in PBS buffer and stored in 25-ml aliquots (40,000 beads/ml) at 4  C until needed.

7.3. Preparation of G (abg) on M2 beads A typical preparation of G-protein–coated beads involves the incubation of an equimolar amount of M2 beads (e.g., a 25-ml aliquot of M2 beads contains 13 pmol FLAG binding sites) and FLAG tagged subunits (b1g2 or b4g2) in 25 ml of G buffer for an hour at 4  C under mild vortex. The beads can then be stored long term at 80  C. Because these experiments allow for the use of various isotypes of Gaij ( j ¼ 1,2,3) subunits, target aij-subunits can be added as needed. It is always useful to determine the surface density of the bg-subunits on each bead to keep track of stability of the beads and for the standardization of measurements over a period of several months. Surface coverage of bg-subunits can be quantitatively determined on the basis of a standard calibration protocol that relies on the fluorescently labeled FLAG peptide described previously (Buranda et al., 2001). Our standard calibration protocols (Wu et al., 2007b) for measuring the number of M2 antibody sites on (Spherotech) 6 mm streptavidin-coated beads has typically yielded 8 to 9 million fluorescent FLAG peptides per bead (Buranda et al., 2001; Simons et al., 2003a) covered by 4 to 4.5 million bivalent anti-FLAG antibodies under surface-saturating conditions. The site density of subunits is then derived from analyzing the difference in the fluorescence intensity of neat anti-FLAG beads (i.e., beads with known maximal surface density of fluorescent FLAG peptide sites) relative to those beads that are partially covered with FLAG tagged bg-subunits with the fluorescent FLAG peptide. In our experience, the functional activity of M2 antibodies drops over time; therefore, over the course of more than 6 months, we have noticed a drop in the surface density of fluorescent FLAG peptide and bg-subunits of 25% (Wu et al., 2007a). The drop in activity of M2 antibodies does not affect the integrity of the ternary complex assembly because it serves as a simple tether of the bg-subunits to the beads. The change in surface coverage only affects the initial amplitude of the signal associated with the ternary complexes at disassembly. Under our normal experimental conditions, the surface coverage of Gbg varied from 45 to 70% of the total available 9 million anti-FLAG–binding sites, depending on the concentration of FLAG tagged Gbg-subunits and the age of the M2 antibody stock (Wu et al., 2007a). The assembly of Ga-subunits onto the Gbg beads can be achieved by mixing Ga with an aliquot of beads in 10 ml G buffer at 4  C for 1 h. The ratio of beads and Ga is governed by the Kd  32 nM (Wu et al., 2007a) of this interaction. The mixture is then centrifuged and resuspended in G buffer at 20,000 beads/ml; this is the empirical standard concentration of beads used for rapid mix flow

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measurements. It is not necessary to saturate sites with Ga-subunits as the limiting reagent turns out to be GPCR as detailed below.

7.4. Assembly of LRG (abg) on beads The assembly of ligand and receptor (LR) complexes on Gabg-bearing beads is performed as previously described (Simons et al., 2003a). An aliquot of the detergent-solubilized receptor (1% dodecyl maltoside) is mixed with a saturating concentration of the ligand, (Kd  4 nM ) (Bennett et al., 2001; Simons et al., 2003a, 2004; Sklar et al., 2000) and then mixed with the G-protein–complexed beads. For the rapid mix experiments, a typical experimental run uses a volume of 35 ml. The receptor concentration is the limiting reagent, thus one would like to optimize the volume fraction associated with the receptor. The maximum concentration of receptor ever recovered from membrane solubilization preparations was 300 nM. Because the bead component contributes 1 ml (20,000 beads/ml), and the ligand volume can be similarly minimized with a sufficiently high concentration, it is possible to minimize the dilution of the receptor during molecular assembly, steps which are typically done in a minimal volume of 10 ml before increasing the volume to the minimal 35 to 40 ml required for measurement with the rapid mix flow cytometer. As previously noted, the ability of the flow cytometer to discriminate between free and bound fluorophores is limited above 200 nM. It is, therefore, advisable to maintain the concentration of the fluorophore that is in stoichiometric excess (i.e., the fluorescent ligand) below 200 nM. The advantage of using a high-affinity ligand (e.g., Kd of fMLFK-FITC is 4 nM ) (Bennett et al., 2001; Simons et al., 2003a, 2004; Sklar et al., 2000) is realized here. The quantitation of the ternary LRG complexes on beads is carried out with standard calibration beads on the basis of fluorescence readings of fMLFK-FITC or EGFP (vide supra). Although relatively high concentrations of FPR are used, 150 nM, the typical surface coverage (Wu et al., 2005b) on a bead is notably low and depends on the isotypes of the components subunits of a heterotrimer. For example, LRG complexes derived from fMLFK-FITC, wild-type FPR, and Gai3b1g2 yielded 20,000 to 30,000 LRG site occupancies (or 0.7% of 4  106 Gabg sites) on beads compared with <10,000 site occupancies when Gai2 was exchanged for Gai3 in the heterotrimer Gai2b1g2 under similar experimental conditions. The low level of total binding may be related to a potentially weak affinity interaction between R and G, with Kd  1 mM (Bennett et al., 2001). Another contributing factor may be that detergent-solubilized receptors originate from cells that are transfected to overexpress the receptor of choice. The unpurified solubilized extracts contain other proteins including endogenous G-proteins that can be present in much higher concentrations than even the overexpressed target receptor. In normal cells, the expression of G-proteins can be as much as 10 to 100 times higher than

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L

A R Bead

3

a

g b

1

2

B ai3

g

Bead

b

1

C L a

g

Bead

b

R

3

1

D

2 L

Bead

a

g b

R

GFP

1

Figure 11.2 Schematics of modular molecular assemblies of ternary complexes on beads. Numbered arrows refer to junction points that are likely to break when complexes are activated by guanine nucleotides. A socket and plug connecter is used to depict the very high-affinity interaction of the epitope tag and bg-subunits of the G-protein (circles labeled with b and g) that are fused with a FLAG epitope tag, which recognizes the biotinylated M2 anti-FLAG antibodies on streptavidin-coated beads. The modular setup of G-protein heterotrimers allows for ai-subunits for capturing receptors (R). Fluorescent components such as GFP or ligand are indicated in green. See text for details.

receptors (Ransnas and Insel, 1988). Therefore, it is possible that the beadborne Gai subunits (30 nM ) are in competition for receptor sites with endogenous Ga-subunits (potentially >>100 nM ) that are cosolubilized with the receptor. A mitigating factor in this assay is that the local concentration of the bead-borne G-proteins is very high relative to the soluble endogenous competitors, thus yielding a practically useful quantity of LRG complexes on beads. Schematics of modularly assembled LRG complexes on beads are summarized in Fig. 11.2 and discussed in the section below.

8. Analysis of Modular Dissassembly of LRG Modules Because LRG complexes can be assembled in modular fashion, it is possible to assess the kinetic and thermodynamic parameters of their interaction at each junction point (Buranda et al., 2007). Disassembly of LRG

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complexes can be analyzed under circumstances driven by guanine nucleotide activation. Junction points are identified in the schematics displayed in Fig. 11.2. The ternary complex of wild-type FPR is shown in Fig. 11.2A. Guanine nucleotide–mediated disassembly of the ternary complex occurs at three junction points as shown by arrows: (1) b
a, (2) a
R, and (3) R
L. The Gbg heterodimeric subunit is virtually nondissociable under physiologic conditions (Oldham and Hamm, 2007). The junction points are distinguishable by kinetics. To identify the kinetics of each break point we examined the reactivity of isolated component modules of the ternary complex and fusion constructs of FPR-Gai2 (Fig. 11.2C) and FPR-GFP (Fig. 11.2D) as described in the following. Spectrofluorometric and rapid mix flow cytometry can be used to analyze the kinetics of component L, R, and G dissociation from the ternary complexes in solution and beads. To isolate the specific joint associated with a particular kinetic measurement, it is useful to first consider components of the ligand-receptor module separately from the components of the heterotrimeric G-protein unit. With the exception of constitutively active systems, R and G generally remain as separate entities in the absence of ligand. Eqs. (11.3 to 11.7) represent the dissociating modules under consideration. Final results are summarized in Table 11.1.

8.1. Real-time spectrofluorometric measurement of the dissociation of L from R KD




L F þ R Ð LF R ! LF þ R kdiss

ð11:3Þ

The interactions between GPCRs and ligands (agonists or partial agonists) have been quantitatively evaluated (Simons et al., 2003a, 2004) and some Kd values have been tabulated in a review chapter (Buranda et al., 2007). We briefly focus on the measurement of ligand dissociation with a fluorometric anti-FITC antibody assay (Sklar et al., 1981), which has been described in more recent publications (Buranda et al., 1999; Key et al., 2001; Simons et al., 2003a). The polyclonal antibody to fluorescein that is used in our laboratory is not commercially available. However, alternative antifluorescein antibodies such as clone4-4-20, A-6421 (Invitrogen.probes. com), or clone FIT-22 (Biolegend.com) can be purchased. We are not aware of previous characterizations of these antibodies, thus the reader would need to perform dilution series experiments to optimize. To measure kdiss in Eq. (11.3), it is necessary to remove endogenous G-protein from solubilized receptors (Bennett et al., 2001). G-proteins can

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Table 11.1 Summary of experimental results of LRG dissociation kinetics measured by small-volume rapid-mix flow cytometry Ga

bg

t, fast (sec)

b1g2

18.3 (GTPgS) 33.8 (GDP) 12.4 (GTPgS) 0.8 0.2 (GTPgS) 1.5 0.4 (GDP) 0.7 0.1(GTPgS) 0.8 0.1 (GTPgS) 1.1 (GDP) 0.6 0.05 (GTPgS) 3.1 0.2 (GTPgS) 5.8 (GDP) 2.4 0.2 (GTPgS) 5.2 0.6 (GDP)

Ligand

Receptor

1a

LF

R-Gai2

2a 3b

LF LF

R-Gai2 R

Gai2

b4g2 b1g2

4b 5b

LF L

R RF

Gai2 Gai2

b4g2 b1g2

6b 7b

L LF

RF R

Gai2 Gai3

b4g2 b1g2

8b

L

RF

Gai3

b1g2

Junctionc


L
RG LR
G LR
G LR
G LR
G LR
G LR
G L RG

Reproduced from (Wu et al., 2007a) with permission. a Kinetic data analyzed with a single-phase exponential model. b Kinetic data analyzed with a two-phase exponential model. The data only show the results of the analysis of the fast component. The slower component was typically two orders of magnitude or more than the fast component (cf. Figure 11.3 in Wu et al. [2007a]). We have attributed the slow component to receptor misfolding (see text for details). Dissociation produced by GTPgS was always faster and to a greater extent than GDP. c Experimentally measured point of dissociation in the ternary complex.

be removed from solubilized receptors by incubating anti-Gi1,2,3 antibody (Calbiochem or Sigma) for 45 min on ice. The immunocomplex of antibody-substrate is removed by incubating with a slurry of protein A-agarose for 30 min. The sample is centrifuged at 14,000g for 30 sec, and the supernatant is removed. The stoichiometric ratio of anti-Gi1,2,3 antibody, or protein A beads to solubilized receptors is determined by sample size, and typically follows recommended guidelines on product data sheets of the commercial reagents. In a cylindrical cuvette, a fluorescein-labeled ligand (e.g., 10 nM ) to the formyl peptide receptor, fMLFK-FITC (LF) is mixed with a 10-fold stoichiometric excess of detergent-solubilized receptor cleared of endogenous G-proteins (vide supra). At the spectrofluorometer, a baseline reading of the intensity of receptor-bound ligand is taken before a 2-ml aliquot of the antifluorescein antibody is added in situ via a Hamilton syringe through a sample port in thousand fold stoichiometric excess to LFR complexes and free LF in the cuvette. Diffusive encounter between antifluorescein antibodies and LFR or LF selectively quenches 95% of the emission intensity of free LF but not RLF complexes, where the receptor’s steric bulk effectively blocks contact between the fluorescein tag on the short peptide and

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the antibody (Sklar et al., 1990). Because the antibody can quench dissociating LF, the rate at which LF is quenched represents a direct measure of its dissociation from R: t1/2  20 sec for fMLFK-FITC.

8.2. Real-time spectrofluorometric measurement of the dissociation of L from RG KD




L F R þ G Ð L F RG ! RG þ L F kdiss

ð11:4Þ

To measure the dissociation of LF from FPR in the presence of G-proteins, exogenous G-proteins (e.g., purified Gai3-subunits) are combined with bg in an equimolar ratio (10 mM ) and mixed with solubilized FPR protein (Bennett et al., 2001) and with 10 nM fMLFK-FITC in a volume of 12 ml and incubated for 2 h at 4  C. Before analysis, samples are diluted to 200 ml and equilibrated to room temperature for 2 min. At the spectrofluorometer, anti-FITC-Ab is added to quench the LF as it dissociates from LRG. The dissociation rate of LF from G-protein–coupled R is typically slower than dissociation from uncoupled R: t1/2  100 sec. The decoupling of R and G by in situ addition of 0.1 mM GTPgS yields a rate similar to LR complex in Eq. (11.3) (Bennett et al., 2001).

8.3. Rapid mix measurement of guanine nucleotide–induced disassembly of ternary complexes The basic operation of a rapid mix flow cytometer has been outlined previously, instrumental details, interface with a standard Beckton Dickinson flow cytometer, setup of automation routine, and calibration beads for mixing, have been described elsewhere (Wu et al., 2005b). A typical run consumes a minimum volume of 35 ml. The 1000-ml volume double-barrel syringes of the rapid mix device can, therefore, be loaded with enough sample volume for several sequential runs. For example, for three consecutive runs, 105 ml of LRG beads in DHPSM buffer (600 beads/ml) are loaded into one of the sample syringes of a small-volume rapid mix device (syringe 1 in Fig. 11.1). An equal volume of DHPSM buffer or 0.2 mM guanine nucleotide is loaded into the other sample syringe (syringe 2 in Fig. 11.1). A buffer-only control experiment is used to establish a baseline measurement of the effects of a twofold dilution of the bead suspension. Other controls involve the use of LRG assemblies made in the presence of GTPgS to inhibit the formation of LRG. The experimental run proceeds according to an automated mixing sequence as described elsewhere (Wu et al., 2005b).

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The time course data are then converted to ASCII format with the FCSQuery program (Bruce Edwards, UNM HSC). Data are analyzed and graphed with commercial software such as Prism software (GraphPad Software, San Diego, CA). To determine the dissociation characteristics, the fluorescence in blocked control samples is subtracted point by point from the time-resolved fluorescence of ligand-binding samples (Wu et al., 2005b, 2007a).

8.4. Real-time rapid mix measurement of the dissociation of Ga from Gbg: disassembly of module in Fig. 11.2B KD




bead  gb þ aF Ð bead  gb aF

aF <<½aor AIF 4

! kdiss

bead  gb þ aF ð11:5Þ

In cells, heterotrimeric G-proteins are composed of GDP bound to Ga subunit, and Gbg heterodimeric subunit, which is virtually nondissociable under physiological conditions (Oldham and Hamm, 2007). On beads, Gbg and fluorescently tagged Ga
GDP subunits form a stable heterotrimer, Kd  32 nM (Wu et al., 2007a). Constitutive dissociation of Ga
GDP from Gbg heterodimers is too slow to be considered for rapid mix (t1/2 > 100 min) cytometry measurements (Wu et al., 2007a). Tetraflouroaluminate, AlF4  , which emulates the g-phosphate of GTP in the nucleotide-binding pocket, can be used to activate the G-protein to yield the dissociation of Ga
GDP
AlF4  from the beads (20 sec < t1/2  30 seconds) (Wu et al., 2007a). This time frame of subunit dissociation is one that is not characteristic of early signaling events.

8.5. Rapid mix measurement of the dissociation of R from Gabg: disassembly of modules in Fig. 11.2A,D KD




GTPg S

bead  gba þ RF L Ð bead  gb aRF L ! bead  gb þ aRF L kdiss

ð11:6aÞ KD




GTPg S

bead  gba þ RF L Ð bead  gba RF L ! bead  gba þ RF L kdiss

ð11:6bÞ

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The molecular assembly of the ternary complex shown in Eqs. (11.6) has two putative junction points, one involving b
a junction and another, which involves a
RF junction. Either junction could contribute to the loss of the GFP tagged receptor (RF) from beads. The disassembly rate of a
RF junction can be distinguished from the already known rate of b
a junction if the former process Eq. (11.6a) is significantly faster than the latter Eq. (11.5). When rapid mix flow cytometry measurements are used, the loss of GFP was shown to occur on the subsecond timeframe, depending on the isotypes of Ga and Gbg-subunits used in the molecular assembly (cf. Table 11.1) (Wu et al., 2007a). The magnitude and range of these dissociation processes are much faster than those measured for the dissociation of aF in Eq. (11.5), which by elimination implicates the disruption of the a
RF junction (Eq. 11.6b) as the correct target of the measurement. Similar dissociation kinetics were also measured with the wild-type complexes (Fig. 11.2A).

8.6. Rapid-mix measurement of the dissociation of LF from RGabg: disassembly of module in Fig. 11.2C bead  gb þ a  RL F Ð bead  gb
a  R
L F KD

GTPg S 5xL F

! kdiss

bead  gb
a  R þ L F

ð11:7Þ To corroborate the conclusions from the analysis of Eq. (11.6) we used a Gai2-fused FPR in the molecular assembly of the heterotrimer. Guanine nucleotide activation of the ternary complex yielded a rate constant that was consistent with the dissociation rate of LF measured from an isolated LFR complex (cf. Eq. 11.4). Furthermore, the addition of GTPgS in the presence of excess LF seemed to inhibit the loss of fluorescence, as one would expect facile rebinding of excess ligand LF to mitigate the decrease in affinity of the RLF interaction because of GTPgS-mediated uncoupling of the receptor from the G-protein. Because the measured separation of R-a and bg can be no faster than the dissociation of LF from LFR, the subsecond dissociation of the ternary complex of Eq. (11.6b) must reflect the dissociation of FPR-GFP from Ga. (Wu et al., 2007a). Table 11.1 shows a summary of the kinetics of disassembly from a variety of junction points from data taken from Wu et al. (2007a). The data also show that addition of a large excess (0.1 mM ) of either GTPgS or GDP to the ternary complexes on beads produces essentially the same rapid dissociation of LR from the heterotrimer with notable differences between subunit isotypes that were used.

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9. Summary and Outlook The advantages of modular assemblies on beads to study GPCR ternary complex dynamics in modular systems have been recently explained in a review chapter (Buranda et al., 2007). The assembly of specific isotypes of promiscuous G-protein subunits can be clearly defined and has the potential of explaining the differences in dynamic and equilibrium roles played by different isotypes of a and bg-subunits (Kukkonen et al., 2001; Lindorfer et al., 1998; Mayeenuddin et al., 2006; McIntire et al., 2001, 2002; Simons et al., 2003b). As shown in Table 11.1, the substitution of b1 for b4 in the Gbg dimer has a small but measurable effect (t1/2 ¼ 18.3 sec vs 12.4 sec) on the dissociation rate of LF, after the receptor uncouples from the G-protein (t1/2 < 1sec). This might arise as a consequence of specific subunit isotypes inducing the receptor to achieve conformational states that display a higher affinity for the ligand (Vauquelin and Liefde, 2005). For example, in the molecular assemblies described here, the stability of the LRG complexes improved according to the rank ai1 < ai2 < ai3 (Bennett et al., 2001). In these systems, soluble ternary complex formation of the receptors with G-proteins allows direct quantitative measurements, which can be analyzed in terms of three-dimensional concentrations (molarity). In contrast to the difficulty of analyzing comparable measurements in two-dimensional membrane systems, the output of these flow cytometric experiments can be analyzed by means of ternary complex simulations in which appropriate parameters can be estimated.

ACKNOWLEDGMENTS This work was supported by NIH Grants K25AI060036, NSFCTS0332315 (T. B.); U54MH074425 (L. A. S.); 1P30CA118100, and The New Mexico State Cigarette Tax to the UNM Cancer Center.

REFERENCES Bennett, T. A., Key, T. A., Gurevich, V. V., Neubig, R., Prossnitz, E. R., and Sklar, L. A. (2001). Real-time analysis of G protein-coupled receptor reconstitution in a solubilized system. J. Biol. Chem. 276, 22453–22460. Buranda, T., Jones, G., Nolan, J., Keij, J., Lopez, G. P., and Sklar, L. A. (1999). Ligand receptor dynamics at streptavidin coated particle surfaces: A flow cytometric and spectrofluorometric study. J. Phys. Chem. B. 103, 3399–3410. Buranda, T., Lopez, G. P., Simons, P., Pastuszyn, A., and Sklar, L. A. (2001). Detection of epitope-tagged proteins in flow cytometry: Fluorescence resonance energy transfer-based assays on beads with femtomole resolution. Anal. Biochem. 298, 151–162.

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Buranda, T., Waller, A., Wu, Y., Simons, P. C., Biggs, S., Prossnitz, E. R., and Sklar, L. A. (2007). Some mechanistic insights into GPCR activation from detergent-solubilized ternary complexes on beads. Adv. Protein Chem. 74, 95–135. Dowal, L., Provitera, P., and Scarlata, S. (2006). Stable association between G alpha(q) and phospholipase C beta 1 in living cells. J. Biol. Chem. 281, 23999–24014. Gilbert, T. L., Prossnitz, E. R., and Sklar, L. A. (1999). The uncoupled state of the human formyl peptide receptor. J. Recep. Signal Transd. Res. 19, 327–340. Hamm, H. E. (1998). The many faces of G protein signaling. J. Biol. Chem. 273, 669–672. Hamm, H. E. (2001). How activated receptors couple to G proteins. Proc. Natl. Acad. Sci. USA 98, 4819–4821. Key, T. A., Bennett, T. A., Foutz, T. D., Gurevich, V. V., Sklar, L. A., and Prossnitz, E. R. (2001). Regulation of formyl peptide receptor agonist affinity by reconstitution with arrestins and heterotrimeric G proteins. J. Biol. Chem. 276, 49204–49212. Kukkonen, J. P., Nasman, J., and Akerman, K. E. O. (2001). Modelling of promiscuous receptor-G(i)/G(s)-protein coupling and effector response. Trends Pharmacol. Sci. 22, 616–622. Lindorfer, M. A., Myung, C. S., Savino, Y., Yasuda, H., Khazan, R., and Garrison, J. C. (1998). Differential activity of the G protein beta(5)gamma(2) subunit at receptors and effectors. J. Biol. Chem. 18, 34429–34436. Lohse, M. J., Bunemann, M., Hoffmann, C., Vilardaga, J. P., and Nikolaev, V. O. (2007a). Monitoring receptor signaling by intramolecular FRET. Curr. Opin. Pharmacol. 7, 547–553. Lohse, M. J., Hoffmann, C., Nikolaev, V. O., Vilardaga, J. P., and Bunemann, M. (2007b). Kinetic analysis of G protein-coupled receptor signaling using fluorescence resonance energy transfer in living cells. Adv. Protein Chem. 74, 167–188. Mayeenuddin, L. H., McIntire, W. E., and Garrison, J. C. (2006). Differential sensitivity of P-Rex1 to isoforms of G protein beta gamma dimers. J. Biol. Chem. 281, 1913–1920. McIntire, W. E., MacCleery, G., and Garrison, J. C. (2001). The G protein beta subunit is a determinant in the coupling of G(s) to the beta(1)-adrenergic and A2a adenosine receptors. J. Biol. Chem. 276, 15801–15809. McIntire, W. E., Myung, C. S., MacCleery, G., Wang, Q., and Garrison, J. C. (2002). Reconstitution of G protein-coupled receptors with recombinant G protein alpha and beta gamma subunits. G Protein Pathways, Pt A, Receptors 343, 372–393. Nolan, J. P., Lauer, S., Prossnitz, E. R., and Sklar, L. A. (1999). Flow cytometry: A versatile tool for all phases of drug discovery. Drug Disc. Today 4, 173–180. Oldham, W. M., and Hamm, H. E. (2007). How do receptors activate G proteins? Adv. Protein Chem. 74, 67–93. Oldham, W. M., and Hamm, H. E. (2008). Heterotrimeric G protein activation by G-protein-coupled receptors. Nat. Rev. 9, 60–71. Ottino, J. M. (1990). Mixing, chaotic advection and turbulence. Ann. Rev. Fluid Mech. 22, 207–253. Peltier, W. R., and Caulfield, C. P. (2003). Mixing efficiency in stratified shear flows. Ann. Rev. Fluid Mech. 35, 135–167. Piyasena, M. E., Buranda, T., Wu, Y., Huang, J., Sklar, L. A., and Lopez, G. P. (2004). Near-simultaneous and real-time detection of multiple analytes in affinity microcolumns. Anal. Chem. 76, 6266–6273. Ransnas, L. A., and Insel, P. A. (1988). Quantitation of the guanine nucleotide binding regulatory protein Gs in S49 cell membranes using antipeptide antibodies to alpha s. J. Biol. Chem. 263, 9482–9485. Robishaw, J. D., and Berlot, C. H. (2004). Translating G protein subunit diversity into functional specificity. Curr. Opin. Cell Biol. 16, 206–209. Seamer, L. C., Kuckuck, F., and Sklar, L. A. (1999). Sheath control to permit stable flow in rapid mix flow cytometry. Cytometry 35, 75–79.

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C H A P T E R

T W E LV E

The Use of Receptor Homology Modeling to Facilitate the Design of Selective Chemokine Receptor Antagonists Percy H. Carter and Andrew J. Tebben Contents 1. Introduction 2. Receptor Expansion of Rhodopsin Models as an Initial Approach 2.1. Protocol development 2.2. Application of the balloon expansion approach to model CCR2 antagonists 3. The Use of b2-Adrenergic Receptor Structure as an Alternative Template 3.1. Comparison of our b2- and rhodopsin-derived models of CCR2 antagonist docking 3.2. Application of the b2 template to develop a new model of CCR1: Comparison to rhodopsin and MembStruk models 3.3. Application of the b2 template to develop a new model of CCR5 4. Conclusions References

250 260 260 265 267 267 269 272 274 276

Abstract Chemokine receptor antagonists have potential applications in fields as diverse as oncology, immunology, cardiovascular diseases, and virology. Although the chemokine receptors are G-protein–coupled receptors, their cognate ligands are small proteins (8 to 12 kDa), and so inhibiting the ligand/receptor interaction has been challenging. In this chapter, we review the use of receptor mutagenesis to probe the allosteric nature of chemokine receptor binding by small molecule antagonists. We then demonstrate how two different homology modeling templates—a balloon-expanded form of rhodopsin and a modified form of b2-adrenergic receptor—can be used to rationalize the mutagenesis data. With these templates, new models are presented for several antagonist/

Research & Development, Bristol-Myers Squibb Company, Princeton, New Jersey, USA Methods in Enzymology, Volume 461 ISSN 0076-6879, DOI: 10.1016/S0076-6879(09)05412-3

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2009 Elsevier Inc. All rights reserved.

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Percy H. Carter and Andrew J. Tebben

receptor interactions previously studied in the literature, including those for CCR1, CCR2, and CCR5. We discuss the strengths of both approaches and offer ideas for how the templates themselves can be used in the absence of mutagenesis data to rationalize structure-activity relationships.

1. Introduction The chemokine receptor family includes
20 G-protein–coupled receptors that play a central role in leukocyte migration and activation (Sallusto and Baggiolini, 2008). Specific family members are also involved in viral entry and angiogenesis. Given this diverse range of important functions, they have been targeted as potential points of pharmaceutical intervention for blunting diseases as diverse as asthma, rheumatoid arthritis, multiple sclerosis, solid organ transplantation, atherosclerosis, cancer, and HIV infection (Viola and Luster, 2008). In all instances, the promise of chemokine receptor antagonism has been one of selective therapy targeted at a critical portion of the disease process. In this chapter, we discuss the design of chemokine receptor antagonists, focusing on a structural approach guided by molecular modeling and receptor mutagenesis. Chemokines are relatively small proteins (8 to 12 kDa) that vary widely in sequence but exhibit similar tertiary structures (Allen et al., 2007). The typical chemokine structure consists of a disordered N-terminus (6 to 10 amino acids), the signature cysteine motif (C, CC, CXC, or CX3C), a loop region, a three-stranded beta-sheet, and a C-terminal alpha helix. Two disulfide bonds typically stabilize this tertiary structure. Notably, despite differences in primary sequence of both the chemokines and their receptors, a substantial amount of promiscuity in ligand binding has been observed in vitro, although the degree varies with the receptor and ligand: for example, CCR3 binds 10 different chemokines, and several of these ligands also bind additional chemokine receptors; in contrast, CXCR5 binds only CXCL13, and this ligand does not bind any additional receptors (Allen et al., 2007). Given the conserved tertiary structure of the chemokine ligands, a general interaction model has been postulated for the family (leading references: Blanpain et al., 2003; Carter, 2002; Datta-Mannan and Stone, 2004). This ‘‘two-site’’ interaction hypothesis posits that (1) the chemokine ‘‘globular core’’ binds to the extracellular N-terminal domain and extracellular loops of the receptor, and (2) key residues in the first portion of the N-loop and the chemokine N-terminus activate the receptor by interaction with the receptor transmembrane bundle and extracellular loop region (Fig. 12.1A). Although exceptions do exist for specific ligand/receptor pairs (Petit, 2008), most of the interactions studied have followed this general paradigm.

Selective Chemokine Receptor Antagonists

251

Figure 12.1 (A) Conceptual model of chemokine and small molecule antagonist binding to a chemokine receptor.The receptor is colored as a gradient from the N-terminus (blue) to C-terminus (red).The chemokine is grey, and the small molecule antagonist is shown in blue sticks. (B) Rhodopsin/retinal crystal structure (1F88) oriented and colored as in panel A. (C) b2/carazolol crystal structure (2RH1).The T4 insertion between TM5 andTM6 has been deleted for clarity.

The general ligand/receptor interaction model just cited is consistent with the ligand promiscuity in the family: different residues in a given ligand can be used for binding to each of its different receptors, and different residues in a receptor can be used for binding to each of its different ligands (Blanpain et al., 2003; Duchesnes et al., 2006; Pakianathan et al., 1997). Thus, the binding topology of two chemokine ligands for a given receptor is generally orthosteric—even though they do not necessarily compete for the same residues of CCR5, they bind to the same receptor region. A central question in the chemokine field has been whether a small molecule antagonist needs to bind orthosterically to the native ligand to be effective, or whether it can antagonize the ligand by means of allosteric binding to the transmembrane region (Allegretti et al., 2008; Carter, 2002). As summarized in Table 12.1 (see also the accompanying Fig. 12.2), both receptor pharmacology and mutagenesis studies have now suggested that a variety of structurally diverse small molecule antagonists bind to specific chemokine receptors with an allosteric mechanism. When receptor mutagenesis has been used, it has suggested a small molecule ligand binding site within the transmembrane region,1 capped by extracellular loop 2, and frequently 1

For the sake of accuracy, it is important to note that this binding site is allosteric to that used by the chemokines for ligand binding, but partially overlapping with that used by the chemokines for ligand activation. However, many of the studies shown in Table I illustrate that mutations that affect antagonist binding do not affect chemokine binding or function. Accordingly, it is not unreasonable to refer to this small molecule binding pocket as allosteric.

252

Table 12.1 Published reports of allosteric binding by chemokine receptor antagonists

Receptor

Cmpd

Pharmacology

Mutagenesis and modeling details

CCR1

UCB 35625 (1)

Insurmountable antagonist of MIP-1a function. Does not block binding.

CCR1

BX-471 (2)

Antagonist.

CCR1

Cu2þ and Zn2þ -chelated bipyridine and phenanthroline

These metal-based agonists enhanced binding of MIP-1a, but reduced the binding of RANTES.

Putative intact residues in TM1 (Y41), 3 (Y113), and 7 (E287) identified from a panel of 33. These three mutants do not affect MIP-1a binding or function. rhodopsin homology model. Putative contact residues in TM3 (Y113, Y114), and TM6 (I259) identified from a panel of 10. These three mutants do not affect MIP-1a binding or function. Membstruck de novo model. Putative contacts identified in TM3 (S110) and 7 (E287) and excluded in the extracellular domain (the binding domain for chemokines). These TM contacts overlap with the TM contacts for RANTES, but not MIP-1a. Highlights different topologies of RANTES and MIP-1a binding.

Key leading reference

de Mendonca et al. (2005)

Vaidehi et al. (2006)

Jensen et al. (2008)

CCR2

RS-136270 (3) and RS504393 (4)

Antagonists

CCR2

Compounds 4 and 5, SB-282241 (6), and TAK-779 (7)

CCR2 Antagonists. Note that TAK-779 (7) also exhibits substantial antagonist activity at CCR5 (see below).

CCR2

Compounds 8 and 9

Antagonists of chemokine binding and function.

CCR2

JNJ-27141491 (10) UCB35625 (1)

Insurmountable antagonism shown. Surmountable antagonist of eotaxin function. Does not block binding.

CCR3

First to characterize the E291 (TM7) mutation in CCR2. This mutation did not affect the neutral pyrrole 3 but had a large effect on spiropiperidine 4. Early homology model. Mutagenesis on 4 antagonists identified contacts in TM7 (E291, T292) and TM3 (Y120, H121); subtle differences were noted among the antagonists. These mutants did not have substantial effects on MCP-1. An early homology model was refined on the basis of the rhodopsin X-ray structure. Mutagenesis showed that the effect of Glu291 (TM7) mutation on antagonist binding was greater for the pyridyl series (8) than the cyclohexyl series (9). No modeling presented. No study reported. The analogous residues from the CCR1 study were also identified as contacts in CCR3.

Mirzadegan et al. (2000)

Berkhout et al. (2003)

Cherney et al. (2008)

Buntinx et al. (2008) Wise et al. (2007)

253

(continued)

Table 12.1 (continued) 254 Receptor

Cmpd

Pharmacology

Mutagenesis and modeling details

CCR4

Compounds 11 and 12

Antagonists of chemokine binding and function.

CCR5

TAK-779 (7), Aplaviroc (13), Maraviroc (14), Sch-C (15), vicriviroc (16)

Noncompetitive antagonism of MIP-1a and RANTES demonstrated. Differential effects on RANTES among compounds, w/13 unique in blocking function but not binding. Long off-rates shown for 13, 14.

Compound 11 bound to both CCR4 and a CCR5/4t chimera that had the CCR4 intracellular tail. 11 did not bind to a CCR4/5t chimera with a CCR5 tail. Compound 12 displaced chemokine from CCR4 but did not displace 11. 12 bound to CCR4 and CCR4/5t, but not CCR5/4t. Each inhibitor seems to use slightly different TM contact residues, but the compounds generally bind in the same pocket (in addition, they compete with each other in pharmacologic assays). Residues of importance in the binding pocket include: W86 (TM2), Y108 (TM3), F109 (TM3), I198 (TM5), Y251 (TM6), and E283 (TM7). Mutation of these individual residues has differential effects on each of the compounds and on RANTES. Rhodopsin homology model.

Key leading reference

Andrews et al. (2008)

Fano et al. (2006) Watson et al. (2005), Kondru et al. (2008), Seibert et al. (2006)

CCR5

Aplaviroc (13), Sch-C, TAK779

See above.

CCR5

Compound 17

Antagonist.

CCR8

LMD-009 (18)

This small molecule agonist was able to activate CCR8 fully, but also displace the native chemokine CCL1.

CXCR1 Repertaxin (19)

Antagonizes a subset of IL-8 functions, but does not block IL-8 binding.

255

Mutagenesis suggests that Aplaviroc makes much more extensive contacts with extracellular loop 2 than does Sch-C or TAK779. Rhodopsin homology model. Limited mutagenesis identified putative contacts in TM2 (W86), TM3 (Y108), TM6 (Y251), and TM7 (E 283). Differences w/TAK-779 discussed. Rhodopsin homology model. Mutagenesis shows key contacts for this agonist are not dissimilar to known contacts for antagonists in other chemokine receptors (e.g., TM7 E286; TM3 Y113). Some of the TM contacts (TM3 Y113) are also used by CCL1. Rhodopsin homology model. Mutagenesis study identified putative contacts in TM1 (Y46), TM2 (K99), and TM3 (V113). IL-8 was not affected by these mutations. A rhodopsin homology model was used.

Maeda et al (2006; 2008)

Castonguay (2003)

Jensen et al. (2007)

Bertini et al. (2004)

(continued)

256

Table 12.1 (continued) Receptor

Cmpd

CXCR2 Sch527123 (20) CXCR4 AMD3100 (21)

Pharmacology

Mutagenesis and modeling details

Insurmountable antagonism shown. Antagonist

No study reported.

CXCR4 AMD3100 (21) and AMD3465 (22)

Antagonizes SDF-1 binding and function.

CXCR4 21, 22, and novel AMD11070 (23)

Antagonist

Note: Please see Fig. 12.2 for chemical structures of compounds described in table.

Key paper that confirmed that AMD3100 bound to the transmembrane and not the exocyclic, receptor domain of CXCR4. Aspartic acids in TM4 (D171) and TM6 (D262) were implicated. Confirmed AMD3100 TM contacts and identified novel contacts for monoclam AMD3465 (e.g., H281, TM7). Strength of other interactions (E288, TM7; D262, TM6; A175, ECL2) enhanced. Confirmed AMD3100 and 3465 contacts, and identified unique contacts for the orally bioavailable non-cyclam AMD11070 (D262, TM6; D97, TM2). Rhodopsin homology model used.

Key leading reference

Gonsiorek (2007) Gerlach (2001)

Rosenkilde et al. (2007)

Wong et al. (2008)

Cl

NH2

H N

I

O

O

O O

N Et

Cl O

NH

Cl

UCB-35625 (1)

Ph

N

F

N

N

CO2H RS-136270 (3)

N

Cl

O

Me

N O

RS-504393 (4)

BX-471 (2)

NH O

N HN

CF3 O

N

H N

N H

O

SB-282241 (6)

R NH

N H

F O

R' F

8 X = NH, R = SMe, R⬘ = NH2 9 X = CH2, R = Cl, R⬘ = H

TAK-779 (7) Cl

Cl

Cl H

O H N

O

O N

CF3 O

H N 4-MePh

N H

Compound 5

X

O

HO

N

O O N

N H JNJ-27141491 (10) S

Cl

N

Cl

N

Figure 12.2 (Continued)

H N

S O2 OMe

S

Compound 11

N

Cl

Cl

N N

N

N N

Compound 12

O

N H

257

O O

n-Bu

HO2C

O N

N N N

F

H OH

F

H N

N

N O

H

O

N Br

N

N O

N Maraviroc (14)

Sch-C (15)

N

Aplaviroc (13) O

p-NO2Ph N CF3

N

N O

N

Me

N

Vicriviroc (16)

O

N

N Me Ph S O2

Me Me

O

OH

N H

Sch527123 (20)

N

NH HN

OMe

H N

NH HN

NH HN AMD3100 (21)

O2 S

O

O N H Repertaxin (19)

NH2 NH N

N HN

O

N

LMD-009 (18)

Compound 17

O N H

O

O

Ph

NH N N

H N

O

OEt

AMD3465 (22)

N

N N H

N N

H

AMD11070 (23)

Figure 12.2 The chemical structures of allosteric chemokine receptor antagonists are illustrated. See Table 12.1 for data supporting the proposed allosteric mechanism.

Selective Chemokine Receptor Antagonists

259

possessing a critical contact with a conserved glutamic acid residue located in TM7 (Rosenkilde and Schwartz, 2006). Receptor homology modeling has extended these experimental observations to suggest that the antagonists typically bind in an extended pocket bounded by TM2, TM3, TM5, TM6, and TM7. This ‘‘classical’’ pocket overlaps with the binding site observed in the crystal structures of retinal in bovine rhodopsin (Palczewski et al., 2000) and carazolol in the b2-adrenergic receptor (Cherezov et al., 2007) (Fig. 12.1B and 1C). An additional allosteric site has been identified deeper inside the receptor bundle, bounded on one side by the intracellular C-terminal receptor domain (Andrews et al., 2008; Grahames et al., 2006). Notably, both the ‘‘classical’’ pocket and ‘‘deeper’’ pocket have been identified in CC and CXC family members. With this broad base of experimental evidence in hand, it is worthwhile to contemplate the implications of allosteric antagonism. From the perspective of efficacy, an allosteric system raises the possibility of function-selective antagonism. The prospects for such selectivity are increased when one considers that the chemokines themselves are known to use different contacts in the transmembrane domain and extracellular loop regions to mediate their different functions—thus, the receptor contacts (and, by extension, conformations) required to modulate chemotaxis can be different from those required to modulate Ca2þ influx (Gavrilin et al., 2005). Because small molecule antagonists bind in the same region as the ‘‘activating domain’’ of the chemokines,1 it is not surprising that there have been reports of small molecule antagonists exhibiting highly dissociated effects on different functions (Bertini et al., 2004; De Lucca et al., 2005). Allosteric modulation also introduces the prospects for ligand-selective antagonism. In the context of CCR5, it might be desirable to modulate specifically the binding of gp120 without affecting the binding of the native chemokine ligands, because this might allow for blockade of viral entry without engendering immunosuppression. Although this has not been demonstrated, it has been shown that the various antagonists for this receptor use subtly different receptor contacts and exhibit different pharmacology toward the different ligands (Maeda et al., 2008; Watson et al., 2005). Unfortunately, however, this system has the additional complication that the gp120 expressed by HIV can change in response to selective pressure, and a recent study has documented that HIV strains resistant to the actions of antagonist maraviroc (14) can bind to maraviroc-bound CCR5, showing that the allosteric antagonism can be circumnavigated by the virus (Westby et al., 2007). Notably, these maraviroc-resistant mutants are still susceptible to the actions of other CCR5 antagonists, consistent with the aforementioned observation that many of these compounds bind to the transmembrane bundle with slightly different binding modes. The ability of small molecule antagonists to disrupt the protein-protein interaction between a chemokine and its receptor by means of allosteric

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modulation has an additional key benefit: it opens the possibility of rational ligand design on the basis of structural considerations. Unfortunately, a peerreviewed description of an X-ray crystal structure of a chemokine receptor has not yet appeared. However, because the transmembrane domain of the chemokine receptors is structurally related to the transmembrane regions of receptors that have been crystallized—rhodopsin (Palczewski et al., 2000), b2-adrenergic receptor (Cherezov et al., 2007), b1-adrenergic receptor (Warne et al., 2008), and the adenosine receptor ( Jaakola et al., 2008)—it is possible to use a receptor homology modeling approach. This approach would not be feasible for an orthosteric chemokine receptor antagonist, because such a compound would bind to the highly charged extracellular N-terminal domain of the chemokine receptor, for which no analogous crystal structure exists. In this chapter, we describe methods for coupling homology modeling with receptor mutagenesis to rationalize the binding of known chemokine receptor antagonists and offer our thoughts on the use of homology modeling and structure/activity relationships to design new chemokine receptor antagonists.

2. Receptor Expansion of Rhodopsin Models as an Initial Approach 2.1. Protocol development A key issue facing GPCR homology modeling is the paucity of relevant template structures, substantially limiting our understanding of receptor conformation and ligand placement. Although bovine rhodopsin (Palczewski et al., 2000) and, more recently, the b2-adenergic (Cherezov et al., 2007) structures have proven to be relevant templates for a number of GPCRs (Fanelli and Benedetti, 2005), they represent two frozen snapshots of a very dynamic family of proteins that bind ligands whose size, shape, and interactions can be quite different from the cocrystallized ligands. Because the ligandbinding site in the initial models is often too small, it can be difficult to place the ligand into the receptor model without modifying its conformation. In doing so, the modeler can introduce bias by placing the ligand in a particular pose and then forcing the receptor to adapt to the presence of the ligand. Although modeling within the chemokine family of receptors faces these same challenges, multiple studies have been reported (Table 12.1) that attempt to rationalize mutagenesis and small molecule structure-activity data in a structural context. To minimize the issue of bias, a chemokine receptor modeling protocol was designed that provides ligand-binding poses to be critically evaluated in the context of the available experimental data (Fig. 12.3). Initially, the starting point for this process was a model based on the bovine rhodopsin

261

Selective Chemokine Receptor Antagonists

Rhodopsin based modeling

b2-adrenergic based modeling

Initial homology model

Initial homology model

Balloon binding site expansion

EC2 loop sampling

Induced fit ligand docking

Evaluation of models against mutagenesis and SAR data

Molecular dynamics refinement

Final model

Figure 12.3 Process for chemokine receptor modeling starting with the rhodopsin and b2 -adrenergic template structures.

crystal structure (Palczewski et al., 2000). Although rhodopsin shares less than 20% sequence homology with the chemokine family, alignment is possible because of the presence of conserved residues within the class A family of GPCRs, coupled with the secondary structure observed in the crystal structure (Fig. 12.4). Within the helical regions, the alignment is anchored to these residues and then extended to the N- and C-termini of the helix with the assumption that insertions and/or deletions are disallowed. The alignment within the loop regions is less well defined because of the lack of conservation, with the exception of EC2. The disulfide link between EC2 and the top of TM3 is conserved within the class A family of GPCRs, fixing this point with the remainder of the loop alignment adjusted around it. Because EC2 forms the top of the ligand-binding site, it is important to align and model this loop correctly. The somewhat arbitrary alignment of the other loops leads to substantially less confidence in those regions, but has less impact, because these seem to have fewer contacts with the small molecule chemokine antagonists. On inspection of the rhodopsin-derived models, it was quickly discovered that the ligand-binding site was largely occluded by aromatic residues not present in rhodopsin. In addition, the C-terminal strand of EC2 was

1.50 2.50 1F88 MNGTEGPNFYVPFSNKTGVVRSPFEAPQYYLAEPWQFSMLAAYMFLlIMLGFPINFLTLYVTVQHKKLRTPLNYILLNLAVADLFMVFGGFTTTL 2RH1 DEVWVVGMGIVMSLIVLAIVFGNVLVITAIAKFERLQTVTNYFITSLACADLVMGLAVVPFGA ccr1 METPNTTEDYDTTTEFDYGDATPCQKVNERAFGAQLLPPLYSLVFVIGLVGNILVVLVLVQYKRLKNMTSIYLLNLAISDLLF-LFTLPFWI ccr2 MLSTSRSRFIRNTNESGEEVTTFFDYDYGAPCHKFDVKQIGAQLLPPLYSLVFIFGFVGNMLVVLILINCKKLKCLTDIYLLNLAISDLLF-LITLPLWA ccr3 MTTSLDTVETFGTTSYYDDVGLLCEKADTRALMAQFVPPLYSLVFTVGLLGNVVVVMILIKYRRLRIMTNIYLLNLAISDLLF-LVTLPFWI ccr5 MDYQVSSPIYDINYYTSEPCQKINVKQIAARLLPPLYSLVFIFGFVGNMLVILILINCKRLKSMTDIYLLNLAISDLFF-LLTVPFWA

1F88 2RH1 ccr1 ccr2 ccr3 ccr5

1F88 2RH1 ccr1 ccr2 ccr3 ccr5 1F88 2RH1 ccr1 ccr2 ccr3 ccr5

3.50 4.50 YTSLHGYFVFGPTGCNLEGFFATLGGEIALWSLVVLAIERYVVVCKPMSN-FRFGENHAIMGVAFTWVMALACAAPPLVGWSRYIP-------EGMQCSC AHILMKMWTFGNFWCEFWTSIDVLCVTASIETLCVIAVDRYFAITSPFKYQSLLTKNKARVIILMVWIVSGLTSFLPIQMHWYRATHQEAINCYAEETCC DYKLKDDWVFGDAMCKILSGFYYTGLYSEIFFIILLTIDRYLAIVHAVFALRARTVTFGVITSIIIWALAILASMPGLYFSKTQWE--------FTHHTC HSAANE~WVFGNAMCKLFTGLYHIGYFGGIFFIILLTIDRYLAIVHAVFALKARTVTFGVVTSVITWLVAVFASVPGIIFTKCQKE--------DSVYVC HYVRGHNWVFGHGMCKLLSGFYHTGLYSEIFFIILLTIDRYLAIVHAVFALRARTVTFGVITSIVTWGLAVLAALPEFIFYETEEL--------FEETLC HYAAAQ~WDFGNTMCQLLTGLYFIGFFSGIFFIILLTIDRYLAVVHAVFALKARTVTFGVVTSVITWVVAVFASLPGIIFTRSQKE--------GLHYTC 5.50 6.50 GIDYYTPHEETNNESFVIYMFVVHFIIPLIVIFFCYGQLVFTVKEAAAATTQKAEKEVTRMVIIMVIAFLICWLPVAGVAFYIFTHFTH-----QGSDFG DFFT--------NQAYAIASSIVSFYVPLVIMVFVYSRVFQEAKRQLKF--CLKEHKALKTLGIIMGTFTLCWLPFFIVNIVHVIQD----T4---NLIR SLHFPHESLREWKLFQALKLNLFGLVLPLLVMIICYTGIIKILLRRPNE----KKSKAVRLIFVIMIIFFLFWTPYNLTILISVFQDFLFTHECEQSRHL GPYFP----RGWNNFHTIMRNILGLVLPLLIMVICYSGILKTLLRCRNE---KKRHRAVRVIFTIMIVYFLFWTPYNIVILLNTFQEFFGLSNCESTSQL SALYPEDTVYSWRHFHTLRMTIFCLVLPLLVMAICYTGIIKTLLRCPSK----KKYKAIRLIFVIMAVFFIFWTPYNVAILLSSYQSILFGNDCERSKHL SSHFPYSQYQFWKNFQTLKIVILGLVLPLLVMVICYSGILKTLLRCRNE---KKRHRAVRLIFTIMIVYFLFWAPYNIVLLLNTFQEFFGLNNCSSSNRL 7.50 PIFMTIPAFFAKTSAVYNPVIYIMMNKQFRNCMVTTLCCGKNPLGDSTTVSKTETSQVAPA KEVYILLNWIGYVNSGFNPLIYCR-SPDFRIAFQELLCL DLAVQVTEVIAYTHCCVNPVIYAFVGERFRKYLRQLFHRRVAVHLVKWLPFLSVDRLERVSSTSPSTGEHE DQATQVTETLGMTHCCINPIIYAFVGEKFRRYLSVFFRKHITKRFCKQCPVFYRETVDGVTSTNTPSTGEQEVSAGL DLVMLVTEVIAYSHCCMNPVIYAFVGERFRKYLRHFFHRHLLMHLGRYIPFLPSEKLERTSSVSPSTAEPE DQAMQVTETLGMTHCCINPIIYAFVGEKFRNYLLVFFQKHIAKRFCKCCSIFQQEAPERASSVYTRSTGEQEISV

Figure 12.4 Structure-based alignment of rhodopsin (1F88), b2 -adrenergic (2RH1) and selected chemokine receptors. The class A anchor residues are boxed with the most conserved residues indicated by Ballesteros/Weinstein numbers (helix number precedes the decimal, the most conserved residue is arbitrarily numbered 50). The T4-lysozme insertion in 2HR1 has been abbreviated as T4 in the b2 -adrenergic sequence.

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buried within the putative ligand-binding site collectively leading to an initial binding pocket too small to allow docking of known chemokine ligands. Side chain remodeling failed to yield a pocket of sufficient size, leading to the design of an expansion protocol that would produce receptor conformations suitable for docking studies (Fig. 12.5). The intent of the binding site expansion protocol is to apply a gentle pressure within the protein such that the shape of the slowly expanding binding site is dictated by the protein not by an artifact of the expansion process (Kimura et al., 2008). The internal pressure is created by the inflation of a ‘‘balloon’’ of Lennard-Jones spheres placed in the binding site whose radii are gradually increased during the course of the simulation (Fig. 12.6). To prevent shape memory within the balloon, the particles have

Figure 12.5 Comparison of the binding pocket volume (mesh) from a rhodopsinbased CCR2 model and the size of a small molecule CCR2 antagonist (shown as CPK).

B

Harmonic tethers

A

C

Figure 12.6 Schematic representation of the balloon expansion process. (A) Initial positioning of the Lennard-Jones spheres on a regularly spaced grid within the binding cavity. (B) Magnified view showing harmonic tethers. (C) Final expanded cavity.

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a very weak attraction to each other. However, to prevent evaporation, each particle is harmonically tethered to its four nearest neighbors; these tethers are reassigned periodically. To maintain the integrity of the helical bundle and to prevent unphysical deformations around the balloon, the backbone dihedrals within the helical regions are constrained except within four residues of the Pro/Gly hinge regions. This also effectively accelerates the simulation, because the helices are treated as semirigid bodies. To correctly model the native receptor environment, the simulation is carried out in a fully solvated periodic box of POPC lipids. As would be expected, the balloon effects a larger movement within the ‘‘soft spots’’ of the protein, with the more structured receptor elements being more resistant to change. In the putative chemokine ligand-binding site, this generally manifests itself as a dramatic change in the position of extracellular loop 2 with smaller movements of the transmembrane helices. Periodic snapshots of the receptor conformation are captured during the expansion process, and these serve as the starting point for ligand docking. By use of this procedure, CCR2 binding sites of sufficient size for ligand docking were obtained (Fig. 12.7). Because of the pressure that the balloon exerts on the side chains, their conformations are arbitrary and can be of high energy, necessitating side chain remodeling. Although an ensemble of receptors with varying side chain conformations could be constructed and docking studies undertaken with each member of the ensemble, it seemed more efficient to use an induced fit protocol like the one described by Sherman et al. (2006). The primary advantage of induced fit is that it positions the ligand and refines the side chain positioning simultaneously. This is accomplished by reducing the van der Waals radii of the receptor side chains, effectively allowing steric clashes to occur during ligand placement. The ligand is then docked and the side chains remodeled around the ligand pose. The refined receptor/ligand complex is rescored, returning a set of potential binding poses. These poses are then evaluated in the context of available mutagenesis and ligand SAR data. The models deemed most consistent with the available data are then

Figure 12.7 Expansion of the CCR2 rhodopsin model transmembrane ligand biding cavity. (A) Initial model. (B) Expanded to sphere radius 0.3. (C) Expanded to sphere radius 0.6.

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further refined by molecular dynamics simulation in the lipid bilayer. Analysis of the resultant trajectory allows the assessment of the stability of the proposed binding mode and the predicted interactions.

2.2. Application of the balloon expansion approach to model CCR2 antagonists This method has been used to generate models of CCR2 in complex with dual CCR2/5 antagonist TAK-779 (7) (Baba et al., 1999) and the CCR2 selective Teijin/Combichem (5) antagonist (Moree et al., 2008). Because it was difficult to predict which expanded receptor conformation would give rise to a disparate set of poses, docking studies were carried out in receptors that had been expanded with a range of particle radii. In practice we found that at r ¼ 0.3, TAK-779 and Teijin were able to dock, but a single bound conformation was observed. A minimum particle size of r ¼ 0.4 was required to generate the desired spread of conformations. Inspection of these conformations in the context of the reported mutagenesis data (Berkhout et al., 2003) revealed initial binding poses that could be refined into models largely consistent with the data as discussed in the following. TAK-779 (7) has been tested against nine mutations within the CCR2 small molecule antagonist binding site, spanning TM1 (Y49F), TM3 (Y120A, H121A, H121F), and TM7 (D284A, Q288A, Y290A, E291Q, T292A) (Berkhout et al., 2003). Although the relative effects of these mutations were modest, changes to the binding IC50 for TAK-779 were observed for Y120A (15-fold reduction), E291Q (30-fold reduction) and T292A (11-fold reduction) (Fig.12.8A). Our rhodopsin-based model (Fig. 12.8B) places the basic amine in proximity to E291 and places the aromatic portion of the bicyclic core in contact with the side chain of Y120. The model suggests a hydrogen bonding contact between the morpholino oxygen and the hydroxyl group of T292. However, SAR studies have shown that the morpholino oxygen is not critical for CCR2 binding affinity, leaving open the possibility that effect of the T292A mutation may be indirect. The model also suggests that much of the binding affinity is derived from hydrophobic and aromatic interactions between the biphenyl moiety and a deep hydrophobic/aromatic channel consisting of Y124, F125, I263, and W256. The contribution of these residues to the binding of TAK-779 has not yet been validated with mutagenesis, although if TAK-779 binding is driven primarily by interactions within this region, it would explain the relatively small contributions of Y120, E291, and T292. The model of TAK-779 in the CCR5 receptor showed that the key contacts are conserved, consistent with its dual CCR2/5 activity (Baba et al., 1999). A second compound of interest was the Teijin lead (5). In contrast to the CCR2/5 dual activity of TAK-779, compound 5 is CCR2-selective, an observation that should explained by the structural model. Teijin also shows

A

B Mutant

C

Fold change

Y49F

4

Y120A

15

H121A

2.6

H121F

0.4

D284A

1.8

H121 F125

R206

R206

T120 Y124

Q288A

3.3

T290A

1.5

H121

F125

Y120

F49 D291

I263 Y124 E291

D284 T292

Q288 T292

Q288

E291Q

30

T292A

11

T290

D284

F49

T290

Figure 12.8 Mutagenesis and modeling of TAK-779 (7) into CCR2. (A) Fold change in TAK-779 binding IC50 relative to wild-type CCR2 (Berkhout et al., 2003). (B) Rhodopsin/balloon-based model of TAK-779 in CCR2. (C) b2 -adrenergic-based model of TAK-779 in CCR2. ˚ of TAK-779 are shown.Those mutated in the Berkhout study are colored red. Residues within 4 A

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a much larger change in potency on mutation of E291 to alanine, suggesting a tighter contact between it and the antagonist basic amine, but a smaller effect in the Y120A mutant (Berkhout et al., 2003) (Fig. 12.9A). Our rhodopsin-based model (Fig. 12.9B) places the basic amine near E291, and Y120 is stacked against the glycine amide, forming a weak interaction. As with TAK-779, the model predicts several interactions that likely contribute to potency but are not yet tested. For example, it seems that the trifluoromethyl phenyl ring forms a face-face stack with Y259 with additional hydrophobic contacts to I263. The CCR2 selectivity for Teijin seems to be due to the projection of the dimethylbenzyl ring into a pocket composed of residues from TM2 (A99 and S101), EC1 (V107), TM3 (Y116), and bounded by the conserved disulfide between EC2 and TM3 (C190 and C113, respectively). Comparison of the residues within this pocket in CCR2 and CCR5 reveals a serine (CCR2, S101) to tyrosine (CCR5, Y89) swap. Notably, the bulky aromatic side chain of Y89 in CCR5 would occlude this pocket, blocking the binding of the dimethylbenzyl moiety of Teijin in CCR5. Our model is thus consistent with the CCR2 selectivity of the Teijin antagonist. Because TAK-779 does not project a group into this pocket (Fig. 12.8B), its affinity is not reduced and may be enhanced by additional hydrophobic interactions with Y89.

3. The Use of b2-Adrenergic Receptor Structure as an Alternative Template 3.1. Comparison of our b2- and rhodopsin-derived models of CCR2 antagonist docking These examples, and several others in the literature (Table 12.1), demonstrate the use of the rhodopsin receptor as a template for chemokine receptor modeling, albeit with manipulation. An alternate template recently became available with the release of the b2-adrenergic/carazolol crystal structure (Cherezov et al., 2007) warranting a comparison of models based on this new template to the existing rhodopsin models to assess its relevance in chemokine modeling. In contrast to the rhodopsin crystal structure, the b2-adrenergic ligand-binding site is larger and more open because of differences in helical and extracellular loop 2 placement. Because of this, the initial chemokine receptor models constructed from the b2-adrenergic template showed binding sites within the transmembrane region of a size sufficient to dock ligands without the need for balloon expansion, allowing us to revise the modeling protocol, eliminating this step from the docking process (Fig. 12.3). Although the transmembrane region enabled docking, for several ligands it was found that EC2 impinged on the binding site causing steric clashes. A remodeling step was added to our revised protocol

A

B Mutant

Fold change

Y49F

0.9

Y120A

5.4

H121A

7.6

H121F

1.9

C

H121

D284A

2.1

Q288A

0.9

E291Q

Inactive

T292A

22.9

H121 Y120

Y120

S101

S101 E291

E291

D284 T292

Y49

Q288

Q288 T292

D284

Figure 12.9 Mutagenesis and modeling of Teijin antagonist 5 into CCR2. (A) Fold change inTeijin binding IC50 relative to wild-type CCR2 (Berkhout et al., 2003). (B) Rhodopsin/balloon-based model of Teijin in CCR2. (C) b2 -adrenergic^based model of Teijin in CCR2. Residues within 4 A˚ of Teijin are shown.Those mutated in the Berkhout study are colored red.

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to enable accurate modeling of EC2 in the presence of ligand. With this protocol, we reevaluated our CCR2 models of TAK-779 (7) and Teijin antagonist 5. As described in the other sections that follow, we also extended our study to examine models of the CCR1 antagonist BX-471 (2) and the CCR5 antagonist Maraviroc (14). The ligand-binding site from our b2 adrenergic–derived CCR2 model was able to accommodate both TAK-779 and Teijin, requiring only a small displacement of EC2. The TAK-779 contacts predicted by the new model are similar to the rhodopsin based model, but the placement of the ligand is slightly different (cf. Fig. 12.8B and 8C). An enlarged cavity exists between TM3, TM5, and TM6 in our b2 model that allows the biphenyl moiety to sit more deeply into the receptor and enhances the number of aromatic and hydrophobic contacts in this region. This displacement toward TM5 places the central phenyl ring in an edge/face contact with Y120 and positions the amine near E291. The morpholino group is packed against TM2 and appears to make only nonspecific hydrophobic contacts with it. The Teijin CCR2 antagonist also fit well into the CCR2 model. Our b2 model suggests that much of the binding affinity is derived from several aromatic and hydrophobic interactions with the trifluoromethyl phenyl ring (Fig. 12.9C). The central amide is in contact with Y120, and this weak interaction is consistent with the mutagenesis data. Teijin also shows a critical dependence on E291, which is predicted to be in a tight salt bridge with the pyrrolidine amine. The dimethyl benzyl group is oriented toward TM2 and TM3, contacting W98, L97, and S101. The basis for the lack of CCR5 potency for the Teijin antagonist can again be explained by the swap of S101 in CCR2 with Y89 in CCR5. Neither of our CCR2 models predicts any direct contact between T292 and the ligands. However, a hydrogen bond is evident between the side chain hydroxyls of T292 and Y49. It is possible that the effect of the T292A mutation is indirect, because removal of the threonine side chain would likely cause a change in its packing with Y49, resulting in a repositioning of TM1 and TM2. Molecular dynamics simulations of the mutant receptor do show a conformational change in this region and a resulting contraction in the size of the pocket (data not shown). As would be expected, the mutation has a larger effect on the more rigid benzyl group of Teijin than the more flexible morpholino amine from TAK-779.

3.2. Application of the b2 template to develop a new model of CCR1: Comparison to rhodopsin and MembStruk models Two models have been reported for the CCR1 receptor: a rhodopsin-based model of UCB35635 (1) (Mendonca et al., 2005), and a MembStrukderived model of BX-471 (2) (Vaidehi et al., 2006). Because both models were generated before the structure of the b2-adrenergic receptor was

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known, we undertook a comparison to the newly generated b2 models. Of particular interest was the BX-471 model, because the MembStruk (Trabanino et al., 2004) method does not rely on the rhodopsin template, but instead constructs the helical bundle de novo, as briefly described here. The MembStruk receptor building process begins by predicting the helical boundaries and building canonical helices. The helices are initially positioned within the membrane by aligning them with the 3-D density map of frog rhodopsin. Their relative translations and orientations are then optimized by means of hydrophobicity predictions. Finally, helical bends and kinks are introduced with molecular dynamics and loops are added to the refined helical bundle. The predicted ligand-binding site is detected by searching the receptor model for areas with sufficient void volumes and ligands are docked into these regions. The initial poses are subjected to energy minimization and side chain remodeling. Final optimized complexes are selected on the basis of their predicted binding energy. The MembStruk CCR1/BX-471 model (Vaidehi et al., 2006) predicts ligand binding into a site overlapping with retinal and carazolol, consistent with the predictions for CCR2 and CCR5. The key interactions are between the chlorophenyl ring Y114 and I259 and the fluoro phenyl ring and Y113. No polar interactions are predicted by the model. Of particular note, there is no interaction between the basic amine and the conserved glutamic acid 287. The model was validated with mutagenesis studies where it was found that the Y113A, I259A, and Y114A mutants led to a >1000-, >1000- and 500-fold loss in binding affinity of BX-471, respectively. The I91A, Y291A, T86A, E287Q, Y41A, Y113F, and L260A mutations had a smaller impact on ligand binding (<100-fold). Ligand SAR showed no change in binding affinity on replacement of the chlorophenyl-urea ring with a trimethoxyphenyl, a complete loss of potency if the para-fluoro phenyl ring is exchanged for a para-methoxy phenyl and if an aminomethyl group is appended to the piperazine ring. These observations are consistent with the predicted binding mode, because the urea does not make any interactions, the fluoro phenyl ring makes a critical interaction with Y113, and the piperazine ring is buried in a hydrophobic pocket. With our comparative modeling scheme, binding models of BX-741 in CCR1 based on rhodopsin and b2 have been constructed (Fig. 12.10). As was observed in our CCR2 work, the binding cavity of the rhodopsin-based CCR1 model was occluded by aromatic residues requiring expansion. On expansion to r ¼ 0.4, the pocket opened into a large hydrophobic pocket bounded by TM3-6 and a smaller pocket delineated by TM1-2 and TM7. The two pockets are separated by the side chain of Y113. BX-471 (2) could be docked into the expanded pocket. The binding mode that was most consistent with the mutagenesis data was similar to that of the MembStruk model (Fig. 12.10B). The fluoro phenyl ring falls into the smaller pocket forming a face-face p-stacking arrangement with Y103, with multiple

A

B

Mutant

Binding IC50 (nM)

C

Ratio

WT

10 ± 5

1.0

Y113A

> 10,000

> 1000

Y113F

464 ± 164

46

I259A

> 10000

> 1000

Y114A

5017 ± 1970

502

I91A

849 ± 287

85

Y291A

541 ± 308

54

T86A

348 ± 180

35

E287Q

344 ± 122

34

Y41A

264 ± 179

26

L260A

58 ± 6

6

Y114

Y114

T86

T86 191 I259

Y113 E287

Y113 I259

Y291

Y41

I91 E287

Y291 Y41

Figure 12.10 Mutagenesis and modeling of BX-471 (2) into CCR1. (A) Binding affinities of BX-471against CCR1mutant receptors (Vaidehi et al., 2006). (B) Binding model of BX-471 in the expanded rhodopsin-derived CCR1 model. BX-471 is shown in yellow, mutations with a >500-fold loss in binding affinity are colored red, those with >20-fold loss are orange. (C) Binding model of BX-471 in the b2 -derived CCR1 model. Residues are shown as in panel B.

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hydrophobic interactions with I91 and Y291. The chlorophenyl ring and its linker fall into the larger pocket, with the key interactions being a stack with Y104 and multiple hydrophobic contacts with I259. The urea moiety, which is quite tolerant of substitution, is oriented toward solvent. No contact between the piperazine amine and the acidic side chain of E287 is predicted. The binding cavity in our b2-derived CCR1 model had sufficient volume to dock BX-471 with only minor changes in the position of EC2 (Fig. 12.10C). A significant difference between this model and the rhodopsin model is the size of the smaller pocket created by TM1-2 and TM7, caused by displacement of TM1-2 relative to TM7. This allowed BX-471 to dock in several orientations not accessible in the rhodopsin model and led to an alternative binding hypothesis. Our b2-based model places the fluoro phenyl ring in the larger pocket contacting Y113, Y114, and I259, with the chlorophenyl ring oriented toward a smaller pocket with interactions to Y41, T86, I91, and Y291. Although the binding mode is flipped relative to both our rhodopsin-based model and Vaidehi’s Membstruck-derived model, the mutagenesis and SAR data suggest that this new pose is also quite plausible. The SAR shows that the fluoro phenyl ring is immutable in contrast to the chlorophenyl ring that is more tolerant of substitution. From the mutagenesis, it is clear that Y113, Y114, and I259 are critical binding partners, likely interacting with fluoro phenyl ring, a key feature in the antagonist. The cholo phenyl ring makes a number of less direct interactions with residues in the smaller pocket, which is consistent with the smaller, but still significant, effect on alanine mutations within this pocket: I91 (85-fold), T86 (35-fold), Y41 (26-fold), and Y291 (54-fold). The solvent exposure of this pocket accommodates the urea moiety and explains the lack of SAR on its substitution.

3.3. Application of the b2 template to develop a new model of CCR5 A new modeling and mutational study of TAK-779 (7), Maraviroc (14), and several additional CCR5 antagonists has recently been reported (Kondru, R., et. al., 2008). Their receptor models were derived from the rhodopsin template and predict a binding mode of TAK-779 resembling our proposed binding mode in CCR2. For comparison, we constructed b2-derived CCR5 models and docked TAK-779 and Maraviroc. The docked pose of TAK-779 is quite similar to our CCR2 models, which is as expected, given the high degree of homology within the binding site and the compound’s potency against both receptors (Fig. 12.11B). The key interactions within the CCR5 model are between F108 and the TAK-779 central phenyl ring and between W86 and the morpholino moiety, consistent with the 28-fold and 53-fold loss in potency for the Y108A and W86A mutations, respectively. One key difference between the Kondru rhodopsin model and our b2-based model is the interaction between the morpholino moiety and the side chain of W86.

A

B

C

Fold change Mutant

TAK-779

Maraviroc

WT

1.0

1.0

W86A

53

10 2.0

W94A

2.8

Y108A

28

70

F109A

2.3

0.9

T195A

1.6

5.0

I198A

6.5

89

W248A

7.4

1.4

Y251A

2.8

12.2

E283A

11

2000

M287A

1.3

0.4

Figure 12.11 Predicted binding modes of TAK-779 (7) and Maraviroc (14) in b2 -derived CCR5 models. (A) Fold change in binding IC50 on mutation of the indicated residue (Kondru et al., 2008). (B) Binding model of TAK-779.TAK-779 is shown in yellow sticks, and the mutated residues are shown as green lines.Y89 is also shown as green lines. (C) Binding model of Maraviroc shown in the same view as panel B.

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The Kondru model predicts a hydrogen bond between the side chain indole NH and the morpholino oxygen. In the b2-derived model (Fig. 12.11B), the indole NH is hydrogen bonded to a side chain carbonyl of E283, with the aromatic portion of W86 forming hydrophobic contacts with the morpholine. The SAR around TAK-779 supports this hypothesis as it has been shown that the morpholine is not critical for activity in closely related series (Shiraishi et. al., 2000). As noted in the CCR2 model, it seems that much of the binding energy is derived from the biphenyl moiety that is buried in a hydrophobic/aromatic pocket between TM3, TM4, and TM5. The residue I198 is located at the top of this pocket and forms a loose contact with the cycloheptyl ring that projects the biphenyl moiety into this pocket. It also seems that the quaternary amine is near the side chain of E283, but does not form any direct interactions. The Kondru rhodopsin model of Maraviroc in CCR5 centers the binding around a critical interaction between the basic amine and E283, as would be predicted from the lack of binding in the E283A mutant receptor. The difluorocyclohexane ring projects toward TM5 at the far end of the pocket and contacts I198. The central phenyl ring is in the middle of the pocket, forming stacking interactions with Y108 and Y251. The disubstituted triazole is on the opposite side of E283 residing in a pocket between TM1, TM2, and TM7, and makes hydrophobic contacts with W86. Our b2-based model positions Maraviroc in a similar orientation, with the basic amine in contact with E283 and the difluorocyclohexyl ring interacting with I198, but differing in the contacts between the central phenyl and the triazole. In our b2-derived model (Fig. 12.11C), the central phenyl ring is pointed away from Y108, toward EC2, and contacting Y251. The triazole ring forms an edge-face interaction with W86, and its isopropyl moiety lies on the face of Y108. This model is consistent with the mutational data, which shows that Maraviroc requires an acidic residue at position 283 and hydrophobic residues at positions 198 and 108. It is also consistent with the smaller effect of mutating W86 and Y251. One key interaction that is predicted in our b2 model—and not described in the Kondru model—is a face-face interaction between Y89 and the triazole ring. This contact may explain Maraviroc’s lack of potency in the CCR2 receptor ( Dorr et al., 2005), as Y89 is replaced by S101, which would not support the aromatic interaction.

4. Conclusions As discussed previously, numerous contributions have been made to the chemokine literature that have used site-directed mutagenesis and receptor homology modeling as a template for rationalization of the binding of known ligands (Table 12.1). In this Methods chapter, we have discussed two complementary approaches to the homology modeling process for

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chemokine receptors (Fig.12.3). The balloon-expansion process allows one to expand the small transmembrane cavity present in the rhodopsin crystal structure to accommodate organic chemokine receptor antagonists. Alternately, one can use the b2-adrenergic model as the template, which then requires modification of EC2 (see also Costanzi, 2008). Although the b2-adrenergic receptor is an exceptionally good starting point for ligand docking, given that it shares the crucial TXP motif in helix 2 (Arias et al., 2003) with the chemokine receptors, we have shown that both templates can provide models of ligand binding that are consistent with the mutagenesis data (Figs. 12.8 to 12.11).2 By performing the modeling studies described previously in a retrospective fashion, it is possible to bring a greater degree of scientific rigor to the process, because more receptor mutants can be made, more pharmacology can be performed, more SAR can be used for input into the model, and more refinement of the model can occur. Of course, the problem is that this process of acquiring detailed data inputs (mutagenesis, pharmacology, SAR) to build the ultimate model takes time and reduces the impact that such activities can have on the speed of a program’s progress. Thus, the question now is, ‘‘are the current models ‘good enough’ to allow for SAR-guided docking in the absence of other experimental evidence?’’ Most activity reported in the GPCR literature related to this question has focused on hit identification (Fujiwara et al., 2007; Sabio et al., 2008; Vaidehi et al., 2006), and some early success has been documented. In the specific instance of the chemokine receptor field, however, no reports of SAR development from hits identified in virtual screening processes have been forthcoming. Likewise, no articles have described the use of homology models to drive progress in a program in the absence of mutagenesis data. However, the large body of accumulated knowledge from the existing mutagenesis and modeling studies should now greatly facilitate application of these models to additional discovery programs. Taken as a whole, these studies delineate a binding site within the transmembrane region that seems to be generally conserved within the chemokine family and reveal a consistent set of interactions in this site. The current models can be used as starting points for the next iteration, focusing the mutagenesis efforts leading to the more rapid model refinement and greater impact. A second favorable consideration is the recent availability of additional templates for receptor modeling. Given the results we have described herein, we feel that the b2-template is well suited for this activity, and there will certainly be others as the crystallization method matures. We encourage those in the field to consider exploring the usefulness of the collective body of mutagenesis data and its application to these new templates.

2

For an interesting example of a b2-adrenergic structure generated by means of rhodopsin homology modeling versus that derived from crystallographic data, see the recent study by Constanzi (2008).

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C H A P T E R

T H I R T E E N

Characterizing Proteolytic Processing of Chemokines by Mass Spectrometry, Biochemistry, Neo-Epitope Antibodies and Functional Assays Amanda E. Starr* and Christopher M. Overall*,† Contents 1. Introduction 2. In vitro Processing and Characterization of Proteolysis 2.1. In vitro cleavage assays 2.2. Endogenous protease cleavage of chemokine 2.3. Detecting chemokine cleavage by TRIS-tricine PAGE 2.4. Identifying cleavage sites by mass spectrometry 2.5. Detection of processed chemokines by neo-epitope antibodies 2.6. In vitro functional characterization of proteolysis 2.7. Transwell migration as an indication of chemotactic potential 2.8. Intracellular calcium mobilization to evaluate receptor activation 2.9. Binding to glycosaminoglycans 3. In Vivo Functional Characterization of Proteolysis 3.1. Chemotaxis in air pouch and peritonitis models 3.2. Subdermal injection 4. Summary Acknowledgments References

* {

282 283 283 286 287 289 294 295 297 300 301 303 303 304 304 304 305

Departments of Biochemistry and Molecular Biology, University of British Columbia, Centre for Blood Research, Life Sciences Institute, Vancouver, British Columbia, Canada Oral Biological and Medical Sciences, Centre for Blood Research, Life Sciences Institute, Vancouver, British Columbia, Canada

Methods in Enzymology, Volume 461 ISSN 0076-6879, DOI: 10.1016/S0076-6879(09)05413-5

#

2009 Elsevier Inc. All rights reserved.

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Abstract The nature, sequence, and length of the carboxy and amino termini of chemokines are important determinants of chemokine function, being essential for both efficient haptotactic gradient formation and cognate receptor activation events of these chemotactic cytokines. Chemokines are susceptible to proteolytic cleavage in both of these regions, which usually results in dramatic changes to the chemokine bioactivity. Herein we provide techniques to assess, detect, and characterize protease activity on chemokines and the biologic outcomes.

1. Introduction The amino acid sequence similarity of chemokines ranges from 20 to 95%, yet the general tertiary structure of chemokines is maintained, indicating the importance of chemokine structure in its function (Allen et al., 2007; Fernandez and Lolis, 2002). The chemokine carboxyterminal a-helix, if rich in basic residues, is important for forming a haptotactic gradient for the recruitment of leukocytes to an inflammatory site (Proudfoot et al., 2003), whereas residues within the 30s-loop and N-loop or in the flexible amino-terminus of the chemokine are involved in binding and activating its cognate receptor through interaction with the transmembrane helix bundle on the leukocyte surface (Baysal and Atilgan, 2001; Blanpain et al., 2003; Pease et al., 1998; Zoffmann et al., 2002). Receptor activation results in second messenger signaling, gene transcription, relocation of receptors from and to the cell membrane, and the release of further inflammatory mediators. Hence the sequence and structure of these critical regions drives the functionality of chemokines. Posttranslational modifications of both the N- and C-termini of chemokines by proteolytic processing is a natural mechanism of chemokine regulation; cleaving chemokines into stronger agonists to chemoattract appropriate cells (Tester et al., 2007) or into antagonists (Cox et al., 2008; Gong and Clark-Lewis, 1995; McQuibban et al., 2000, 2001, 2002) to terminate the intercellular signaling events, loss of agonist activity causing receptor switching for recruitment of an alternate cell lineage (McQuibban et al., 2001; Vergote et al., 2006), or alternatively modifying the GAG binding domain to prevent gradient formation (Cox et al., 2008). For example, proteolysis of CCL7/monocyte chemotactic protein-3 (MCP-3) by matrix metalloprotease (MMP)-2 or murine (m) LIX by MMP-8 results in N-terminal truncation of the first 4 amino-terminal residues of the chemokines (McQuibban et al., 2000; Tester et al., 2007), truncations that result in strong receptor antagonists, and in the case of CCL7, capable of reversing inflammatory responses in vivo (McQuibban et al., 2000, 2002).

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Conversely, truncation of the first 4 amino-terminal residues of LIX results in a more potent chemoattractant (Tester et al., 2007). In 2000, we used a novel yeast two-hybrid approach to first identify chemokines as substrates of MMPs (McQuibban et al., 2000). Since then, a number of proteases have been shown to cleave chemokines (reviewed by Wolf et al. 2008) by both hypothesis-driven (Ajami et al., 2008; Cox et al., 2008; Dean et al., 2008; Tester et al., 2007) and by hypothesis-generating (Dean and Overall, 2007) experiments. Herein, we provide methods used to evaluate the capacity of proteases to process chemokines, to evaluate the functional effects of truncation both in vitro and in vivo, and to detect these chemokine truncation variants in cell culture and in vivo.

2. In vitro Processing and Characterization of Proteolysis 2.1. In vitro cleavage assays Chemokine proteolysis can first be evaluated in a simple biologic system with minimal components, specifically a chemokine, a protease, and buffer. The use of synthetic chemokines rather than recombinant chemokines is preferred (Clark-Lewis et al., 1997); these are functionally and structurally identical to their recombinant counterparts but have great advantage in their purity and sufficient quantity, and, importantly, the ability to make synthetically truncated forms that correspond in length to the observed proteolyzed chemokine as cleaved chemokine analogs. A significant advantage over recombinant chemokines is the absence of lipopolysaccharide (LPS), which always contaminates bacterially expressed proteins and hence requires extensive cleanup before biological assays. Furthermore, having homogenous preparations of the exact cleavage product simplifies data interpretation, especially where a protease cleaves at multiple sites in a chemokine. Purifying significant quantities of each product generated from proteolysis can be extremely difficult and rarely can 100% pure preparations be obtained. Synthetic cleaved analogs of proteolyzed chemokines can, therefore, be comprehensively characterized by cellular and in vivo assays because of the ease in obtaining milligram quantities of these mediators. Chemokines are dissolved in water to a final stock concentration of 1 mg/ml, aliquotted, and stored at
80  C after snap freezing in liquid N2. Cleavage of the chemokines in vitro is carried out in a buffer system, originally made up as a 10 stock that is appropriate to the enzyme of interest and is compatible with mass spectrometry (MS). The source of chemokines is important to note when preparing the buffer. Although synthesized chemokines are free from other buffer systems, recombinant chemokines may be lyophilized from a phosphate buffer and so for assaying

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Table 13.1 Cleavage assay buffer recipes Enzyme

10 Assay buffer

Notes

MMPs

2 M NaCl 50 mM CaCl2 0.5 M TRIS-HCl 0.05% Brij 0.025% NaN3

pH to 7.4 Brij and NaN3 reduce the sensitivity of MALDI-TOF

Cathepsins

0.5 M Sodium citrate 0.5 M NaCl

pH to 4.0

PBS 40 mM EDTA 20 mM L-cysteine

pH to 6.8

Dipeptidyl 0.5 M TRIS peptidases 10 mM EDTA

pH to 7.6

Table 13.2 Common reagent compatibility limits for MALDI-TOF MS Reagent

Maximum concentration

Urea Guanidine-HCL Dithiothreitol, b-Mercaptoethanol NaCl Alkali metal salts HEPES, MOPS, TRIS buffer NH4HCO3 Sodium hydroxide Sodium azide Phosphate buffer DMSO Glycerol Tween, Triton-X SDS

2M 2M 50 mM 50 mM 50 mM 50 mM 50 mM 50 mM 50 mM 15 mM 10 mM 20% 1% 0.1% 0.01%

protease activity requiring calcium, additional calcium is necessary because of precipitation of calcium phosphates, which also alters the pH. Cleavage assay buffers are provided in Table 13.1; common protease assay buffer reagents that are incompatible with MS, and thus should be avoided, are provided in Table 13.2.

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Before incubation with the chemokines, proteases should be activated and active site titrated against appropriate protease inhibitors to ensure the enzyme/chemokine mole ratio is based on active enzyme rather than total protein. In general, MMPs are activated in a minimal volume with 1 mM APMA at 37  C for 1 h and then an aliquot titrated against TIMP-1 or -2 with a quenched fluorescence assay (Bickett et al., 1993, 1994). We first evaluate cleavage of chemokines at a mole ratio of 1:10 enzyme/chemokine and if cleavage is detected, decrease the amount of enzyme in subsequent assays. This is to ensure that a definite ‘‘no cleavage’’ result is, in fact, valid. Samples evaluated must include (1) chemokine alone, (2) protease alone, and (3) chemokine þ protease; additional controls such as (4) assay buffer, (5) protease inhibitor alone, and (6) chemokine þ protease þ protease inhibitor, should also be included, because they are important for later evaluation of functional effects of proteolysis. Cleavage in the presence of glycosaminoglycans (GAGs) may also be considered, because these are critical components in gradient establishment in vivo (Proudfoot et al., 2003). Although we have never found that GAGs can reduce cleavage of a chemokine (Cox et al., 2008; McQuibban et al., 2001), it is possible that protease binding to a GAG chain may colocalize the chemokine with a similarly bound protease and so enhance cleavage kinetics. Chemokine cleavage is evaluated at pH 7.4 at 37  C. Cleavage assays are best performed in a 15-ml total reaction volume containing active enzyme at a volume calculated to be 10% molar amount of the chemokine, 1.5 ml of 10 cleavage assay buffer, and 1.5 ml of 1 mg/ml stock chemokine for a final chemokine concentration of 0.1 mg/ml; this allows sufficient product for analysis by two silver-stained gels (Table 13.3) and enough sample to also be evaluated by MS. The additional volume is made up with water (note the utility of H2O18 for ambiguous samples as discussed in MS section). The reaction volume can easily be scaled up and works just as well. To determine the time required for cleavage, an initial experiment should be performed in which a 1-ml aliquot is removed at 30- or 60-min intervals and spotted on a MALDI plate, as outlined later, and analyzed for cleavage; subsequent cleavage assays can be completed at one time point after determining the time required for complete chemokine cleavage. In general, MMP cleavage of chemokines is evaluated at 16 h, whereas cathepsins and dipeptidyl peptidases are evaluated within a 4-h time period. In vitro cleavage reactions can be stopped by the addition of appropriate enzyme inhibitor, SDS-PAGE loading buffer (not appropriate before MS), combining with MS matrix and spotting, or by snap freezing samples in liquid nitrogen. In preparation for electrophoretic analysis, samples are heat denatured then briefly centrifuged to ensure all the sample is collected at the bottom of the tube; samples can then be stored at
20  C for analysis at a later date.

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Table 13.3 Silver stain materials and protocol

Step

Reagent

1. Fix

40% Methanol, 10% acetic acid

2. Prestain

0.15 g K3Fe(CN)6 0.25 g Na2S2O3(5 H2O) Dissolved in 50 ml water

3. Wash

H2O

4. Silver

5. Rinse

4.1 g AgNO3 in 200 ml water for 10 stock; use 50 ml per gel at 1x H2 O

6. Rinse

2.9% Na2CO3

7. Develop 2.9% Na2CO3 þ 0.1% formaldehyde 8. Stop 5% Acetic acid

Shaking incubation

15 to a maximum of 30 min 5 min

2 10 min (until colorless) 20 min

2 10 sec 2 10 sec Up to 5 min

2.2. Endogenous protease cleavage of chemokine To assess protease cleavage of chemokines in a cellular context, full-length chemokine can be added to primary cells, cell lines, or conditioned media from cells known to produce the enzyme of interest. Cells may require preincubation with a stimulant to induce enzyme production, for example Con A activation of fibroblasts for the production of active MMP-2 (McQuibban et al., 2000; Overall and Sodek, 1990). Depending on the cell type and relative quantity of enzyme produced, 0.5 to 5  107 cell/ml in appropriate serum-free media is incubated with sufficient chemokine for visualization on a silver-stained gel after incubation with the cells—this amounts to a minimum final concentration of 0.1 mg/ml chemokine in the media. Note that chemokines bind to cell membranes, reducing the amount of chemokine available in the conditioned media for detection after the assay, thus more than 0.1 mg/ml of chemokine may be required. Because of the high concentration of chemokine, it is advantageous to evaluate the cleavage in as low a volume of medium as possible, ranging from 100 to 500 ml. As with in vitro cleavage described previously, samples analyzed should include (1) cells alone, (2) chemokine alone, (3) cells þ chemokine, (4) cells þ inhibitor, (5) cells þ chemokine þ inhibitor. Samples are incubated at 37  C; at 30-min intervals, 25-ml aliquots are removed, cells spun out, and the supernatant analyzed for chemokine cleavage with MS, TRIS-tricine

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PAGE, and by Western blot or enzyme-linked immunosorbent assay with antibodies to full-length chemokine and neoepitope antibodies.

2.3. Detecting chemokine cleavage by TRIS-tricine PAGE Specific processing at the terminus of a chemokine generally results in the removal of a small number of amino acids (from 1 to 10), consequently shifting the molecular weight of the chemokine by less than 10%. The product of proteolysis may be visualized and compared with the full-length chemokine by staining of samples after TRIS-tricine PAGE (Fig. 13.1). In comparison, SDS-PAGE with conventional TRIS-glycine gels lack sufficient resolution to detect mobility shifts of a few hundred Daltons. Electrophoresis is best performed with 5 ml of in vitro cleavage assay product (corresponding to 0.5 mg) in 2 ml of 4 sample buffer (48 g urea, 8 g SDS to 100 ml in 1 M TRIS-HCl pH 6.8, 100 mM DTT, and bromophenol blue or Coomassie G250) per well in a freshly prepared 0.75-mm TRIS-tricine 15% polyacrylamide gel (Table 13.4); note that the sample buffer does not contain glycerol because this clings to lane wells and causes ‘‘smiling’’ of the gel. In its place, we use 2 M urea that increases the sample density and is also a denaturant, so improves band resolution. The running buffers are prepared such that a pH gradient is established; the upper reservoir running buffer (0.2 M TRIS) is at pH 9.0, whereas the bottom reservoir running buffer (0.1 M TRIS, 0.1 M tricine, 0.1% SDS) is at pH 8.2. Samples are mobilized through the stacking gel at 40 volts for

CCL7

CCL8 MMP-7

−

+

MMP-12

−

−

− +

−

+

−

−

− +

4938281714-

63-

Figure 13.1 Silver-stained 15% TRIS-tricine gel indicating a mobility shift of the indicated chemokines after 16 h incubation at 37  C in the absence or presence of a 1:10 molar ratio of the catalytic domains of MMP-7 or MMP-12. Arrows indicate the full-length chemokine; arrowheads indicate the truncated chemokine. CCL8 is indicated in black, CCL7 in grey.

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Table 13.4 Reagents for the preparation of five TRIS-tricine 15% polyacrylamide gels Separating gel

Stacking gel

Components

Gel buffer

8.3 ml

5 ml

30% Acrylamide Water 10% APS TEMED

12.4 ml

2.6 ml

3 M TRIS, 0.3% SDS, pH 8.45 in 32% glycerol 30% Acrylamide/bis solution 29:1

4.1 ml 188 ml 6.3 ml

12.2 ml 120 ml 12 ml

Add second to last Add last

approximately 1 h, and through the separating gel at 60 to 80 volts for approximately 5 h until the dye front has run off. In TRIS-tricine gels, a slow electrophoresis improves the resolution and band separation. The gel can be incubated in prestain (40% methanol, 10% acetic acid) for up to 1 h but should not be left for extended periods before silver staining, because bands will be diffuse and indistinct or diffuse completely out of the gel. Alternately, gels can be stained with Coomassie brilliant blue, although twice as much cleavage product would be required to ensure that it is visible. TRIS-tricine PAGE, combined with densitometry, is an effective way to estimate the t1/2 of proteolysis, and with Eq. (13.1), the kcat/kM kinetics of chemokine cleavage. In vitro cleavage can be carried out as previously stated, although an increased volume is required. Aliquots of 10 ml are removed at equal time intervals from the in vitro cleavage assay at a minimum of 8 time points (including the ‘‘0’’); the protease activity is stopped as outlined previously. At completion of the timeline, samples are subjected to TRIS-tricine PAGE and a mobility shift observed by staining. It is critical to stain with Coomassie brilliant blue rather than silver stain, because the latter can easily saturate and is no longer in the linear range, thereby preventing accurate densitometric analyses. With software that measures density (general available with gel documentation or scanning equipment), the time point at which the density of the full-length chemokine is half of the density of the same band at the zero time point represents the t1/2. Using Eq. (13.1), with known enzyme and chemokine concentrations, and experimentally determined t1/2, the observed kcat/kM is calculated. This value, also known as the specificity constant, indicates the relative capacity for a given protease toward that chemokine as a substrate.

kcat k In2 0:69 Where k ¼ ¼ ¼ kM ½E t1=2 t1=2

ð13:1Þ

Chemokine Proteolysis Detection and Function

289

2.4. Identifying cleavage sites by mass spectrometry Mass spectrometry (MS) is an efficient and accurate means of identifying the mass of a processed chemokine and, by comparison with the full-length counterpart, enables deconvolution of the mass to charge (m/z) ratios of the full-length and protease-processed products to identify the cleavage site without performing tandem mass spectrometry or Edman sequencing. Matrixassisted laser desorption ionization time-of-flight (MALDI-TOF) MS is a sensitive method that requires minimal sample preparation yet yields accurate results. Single charged species are most commonly obtained with MALDITOF, reducing the complexity of spectra and hence simplifying data interpretation. Occasionally, double-charged species are detected by MALDI-TOF at an m/z ratio corresponding to a mass one half of the actual mass of the peptide. As the name suggests, MALDI-TOF transfers energy from a laser source to a sample, thus causing sample ionization by means of a chemical matrix. The capacity of a sample to be ionized is reduced by the presence of salts and certain detergents (Henzel and Stults, 2001) (Table 13.2), and so, ideally, contaminants would have been removed before chemokine cleavage. Cleavage products in a low salt buffer, such as the one described (Table 13.1), can be used without any further preparation. If the cleavage assay buffer or the enzyme preparation has contaminants present, the sample may require a cleanup step before MS. ZipTips (Millipore) or, preferably, STAGE tips (Rappsilber et al., 2003) are a useful means of reducing salts from small volumes; following the manufacturers protocol, ZipTips are an effective tool but tedious in nature so useful for no more than 10 samples at a time. For cleanup of a greater number of samples, washing of the samples on the MALDI plate is possible and effective (outlined in the following). The matrix used for MALDI-TOF of chemokines is a sinapinic acid solution consisting of 7 to 10% (w/v) 3,5-dimethoxy-4-hydroxycinnamic acid, 30% acetonitrile, and 0.3% trifluoroacetic acid, which is stored at 4  C. Any undissolved matrix from this saturated solution can be centrifuged out or allowed to settle out and only the supernatant used for sample analysis. The matrix is combined with sample in a 1:1 ratio either before or directly spotted onto a standard stainless steel MALDI sample plate and left to air-dry; this dry droplet method works effectively, although alternative methods can be found elsewhere ( Jimenez, 2005). Chemokine cleavage can be evaluated by MALDI-TOF in either linear or reflective mode. Because the path of travel is further in reflective mode than in linear mode, a higher laser intensity is required and may not work as well for some of the larger chemokines (>10,000 Da). In reflector mode, MALDITOF can separate the isotopic variants of a sample and thus can provide monoisotopic masses. For peptides or proteins greater than 15,000 m/z, the isotopic distribution follows Gaussian distribution, and so the average masses is applicable (Strupat, 2005).

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Table 13.5 Voyager-DE STRTM settings for efficient spectral acquisition Control

Setting

Notes

Mode of operation Extraction mode Polarity Acquisition control Accelerating voltage Grid voltage Extraction delay time Acquisition mass range Number of laser shots Laser intensity

Linear

Reflector mode may also be used

Calibration type Calibration matrix

Delayed Positive Manual 20,000V 92-95% 500-700 nsec 1,000-15,000 Da

Higher values favored Lower values favor peptides of higher m/z This range can be narrowed with subsequent acquisitions

50-100 2,000-5,000 Default External Sinapic acid

Highly variable, depending on age of laser and machine setup Used to create a calibration file User created calibration file Adjust if an alternate matrix is used

The samples outlined herein have been analyzed on a Voyager-DETM STR BioSpectrometer Workstation (Perspective Biosystems). Calibration of the Voyager-DETM is performed with an external calibration of SequazymeTM Peptide Mass Standards Kit Calibration Mixture 3 (Applied Biosystems) that contains bovine insulin (þ1 at 5735.6), E. coli thioredoxin (þ2 at 8476.8; þ1 at 16,952.6), and horse apomyoglobin (þ1 at 11,674.5). From this, an internal calibration file is made in manual calibration mode and applied for sample analysis. Alternately, a custom pool of proteins or chemokines with validated masses can be used for calibration; a minimum of three proteins is suggested. In addition, once the mass of the parent molecule is known, calibration of a given spectra can be adjusted on the basis of validated masses of the full-length chemokine as an internal standard found within the spectra. Spectral data on the Voyager-DETM are obtained with the manufacturer-installed method for myoglobin in linear mode, with modifications as outlined in Table 13.5. With the exception of laser intensity, which depends in part on the age of the laser and the initial equipment setup, most parameters need not be changed to obtain quality spectra. Sample spectra are obtained manually and accepted only in the saturation range of 1  104 to 6  104. If the signal-to-noise ratio is low, the sample

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291

may require cleanup. The most effective method for cleaning a sample once it is spotted on the MALDI plate is to use water. With an equal volume of ice-cold water as the total sample applied (e.g., 1 ml for a 100-spot plate), pipette up and down over the spot several times and then discard the excess solution; allow the sample to air-dry again before reanalysis. The predicted m/z of a chemokine is calculated by Eq. (13.2). Note that the molecular weight is a function of the average masses of the composite amino acids. The obtained m/z will likely differ from the predicted m/z because of isotopic variants error. When properly calibrated, MALDI-TOF accuracy of mass determination is 0.001 to 0.01%. Thus for a protein of 10,000 the error would be less then 10; in practice, we find the error to be <0.0005%. A number of web sites provide estimations of theoretical masses based on the protein sequence, the best of which enable for the input of amino- or carboxy-terminal modifications that result in a change to the amino acid, and correspondingly peptide, molecular weight. One such web site is http://rna.rega.kuleuven.ac.be/masspec/pepcalc.htm.

m Mass þ 1ðchargeÞ ¼ z charge

ð13:2Þ

Chemokine cleavage is evident with MS by comparison of the chemokine control with the chemokine þ enzyme sample; appearance of a peak at an m/z lower than the original chemokine or a complete shift of the m/z indicates chemokine processing (Fig. 13.2). The site of cleavage can be deconvoluted by assignment of the size differential of the chemokine because of the presence of protease to the corresponding amino acid sequence from the chemokine. In Table 13.6 we illustrate this process with potential cleavage products of CCL8 and their theoretical predicted m/z ratios and two actual cleavage products generated by MMP7 cleavage of the chemokine. We use an in-house program, CLIP-PeptID (available for download at our web site www.clip.ubc.ca/resources) that calculates the probability of cleavage sites with the average amino acid masses from an input of the full-length sequence and both predicted and observed masses; these results can be confirmed by N-terminal Edman sequencing of TRIStricine PAGE samples. Note that for N-terminal sequencing, it is critical to use a sample-loading buffer that lacks urea, which modifies proteins. Instead, a sufficient amount of sample for sequencing (generally greater than 5 pM) should be loaded in 4 sample buffer (5% SDS, 15% glycerol, 250 mM TRIS, pH 6.8, and 0.1% bromophenol blue); after electrophoresis the protein is electroblotted to PVDF membrane, because nitrocellulose is not compatible with Edman chemistry, and then stained with Coomassie brilliant blue. The stained bands can then easily be cut out for sequencing. There are occasions in which the processed peak m/z could be due to cleavage of the chemokine in either the N- or C-termini. In these ambiguous

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A

CCL7 (1 − 76) 8953

B 2.0E + 4

50

CCL8 (1 − 76) 8896

2.4E + 4

CCL8 (1 − 73) 8557 CCL8 (1 − 76)

2.5E + 4

100

Relative intensity (%)

Relative intensity (%)

100

50

0

0

C

D CCL7 (5 − 76) 8579

100

4.9E + 4

100

Relative intensity (%)

Relative intensity (%)

8896

50 8781

50

CCL8 (5 − 73) 8146

CCL7 8953

8343

0

0

E

F CCL7 (5 − 76) 8570

2.0E + 4

50

0 7000

100

Relative intensity (%)

Relative intensity (%)

100

7600

8200

8800

9400

Mass-to-charge ratio (m/z)

10,000

CCL8 (1 − 73) 8579

2.0E + 4

50

0 7000

7600

8200

8800

9400

10,000

Mass-to-charge ratio (m/z)

Figure 13.2 Spectra obtained in linear mode by MALDI-TOF MS on aVoyageur-DETM STR of (A) CCL7 and (B) CCL8 after 16 h incubation at 37  C in the absence or presence of a 1:10 molar ratio of the catalytic domains of (C, D) MMP-7 or (E, F)MMP -12. In the presence of enzyme, shifts in molecular weight are evident and the cleavage product, determined by CLIP-PeptID, indicated.

cases, repeating the in vitro cleavage assay in conditions containing heavyoxygen water, namely H218O, can enable identification of the termini involved. Specifically, the amounts of chemokine, protease, and assay buffer are exactly the same as outlined previously, but the extra volume in the 15-ml reaction is made up with highest grade heavy water. The purity of the H218O is critical, given the presence of H216O from the chemokine, enzyme, and buffer stocks that are used in the cleavage assay. During proteolysis, the amino portion of a scissile bond incorporates an oxygen

Table 13.6

Theoretical masses for deconvolution of CCL8 cleavage products generated by MMP7

Sequence

Amino acids

Theoretical mass

QPDSVSIPITCCFNVINRKIPIQRLESYTRITNIQCPKEAVIFKTKRGKEVCADPKERWVRDSMKHLDQIFQNLKP PDSVSIPITCCFNVINRKIPIQRLESYTRITNIQCPKEAVIFKTKRGKEVCADPKERWVRDSMKHLDQIFQNLKP DSVSIPITCCFNVINRKIPIQRLESYTRITNIQCPKEAVIFKTKRGKEVCADPKERWVRDSMKHLDQIFQNLKP SVSIPITCCFNVINRKIPIQRLESYTRITNIQCPKEAVIFKTKRGKEVCADPKERWVRDSMKHLDQIFQNLKP VSIPITCCFNVINRKIPIQRLESYTRITNIQCPKEAVIFKTKRGKEVCADPKERWVRDSMKHLDQIFQNLKP SIPITCCFNVINRKIPIQRLESYTRITNIQCPKEAVIFKTKRGKEVCADPKERWVRDSMKHLDQIFQNLKP IPITCCFNVINRKIPIQRLESYTRITNIQCPKEAVIFKTKRGKEVCADPKERWVRDSMKHLDQIFQNLKP PDSVSIPITCCFNVINRKIPIQRLESYTRITNIQCPKEAVIFKTKRGKEVCADPKERWVRDSMKHLDQIFQNLK DSVSIPITCCFNVINRKIPIQRLESYTRITNIQCPKEAVIFKTKRGKEVCADPKERWVRDSMKHLDQIFQNL SVSIPITCCFNVINRKIPIQRLESYTRITNIQCPKEAVIFKTKRGKEVCADPKERWVRDSMKHLDQIFQN VSIPITCCFNVINRKIPIQRLESYTRITNIQCPKEAVIFKTKRGKEVCADPKERWVRDSMKHLDQIFQN QPDSVSIPITCCFNVINRKIPIQRLESYTRITNIQCPKEAVIFKTKRGKEVCADPKERWVRDSMKHLDQIF QPDSVSIPITCCFNVINRKIPIQRLESYTRITNIQCPKEAVIFKTKRGKEVCADPKERWVRDSMKHLDQIFQ QPDSVSIPITCCFNVINRKIPIQRLESYTRITNIQCPKEAVIFKTKRGKEVCADPKERWVRDSMKHLDQIFQN QPDSVSIPITCCFNVINRKIPIQRLESYTRITNIQCPKEAVIFKTKRGKEVCADPKERWVRDSMKHLDQIFQNL QPDSVSIPITCCFNVINRKIPIQRLESYTRITNIQCPKEAVIFKTKRGKEVCADPKERWVRDSMKHLDQIFQNLK

1-76 2-76 3-76 4-76 5-76 6-76 7-76 2-75 3-74 4-73 5-73 1-71 1-72 1-73 1-74 1-75

8896.4 8786.3 8689.2 8574.1 8487.1 8387.9 8300.9 8689.2 8463.9 8235.7 8148.6 8315.8 8443.9 8558.0 8671.1 8799.3

Obtained m/z

8146

8557

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Amanda E. Starr and Christopher M. Overall

atom (in the form of —OH) from the surrounding water, whereas the carboxy portion incorporates a hydrogen atom. By comparison with the cleavage sample from H216O, an N-terminal cleavage from the H218O sample would have a difference in the m/z of 2, whereas a C-terminal cleavage would show no difference in the m/z. Such reactions are best analyzed by MALDI-TOF MS, where the prominent single charged state produces a 2-m/z shift in the ion peak corresponding to the C-terminal cleavage product. In comparison, with MS after electrospray ionization, the doubly charged state is more common, reducing the MS1 mass shift to 1 Da, which can be ambiguous to identify.

2.5. Detection of processed chemokines by neo-epitope antibodies The capacity of an enzyme to cleave chemokines, and have functional consequences both in vitro and in vivo, suggests a role for this posttranslational modification event in the regulation of chemokine function. Yet, whether this processing truly does occur in vivo has been shown in a limited manner because it requires tools that differentiate between full-length and truncated forms of chemokines. Antibodies raised to the whole chemokine will often recognize both full-length and cleaved forms and so cannot reliably be used to distinguish a cleavage product just 4 or so amino acid residues shorter than the full-length molecule. Similarly, antibodies raised to the N- or C-termini (typically raised with 10- to 18-mer peptides) recognize peptides or protein with an intact N- or C-terminus, respectively. After cleavage, these immunoreactive bands on blots are lost (e.g., McQuibban et al., 2000). However, loss of signal is not unequivocal evidence for proteolysis; gain of signal is preferred. To do this, neo-epitope antibodies can be used (Hughes et al., 1992). Proteolysis is an irreversible modification of protein structure resulting in new N- and C-terminal epitopes termed a neo-epitope; applying this knowledge to create antibodies specific to the new epitope, so called neoepitope antibodies, enables for the unequivocal identification of processed chemokines from in vivo samples (McQuibban et al., 2000). Neo-epitope antibodies are highly specific affinity-purified polyclonal antibodies prepared to recognize the novel N- or C-termini of a protein in which the free amino or carboxyl group, respectively, is an integral part of the antibody recognition site, in this case the new terminus of a protease-truncated chemokine. Such antibodies will not recognize an intact scissile bond in the full-length protein where an amide bond replaces the free termini and, hence, alters potential antibody recognition. To generate neo-epitope antibodies, a peptide based on the short sequence corresponding to the five new terminal residues is used. The peptide must have free N-terminal amino groups, because this replaces the amide bond, which is recognized by the antibody to differentiate the

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295

cleavage product for the full-length chemokine. The use of 5 residues reduces the chance of the antibodies being made to internal sequences that might be recognized in the full-length chemokine. We then incorporate an additional glycine-glycine-cysteine sequence to the carboxyterminal side of the specific sequence; the glycines provide flexibility and act as a spacer, whereas the C-terminal cysteine residue is used for coupling the peptide to keyhole limpet hemocyanin (KLH) for effective immunization, or to chromatography beads for affinity purification of the antibody. Separately, a non-prime side cleavage product can be used to design a neo-epitope antigen corresponding to the new free carboxyl side of the cleavage site on the non-prime side of the scissile bond. As before, we incorporate an N-terminal cysteine-glycine-glycine linked to the five amino acid peptide. Peptide (10 mg) is coupled to 5 mg of KLH overnight in the presence of 0.8 mg succinimidyl 4-(N-Maleimidomethyl) cyclohexane-1-carboxylate (SMCC) to yield 1 ml of coupled KLH-peptide (Table 13.7). For the initial injection, 200 ml corresponding to 200 mg of KLH-peptide is emulsified in 1 ml of complete Freund’s adjuvant and injected at four subcutaneous sites in rabbits, 250 ml each. At this time, a 10-ml blood sample is obtained (anticoagulant-free), allowed to coagulate at 37  C for 1 h and clot contraction at 4  C for 3 h; plasma isolated by centrifugation is stored as a baseline for future enzyme-linked immunosorbent assay (ELISA) assays. Boost injections are prepared as with the initial injection but in incomplete Freund’s adjuvant and are given at 3-to 4-week intervals IM (Table 13.7). Test bleeds are sampled 10 days after injection, and plasma is analyzed by ELISA to the peptide. When ELISA indicates acceptable levels of antibody present (generally OD >1 at serum dilution >700) a full-body bleed is obtained. Antibodies are purified from serum with the peptide coupled to SulfoLink (Pierce Biotechnology), as per the manufacturer’s protocol, through the cysteine of the synthesized peptide. Neo-epitope antibodies can be characterized by Western blot against the truncated chemokine in both absence and presence of DTT. It is also necessary to confirm that only the expected band is detected in a more complex sample before the use of the antibody to evaluate tissue samples in ELISA, Western blot analysis, or immunohistochemistry.

2.6. In vitro functional characterization of proteolysis The functional effects of chemokine proteolysis are evaluated by comparison of full-length synthetic chemokine with a synthesized cleavage analog of the chemokine. If versions of the truncated form of the chemokine cannot be synthesized, it is possible to use the in vitro cleavage product; this will require additional controls in all assays including cleavage buffer, and enzyme alone in cleavage buffer. Alternately, it may be possible to cleanup cleavage product samples with gel filtration or affinity chromatography.

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Table 13.7 Neo-epitope peptide coupling and rabbit immunization

Materials SMCC, Succinimidyl 4-(N-Maleimidomethyl) cyclohexane-1-carboxylate KLH, keyhole limpet hemocyanin, Spin column, Sephadex G10 resin, 4 M guanidine HCl, DMF, dimethyl formamide, DTT, dithiothreitol, PBS, pH 7.5, 10 mg of peptide. Procedure 1. Prepare a spin column with a 1 ml tuberculin syringe with G10 resin hydrated in 4 M GuHCl/PBS. Fill to the rim of the column. 2. Dissolve 0.8 mg SMCC in 30 ml DMF and 5 mg KLH in 1 ml PBS. The KLH never fully dissolves. 3. Add the SMCC to the KLH and stir at room temperature for 30 min. 4. Dissolve 10 mg of peptide in 300 ml 4 M GuHCl/PBS. If the peptide is insoluble, add a little ammonium hydroxide. 5. Add 7 to 7.5 mg DTT to the dissolved peptide. Let stand for 10 min. 6. Gel filtration: the KLH/SMCC should be in the receiving tube. Add the peptide to the column. Centrifuge at 1000 rpm for 3 min. Add 250 ml 4 M GuHCl/PBS. Centrifuge at 1000 rpm for 3 min. 7. Add a mini-stirrer to the mixture, cap, and stir overnight. Peptide

SMCC/KLH

Emulsification with Freund’s adjuvant 1. Connect two sterile glass syringes (with 18-gauge needles) together with a short piece of tubing. 2. For each rabbit add 200 ml coupled peptide to 1 ml Freund’s adjuvant. Use complete Freund’s adjuvant for the initial injection and incomplete Freund’s adjuvant for all boosts. 3. Transfer the mixture back and forth between the syringes at least three times. Be very careful not to stab yourself and wear a face shield. 4. Take the emulsified mixture to the animal facility with the syringes still coupled together and two fresh 18-gauge needles per rabbit. Just before injection reemulsify, disconnect syringes, and inject with one of the syringes with a fresh sterile needle. Immunization schedule 1. Before the first injection have a 10 ml prebleed done (no heparin). 2. Coupled peptide (emulsified with Freund’s complete adjuvant) is injected at 4 sites subcutaneously (1 ml total).

x

Chemokine Proteolysis Detection and Function

297

Table 13.7 (continued)

3. 1st boost at 3-4 weeks. Coupled peptide (emulsified with Freund’s incomplete) is injected at two intramuscular sites. Order a 10-ml test bleed for 10 days after the injections (1 ml total). 4. On the day of the test bleed process the blood as described and do an ELISA on plates coated with the peptide the previous night. If it is a good antibody titer immediately request a ‘‘full body bleed’’. Timing is critical as the maximum antibody production is 10 days after injection. If you delay processing, then your antibody yield will be lower. 5. Second boost is 3 weeks after first boost and is performed exactly as above for first boost. All subsequent boosts are done 3 weeks apart.

We have had success binding chemokines with heparin Sepharose, but the protease-binding capacity needs to be evaluated on an individual basis to determine whether the enzyme and chemokine would elute separately. It is possible to use C18 HPLC to separate protease, cleaved and full-length chemokines, and then refold the denatured chemokine products. However, negative effects in a functional assay can be difficult to interpret as to whether it is due to loss of agonist activity or loss of 3-D structure of the chemokine with commensurate loss of activity. In addition, it may be advisable to preincubate cells with either the full-length or cleaved chemokine before an experiment to confirm the inhibitory effects because of competitive receptor binding or desensitization.

2.7. Transwell migration as an indication of chemotactic potential Chemotaxis is not the sole function of chemokines, yet all chemokines are known to attract one or more cell types through receptor binding and activation. In vitro, transwell migration enables for measurement of the capacity of cells to move toward a stimulus. The types of cells used for a given chemokine in transwell migration assays are based on the expected target receptor expression (Murphy, 2002; Murphy et al., 2000), although proteolytic processing of chemokines is known to cause receptor switching (Vergote et al., 2006), and so alternate cells may necessitate investigation. Both primary cells and cell lines expressing the appropriate receptor can be used for Transwell migration assays, although primary cells may constrain the number conditions assayed because of the number of cells isolated on a given day, and for the less abundant cells (e.g., eosinophils and monocytes) this can be a limiting factor. Chemokine receptor transfected PreB cells are a clean system that provides a definitive result on the effect of chemokine processing toward a single receptor.

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For a limited number of studies commercially available disposable chambers are practical because of their simplicity and reproducibility. However, when doing a large number of assays, reusable 48- or 96-well chambers (Neuroprobe) become more economical but require skill at a number of steps (e.g., loading chemoattractants and cells, laying and removing membrane). When assaying primary cells, a low-volume chamber such as a 48-well microchemotaxis chamber (AP48, Neuroprobe) is advantageous, although is difficult to use effectively. When cell number is less of an issue, a 96-well chemotaxis chamber (A or MB Series, Neuroprobe) is useful, because it is less prone to user error. Chemoattractants, including full-length and truncated chemokine and additional controls such as cleavage assay buffer or enzyme should be diluted in a chemotaxis assay buffer of serum-free RPMI þ BSA (0.1 to 1.0%) at neutral pH. In general, a dose-response curve of cells to a stimulus is parabolic in shape, for example low at 0 nM, peaking at 10 nM, and decreasing to baseline by 1000 nM. Therefore, we start with our stimuli in the range of 0.1 to 100 nM (Fig 13.3). It is critical to include a chemotaxis assay buffer control to establish a baseline for chemokinesis. Primary cells are isolated on the day of use, whereas established cell lines are grown for 2 to 3 days, and maintained at a density below 1  106 cell/ml. Cells are washed and resuspended in chemotaxis assay buffer at 1 to 5  106 cells/ml. The cell number depends on the cells and the chamber used and generally equals 2  105 cells/well; Table 13.8 outlines the general conditions used by our laboratory. The assay should be set up according to the manufacturers protocol, with chemoattractants in the lower chamber separated from the cells in the upper chamber by an appropriately pore-sized membrane. At minimum, samples should be evaluated in quadruplicate. When a reusable apparatus is used, we have found a number of modifications necessary for consistent results. The 48-well lower chamber has a

Chemotactic index

2.5

CCL-7 CCL-7 + MMP-12

2.0 1.5 1.0 0.5 0.01

0.1

1

10

100

Chemokine concentration (nM)

Figure 13.3 Representative chemotactic response of THP-1 cells after a 90-min incubation at 37  C toward CCL7, or chemokine previously cleaved in vitro with MMP-12 to result in a CCL7 (5-76) product.

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Table 13.8 Chemotaxis parameters for various cell types Filter pore size (mm)

Migration time (min)

Cell type

Chamber

Cell number (106 cell/ml)

Peripheral T cell

48-well

5.0

5

180

Peripheral neutrophils Peripheral monocytes

48-well

1.0

3

60

48-well

1.0

5

90

Monocyte cell 96-well line

1.0

5

90

96-well PreB cell receptor transfectants

1.5

5

180

Additional notes

T-cells will require activation before chemotaxis

After aspirating cells, wash with 2 mM EDTA and incubate at 4  C for 20 min. Aspirate and continue with water wash After aspirating cells, wash with 2 mM EDTA and incubate at 4  C for 20 min. Aspirate and continue with water wash

capacity of 25 ml; we add chemokine by rapid ejection with a pipette set to 30 ml but ending at the first stop (not blowing out) to prevent formation of bubbles but ensuring a positive meniscus. Supporting a membrane on both ends with forceps, without touching the chamber, center it over top of the chamber and lay it down gently starting at the middle and then towards

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the two ends—once it has touched the lower chambers it can not be moved. Place the upper chamber on and tighten the screws. Add 50 ml of cells to the upper well again in a rapid motion, ensuring that there is no air bubble between the membrane and cells; if a bubble is created, aspirate the cells out to dryness and try again. The 96-well lower chamber that we use has a capacity of 100 ml but similar to the preceding description, we add chemoattractant with a pipette set to 108 ml. The framed filter is easier to overlay, starting with the frame angled against the chamber on one side and then laying it flat. The prepared chambers are incubated at 37  C in 5% CO2 for the indicated time points, after which cells in the upper chamber are aspirated off, membranes washed, and aspirated (Table 13.8). The chamber is then hit on a surface to detach cells stuck to the lower side of the filter. When opening the chambers, it is useful to place forceps just under the edge of the membrane or frame so that it lifts with the chamber lid to prevent the interwell mixing that can occur otherwise. The filter can be dried and saved for staining. Cells that have migrated into the lower chambers are transferred to a fluorescence 96-well plate for counting with CyQuant (Invitrogen), a fluorescent DNA dye, or a similar dye system. A standard curve of cells ranging from 0 to 50,000 cells per well is also added to the plate to control for linearity. Plates are frozen at
70  C for a minimum of 2 h and then thawed; 200 ml of CyQuant is mixed with the freeze-thaw lysate and fluorescence evaluated by excitation/emission at 485/538. Relative fluorescence of samples is transformed against the fluorescence of the chemotaxis assay buffer (chemokinesis) control to obtain a chemotactic index.

2.8. Intracellular calcium mobilization to evaluate receptor activation Activation of the G-protein–coupled receptor (GPCR), which chemokines bind, causes intracellular signaling cascades that include mobilization of calcium stores from intracellular pools to result in the rapid increase in cytosolic free calcium concentration. There are a number of means of measuring calcium mobilization (Takahashi et al., 1999), although fluorescent indicators are most widely used. Fluo-4 (Invitrogen) is a lipid-soluble ester that is a calcium chelator. The ester-derivative crosses the plasma membrane to enter the cytosol where, once cleaved by esterases, it generates a hydrophilic acid form entrapped within the cell that is Ca2þ sensing. Fluo-4 can be resuspended to 1 mM stock in DMSO and stored at
20  C. Stimulants (in vitro cleavage samples) are resuspended as a 10 stock in assay buffer (Table 13.9) before use. The same cell types as used for the chemotaxis assay should be used for this assay. Cells are resuspended to 1  107 cell/ml in RPMI þ 1% FBS, and loaded with Fluo-4 at a final concentration of 2 mM

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Table 13.9 Calcium mobilization reagents Reagent

Recipe

Notes

1 mM Fluo-4 50 mg Fluo-4 in 45.5 ml DMSO AM 100 mM Dissolve 285 mg in 8 ml water, pH to Probenecid 9-10, and bring volume to 10 ml with water

Store at
20  C for 1 wk Precipitates out of solution below pH 9.0 Store at 4  C

Wash/assay buffer

Store at 4  C

20 mM HEPES 2.5 mM Probenecid 0.1% BSA Made up to 100 ml in Hank’s balanced salt solution

for 30 min at 37  C. Cells are then washed twice gently with assay buffer and resuspended to a final volume of 1  106 cells/ml in assay buffer. Calcium mobilization is evaluated at 37  C on a suitable fluorimeter such as an LS50B with excitation/emission wavelengths of 494/514 nm. With 630 ml of Fluo-loaded cell suspension/cuvette, the emission is evaluated at baseline for 20 sec before addition of 70 ml of stimulus. After 150 sec, 35 ml of 10 mM ionomycin (in DMSO) is added to obtain the Fmax, and then 35 ml of 100 mM EGTA is added to obtain the Fmin. The amount of calcium mobilized is calculated as per Eq. (13.3), given that the Kd of Fluo-4 is 345 (Gee et al., 2000), and F is the value obtained for the stimulant. Examples of expected results for calcium mobilization are shown in Fig. 13.4.



Ca2þ

 free

¼ Kd

ðF
Fmin Þ ðFmax
FÞ

ð13:3Þ

2.9. Binding to glycosaminoglycans The interaction between chemokines and glycosaminoglycans (GAGs) is critical to the formation of the haptotactic gradient that signals for leukocyte migration in infection or disease (Handel et al., 2005; Proudfoot et al., 2003). Proteolysis of chemokines at GAG-binding sites can result in the elimination of a gradient in vivo, and thus loss of a potential TH1 cell response (Cox et al., 2008) or antiinflammatory response ( Johnson et al., 2004, 2005). A number of mechanisms can be used to evaluate the effect of chemokine proteolysis on GAG binding (Proudfoot, 2006), although a heparin Sepharose column in combination with a cation exchange column is a simple and rapid means.

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A

RFU

80

CCL7 100 nM CCL7 50 nM CCL7 10 nM CCL7 1 nM CCL7 100 nM+ MMP-12 CCL7 (5−76) 100 nM

60 40 20 0

B

25

50 75 Time (s)

100

125

60

RFU

50

CCL8 100 nM CCL8 50 nM CCL8 10 nM CCL8 1 nM CCL8 100 nM + MMP-12

40 30 20 0

Ca2 + mobilized (nM)

C

25

50

75

100

125

Time (s)

400

CCL7 CCL7 + MMP-12 CCL8 CCL-8 + MMP-12

300 200 100 0 1

10 Chemokine (nM)

100

Figure 13.4 Representative calcium mobilization tracings from Fluo-4 loaded THP-1 cells obtained from (A) CCL7 or (B) CCL8 at the indicated concentrations and from the chemokines previously cleaved with MMP-12, or with a synthetic analog of the cleavage site. (C) Quantitation of the calcium mobilized with Fmax from ionomycin and Fmin with EDTA.

With 20 ml of in vitro cleavage product, corresponding to 2 mg, diluted 10-fold in 10 mM potassium phosphate, pH 7.5, this is loaded onto a 1 ml HiTrap heparin Sepharose column on an AKTA Purifier. After 10 column volumes of washing, a linear gradient of 0 to 1.5 M NaCl is applied over 30 min at a flow rate of 1.0 ml/min and monitored by inline absorbance at 214 nm. The resulting chromatograms of full-length and truncated

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chemokine can be compared to evaluate the effect of truncation on binding capacity. The experiment should be repeated, substituting a cation exchange column for the heparin column to ensure that observed effects are due to GAG interaction rather than ionic interactions.

3. In Vivo Functional Characterization of Proteolysis 3.1. Chemotaxis in air pouch and peritonitis models The mouse peritoneal cavity and the air pouch provide excellent systems for the validation of biochemical data on the effects of chemokine cleavage. Both models are simple experimental systems that enable for cellular migration to be evaluated, mimicking aspects of an inflammatory response. Furthermore, the simplicity of the models enables for time courses to be completed with reproducible results. In the air pouch model, a pouch is initially created by subcutaneous injection with a 27-gauge needle of 3 ml of 0.22-mm filtered air into the mouse dorsal thorax of an anesthetized mouse. The pouch is reinflated with 2 ml of sterile air at day 3, and by day 5 the pouch has a lining of tissue under the skin containing many resident cells including macrophages (Edwards et al., 1981). Chemokine (5 mg) resuspended in 1 ml of 0.5% carboxy methyl cellulose solution is injected directly into the pouch at day 5 or later depending on the cell type to be evaluated; to analyze endogenous chemokine levels, lipopolysaccharide, carrageenan, or alternative irritants can be injected into the pouch to initiate an inflammatory response (Dawson et al., 1989, 1991). At different times (Sedgwick et al., 1985), the animals are euthanized and the pouch lavaged with 2 ml PBS, with complete exudate being removed enabling for analysis of both the fluid phase and cells. An aliquot of cells can be counted with CyQuant as for the chemotaxis assay; another sample containing 30,000 cells can be used for differential staining of a cytospin (800 rpm, 5 min), and after centrifuging out cells, the remaining lavage fluid can be stored for biochemical analysis including Western blotting. A disadvantage of the air pouch model is that not all chemokines efficiently attract cells into the air pouch (Perretti and Getting, 2003); in these cases the peritonitis model can be used. Because of the high vascularization and proximity of organs, there is a greater risk of blood contamination into samples compared with the air pouch. Furthermore, not all of the exudate will be recovered in this model. Yet, the peritoneal cavity has a high number of resident macrophages and will often produce a cellular response by those chemokines that do not in the air pouch model. With a 27-gauge needle, 0.2 to 2 mg chemokine in sterile PBS to a total volume no greater than 0.5 ml is injected into the intraperitoneum. After 4 to 24 h,

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animals are anesthetized by carbon dioxide before lavage of the cavity. With a 27-gauge needle, 4 ml of PBS is injected IP, the needle removed, and the abdomen gently massaged. By cutting the top layer of skin from the abdomin, a visceral window can be created to ensure removal of lavage fluid without organ damage occurring. As with the air pouch model, cells can be counted and fluid saved for later biochemical analysis. In these models, comparison of the total number of cells obtained from a full-length chemokine versus a truncated counterpart will indicate the chemokinetic capacity of the protein in vivo.

3.2. Subdermal injection An alternative, yet simplistic, approach to evaluate the effect of chemokine cleavage in vivo is by subcutaneous injection. By use of two different sites on each mouse, 500 ng of full-length or truncated chemokine, or a combination of both, in 100 ml of pyrogen-free saline is injected subcutaneously. After 18 h, mice are sacrificed and skin tissue collected and paraffin embedded. Hematoxylin and eosin or immunohistochemistry stained sections can be analyzed to enumerate the infiltrate in each condition (McQuibban et al., 2000).

4. Summary Proteolysis of chemokines is a nonreversible event that modifies the function of the chemokine. It is critical to know the enzymes involved in processing chemokines and the functional effects of these posttranslational modifications to accurately project the function of this in both homeostasis and in disease. The methods presented herein provide researchers with tools to better evaluate the roles of proteolysis in chemokine modification.

ACKNOWLEDGMENTS We are indebted to the great number of trainees that have modified and improved the methods herein. C. M. O. is a Canadian Research Chair in Metalloproteinase Proteomics and Systems Biology and has research grants from the Canadian Institutes of Health Research, the National Cancer Institute of Canada, and a Centre Grant from the Michael Smith Foundation for Health Research (UBC Centre for Blood Research). A. E. S is a Natural Science and Engineering Research Council Canadian Graduate Scholar and a Canadian Institutes of Health Research Strategic Training Fellow, with additional funding support from Michael Smith Foundation for Health Research.

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REFERENCES Ajami, K., Pitman, M. R., Wilson, C. H., Park, J., Menz, R. I., Starr, A. E., Cox, J. H., Abbott, C. A., Overall, C. M., and Gorrell, M. D. (2008). Stromal cell-derived factors 1alpha and 1beta, inflammatory protein-10 and interferon-inducible T cell chemoattractant are novel substrates of dipeptidyl peptidase 8. FEBS Lett. 582, 819–825. Allen, S. J., Crown, S. E., and Handel, T. M. (2007). Chemokine: Receptor structure, interactions, and antagonism. Annu. Rev. Immunol. 25, 787–820. Baysal, C., and Atilgan, A. R. (2001). Elucidating the structural mechanisms for biological activity of the chemokine family. Proteins 43, 150–160. Bickett, D. M., Green, M. D., Berman, J., Dezube, M., Howe, A. S., Brown, P. J., Roth, J. T., and McGeehan, G. M. (1993). A high throughput fluorogenic substrate for interstitial collagenase (MMP-1) and gelatinase (MMP-9). Anal. Biochem. 212, 58–64. Bickett, D. M., Green, M. D., Wagner, C., Roth, J. T., Berman, J., and McGeehan, G. M. (1994). A high throughput fluorogenic substrate for stromelysin (MMP-3). Ann. N. Y. Acad. Sci. 732, 351–355. Blanpain, C., Doranz, B. J., Bondue, A., Govaerts, C., De Leener, A., Vassart, G., Doms, R. W., Proudfoot, A., and Parmentier, M. (2003). The core domain of chemokines binds CCR5 extracellular domains while their amino terminus interacts with the transmembrane helix bundle. J. Biol. Chem. 278, 5179–5187. Clark-Lewis, I., Vo, L., Owen, P., and Anderson, J. (1997). Chemical synthesis, purification, and folding of C-X-C and C-C chemokines. Methods Enzymol. 287, 233–250. Cox, J. H., Dean, R. A., Roberts, C. R., and Overall, C. M. (2008). Matrix metalloproteinase processing of CXCL11/I-TAC results in loss of chemoattractant activity and altered glycosaminoglycan binding. J. Biol. Chem. 283, 19389–19399. Dawson, J., Sedgwick, A. D., Edwards, J. C., and Lees, P. (1989). Lymphocyte kinetics in a murine model of chronic inflammation. Agents Actions 27, 461–464. Dawson, J., Sedgwick, A. D., Edwards, J. C., and Lees, P. (1991). A comparative study of the cellular, exudative and histological responses to carrageenan, dextran and zymosan in the mouse. Int. J. Tissue React. 13, 171–185. Dean, R. A., Cox, J. H., Bellac, C. L., Doucet, A., Starr, A. E., and Overall, C. M. (2008). Macrophage-specific metalloelastase (MMP-12) truncates and inactivates ELR þ CXC chemokines and generates CCL2, -7, -8, and -13 antagonists: Potential role of the macrophage in terminating polymorphonuclear leukocyte influx. Blood 112, 3455–3464. Dean, R. A., and Overall, C. M. (2007). Proteomics discovery of metalloproteinase substrates in the cellular context by iTRAQ labeling reveals a diverse MMP-2 substrate degradome. Mol. Cell Proteomics 6, 611–623. Edwards, J. C., Sedgwick, A. D., and Willoughby, D. A. (1981). The formation of a structure with the features of synovial lining by subcutaneous injection of air: An in vivo tissue culture system. J. Pathol. 134, 147–156. Fernandez, E. J., and Lolis, E. (2002). Structure, function, and inhibition of chemokines. Annu. Rev. Pharmacol. Toxicol. 42, 469–499. Gee, K. R., Brown, K. A., Chen, W. N., Bishop-Stewart, J., Gray, D., and Johnson, I. (2000). Chemical and physiological characterization of fluo-4 Ca(2þ)-indicator dyes. Cell Calcium 27, 97–106. Gong, J. H., and Clark-Lewis, I. (1995). Antagonists of monocyte chemoattractant protein 1 identified by modification of functionally critical NH2-terminal residues. J. Exp. Med. 181, 631–640. Handel, T. M., Johnson, Z., Crown, S. E., Lau, E. K., and Proudfoot, A. E. (2005). Regulation of protein function by glycosaminoglycans—as exemplified by chemokines. Annu. Rev. Biochem. 74, 385–410.

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Henzel, W. J., and Stults, J. T. (2001). Matrix-assisted laser desorption/ionization timeof-flight mass analysis of peptides. Curr. Protoc. Protein Sci. 16, Unit 16 2. Hughes, C. E., Caterson, B., White, R. J., Roughley, P. J., and Mort, J. S. (1992). Monoclonal antibodies recognizing protease-generated neoepitopes from cartilage proteoglycan degradation. Application to studies of human link protein cleavage by stromelysin. J. Biol. Chem. 267, 16011–16014. Jimenez, C. R. (2005). Batch introduction techniques. Methods Enzymol. 405, 36–49. Johnson, Z., Kosco-Vilbois, M. H., Herren, S., Cirillo, R., Muzio, V., Zaratin, P., Carbonatto, M., Mack, M., Smailbegovic, A., Rose, M., Lever, R., Page, C., et al. (2004). Interference with heparin binding and oligomerization creates a novel antiinflammatory strategy targeting the chemokine system. J. Immunol. 173, 5776–5785. Johnson, Z., Proudfoot, A. E., and Handel, T. M. (2005). Interaction of chemokines and glycosaminoglycans: A new twist in the regulation of chemokine function with opportunities for therapeutic intervention. Cytokine Growth Factor Rev. 16, 625–636. McQuibban, G. A., Butler, G. S., Gong, J. H., Bendall, L., Power, C., Clark-Lewis, I., and Overall, C. M. (2001). Matrix metalloproteinase activity inactivates the CXC chemokine stromal cell-derived factor-1. J. Biol. Chem. 276, 43503–43508. McQuibban, G. A., Gong, J. H., Tam, E. M., McCulloch, C. A., Clark-Lewis, I., and Overall, C. M. (2000). Inflammation dampened by gelatinase A cleavage of monocyte chemoattractant protein-3. Science 289, 1202–1206. McQuibban, G. A., Gong, J. H., Wong, J. P., Wallace, J. L., Clark-Lewis, I., and Overall, C. M. (2002). Matrix metalloproteinase processing of monocyte chemoattractant proteins generates CC chemokine receptor antagonists with anti-inflammatory properties in vivo. Blood 100, 1160–1167. Murphy, P. M. (2002). International Union of Pharmacology. XXX. Update on chemokine receptor nomenclature. Pharmacol. Rev. 54, 227–229. Murphy, P. M., Baggiolini, M., Charo, I. F., Hebert, C. A., Horuk, R., Matsushima, K., Miller, L. H., Oppenheim, J. J., and Power, C. A. (2000). International union of pharmacology. XXII. Nomenclature for chemokine receptors. Pharmacol. Rev. 52, 145–176. Overall, C. M., and Sodek, J. (1990). Concanavalin A produces a matrix-degradative phenotype in human fibroblasts. Induction and endogenous activation of collagenase, 72-kDa gelatinase, and Pump-1 is accompanied by the suppression of the tissue inhibitor of matrix metalloproteinases. J. Biol. Chem. 265, 21141–21151. Pease, J. E., Wang, J., Ponath, P. D., and Murphy, P. M. (1998). The N-terminal extracellular segments of the chemokine receptors CCR1 and CCR3 are determinants for MIP1alpha and eotaxin binding, respectively, but a second domain is essential for efficient receptor activation. J. Biol. Chem. 273, 19972–19976. Perretti, M., and Getting, S. J. (2003). Migration of specific leukocyte subsets in response to cytokine or chemokine application in vivo. Methods Mol. Biol. 225, 139–146. Proudfoot, A. E. (2006). The biological relevance of chemokine-proteoglycan interactions. Biochem. Soc. Trans. 34, 422–426. Proudfoot, A. E., Handel, T. M., Johnson, Z., Lau, E. K., LiWang, P., Clark-Lewis, I., Borlat, F., Wells, T. N., and Kosco-Vilbois, M. H. (2003). Glycosaminoglycan binding and oligomerization are essential for the in vivo activity of certain chemokines. Proc. Natl. Acad. Sci. USA 100, 1885–1890. Rappsilber, J., Ishihama, Y., and Mann, M. (2003). Stop and go extraction tips for matrixassisted laser desorption/ionization, nanoelectrospray, and LC/MS sample pretreatment in proteomics. Anal. Chem. 75, 663–670. Sedgwick, A. D., Moore, A. R., Al-Duaij, A. Y., Edwards, J. C., and Willoughby, D. A. (1985). The immune response to pertussis in the 6-day air pouch: A model of chronic synovitis. Br. J. Exp. Pathol. 66, 455–464.

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Strupat, K. (2005). Molecular weight determination of peptides and proteins by ESI and MALDI. Methods Enzymol. 405, 1–36. Takahashi, A., Camacho, P., Lechleiter, J. D., and Herman, B. (1999). Measurement of intracellular calcium. Physiol. Rev. 79, 1089–1125. Tester, A. M., Cox, J. H., Connor, A. R., Starr, A. E., Dean, R. A., Puente, X. S., LopezOtin, C., and Overall, C. M. (2007). LPS responsiveness and neutrophil chemotaxis in vivo require PMN MMP-8 activity. PLoS ONE 2, e312. Vergote, D., Butler, G. S., Ooms, M., Cox, J. H., Silva, C., Hollenberg, M. D., Jhamandas, J. H., Overall, C. M., and Power, C. (2006). Proteolytic processing of SDF-1alpha reveals a change in receptor specificity mediating HIV-associated neurodegeneration. Proc. Natl. Acad. Sci. USA 103, 19182–19187. Wolf, M., Albrecht, S., and Marki, C. (2008). Proteolytic processing of chemokines: Implications in physiological and pathological conditions. Int. J. Biochem. Cell Biol. 40, 1185–1198. Zoffmann, S., Chollet, A., and Galzi, J. L. (2002). Identification of the extracellular loop 2 as the point of interaction between the N terminus of the chemokine MIP-1alpha and its CCR1 receptor. Mol. Pharmacol. 62, 729–736.

C H A P T E R

F O U R T E E N

Real-Time In Vitro Assays For Studying the Role of Chemokines in Lymphocyte Transendothelial Migration Under Physiologic Flow Conditions Ziv Shulman and Ronen Alon Contents 1. Introduction 2. Methods for Investigation of Lymphocyte Crawling and Transendothelial Migration (TEM) Under Shear Flow 2.1. Live imaging microscopy of human T-cell crawling and TEM 2.2. Live imaging of murine T-cell TEM through cytokine-activated murine endothelial cell lines 2.3. Live fluorescence imaging of T-cell crawling and transendothelial migration 2.4. Immunofluorescent staining of integrins, integrin ligands, and cytoskeletal adaptors in crawling and transmigrating T-cells 2.5. Tracking transiently expressed fluorescent-tagged proteins on endothelial cells in real time Acknowledgments References

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Abstract The mechanisms underlying leukocyte migration across endothelial barriers are still largely elusive. Integrin activation by chemokine signals is a key checkpoint in this process. Most of the current knowledge on transendothelial migration (TEM) of leukocytes has been derived from in vitro modified Boyden-chamber transfilter migration assays. In these assays, leukocyte migration toward chemokine gradients established across an endothelial barrier is measured under shear-free conditions. Consequently, these assays do not address the critical contribution of shear forces to dynamic integrin activation and

Department of Immunology, The Weizmann Institute of Science, Rehovot, Israel Methods in Enzymology, Volume 461 ISSN 0076-6879, DOI: 10.1016/S0076-6879(09)05414-7

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2009 Elsevier Inc. All rights reserved.

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redistribution at focal lymphocyte-endothelial contacts. Endothelial chemokines are displayed at high levels on blood vessel walls in vivo and play critical roles in both integrin activation and polarization of leukocytes on blood vessels, yet transwell assays do not assess the role of these chemokines in leukocyte TEM. To overcome these two drawbacks, several laboratories, including our group, developed assays based on in vitro live imaging microscopy to follow leukocyte migration across endothelial barriers that display defined compositions of integrin-stimulatory chemokines. These assays not only successfully simulate physiologic TEM processes but also enable the tracking and dissection of leukocyte adhesion, motility, and crossing of endothelial barriers in real time and under physiologic flow conditions. In addition, fluorescent tagging of membranes, adhesion molecules, and cytoskeletal regulatory elements on the endothelial barrier or the leukocyte can provide key spatial and temporal information on the mode of activity of these elements during distinct stages of leukocyte TEM. After fixation, subcellular changes in the redistribution of these key molecules can be further dissected by immunofluorescence tools and by ultrastructural analysis based on scanning and transmission electron microscopy.

1. Introduction A key checkpoint in leukocyte recruitment to inflammatory targets is their firm arrest on vascular endothelial cells (EC) by means of the activation of specific integrin adhesion molecules and their ability to maintain resistance to detachment by disruptive shear forces during crawling on the luminal surface of the endothelium to sites of diapedesis (Ley et al., 2007; Phillipson et al., 2006; Schenkel et al., 2004; Shulman et al., 2009). Endothelial chemokines are instrumental for these multiple integrin-mediated processes, because lymphocyte integrins require sequential and transient activation signals from endothelial chemokines displayed on the apical luminal aspects of endothelial cells (Laudanna and Alon, 2006). Endothelial chemokines (apical as well as basal) also activate the actin remodeling Rho family GTPases in lymphocytes adhering to the endothelium and, thereby, coordinate actin-dependent protrusions at the leukocyte leading edge, with myosin-dependent release at the leukocyte rear (Ridley et al., 2003; Vicente-Manzanares and Sanchez-Madrid, 2004). Small subsets of lymphocytes (e.g., effector lymphocytes, or blasts stimulated with anti-CD3 and anti-CD28 mAbs or with PHA and expanded in the presence of IL-2) and other leukocytes (e.g., subsets of neutrophils) express activated integrins that can mediate firm adhesion and motility over endothelial ligands even without chemokine or chemoattractant signals (Cinamon et al., 2004; Hogg et al., 2003). Despite the increasing evidence that chemokine-regulated integrin-mediated adhesiveness is a critical checkpoint in physiologic

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transendothelial migration (TEM), traditional motility and TEM assays have been performed under shear-free conditions with transwell chamber assays, in which chemotactic gradients are established across the endothelial barriers (Ding et al., 2000; Roth et al., 1995). These assays were argued to be inadequate for the simulation of physiologic TEM processes, because they did not incorporate the role of integrins, and of integrin adhesiveness under disruptive shear forces, nor did they assess the contribution of apical endothelial chemokines in integrin activation underlying TEM. Over the past few years, alternative in vitro assays were developed and optimized for TEM studies of both resting and effector T-cells (Barreiro et al., 2002; Carman et al., 2003; Millan et al., 2006). These assays have made use of real-time microscopy to track, at a single cell level, the ability of leukocytes to cross over and through activated endothelial monolayers and to monitor subcellular changes both on the leukocyte and on the endothelial surface associated with TEM. Nevertheless, these studies are usually unable to assess the contribution of shear forces exerted on the leukocyte-endothelial interface (Barreiro et al., 2002; Carman et al., 2003, 2007). Furthermore, even when incorporating shear forces into their TEM assays, many studies did not attempt to differentiate between the roles of endothelial-displayed chemokines at distinct stages of leukocyte TEM. Such dissection requires the systematic neutralization of specific chemokine receptors on the investigated subsets of leukocytes (Weber et al., 1999). The large number of potential chemokines endogenously presented by activated endothelial cells (Piali et al., 1998; Rot and von Andrian, 2004; Weber et al., 1999) and the heterogeneity of chemokine receptor expression on different subsets of leukocytes (Rot and von Andrian, 2004) have imposed major difficulties in addressing the multiple roles of chemokines in promoting leukocyte TEM. These obstacles are more pronounced when the investigated leukocyte subset expresses highly activated integrins (e.g., lymphoblasts, subsets of activated neutrophils, and monocytes) that can partially bypass chemokine signals by triggering alternative promigratory integrin-driven cytoskeletal machineries by means of outside-in signaling (Cinamon et al., 2004; Ferreira et al., 2006; Smith et al., 2005). In early studies, we found that on activation with inflammatory cytokines such as TNF-a or IL-1, different ECs, although expressing key vascular adhesion ligands, including E-selectin, VCAM-1, and ICAM-1, are not crossed by adherent primary lymphocytes (Cinamon et al., 2001b), possibly because of a lack of apically displayed chemokines for these lymphocytes. Introduction of such specific integrin-activating chemokines overlaid on the apical endothelial interface not only enhances stable shear resistant adhesions of resting lymphocytes but also promotes their subsequent motility (crawling) over the apical endothelial surface, followed by TEM (Cinamon et al., 2001b; Shulman et al., 2009). Remarkably, under these conditions, shear stress application strongly augments the TEM of both resting and effector T-cells

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(Cinamon et al., 2001b; unpublished results) by means of dynamic activation of integrin-ligand bonds at the lymphocyte-endothelial interface (Astrof et al., 2006; Woolf et al., 2007). Cytokine-activated EC monolayers can also support variable degrees of TEM of neutrophils, monocytes, eosinophils, as well as of highly activated T-cells through the function of endogenous endothelial chemokines (Carman et al., 2003; Cinamon et al., 2004; Cuvelier and Patel, 2001; Weber et al., 1999). These inflammatory chemokines can trigger both adhesion and TEM of effector T-cell subsets under various shear conditions (unpublished results). Nevertheless, it is still difficult to assign the specific contribution of a given chemokine signal to a given step in the TEM process because of the difficulty in quantifying both the density and distribution of chemokines at apical junctional and subluminal compartments (Cuvelier and Patel, 2001; Weber et al., 1999). Attempts to overcome these difficulties have been recently conducted with advanced multiwell flow chamber devices (Schreiber et al., 2007).

2. Methods for Investigation of Lymphocyte Crawling and Transendothelial Migration (TEM) Under Shear Flow 2.1. Live imaging microscopy of human T-cell crawling and TEM This assay is conducted in a parallel-plate flow chamber setup simulating physiologic shear flow conditions and monitors leukocyte interactions with defined endothelial barriers reconstituted with apical chemokines. Human umbilical vein endothelial cells (HUVEC) or another EC type (such as microvascular EC) are stimulated with TNF-a to upregulate both selectins and integrin ligands. The EC can be stimulated with other cytokine cocktails such as IL-4 and IFN-g that induce upregulation of different adhesion molecules repertoire (Bevilacqua, 1993) and promote TEM of various leukocytes subsets (Cuvelier and Patel, 2001). Shear stress is generated with an automated syringe pump attached to the outlet side of the flow chamber, and the entire experiment is recorded with time-lapse microscopy (Fig. 14.1). Some studies have recently made use of various advanced flow chambers in which the endothelial cells are grown on stromal cells (McGettrick et al., 2007). This allows the simulation and tracking of the migratory behavior of leukocytes that have passed the endothelial barrier and engage with subendothelial pericytes and the basement membrane of the EC (Sixt et al., 2001; Wang et al., 2006). Other chambers, which allow introduction of chemokines to the basal side of the endothelial monolayer, can be used to differentiate the function of subluminal chemokines from the role of apical

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Glass syringe Inlet tube Outlet tube

Binding medium reservoir

1 2 3 ^ 4 5 6 > 7 8 9 < * 0 # E

Gasket

Disposable syringe

Programmable syringe pump

Vacuum

Petri dish

Inverted microscope connected to digital camera

Endothelial monolayer

Computerized timelapse recording

Figure 14.1 Scheme of a standard flow chamber set up. A glass dish forming the bottom of the chamber is seeded with EC and placed on an inverted microscope. Leukocytes are perfused through the inlet tube with the syringe pump.The leukocytes flow through the chamber and interact with the endothelial monolayer on the glass bottom dish. Images are acquired using a digital CCD camera and displayed on the computer screen.

endothelial chemokines in leukocyte integrin activation and leukocyte protrusion on and through the endothelial barrier (Schreiber et al., 2007). Both morphologic changes and detailed migratory properties of all leukocytes adhering to the endothelial monolayer can be readily monitored at a single-cell level within the field of view. Real-time tracking of subcellular distribution of adhesion molecules and cytoskeletal regulators of motility can be conducted with fluorescent probes (Barreiro et al., 2002, 2008; Yang et al., 2005). In addition, fluorescence detection of molecules with mAbs and ultrastructural analysis of actively migrating lymphocytes and their endothelial counterparts can be performed on samples fixed at various time points. Digitally recorded segments are analyzed offline either manually or with computerized cell tracking (Cinamon et al., 2001b). In this section the basic assay is described. Other variations (such as fluorescent labeling of migrating T-cells and specific molecules) are explained in detail in the following sections.

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2.1.1. Reagents, cells, and tissue culture Preparation of HUVEC (primary culture, 2 to 4 passages) was reviewed elsewhere (Larrivee and Karsan, 2005). HUVEC or human dermal microvascular endothelial cells (HDMVEC) can also be purchased commercially from companies such as Promocell (Heidelberg, Germany). HUVEC culture medium consists of the following: M-199 (Sigma-Aldrich, St. Louis, MO) supplemented with 10% LPS-free fetal calf serum, penicillin (100 ng/ml), streptomycin (100 U/ml, all from Biological Industries, Israel), endothelial mitogen (Biomedical Technologies Inc, Stoughton, MA), and porcine heparin (Sigma-Aldrich, 5 U/ml). Human plasma fibronectin (FN, Sigma-Aldrich) is dissolved in sterile PBS at 20 mg/ml. Trypsin-EDTA solution is obtained from Sigma-Aldrich. Recombinant human TNF-a is prepared at 2 ng/ml (R&D Systems Inc., Minneapolis, MN). Peripheral blood lymphocytes (PBL) medium consists of RPMI-1640 (Sigma-Aldrich) supplemented with 10% LPS-free fetal calf serum, penicillin (100 ng/ml), streptomycin (100 U/ml), L-glutamine (2 mM ), and sodium pyruvate (1 mM ). Cell-binding medium contains cation-free Hank’s balanced solution (Sigma-Aldrich) supplemented with 10 mM HEPES, pH 7.4, containing 2 mg/ml of bovine serum albumin and 1 mM of Ca2þ and Mg2þ. The medium is maintained at 37  C throughout the assay. Human recombinant CXCL12 or CCL19, purchased from R&D systems (Minneapolis, MN), is dissolved in binding medium at 1 mg/ml. Petri polystyrene dishes, 60  15 mm (Falcon, Franklin Lakes, NJ) are prepared with a 37-mm diameter hole (custom made). A microscope cover glass (#1), 45 mm in diameter (Marienfeld GMBH & Co., Germany), is glued to the bottom of the dish with silicone glue. Nylon wool columns are from NOVAmed ( Jerusalem, Israel). Nontissue culture 6-well plates are obtained from Falcon (Franklin Lakes, NJ). Anti-CD3 (clone, OKT3) and anti-CD28 (clone, CD28.2) are purchased from eBioscience (San Diego, CA). IL-2 is obtained from CHIRON Corporation (Emeryville, CA). Effector medium is similar to PBL medium, with the addition of 50 mM b-mercaptoethanol (SigmaAldrich). Washing solution consists of 10 mM EDTA. 2.1.2. Equipment An inverted microscope with phase-contrast or differential interference contrast (DIC) objectives (e.g., Nikon, Japan) is connected to a high-resolution CCD digital camera (e.g., LIS-700, Applitech, Israel). The system is kept at 37  C. The flow chamber (parallel plate flow chamber kit, GlycoTech, Rockville, MD, gasket thickness 0.01 inch, channel width 2.5 mm, 1/16-inch tubes) is connected to an automated syringe pump (Harvard Apparatus, Natick, MA) and a vacuum pump (MasterFlex, Cole-Palmer Instrument Co., Niles, IL, and see also Fig. 14.1). Other equipment includes a disposable 10-ml plastic syringe, 30-ml glass syringe greased with vacuum silicon grease and connected to a 3-way Luer-Lok (Sigma-Aldrich).

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2.1.3. Procedure 2.1.3.1. Isolation of resting T-cells Human PBLs are isolated from the citrate-anticoagulated whole blood of healthy donors by dextran sedimentation and density separation over Ficoll-Hypaque (Carr et al., 1996). 1. Overlay blood on 12 ml Ficoll in 50-ml tubes and centrifuge at 800g for 30 min without acceleration and breaking of the rotor. 2. Collect the mononuclear phase and wash the cells twice with 50 ml PBS; resuspend cells in PBS containing 5% FCS to a final concentration of 40  106 cells/ml. 3. Load 80  106 cells in 2 ml volume on nylon wool column and incubate for 45 min at room temperature. 4. Elute cells from the column with 8 ml PBS, wash, resuspend in PBL medium, and plate on plastic dish for 2 h to enable monocyte adherence. The resulting PBLs (>90% CD3þ T lymphocytes) should be cultured in PBL medium for 15 to 18 h before use. 5. For isolation of memory CD45ROþ or naı¨ve CD45RAþ population, T-cells should be purified with appropriate negative depletion magnetic beads (e.g., BD Bioscience (San Jose, CA) anti-human CD45RO/RA particles). 2.1.3.2. Preparation of effector T-cells Resting T-cells prepared as described previously can be further activated and expanded to form effector T-cells.

1. Coat 6-well plates (nontissue culture treated) with 2 ml of PBS per well containing 1 mg/ml anti-CD3 and 1 mg/ml anti-CD28 mAbs and incubate for 16 h at 4  C (or for 2 h at 37  C). 2. Wash wells with 3 ml PBS and block with 1% BSA in PBS for 20 min at 37  C. Wash wells with PBS. Wells can be stored for up to 7 days at 4  C. 3. Seed 4  106 freshly isolated lymphocytes in the wells, and incubate for 2 to 3 days at 37  C (in the presence of 5% CO2). 4. Transfer cells to a dish containing 10 ml fresh medium supplemented with 350 U/ml human IL-2. Incubate cells for additional 3 days at 37  C and 5% CO2. 5. Transfer cells to a new dish containing 50 ml fresh medium supplemented with 350 U/ml IL-2. Activated T-cells can be used between 7 and 12 days after initial activation. Dilute cells three times every 3 days in effector medium containing 350 U/ml IL-2. 6. Wash the cells 16 h before the experiment to remove cytokines that can interfere with cell quiescence. Resuspend cells in fresh effector medium containing 350 U/ml IL-2. The resulting effector cells are CD3 positive and include comparable fractions of CD4 and CD8 subsets and variable composition of T-cell subsets.

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2.1.3.3. Preparation and stimulation of EC HUVEC undergoing massive proliferation does not respond efficiently to TNF-a, and thus HUVEC that were maintained in a fully confluent monolayer for 2 to 3 days should be used for TEM assays. HUVEC should be plated on dishes at least 24 h before the planned experiment. This allows the cells to generate a confluent monolayer, and, upon cytokine activation, to acquire the adhesion and junctional molecular repertoire found on inflamed endothelial cells. Each migration assay is performed on a separate HUVEC-containing dish. Similar preparation is used for investigation of crawling and TEM on other endothelial cell types such as HDMVEC.

1. Wipe glass bottom dishes and covers with ethanol on a paper wipe, and air dry under sterile conditions. 2. Add a 15-ml drop of FN to the center of the dish and incubate at 37  C for 1 h. Wash three times with 15 ml PBS (sterile). Avoid dehydration of the FN drop. 3. Harvest HUVEC from a long-term tissue culture plate by addition of trypsin-EDTA solution. Incubate for 2 min. Add 5 ml HUVEC medium and collect cells by gentle pipetting. Wash the cells in HUVEC medium (200g, 4 min). 4. Resuspend the pellet in HUVEC medium, and adjust volume to reach final concentration of 3  106 cells/ml. Add a 15-ml drop of HUVEC to prepared dishes on the coated FN and incubate for 30 min in a humidified incubator. This procedure is designed to minimize the amount of EC required. We have also found that the chamber attaches more tightly to unseeded areas of the dish, thereby maintaining a better vacuum sealing of the chamber. 5. Add 3 ml of HUVEC medium containing 2 ng/ml TNF-a, and incubate at 37  C and 5% CO2 for 18 to 26 h. 2.1.3.4. Measurements of lymphocyte crawling and transendothelial migration under shear flow

1. Place the lower part of a test dish on the stage of an inverted microscope equipped with a 20 phase-contrast objective (see Note 1). The microscope should be equipped with a chamber or a stage with controlled temperature, set to 37  C. Place the flow chamber in the dish. Attach the inlet tube to connect the inlet hole of the chamber to a 50-ml reservoir tube filled with binding medium. Attach the outlet tube to a 3-way Luer-Lok that is connected to the glass syringe of the automated pump. Connect a 10-ml disposable syringe to the third outlet of the lock. Use this syringe to manually pump binding medium through the system. Connect the vacuum pump to the vacuum outlet of the chamber. Pump medium throughout the system. Ensure that the vacuum tightly seals the chamber to the dish. Refer to Fig.14.1 for further clarification.

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2. Disconnect the vacuum and remove the test dish. Place a new dish coated with a HUVEC monolayer on the microscope stage. Locate a field of view on the monolayer. The field should be confluent and located near the upstream edge of the monolayer to minimize leukocyte rolling or crawling into the field of view from upstream fields not recorded. Place the flow chamber over the coated monolayer. Connect the chamber to the pump. Make sure that the chamber is tightly sealed to the dish and no air bubbles are introduced through it. Any air perfused over the HUVEC monolayer will irreversibly damage it. 3. Wash the monolayer with a disposable syringe (Fig. 14.1) containing binding medium. To adsorb a chemokine of interest onto the HUVEC monolayer, perfuse 100 ml of chemokine-containing binding medium introduced with the disposable syringe (see Note 2). The entire volume of medium should enter the chamber, thereby keeping air out. Incubate chemokine for 5 min. Collect the unbound chemokine by backpumping the chemokine-containing medium in the reverse direction with the disposable syringe. Return the inlet tube to the binding medium reservoir and wash the system extensively (at least 2 ml) to remove any traces of soluble chemokine. Effector T-cells do not require addition of exogenous chemokines to the HUVEC (see Note 2). 4. Place 1  106 cultured lymphocytes in a 1.5-ml tube and mix with an equal volume of EDTA solution to remove cell-bound integrin ligands. Wash cells by centrifugation (200g, 4 min) and resuspend pellet in 50 ml binding medium. Pump the lymphocyte suspension until the entire volume enters the inlet tube (Fig. 14.1). Return the inlet to the reservoir containing 50 ml binding medium. Ensure that no air bubbles enter the inlet tube during this manipulation. Set the automated pump to provide a constant shear flow of 5 dyn/cm2 for any required time period. 5. Start recording in real-time mode. Once the cell flux enters to the field of view, stop the pump and immediately activate the preset flow program (see Note 3). Record migration phase at 1 frame/10 sec. 2.1.3.5. Analysis of lymphocyte crawling and TEM Motion analysis should be performed manually on all cells interacting with the endothelial monolayer in the microscopic field of view. Lymphocytes are individually tracked from their site of interaction with the endothelial surface at the end of the accumulation phase and throughout their migration phase (Fig. 14.2). Only leukocytes that have accumulated in the field of view during the accumulation phase are analyzed. Lymphocytes rolling or crawling into the field of view from upstream fields, as well as lymphocytes captured to the EC during the migration phase, should not be included in the analysis. Four distinct categories of accumulating lymphocytes are generally defined in this type of analysis (Fig. 14.2): (1) lymphocytes that roll away or detach from the ECs during the migration phase are considered ‘‘detached’’;

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Flow

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Figure 14.2 Analysis of leukocyte TEM under physiological shear flow in a parallel plate flow chamber assay. This assay analyzes separate steps in the migratory cascade of individual leukocytes interacting with a cytokine-activated EC monolayer under shear flow, in the presence of chemokines reconstituted on the apical surface of the monolayer. To allow leukocytes to accumulate on the monolayer, leukocytes are perfused at low physiological shear flow (accumulation phase, recorded in real-time). The flow is then increased to higher rates, generating shear stresses of interest, which are kept constant throughout the assay (migration phase, recorded in time lapse mode). Motion analysis is performed manually on all adherent cells from their initial point of capture onto the endothelial surface (I) and throughout the entire assay period. Both the morphological changes and migratory patterns of the leukocytes adhering to the endothelial monolayers are monitored at a single cell level. The indicated steps are monitored: I) rolling and arrest; II) detachment from original adhesion site; III) spreading; IV) firm stationary adhesion; V) crawling over the EC; VI) transmigration through the EC. Adapted from Cinamon et al. Nature Immunology, 2001.

(2) lymphocytes that remain stationary throughout the migration phase, or locomote less than their diameter, are considered as ‘‘resist detachment’’; (3) lymphocytes that spread and migrate over the EC surface throughout the assay period without crossing the EC barrier are considered ‘‘crawling’’; (4) lymphocytes that migrate for variable distances on the ECs and eventually transmigrate through the monolayer are considered ‘‘crawling and transmigrating’’. Because lymphocytes (and other leukocytes) may turn dark and be falsely counted as transmigrating cells, only lymphocytes that undergo stepwise darkening of their leading edge and retain their dark images while crawling underneath the ECs, should be considered transmigrating cells (see Section 2.3). The different categories are either presented as a percentage of the originally accumulated lymphocytes or normalized to the number of cells interacting with the EC in the first accumulation phase. Notes 1. We recommend the use of a 20 phase-contrast objective for tracking crawling and TEM in real time. This magnification also allows tracking of both motion and morphologic changes (see analysis section) of a

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reasonable number of leukocytes (40 to 80 cells in a typical field of view). DIC objectives can also be used, but TEM is less prominent with these magnifications. It is, therefore, recommended to label lymphocytes with a fluorescent marker when DIC objectives (see next sections) are used. CCD cameras with a particularly large recording area are suggested (Fig. 14.1). 2. Lymphocyte TEM not only depends on the type of chemokine added but also on its dose. We showed that low levels (less than 0.1 mg/ml) of CXCL12 or CCL19 sufficient for triggering rapid integrin-mediated adhesion strengthening of accumulated lymphocytes is insufficient to trigger their subsequent TEM. Thus, two distinct thresholds of ECbound chemokine levels can be defined: one for adhesion and a higher one for TEM (Cinamon et al., 2001a). Different chemokines may induce TEM at different concentrations because of differences in the efficacy of their immobilization on the endothelial surface. Notably, not all chemokines are adsorbed to the HUVEC monolayers at sufficient levels or with sufficient stability to promote lymphocyte adhesion or TEM. CCL21, a co-ligand of the CCR7 receptor, the major receptor for CCL19 on resting T lymphocytes is only weakly adsorbed to the HUVEC monolayers (unpublished results). Other chemokines for resting or activated T-cells such as IP-10 (CXCL10), MIP-1b (CCL4), and RANTES (CCL5), bind transiently to the HUVEC but are readily washed out during the early phases of the migration assay and can not be assessed for their TEM potential. TNF-a–stimulated HUVEC secrete several chemokines such as CXCL1, CXCL10, CCL2, and CCL5 at levels that are too low to stimulate resting lymphocytes (Weber et al., 1999). These endothelial chemokines can, however, stimulate effector T-cell TEM by means of chemotaxis toward subluminal chemokines (unpublished results). 3. The automated pump program used to study lymphocyte TEM should be set to provide a low shear stress of 0.75 dyn/cm2 for 1 min (accumulation phase, see Fig. 14.2) and then a midrange physiologic shear stress of 5 dyn/cm2 for an additional 15-min period (migration phase, see Fig. 14.2). The geometry of the flow chamber does not enable lymphocytes to accumulate on adhesive endothelial surfaces at this high shear stress; however, once accumulated, lymphocytes remain adhesive and shear resistant for prolonged periods at a very broad range of shear stresses (5 to 20 dyn/cm2). The short accumulation phase is also required to synchronize the leukocyte arrest, such that most of the post arrest events and the subsequent TEM take place within a narrow time window (typically within 6 to 10 min after accumulation of resting lymphocytes, and 2 to 5 min after accumulation of effector lymphocytes). In addition, low shear flow allows selection of a representative fraction of adhesive lymphocytes within the heterogeneous PBL population. Accumulation

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of lymphocytes conducted at too high a shear flow may bias the system toward small highly activated subsets and should be avoided. For control experiments, the lymphocytes can be settled on the endothelial cells and monitored in the absence of shear flow.

2.2. Live imaging of murine T-cell TEM through cytokine-activated murine endothelial cell lines In addition to human leukocytes, many studies use knockout mice to dissect the role of cytoskeletal effectors and integrin regulatory machineries in leukocytes TEM across murine endothelial barriers (Shimonaka et al., 2003; Zhang et al., 2006). We, therefore, developed a transendothelial assay with murine spleen–derived lymphocytes and cytokine-stimulated murine endothelial cell lines (immortalized). Resting spleen T-cells express functional LFA-1, VLA-4, and a4b7 (Luster et al., 2005) and use CCR7, the receptor for CCL21 and CCL19, rather than the ubiquitous CXCR4 as their primary chemokine receptor (Shulman et al., 2006). We have used the brain-derived EC line, b.End3 as our primary substrate, because on cytokine activation, it is induced to express P- and E-selectin and all key integrin ligands (including MadCAM-1 [Sikorski et al., 1993]). As found for human T-cells and human EC monolayers, the TEM of T-splenocytes across b. End3 also requires apical chemokines signals and application of shear flow on adherent lymphocytes (unpublished results). 2.2.1. Reagents, cells, and tissue culture BEnd.3 cells are described elsewhere (Sikorski et al., 1993). BEnd.3 culture medium consists of the following: RMPI (Sigma-Aldrich) supplemented with 10% LPS-free fetal calf serum, penicillin, and streptomycin (all from Biomedical Technologies Inc.). C57B1/6 mice (Harlan, Israel), cell strainer (Falcon, Franklin Lakes, NJ), negative cell isolation CD3þ kit (MACS, Milteny Biotec, Germany). Murine TNF-a and CCL21 are both from R&D Systems Inc. (Minneapolis, MN). Red blood cell–lysing buffer is from Sigma-Aldrich. Murine spleen–derived T-cells are cultured in PBL medium. 2.2.2. Procedure 2.2.2.1. Isolation and preparation of murine T-splenocytes 1. Dissect splenocytes from spleens of 4- to 10-week-old mice. Spleens should be rubbed through a cell strainer, removed to a 15-ml tube, and centrifuged at 200g for 5 min. Resuspend cells in 1 ml red blood cell– lysing buffer and incubate for 4 min. Add 10 ml PBS and centrifuge (200g, 5 min).

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2. Resuspend cells and culture overnight in the same medium used for culturing human PBL. Separate T-cells with magnetic beads by negative selection according to the manufacturer’s instructions and incubate for additional 2 h to enable recovery. It is not recommended to use beadisolated T-cells from spleens immediately after separation, because they are less reactive to chemokines. 2.2.2.2. Preparation and stimulation of bEnd.3 cells BEnd.3 cells must be kept fully confluent for 2 to 3 days, harvested, and plated on dishes at least 24 h before the planned experiment, as described for HUVEC. Plate bEnd.3 cells at confluence on FN spots (20 mg/ml in PBS) as described for HUVEC and stimulate them for 24 h with murine TNF-a (10 ng/ml). 2.2.2.3. Crawling and transendothelial migration assay under shear flow The flow chamber setup used for studies of T-splenocyte migration through bEnd.3 is identical to that described for human lymphocytes; 2 mg/ ml murine CCL21 is overlaid on the bEnd.3 monolayer as described for HUVEC. T-splenocytes generally adhere less efficiently to activated bEnd.3 than human T-cells on HUVEC, and, therefore, the shear flow used for the accumulation and migration phases must be adjusted accordingly.

2.3. Live fluorescence imaging of T-cell crawling and transendothelial migration Phase-contrast objectives allow good detection of leukocyte TEM. This is based on the finding that the leading edge of the transmigrating leukocyte changes gradually from white to dark as this large protrusion extends underneath the endothelial barrier (Cinamon et al., 2001a). To observe further details of the morphologic changes of the leading edge, as well as of the uropod of both crawling and transmigrating leukocytes, the cells can be labeled with inert fluorescent dyes. This approach also allows enhanced differentiation between apical and subluminal leading edges generated by crawling and transmigrating leukocytes, respectively. Fluorescent labeling also greatly facilitates computerized tracking of the migrating leukocytes. Several dyes are available for tracking migrating lymphocytes, each with distinct phototoxic side effects. For instance, DiD (1,10 -dioctadecyl3,3,30 ,30 -tetramethylindodicarbocyanine perchlorate or its analogs) is incorporated into both the plasma membrane and the internal cell membranes and allows visualization of small protrusive projections of the labeled leukocyte underneath the EC barrier, invisible by standard DIC light microscopy (Shulman et al., 2009). Because this dye is highly phototoxic in leukocytes, it should be used at minimal concentrations with minimal exposure to fluorescent light. Cell Tracker Orange CMTMR is a

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membrane permeant global tracer with lower phototoxic side effects than common DiD derivatives. Another dye with negligible phototoxicity is BCECF-AM (20 ,70 -bis(carboxyethyl)-4(or 5)-carboxyfluorescein diacetoxymethyl ester) (Woolf et al., 2007), a membrane-permeable substrate for cytosolic esterases, which is retained in live cells after being intracellularly hydrolyzed. This dye is, therefore, the preferred option for tracking lymphocyte motility and TEM at high resolution, especially by DIC microscopy. 2.3.1. Reagents DiD, Cell tracker Orange-CMTMR, and BCECF-AM are all obtained from Invitrogen (Carlsbad, CA). 2.3.2. Procedure 1. Wash cells in EDTA solution and resuspend in PBS containing either DiD (4 mg/ml, 30 min), CMTMR (1 mM, 20 min), or BCECF-AM (1 mM, 2 min). Wash cells twice before introduction to the flow assay. CMTMR-labeled cells must be incubated for an additional 30 min in medium before use in the assay to remove excess dye. 2. Track cells for 15 to 20 min at rates of 4 to 6 frames/min. Higher acquisition rates can induce phototoxicity and should be avoided. To minimize phototoxicity, the fluorescence excitation exposure should be adjusted to the minimal level required for signal detection.

2.4. Immunofluorescent staining of integrins, integrin ligands, and cytoskeletal adaptors in crawling and transmigrating T-cells Subcellular spatiotemporal analysis of integrins has been recently tested with three approaches: live imaging of leukocytes transiently transfected with integrins fused to green fluorescent protein such as EGFP (Katagiri et al., 2006; Kim et al., 2003, 2004); live imaging of leukocytes pretreated with nonblocking fluorescent anti-integrin mAbs (Shaw et al., 2004; Smith et al., 2005); and postfixation staining at various time points after leukocyte arrest during spreading, crawling, and endothelial crossing (Carman et al., 2003; Morin et al., 2008). GFP fused to the short LFA-1 tail can interfere with the integrin distribution, because it is often retained at the rear of motile T-cells, in sharp contrast to the distribution of endogenous LFA-1 (unpublished results). Live imaging with nonblocking mAbs allows tracking of both VLA4 and LFA-1 in motile lymphocytes (Smith et al., 2005; Woolf et al., 2007), as well as in other leukocytes (Shaw et al., 2004). In some cases, these mAbs can cluster their integrin targets, leading to artificial enrichment of the mAb at particular cellular compartments (Smith et al., 2005; unpublished results).

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We, therefore, recommend imaging integrin distribution after mild postfixation staining with appropriate mAbs (see Note 1), despite the inability of this method to capture the temporal dynamic changes of integrin redistribution in motile leukocytes. Further processing of the acquired images by deconvolution enhances the fluorescent signals and allows detection of microclustering in specific compartments of the T-cells visualized by DIC microscopy (see Note 2). Permeabilization of the cells allows further analysis of their cytoskeletal integrin partners and associated adaptors and kinases (Shulman et al., 2009) (see Note 3). DIC and fluorescence microscopy offer limited spatial resolution, and thus imaging of cellular structures smaller than 400 nm becomes increasingly difficult. Electron microscopy allows ultrastructural analysis of leukocyte protrusions into the endothelial cells both in vivo and in vitro (Carman et al., 2007; Marchesi, 1961; Shulman et al., 2009) (see Note 4). 2.4.1. Reagents Paraformaldehyde is obtained from MERCK (Darmstadt, Germany). Sucrose, TRIS buffer solution (TBS, 25 mM TRIS, pH 7.4, 150 mM NaCl), saponin, and blocking serum are all from Sigma-Aldrich. Liquid blocker pap pen (a water-repellant marking pen) is obtained from Daido Sangyo Co. (Tokyo, Japan). 2.4.2. Procedure 1. Perfuse fixative solution through the chamber at desired time points during the flow assay. This is achieved by transferring the inlet tube from the binding medium reservoir to a tube containing 4% paraformaldehyde and 2% sucrose in PBS at 37  C. Once the perfused fixative reaches the chamber, the fixative must be continuously perfused for an additional 5 min. 2. Disconnect the chamber from the vacuum and carefully separate it from the glass-bottom dish that is taken for further processing. Wash the chamber extensively to remove all traces of fixative before the following run. If the fixation is to be performed under shear-free conditions, then after the assay is stopped, quickly and carefully remove the chamber and immediately incubate the dish with fixative. After fixation the samples are extensively washed three times with PBS and can be kept in 4  C until further processing. 3. Discard PBS and mark a circle around the cells with a liquid blocker pap pen. This procedure dramatically reduces the volumes of the solutions subsequently required to stain the fixed sample. Block samples with 50 ml TBS supplemented with the corresponding serum (20%) for 20 min at 37  C. 4. Remove the serum without washing and incubate the samples for 45 min, at 37  C with 30 to 50ml of TBS containing either unlabeled or directly labeled primary antibodies. Wash cells with 3 ml TBS for 5 min at least three times.

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5. If necessary, incubate the cells with a secondary antibody for an additional 30 min at room temperature. Wash cells in TBS five times for 5 min. 6. For costaining of intracellular molecules and membranal integrins, permeabilize the fixed cells with 0.1% saponin for 5 min. All of the solutions subsequently used must contain 0.05% saponin (see Note 3). After permeabilization, block cells with 10% serum in TBS/saponin. Incubate cells with primary and secondary antibodies, as described previously. 7. Wash cells five times with 3 ml TBS/saponin for 5 min followed by two washes with saponin-free TBS. Add 20% relevant serum in PBS for 10 min to quench both saponin activity and the nonspecific binding of secondary antibodies. 8. Image fixed cells with either confocal or wide-field fluorescence microscopy. To detect microclustering of integrins, use an oil 60/1.4 PlanApo (DIC) objective (see Note 2). We performed postfixation immunofluorescence staining of transmigrating T-cells with antiICAM-1-PE and anti-LFA-1-Alexa-488 mAbs and analyzed the resulting images with the SoftWoRx software (Applied Precision). With this approach, we could detect ICAM-1 and LFA-1 rings surrounding actively transmigrating T-cells (Fig. 14.3) as previously described for neutrophils (Shaw et al., 2004). Notes 1. To visualize functional LFA-1 subsets occupied by endothelial ICAM-1, standard LFA-1, or ICAM-1, blocking mAbs cannot be used for fluorescence imaging because their binding sites are already occupied by ligand. The anti-aL, TS2/4 mAb (Shaw et al., 2004), and the anti-a4, B5G10 (Kamata et al., 1995), are both nonblocking mAbs that efficiently stain

Figure 14.3 T-cells transmigrating throughTNF-a activated endothelium form LFA-1 and ICAM-1 rings.T-cells transmigrating through activated HUVEC under shear flow, overlaid with CXCL12 were fixed after several mins and stained with anti-LFA-1Alexa-488 (clone, TS2/4, green), and anti-ICAM-1-PE (clone, HA58, red). Fluorescent z-stack image sections were subjected to digital deconvolution. Scale bar represents 3mm. An ICAM-1 ring overlapping with an LFA-1 ring is formed around transmigrating T-cells.

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both ligand-free and ligand-occupied integrins at high efficiency. Nonblocking mAbs that recognize fixation-insensitive neoepitopes associated with high-affinity integrin conformational states can also be used. 2. DIC allows high-quality imaging of morphologic changes in cell shape (such as leading edge and trailing edge) and, thus, is preferred over regular phase-contrast microscopy when analyzing fixed cells. Combined with fluorescence microscopy, images can be acquired as z-stack sections (4- to 6-mm thick and 0.2 mm apart). To reduce background noise and enhance the fluorescent signal, the z-stack sections should be subjected to digital deconvolution. For example, we use the SoftWoRx software (Applied Precision) for deconvolution processing. 3. Permeabilization of cells with Triton X-100 severely damages the outer cell membrane. Saponin is a reversible cholesterol chelator that disrupts cellular membranes more gently and is preferred over Triton X-100. To minimize disruption of membranal proteins and to avoid nonspecific mAb staining in the cytosol, cells should be first permeabilized, stained for the cytoplasmic molecules of interest, and subsequently washed and incubated in serum to remove the saponin. The membrane integrity is largely restored after saponin removal, allowing the conservation of membranal and cortical cytoskeletal complexes associated with cell surface integrins. 4. Fixed samples can be processed for transmission electron microscopy (EM) or scanning EM as described (Carman et al., 2007; Cinamon et al., 2001b; Shulman et al., 2009). Transmission EM is a more complex method that requires sampling numerous thin sections cut through individual lymphocytes and endothelial cells. The major advantage offered by transmission EM is the ability to probe the direct interface between two adherent cells (e.g., the bottom of a lymphocyte crawling on an endothelial cell). Another advantage of this tool is the ability to combine ultrastructural analysis of cellular membranes with immunolabeling of specific molecules of interest (e.g., by immunogold labeling). Scanning EM imaging of large fields of view is highly recommended as a first stage of any ultrastructural analysis of leukocyte TEM. A scanning EM image of a T-cell crossing cytokine-stimulated HUVEC through a paracellular route (TEM between two opposing ECs) is shown in Fig. 14.4.

2.5. Tracking transiently expressed fluorescent-tagged proteins on endothelial cells in real time Adherent and migrating leukocytes induce redistribution of multiple endothelial molecules during their crawling and TEM. These include both ligands occupied by adhesion and costimulatory receptors on the migrating leukocytes (e.g., ICAM-1, VCAM-1, and PECAM-1 [Barreiro et al., 2002, 2008;

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Figure 14.4 Scanning electron micrograph of a T-cell undergoing paracellular TEM. T-cells undergoing TEM through TNF-a-activated HUVEC bearing CXCL12 were fixed after 3 min and processed for scanning EM. An image of a T-cell crossing the EC monolayer through endothelial junction is shown. Scale bar represents 3 mm.

Carman et al., 2003; Mamdouh et al., 2003]), as well as junctional molecules not directly occupied by the transmigrating leukocyte (e.g., VE-cadherin [Alcaide et al., 2008; Shaw et al., 2001]). Labeling of these molecules with nonblocking fluorescently tagged mAbs or mAb fragments has been successfully implemented in in vitro imaging of monocyte and neutrophil TEM. Because this approach may also perturb signaling pathways of these molecules, it should be used with caution. Alternative, fluorescent fusion proteins of these endothelial ligands retain their distribution, cytoskeletal associations, and signaling activities, although the ability of these fusion molecules to also recycle between endocytic compartments has not been systematically verified (Barreiro et al., 2002, 2008; van Buul et al., 2007; Yang et al., 2005; Shulman et al., 2009). 2.5.1. Reagents Plasmid of interest (e.g., ICAM-1-GFP), HUVEC transfection kit (e.g., AMAXA, Gaithersburg, MD) and electroporator device (e.g., AMAXA). 2.5.2. Procedure 1. Transfer trypsinized HUVEC to a 15-ml tube and centrifuge at 200g for 4 min. Resuspend HUVEC in 100 ml Nucleofactor solution (AMAXA) supplemented with 5 mg plasmid, and transfer to an AMAXA cuvette. Electroporation is performed according to the manufacturer’s instructions. 2. Transfer cells to a 6-well plate containing fresh medium for recovery. Global transfection is not required, because regions within the HUVEC monolayer enriched for the ectopically expressed fluorescent molecule can be chosen after the dish is set on the microscope stage (see following).

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3. After 16 h posttransfection, replate trypsinized HUVEC on glass dishes as described previously. HUVEC should then be stimulated with TNF-a or other cytokines for 18 to 26 h. 4. Image the cells with fluorescent microscope (e.g., DeltaVision system, Delta Vision Spectris RT, Applied Precisions, Issaquah, WA) equipped with 40/0.95 or 20/0.7 NA PlanApo DIC objective and motorized stage that allows recordings of multiple fields of view with high spatial precision. Before lymphocyte perfusion, choose HUVEC fields expressing high levels of the fluorescent protein of interest and set the computerized stage for cyclic tracking of these HUVEC fields. Set the excitation intensity and exposure time to minimum to reduce phototoxicity. A T-cell transmigrating through HUVEC transfected with ICAM1-GFP, monitored during active transendothelial migration by time-lapse microscopy, is depicted in Fig. 14.5.

DIC ICAM-1-GFP

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Figure 14.5 Dynamics of an ICAM-1-GFP ring rearranged by transmigrating T-cell. Time lapse images of a representative T-cell transmigrating under shear flow through TNF-a-activated HUVEC transiently expressing ICAM-1-GFP and bearing CXCL12. Right panels depict ICAM-1-GFP fluorescent images. Left panels depict DIC images in blue, overlaid with the corresponding fluorescent images. A short lived ICAM-1-GFP ring is formed by the transmigrating T-cell as it crosses through the HUVEC. Scale bar represents 10 mm.Time is shown in min.

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ACKNOWLEDGMENTS We thank S. Schwarzbaum for editorial assistance and Drs. O. Barreiro (University Autonoma, Madrid) and Sara Feigelson for helpful suggestions. R. A. is the Incumbent of The Linda Jacobs Chair in Immune and Stem Cell Research. R. A. is supported by the Israel Science Foundation, the Minerva Foundation, Germany, and by MAIN, the EU6 Program for Migration and Inflammation.

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Shaw, S. K., Bamba, P. S., Perkins, B. N., and Luscinskas, F. W. (2001). Real-time imaging of vascular endothelial-cadherin during leukocyte transmigration across endothelium. J. Immunol. 167, 2323–2330. Shaw, S. K., Ma, S., Kim, M. B., Rao, R. M., Hartman, C. U., Froio, R. M., Yang, L., Jones, T., Liu, Y., Nusrat, A., Parkos, C. A., and Luscinskas, F. W. (2004). Coordinated redistribution of leukocyte LFA-1 and endothelial cell ICAM-1 accompany neutrophil transmigration. J. Exp. Med. 200, 1571–1580. Shimonaka, M., Katagiri, K., Nakayama, T., Fujita, N., Tsuruo, T., Yoshie, O., and Kinashi, T. (2003). Rap1 translates chemokine signals to integrin activation, cell polarization, and motility across vascular endothelium under flow. J. Cell Biol. 161, 417–427. Shulman, Z., Shinder, V., Klein, E., Grabovsky, V., Yeger, O., Montresor, A., Bolomini-Vittori, M., Feigelson, S. W., Kirchhausen, T., Laudanna, C., Shakhar, G., and Alon, R. (2009). Lymphocyte crawling and transendothelial migration require chemokine triggering of high affinity LFA-1 integrin. Immunity 30, 384–396. Shulman, Z., Pasvolsky, R., Woolf, E., Grabovsky, V., Feigelson, S. W., Erez, N., Fukui, Y., and Alon, R. (2006). DOCK2 regulates chemokine-triggered lateral lymphocyte motility but not transendothelial migration. Blood 108, 2150–2158. Sikorski, E. E., Hallmann, R., Berg, E. L., and Butcher, E. C. (1993). The Peyer’s patch high endothelial receptor for lymphocytes, the mucosal vascular addressin, is induced on a murine endothelial cell line by tumor necrosis factor-alpha and IL-1. J. Immunol. 151, 5239–5250. Sixt, M., Engelhardt, B., Pausch, F., Hallmann, R., Wendler, O., and Sorokin, L. M. (2001). Endothelial cell laminin isoforms, laminins 8 and 10, play decisive roles in T cell recruitment across the blood-brain barrier in experimental autoimmune encephalomyelitis. J. Cell Biol. 153, 933–946. Smith, A., Carrasco, Y. R., Stanley, P., Kieffer, N., Batista, F. D., and Hogg, N. (2005). A talin-dependent LFA-1 focal zone is formed by rapidly migrating T lymphocytes. J. Cell Biol. 170, 141–151. van Buul, J. D., Allingham, M. J., Samson, T., Meller, J., Boulter, E., Garcia-Mata, R., and Burridge, K. (2007). RhoG regulates endothelial apical cup assembly downstream from ICAM1 engagement and is involved in leukocyte trans-endothelial migration. J. Cell Biol. 178, 1279–1293. Vicente-Manzanares, M., and Sanchez-Madrid, F. (2004). Role of the cytoskeleton during leukocyte responses. Nat. Rev. Immunol. 4, 1–14. Wang, S., Voisin, M. B., Larbi, K. Y., Dangerfield, J., Scheiermann, C., Tran, M., Maxwell, P. H., Sorokin, L., and Nourshargh, S. (2006). Venular basement membranes contain specific matrix protein low expression regions that act as exit points for emigrating neutrophils. J. Exp. Med. 203, 1519–1532. Weber, K. S., von Hundelshausen, P., Clark-Lewis, I., Weber, P. C., and Weber, C. (1999). Differential immobilization and hierarchical involvement of chemokines in monocyte arrest and transmigration on inflamed endothelium in shear flow. Eur. J. Immunol. 29, 700–712. Woolf, E., Grigorova, I., Sagiv, A., Grabovsky, V., Feigelson, S. W., Shulman, Z., Hartmann, T., Sixt, M., Cyster, J. G., and Alon, R. (2007). Lymph node chemokines promote sustained T lymphocyte motility without triggering stable integrin adhesiveness in the absence of shear forces. Nat. Immunol. 8, 1076–1085. Yang, L., Froio, R. M., Sciuto, T., Dvorak, A. M., Alon, R., and Luscinskas, F. W. (2005). ICAM-1 regulates neutrophil adhesion and transcellular migration of TNF-alphaactivated vascular endothelium under flow. Blood 106, 584–592. Zhang, H., Schaff, U. Y., Green, C. E., Chen, H., Sarantos, M. R., Hu, Y., Wara, D., Simon, S. I., and Lowell, C. A. (2006). Impaired integrin-dependent function in WiskottAldrich syndrome protein-deficient murine and human neutrophils. Immunity 25, 285–295.

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F I F T E E N

A Microfluidics-Based Method for Analyzing Leukocyte Migration to Chemoattractant Gradients Francis Lin*,†,‡ Contents 334

1. Introduction 1.1. Chemoattractants, chemoattractant receptors, and leukocyte trafficking 1.2. Conventional methods for analyzing leukocyte migration and chemotaxis 1.3. Microfluidic devices for cell migration research 2. Preparation of Microfluidic Devices 2.1. Design of microfluidic devices 2.2. Fabrication of microfluidic devices 2.3. Substrate preparation 3. Generation of Chemoattractant Gradients 3.1. Principle of microfluidic gradient generation 3.2. Measurement of chemoattractant gradients in microfluidic devices 4. Preparation of Cells 4.1. Isolation of human blood leukocytes 4.2. Purification, differentiation, and characterizations of leukocyte subpopulations 5. Experimental Setup 5.1. Assembly of microfluidic system 5.2. Environmental controls 5.3. Cell loading 5.4. Time-lapse optical microscopy 6. Data Analysis 6.1. Image processing and cell tracking

* {

{

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Laboratory of Immunology and Vascular Biology, Department of Pathology, School of Medicine, Stanford University, Stanford, California, USA Center for Molecular Biology and Medicine, Veterans Affairs Palo Alto Health Care System, Palo Alto, California, USA Department of Physics and Astronomy, University of Manitoba, Winnipeg, Manitoba, Canada

Methods in Enzymology, Volume 461 ISSN 0076-6879, DOI: 10.1016/S0076-6879(09)05415-9

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2009 Elsevier Inc. All rights reserved.

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6.2. Characterizations of cell orientation 6.3. Characterizations of cell motility 6.4. Characterizations of persistent migration and chemotaxis 6.5. Subregion analysis 7. Conclusion Acknowledgments References

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Abstract Leukocyte trafficking in tissues mediates cellular immune responses and can be directed by chemotactic factors such as chemokines. Understanding chemotactic responses of leukocytes to chemoattractant gradients is of great interest and importance to both basic science and clinical research. Conventional methods for studying leukocyte migration and chemotaxis generally lack the ability to maintain and manipulate gradient profiles. In contrast, microfluidic devices can generate well-defined stable chemical gradients and can precisely modify gradient conditions in space and time. Previously, microfluidic gradientgenerating devices have been used to investigate various aspects of leukocyte migration in different chemoattractant fields with the focus on human blood neutrophils. Recently, chemotaxis of human blood T cells in chemokine gradients was successfully demonstrated in a microfluidic device. In this chapter, the detailed method of analyzing the migration of human blood neutrophils and T cells in chemoattractant gradients with microfluidic devices is described.

1. Introduction 1.1. Chemoattractants, chemoattractant receptors, and leukocyte trafficking Leukocytes respond to various chemotactic factors such as chemokines, and such chemotactic responses mediate leukocyte trafficking in tissues (Kubes, 2002). Particularly, chemokine families represent a unique and important class of attractant molecules. Chemokine-mediated leukocyte homing is highly subset selective depending on the chemokine/receptor pairs expressed by specific tissues and cell populations (Baggiolini, 1998; Campbell and Butcher, 2000). Because circulating peripheral blood leukocytes express various chemoattractant receptors, they provide rich and diverse cell sources for experimental studies of leukocyte migration and chemotaxis in vitro.

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1.2. Conventional methods for analyzing leukocyte migration and chemotaxis Commonly used conventional cell migration assays include transwell assay or Boyden chamber, under agarose assay, micropipette-based assay, Zigmond chamber, and Dunn chamber (Boyden, 1962; Lohof et al., 1992; Nelson, 1975; Zicha et al., 1997; Zigmond, 1977). These macroscale size assays generate chemical gradients by free diffusion of attractant molecules in medium and generally lack the ability of maintaining stable gradient and precisely manipulating gradient profiles. Particularly, as one of the most broadly used chemotaxis assays in biology and immunology research, transwell assay is further limited by its requirement of large input cell number and the inability of visualizing cell movement in real time. Despite these limitations, transwell assay is useful for high-throughput evaluation of leukocyte migration to different chemoattractants and for post-assay flow cytometric analysis to identify different subsets of migrated cells.

1.3. Microfluidic devices for cell migration research Microfluidic gradient-generating devices have advantages over conventional cell migration assays for microenvironmental control and miniaturization and allow real-time visualization of cell movement. The main class of microfluidic gradient generator is based on controlled chemical mixing of laminar flows in the microfluidic channels (Lin et al., 2008). This method allows configuration of stable chemical gradient with simple or complex shapes. In addition, several strategies have been developed to dynamically vary gradient profiles over time (Irimia et al., 2006; Lin et al., 2004b). Over the past decade, the microfluidics-based approach has developed a growing interest in the cell migration community and is becoming an enabling tool for single-cell–based quantitative analysis of cell migration and chemotaxis. Several studies have characterized the migration of human blood neutrophils in simple and complex gradients of chemokine IL-8 ( Jeon et al., 2002; Lin et al., 2004a). In addition, microfluidic devices have been used to study the chemorepulsive response of neutrophils to high-dose IL-8 gradients (Tharp et al., 2006). Taking advantage of microfluidic devices for dynamically varying gradient profiles, neutrophil migration in response to fastswitching IL-8 gradient was investigated (Irimia et al., 2006). Furthermore, microfluidic devices were used to quantitatively study the interactions of competing gradients of chemokine IL-8 and lipid product LTB4 in directing neutrophil migration (Lin et al., 2005). Recently, chemotaxis of human blood T cells to gradients of chemokine CCL19 and CXCL12 in microfluidic devices was demonstrated as well (Lin and Butcher, 2006). Because of the unique features of microfluidic devices for manipulating gradients and its increasing use in studying cell migration, I describe here the method

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of the use of flow-based microfluidic systems for analyzing leukocyte migration in chemoattractant gradients. The focus of the chapter is to provide the guidelines to help other scientists effectively use the microfluidics-based method for their research toward a better understanding of leukocyte migration and trafficking.

2. Preparation of Microfluidic Devices 2.1. Design of microfluidic devices The flow-based microfluidic gradient-generating devices, either a ‘‘Y’’type device or a network device, are designed with specialized computer programs such as Freehand (Macromedia, CA) and AutoCAD (Autodesk, Inc., CA) ( Jeon et al., 2002). The simple ‘‘Y’’-type design has two fluidic inlets and a main gradient channel (Fig. 15.1A) (Lin and Butcher, 2006). The network device consists of a mixing microchannel network between the fluidic inlets and the main gradient channel as described previously (Fig. 15.1B) ( Jeon et al., 2000). The mixing channels in the network are approximately 3-50-mm wide. These mixing channels should be long enough for complete chemical mixing (typically several tens of millimeters), depending on the flow rate and diffusive rate of the chemical, and a curved A

B Network device

“Y” device Buffer

Chemokine

Fluid inlets Cell inlets

Cell

Cell Outlet

Figure 15.1 Gradient generation in microfluidic device. (A) Illustration of gradient generation in the ‘‘Y’’-type device. Fluorescence micrograph of FITC-dextran (as the readout of chemokine concentration) at 6 mm below the junction of the ‘‘Y’’channel is shown. The scale bar represents 50 mm. (Lin and Butcher, 2006). Reproduced by permission of The Royal Society of Chemistry. (B) Illustration of gradient generation in the network device. Fluorescence micrograph of FITC-dextran (as the readout of chemoattractant concentration) in the gradient channel is shown. The scale bar represents 50 mm.

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design (not shown in Fig. 15.1B) is often used to reduce the size of the device. The width of the main gradient channel varies from several hundreds of micrometers to several millimeters, depending on the size and the migration speed of the cell for the study. For leukocytes with the typical size of approximately 10 mm in diameter and the migration speed of approximately 10 mm/min, a few hundred micrometers is often used for the width of the gradient channel. The cell-loading inlets are designed on either one side or both sides of the gradient generator with relatively small intersections with the upper portion of the gradient channel to minimize flow disturbance. The completed design is printed to a transparency mask with a high-resolution printer consistent with the type of the photoresist for fabrication (e.g., negative patterns for SU-8 photoresist).

2.2. Fabrication of microfluidic devices The design is negatively patterned on a silicon wafer (
100 mm high) by 1:1 contact photolithography of SU-8 50 photoresist (MicroChem, MA) through the transparency mask. Detailed protocol of SU-8–based photolithography can be found elsewhere. After the optical lithographic steps, the silicon master is stamped to PDMS (Sylgard 184, Dow Corning, MI) with the standard soft-lithography technique. After 1 to 2 h of baking at 80  C in an oven or on a hotplate, the PDMS replica is cut and detached from the master. Inlets and outlets (
1-mm diameter holes) for the fluids and cells are punched out with sharpened needles. The surface of the PDMS replica and a clean glass cover slide are treated with air plasma for 1 to 2 min with a plasma cleaner (Harrick Scientific, NY) and brought together to form an irreversible seal to complete the microfluidic channels. This step also helps clean the PDMS surface and the cover slide and modifies PDMS surface to be hydrophilic. Cellophane tape and/or air blowing is often used to clean the PDMS replica before plasma treatment. The completed microfluidic device is wetted by filling with DI water to preserve hydrophilicity of the PDMS channels and can be saved in a 4  C fridge for up to a few days before use.

2.3. Substrate preparation To provide a substrate for cell adhesion and migration, the main gradient channel is coated with adhesion promoting factors. For leukocytes, fibronectin (BD Bioscience, CA) is used to coat the gradient channel. Because of the low dimension of the microfluidic channel, a high concentration of the coating solution is used to achieve the required substrate surface density. Depending on the cell type, the substrate density should be optimized by testing a range of concentration of the coating solution. For example, we coat the channel at 2.5 mg cm2 of surface density of fibronectin for human blood neutrophils and T cells by adding 0.4 ml of 0.25 mg ml1 fibronectin

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solution to the gradient channel (0.04 cm2 of surface area) for at least 1 h at room temperature. The fibronectin-coated device is blocked with 2% BSA for another hour at room temperature before use.

3. Generation of Chemoattractant Gradients 3.1. Principle of microfluidic gradient generation The flow-based microfluidic devices generate chemical concentration gradients by controlled mixing of laminar flows in the microchannels (Lin et al., 2008). In the ‘‘Y’’-type device, medium and chemoattractant solutions are continuously infused into the device by syringe pumps from separate inlets. The chemical streams mix in the main gradient channel and diffuse into a gradient across the channel. The gradient profile develops along the channel by diffusion, and its shape is stable at any point along the channel (Fig. 15.1A). As described previously (Lin et al., 2008), the gradient profile can be theoretically predicted by the diffusion model. The advantage of the ‘‘Y’’-type device is its simple design, ease of use, the ability of generating single and overlapping gradients, and rapid gradient switching. The drawback is its inflexibility for manipulating spatial gradient profiles. Similar to the ‘‘Y’’-type device, gradient generation in the network device relies on chemical mixing of continuous laminar flows in the micro-channels. Its principle is different from the ‘‘Y’’-type device by repeated mixing and splitting of chemical streams through the microchannel network. The flow in the network is regulated by the fluidic resistance and can be modeled in analogy to an electrical resistor circuit (Dertinger et al., 2001; Jeon et al., 2000). The network generates multiple output streams with different defined chemical concentrations, which subsequently flow into the main gradient channel, forming a gradient across the channel (Fig. 15.1B). The gradient profile is determined by the inlet configuration and the structure of the micro-channel network, and the resolution of the gradient is proportional to the size of the micro-channel network. For example, a symmetric design (with medium and chemoattractant inlets evenly distributed above the network) produces linear gradients (Fig. 15.1B), and an asymmetric design (with more medium inlets than chemoattractant inlets or vice versa, or with unequal flow rates) creates nonlinear gradients (Lin et al., 2004b). By varying chemical input concentrations, different gradient shapes can be configured and manipulated dynamically (Lin et al., 2004b). The network device is also capable of generating overlapping gradients of different chemoattractants (Dertinger et al., 2001; Jeon et al., 2000; Lin et al., 2005). Comparing to the ‘‘Y’’-type device, the network device can more flexibly manipulate gradient profiles in space and can maintain stable gradient with the same shape over a longer distance

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along the channel. The drawback is the relatively large size of the device and complicated design. Both the ‘‘Y’’-type device and the network device can generate gradient of complex shapes by aligning multiple gradientgenerating units in parallel with the output streams united in a common gradient channel (Dertinger et al., 2001).

3.2. Measurement of chemoattractant gradients in microfluidic devices Chemoattractant solutions are mixed with fluorescent additives for visualization and measurement of chemoattractant gradient in the micro-channel by fluorescence microscopy (Fig. 15.1). The fluorescent additives are chosen to have similar molecular weight to the chemoattractant molecules. For example, because most chemokine molecules have the molecular weight of approximately 10 kDa, FITC-dextran 10 kDa or similar is used. The fluorescent dye should be prepared in the same medium as the chemoattractant solution, and only a small amount should be added to the chemoattractant solution to minimize its effect on cells (typically less than 2% of the total chemoattractant solution). For overlapping gradients of different chemoattractants, fluorescent dyes of different colors should be used. Fluorescence intensity of the dyes is measured as the average over the height of the channel assuming the presence of the cell does not significantly modify the gradient. This assumption applies to leukocytes in a 50- to 100-mm-high channel. Confocal imaging may be required to accurately determine the gradient around the cell. The gradient should be checked repeatedly over the duration of the cell migration experiment (typically 20 min to 90 min for leukocytes). It is worthwhile pointing out that the gradient may fluctuate at low flow rate because of the step nature of the syringe pump–based fluid delivery. Frequent gradient measurements will be helpful to determine gradient stability.

4. Preparation of Cells 4.1. Isolation of human blood leukocytes Human blood leukocytes are isolated from whole blood or buffy coats obtained from healthy blood donors. Polymorphonuclear cells (PMN) or peripheral blood mononuclear cells (PBMC) are isolated with a standard gradient centrifugation method. Isolated cells are washed with PBS and HBSS several times. Red blood cells (RBC) are removed from PMN with RBC lysis buffer to enrich the neutrophil population. Enriched neutrophils are resuspended in HBSS before use. Lymphocytes are enriched from PBMC by incubating PBMC in a flask for 2 h or longer to remove adherent monocytes.

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Total lymphocytes in suspension are resuspended in culture medium before further processing. Because of the different life span of neutrophils and lymphocytes in vitro, neutrophils should be isolated from fresh blood within 1 to 2 h after drawing and used for experiment within 8 h for best results. Lymphocytes, however, can be isolated from blood drawn in the previous day.

4.2. Purification, differentiation, and characterizations of leukocyte subpopulations To obtain T cells from PBMC or total lymphocytes, FACS sorting or magnetic cell selection can be used. Alternately, T cells can be activated by incubating PBMC or total lymphocytes in an anti-CD3/CD28 antibodies-(R&D Systems, MN) coated 24-well plate in supplemented culture medium (RPMI-1640 GLUTAMAX medium with 25 mM HEPES buffer [Gibco, CA], 1% penicillin-streptomycin, 10% heat-inactivated FBS, and 1% nonessential amino acids [Fisher]) in a 37  C incubator with 8% CO2 injection for 2 days. After the activation, cells in the solution are transferred to a flask and cultured in supplemented culture medium in the presence of 12.5 ng ml1 IL-2 (R&D Systems, MN) for at least 3 days before use. This method offers an easy and inexpensive way of generating a T-cell population, and these cells can be used for experiment within 2 weeks. Before cell migration experiments in microfluidic devices, the purity and chemoattractant receptor expression of the cells are characterized by FACS. For activated T cells, the level of certain chemoattractant receptor expression (e.g., CCR7) may vary over time after activation, which may consequently affect chemotactic responses to chemoattractant gradients (e.g., CCL19 and CCL21). Chemotaxis of cells to chemoattractants is also tested in standard transwell assays (Lin and Butcher, 2006). These additional steps will ensure the cell purity for microscopic analysis in microfluidic devices and will verify whether the cells may respond to chemoattractants through chemoattractant receptor signaling.

5. Experimental Setup 5.1. Assembly of microfluidic system The migration medium is prepared with RPMI-1640 GLUTAMAX medium with 0.2% BSA. The medium is incubated in a 37  C incubator with 8% CO2 for a few hours or overnight followed by the addition of 25mM HEPES buffer, which helps maintain the pH of the medium. The medium with or without chemoattractant is loaded into syringes, which are installed to syringe pumps and connected to the inlets of the microfluidic

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device through tubing for fluid delivery. The microfluidic device is placed on the stage of an inverted microscope, and bubbles trapped in the microfluidic channels are removed by pumping the fluid at high flow rate through the channels. These steps complete the setup of the microfluidic system.

5.2. Environmental controls The device is maintained at 37  C with a stage incubator that encloses the entire microscope stage and blows hot air or by attaching a transparent heater to the back of the cover slide (Thermal-Clear Transparent Heater, Minco, MN). Good cell migration results with both temperature control methods have been demonstrated (Lin and Butcher, 2006; Lin et al., 2004a, 2005). The transparent heater is inexpensive and is easier to set up. However, it only heats the bottom of the device and often produces bubbles in the microfluidic channels and, therefore, is most suitable for short-time experiments.

5.3. Cell loading Typically, 5000 to 10,000 cells in 15mL volume of medium are prepared and loaded into the microfluidic device from the cell loading inlets. Approximately 1000 to 2000 cells were allowed to settle in the gradient channel for 5 to 10 min before applying the gradient. The cell loading inlets are then sealed with adhesive seal tabs (Fisher) to reduce flow disturbance. Low flow rate is used to minimize shear stress on cells (e.g., we use 0.2 ml min1 or 0.095 mm sec1 in our device).

5.4. Time-lapse optical microscopy After the cells are seeded and the desired stable temperature is reached, a microscope field is chosen in the gradient channel with a 10 or 20 objective for observation of cells. For the ‘‘Y’’-type device, the observation field is centered a few millimeters below the junction of the input channels for a more continuous gradient (Lin and Butcher, 2006b). In contrast, the selection of the visualization field in the network device is less critical. It is recommended to select the visualization field with sufficient number of cells for statistical analysis and enough spacing among individual cells to minimize cell-cell interactions and allow single cell tracking. The gradient is checked before image acquisition. Cell migration in the microfluidic device is recorded at 2 to 6 frames/min1 for 20 to 90 min with a CCD camera. It is recommended to monitor the gradient through the experiment if possible. Figure 15.2 shows the micrographs of T cells in a chemokine

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Human T cells to CCL19 gradient 0 min

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Figure 15.2 Leukocyte chemotaxis to chemoattractant gradients in microfluidic devices. (A) Images of human peripheral blood Tcells in the gradient channel of a‘‘Y’’type device at the beginning (0 min) and in the end (20 min) of the migration experiment in a nonlinear gradient of chemokine CCL19 (concentration increases from the left to the right in the channel).The scale bar represents 50 mm. (Lin and Butcher, 2006). Reproduced by permission of The Royal Society of Chemistry. (B) Images of human peripheral blood neutrophils in the gradient channel of a network device at the beginning (0 min) and in the end (30 min) of the migration experiment in a linear LTB4 gradient (concentration increases from the left to the right in the channel). The scale bar represents 50mm.

CCL19 gradient in a ‘‘Y’’-type device (Fig. 15.2A) (Lin and Butcher, 2006) and neutrophils in a lipid product LTB4 gradient in a network device (Fig. 15.2B) at the beginning and in the end of the migration experiment.

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6. Data Analysis 6.1. Image processing and cell tracking Before cell tracking, the time-lapse micrographs are processed by subtracting the background and removing the noise. Then the movement of individual cells is tracked manually or with automated tracking algorithms. Some popular tracking programs include ImageJ (v1.34s, NIH, MD) with the cell tracking plug-in, and MetaMorph (Universal Imaging, PA). The tracking data are then exported to third-party programs for analysis.

6.2. Characterizations of cell orientation To quantitatively evaluate the orientation response of cells, the percentage of chemotaxing cells and chemotactic index (C.I.) are calculated (Lin and Butcher, 2006; Lin et al., 2004a, 2005), and statistical analysis of cell migration angles is performed. C.I. is defined as the ratio of the displacement of cells toward the gradient (Dx) to the total migration distance (d ).

C:I: ¼

Dx d

ð15:1Þ

The percentage of chemotaxing cells is defined as the percentage of cells that has positive displacement toward the gradient (þDx) or positive C.I. Statistical analysis of migration angles is performed with Oriana for Windows (Kovach Computing Services, Wales, UK) to examine the directionality of the cell movement. Migration angles (calculated from x-y coordinates at the beginning and the end of the cell tracks) are summarized in a direction plot, which is a rose diagram showing the distribution of angles grouped in 20-degree intervals, with the radius of each wedge indicating cell number. The Rayleigh test for circular uniformity is applied, with a significance level of 0.05. When there is significant directionality, the mean angle and the 95% confidence interval are calculated. A Modified Rayleigh test (V test) is also applied to test whether deviations from the direction of the gradient are significant

6.3. Characterizations of cell motility The absolute motility of cells is quantified by calculating the average cell speed.

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V ¼

d Dt

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The random motility of cells is also quantified by calculating the mean square displacement < r 2 ðtÞ > of cells as a function of time, t, and is fitted with a Langevin interpolation formula (Lin et al., 2004a),

< r 2 ðtÞ >¼ D½t  tð1  et Þ t

ð15:3Þ

Diffusion constant, D, and the characteristic migration time, t, of the cells are extracted from the Langevin fit. The diffusion constant is used to describe the random motility of cells. In addition, motility index (M.I., defined as the ratio of displacement from starting position, r, to the maximum displacement, rmax) is used to quantify the random motility of cells (Lin et al., 2004a; 2005),

M:I: ¼

r rmax

ð15:4Þ

where rmax is the product of the average migration speed of cells (
10 mm/ min) and time.

6.4. Characterizations of persistent migration and chemotaxis To characterize the persistence of cell migration, the number of significant turnings of cells (e.g., Dy > 45 ) during the time course of the experiment is analyzed. The mean migration distance between each turning is also calculated. To quantify the effectiveness of cell migration toward the chemoattractant gradient, the effective chemotactic index (E.C.I.) is used (Lin et al., 2004a, 2005). E.C.I. is defined as the product of C.I. and M.I.,

E:C:I: ¼ C:I:  M:I:

ð15:5Þ

6.5. Subregion analysis To compare cell migration in different regions of the microfluidic channel, the subregion analysis is performed (Lin and Butcher, 2006; Saadi et al., 2006; Wang et al., 2004). For example, in competing chemoattractant gradients, cell tracks are divided into a ‘‘left’’ population (the initial position of the cell is in the left half of the channel) and a ‘‘right’’ population

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(the initial position of the cell is in the right half of the channel). All parameters and analysis methods as described previously are evaluated separately for each subregion. To assess the difference of the parameters between different conditions or regions, the Student’s two-sample (two-tailed) t test and ANOVA are performed. Quantitative analysis is complemented by direct visualization of cell migration from time-lapse images (Fig. 15.2) and trajectories based on the tracking data.

7. Conclusion The microfluidics-based method described in this chapter is an enabling tool for single-cell–based analysis of leukocyte migration and chemotaxis to chemoattractant gradients. It allows quantitative studies of leukocyte migration in response to different chemoattractant gradients with simple or complex shapes. Such an approach is particularly useful for measuring the migration of rare cell types. In addition, the flow-based microfluidic devices help dissect chemoattractant-induced cell responses from cell-cell interactions. Owing to the unique ability of microfluidic devices for configuring spatiotemporal chemoattractant gradients, the microfluidics-based method enables systematic investigations of the regulations of immune cell migration and trafficking by complex guiding signals. In addition to quantitative characterizations of cell movement in chemoattractant gradients as described in this chapter, the microfluidics-based method allows visualization and analysis of intracellular chemotactic signaling as well. The limitations of the described microfluidic method are the mechanical disturbance to cells induced by the flow, the lack of its ability for configuring 2-D chemical gradients, and low throughput of experimentation. To overcome these limitations, several strategies for configuring a flow-free microfluidic gradient have been developed (Chung et al., 2006; Diao et al., 2006; Kanegasaki et al., 2003; Keenan et al., 2006; Lin et al., 2008). Particularly, a microfluidic microinjector device has been developed, which has the potential for generating 2-D gradients in a flow-free environment (Chung et al., 2006). Further development of these alternative approaches will complement the flow-based method for analyzing leukocyte migration. It is also desirable to develop a new microfluidics-based method that would allow highly parallel measurements of leukocyte migration in different chemoattractant gradients on a single chip. Finally, the described method limits cell migration studies on 2-D surfaces. Generation of microfluidic gradient in 3-D extracellular matrix will better mimic tissue environment for advanced cell migration analysis (Mosadegh et al., 2007; Saadi et al., 2007).

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ACKNOWLEDGMENTS I thank Dr. Noo Li Jeon at the University of California-Irvine, and the members of the Jeon laboratory, for neutrophil migration studies with microfluidic devices. I also thank Dr. Eugene C. Butcher at Stanford University, and the members of the Butcher laboratory, for T cell migration studies with microfluidic devices.

REFERENCES Baggiolini, M. (1998). Chemokines and leukocyte traffic. Nature 392, 565–568. Boyden, S. V. (1962). The chemotactic effect of mixtures of antibody and antigen on polymorphonuclear leukocytes. J. Exp. Med. 115, 453. Campbell, J., and Butcher, E. (2000). Chemokines in tissue-specific and microenvironmentspecific lymphocyte homing. Curr. Opin. Immunol. 12, 336–341. Chung, B. G., Lin, F., and Jeon, N. L. (2006). A microfluidic multi-injector for gradient generation. Lab. Chip. 6, 764–768. Dertinger, S. K. W., Chiu, D. T., Jeon, N. L., and Whitesides, G. M. (2001). Generation of gradients having complex shapes using microfluidic networks. Anal. Chem. 73, 1240–1246. Diao, J., Young, L., Kim, S., Fogarty, E. A., Heilman, S. M., Zhou, P., Shuler, M. L., Wu, M., and DeLisa, M. P. (2006). A three-channel microfluidic device for generating static linear gradients and its application to the quantitative analysis of bacterial chemotaxis. Lab. Chip. 6, 381–388. Irimia, D., Liu, S.-Y., Tharp, W. G., Samadani, A., Toner, M., and Poznansky, M. C. (2006). Microfluidic system for measuring neutrophil migratory responses to fast switches of chemical gradients. Lab. Chip. 6, 191–198. Jeon, N. L., Baskaran, H., Dertinger, S. K. W., Whitesides, G. M., Water, L. V. D., and Toner, M. (2002). Neutrophil chemotaxis in linear and complex gradients of interleukin-8 formed in a microfabricated device. Nat. Biotechnol. 20, 826–830. Jeon, N. L., Dertinger, S. K. W., Chiu, D. T., Choi, I. S., Stroock, A. D., and Whitesides, G. M. (2000). Generation of solution and surface gradients using microfluidic systems. Langmuir. 16, 8311–8316. Kanegasaki, S., Nomura, Y., Nitta, N., Akiyama, S., Tamatani, T., Goshoh, Y., Yoshida, T., Sato, T., and Kikuchi, Y. (2003). A novel optical assay system for the quantitative measurement of chemotaxis. J. Immunol. Methods 282, 1–11. Keenan, T. M., Hsu, C.-H., and Folch, A. (2006). Microfluidic ‘‘jets’’ for generating steadystate gradients of soluble molecules on open surfaces. Appl. Phys. Lett. 89, 114103. Kubes, P. (2002). Introduction: The complexities of leukocyte recruitment. Semin. Immunol. 14, 65–72. Lin, F., and Butcher, E. C. (2006). T cell chemotaxis in a simple microfluidic device. Lab. Chip. 6, 1462–1469. Lin, F., Chung, B. G., Saadi, W., and Jeon, N. L. (2008). Gradient-Generating Microfluidic Devices for Cell Biology Research. Chapter 2: Micro- and Nano-Engineering of the Cell Microenvironment: Technologies and Applications : Artech House Publishing Inc, MA, USA. Lin, F., Nguyen, C., Wang, S., Saadi, W., Gross, S., and Jeon, N. (2005). Neutrophil migration in opposing chemoattractant gradients using microfluidic chemotaxis devices. Ann. Biomed. Eng. 33, 475–482.

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Lin, F., Nguyen, C. M., Wang, S. J., Saadi, W., Gross, S. P., and Jeon, N. L. (2004a). Effective neutrophil chemotaxis is strongly influenced by mean IL-8 concentration. Biochem. Biophys. Res. Commun. 319, 576–581. Lin, F., Saadi, W., Rhee, S. W., Wang, S.-J., Mittal, S., and Jeon, N. L. (2004b). Generation of dynamic temporal and spatial concentration gradients using microfluidic devices. Lab. Chip. 4, 164–167. Lohof, A., Quillan, M., Dan, Y., and Poo, M. (1992). Asymmetric modulation of cytosolic cAMP activity induces growth cone turning. J. Neurosci. 12, 1253–1261. Mosadegh, B., Huang, C., Park, J. W., Shin, H. S., Chung, B. G., Hwang, S. K., Lee, K. H., Kim, H. J., Brody, J., and Jeon, N. L. (2007). Generation of stable complex gradients across two-dimensional surfaces and three-dimensional gels. Langmuir. 23, 10910–10912. Nelson, R. D., Quie, P. G., and Simmons, R. L. (1975). Chemotaxis under agarose: A new and simple method for measuring chemotaxis and spontaneous migration of human polymorphonuclear leukocytes and monocytes. J. Immunol. 115, 1650–1656. Saadi, W., Rhee, S. W., Lin, F., Vahidi, B., Chung, B. G., and Jeon, N. L. (2007). Generation of stable concentration gradients in 2D and 3D environments using a microfluidic ladder chamber. Biomed. Microdevices 9, 627–635. Saadi, W., Wang, S. J., Lin, F., and Jeon, N. L. (2006). A parallel-gradient microfluidic chamber for quantitative analysis of breast cancer cell chemotaxis. Biomed. Microdevices 8, 109–118. Tharp, W. G., Yadav, R., Irimia, D., Upadhyaya, A., Samadani, A., Hurtado, O., Liu, S. Y., Munisamy, S., Brainard, D. M., Mahon, M. J., Nourshargh, S., van Oudenaarden, A., et al. (2006). Neutrophil chemorepulsion in defined interleukin-8 gradients in vitro and in vivo. J. Leukoc. Biol. 79, 539–554. Wang, S. J., Saadi, W., Lin, F., Minh-Canh Nguyen, C., and Li Jeon, N. (2004). Differential effects of EGF gradient profiles on MDA-MB-231 breast cancer cell chemotaxis. Exp. Cell Res. 300, 180–189. Zicha, D., Dunn, G., and Jones, G. (1997). Analyzing chemotaxis using the Dunn directviewing chamber. Methods Mol. Biol. 75, 449–457. Zigmond, S. (1977). Ability of polymorphonuclear leukocytes to orient in gradients of chemotactic factors. J. Cell Biol. 75, 606–616.

C H A P T E R

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Two-Photon Microscopy and Multidimensional Analysis of Cell Dynamics Bernd H. Zinselmeyer,* John Dempster,† David L. Wokosin,‡ Jonathan J. Cannon,§ Robert Pless,§ Ian Parker,} and Mark J. Miller* Contents 1. Introduction 2. 2P Microscope Systems 2.1. Scan heads and femtosecond lasers 2.2. Acquisition software 2.3. Signal detection and optical filters 2.4. Laser attenuation and fast shuttering 2.5. Sample power control 2.6. Pulse compression 3. Fluorescent Reporters 3.1. Fluorescent dyes 3.2. Genetically encoded fluorescent proteins 3.3. Autofluorescence and second harmonic generation signals 4. Imaging Preparations 4.1. Explant imaging 4.2. Intravital imaging 4.3. Imaging peripheral tissues 5. Image Acquisition 5.1. Laser power and PMT gain 5.2. Cell density 5.3. Z-series acquisition and time resolution * {

{ }

}

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Washington University School of Medicine, Department of Pathology and Immunology, St. Louis, Missouri, USA University of Strathclyde, Institute for Pharmacy & Biomedical Sciences, Glasgow, Scotland, United Kingdom Northwestern University, Department of Physiology, Chicago, Illinois, USA Department of Computer Science and Engineering, Washington University in St. Louis, St. Louis, Missouri, USA Departments of Neurobiology and Behavior, and Physiology and Biophysics, University of California, Irvine, California, USA

Methods in Enzymology, Volume 461 ISSN 0076-6879, DOI: 10.1016/S0076-6879(09)05416-0

#

2009 Elsevier Inc. All rights reserved.

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6. Multidimensional Analysis 6.1. Cell detection 6.2. Cell tracking 6.3. Cell and tissue morphology 6.4. Cluster and neighbor analysis 6.5. Analysis of cell migration 7. Presentation of 2P Microscopy Images 7.1. 2-D images 7.2. Cell tracks 7.3. 3-D rotations and time-lapse movies References

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Abstract Two-photon (2P) microscopy is a high-resolution imaging technique that was initially applied by neurobiologists and developmental cell biologists but has subsequently been broadly adapted by immunologists. The value of 2P microscopy is that it affords an unparalleled view of single-cell spatiotemporal dynamics deep within intact tissues and organs. As the technology develops and new transgenic mice and fluorescent probes become available, 2P microscopy will serve as an increasingly valuable tool for assessing cell function and probing molecular mechanisms. Here we discuss the technical aspects related to 2P microscope design, explain in detail various tissue imaging preparations, and walk the reader through the often daunting process of analyzing multidimensional data sets and presenting the experimental results.

1. Introduction The theory describing two-photon (2P) excitation of fluorescence was first published by Maria Go¨ppert (1929) as part of her doctoral work in physics at the University of Go¨ttingen. Nearly 60 years later, Denk and Webb introduced 2P microscopy as a high-resolution imaging technique for studying biologic tissues (Denk et al., 1990). Neurobiologists were among the first to adopt 2P microscopy for biologic studies (Yuste et al., 2005), but it is now used widely by cell biologists and immunologists (Germain et al., 2006; Masters and So, 2008). The value of 2P microscopy is that the behavior of individual cells can be studied in the context of their native 3-D environments within tissues including skin (Matheu et al., 2008a; Peters et al., 2008; Zinselmeyer et al., 2008), spinal cord (Kawakami et al., 2005), gut (Chieppa et al., 2006), bone marrow (Cavanagh et al., 2005; Celso et al., 2008), and lymphoid organs (Aoshi et al., 2008; Bousso and

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Robey, 2004; Lindquist et al., 2004; Mempel et al., 2004a; Miller et al., 2002, 2004a; Shakhar et al., 2005; Witt et al., 2005). Recently, 2P microscopy has been applied to study the dynamic interplay of host-pathogen interactions in vivo during viral, protozoan, and bacterial infection (Chieppa et al., 2006; Egen et al., 2008; Peters et al., 2008). As the technology advances and new transgenic reporter mice and fluorescent probes become available, 2P microscopy will allow the immune response to be assessed at a functional level by providing readouts for intracellular signaling (Bhakta and Lewis, 2005; Bhakta et al., 2005), gene expression, cell proliferation (Miller et al., 2002), chemotaxis (Beuneu et al., 2006; Castellino et al., 2006; Hugues et al., 2006; Okada et al., 2005), and CTL killing (Boissonnas et al., 2007; Mempel et al., 2006). 2P excitation occurs when two longer-wavelength lower-energy photons (together having the equivalent energy of a single higher-energy photon) are absorbed as a single quantum of energy by a fluorophore, thereby promoting an electron to an excited state. From this point on, the process of fluorescence emission is identical to single photon excitation. The electron releases some of its energy through nonradiative processes and eventually (in the range of nanoseconds, www.olympusfluoview.com/) returns to its ground state, emitting the remaining energy as a lower energy photon. For 2P excitation to take place, the two photons need to be absorbed nearly instantaneously (within attoseconds). The high photon densities required for this low probability event to occur can be achieved by use of a microscope objective to focus a femtosecond pulsed Ti: Sapphire laser beam into a diffraction-limited spot (<1 mm) in the specimen. Because excitation effectively occurs only at the point of focus, the emitted fluorescence is localized in 3-D space. This allows the specimen to be optically sectioned by laterally scanning the laser spot in x and y dimensions and moving the laser focus sequentially in the z axis with an automated z-focus motor. The fluorescence emission is collected by photomultiplier tubes (PMT) at each point in the scan to build a digital image pixel by pixel. Z-stacks can be acquired repeatedly from the sample to generate 3-D timelapse data. Once the images are collected, they are rendered in 3-D and cell analyzed quantitatively for velocity, colocalization, shape, volume, number, intensity, and color. Although 2P microscopy is expensive and the analysis time consuming, the technique provides single-cell spatiotemporal information that other imaging techniques cannot. In particular, 2P microscopy involves significantly less sample photodamage than confocal microscopy (this substantially improves cell viability) and, because of the reduced scattering of the infrared excitation light, images can be acquired several hundred microns deep in native tissues (compared with <80 mm with confocal microscopy) making it an extremely powerful technology for in vivo imaging (Masters and So, 2008).

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2. 2P Microscope Systems 2.1. Scan heads and femtosecond lasers In the past several years, 2P microscopy systems designed for biologic research have become commercially available. The recent trend is toward commercial laser-scanning microscope systems that are dedicated for 2P microscopy (i.e., without confocal detection capability and the added expense of visible lasers). The advantages of these commercial systems are that they are installed for the researcher, and service and maintenance is provided by the vendor. Moreover, these systems are designed to support a number of different imaging applications and often come with extensive user-friendly acquisition software and, in some cases, basic analysis software. On the other hand, several researchers have chosen to build their own systems (Leybaert et al., 2005; Nguyen et al., 2001; Okada et al., 2005; Tang et al., 2006). Many technical details regarding the construction of these systems are posted on these researchers’ web sites (URLs: http://parkerlab. bio.uci.edu/microscopy_construction.htm; http://users.umassmed.edu/ michael.sanderson/mjslab/confocal_microscopy_main.htm; http://pathology. ucsf.edu//krummel/2PhotonHome.html). These sites are an invaluable resource for those interested in building their own systems. The advantage of a custom-built system is that it can be tailored to specific applications, such as intravital imaging, and optimized for sensitivity and speed. Moreover, once an investigator builds a system, they are in a position to further modify the equipment for new applications or quickly repair the system as needed without having to rely on the microscope vendor for service. The 2P microscope built in our laboratory (Fig. 16.1) is based on Ian Parker’s prototype instrument at UC Irvine (Nguyen et al., 2001) but incorporates several further design improvements. First, the system is capable of capturing full-frame images at video-rate (30 f/sec) for up to four fluorescent detection channels simultaneously; whereas, commercial 2PE systems typically have two non-descanned detection channels and are limited to
2 f/sec for the same scanned area and resolution. Recently, several commercial systems have introduced videorate scan heads as an option. These systems, using resonance (Leica) and accousto-optic device (AOD) scanning (Prairie), can also reach 30 f/sec. Rapid scanning is especially useful for quickly exploring the tissue for a region of interest and when analyzing highly dynamic phenomena such as leukocyte recruitment from the circulation. A second novel feature of our system is that it is equipped with two tunable Ti: Sapphire lasers (Chameleon XR Ti: sapphire laser, Coherent) (Fig. 16.1A), which allows fluorescent probes with different optimal excitation wavelengths to be used simultaneously (e.g., YFP and CMAC),

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Figure 16.1 Dual-beam two-photon microscope system and imaging chambers. (A) optical layout of the system, showing the laser paths (red and orange) and crucial optical components. (B) Equipment rack containing acquisition computer, heating unit, modulator (Pockels cells) power supplies, scanner control electronics and PMT gain controls, joy stick for controlling the stage movement and focus, a potentiometer box to manually set laser attenuation, a shutter controller, and the acquisition monitor for viewing the specimen in real time. (C) Microscope stand and fluidics.Various imaging chambers for (D) explant tissue imaging (Harvard Apparatus), (E) ear imaging, (F) bone marrow imaging in the skull (with gas anesthesia connectors) (Harvard Apparatus), (G) footpad imaging, (H) intravital imaging of internal organs. Scale bar ¼ 3cm.

which excite optimally at 915 nm and 780 nm, respectively. This makes it possible to discriminate complex mixtures of cells that cannot be separately identified by other 2P microscopes (Wokosin et al., 2004) and to run internal controls (e.g., polyclonal T cells for antigen presentation experiments). Moreover, by alternating the laser lines with Pockels cells (Fig. 16.1A) as described in the section following, two probes with similar emission spectra, but different excitation optima, such as CMAC and CFP can be used together. This greatly expands the number of reporters that can be used in a single experiment. For example, in Fig. 16.2, a laser tuned to 900 nm was used to excite CFP, GFP, and YFP and a second laser tuned to 800 nm to excite CMAC and CMTMR. In this case the 900-nm and 800-nm images were acquired during alternate z-stacks (every 30 sec). This

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Figure 16.2 Imaging fluorescent proteins and fluorescent dyes with fast laser switching. Four different groups of CD4þ T cells (2  106 each) were adoptively transferred into a CD11c-YFP transgenic mouse (Lindquist et al., 2004). CFP- and GFP-expressing Tcells were isolated from transgenic mice expressing these fluorescent proteins under the control of the actin-promotor (The Jackson Laboratory).Two other groups of Tcells had been stained with CMTMR and CMAC. (A) 3-D view of lymph node excited at 920 nm (Laser #1), showing YFPþ dendritic cells (yellow); GFP-expressing Tcells (cyan), and CFP-expressing T cells (blue). (B) The same field of view excited at 790 nm (Laser #2), showing CMTMR-labeled T cells (red) and CMAC-labeled T cells (blue). (C and D) Three time-lapse images where the laser excitation was alternated between (C) 920 nm and (D) 790 nm.Times are indicated in min:sec.

is sufficient for many applications, but the laser lines could also be switched during each z-step, enabling imaging of four fluorescent proteins and four fluorescent dyes with only a 33 to 500 msec time difference.

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2.2. Acquisition software We developed custom software (ImageWarp, A&B software) in collaboration with A&B software (Boris Nalibotski), to perform on-the-fly image correction (for the Raven camera board, Bitflow) and to control hardware components, such as the z-focus motor and laser shutters (Fig. 16.1B). Multi-dimensional data files (intensity, color, time, and three spatial dimensions) are streamed to a lab server (X-Serve with 3.75 Tb capacity RAID5 array, Apple inc.) after the acquisition. Others have used Video Savant (IO Industries) or Slidebook (Intelligent Imaging Innovations Inc.) as their acquisition and hardware control software. The preferred formats for multi-dimensional data files are either tiff stack (compatible with a wide range of software platforms) or Metamorph stk files, which are archived and accessed efficiently. Importantly, formats should be recognized by commercially available software for image rendering and analysis such as Volocity (Improvision) and Imaris (Bitplane). Although automated tracking software works for many applications, manual tracking is often necessary in experiments in which cell densities are high or in situations in which intensity thresholding is problematic. In any case, we found it useful to use manual tracking software such as Picviewer (compatible with tiff, stk, and pic files, John Dempster) to validate the results obtained with automated tracking software, because automated tracking can be prone to errors.

2.3. Signal detection and optical filters Our system uses four multi-alkali PMTs (Electron tubes) mounted in the epifluorescence module, as close as possible to the back aperture of the objective (XLUMPlanFI 20x/0.95NA waterdipping, Olympus) (Fig. 16.1A). The box contains a rail to hold up to three Olympus filter cubes in series. For most applications, we use high-efficiency dichroic filters (Semrock) for separating the fluorescence emission, without added bandpass filters. This configuration maximizes detection efficiency at the expense of clean channel separation. In most situations, moderate signal crosstalk does not impair cell tracking or performing morphometric analysis. However, signal bleedthrough can cause problems for automated tracking software. If automated tracking is to be performed later, it may be necessary to install bandpass filters to ‘‘clean up’’ the channels, but this comes with a cost. Because bandpass filters reduce the signal intensity, more laser power must be used to achieve comparable signal, which may adversely impact cell viability in the specimen. Our advice is to purchase a filter cube with each dichroic mirror and clearly label it to facilitate swapping the filters in and out of the system and to prevent them from getting lost, damaged, or mixed up. The dichroic

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mirrors (for separating fluorescence emission) we have found most useful for separating commonly used fluorescent probes in our laboratory are: 458 nm; 2nd harmonic generation signals 480 to 490 nm; CMAC and CFP 505 nm; GFP (505 nm divides GFP into blue and green channel; therefore, cells are cyan and can be easily distinguished from YFP) 525 nm; GFP 540 nm; YFP 560 nm; Rhodamine-dextran, CMTMR, RFP 590-nm; CMTPX, 605-nm FluoSpheres, or 655-nm quantum dots. It is important to check the dichroic filter transmission spectra below 400 nm. This is an issue with 2P microscopy because second and third harmonic generation signals will bleedthrough into the longer wavelength channels. To prevent shorter wavelength light from contaminating other channels, make sure the first dichroic filter, in the series (i.e., the blue filter) has good blocking characteristics into the 300-nm range. Emitted fluorescence collected through the objective lens is reflected into the detector head by a dichroic mirror that transmits the IR wavelengths (>680 nm) of the excitation laser beam. The cube holding this dichroic also includes a barrier filter to block laser light reaching the detectors. Selection of this filter is crucial, because the laser beam is many orders of magnitude brighter than the fluorescence signals, and dichroics and filters specially designed for multiphoton applications are available from several suppliers. We have also found it necessary to place a longpass (>680 nm) filter in the laser excitation path to block low levels of visible wavelengths emitted by the Chameleon laser.

2.4. Laser attenuation and fast shuttering The laser beam from each Chameleon laser is routed through an electrooptical modulator to enable precise and rapid control of the power at the sample plane. The modulators (M350-50-02-BK, ConOptics) can reduce the laser power by the full extinction ratio (
400:1) over the tuning range of the lasers. The M350-50 modulator uses 50 mm of potassium dideuterium phosphate (KD*P) birefringence crystal (two crystals of 25 mm), and yields an effective interaction region for the Pockels effect of 3.1-mm diameter. The modulator crystal cavity is filled with index-matched fluid (FC-43, n
1.291) to provide a device with low insertion loss and very high damage thresholds. The broadband antireflection coating wavelength range is 700 nm to 1200 nm (02) and has been verified to have 5% insertion loss over this entire wavelength range. The KD*P series crystals (M350) have intrinsic piezoelectric resonances near 64 kHz, which can cause sustained ringing with rapid voltage changes and can also introduce spatial problems

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with the exiting laser beam profile. A special resonance clamped option (BK) has been introduced to move these resonances past 200 KHz to better match to the frequency range possible with KD*P modulators and the M302 drivers. The input drive voltage (0 to 2V) is amplified by
375 times by the modulator driver (M320RM, ConOptics) before being applied to the crystals. A full change in transmission intensity requires
5 msec with this driver and modulator combination. The modulators were installed with the polarizer parallel to the plane of polarization of the laser, which is parallel with the top of the antivibration table. Thus, 0V drive voltage results in maximum power transmission.

2.5. Sample power control A custom-written Delphi program was created (PowerCal, John Dempster) to calibrate and control the electro-optical modulators from a personal computer with a digital-to-analog voltage card (PCI-6014, National Instruments) by means of drive voltage output signals. The parallel polarizer modulator configuration requires a cos2 equation to relate the drive voltage to the actual transmission. Longer laser wavelengths require more drive voltage to achieve full extinction, so the drive voltage is normalized by a wavelength dependent value, Vp, for a full l/2 shift in polarization. The PowerCal program also features a rapid end-of-frame triggering option that can be controlled by an ImageWarp script ( Jonathan Cannon) to alternate the two modulators between the imaging sample power and minimum sample power (full modulator extinction). With this ratiometric mode, we were able to acquire stable, alternating excitation wavelength imaging at 30 frames per second. The Chameleon laser output power is
1.5 W at 780 nm (and less at other wavelengths), which poses no detectable thermal heating drifting effects of the M350 modulator transmission. Higher laser powers (>2 W into 1 mm2) have been shown to induce an exponentially varying signal with time. A separate potentiometer box was created to derive the modulator drive voltages; this permitted manual control of the sample power for each laser. This manual/remote feature is often used during initial image acquisition with the fast scanning system.

2.6. Pulse compression As the TI: sapphire laser passes through the optical components of the system, the laser pulse becomes broadened (positive dispersion), because the longer wavelengths of light travel faster through these materials. Pulse dispersion can substantially lower the peak power of the laser at the sample and, therefore, decrease the efficiency of 2P excitation. To correct for dispersion in the system, precompensation is performed with a set of prisms (Fork, 1986) to introduce negative dispersion (slowing down the longer

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wavelengths of light) and restore the pulse width at the sample. Our system uses a prism-based pulse compression unit (FemtoControl, Coherent), which in our hands has yielded increased excitation efficiency and tissue imaging depth (
30 to 50% deeper).

3. Fluorescent Reporters Although 2P microscopy can be achieved by use of intrinsic signals (autofluorescence, second-harmonic generation), many applications require that specific cell populations be fluorescently labeled. This is most often accomplished by staining cells with vital fluorescent dyes or by expressing genetically encoded fluorescent protein in a cell lineage specific manner.

3.1. Fluorescent dyes One approach that has worked well with leukocytes is to isolate the cell type of interest by magnetic bead separation or density gradient centrifugation and label the cells with fluorescent dyes (Matheu and Cahalan, 2007). CellTracker probes CMAC, CFSE, CMTMR, CMTPX (Invitrogen) are commonly used for this purpose, as well as other dyes such as SNARF, which works well in combination with CFSE (Germain et al., 2005). A typical staining protocol for leukocytes (T cells, B cells, bone marrow neutrophils, and freshly isolated splenic DCs) is described in the following and summarized in Table 16.1. The dye concentrations in this table have been optimized to balance the fluorescence intensity of cotransferred leukocyte populations during subsequent imaging. 3.1.1. Dye-labeling protocol for leukocytes Stock solutions are made by dissolving lyophilized dyes in DMSO to achieve the following concentrations: 20 mM CMAC, 10 mM CFSE, CMTMR, and CMTPX. For CFSE and CMTPX, which come in predispensed 50-mg vials, add 7.3 ml DMSO to the tube and vortex or flicking the tube vigorously with your finger to redissolve the material. Dyes can be aliquoted and stored at 20  C for several months. Freezing and thawing the stock solutions multiple times should be avoided. Cell staining works well in CO2-independent medium (Gibco). When staining with CMTPX, we suggest adding 1% BSA to the medium to improve cell recovery. The cell density during staining should be approximately 10  106 cells/ml (for less than 10  106 cells use 1 ml). Dilute the stocks as in Table 16.1, into a 15-ml Falcon tube. For example, to stain 40 million cells with CMAC, 4 ml of 50 mM staining solution will be needed.

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Table 16.1 Summary of a leukocyte staining protocol optimized for two-photon imaging

Dye

Stock solution 7.3 ml DMSO to 50-mg vial

CMAC

20 mM

CFSE

10 mM

CMTMR 10 mM

CMTPX

10 mM

Final concentration

2.5 ml Stock into 1 ml medium ¼ 50 mM 0.5 ml Stock into 1 ml medium ¼ 5 mM 1 ml Stock into 1 ml medium ¼ 10 mM 1.5 ml Stock into 1 ml medium ¼ 15 mM

Medium

Incubation @ 37  C

CO2 independent

40 min

CO2 independent

30-40 min

CO2 Independent

40 min

CO2 independent + 1% BSA

40 min

Pellet the cells in a 15-ml Falcon tube by centrifugation at 300g (neutrophils require
800g) for 6 to 10 min. Carefully remove the supernatant, and resuspend the cell pellet in 1 ml of CO2 independent medium with vortexing. In a separate tube, add 10 ml of 20 mM CMAC stock solution to 3 ml of medium and mix thoroughly. Add the 3 ml of staining solution to the 1 ml of resuspended cells and mix well by pipetting up and down several times. This approach ensures that the cells are stained homogeneously. Incubate the tube at 37  C for 40 min, mixing the 15-ml Falcon tube twice during the incubation period. After the incubation, fill the tube with cold medium and centrifuge (6 to 10 min at 300g). Remove the supernatant and wash once more if desired. Resuspend the pellet in 200 to 250 ml of PBS for adoptive transfer. Stained cells should be not stored for more than a few hours at 4  C, whereas unstained cells can be stored overnight at 4  C and labeled the next day with
20 to 25% loss in cell number.

3.2. Genetically encoded fluorescent proteins Alternately, experiments can use transgenic mice that express fluorescent proteins in a lineage-specific fashion. In our hands, several transgenic models have excellent 2P imaging characteristics; CD11c-eYFP (for dendritic cells

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[Lindquist et al., 2004], CX3CR1 for monocytes and dendritic cells [Geissmann et al., 2003], LysM-eGFP for monocytes and neutrophils [Faust et al., 2000]). In these models, cells are brightly labeled, and the expression is reasonably specific with minimal background expression. In addition, transgenic mice expressing global CFP, GFP, YFP (The Jackson Laboratory), and RFP (Vintersten et al., 2004) driven by the chicken b-actin promoter is useful in cases in which the cells of interest can be isolated and adoptively transferred into suitable recipient strains. In the transgenic models mentioned previously, the fluorescent protein expression level is high, and cells can be detected easily with 2P microscopy. However, this is more often the exception rather than the rule. As a general guideline, if the fluorescence intensity of the cell of interest is
2 units over background by flow cytometry, then the cells are likely bright enough to be imaged by 2P microscopy.

3.3. Autofluorescence and second harmonic generation signals Also, tissues and cells can emit intrinsic signals that are useful as tissue landmarks. These include the second harmonic generation signal produced as the 2P laser interacts with non-centrosymmetric materials such as collagen in the skin and connective tissues (Gauderon et al., 2001; Zoumi et al., 2002). For excitation at 900 nm, a second harmonic generation signal at 450 nm will be produced (half the wavelength of the incident light). Some tissues, for example skeletal muscle (Rothstein et al., 2005) and pancreatic islets (Rocheleau and Piston, 2003), have strong autofluorescence because of NAD(P)H and flavoproteins. In some cases, autofluorescence is bright enough to visualize individual cells without labeling, such as with certain macrophages.

4. Imaging Preparations 2P imaging preparations generally take three main forms: (1) explanted tissues and intact organs placed under the flow of suitable medium; (2) invasive intravital imaging and; (3) noninvasive imaging of accessible surfaces, such as the skin or cornea.

4.1. Explant imaging Despite the caveats associated with explant preparations, they are undoubtedly more physiologic than most in vitro cell systems and have the additional advantages of being easy to work with (compared with intravital imaging preparations), yielding robust and reproducible results and allowing tissues to be studied that cannot be accessed otherwise. Moreover, they minimize

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animal welfare issues that might arise with live animal imaging studies. In many cases, explant imaging yields results indistinguishable from intravital imaging (Mempel et al., 2004a; Miller et al., 2002; Shakhar et al., 2005). Because explant studies can be performed more quickly and easily, it is useful to use this approach initially and perform a limited number of intravital experiments to validate the results. The methods described in the following sections were developed for imaging lymphoid tissues, and for simplicity we will focus on those tissues. However, with only slight modifications explant imaging can be successfully used to examine a diverse range of nonlymphoid tissues including the brain, kidney, lung, liver, stomach, gut, and bone. Although explanted preparations are often a significant improvement over existing in vitro models, it is possible that the loss of blood flow and innervation might alter host cell behavior. This was an initial criticism of explanted lymph node imaging studies (von Andrian, 2002), but cell behaviors were shown subsequently to be remarkably similar in explant and intravital preparations (Mempel et al., 2004a; Miller et al., 2002, 2003; Shakhar et al., 2005). 4.1.1. Explant imaging protocol See Matheu et al. (2007) for a video illustrating these procedures: The animal is euthanized and the tissue harvested and placed in a small Petri dish containing medium. Our laboratory uses CO2- independent medium (Gibco); most tissues remain viable for several hours stored at room temperature in this medium. Placing tissues on ice might be beneficial in some cases, but in our experience room temperature works best with lymphoid tissues. The tissue of interests is then glued to an unbreakable plastic coverslip (Fisher). Cut the coverslip to the appropriate size (i.e., big enough to hold the tissue, but small enough to fit in the flow chamber) and apply a thin layer of veterinary grade superglue (VetBond, 3M) with the small piece of paper that separates the coverslips in the box. Leave one corner uncoated for manipulating the coverslip later. To prevent rolling the sample in the glue, place the tissue on the coverslip in one smooth movement with a small pair of curved forceps. It is helpful to hold the cover slip firmly to the bench with a second pair of curved forceps placed on the unglued corner. The tissue must be placed on the coverslip within
1 min of spreading the glue or the tissue might fail to adhere properly. To prevent the excess glue on the coverslip from ‘‘shrink wrapping’’ the tissue when you place it back in the Petri dish, invert the tissue and dip it into the medium tissue side down to cure the remaining glue. Once the glue is cured, the coverslip can be placed tissue side up in the petri dish and stored at RT until imaging. In some tissues where imaging depth is limited, such as the spleen, it may be necessary to section the tissue to expose the regions of interest (Aoshi et al., 2008). Secure the spleen to a plastic coverslip with a thin film of VetBond as described previously. Section the spleen longitudinally with a

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Vibratome (Pelco) set to speed 3 and displacement 5, remove
500 mm of the overlying red pulp and expose the marginal zone and the white pulp. The angle of the blade is critical; try experimenting with different angles until sections are cut cleanly and consistently. There is concern that sectioning the spleen will damage the tissue and alter cell behavior; therefore, image white pulp regions that seem to be intact on the basis of the presence of a ‘‘cap’’ of undamaged marginal zone macrophages. The flow chamber should be set up 15 to 30 min ahead of time to allow the flow chamber to equilibrate at 37  C before imaging is started. It is important to submerge the objective into the medium to stabilize the bath temperature and prevent bubbles from forming later (i.e., when a room temperature objective is placed in 37  C medium). The ceramic surface of the objective is a good insulator and heating the objective is not necessary in most cases. We use a peristaltic pump (Watson-Marlow) to deliver media from a reservoir (500-ml round glass bottle) to the inline heater, which is attached to the flow chamber (Warner) (Fig. 16.1C). Microwave the bottle of medium first for several minutes to warm it and then maintain the temperature at 37 to 45  C with a heating blanket (place the bottle and heating blanket in a Styrofoam bucket for insulation) (Fig. 16.1C). For tissue culture media that is designed for use in a 5% CO2 incubator, we bubble carbogen gas (5% CO2, 95% O2) through an aquarium air stone placed in the reservoir (Fig. 16.1C). This serves to oxygenate the media and stabilize the pH, (i.e., dissolved CO2 is important for regulating pH in tissue culture media). There is some controversy about how much oxygen is required to maintain physiologic motility of cells, but protocols range from 20 to 95% (Germain et al., 2005; Huang et al., 2007; Miller et al., 2002). Carbogen gas has worked well in our hands, and we suspect that the amount of O2 dissolved in the medium is relatively low by the time it reaches the chamber. However, this protocol might not work well for every tissue, and the reader is advised to consult the scientific literature for additional information. We have used a variety of media to maintain the tissue during imaging. Usually what works well for tissue or organ culture will work well for explant imaging too. One notable exception is that fetal calf serum (FCS) should be left out of the media, because bubbling carbogen will cause it to froth (and create a sticky mess on the optical bench). For explant imaging, FCS is most likely unnecessary, because cells are within their native tissue environments. For lymphoid tissues RPMI (Miller et al., 2002, 2004b) or DMEM works well. For spleen explant imaging where the spleen has been sectioned with a Vibratome, we found that high-glucose DMEM minimizes tissue swelling and improves imaging results (Aoshi et al., 2008). Although we use DMEM without phenol red, it is unlikely that the indicator dye interferes substantially with imaging, because RPMI with phenol red works well in our hands. If a tissue swells or shrinks, it likely indicates that either the temperature is fluctuating or that the medium is not isotonic with the tissue. First, verify that flow of medium is constant and the heating unit is working properly.

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If this does not solve the problem, try adjusting the osmolarity of the medium (e.g., if the medium appears hypotonic and the tissue is swelling, try adding extra glucose to make the medium isotonic). In our experience, explanted lymphoid tissues remain viable for 4 or more hours, but each tissue will be different, and some tissues, such as the pancreas, are difficult to preserve. As a general rule, imaging should be limited to several hours to ensure that the images are representative of in vivo behaviors. Any wholesale decline in cell motility or loss of cell morphology could indicate that the preparation is no longer viable.

4.2. Intravital imaging Various intravital chambers (Fig. 16.1E-H) have been developed to stabilize lymph nodes for imaging and maintain blood flow and lymphatic drainage (Lammermann et al., 2008; Lindquist et al., 2004; Mempel et al., 2004a; Miller et al., 2003). These preparations maintain tissue viability for several hours based on the preservation of cell motility (a rapid decline in leukocyte motility is an indication that the tissue is no longer viable). 4.2.1. Intravital imaging protocol The mouse is anesthetized with isoflurane delivered in a stream of O2. Anesthesia is induced at 4% isoflurane, and once the animal becomes unresponsive (assessed by toe pinch), the isoflurane can be lowered to 1.5 to 2% to maintain anesthesia. Isoflurane provides stable and convenient anesthesia for most intravital imaging preparations. In particular, B6 mice respond in a highly predictable fashion and can be anesthetized with isoflurane for several hours without serious side effects. However, other strains of mice, for example BALB/c mice, can respond less predictably. The respiration rate of the mouse should be monitored closely to fine-tune the plane of anesthesia. If isoflurane does not work for a given mouse strain or preparation, injectable anesthetics might be more suitable, such as Avertin (1.2% Avertin is given i.p. at an initial dose of 0.02 ml/g, with supplemental doses of one half the initial bolus given at a frequency of
45 to 90 min) or a combination of ketamine, xylazine, and acepromazine (s.c. injection of 100 mg ketamine, 15 mg xylazine, 2.5 mg acepromazine per kg and anesthesia maintained with hourly injections of half the induction dose). To prevent the mouse from becoming dehydrated, administer PBS or saline (100 ml, s.c.) every 1 to 2 h as needed. To image the inguinal lymph node, make a midline incision in the lower portion of the abdomen with round-tipped surgical scissors. Take care not to cut through the peritoneal membrane. Gently pull away a flap of skin containing the inguinal lymph node and glue (Vetbond, 3M) a rubber O-ring (17-mm outside diameter, centered over the lymph node) on the inner side of the skin flap. Place the mouse in the imaging apparatus on top of the warming plate (35 to 36  C, to help regulate the mouse’s body temperature). Insert the O-ring into a flanged Plexiglas support and

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secure the tissue between the support and the heating platform. Be careful not to compress the tissue and cut off the blood flow to the lymph node. Seal the O-ring with petroleum jelly to prevent the objective immersion medium (PBS or saline) from leaking out. Maintain the imaging chamber temperature at 35 to 36  C with a thermistor placed in the liquid. If the lymph node is covered by a layer of fat (this is often the case for inguinal lymph nodes), the fat will severely degrade, the quality and depth of imaging. Therefore, we recommend removing the fat pad with finetipped Dumont forceps. Removing the fat should be performed carefully under a dissecting microscope to avoid breaking blood vessels or damaging the lymph node. Alternately, the lymph node can be imaged through naturally occurring ‘‘windows’’ in the fat pads that are frequently seen in young mice (
4 weeks old). To image blood vessels and assess blood flow in the lymph node, we inject i.v. or retro-orbitally 10 to 20 mg/ml tetramethylrhodamine dextran (2000 kDa, Invitrogen) or 20 ml of 655-nm nontargeted quantum dots (Invitrogen). In many cases, imaging the popliteal, inguinal or cervical lymph node is possible. The popliteal and inguinal imaging preparations have been well described (Memple et al., 2004b; Miller et al., 2003; Shakhar et al., 2005). Imaging cervical lymph nodes is advantageous, because they do not have a tightly associated fat pad and the lymphatic drainage is highly predictable (i.e., injecting the ear or nape of the neck drains to the cervical lymph nodes reproducibly). For imaging the cervical lymph nodes, our approach is essentially the same as for the inguinal lymph node preparation, except we use our intravital imaging chamber (Fig. 16.1H) (Miller et al., 2003). Make a small incision longitudinally along the throat. A small skin flap containing the cervical lymph nodes can be mobilized and inverted with the index finger and thumb. If necessary, any overlying tissue can be gently moved to the side with a fingertip or forceps while maintaining pressure from the index finger from the outer side of the skin flap. Apply VetBond to the underside of the glass coverslip of the intravital chamber (Fig. 16.1H), leaving a small ‘‘glueless’’ window in the center. Lower the coverglass over the tissue guiding the lymph node into the glueless window. Gently press the tissue into the glass until firm contact is made. The surrounding tissue will become glued to the coverglass and support the lymph node against the window. If a small amount of glue comes in contact with the lymph node, the preparation will still work; however, it is best to avoid contact as much as possible.

4.3. Imaging peripheral tissues In some cases it is possible to image in a purely noninvasive fashion such as in the ear (Matheu et al., 2008a,b; Peters et al., 2008), footpad (Zinselmeyer et al., 2008), or eye (Yeh et al., 2002). This approach is particularly useful for examining host effector responses to infection in peripheral tissues.

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4.3.1. Noninvasive imaging protocol The animal subject is anesthetized with isoflurane delivered in a stream of O2. Anesthesia is induced at 4% isoflurane, and once the animal becomes unresponsive (assessed by toe pinch), then the isoflurane is lowered to 1.5 to 2% to maintain anesthesia. During imaging experiments with live mice, the mice are deeply anesthetized with isoflurane for restraint and to minimize stress on the animal subject. The depth of anesthesia should be assessed throughout the procedure by checking for the absence of a toe pinch reflex and by monitoring the respiration rate. To secure the paw or ear to the imaging apparatus (Fig. 16.1E,G), we apply a thin film of VetBond (3M) tissue adhesive to the glass surface of the chamber and hold the tissue in place by applying gentle pressure for 10 to 15 sec or until it is securely attached. In some cases, it might be necessary to use a thin film of higher viscosity and faster drying adhesive (superglue gel) to hold the tissue. For footpad imaging, the chamber (Fig. 16.1G) is filled with PBS. For ear imaging a drop of PBS is placed between the ear and the objective and held in place by surface tension alone. This approach works particularly well for the inside surface of the ear, because the ear itself creates a natural fluid chamber. The mouse’s core body temperature is maintained by placing it on a warming pad (Braintree Scientific) set to 37  C and supplemental fluids (saline) are administered i.p. or by retro-orbital injection as needed. We inject (i.v. or retro-orbital) or 1 mg/ml dextran, tetramethylrhodamine, 2,000,000 MW (Invitrogen), or 20 ml of quantum dots to label blood vessels during imaging. In many cases, peripheral tissues can be imaged for up to 4 h without compromising the normal physiology of the tissue. Typically the mouse is euthanized while under anesthesia. However, longitudinal imaging studies are also possible with this approach, because it is noninvasive and does not harm the animal. If the mouse is to be revived for longitudinal studies, we recommend imaging for shorter periods of time (
2 h) to minimize the risk of dehydration or anesthesia overdose and imaging no more than 5 time points in 10 days.

5. Image Acquisition Carefully choosing the acquisition settings is crucial to ensure that the experiment can be successfully analyzed (Fig. 16.3). If the signal is too low, the cell density too high, or the time resolution inappropriate for the phenomena one wishes to study, then the analysis is doomed from the start. Also, the local tissue environment can have a significant impact on cell motility and function; therefore, if possible, include an internal control population of cells to compare, side-by-side, with the behavior of your cell

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Image acquisition: Cell density Brightness Color separation PMT balance Sampling rate/depth Specimen viability Photodamage

Data archiving and backup: Server with RAID 5 storage User portable hard drives Weekly institutional backup

Ag-specific

Control

70 60

8

Events

Number of objects

10

80

50

6

500

15

400 300

10

200 y = 74.465x 4 6 Time [min]

20 10 0 0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32

12345 6

12 3 4 56

Instantaneous velocity [mm/min]

Number of neighbours (< = 25 um)

Mutant

WT

30

2

8

0

40

4

100 0

5

Meandering index

Static measures: Morphology (shape, size, intensity) Cell number and distribution Co-localization Cluster analysis Neighbor analysis

Median track-velocity [mm min−1]

Cell dynamics: Velocity Meandering Arrest Turns Displacement plots Motility coefficient Interstitial transit rate Tracks

Image presentation: Maximum intensity projections Time-lapse movies Pseudocolor depth 3D rendered views Smoothing Contrast enhancement Color balance Time and scale legends

Displacement [mm2]

Data analysis

0.50 0.25 0.00

WT

Mutant

Figure 16.3 Flowchart illustrating the various considerations and procedural steps from image acquisition to analysis and the presentation of results.

of interest. Examples of internal controls include cotransferring polyclonal T cells along with antigen-specific T cells to examine antigen recognition or comparing gene-deficient and wild-type cells side by side.

5.1. Laser power and PMT gain Laser intensity and PMT gain must be set carefully to minimize photodamage to the tissue and to avoid oversaturation of the acquired images. To preserve cell viability, set the laser power (exposure dose) as low as possible and adjust the PMT gain as high as possible to optimize the signalto-noise ratio. The cells of interest should be 3 to 10-fold greater in intensity compared to the highest background level. Be careful not to saturate the signal; if pixels flare or are reading close to the maximum gray level (256 on our 8-bit acquisition system), the laser power should be reduced. If the laser power and PMT gain are properly set, cells should remain motile and viable within a 1 to 2 h imaging window. A key factor is how much laser energy

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the cells are exposed to during the experiment. For example, if images are taken every 30 sec with 15 frames averaged (0.5 sec per z-step) and 31 zsteps with
25% relative laser power (Chameleon XR tuned to 900nm), leukocytes will remain motile for the entire 1 hr imaging record. When events need to be followed over a long period of time, one can sacrifice time resolution for duration. Therefore, to image for 2 h with equivalent photodamage to 1 h, take a time point every 1 min instead of every 30 sec. This is only a general rule of thumb, and viability will vary substantially depending on the laser wavelength, the dyes used, the tissue imaged, and the cells of interest. However, we do not mean to imply that laser power and exposure duration are perfectly linearly interrelated. In our experience, cell damage seems to increase as a steep function of laser power so that, for example, a doubling in exposure time has little effect, whereas a 30% increase in power may rapidly kill cells. Keep in mind that if the cells are slow-moving or sessile (dendritic cells for example), they will accumulate more photodamage than highly motile cells or cells flowing in the circulation that are exposed to the laser for a shorter amount of time. When the experiment involves two or more colors, an attempt should be made to match the intensity of each channel. This can be accomplished by adjusting the dye conditions, adjusting the gain separately for each channel or by choosing a laser excitation wavelength to favor a dimmer fluorescent probe over a brighter one. For example, if CFSE is too bright when imaging with CMTMR, tune the 2P laser wavelength from 780 nm to 820 nm to balance the signals. The longer laser wavelength will excite CMTMR more efficiently and increase its brightness, while at the same time decrease CFSE excitation and fluorescence.

5.2. Cell density If densities are too high, it becomes difficult to unambiguously track individual cells. Conversely, although it is easy to track sparsely distributed cells, the ‘‘n’’ numbers for statistical analysis become distressingly small. It is often helpful to use different concentrations of cells in experiments for quantitative analysis versus those aimed at producing movies for presentations and online publication.

5.3. Z-series acquisition and time resolution The size of the observed volume and the number of z-planes has to be chosen carefully. The minimum distance between z-planes in the 3-D stack is set on the basis of the axial resolution of the 2P microscopy, which is typically 1.5 mm and on the thickness of the cells of interest (~4–10 mm for leukocytes). If you only want to track a cell’s position, the z-step can be quite large, the criterion being that a cell cannot ‘‘disappear’’ between

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successive planes. A larger number of z-steps will provide a larger imaging region and allow cells to be tracked for longer distances. However, the more z-planes acquired, the slower the acquisition time for the complete volume, the longer the time interval between time points and the lower the tracking precision. With a microscope scanning at video rate and 15 frames averaged for each full frame, typical volumes of 200  250  75 mm (21 z-planes, 2.5 mm/step) can be acquired at intervals of 25 to 35 sec. Averaging 10 to 30 frames at each z-plane can substantially increase the contrast of the image, but the tradeoff is that the time resolution between frames is decreased, which can cause fast-moving cells to appear stretched or be blurred in the images.

6. Multidimensional Analysis Once the data are in hand, the painstaking process begins of analyzing the data and generating plots, figures, and movies (Fig. 16.3). One good day of imaging can generate a week’s worth of analysis.

6.1. Cell detection The raw data produced by the laser-scanning microscope is a series of 3-D image stacks containing one or more fluorescence intensity channels, depending on how many different fluorophores were used in the experiment. To facilitate the analysis of cell movement and behavior, the location of cells within each 3-D image stack must be determined and the path of each cell tracked between successive time points. Within a 3-D image, fluorescently labeled cells appear as objects consisting of contiguous blocks of bright against a relatively dark background. The high-contrast ratios and the fact that cells appear as single objects with little internal ultrastructure allow simple intensity threshold–based criteria to be used to detect objects. It is important to note that bright spherical objects tend to elongate in the z-dimension. This phenomenon was described in the early days of confocal microscopy (White et al., 1987). Nevertheless, the magnitude and mechanism of elongation along the z-axis is controversial (Lee et al., 2008). This elongation is especially pronounced with 2P microscopy, because the voxel resolution in the z-axis is typically 1.5 mm or more. This phenomenon must be taken into consideration when rendering the data in 3-D and can be minimized by use of the minimum laser power necessary and avoiding oversaturating the PMTs. An intensity threshold is defined, which separates the brightly fluorescent cell from the dim background. An appropriate threshold level can be obtained by plotting an intensity profile through the midpoint of a typical cell and the surrounding background, setting the threshold midway

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between the peak cell intensity and background intensity. In most cases in which a good contrast ratio is available, slight variation in the chosen intensity threshold has little impact on cell motility measurements. However, it is worth noting that cell volume measurements will be greatly affected by threshold setting, with lower thresholds including more within the object and hence increasing the apparent volume. Once a threshold has been defined, the within each 3-D stack are classified into sets of objects, defined as contiguous groups of thresholdexceeding, within each plane and on adjacent planes within the stack. A volume-limit criterion is then usually applied so that objects below a predefined volume (e.g., single pixels and other small artifacts) are discarded. The 3-D location of a cell is typically defined as it centroid, computed as the mean location of the within the object. The volume of the object can be computed from the number of and the known dimensions of each.

6.2. Cell tracking Tracking of cells requires the identification of the object corresponding to each particular cell within the 3-D image at successive time points. This can be done manually or automatically. Although the threshold-based detection of objects is straightforward with standard algorithms, the automatic tracking of objects is more problematic. Cells can be matched between time points by a variety of criteria: volume, shape, overlapping volume, distance of separation. However, cells change shape, orientation and apparent volume between time points move in and out of the imaged volume, merge, and separate. The automatic algorithms currently available cannot be relied on to unambiguously track individual cells under all conditions with 100% reliability. Consequently, careful scrutiny of the results of automatic tracking algorithms, with the ability to manually edit or delete putative tracks, is essential. Given the need for such inspection and validation, manual tracking of objects by the user can be just as effective and no more time consuming. The two most widely used, commercially available, packages capable of the automatic detection and tracking of objects in 3-D are Imaris (Bitplane, Zurich, Switzerland) and Volocity (Improvision, Coventry, UK). We ourselves have also used an open source package PicViewer ( J. Dempster, University of Strathclyde) capable of automatic object detection and manual object tracking.

6.3. Cell and tissue morphology Although a primary application for 2P microscopy is to study single-cell motility, the 3-D nature of the technique provides several further useful measures. Simple observations such as the shape of cells (Miller et al., 2002), the

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number of cells, or the 3-D distribution of a cells in a tissue can be be highly informative. 2P microscopy can help visualize the 3-D arrangement of cells in native tissues and provide insight that is difficult to glean from fixed section imaging. Moreover, 2P microscopy can allow researchers to correlate differences in cell morphology and cell behavior between different tissue locations (Millington et al., 2007).

6.4. Cluster and neighbor analysis Under many conditions, groups of two or more cells are found clustered together, showing relatively little movement during the typical imaging period (30 to 60 min). It is difficult to investigate directly the time course of these long-lasting clusters; however, the number and size of individual motile cells and stable cell clusters found during a imaging period nevertheless provides an insight into cellular activity, with differences being readily demonstrable between different immunologic states (Zinselmeyer et al., 2005) Cell clustering can be quantified in terms of the number of cells in contact with each other or within a certain radius of each other (Gelman et al., 2009). Contact clusters appear as single objects with volumes larger than expected for single cells. With an estimate of mean cell volume obtained from single motile cells, the number of cells in each cluster can be obtained from the volume of the object and a distribution of the number of cells existing as individual cells or clusters of various sizes produced. For cells not in direct contact, clustering can be quantified in terms of the number of neighbors within a given distance of each cell. In the case of T-cell antigenrecognition events where the APC is not fluorescently labeled, a cell to cell distance threshold of between 20 and 30 mm is appropriate. When analyzing cell clustering, it is necessary to take into account that a certain number of apparent clusters can be expected by chance even in the case of totally independent cell motility. The likely number of such random clusters, which will increase with the number of cells in the imaging volume, can be estimated with simple Monte-Carlo simulations (Zinselmeyer et al., 2005).

6.5. Analysis of cell migration Once cells have been tracked and the raw data are in hand, several parameters can be used to quantitatively describe the migration behavior of the cells of interest.

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6.5.1. Velocity Cell velocity can be analyzed either as instantaneous velocity (Miller et al., 2002) or track velocity (Aoshi et al., 2008; Mempel et al., 2004a; Zinselmeyer et al., 2005). The most basic measure is ‘‘instantaneous’’ cell velocity, derived from the displacement of the cell centroid between adjacent time periods. Moreover, coarse time resolution between images can lead to an under estimate of peak cell velocities if cells velocities fluctuate rapidly. Because velocity can vary depending on the acquisition parameters. The track velocity can be obtained as the median or mean instantaneous velocity computed from all time intervals throughout a track, typically 6 to 14 time points at 20- to 50-sec intervals. The instantaneously velocity can be easily computed for all cells within the imaging volume for pairs of adjacent time points, and the velocity distribution plotted as a histogram. Because some cells are very fast and transit the imaged area very quickly, it is difficult to track them so they are not included in the tracks, but they can still be a large part of the population; for this reason it makes sense to report instantaneous velocity (which is usually faster) as well as track velocity. 6.5.2. Displacement plot The displacement from an initial position of an object moving with a constant velocity but randomly changing direction can be shown to be on average linearly proportional to the square root of the elapsed time (Wei et al., 2003). A plot of mean displacement for a cell (or group of cells) vs time1/2 (or more correctly displacement2 vs time) provides an indication of whether cells are following random trajectories or are moving in a more directed fashion (neutrophil chemotaxis toward bacteria for instance). If cell movement is approximately a random walk, this plot yields a straight line on displacement2 vs time, whereas directed motion will yield an upwardly curved plot. The linearity of the displacement plot can be estimated by fitting a straight line with linear regression and inspection of the goodness fit from the square of the correlation coefficient, R2. 6.5.3. Motility coefficient The slope of the fitted line on a displacement2 vs time plot provides an estimate of the rate of random cell motion, with larger slopes indicating faster motion and greater displacement over any given period of time. By analogy with the diffusion coefficient of molecules, this has also been expressed as the 3-D motility coefficient Eq. (16.1) (Wei et al., 2003).

D¼

slope2 6

ð16:1Þ

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There is some confusion in the literature as to the correct form of the motility coefficient. The correct divisor is 4 if measurements were made only in 2D, and 6 if in 3D. The ‘motility coefficient’ should come out the same for both cases as cell motility is isotropic. In some cases, it may be simpler to report the slope of displacement vs time1/2. For directed migration, a plot of displacement vs time with a similarly fitted straight line can be useful (Graham et al., 2009). 6.5.4. Transit rate For cells displaying a strong persistence of motion (i.e., continuing to move in the same direction), cell displacement from the origin over time (distance/time) is linear over long intervals. The slope of a linear regression line is equivalent to the cell interstitial transit rate. This descriptive parameter can be used to predict how long cells (e.g., neutrophils) will take to migrate from one location in the tissue (the blood vessels) to another area (site of bacterial infection). The transit rate is a robust parameter and can be compared between different experiments with different time settings as long as data for several positions of the same cell are available over a longer time interval (typically a minimum of 4 positions over 6 min). If cells are moving randomly, the motility coefficient is more appropriate to describe cell migration (see earlier). Both motility coefficient and transit rate can be compared even if calculated from samples with different acquisition times. 6.5.5. Arrest coefficient This value is calculated as the ratio of the time cells are moving or not moving (instantaneous speeds <2 mm min1/2) vs the total time the cell is observed. The arrest coefficient is sensitive to the time interval of the experiment, because cell motility might be intermittent (i.e., with more frequent sampling, fewer arrested cells will be detected), and care must be taken to ensure that the sampling rate is the same when different groups are being compared. Considering that the arrest coefficient is calculated from cell tracks, the value reported will only represents a percentage of cells in the entire population. 6.5.6. Turning angle The cell turning angle is the angular (180 to þ180 ) change in direction of cell motion within the plane defined by the locations of the cell within three successive images (Mempel et al., 2004a). The distribution of turning angles provides an estimate of the directedness of cell motion. A cell exhibiting completely random motion would exhibit an even distribution of turning angles. Nonrandom or directed cell motion will show show an over abundance of prefered turning angles. Cell motility is influenced by turning angle and the instantaneous cell velocity, with motility being directly proportional to velocity and inversely proportional to turning angle. An example of a reduction in cell motility mediated by increased

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turning angle rather than change in velocity can be seen in Mempel et al. (2004a). Finally, as for instantaneous velocity, the estimate of turning angle is very dependent on the image stack acquisition interval. 6.5.7. Meandering index The meandering index for a cell track is computed as the displacement between the initial and final points on each the track divided by the total length of the random path. It provides another index of the directedness of cell movement. Cell movement in a straight line between the initial and final points, with no deviations, will yield a meandering index of 1. The more the track deviates from the straight line path, the lower the index value. Cells exhibiting frequent angle changes will produce tracks with lower meandering indices.

7. Presentation of 2P Microscopy Images Presenting multidimensional data in an intelligible and convincing manner can be challenging, especially considering that our primary form of scientific communication is essentially a 2-D printed page.

7.1. 2-D images The most common method for presenting 3-D z-stacks in 2-D is to create a maximum intensity projection (MIP) in the z-dimension. Maximum intensity projections can also be created along the x or y axis to show orthogonal views of 3-D–rendered images. The problem with this presentation method is that details are often obscured by fluorescence above or below the object of interest. A common solution is to show the z-stack as a sequence of images. Because individual z planes are shown, image details that were lost in the MIP are revealed and object colocalization can be easily confirmed in 3-D (x, y, and z or the thickness of the section). An alternate method for presenting 3-D information on a 2-D page is to assign colors to different depths in the image, essentially color-encoding depth (Miller et al., 2003). Z-sections or groups of z-sections are pseudocolored blue, green, and red and slightly overlapped to create color scale that is useful for approximating a cell’s position in 3-D space from a maximum intensity projection. This technique is limited by the number of colors available to encode the z-steps. However, it can be used to discriminate between colocalized cells and cells that are actually separated in the z-dimension but appear to be in contact because they overlap in the x- and y-dimensions.

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It is important to include scale bars or measured grid lines and time stamps in the images whenever possible. This provides essential context for the reader and facilitates comparisons between different published studies. Most analysis programs contain dialogs for image contrast enhancement, color balancing, smoothing, and more. If used judiciously, image enhancement can help highlight key features of the image making them easier to interpret. However, there is always danger that overly manipulated images can obscure important details and bias the scientific interpretation. The best approach is that when image enhancement is required, use linear contrast enhancement methods (avoid manipulating the gamma) and standardize the process across experimental groups. As a general rule, it is best to present data with as little digital processing as possible. Different smoothing algorithms can substantially affect the resulting image. If objects of interest are approximately spherical (e.g., an arrested lymphocyte), a Gaussian filter will work well to remove noise. On the other hand, if the object has more complex features, such as the fine processes of dendritic cells or collagen fibers, then a median filter will be better for enhancing the image without smoothing away important details. Most software programs have tutorials that will guide you through the process of selecting the proper filtering method for your images.

7.2. Cell tracks Displaying cell tracks is a useful method for conveying qualitatively how a cell moves in the tissue. Cell tracks can be traced over a series of time-lapse images to show the paths of specific cells in the experiment. Individual cells can be shown with different colored lines, and points representing the cell’s center of mass provide information about how fast the cell is moving and whether the movement is fluctuating or constant. Alternately, cell tracks can be normalized to their starting positions and overlaid on coordinate axes (Miller et al., 2002). This presentation is especially useful for displaying random cell migration. The reader can see quickly multiple representative cell tracks and gain a sense of whether the paths are straight, curved, disjointed, or a heterogeneous mixture. This same plot can suggest that cell migration is constrained or has a directional bias. Okada et al. (2005) used cell track plots from different regions to show that the migration of antigen-specific B cells changed from random to highly directed (consistent with chemotaxis) near the follicular boundary.

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7.3. 3-D rotations and time-lapse movies Presenting multidimensional data has become easier as many journals now host supplemental movies on their web sites to support published work. In general, it is useful to start with a written description of the phenomena accompanied by a supplemental movie so that the reader has an opportunity to grasp the overall 3-D structure or behavior of interest. Popular formats include QuickTime and AVI, which strike a good balance between the need for sufficient resolution with the need for the file to be small enough for download from a web site. We typically smooth and contrast-enhance the movies to bring out the elements of interest. This should not be done on the primary data (this could affect the analysis), but on a duplicate data set used only for presentation purposes. Annotations such as a scale bar and time stamp are highly recommended. If possible, identify the cell or behavior of interest by circling or placing arrows in the movie. The more annotation the movie has the easier it is for the reader to understand what you are attempting to show. Figure captions should give details about the time and spatial resolution of the images and general information regarding any digital enhancements that were made.

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Zymosan-Induced Peritonitis as a Simple Experimental System for the Study of Inflammation Jenna L. Cash, Gemma E. White, and David R. Greaves Contents 1. Introduction 1.1. Acute and chronic inflammation 1.2. Peritoneal models of acute inflammation 1.3. Advantages of the zymosan-induced peritonitis (ZIP) model 1.4. Applications of the ZIP model 2. Materials 3. Methods 3.1. Pretreatment with antiinflammatory agents and induction of inflammation 3.2. Lavaging the peritoneal cavity 3.3. Cell counting and FACS staining to determine cellular composition 3.4. Alternate protocol—determining cellular composition by cell and nuclear morphology 3.5. Data calculations 3.6. Exclusion criteria after peritoneal lavage 4. Expected Results 4.1. Leukocyte recruitment 4.2. Inflammatory mediators 5. Other Considerations 5.1. Dose of zymosan 5.2. Gr-1 or Ly-6G? Acknowledgments References

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Abstract The acute inflammatory response occurs as a result of tissue injury or infection and is characterized by the coordinated recruitment of leukocytes in response to inflammatory mediators including chemokines. This process generally resolves within a matter of days, and normal tissue architecture is restored by a process of wound healing. Failure to resolve the injury can result in chronic inflammation. Much of our understanding of the specific mediators and cell types involved in acute inflammation has come from sterile peritonitis models. The injection of a wide range of irritants into the peritoneal cavity induces the hallmarks of inflammation, including pain, leukocyte infiltration, and synthesis of inflammatory mediators. Intraperitoneal injection of zymosan, a polysaccharide cell wall component derived from Saccharomyces cerevisiae, has been widely used as a self-resolving model of acute inflammation that peaks within a few hours and is cleared within 48 to 72 h. We have used the zymosan-induced peritonitis model extensively to quantify the recruitment of monocytes and neutrophils into the peritoneal cavity and to study the effects of existing and novel antiinflammatory drugs. We discuss some of the applications and advantages of the zymosan-induced peritonitis model and describe the method for analysis of leukocyte recruitment and inflammatory mediator production in response to zymosan.

1. Introduction 1.1. Acute and chronic inflammation Inflammation is the response of vascularized tissues to injury, irritation, and infection. In most cases, the inflammatory response is successfully resolved, and, where necessary, a process of wound healing is initiated. Acute inflammation is most often associated with a neutrophil-rich cellular infiltrate and is generally resolved in a period of days, whereas chronic inflammation is characterized by a cellular infiltrate containing many more mononuclear cells (monocyte/macrophages and lymphocytes) (reviewed in Medzhitov [2008] and Nathan [2002]). Chronic inflammation continues for weeks or years and is characterized by continuing leukocyte recruitment, often leading to irreversible tissue remodeling, tissue damage, and loss of function. Good examples of this disease process are provided by rheumatoid arthritis and chronic asthma (for reviews see Firestein [2003] and Galli et al. [2008]). The cardinal signs of inflammation (pain, redness, heat, and swelling) have been recognized for nearly two millennia, but it was only in the late twentieth century that the identity of the molecules that mediate the histologic and physiologic changes seen in acute inflammation were identified (Majno and Joris, 1996). Investigating the role of individual inflammatory

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mediators in acute inflammation, including complement proteins (Forrest et al., 1986), prostaglandins (Velo et al., 1973), leukotrienes (Lefkowith, 1988), cytokines (Fantuzzi et al., 1997), and chemokines (Ajuebor et al., 1998), has been greatly aided by the availability of simple models of sterile peritonitis, which allow the accurate quantitation of leukocyte recruitment into an easily accessible serosal cavity. More recently, sterile peritonitis models have proved useful for the analysis of animals in which specific inflammatory mediators or their receptors have been ablated genetically or targeted by neutralizing antibodies (Mack et al., 2001; Wengner et al., 2008). Experimental peritonitis models have, therefore, proved an indispensable tool for the explanation of acute inflammatory processes, the mechanisms of action of antiinflammatory drugs, and are increasingly being used to test novel antiinflammatory therapies, including antichemokine and antichemokine receptor strategies (Bursill et al., 2003; van Wanrooij et al., 2008). As we will discuss in the following, sterile peritonitis models have also allowed the study of novel endogenous antiinflammatory pathways (Arita et al., 2005; Cash et al., 2008; Chatterjee et al., 2005).

1.2. Peritoneal models of acute inflammation Infectious peritonitis provoked by the injection of pathogens into the peritoneal cavity has been used as a model to study innate immunity and acute inflammation since the time of Mechnikov (Mechnikov, 1892). However, infectious peritonitis models are hard to control, because the exact time course of the inflammatory response depends on both the pathogenicity and growth rate of the specific microorganisms used and the magnitude and efficacy of the host immune response. Certain infectious peritonitis models, such as the cecal ligation and puncture (CLP) model, have been developed to mimic the polymicrobial sepsis most commonly encountered in the clinic (Ness et al., 2003; Rittirsch et al., 2007). However, sterile peritonitis is sometimes observed clinically, for example, after leakage of sterile body fluids into the peritoneal cavity after surgery. Thus, experimental animal models can be used to study specific aspects of the pathophysiology of peritonitis as it presents in the clinic, but these models are most useful for illuminating the general mechanisms of inflammation and testing novel antiinflammatory strategies. The intraperitoneal injection of a wide range of irritants, including thioglycollate broth (Chen et al., 2008; Henderson et al., 2003), polyacrylamide beads (Bursill et al., 2003), and inflammatory cytokines such as IL-1 (Paul-Clark et al., 2004), leads to an acute inflammatory response that peaks within hours. Injection of zymosan, the insoluble polysaccharide cell wall component derived from Saccharomyces cerevisiae, has been widely used as a self-resolving model of peritoneal inflammation in mice (Rao et al., 1994),

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rats (Zagorski and Wahl, 1997), and rabbits (Forrest et al., 1986). Intraperitoneal injection of zymosan in mice was first described by Doherty et al. (1985), and the authors reported that zymosan injection induced all the hallmarks of acute inflammation, including pain, leukocyte infiltration, and synthesis of inflammatory mediators including leukotrienes and prostaglandins (Doherty et al., 1985). These experiments stemmed from the finding that incubation of zymosan with peritoneal macrophages in vitro led to generation of arachidonic acid metabolites (Rouzer et al., 1980; Scott et al., 1980). Indeed, one of the advantages of this model is that it provides a direct analog of many of the features observed in vitro after macrophage treatment with zymosan. Macrophage recognition of unopsonized zymosan in vitro is mediated by the b-glucan receptor dectin-1 (Brown et al., 2002); whereas collaborative signaling from TLR2 by an MyD88-dependent signaling pathway leads to the generation of inflammatory mediators (Brown et al., 2003). Peritonitis experiments in knockout animals demonstrated that dectin-1 is also critical for zymosan recognition in vivo, and absence of dectin-1 led to impaired recognition of fungi and uncontrolled fungal infection (Taylor et al., 2007).

1.3. Advantages of the zymosan-induced peritonitis (ZIP) model There are several advantages to the use of zymosan over other peritoneal inflammagens or the use of alternative models of inflammation. First, the mild-to-moderate severity of the inflammatory insult (which can be varied with the dose of zymosan; see Fig. 17.4) means that inflammation selfresolves within 48 to 72 h, mimicking the normal inflammatory response of an immunocompetent individual. Second, injection of inflammatory agents such as zymosan into the peritoneal cavity (rather than other sites [e.g., the skin, the paw, or the GI tract]) allows collection of a reasonable quantity of exudate for the analysis of multiple inflammatory mediators. Third, injection into a serosal cavity rather than an artificially created cavity such as a sterile air pouch means that leukocytes exit from the site of inflammation by way of their natural conduits to the draining lymph node (Bellingan et al., 1996; Schwab et al., 2007). Finally, the relative technical simplicity and reproducibility of this model enables it to be used by a wide range of researchers. In addition, because peak neutrophil levels occur within 4 h of a 10-mg zymosan injection, data can be generated and analyzed within a short time frame.

1.4. Applications of the ZIP model Peritonitis models have been used extensively for quantitative studies of leukocyte recruitment and to identify the key inflammatory mediators involved. Ajuebor et al. have used the ZIP model to study the role of

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cytokines and chemokines in inflammation (Ajuebor et al., 1998, 1999a,b). The monocyte chemoattractant MCP-1 ( JE/CCL2) was shown to be generated in a time-dependent manner after zymosan injection that preceded the influx of monocytes into the peritoneal cavity. Furthermore, blockade of MCP-1 with a neutralizing antibody attenuated this inflammatory response, whereas administration of recombinant MCP-1 recapitulated the leukocyte recruitment seen in response to zymosan, suggesting a key role for this chemokine (Ajuebor et al., 1998). ZIP experiments have also been used to demonstrate the role of specific cell types in inflammation. Depletion of mast cells (with the compound 48/80) inhibits leukocyte accumulation and chemokine production; whereas resident macrophage depletion (with dichloromethylene-bisphosphonate) augments the recruitment of leukocytes in response to zymosan (Ajuebor et al., 1999a). Moreover, selective pharmacologic depletion of resident mast cells and macrophages revealed a crucial role for both cell types in mediating increased vascular permeability in response to zymosan (Kolaczkowska et al., 2002). In a recent publication with RAG knockout animals, the absence of lymphocytes was shown to have no effect on neutrophil accumulation or vascular permeability in ZIP (Kolaczkowska et al., 2008). Thus, this model facilitates an understanding of the role of specific mediators and cell types in inflammation. Furthermore, ZIP provides a useful assay for the phenotyping of transgenic mice. Defects or enhancement of inflammatory responses after gene deletion or overexpression can be assessed rapidly over hours/days. Deletion of the leukotriene B4 receptor (BLTR), for example, led to a significant reduction in peritoneal neutrophil influx in response to zymosan, confirming a key role for this mediator in neutrophil recruitment (Haribabu et al., 2000). Deletion of the protein annexin 1 (AnxA1/lipocortin), however, enhanced neutrophil recruitment in ZIP, confirming its role as an endogenous antiinflammatory mediator (Chatterjee et al., 2005). Finally, perhaps the most useful application of ZIP experiments is the testing of new antiinflammatory compounds. In the initial description of this model Doherty et al. (1985) demonstrated that the antiinflammatory drugs indomethacin and phenidone were effective in reducing leukocyte infiltration and prostaglandin synthesis in response to zymosan (Doherty et al., 1985). Recently, investigators have begun to appreciate that both the magnitude and the duration of the host response to zymosan is regulated by endogenous lipid (Serhan et al., 2008) and peptide mediators (Cash et al., 2008). Work from the laboratory of Charles Serhan followed the production of novel arachadonate metabolites in the zymosan peritonitis model and identified a novel mediator, resolvin E1, as a molecule produced during the course of acute inflammation (Serhan et al., 2000). Chemically synthesised resolvin E1 was then shown to have potent antiinflammatory effects in both ZIP and TNBS-induced acute colitis (Arita et al., 2005). ZIP has also been used to study the production of haematopoietic prostaglandin D2

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synthase (hPGD2S) metabolites in both wild-type and hPGD2S knockout mice and demonstrate their role in the resolution of inflammation (Rajakariar et al., 2007). Furthermore, work from our own laboratory has shown that peptides derived from the plasma protein chemerin have potent antiinflammatory properties in the ZIP model (Cash et al., 2008). Intraperitoneal injection of chemerin-neutralizing antibodies with in vitro activity against both full-length chemerin and chemerin-derived peptides before zymosan challenge significantly increases both neutrophil and monocyte recruitment at 4 and 24 h in the ZIP model. Taken together, these experiments show the usefulness of the zymosan peritonitis model to both identify and characterize novel endogenous antiinflammatory pathways in vivo (Yoshimura and Oppenheim, 2008). In the following sections, we detail the materials and methods that we have successfully used to quantify recruitment of neutrophils and monocytes into the peritoneal cavity in response to zymosan. We also include examples of how ZIP can be used to study the effect antiinflammatory agents have on leukocyte recruitment and chemokine production.

2. Materials All animal studies should be conducted with local ethical approval and in accordance with national regulations (in the UK, following the Home Office Guidance on the Operation of Animals, Scientific Procedures Act, 1986). Antiinflammatory compound storage: If the molecule is a peptide or protein, manufacturers’ instructions normally recommend reconstitution with sterile PBS supplemented with 0.1% (w/v) low-endotoxin BSA (Sigma Aldrich). Peptides are normally stable for 6 mo when stored at
20  C, whereas proteins can generally be stored for 1 to 2 y. Lipids, however, are much less stable and require reconstitution in ethanol or DMSO. Fresh working solutions should be prepared for each in vivo experiment. Zymosan from Saccharomyces cerevisiae (Sigma Aldrich): Zymosan should be stored at 4  C and fresh working solutions prepared for each in vivo experiment. Zymosan suspensions require vigorous mixing to ensure even distribution of zymosan particles. Vehicle for antiinflammatory and zymosan solution: Sterile low-endotoxin PBS should be used for peritonitis experiments (Lonza). Syringes for injection: We recommend Micro-Fine 29G  12.7-mm diabetic syringes (Becton Dickinson). Washing solution for peritoneal lavage: 2 mM EDTA (Lonza) in sterile PBS, can be stored at 4  C for up to 2 weeks.

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Trypan blue (0.4%) solution (Sigma Aldrich). 1% Formalin: formaldehyde 1% v/v in PBS. FACS Buffer: 5% (v/v) heat-inactivated rabbit sera (Invitrogen, heat inactivated at 56  C for 30 min), 0.5% (w/v) BSA, 5 mM EDTA, 2 mM NaN3 in PBS. This is stored at
20  C until required. Fc-receptor blocking antibody: Rat anti-mouse CD16/CD32 (FcgRII/III) (clone 2.4G2, AbD Serotec). Anti-7/4-FITC (AbD Serotec, catalogue number MCA771F) and antiLy-6G-PE (clone 1A8, BD Pharmingen, catalogue number 551461). Optional (for determining cellular composition by nuclear morphology) HemacolorÒ rapid staining set, VWR.

3. Methods 3.1. Pretreatment with antiinflammatory agents and induction of inflammation Published ZIP experiments from our laboratory have involved injection of antiinflammatory compounds 1 h before the i.p. injection of zymosan (Cash et al., 2008). The time used for this pretreatment depends largely on the mode of action of the antiinflammatory compound used. The procedure for administration of antiinflammatory compounds and zymosan is as follows. Dilute the candidate antiinflammatory agent in sterile PBS to produce the required dose in 0.5 ml of PBS. Scruff the mouse firmly and inject 0.5 ml of antiinflammatory agent into the peritoneal cavity with a 12.7-mm 29-G needle. Take care to avoid injuring the intestines or liver, because this can result in bleeding and the need to discard the lavage sample because of contamination with circulating leukocytes. Dissolve 10 mg zymosan from Saccharomyces cerevisiae in 50 ml sterile PBS then dilute 1 in 10 to obtain a 20 mg/ml working solution. Up to 1 h after injection of antiinflammatory compound, inject 0.5 ml zymosan i.p. (10 mg/mouse peritoneal cavity; mix zymosan immediately before injection to ensure an even suspension) with a 12.7-mm 29-G needle. Note: We use 10 mg zymosan per mouse peritoneal cavity; however, some researchers use higher doses (see Fig. 17.4).

3.2. Lavaging the peritoneal cavity The peritoneal cavity is lavaged 0 to 48 h after injection of zymosan; see Section 4.1 for a detailed discussion of the kinetics of leukocyte recruitment.

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Sacrifice mice by exposure to a rising concentration of carbon dioxide and confirm death by cervical dislocation. Make a small (0.5 cm) incision along the midline of the abdomen allowing the skin to be pulled back to expose the abdomen, which is then sprayed with 70% ethanol. Inject 5 ml ice-cold PBS/2 mM EDTA washing solution with a syringe and 5/8-inch 25-G needle. Gently massage the mouse abdomen with the length of a 2-inch 19-G needle to ensure that cells that are loosely adherent to the peritoneal wall or other organs will detach and become suspended in the lavage fluid. Use a 19-G needle to gently and slowly extract the lavage fluid from the peritoneal cavity. Transfer the fluid to a 15-ml centrifuge tube and keep on ice. Note: The peritoneal cavity has a large dead volume, meaning that only a portion of the washing solution will be retrieved, typically 4 ml lavage fluid is recovered out of 5 ml PBS/EDTA injected. However, only a 200- to 300-ml sample is required for FACS staining and a further cell-free 500 ml stored at
80  C for use in Luminex assays or ELISAs. For other applications such as mass spectroscopy for eicosanoids, it may be necessary to lavage with smaller volumes of PBS-EDTA.

3.3. Cell counting and FACS staining to determine cellular composition With a hemocytometer and trypan blue count the cells in 20 ml of lavage fluid diluted into 50 ml trypan blue þ 30 ml PBS. Centrifuge 200 to 300 ml lavage fluid at 4  C for 5 min at 1000 rpm. Remove supernatant and resuspend cell pellet in residual washing solution by flicking the microcentrifuge tube. Block Fc receptors with 50 ml FACS buffer containing 2.5 mg/ml antimouse 2.4G2 FcgRII/III for 5 to 10 min on ice. Stain cells for 10 to 15 min on ice and in the dark with 50 ml FACS buffer containing 4 mg/ml PE-conjugated anti-mouse Ly-6G and 10 mg/ml FITC-conjugated anti-mouse 7/4. Fix cells with 300 ml 1% (v/v) formalin. It is important to flick the tube before fixing and throughout staining to ensure thorough mixing of solutions and removal of cell clumps. Store FACS samples at 4  C in the dark until analysis can be performed, and not longer than 48 h. For FACS analysis, cells are initially gated with forward and side scatter to exclude cell debris. This gated population is then interrogated: construct gates around two populations, the neutrophils (7/4high, Ly-6Ghigh) and inflammatory monocytes (7/4high, Ly-6Glow; Fig.17. 2), and record the percentage of cells falling within each gate.

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In addition, centrifuge 500 ml lavage fluid at 4  C for 5 min at 1000 rpm, transfer supernatant to a new microcentrifuge tube and store at
80  C for future chemokine/cytokine analysis. Note: The neutrophil differentiation antigen 7/4 shows polymorphic expression on inbred mouse strains: neutrophils from C57BL/6 mice have high levels of 7/4 antigen, whereas other strains, for example BALB/C, have undetectable levels of 7/4 antigen (Hirsch and Gordon, 1983). Thus, this FACS method for enumerating neutrophils may not be suitable for all mouse strains.

3.4. Alternate protocol—determining cellular composition by cell and nuclear morphology Staining with methylene blue and eosin or hematoxylin and eosin enables distinctions between leukocytes to be made through differences in cell and nuclear morphology. Monocytes/macrophages are distinguished by their kidney-shaped nucleus and large cytoplasm. Neutrophils are apparent from their multilobed nucleus and much smaller cytoplasm than monocytes and macrophages. Lymphocytes are easily identifiable from their spherical nucleus and very small cytoplasm.

3.5. Data calculations To calculate the number of peritoneal exudate cells (PECs) per ml of lavage fluid

X ðcells=mlÞ ¼ N  5  104

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Where X is derived from Eq. (17.1) and 5 is the volume of washing solution added per cavity in ml. To calculate the number of neutrophils/monocytes per cavity

Z ðnumber of monocytes=neutrophils per cavityÞ ¼ %monocytes=neutrophils  Y

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Where Z is the percentage of monocytes and neutrophils present obtained from FACS analysis (see step 8 above), and Y is derived from Eq. (2).

3.6. Exclusion criteria after peritoneal lavage The most frequently used exclusion criterion is blood contamination in the lavage fluid. The peritoneal cavity is highly vascularized; therefore, there is a substantial risk of producing a blood-contaminated sample. Touching the liver or intestines during i.p. injection can lead to blood being present in the sample. Blood-contaminated samples should be discarded, because even a relatively small amount of blood can grossly affect the leukocyte count in the lavage fluid. Good i.p. injection technique is essential for reliable and robust data to be obtained with this model of inflammation. Therefore, any injection errors noticed at the time of injection should be noted, and these animals excluded from the study. Injection errors include obvious subcutaneous localization of substance being injected or a substantial volume of injected fluid leaking back out of the injection site. Bleeding at the site of injection: This is rare, and bleeding is generally caused by severing cutaneous blood vessels rather than an inherent problem with the injection technique.

4. Expected Results 4.1. Leukocyte recruitment Administration of zymosan i.p. produces a time-dependent extravasation of inflammatory cells into the peritoneal cavity, which follows the typical profile of an acute inflammatory response. Unless otherwise stated, all data discussed refer to the use of a 10-mg dose of zymosan. Neutrophils are the first leukocytes to infiltrate the cavity, detectable at 2 h post-zymosan with peak neutrophilia occurring at 4 h (1.95  106 cells; Fig. 17.1 A and C and Fig. 17.2). Monocyte influx into the inflamed cavity is first detectable after 4 h (0.69  106 cells), peaking at 24 h post-zymosan injection (1.25  106 cells) and declining thereafter (Fig. 17.1 B and D and Fig. 17.2). ZIP selfresolves 48 h after a 10-mg zymosan challenge. To follow the peritoneal inflammation throughout its duration, peritoneal cavities are typically lavaged 0 h (to provide a baseline), 2, 4, 8, 16, 24, and 48 h after zymosan challenge. Inflammatory monocytes that have recently been recruited to the peritoneal cavity are 7/4high, Ly-6Glow, F4/80low. However, as they mature into macrophages (MFs) 7/4 expression decreases, resulting in a ‘‘smeared’’

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population of monocytes/MFs on the 7/4 vs Ly-6G FACS plot (Fig. 17.2; [Gordon and Taylor, 2005; Taylor et al., 2003]). F4/80 expression is upregulated as monocytes mature into MFs (Taylor et al., 2003); therefore, any scientist wishing to focus on monocyte/MFs levels during the latter points of peritoneal inflammation may wish to stain for 7/4 vs F4/80 in addition to 7/4 vs Ly-6G.

4.2. Inflammatory mediators With a Luminex multiplex assay or ELISA kits, cytokine and chemokine levels in peritoneal lavage fluid can be assessed at the 4 h time point. The inflammatory cytokines TNFa (4 ng/cavity), IL-12 p40 (500 pg/cavity), and IL-1b (400 pg/cavity) are easily detectable at this time point, as is the neutrophil chemoattractant KC/CXCL1 (300 pg/ml) and the monocyte chemotactic agent JE/CCL2 (3 ng/ml; Fig. 17.3). Suppression of inflammatory cytokine expression is obviously an important endpoint when testing a novel antiinflammatory agent, because it indicates a dampening of the inflammatory response. Following the expression of chemoattractant proteins can provide some insight into the mechanism by which leukocyte levels may be altered by an inflammagen or an antiinflammatory drug. We find the 4 h time point useful because both monocytes and neutrophils are present in the peritoneal cavity in significant numbers, and several important cytokines and chemokines are easily detectable in the lavage fluid (Fig. 17.3). With respect to characterizing a novel antiinflammatory agent, a number of parameters can be assessed. Number of monocytes and neutrophils in the peritoneal cavity and, therefore, percentage suppression of inflammatory cell recruitment Rate of monocyte and neutrophil influx into the peritoneal cavity Time at which peak neutrophil and monocyte levels occur Time at which inflammation resolves Expression of inflammatory cytokines and chemokines within the peritoneal lavage fluid Figure 17.1 Neutrophil and monocyte recruitment into the peritoneal cavity after zymosan challenge. C57Bl6/J mice were dosed i.p. with zymosan (10 mg in 0.5 ml PBS, 2 106 particles per cavity). Peritoneal exudate cells (PECs) were harvested by peritoneal lavage at multiple time points (A) and (B) or after 4 h (C) and (D). Total PECs were quantified and cellular composition (neutrophils vs monocytes) determined by FACS analysis as described in the text. Gates were constructed around two populations, the neutrophils (7/4high, Ly-6Ghigh) and monocytes (7/4high, Ly-6Glow). (A) and (B) Shown as mean  SEM. (C) and (D) Show individual animal data, with the mean shown as a solid line.

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Total peritoneal mediator (pg)

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Figure 17.3 Peritoneal cytokine and chemokine levels 4 h after zymosan challenge. C57Bl6/J mice were dosed i.p. with zymosan (10 mg in 0.5 ml PBS, 2  106 particles per cavity). Peritoneal exudate cells (PECs) were harvested by peritoneal lavage 4 h after i.p. zymosan administration. Cell-free peritoneal lavage fluid was assayed forTNFaKC, IL-6, IL-1b, and JE by Luminex assays and ELISAs.

5. Other Considerations 5.1. Dose of zymosan The ZIP model is a widely used and well-characterized experimental system. However, the dose of zymosan administered per mouse peritoneal cavity varies in the literature from 1 mg/cavity to 1 mg/cavity. We routinely use a dose of 10 mg/cavity (1 to 2 zymosan particles per resident MF), because recent data suggest that administration of high doses of zymosan results in activation of additional inflammatory pathways, and, indeed, the expression profile of inflammatory cytokines and chemokines is altered in concordance with this (Fig. 17.4). It is postulated that high zymosan doses such as 1 mg/cavity (equivalent to 200 zymosan particles per resident MF) can overwhelm the resident peritoneal MFs, leading to irritation of the cavity and activation of mast cells. The CC chemokine RANTES/ CCL5 (monocyte and T cell chemoattractant) is not detectable in the lavage fluid of mice administered 10 mg zymosan i.p.; however, when the dose is increased to 1 mg zymosan/cavity, substantial levels of RANTES are present in the lavage fluid (Fig. 17.4D). The neutrophil chemoattractant, KC is expressed at the 4 h time point in response to 10 mg zymosan; however, a 1-mg dose of zymosan results in more than a 10-fold increase in KC levels (>3 ng/cavity at 4 h time point, Fig. 17.4C). By use of a lower dose of zymosan, such as 10 mg/peritoneal cavity, it is likely that we are looking at a simpler model of inflammation and possibly one that more closely represents a minor pathogen in vivo that self-resolves within 48 h.

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Figure 17.4 Peritoneal leukocyte numbers and expression of chemokines in response to administration of a range of zymosan doses. (A-D) C57Bl6/J mice were dosed i.p. with 0 mg zymosan (PBS), 10, 100, and 1000 mg zymosan. Peritoneal exudate cells (PECs) were harvested by peritoneal lavage 4 h after zymosan administration. Total PECs were quantified and cellular composition (neutrophils; [A] and monocytes [B]) determined by FACS analysis as described in the text. Cell-free peritoneal lavage fluid was assayed for KC [C] and RANTES [D] expression by ELISA.

Neutrophil and monocyte recruitment 4 h after i.p. administration of 0, 10, 100, and 1000 mg zymosan is shown in Fig. 17.4A and B. Injection of 1 mg zymosan leads to massive recruitment of neutrophils into the peritoneal cavity after 4 h and induces peritoneal inflammation that takes at least 96 h to resolve (Bannenberg et al., 2005; Damazo et al., 2006).

5.2. Gr-1 or Ly-6G? There has recently been some controversy over the use of the antigranulocyte receptor-1 (Gr-1) mAb, RB6-8C5. RB6-8C5 has been extensively used in vivo to deplete neutrophils; however, RB6-8C5 binds to Ly-6G and Ly-6C. Ly-6G is present on neutrophils, whereas Ly-6C is expressed on

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subpopulations of monocytes, lymphocytes, and dendritic cells in addition to its expression on neutrophils (Daley et al., 2008). It is, therefore, likely that FACS staining with anti-Gr-1 and anti-7/4 mAbs results in the detection of Ly-6C-positive monocytes as well as neutrophils. Indeed, Hogg et al. have directly compared clone 1A8, which binds Ly-6G to RB6-8C5, and have shown that when anti-Gr-1 is used instead of anti-Ly-6G antibody the monocyte and neutrophil populations come close to merging because of presence of a Ly-6C positive subpopulation of monocytes (Henderson et al., 2003). Care should, therefore, be taken to ensure that Ly6G staining is performed with the 1A8 mAb.

ACKNOWLEDGMENTS Work in the Greaves Laboratory is funded by the British Heart Foundation. The authors have no conflicts of interest.

REFERENCES Ajuebor, M. N., Das, A. M., Virag, L., Flower, R. J., Szabo, C., and Perretti, M. (1999a). Role of resident peritoneal macrophages and mast cells in chemokine production and neutrophil migration in acute inflammation: Evidence for an inhibitory loop involving endogenous IL-10. J. Immunol. 162, 1685–1691. Ajuebor, M. N., Das, A. M., Virag, L., Szabo, C., and Perretti, M. (1999b). Regulation of macrophage inflammatory protein-1 alpha expression and function by endogenous interleukin-10 in a model of acute inflammation. Biochem. Biophys. Res. Commun. 255, 279–282. Ajuebor, M. N., Flower, R. J., Hannon, R., Christie, M., Bowers, K., Verity, A., and Perretti, M. (1998). Endogenous monocyte chemoattractant protein-1 recruits monocytes in the zymosan peritonitis model. J. Leukoc. Biol. 63, 108–116. Arita, M., Yoshida, M., Hong, S., Tjonahen, E., Glickman, J. N., Petasis, N. A., Blumberg, R. S., and Serhan, C. N. (2005). Resolvin E1, an endogenous lipid mediator derived from omega-3 eicosapentaenoic acid, protects against 2,4,6-trinitrobenzene sulfonic acid-induced colitis. Proc. Natl. Acad. Sci. USA 102, 7671–7676. Bannenberg, G. L., Chiang, N., Ariel, A., Arita, M., Tjonahen, E., Gotlinger, K. H., Hong, S., and Serhan, C. N. (2005). Molecular circuits of resolution: Formation and actions of resolvins and protectins. J. Immunol. 174, 4345–4355. Bellingan, G. J., Caldwell, H., Howie, S. E., Dransfield, I., and Haslett, C. (1996). In vivo fate of the inflammatory macrophage during the resolution of inflammation: Inflammatory macrophages do not die locally, but emigrate to the draining lymph nodes. J. Immunol. 157, 2577–2585. Brown, G. D., Herre, J., Williams, D. L., Willment, J. A., Marshall, A. S. J., and Gordon, S. (2003). Dectin-1 mediates the biological effects of {beta}-glucans. J. Exp. Med. 197, 1119–1124. Brown, G. D., Taylor, P. R., Reid, D. M., Willment, J. A., Williams, D. L., MartinezPomares, L., Wong, S. Y. C., and Gordon, S. (2002). Dectin-1 is a major {beta}-glucan receptor on macrophages. J. Exp. Med. 196, 407–412.

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(2001). Expression and Characterization of the Chemokine Receptors CCR2 and CCR5 in Mice. J. Immunol. 166, 4697–4704. Majno, G., and Joris, I. (1996). ‘‘Cells, Tissues, and Disease’’ Blackwell Science, Oxford. Mechnikov, E. (1892). ‘‘Lec¸ons sur la pathologie compare´e de l’inflammation’’ Masson et Cie, Paris. Medzhitov, R. (2008). Origin and physiological roles of inflammation. Nature 454, 428–435. Nathan, C. (2002). Points of control in inflammation. Nature 420, 846–852. Ness, T. L., Hogaboam, C. M., Strieter, R. M., and Kunkel, S. L. (2003). Immunomodulatory role of CXCR2 during experimental septic peritonitis. J. Immunol. 171, 3775–3784. Paul-Clark, M. J., Van Cao, T., Moradi-Bidhendi, N., Cooper, D., and Gilroy, D. W. (2004). 15-Epi-lipoxin A4-mediated induction of nitric oxide explains how aspirin inhibits acute inflammation. J. Exp. Med. 200, 69–78. Rajakariar, R., Hilliard, M., Lawrence, T., Trivedi, S., Colville-Nash, P., Bellingan, G., Fitzgerald, D., Yaqoob, M. M., and Gilroy, D. W. (2007). Hematopoietic prostaglandin D2 synthase controls the onset and resolution of acute inflammation through PGD2 and 15-deoxyIˆ’’12aˆ ‘‘14 PGJ2. Proc. Natl. Acad. Sci. USA 104, 20979–20984. Rao, T. S., Currie, J. L., Shaffer, A. F., and Isakson, P. C. (1994). In vivo characterization of zymosan-induced mouse peritoneal inflammation. J. Pharmacol. Exp. Ther. 269, 917–925. Rittirsch, D., Hoesel, L. M., and Ward, P. A. (2007). The disconnect between animal models of sepsis and human sepsis. J. Leukoc. Biol. 81, 137–143. Rouzer, C. A., Scott, W. A., Cohn, Z. A., Blackburn, P., and Manning, J. M. (1980). Mouse peritoneal macrophages release leukotriene C in response to a phagocytic stimulus. Proc. Natl. Acad. Sci. USA 77, 4928–4932. Schwab, J. M., Chiang, N., Arita, M., and Serhan, C. N. (2007). Resolvin E1 and protectin D1 activate inflammation-resolution programmes. Nature 447, 869–874. Scott, W. A., Zrike, J. M., Hamill, A. L., Kempe, J., and Cohn, Z. A. (1980). Regulation of arachidonic acid metabolites in macrophages. J. Exp. Med. 152, 324–335. Serhan, C. N., Chiang, N., and Van Dyke, T. E. (2008). Resolving inflammation: Dual antiinflammatory and pro-resolution lipid mediators. Nat. Rev. Immunol. 8, 349–361. Serhan, C. N., Clish, C. B., Brannon, J., Colgan, S. P., Chiang, N., and Gronert, K. (2000). Novel functional sets of lipid-derived mediators with antiinflammatory actions generated from omega-3 fatty acids via cyclooxygenase 2-nonsteroidal antiinflammatory drugs and transcellular processing. J. Exp. Med. 192, 1197–1204. Taylor, P. R., Brown, G. D., Geldhof, A. B., Martinez-Pomares, L., and Gordon, S. (2003). Pattern recognition receptors and differentiation antigens define murine myeloid cell heterogeneity ex vivo. Eur. J. Immunol. 33, 2090–2097. Taylor, P. R., Tsoni, S. V., Willment, J. A., Dennehy, K. M., Rosas, M., Findon, H., Haynes, K., Steele, C., Botto, M., Gordon, S., and Brown, G. D. (2007). Dectin-1 is required for [beta]-glucan recognition and control of fungal infection. Nat. Immunol. 8, 31–38. van Wanrooij, E. J. A., de Jager, S. C. A., van Es, T., de Vos, P., Birch, H. L., Owen, D. A., Watson, R. J., Biessen, E. A. L., Chapman, G. A., van Berkel, T. J. C., and Kuiper, J. (2008). CXCR3 Antagonist NBI-74330 attenuates atherosclerotic plaque formation in LDL receptor-deficient mice. Arterioscler. Thromb. Vasc. Biol. 28, 251–257. Velo, G. P., Dunn, C. J., Giroud, J. P., Timsit, J., and Willoughby, D. A. (1973). Distribution of prostaglandins in inflammatory exudate. J. Pathol. 111, 149–158. Wengner, A. M., Pitchford, S. C., Furze, R. C., and Rankin, S. M. (2008). The coordinated action of G-CSF and ELR þ CXC chemokines in neutrophil mobilization during acute inflammation. Blood 111, 42–49. Yoshimura, T., and Oppenheim, J. J. (2008). Chemerin reveals its chimeric nature. J. Exp. Med. 205, 2187–2190. Zagorski, J., and Wahl, S. M. (1997). Inhibition of acute peritoneal inflammation in rats by a cytokine-induced neutrophil chemoattractant receptor antagonist. J. Immunol. 159, 1059–1062.

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A Chemokine-Mediated In Vivo T-Cell Recruitment Assay Gabriele S. V. Campanella and Andrew D. Luster Contents 1. Introduction 2. In Vitro Activation of T Lymphocytes 2.1. Purification of CD8 T lymphocytes and preparation of antigen-presenting cells 2.2. Culturing of CD8 T lymphocytes 2.3. In vitro characterization of CD8 T lymphocytes 3. In Vivo Chemokine-Mediated Recruitment 3.1. Adoptive transfer of T lymphocytes 3.2. Intratracheal instillation of chemokines 3.3. Bronchial alveolar lavage and T lymphocyte analysis 4. Use of In Vivo Recruitment Assay for Chemokine Studies 4.1. Chemokine mutant analysis 4.2. Chemokine receptor mutant analysis 4.3. In vivo testing of inhibitory antibodies and small molecule antagonists 5. Conclusion Acknowledgments References

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Abstract The ability of chemokines to induce the migration of cells expressing their cognate G-protein–coupled receptor is a characteristic property of chemokine function. To study this important function, in vitro chemotaxis assays are most often used, which, although useful, lack many components of the complex in vivo trafficking process. Reliable in vivo recruitment assays have been very difficult to establish. We describe a robust in vivo T-cell recruitment assay for adoptively transferred T lymphocytes in mice. Instillation of the CXCR3 chemokine ligands IP-10/CXCL10 or I-TAC/CXCL11 into the airways results in robust

Center for Immunology and Inflammatory Diseases, Division of Rheumatology, Allergy and Immunology, Massachusetts General Hospital, Harvard Medical School, Charlestown, Massachusetts, USA Methods in Enzymology, Volume 461 ISSN 0076-6879, DOI: 10.1016/S0076-6879(09)05418-4

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recruitment of transferred T lymphocytes. The assay thereby models the natural environment of chemokine function, as chemokines are expressed in the airways during inflammation, inducing selective leukocyte homing. This assay is particularly useful for the analysis of chemokine and chemokine receptor mutants in structure function studies and for testing the in vivo efficacy of inhibitory chemokine and chemokine receptor antibodies and small molecule antagonists.

1. Introduction Trafficking of leukocytes to sites of inflammation is a complex process. Chemokines and other chemoattractants play important roles in multiple aspects of this process. Chemokines presented by endothelial glycosaminoglycans bind to their cognate G-protein–coupled receptors on leukocytes, resulting in the activation of leukocyte integrins, firm arrest, and subsequent leukocyte extravasation through the endothelium into the tissue. Chemokines also contribute to migration, retention, and survival of leukocytes once in the tissue (Luster et al., 2005). The ability of chemokines to induce migration of leukocytes has been widely studied in vitro, but robust in vivo recruitment assays to study chemokine functions in vivo are rarely used. Although very useful, in vitro chemotactic assays are limited in that they lack many components of the complex in vivo trafficking process. In the most commonly used in vitro chemotaxis assays, exemplified by the Boyden transwell chamber, chemokines and cells are placed on opposite sides of a membrane with a specific pore size. The cells are allowed to migrate through the membrane in response to the chemokine, and their numbers are compared with the numbers of cells migrating without chemokine. These chemotaxis assays clearly lack many of the components of in vivo migration, such as a chemokine gradient, chemokine presentation by endothelial cells, and physiologic flow. To overcome some of these limitations, in some in vitro chemotaxis assays, the membranes are coated with extracellular matrix proteins, or endothelial or epithelial cells are grown on the membrane, simulating the transmigration process. Furthermore, some chemotactic chambers try to attain a chemotactic gradient along which leukocytes can migrate (Zicha et al., 1991; Zigmond, 1977). Still others model physiologic flow by use of flow chambers (see Chapter 14). However, each of these systems can only partially mimic the complex in vivo trafficking process. Therefore, to fully investigate the ability of chemokines to induce leukocyte trafficking, a robust in vivo recruitment assay is required. In this chapter, we describe such an assay for chemokine-mediated recruitment of T cells into the airways of mice.

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2. In Vitro Activation of T Lymphocytes The availability of large numbers of a uniform cell population responsive to the chemokine of interest is critical for this recruitment assay. The CXCR3 chemokine ligands IP-10/CXCL10 and I-TAC/CXCL11 mediate migration of activated T cells. Thus, in naı¨ve animals CXCR3 responsive T cells are relatively sparse. Instead of systemic activation of the endogenous immune system by agents like adjuvants, in this assay, T lymphocytes are activated in vitro and then adoptively transferred into naı¨ve animals. These adoptively transferred cells can be tracked by markers (e.g., Thy1.1 allele), resulting in high recruitment indices with low backgrounds. The responsiveness of adoptively transferred cells to the chemokine of interest should be tested in vitro before the in vivo recruitment assay is conducted. For our purposes, we activate CD8þ T lymphocyte from T cell receptor– transgenic mice in the C57Bl/6 background specific for the ovalbumin peptide SIINFEKL (OVA257–264) (OT-I mice) (Clarke et al., 2000; Hogquist et al., 1994). This allows for the efficient expansion of CD8 T lymphocytes with the SIINFEKL peptide in vitro. The protocol used for in vitro culturing of activated CD8 T lymphocytes and their in vitro characterization is described in the following.

2.1. Purification of CD8 T lymphocytes and preparation of antigen-presenting cells 1. Prepare fresh buffer for bead selection (termed here ‘‘MACS buffer’’), with PBS without Ca2þMg2þ, adding 0.5% BSA and 2 mM EDTA. Sterile-filter and degas buffer. This buffer can be stored for up to 10 days at 4  C. 2. Prepare cell culture medium. We use RPMI with 10% heat-inactivated fetal calf serum (FCS) (Sigma), 10 mM HEPES, 100 U/ml Pen/Strep, 2 mM L-glutamine, 1 nonessential amino acids, 1 mM Na pyruvate. In our experience, the FCS can greatly affect the growth and activity of the cultured effector CD8 T lymphocytes. We recommend testing different types and batches of serum and using the same lot of serum for subsequent experiments. 3. Harvest spleen and peripheral lymph nodes (we normally harvest inguinal, popliteal, axillary, brachial, internal jugular, superficial cervical, and facial lymph nodes, depending on the desired number of CD8 T lymphocytes) from C57Bl/6 OT-I mice. Place in tube with sterile HBSS, kept on ice. 4. Harvest spleen from 1 to 2 wild-type C57Bl/6 mice and place in tube with sterile HBSS kept on ice. These spleens will provide the

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antigen-presenting cells (APCs) for presenting the Ova peptide to the CD8 T lymphocytes. Prepare lymphatic cell suspension by straining spleens and lymph nodes through a 70-mm cell strainer with HBSS, both for CD8 T lymphocytes from OT-I mouse and for antigen-presenting cells. Spin cells for 10 min at 1500 rpm, remove supernatant. Gently resuspend pellet in 1 ml of red cell lysis buffer (Sigma Aldrich) and incubate for 3 min at room temperature. Add HBSS (15 to 20 ml), shake lightly. Spin for 10 min at 1500 rpm. Decant supernatant, gently resuspend pellet in 10 ml HBSS. Keep antigen-presenting cells for step 19. For cells from OT-I mouse, spin cells for 10 min at 1500 rpm. Decant supernatant. To avoid any cell clumps, which might interfere with the CD8 bead selection, pass cells through a 30-mm preselection cell strainer (MACS preseparation filter, Miltenyi Biotech #130-041-407). Wet preselection cell strainer with 500 ml MACS buffer. Resuspend OT-I cells in 2 ml MACS buffer and pass through 30-mm strainer into new tube. Wash cell strainer with 500 ml MACS buffer three times. Count cells. Spin down cells at 1500 rpm for 5 min and resuspend in 90 ml per 107 cells MACS-buffer. Add 1 ml anti-CD8a microbeads (Miltenyi Biotech 130-049-401) per 106 total cells. Incubate for 20 min in 12  C H2O bath. Add 10 ml MACS-buffer and spin at 300g, 10 min. Meanwhile, place MACS Separation LSþ column (Miltenyi Biotech #130-042-401) inside magnet slot and prerun with 3 ml MACS-buffer. Resuspend cells in 5 ml MACS-buffer. It is very important to avoid any bubbles during resuspension and during the whole bead selection process. Add the CD8a-bead labeled cells to the column, and collect the flowthrough into a 50-ml tube. Wash column with 3 ml MACS-buffer at least 3 times. When the column is almost empty, remove it from the magnet and place it inside a 15-ml tube. Fill the column again with 5 ml MACS-buffer and apply the plunger into the tube. Most CD8 T lymphocytes will elute in the first drops after the column is removed from the magnet. It is, therefore, very important to place the column into the new tube immediately after being removed from magnet or already having the column under the new tube when removing it from the magnet. Add cell culture media to cell suspension to relieve cells from the MACS buffer. Spin down cells at 1500 rpm for 10 min and resuspend in 5 ml cell culture media, count CD8 T lymphocytes. Adjust cell concentration to 1  106/ml. We normally obtain between 10 and 25 million CD8 T lymphocyte per mouse.

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18. Irradiate APCs from step 9 with 3000 rad. Alternately, the cells can be treated with mitomycin-C. 19. Spin APCs at 1500 rpm for 10 min and resuspend in 5 ml cell culture media. Count. Adjust concentration to 10 to 12 million/ml.

2.2. Culturing of CD8 T lymphocytes We usually culture 5  106 purified CD8 T lymphocytes with 5 to 6  107 APCs in T75 tissue culture flasks, as described in the following. 1. Incubate antigen-presenting cells with SIINFEKL Ova peptide for 5 min. We resuspend the SIINFEKL peptide at 200 mg/ml and add 105 ml per 50 to 60 million APC used per T75 flask. 2. Place peptide pulsed APCs (50 to 60 million total), CD8 T lymphocytes (5 million total) in T75 flask, adding culture medium to a total volume of 30 ml. 3. Add anti-CD28 (BD Pharmingen, #553294, 2 mg/ml final), IL-2 (Peprotech, #212-12, 10 ng/ml final), IL-12 (R&D, #419-ML-010, 10 ng/ml final). Culture cells in 37  C, 5 % CO2 in a humidified incubator. 4. On day 3 after purification, split cells in half using cell culture media supplemented with 10 ng/ml IL-2. We do not spin down the cells but add 30 ml new media with IL-2 to each 30-ml culture. After gently mixing, 30 ml of cells are transferred to a new T75 flask. By day 3, if the cells are growing well, they should form little cell clumps. 5. The activated CD8 effector T lymphocytes can be used after 5 or 6 days of in vitro activation. If cells are used after 6 days, on day 5, we feed the cells by adding 15 ml of culture medium supplemented with IL-2 per 30 ml culture. For CXCR3 ligand induced migration, we found that CD8 T lymphocyte activated for 6-day in vitro display the highest in vivo recruitment activity (Campanella et al., 2008). 6. Harvest cells: We harvest the effector CD8 T lymphocytes with Lympholyte M (Cedarlane) to remove dead cells (in particular APCs). For this, cells are spun down and the cell pellet from each T75 flask resupended in 5 ml room temperature HBSS. The cells are transferred into 15-ml Falcon tube and 5 ml of Lympholyte M are added to the bottom of the tube. The cells are spun for 25 min at room temperature at 1000g. 7. Carefully collect the lymphocyte fraction at the interface. Wash the CD8 T lymphocytes three times in HBSS. Count cells. 8. The effector CD8 T lymphocytes can now be used for the in vivo recruitment assay (see below). 9. The effector CD8 T lymphocytes can be further cultured to test their responsiveness to chemokines at the time of chemokine instillation. We plate the cells at 0.5  106/ml in cell culture medium supplemented with IL-2. Depending on cell growth, the cells are fed every 2 days with fresh media.

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2.3. In vitro characterization of CD8 T lymphocytes The activation and purity of the effector cells can be evaluated by flow cytometry. We usually use the activation markers CD25 and CD62L to test the activation status of the cells. As shown in Fig. 18.1, before culturing (day 0), the CD8 bead–purified T cells express high levels of CD62L and low levels of CD25. After 6 days of in vitro activation (day 6), the cells express lower levels of CD62L and very high levels of CD25.

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Figure 18.1 Characterization of in vitro activated CD8þ T lymphocytes. (A) Expression of activation markers CD62L and CD25 on day 0 and 6 of culture, as determined by Flow cytometry. (B) Expression of CXCR3 on different days of in vitro culture. (C) Expression of CXCR3 onThy1.1þ T lymphocytes in the spleen 3 days after adoptive transfer of cells. Reprinted with permission from Campanella et al. (2008).

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Furthermore, we analyze the expression of the chemokine receptor of interest by flow cytometry. In this case, we analyzed the expression of CXCR3 with a directly conjugated anti-CXCR3 antibody from R&D systems. Interestingly, we found that the expression of CXCR3 after 6 days of in vitro activation was very low on the effector CD8 T lymphocytes (Fig. 18.1B). After further in vitro culturing in the presence of IL-2, CXCR3 expression increased and peaked at day 8. This indicates that on the day when the cells are adoptively transferred into mice, they are not yet responsive to the CXCR3 chemokines IP-10 and I-TAC. It is critical to evaluate the chemokine receptor expression of the transferred cells in vivo at the time they are required to migrate in response to the chemokines. We, therefore, evaluated CXCR3 expression of the transferred cells in the spleen on the day of harvest, with the Thy1.1 marker on the transferred cells, after injection into Thy1.2 mice. As seen in Fig. 18.1C, CXCR3 expression was high on Thy1.1þ transferred cells on the day of harvest, a critical prerequisite for the cells to be responsive to CXCR3 ligands. This in vivo recruitment assay relies on the presence of a large population of adoptively transferred cells, which are responsive to the chemokine of interest. The responsiveness to the chemokine of interest should be validated during the establishment of the in vivo assay. We routinely use two different in vitro assays to evaluate the effector T lymphocytes for their ability to respond to chemokines. First, we conduct receptor internalization assays, in which the ability of chemokines to induce receptor internalization is measured. The method and characteristics of CXCR3 internalization have been described in detail elsewhere (Sauty et al., 2001). Activated CD8þ T cells were cultured with IL-2 as described previously for a total of 8 or 9 days. The cells were washed and resuspended in culture media at a concentration of 0.5  106/ml. Different concentrations of I-TAC or IP-10 (usually 10 to 1000 ng/ml) were added to the cells and incubated for 30 min at 37  C. The cells were washed and stained with antimCXCR3 antibody conjugated to PE (R&D Systems) or an IgG control and analyzed by FACS. As can been seen in Fig. 18.2A, the addition of both 100 ng/ml IP-10 or I-TAC induced robust internalization of CXCR3, with I-TAC having a stronger effect than IP-10, as previously described (Colvin et al., 2004; Sauty et al., 2001). Second, we test the in vitro chemotactic activity of the effector cells (Fig. 18.2B). Different methods of in vitro chemotaxis can be used. In our case, IP-10 or I-TAC were diluted in RPMI media supplemented with 1% low endotoxin BSA (Sigma Aldrich) and added to the bottom well of a 96-well chemotaxis plate (Neuroprobe). Activated effector T cells (days 8 to 9 in culture with IL-2) were washed and resuspended in the same buffer at a concentration of 0.5  106 cells/ml and 50 ml of cells were added on top of the membrane (5-mm pore size, polycarbonate filters). The chemotaxis plate was incubated at 37  C for 2 h and transferred to 4  C for 10 min before

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removing the membrane. The cells that had migrated to the bottom wells were counted under a microscope. Chemotactic indices were calculated by dividing the number of cells in the bottom well in response to the chemokine by the average number of cells in the bottom well without the addition of chemokines. As seen in Fig. 18.2B, both IP-10 and I-TAC induced strong chemotaxis of the effector T lymphocytes, confirming that these cells were responsive to our chemokines of interest.

3. In Vivo Chemokine-Mediated Recruitment The in vivo recruitment assay consists of three main steps: (1) adoptive transfer of in vitro activated effector T lymphocytes; (2) instillation of chemokine into a well-defined tissue compartment; and (3) harvest and subsequent analysis of T lymphocytes that have trafficked in response to the instilled chemokine.

3.1. Adoptive transfer of T lymphocytes To provide a large target cell population responsive to the chemokine of interest, effector T lymphocytes are activated in vitro as previously described. In our case, effector CD8 T lymphocytes are activated for 6 days in culture. Similarly, activated CD4 T lymphocytes can also be used as we have

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previously described (Campanella et al., 2008). In our experience, adoptive transfer of 5 million to 15 million effector cells results in good recruitment indices. Injection of higher numbers of effector cells resulted in higher numbers of recruited cells but also increased the background number of effector cells present in the anatomic site chosen for chemokine instillation (Campanella et al., 2008). Therefore, we usually adoptively transfer 7  106 effector CD8 T lymphocytes in 500 ml HBSS. We transfer the effector cells by intraperitoneal injection into mice and instill the chemokine 48 h after cell transfer. Alternately, the effector cells could be transferred by tail vein injection, in which case the chemokines may need to be instilled earlier (e.g., 24 h) because i.v.-injected cells enter the bloodsteam faster than i.p.-injected cells.

3.2. Intratracheal instillation of chemokines Two days after intraperitoneal transfer of effector cells, the chemokines are injected into mice. Different anatomic locations can be chosen for chemokine instillation. We first tried injection of chemokines into the peritoneum (after i.v. transfer of effector cells) but did not obtain robust and specific recruitment indices after peritoneal washes. As an alternative, we chose to instill chemokines into the airways as a defined anatomic compartment. IP10 and I-TAC are expressed by bronchial epithelial cells during various inflammatory diseases, as shown for tuberculosis (Sauty et al., 1999), chronic obstructive pulmonary disease (COPD) (Saetta et al., 2002), and rhinovirus infections (Spurrell et al., 2005), resulting in the recruitment of CXCR3þ lymphocytes into the airways. Intratracheal injections, therefore, model the natural environment in which chemokines are expressed during inflammation. Furthermore, the airways are an anatomic site, where few T lymphocytes are present in the absence of chemokine instillation and few adoptively transferred effector T lymphocytes migrate into the airways without a stimulus. Intratracheal injections are fast and easy to perform, but at the beginning this should be practiced to ensure that they could be performed reproducibly. For those with no experience in intratracheal injection, a dye can first be used for practice. Successful intratracheal injection of the dye can then be confirmed by opening the chest cavity of the mice to observe whether the dye has reached the lungs. Below is a detailed description of intratracheal chemokine instillation. 1. Sedate mice with ketamine/xylazine (100 mg/kg and 12 mg/kg) given by i. p. injection. 2. Extend neck of mice, and swap neck with 70% ethanol. 3. After a small 0.5-cm incision along the midline of the neck, gently expose the trachea.

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4. Under direct visualization of the trachea, inject chemokine in 50 ml PBS, or PBS only as a control, with a 28-gauge bent needle. 5. Close the neck with suture or wound staples. Allow mice to recover on a warming bed for 30 min. 6. The mice generally tolerate this procedure well without respiratory compromise.

3.3. Bronchial alveolar lavage and T lymphocyte analysis Recruitment of T lymphocytes to the airways is analyzed by bronchial alveolar lavage (BAL). We obtained maximal specific recruitment of T lymphocytes in response to chemokines 18 h after intratracheal injection (Campanella et al., 2008), but this might vary for other chemokines and other cell types. After BAL, the cells in the BAL fluid are analyzed by flow cytometry. Following is a detailed protocol for these procedures. 1. Sedate mice with ketamine/ xylazine (100 mg/kg and 12 mg/kg) given by i. p. injection. 2. Exsanguinate mice by cutting renal artery. 3. Extend neck and cut open the wound of intratracheal injection. 4. Expose trachea. Guide a suture thread underneath the trachea. 5. Make small incision near the top of the trachea. 6. Insert into the trachea a thin tubing attached to three-way stopcock attached to one empty 3-ml syringe and one 3-ml syringe filled with PBS, without Ca2þ and Mg2þ, supplemented with 2 mM EDTA. 7. Use thread passed under trachea to tighten the tubing in the trachea. 8. Wash the airways with six sequential 0.5-ml washes. 9. Spin down BAL fluid, 10 min at 1500 rpm. The supernatant can be retained for analysis of chemokine or cytokine levels if desired. 10. (Optional) Resuspend cell pellet in 0.5 ml RBC lysis buffer, incubate for 2 min at room temperature. Add 10 ml of HBSS and spin down cells. 11. Resuspend cells in 200 ml PBS þ 0.5% FCS. Count cells. 12. Add 2.4G2 anti-FcgIII/II receptor (BD Pharmingen), incubate for 10 min on ice. 13. Stain cells with desired antibodies for flow cytometry. In our case, we stain with FITC-conjugated anti-murine CD3, PE-conjugated anti-murine CD4, or PE-conjugated anti-murine CD90.1 and APC-conjugated anti-murine CD8 (all from BD Pharmingen) at 4  C for 20 min. 14. Analyze cells by cytofluorimetry. As seen in Fig. 18.3, after instillation of PBS into the airways, very few T lymphocytes are present in the BAL fluid. After instillation of 5 mg I-TAC, large numbers of T lymphocytes infiltrate into the airways. Use of the Thy1.1 marker clearly reveals that most of the infiltrated T lymphocytes are the adoptively transferred effector CD8 T lymphocytes. Instillation of different

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Figure 18.3 Flow cytometric analysis of CD8þ T lymphocyte recruitment into the airways induced by I-TAC. I-TAC (5 mg) was injected intratracheally after adoptive transfer of activated CD8þ T lymphocytes 48 h prior. The BAL was harvested 18 h later, and CD8þ T lymphocytes were analyzed by flow cytometry after gating on the lymphocyte subpopulation.The percentages of CD8þ/CD3þ Tcells of total events are shown in the upper right corners. Reprinted with permission from Campanella et al. (2008).

concentration of IP-10 or I-TAC shows that CD8 T lymphocyte recruitment depends on chemokine concentration. The lowest amount of chemokine used, 0.5 mg, induces statistically significant recruitment indices of 3.7 and 5.8 for IP-10 and I-TAC, respectively. Instillation of 5 mg results in increased recruitment indices of 15.7 and 12.5, whereas instillation of 50 mg IP-10 or I-TAC yields recruitment indices of 53.6 and 58.8, respectively (Fig. 18.4).

4. Use of In Vivo Recruitment Assay for Chemokine Studies This in vivo recruitment assay can be used to evaluate the in vivo biology of chemokines. It is especially useful for chemokine structure function studies, in which the functions of different chemokine mutants

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B 12 10

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Figure 18.4 Dose response of I-TAC^ and IP-10^induced recruitment of activated CD8þ T lymphocytes in vivo. PBS, I-TAC, or IP-10 was injected intratracheally at the indicated amount. The BAL was harvested 18 h later, and CD8þ T lymphocytes were analyzed by flow cytometry. (A) Total CD8þ T lymphocytes in BAL. (B) Recruitment index was calculated in comparison to intratracheal injection of PBS. *p < 0.05, ** p < 0.001 compared with PBS injection. Reprinted with permission from Campanella et al. (2008).

or chemokine receptor mutants are analyzed. In most studies to date, the biologic effect of mutations is only tested with in vitro assays of chemokine function. However, for some mutations the true biologic significance will only become apparent by use of an in vivo assay like the one described here. Furthermore, testing the in vivo efficacy of blocking antibodies or antagonists can only be done with a robust in vivo recruitment assay like the one described here.

4.1. Chemokine mutant analysis One example of the clear need for in vivo analysis of chemokine mutants was revealed by our investigation into the role of IP-10 oligomerization (Campanella et al., 2006). We found that an obligate IP-10 monomer, which contains the synthetic mutation L27NMe, was able to induce chemotaxis of effector T cells with the same efficacy as wild-type IP-10, although it required 10-fold higher concentrations (Fig. 18.5A). However, in the in vivo recruitment assay described here, monomeric IP-10 was not able to induce any homing of T lymphocytes even at the highest concentration tested (Fig. 18.5B). This was in contrast to another IP-10 mutant, R22E, which had similarly reduced CXCR3 and heparin binding affinity as monomeric IP-10 and similar in vitro chemotactic potential. Mutant R22E was able to induce in vivo recruitment of effector T cells at higher concentrations, clearly demonstrating that IP-10 oligomerization is required for the induction of in vivo T-cell trafficking. This conclusion only became

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Figure 18.5 Analysis of IP-10 mutants by in vitro and in vivo recruitment assays. (A) In vitro chemotaxis. Chemotaxis of activated OT-I CD8þ Tcells in response to IP-10 (wild type or mutants) was performed in duplicate with a Neuroprobe chamber. One representative assay out of three experiments is shown. (B) In vivo recruitment assay. IP-10 (wild type or mutant) was injected intratracheally at the indicated concentration after adoptive transfer of activated OT-I CD8þ cells 48 h prior. The BAL was harvested 18 h later, and CD8þ Tcells were analyzed by flow cytometry. The recruitment index was calculated in comparison with intratracheal injection of PBS. Reprinted with permission from Campanella et al. (2006).

apparent with an in vivo recruitment assay. A third mutant, R8A, which induced no in vitro T-cell chemotaxis even at the highest concentration tested, also did not cause any in vivo homing. This recruitment assay, therefore, is very useful to evaluate the in vivo effect of chemokine mutations.

4.2. Chemokine receptor mutant analysis This recruitment assay is also very useful for the investigation of the in vivo effects of chemokine receptor mutations, which so far have only been analyzed in vitro. We have started this process by comparing the recruitment of wild-type and CXCR3-deficient (CXCR3 KO) effector T cells in response to IP-10. To directly compare the recruitment of both cell types in the same mouse, we used Thy1.1 wild-type OT-I effector T cells and Thy1.2 CXCR3 KO OT-I effector T cells and adoptively cotransferred them into Thy1.1xThy1.2 mice. Two days later, 5 mg IP-10 or PBS was instilled into the airways as described previously, and 18 h later the numbers of wild-type and CXCR3 KO effector cells in the spleen and airways were evaluated. Cotransfer of both wild-type and KO or mutant effector cells into the same mouse allows for the calculation of homing ratios as the ratio of wild-type: KO effector cells recovered from each anatomic site. As seen in Fig. 18.6, the homing ratio in the spleen was close to 1 and did not change after chemokine instillation into the airways. However, IP-10

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Gabriele S. V. Campanella and Andrew D. Luster

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Figure 18.6 Cotransfer of wt- and CXCR3 KO^activated CD8þ Tcells. Activated wt (Thy1.1) and CXCR3 KO (Thy1.2) OT-I cells (5  106 each) were adoptively transferred into the sameThy1.1xThy1.2 mice. Forty-eight hours later, PBS or 5 mg IP-10 was injected intratracheally. The BAL and spleen were harvested 18 h later, and Thy1.1 and Thy1.2 single positive cells were analyzed by flow cytometry as shown after gating on CD3þ/ CD8þ T lymphocytes.The homing ratio was calculated as wt/CXCR3 KO OT-I CD8þ T lymphocytes. *p < 0.05 compared with PBS injection. Reprinted with permission from Campanella et al. (2008).

instillation in the airways resulted in trafficking of wild-type (Thy1.1þ) effector T cells into the airways, but not of CXCR3 KO (Thy1.2þ) effector T cells. In a similar manner, the in vivo effect of chemokine receptor mutations could be analyzed. For this, chemokine receptor mutants could be transfected either into cell lines or into CXCR3 KO primary cells. These transfected cells could then be adoptively transferred into mice to determine their trafficking potential to different chemokines.

4.3. In vivo testing of inhibitory antibodies and small molecule antagonists A robust in vivo recruitment assay is also very useful to test the potency of inhibitory antibodies or small-molecule antagonists against chemokines and chemokine receptors. To confirm the activity of a monoclonal anti-IP-10 antibody produced in our laboratory (1F11) (Khan et al., 2000), we intraperitoneally injected the antibody 4 h before cell transfer and 2 h after intratracheal IP-10 instillation. Injection of 1 mg anti-IP-10 antibody, corresponding to a 10-fold molar excess compared with IP-10, reduced the recruitment index from 9.1 for administration of control antibody to 3.2, a statistically significant reduction (Fig. 18.7). Injection of 0.1 mg anti-IP-10 antibody only slightly reduced the recruitment index to 5.2, which was not statistically significant. The in vivo inhibitory activity of our anti-IP-10 antibody was thereby confirmed with this in vivo recruitment assay.

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14

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Figure 18.7 Testing the in vivo efficacyof a monoclonal antibody against IP-10. Anti-IP10 monoclonal (1F11) (1 mg or 0.1 mg) or isotype control monoclonal antibody (IgG) (1 mg) was injected i. p. into mice 4 h before adoptive transfer of CD8þ T lymphocytes and 2 h after intratracheal injection of PBS or IP-10 (5 mg).The assay was then performed as described in Fig. 18.4. *p < 0.01 compared with PBS injection, **p < 0.02 compared with IP-10 instillation. Reprinted with permission from Campanella et al. (2008).

5. Conclusion We have developed a robust, reproducible in vivo chemokinemediated T-cell recruitment assay. This assay uses the adoptive transfer of in vitro–generated antigen-specific effector T cells into the peritoneum of naı¨ve mice followed by the intratracheal injection of chemokine into the airways. BAL allows for the recovery of T cells that are recruited into the airway. With the airway, this assay results in high recruitment indices with low background. We have also illustrated that this assay can be effectively used to study the in vivo activity of chemokine and chemokine receptor mutants as well as the in vivo efficacy of inhibitory antibodies and smallmolecule antagonists. We believe that in vivo recruitment assays should be more widely used to study the biologic activity of chemokines. The availability of assays such as the one described here will help in this regard.

ACKNOWLEDGMENTS This work was supported by a grant from the National Institutes of Health CA069212.

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REFERENCES Campanella, G. S., Grimm, J., Manice, L. A., Colvin, R. A., Medoff, B. D., Wojtkiewicz, G. R., Weissleder, R., and Luster, A. D. (2006). Oligomerization of CXCL10 is necessary for endothelial cell presentation and in vivo activity. J. Immunol. 177, 6991–6998. Campanella, G. S., Medoff, B. D., Manice, L. A., Colvin, R. A., and Luster, A. D. (2008). Development of a novel chemokine-mediated in vivo T cell recruitment assay. J. Immunol. Methods 331, 127–139. Clarke, S. R., Barnden, M., Kurts, C., Carbone, F. R., Miller, J. F., and Heath, W. R. (2000). Characterization of the ovalbumin-specific TCR transgenic line OT-I: MHC elements for positive and negative selection. Immunol. Cell Biol. 78, 110–117. Colvin, R. A., Campanella, G. S., Sun, J., and Luster, A. D. (2004). Intracellular domains of CXCR3 that mediate CXCL9, CXCL10, and CXCL11 function. J. Biol. Chem. 279, 30219–30227. Hogquist, K. A., Jameson, S. C., Heath, W. R., Howard, J. L., Bevan, M. J., and Carbone, F. R. (1994). T cell receptor antagonist peptides induce positive selection. Cell 76, 17–27. Khan, I. A., MacLean, J. A., Lee, F. S., Casciotti, L., DeHaan, E., Schwartzman, J. D., and Luster, A. D. (2000). IP-10 is critical for effector T cell trafficking and host survival in Toxoplasma gondii infection. Immunity 12, 483–494. Luster, A. D., Alon, R., and von Andrian, U. H. (2005). Immune cell migration in inflammation: Present and future therapeutic targets. Nat. Immunol. 6, 1182–1190. Saetta, M., Mariani, M., Panina-Bordignon, P., Turato, G., Buonsanti, C., Baraldo, S., Bellettato, C. M., Papi, A., Corbetta, L., Zuin, R., Sinigaglia, F., and Fabbri, L. M. (2002). Increased expression of the chemokine receptor CXCR3 and its ligand CXCL10 in peripheral airways of smokers with chronic obstructive pulmonary disease. Am. J. Respir. Crit. Care. Med. 165, 1404–1409. Sauty, A., Colvin, R. A., Wagner, L., Rochat, S., Spertini, F., and Luster, A. D. (2001). CXCR3 internalization following T cell-endothelial cell contact: preferential role of IFN-inducible T cell alpha chemoattractant (CXCL11). J. Immunol. 167, 7084–7093. Sauty, A., Dziejman, M., Taha, R. A., Iarossi, A. S., Neote, K., Garcia-Zepeda, E. A., Hamid, Q., and Luster, A. D. (1999). The T cell-specific CXC chemokines IP-10, Mig, and I-TAC are expressed by activated human bronchial epithelial cells. J. Immunol. 162, 3549–3558. Spurrell, J. C., Wiehler, S., Zaheer, R. S., Sanders, S. P., and Proud, D. (2005). Human airway epithelial cells produce IP-10 (CXCL10) in vitro and in vivo upon rhinovirus infection. Am. J. Physiol. Lung Cell Mol. Physiol. 289, L85–95. Zicha, D., Dunn, G. A., and Brown, A. F. (1991). A new direct-viewing chemotaxis chamber. J. Cell Sci. 99(Pt 4), 769–775. Zigmond, S. H. (1977). Ability of polymorphonuclear leukocytes to orient in gradients of chemotactic factors. J. Cell Biol. 75, 606–616.

Author Index

A Abbott, C. A., 283 Abe, S., 149 Abrahams, J., 381 Abrol, R., 252, 269, 270, 271, 275 Acharya, P., 154 Acharya, S., 178 Addison, C. L., 106 Adolfsen, W., 255 Aebersold, R., 16 Afenyi-Annan, A., 193 Agnati, L., 116, 118 Ajami, K., 283 Ajuebor, M. N., 381, 382, 383 Akalin, E., 193 Akerman, K. E. O., 245 Akiyama, S., 345 Alam, S. M., 150, 153 Albar, J. P., 108, 109, 209 Albina, J. E., 394 Albrecht, S., 283 Alcaide, P., 328 Alcami, A., 106 Al-Duaij, A. Y., 303 Alexander, J. M., 73 Alexander-Brett, J. M., 89 Ali, S., 72, 73, 76, 86 Allavena, P., 5 Allegretti, M., 251 Allen, R. A., 107, 253 Allen, S. J., 34, 180, 205, 282 Allikmets, R., 208 Allingham, M. J., 328 Alon, R., 311, 312, 313, 314, 315, 317, 320, 321, 322, 323, 324, 327, 328 Alouani, S., 176 Altenbach, C., 176, 178 Altieri, A. S., 39, 40 Alves, I. D., 123, 129, 133, 135, 137, 138, 139, 140, 141, 143, 144 Amara, A., 74, 76, 89 Amaral, O. B., 222 Anafi, D., 128, 129 Anders, H.-J., 381 Andersen, M. B., 176, 180, 181 Anderson, J., 16, 283 Andrews, G., 254, 259 Andrieu, E. U., 213

Angers, S., 108, 213 Antaramian, A., 178 Aoshi, T., 350, 361, 362, 371 Appella, E., 4, 5 Applebe, S., 207, 208, 209, 213, 214, 217, 220 Aramaki, Y., 265, 274 Archer-Lahlou, E., 112 Arenberg, D. A., 106 Arias, D. A., 275 Ariel, A., 393 Arita, K., 21 Arita, M., 381, 382, 383, 393 Armour, D., 175, 274 Arnold, B., 383 Arnold, E., 255 Arnold, G. F., 255 Artis, D. R., 251 Ashman, K., 149 Ashmun, R. A., 23 Ashton, B. A., 24 Astrof, N. S., 314 Atherton, E., 16 Atilgan, A. R., 282 Audet, M., 111 Audet, N., 112 Auerbach, S., 328 Ayoub, M. A., 213, 221 B Baba, M., 265, 274 Babcock, G. J., 150, 213 Bacakova, L., 181 Bach, A., 178 Baggiolini, M., 4, 16, 31, 106, 107, 174, 250, 297, 334 Baker, J. G., 174, 260 Balbo, A., 35, 37, 39, 90 Baldwin, E. T., 47 Ballantyne, C. M., 312 Ballesteros, J. A., 177, 178 Ballet, S., 213 Bamba, P. S., 328 Bandyopadhyay, S., 194 Bannenberg, G. L., 393 Bannert, N., 53, 149 Barinka, C., 47 Barone, K. M., 148 Baroudy, B. M., 254

413

414 Barreiro, O., 313, 315, 327, 328 Barrera, J. L., 106 Barteczko, M., 383 Baryshnikova, O. K., 43 Baskaran, H., 335, 336 Batista, F. D., 313, 324 Bautista, D. A., 275 Baysal, C., 282 Bazin, H., 216, 221 Beaujouan, J. C., 139, 140 Beaver, T. H., 382, 383 Beccari, A., 251, 255, 259 Beck-Sickinger, A. G., 176 Begg, G., 11 Behnke, C. A., 138, 174, 176, 177, 259, 260, 261 Beisswanger, R., 149 Bellac, C. I., 283 Bellingan, G. J., 382, 384 Belperio, J. A., 106 Bendall, L., 282, 283, 285, 286, 294, 304 Benkirane, M., 208 Benko, G., 177 Benned-Jensen, T., 176, 179 Bennett, T. A., 238, 240, 242, 245 Berahovich, R. D., 282 Berchiche, Y. A., 107, 209, 213 Berg, E. L., 322 Berger, E. A., 106 Berglund, M. M., 176 Berkhout, T. A., 175, 253, 265, 266, 267, 268 Berlot, C. H., 228 Berman, J., 285 Bertini, R., 251, 255, 259 Bertozzi, C. R., 148 Beuken, E. V., 178 Beuneu, H., 351 Bevilacqua, M. P., 314 Bewley, C. A., 154 Beyermann, M., 21 Bhakta, S., 175, 253, 351 Bickett, D. M., 285 Bienert, M., 21 Biessen, E. A. L., 381 Biggs, S., 229, 230, 234, 239, 240, 245 Biggs, S. M., 238, 240 Billah, M., 256 Billiau, A., 4, 5, 6, 7, 8, 9, 10 Birch, H. L., 381 Birnbaumer, M., 178 Biscone, M. J., 175, 180 Bishop-Stewart, J., 301 Bizzarri, C., 251, 255, 259 Blackburn, P., 382 Blain, K. Y., 32, 33, 47 Blaney, F. E., 175, 253, 265, 266, 267, 268 Blanpain, C., 213, 250, 251, 282 Blaschke, S., 52

Author Index

Blauvelt, A., 107 Blumberg, R. S., 381, 383 Bock, C. B., 383 Bockaert, J., 111 Bodart, V., 256 Boeckx, S., 253 Boguslavski, V., 141, 144 Boismenu, R., 52 Boissonnas, A., 351 Bondue, A., 250, 251, 282 Bonecchi, R., 4, 106 Bonomi, M., 153 Boranic, M., 23 Borgeat, P., 382, 383 Borisy, G., 312 Borlat, F., 82, 88, 93, 282, 285, 301, 302 Borroni, E. M., 106 Borsetti, A., 149 Borzilleri, K. A., 57 Bot, G., 209 Bota, D., 153 Botto, M., 382 Boulter, E., 328 Bourne, H. R., 185, 186 Bourrier, E., 221 Bousso, P., 350 Boute, N., 111 Bouvier, M., 107, 108, 111, 112, 209, 213, 215 Bowers, K., 381, 383 Boyden, S. V., 335 Bradford, M. M., 12 Brainard, D. M., 335 Brand, L., 212 Brandt, E., 4 Brannon, J., 383 Braunersreuther, V., 73 Brautigan, D. L., 114 Breeze, A. L., 45 Breit, A., 213 Breljak, D., 23 Bridger, G., 256 Bridger, G. J., 256, 259 Bridges, A. M., 175, 253, 265, 266, 267, 268 Broach, J., 275 Brock, A. F., 5 Brock, C., 221 Brody, J., 345 Brown, G. D., 382, 390 Brown, K. A., 301 Brown, M. F., 125, 126, 128, 134, 138, 139, 143 Brown, P. J., 285 Brudel, M., 21 Bruggeman, C. A., 178 Bruhl, H., 381 Buchanan, M., 106 Buchbinder, S. P., 208 Buckley, C. D., 314

415

Author Index

Bulenger, S., 213 Bundgaard, J. R., 149 Bunemann, M., 229 Buntinx, M., 253 Buracchi, C., 106 Buranda, T., 227, 229, 230, 231, 232, 233, 234, 236, 237, 238, 239, 240, 241, 242, 243, 244, 245 Burdick, M. D., 106 Burghammer, M., 174 Burridge, K., 312, 328 Bursill, C. A., 381 Burton, D. R., 153, 159 Butcher, E., 334, 340, 341, 342, 343, 344 Butcher, E. C., 31, 322 Butler, G. S., 282, 283, 285, 286, 294, 297, 304 Buttle, D. J., 24 C Cadene, M., 158 Cafiso, D. S., 176 Cahalan, M. D., 358 Cai, K., 178 Cai, S., 381 Cain, D. W., 314, 315 Caldwell, C. G., 255 Caldwell, H., 382 Camacho, P., 300 Campanella, G. S., 33, 35, 53, 76, 397, 401, 405, 406, 407, 408, 409, 410, 411 Campbell, J., 334 Camphausen, R. T., 148 Campos, S. K., 230, 236, 237 Canals, M., 219, 222 Candelore, M. R., 176 Canela, E. I., 116, 118 Cannon, J. J., 349 Capetillo, S., 9 Carbonatto, M., 301 Cardosa, A. A., 149 Cardullo, R. A., 111 Carlton, M. B., 381, 383, 384, 385 Carman, C. V., 313, 314, 324, 325, 327, 328 Carpenter, A., 381 Carr, I. C., 213 Carr, M. W., 313, 317 Carrasco, Y. R., 313, 324 Carriba, P., 116, 118 Carrieri, A., 277 Carrington, M., 208 Carson, M. J., 181 Carter, P. H., 249, 250, 251, 253 Casado, V., 114, 117 Cash, J. L., 379, 381, 383, 384, 385 Cassidy, C. K., 43 Castellino, F., 351 Castonguay, L. A., 255

Catalano, M., 209 Caterson, B., 294 Catron, D., 106 Caulfield, C. P., 231, 232 Cavanagh, L. L., 350 Cayabyab, M., 149, 150 Celso, C. L., 350 Ceradini, D., 208 Cerdan, C., 52 Cervellera, M. N., 255, 259 Cesta, M. C., 255, 259 Chait, B. T., 21, 158 Chakravarty, L., 150, 259 Chambers, R. C., 381 Chan, S. D., 186 Chance, M. R., 96, 97 Changeux, J. P., 178 Channon, K. M., 381 Chao, J., 256 Chapman, G. A., 381 Charo, I. F., 31, 174, 297 Charvatova, O., 97 Chassaing, G., 139 Chatterjee, B. E., 381, 383 Chaudhuri, A., 192 Chayen, N. E., 250 Chemel, B. R., 222 Chen, C., 209 Chen, D., 381 Chen, H., 322 Chen, J., 314 Chen, W. N., 301 Chen, X., 328 Chen, Z. Q., 52, 228, 229 Cherezov, V., 174, 259, 260, 267 Cherney, R. J., 253 Chiang, N., 382, 383, 393 Chien, E. Y. T., 174, 260 Chieppa, M., 351 Chin, Y. E., 324 Chinenov, Y., 222 Chitnis, C. E., 153, 196, 197 Chiu, D. T., 338, 339 Chklovskaia, E., 323 Choe, H., 147, 149, 150, 153, 154, 155, 156, 159, 162, 195 Choe, H. W., 174, 176 Choe, S., 208 Choi, H. J., 174, 259, 260, 267 Choi, I. S., 338 Chollet, A., 282 Christie, M., 381, 383 Christophers, E., 5 Christopoulos, A., 181 Chuang, L. F., 211 Chuang, R. Y., 211 Chun, R. F., 208 Chung, B. G., 345

416 Chung, S., 154, 155, 156 Ciano, K. A., 141, 144 Ciaramella, G., 259 Cihak, J., 381 Cimino, D. F., 234, 238, 240, 245 Cinamon, G., 312, 313, 314, 315, 320, 321, 323, 327 Ciotti, M. T., 209 Cirillo, R., 301 Ciruela, F., 116, 118, 222 Clader, J. W., 254 Clapham, P. R., 176 Clark, P., 313 Clark, S. J., 24 Clarke, S. R., 399 Clark-Lewis, I., 16, 24, 31, 54, 176, 282, 283, 285, 286, 294, 301, 302, 304, 313, 314, 321 Clish, C. B., 383 Clore, G. M., 36, 44, 53 Cochrane, C. G., 234, 240 Coesemans, E., 253 Cognaux, J., 208 Cohn, Z. A., 382 Colarusso, P., 312 Colgan, S. P., 383 Colledge, W. H., 381, 383, 384, 385 Colville-Nash, P., 384 Colvin, R. A., 403 Combs, C. A., 107 Comps-Agrar, L., 221 Conings, R., 4, 5, 13, 21 Conklin, B. R., 185, 186 Connolly, M. D., 394 Connor, A. R., 282, 283 Cooper, D., 381 Cooper, D. G., 175, 253, 265, 266, 267, 268 Corbeil, D., 149, 163 Cormier, E. G., 154, 155 Corness, K. M., 148 Corsel, J. W., 134 Corte´s, A., 116, 118 Costa, T., 178 Costagliola, S., 153, 208 Costanzi, S., 275 Cotecchia, S., 178 Coulin, F., 176 Coulon, V., 111 Couturier, C., 213 Coward, P., 186 Cowell, S., 135, 138, 140 Cowell, S. M., 139, 140 Cox, H. M., 178 Cox, J. H., 282, 283, 285, 297, 301 Craig, S., 149 Crocker, E., 178 Crown, S. E., 24, 33, 34, 36, 42, 43, 44, 53, 93, 94, 180, 205, 282, 301

Author Index

Cumming, D. A., 148 Currie, J. L., 381 Curtis, C. A., 178 Cutbush, M., 192 Cuvelier, S. L., 314 Cuypers, P. A., 134 Cybulsky, M. I., 312 Cyster, J. G., 314, 324 Czaplewski, L. G., 32, 33, 34, 36, 37 D da Fonseca, P. C., 252, 253, 269 Daley, J. M., 394 Damazo, A. S., 393 Dan, Y., 335 Dangerfield, J., 314 Dankwardt, J., 175, 253 Darbonne, W. C., 193, 198 Das, A. M., 86, 383 Das, D., 255, 259 Datta-Mannan, A., 250 Daugherty, B. L., 255 David, R., 176 Dawson, J., 303 Dawson, T. C., 194 Day, A. J., 24 de, P. C., 177 Dean, M., 208 Dean, R. A., 282, 283, 285, 301 de Ana, A. M., 208, 209 De Benedetti, P. G., 260 Decicco, C. P., 253 Decock, B., 4, 5 de Jager, S. C. A., 381 Dekeyzer, L., 4, 5, 21 de la Fuente, M. A., 313, 325, 327 Delagrange, P., 213 Delaroche, D., 139, 140 De Leener, A., 250, 251, 282 DeLisa, M. P., 345 del Real, G., 107 del Sol, A., 107 De Lucca, G. V., 259 de Mendonc¸a, F. L., 252, 269, 270, 271, 275 Dempster, J., 349 Deng, X., 222 Denk, W., 350 Dennehy, K. M., 382 Deno, G., 256 Dertinger, S. K. W., 335, 336, 338, 339 Deruaz, M., 86 Desjardin, E., 149 Detheux, M., 23 Deupi, X., 177 Devanathan, S., 129, 133, 135, 139, 140 de Vos, P., 381 Dewald, B., 31

417

Author Index

de Winter, R. J., 198 Dezube, M., 285 Diao, J., 345 Di Bartolomeo, S., 209 Di Bitondo, R., 255, 259 Di Cioccio, V., 255, 259 Dick, F., 21 Diehl, F., 175, 253 Dillen, C., 4, 5, 13, 21 Dilloo, D., 52 Dinarello, C. A., 381 Ding, J., 255 Ding, Z., 313 Dioszegi, M., 254, 272, 273 Di Salvo, J., 255 Dixon, J. P., 381, 383, 384, 385 Dixon, R. A., 176 Dobbs, S., 175, 274 Doftman, T., 153, 159 Doherty, N. S., 382, 383 Dohrmann, U., 149 Doi, R. H., 211 Do¨lling, R., 21 Domaille, P. J., 45, 90 Doms, R. W., 175, 180, 250, 251, 282 Donfield, S., 208 Dong, C., 54 Doran, J., 381, 383, 384, 385 Doranz, B. J., 208, 250, 251, 282 Dorfman, T., 154, 156 Dorling, A., 381 Dorn, C. P., 196 Dorner, B., 54 Dorr, P., 175, 259, 274 Doucet, A., 283 Dowal, L., 229 Doyon, J., 253 Dragan, S., 150, 259 Dragic, T., 154, 155, 254 Dransfield, I., 382 Du, X., 228, 229 Duchesnes, C. E., 251, 253 Dudek, A. Z., 34, 44 Duncia, J. V., 259 Dunn, C. J., 381 Dunn, G., 335 Dunning, L., 175, 180, 252, 269, 270, 271, 275 Durinx, C., 23 Durroux, T., 221 Dvorak, A. M., 313, 315, 325, 327, 328 Dvorak, H. F., 313, 325, 327 Dwir, O., 321, 323 Dwyer, M., 256 E Ebberink, R., 16, 21 Ebi, B., 175, 253 Edman, P., 11

Edwards, B. S., 229, 230 Edwards, J. C., 303 Edwards, P. C., 174, 260 Egen, J. G., 351 Ehlert, J. E., 106 Eidne, K. A., 111, 212, 224 Eilers, M., 178 Elangovan, M., 113, 114 El Asmar, L., 213 Elder, A., 175, 179, 180, 255 El-Fakahany, E. E., 181 Elling, C. E., 174, 176, 177, 178, 180 Elliot, E., 113, 114 Ellyard, J. I., 34, 84, 86 Emmett, G., 259 Endo, N., 265 Engel, A., 208 Engelhardt, B., 314 Erez, N., 313, 322 Erickson, D., 208 Ernst, O. P., 174, 176, 178 F Fagni, L., 111 Falsone, S. F., 95, 96 Fan, X., 256 Fanelli, F., 178, 260 Fanning, D., 265 Fano, A., 277 Fantuzzi, G., 381 Farber, C. M., 208 Farber, J. M., 106 Farfel, Z., 185, 186 Farid, R., 264 Farrens, D. L., 176 Farrow, N. A., 58 Farzan, M., 53, 147, 149, 150, 153, 154, 155, 156, 159, 162, 213 Faust, N., 360 Fay, S. P., 242 Fazekas de St Groth, B., 323 Feigelson, S. W., 313, 314, 321, 322, 323, 324 Feng, X., 174 Fermas, S., 34 Fernandez, E. J., 32, 33, 282 Fernandez, S., 107, 209 Fernando, P. H., 149 Ferre´, S., 116, 118 Ferreira, A. M., 313 Fidock, M., 213 Fields, C. G., 19, 21 Fields, G. B., 19, 21 Filer, A., 314 Filipek, S., 177, 178, 208 Findon, H., 382 Finke, P. E., 196, 255 Firestein, G. S., 380 Firtel, R. A., 312

418

Author Index

Fischetti, R. F., 174 Fitzgerald, D., 384 Fitzhugh, D. J., 107 Flad, H. D., 4 Flavell, R. A., 381 Floriano, W. B., 252, 269, 270, 271, 275 Flower, R. J., 381, 383, 393 Fogarty, E. A., 345 Folch, A., 345 Fong, A. M., 53, 150, 153 Forbes, I. T., 175, 253, 265, 266, 267, 268 Forceille, C., 208 Fork, R. L., 357 Formaneck, M. S., 67 Forrest, M. J., 381, 382 Forster, T., 212 Fossetta, J., 256 Fossier, P., 213 Fotiadis, D., 208 Foutz, T., 233, 234, 237, 238, 240, 245 Foutz, T. D., 240 Fox, B. A., 138, 174, 176, 177, 259, 260, 261 Fox, J. M., 34, 252, 269, 270, 271, 275 Fradkov, A. F., 219 Fraeyman, A., 4, 5, 21 Franco, R., 116, 118, 222 Franitza, S., 321, 323 Fredriksson, R., 176 Freer, R. J., 242 Fremont, D. H., 89 Fricker, S. P., 256 Fridmanis, D., 176 Friedrich, W., 327 Friesner, R. A., 264 Frimurer, T. M., 174, 176, 177, 178, 180, 181 Frink, M., 381 Fritze, O., 178 Froio, R. M., 315, 324, 326, 328 Froyen, G., 6, 7, 8, 9, 10 Fujii, N., 107, 209, 213 Fujimoto, E. K., 12 Fujino, M., 265, 274 Fujita, N., 322 Fujiwara, Y., 275 Fukui, T., 4 Fukui, Y., 313, 322 Fukuma, N., 194 Furthmayr, H., 313, 315, 327, 328 Furukawa, H., 23 Furutani, Y., 4 Furze, R. C., 381 Fuxe, K., 116, 118 G Gabrilovac, J., 23 Gaffney, T., 176 Gale´s, C., 112

Galino, J., 222 Galli, S. J., 380 Galliera, E., 255, 259 Galzi, J. L., 282 Gandia, J., 222 Gao, J., 153 Garcia-Mata, R., 328 Gardner, D. S., 259 Gardner, L., 24 Garrison, J. C., 229, 230, 233, 234, 237, 238, 240, 241, 243, 244, 245 Gartner, F. H., 12 Gauderon, R., 360 Gaudry, J. P., 88, 93, 398 Gauldie, J., 107 Gaus, K., 323 Gavrilin, M. A., 150, 259 Gavrilov, S., 254 Ge, N., 106 Gee, K. R., 301 Geha, R. S., 313, 325, 327 Geissmann, F., 360 Geldhof, A. B., 390 Georget, V., 116 Georgieva, T., 139 Gerard, C., 149, 150, 153, 154, 155, 156 Gerard, N., 149 Gerard, N. P., 149, 150, 153, 154, 155, 156 Geretti, E., 89, 93 Gerlach, L. O., 176, 180, 256, 259 Germain, R. N., 350, 358, 362 Gerstoft, J., 176 Gether, U., 174, 177 Getting, S. J., 303 Geumann, U., 176 Ghanouni, P., 177 Ghosh, S., 175, 178, 179, 255 Gijsbers, K., 4, 5, 21 Gilbert, S., 178 Gilbert, T. L., 234 Giles, K., 312 Gilissen, R. A., 253 Gilman, A. G., 229 Gilroy, D. W., 381, 384 Gimbrone, M. A., 5 Ginsberg, M. H., 312 Giralt, E., 21 Girod, A., 116 Giroud, J. P., 381 Gisin, B. F., 21 Glickman, J. N., 381, 383 Glowinski, J. A., 139, 140 Glyn, M., 313 Goddard, W. A. III, 270 Godessart, N., 179 Goedert, J. J., 208 Goeke, N. M., 12 Goger, B., 87, 88

419

Author Index

Golan, D. E., 328 Gomez, L., 107 Gomperts, E., 208 Gong, J. H., 282, 283, 285, 286, 294, 304 Gonsiorek, W., 256 Goossens, J., 253 Go¨ppert, M., 350 Gordon, S., 382, 387, 390 Gorrell, M. D., 283 Goshoh, Y., 345 Gotlinger, K. H., 393 Gouwy, M., 4, 5, 13, 21, 23, 24 Govaerts, C., 250, 251, 282 Goya, I., 150 Grabovsky, V., 313, 314, 321, 322, 323, 324 Graham, F. L., 107 Grahames, C., 259 Graves, D. T., 4 Graves, S. W., 229, 230 Gray, D., 301 Greaves, D. R., 379, 381, 383, 384, 385 Green, C. E., 322 Green, M. D., 285 Gribble, A. D., 175, 253, 265, 266, 267, 268 Griffin, P. R., 4, 175, 274 Griffith, M. T., 174, 260 Grigorova, I., 314, 324 Grillet, B., 4, 5, 21 Grimberg, B. T., 195 Gronenborn, A. M., 53 Gronert, K., 383 Groot, P. H., 175, 253, 265, 266, 267, 268 Gross, S. P., 341, 343, 344 Gruijthuijsen, Y. K., 178 Grundner, C., 153, 159 Guarnieri, F., 178 Guevara, J., Jr., 9 Gulina, I. V., 150, 259 Guo, Q., 238, 240 Gurevich, V. V., 238, 240, 242, 245 Guth, A. C., 154, 156 Gutierrez, J., 150, 175, 180 H Hackney, L. A., 255, 259 Hada, T., 265 Hadley, T. J., 193 Haelens, A., 6, 7, 8, 9, 10 Haenel, J., 21 Haitina, T., 176 Halatin, P., 128, 129 Hale, J. J., 255 Hall, S. E., 270 Hallmann, R., 314, 322 Hamel, D. J., 31, 71 Hamill, A. L., 382 Hamm, H. E., 229, 235, 240, 243

Handel, T. M., 4, 20, 24, 31, 34, 35, 45, 46, 71, 72, 74, 75, 80, 81, 82, 89, 91, 93, 180, 200, 205, 282, 285, 301, 302 Hannon, R., 381, 383 Hans, D., 195 Hanson, M. A., 174, 259, 260, 267 Haraldsen, G., 194 Harder, T., 323 Harding, M. W., 381 Hardy, A., 175, 253, 265, 266, 267, 268 Haribabu, B., 150, 153, 383 Harrison, C., 111 Hart, R., 381, 383, 384, 385 Hartley, O., 31 Hartman, C. U., 324, 326 Hartmann, T., 314, 324 Hashimoto, H., 21 Haskell, C. A., 175, 180 Haslett, C., 382 Hass, P. E., 5 Hatse, S., 256 Hayflick, J. S., 313 Haynes, K., 382 He, T., 208 He, W., 193 Hebert, C. A., 5, 174, 251, 297 Heilman, S. M., 345 Heim, R., 113, 219 Heit, B., 312 Hemker, H. C., 134 Hemmerich, S., 74 Henderson, R., 174, 260 Henderson, R. B., 381, 394 Hendrick, A. G., 381, 383, 384, 385 Henneicke, H. H., 5 Henzel, W. J., 289 Herman, B., 300 Hermans, B., 253 Hermanson, G. T., 12 Hermens, W. T., 134 Hernanz-Falco´n, P., 107 Herndon, M. E., 76 Herre, J., 382 Herren, S., 301 Herz, A., 178 Hesk, D., 256 Hesselgesser, J., 196, 197 Heveker, N., 107, 209, 213 Hewlett, L., 313 Higgs, H. N., 327 Hildebrand, P. W., 174, 176 Hilliard, M., 384 Hirsch, S., 387 Hirshfeld, A., 178 Hitt, M., 107 Hitti, M., 195 Hobbs, J. A. R., 381, 394 Hoesel, L. M., 381

420

Author Index

Hoffmann, C., 229 Hofmann, K. P., 174, 176, 178 Hogaboam, C. M., 381 Hogg, N., 312, 313, 324, 381, 394 Hogquist, K. A., 399 Hollenberg, M. D., 282, 297 Holliday, N. D., 178 Holmes, W. D., 36, 38, 39, 42 Holst, B., 174, 176, 177, 178, 180, 181 Homburger, V., 111 Homey, B., 34, 106 Hong, S., 381, 383, 393 Hood, L. E., 11 Hoogewerf, A. J., 24, 33, 42, 75, 81 Hopkins, A. L., 194 Hori, T., 138, 174, 176, 177, 259, 260, 261 Horuk, R., 106, 174, 175, 179, 180, 191, 192, 193, 195, 208, 297 Horwitz, A. R., 312 Howard, M. C., 282 Howe, A. S., 285 Howie, S. E., 382 Hruby, V. J., 123, 128, 135, 137, 138, 139, 140, 141, 143, 144 Hsu, C.-H., 345 Hu, C. D., 222 Hu, Y., 322 Huang, C., 345 Huang, C. C., 153, 154, 159 Huang, H., 52 Huang, J., 231 Huang, J. H., 362 Huang, Y., 208 Hub, E., 200 Hubbell, C. M., 176 Hubbell, W. L., 176, 178 Hughes, C. E., 294 Hugues, S., 351 Hulme, E. C., 178 Humphries, G. M., 186 Hunkapiller, M. W., 11 Hunt, D. F., 4 Hurtado, O., 335 Hussan, S. S., 154 Huttley, G. A., 208 Huttner, W. B., 148, 149, 163 Hwang, S. K., 345 Hwang, S. T., 107 Hyun, Y. M., 324 I Ife, R. J., 175, 253, 265, 266, 267, 268 Iizawa, Y., 265 Ijzerman, A. P., 174, 260 Imai, M., 265 Imai, T., 150, 153 Imamura, M., 324 Imberty, A., 34, 46

Imoto, H., 274 Insel, P. A., 239 Irimia, D., 335 Irvine, B., 175, 274 Isaacs, H., 313 Isakson, P. C., 381 Ishihama, Y., 289 Ishima, R., 43 Islam, I., 175, 180 Issad, T., 111 Issafras, H., 213 Issekutz, T. B., 313 J Jaakola, V. P., 174, 260 Jacobson, L. P., 208 Jacobson, M. P., 264 Jakubik, J., 181 Jakway, J., 256 Jansen, J. C., 7, 8, 9, 10 Jansma, A., 31 Janssen, M. P., 134 Jarnagin, K., 74 Javitch, J. A., 177, 178 Jeang, K. T., 208 Jenkinson, S., 175, 254, 259 Jensen, A. D., 177 Jensen, P. C., 173, 175, 179, 180, 181, 252, 255 Jeon, N., 341, 343, 344 Jeon, N. L., 335, 336, 338, 339, 343, 344, 345 Jesaitis, J., 234, 240 Jessup, W., 323 Jezak, H., 253 Jhamandas, J. H., 282, 297 Ji, J., 254, 272, 273 Jiang, Y., 4 Jilma-Stohlawetz, P., 194, 199 Jimenez, C. R., 289 Jin, D. Y., 208 Jin, H., 32, 33, 36, 37, 45 Jin, Z., 208 Jockers, R., 111, 213 Johnsen, A. H., 176 Johnson, C. H., 213 Johnson, I., 301 Johnson, Z., 4, 20, 24, 34, 72, 73, 75, 82, 86, 88, 95, 282, 285, 301, 302 Johnston, D. A., 9 Jones, C., 254, 259 Jones, D. R., 107, 209 Jones, G., 231, 236, 240, 335 Jones, G. C., 24 Jones, K., 275 Jones, P. G., 178 Jones, T., 324, 326 Jorgensen, R., 176, 180 Joris, I., 380

421

Author Index

Jose, P. J., 381, 382 Juan, D., 107 Julius, D., 185, 186 Jun, C. D., 313, 314, 324, 328 K Kadi, L., 85 Kam, V. W., 270 Kamata, T., 326 Kanauchi, A., 213 Kanegasaki, S., 345 Kang, S., 208 Kanzaki, N., 265, 274 Karnik, S. S., 178 Karsan, A., 316 Kaslow, R., 208 Kasuya, A., 23 Katagiri, K., 322, 324 Kataoka, K., 265 Kaur, R., 175, 253, 265, 266, 267, 268 Kawaida, R., 23 Kawakami, N., 350 Kawamura, T., 107 Kawano, T., 150, 259 Kawashima, H., 89 Kay, T. A., 240 Kazmierski, W., 175, 254, 259 Keane, M. P., 106 Keenan, T. M., 345 Kehlen, A., 23 Kehoe, J. W., 148 Keij, J., 231, 236, 240 Kellett, E., 112, 213 Kellner, R., 149 Kelner, G., 52 Kemel, M. L., 140 Kempe, J., 382 Kenakin, T., 175, 181, 254, 259 Kenworthy, A. K., 116 Kernchen, F., 21 Kerppola, T. K., 222 Key, T. A., 238, 242, 245 Keys, R., 176 Khan, I. A., 410 Khazan, R., 245 Khorana, H. G., 176, 178 Kieffer, N., 313, 324 Kikuchi, Y., 345 Kilburn, R., 255 Kim, H. J., 345 Kim, M., 324 Kim, M. B., 324, 326 Kim, S., 345 Kim, U. T., 259 Kim, Y. J., 174, 176 Kimura, S. R., 263 Kinashi, T., 322, 324 King, D. S., 19

King, M. R., 324 Kinter, M., 8, 11 Kiprilov, E., 150 Kledal, T. N., 176, 178 Klee, W. A., 178 Klenk, D. C., 12 Klovins, J., 176 Kobilka, B., 139 Kobilka, B. K., 259, 260, 267 Kobilka, T. S., 174, 259, 260, 267 Koch, J., 153 Kochanny, M., 252, 269, 270, 271, 275 Kohr, W. J., 5 Kolaczkowska, E., 383 Kolattukudy, P. E., 150, 259 Kolbeck, R., 175, 179, 255 Kolchinsky, P., 149, 150 Kondru, R., 254, 272, 273 Koopmann, W., 74, 76, 81 Koovakat, S., 252, 269, 270, 271, 275 Kop, J. M. M., 134 Kosco-Vilbois, M. H., 282, 285, 301, 302 Koshland, D. E., 178 Koski, G., 178 Kostenis, E., 185, 186 Kottmann, A., 122 Koup, R. A., 208 Kowalczyk, A., 328 Krangel, M. S., 74, 76, 81 Krause, E., 21 Krauss, N., 174, 176 Kremer, L., 150, 175, 180 Kroeger, K. M., 212 Krohn, P. K., 12 Ku, G., 381 Kubes, P., 312, 334 Kubota, K., 23 Kuckuck, F., 229 Kuhmann, S. E., 254 Kuhn, J., 153, 154 Kuhn, P., 174, 259, 260, 267 Kuida, K., 381 Kuiper, J., 381 Kukkonen, J. P., 245 Kuksa, V., 178 Kuloglu, E. S., 53, 54, 56, 57, 58, 60 Kumasaka, T., 138, 174, 176, 177, 259, 260, 261 Kungl, A. J., 88, 93 Kunimoto, R., 174 Kunkel, E. J., 31 Kunkel, S. L., 107, 381 Kunstman, K., 208 Kuroda, M., 122 Kuschert, G. S., 24, 34, 36 Kuschert, G. S. V., 74, 80, 81, 92 Kusnetzow, A. K., 176 Kuta, E. G., 251 Kwong, P. D., 153, 159

422

Author Index L

Labas, Y. A., 219 Labbe-Jullie, C., 213 Labrecque, J., 256 Lagerstrom, M. C., 176 Lalani, A. S., 73 Lam, S. N., 154 Lambeir, A. M., 23 Landau, N. R., 208 Lander, A. D., 34 Lane, J. R., 174, 260 Lane, W. S., 149 Langley, D. R., 263 Langner, J., 23 Lanzavecchia, A., 106 Lapierre, J. M., 175, 253 Lapoumeroulie, C., 208 Larbi, K. Y., 314 LaRosa, G., 149, 313 Larrivee, B., 316 Larsen, C. G., 4 Laschinger, M., 312 Lau, E. K., 24, 33, 34, 76, 80, 81, 83, 87, 88, 90, 93, 282, 285, 301, 302 Laudanna, C., 312 Lauer, J. L., 21 Lauer, S., 230 Laurence, J. S., 90, 91 Lauro, C., 209 Lavielle, S., 139, 140 Lawrence, T., 384 Le, T. I., 174, 176, 177 Leach, K., 181 Lechleiter, J. D., 300 Lechler, R. I., 381 Lee, D., 324 Lee, G. S., 368 Lee, H. S., 162 Lee, J. S., 201 Lee, K. H., 345 Lee, M. M., 107 Lees, P., 303 Lefkowith, J. B., 381 Lenaerts, J. P., 5 Leonard, E. J., 4, 5 Leslie, A. G. W., 174, 260 Le Trong, I., 138, 259, 260, 261 Leung, D. W., 5, 153, 154 Leurs, R., 178 Lever, R., 301 Levoye, A., 213 Lewis, J., 233, 234, 237, 238, 240, 245 Lewis, M., 259 Lewis, R. S., 351 Ley, K., 312 Leybaert, L., 352 Li, J., 209 Li, W., 153, 156, 159

Liang, M., 175, 180, 252, 269, 270, 271, 275 Liang, Y., 208 Liapakis, G., 177, 178 Liauw, A., 259 Libert, F., 208 Liefde, I. V., 245 Liekens, S., 23 Liesnard, C., 208 Li Jeon, N., 344 Liliom, K., 275 Lim, W. K., 233, 234, 237, 238, 240, 245 Limatola, C., 209 Lin, F., 333, 335, 340, 341, 342, 343, 344, 345 Lin, S. W., 154 Linder, S., 327 Lindorfer, M. A., 245 Lindquist, R. L., 354, 361 Ling, M. K., 176 Lisa, V., 181 Littman, D., 122 Liu, C. C., 155, 161, 162 Liu, H., 222 Liu, L., 312 Liu, M. C., 149 Liu, R., 208 Liu, S.-Y., 335 Liu, T. Y., 51 Liu, Y., 324, 326 Liu-Chen, L. Y., 209 Livingston, D. J., 381 LiWang, P. J., 43, 282, 285, 301, 302 Lluis, C., 16, 116, 118, 222 Lo, Y. C., 253 Locati, M., 4, 106, 251, 255, 259 Loetscher, P., 31, 107 Lohof, A., 335 Lohse, M. J., 229 Lolis, E., 32, 33, 282 Lomb, D. A., 208 Look, A. T., 23 Loos, T., 3, 4, 5, 13, 21, 23, 24 Lopez, G. P., 229, 230, 231, 232, 236, 237, 238, 240, 241, 242, 243, 244 Lopez-Gimenez, J. F., 213, 219, 222 Lopez-Otin, C., 282, 283 Lortat-Jacob, H., 34, 46 Louie, L. G., 224 Lowe, D. G., 5 Lowell, C. A., 322 Lowman, H. B., 33, 36, 37 Lu, Z. L., 178 Lubkowski, J., 47, 90 Lucas, P., 107, 116 Lucas-Meunier, E., 213 Lucibello, M., 176 Luckow, B., 381 Luis, E. A., 5 Lukacs, N. W., 107

423

Author Index

Lukyanov, S. A., 219 Lundell, D. J., 256 Luscinskas, F. W., 315, 324, 326, 328 Luster, A. D., 179, 250, 322, 397, 398 Lustig, K. D., 185, 186 Luttichau, H. R., 176 Lynam, E., 238 Lynch, C. L., 255 M Ma, S., 324, 326 MacArthur, M. W., 177 Macartney, M., 175, 274 MacCleery, G., 233, 245 MacCoss, M., 255 MacDonald, J., 128, 129 MacDonald, M. E., 208 Mack, A. V., 162 Mack, M., 301, 381 Mackay, C., 106 Mackay, C. R., 106, 149, 313 Macleod, H. A., 124, 125, 126, 127, 128, 131, 134, 139, 140 Maeda, K., 255, 259 Mahieu, F., 5, 6 Mahon, M. J., 335 Mahoney, D. J., 24 Majno, G., 380 Majstoravich, S., 327 Mallia, A. K., 12 Mallinder, P., 259 Mallo, J., 116, 118 Mamdouh, Z., 312, 328 Mandell, J. G., 96 Man˜es, S., 107 Mann, M., 289 Manning, J. M., 382 Mantovani, A., 4, 5, 106, 251, 255, 259 Many, M. C., 153 Marcaurelle, L. A., 54 Marchesi, V., 325 Marchione, R. J., 156 Marie, C., 198 Markelov, M. L., 219 Marki, C., 283 Marquez, G., 150, 175, 180 Marshall, A. S. J., 382 Martin, B. A., 9 Martin, D. A., 209 Martin, K. A., 150 Martin, S. R., 208 Martı´n de Ana, A., 107, 108, 109 Martinez, A., 208, 209 Martı´nez, A. C., 107, 116, 150, 175, 180 Martinez, F. O., 255, 259 Martinez-A, C., 107, 108, 109 Martı´nez-Mun˜oz, L., 105, 116 Martinez-Pomares, L., 382, 390

Marullo, S., 213 Masters, B. R., 350, 351 Matheu, M. P., 350, 358, 364 Mathies, M., 381, 394 Mathis, G., 216 Matsushima, K., 4, 5, 174, 297 Matz, M. V., 219 Maudgal, P. C., 4, 5, 13, 21 Maurel, D., 221 Maxfield, F. R., 328 Maxwell, P. H., 314 May, L. T., 181 Mayadas, T. N., 328 Mayeenuddin, L. H., 245 McCarley, D., 175, 253 McClanahan, T., 106 McCombie, S. W., 254 McCornack, M. A., 43 McDowall, A., 312 McGeehan, G. M., 285 McGettrick, H. M., 314 McIntire, W. E., 229, 230, 233, 234, 237, 241, 243, 244, 245 McIntosh, F., 259 McQuibban, G. A., 282, 283, 285, 286, 294, 304 McVey, J. H., 381 McVey, M., 112, 213 Mechnikov, E., 381 Medzhitov, R., 380 Meguro, K., 265 Mellado, M., 105, 107, 108, 109, 115, 208, 209 Meller, J., 328 Mempel, T. R., 351, 361, 363, 371, 372 Menten, P., 23 Menz, R. I., 283 Mercier, J. F., 213 Mergler, M., 21 Merrifield, R. B., 21 Metz, M., 256 Miao, Z., 282 Michael, N. L., 224 Middleton, J., 24, 200 Millan, J., 313 Miller, L. H., 174, 192, 195, 197, 297 Miller, M. J., 349, 351, 361, 362, 363, 369, 373, 374 Miller, R. J., 220 Milligan, G., 107, 112, 207, 208, 209, 210, 213, 214, 215, 217, 219, 220, 222 Millington, O. R., 370 Mills, J. H., 162 Mills, S. G., 255 Milner, C. M., 24 Minh-Canh Nguyen, C., 344 Minowa, Y., 174 Mirzabekov, T., 149, 150 Mirzadegan, T., 175, 177, 253, 254, 272, 273 Mitsuya, H., 255, 259

424

Author Index

Mittal, S., 335 Miyakawa, T., 255 Miyano, M., 138, 174, 176, 177, 259, 260, 261 Modi, W. S., 52 Moechars, D., 253 Mohar, A., 106 Monod, J., 178 Monterrubio, M., 107, 116 Montoya, M. C., 313, 315, 327, 328 Moore, A. R., 303 Moore, K. L., 148, 149 Moore, M. J., 153, 154, 156 Moores, K. E., 175, 253, 265, 266, 267, 268 Moradi-Bidhendi, N., 381 Moree, W. J., 265 Moreno-Ortiz, M. C., 209 Morgans, D., Jr., 175, 253 Mori, J., 175, 259, 274 Morin, N. A., 324 Morrison, L. E., 216 Mort, J. S., 294 Mortier, A., 3, 4, 5, 13, 21, 23, 24 Mosadegh, B., 345 Moser, B., 16, 31, 107, 313 Mosley, M., 259 Motoshima, H., 138, 174, 176, 177, 259, 260, 261 Mouillac, B., 139, 140 Moukhametzianov, R., 174, 260 Mueller, H., 242 Mueller, P., 131 Mulkins, M., 175, 253 Mu¨ller, A., 106 Muller, W. A., 312, 328 Mulloy, B., 24 Munisamy, S., 335 Muroga, Y., 265 Murphy, E., 106 Murphy, P. M., 106, 174, 251, 282, 297 Murzin, A. G., 53 Muthukumaraswamy, N., 242 Muyldermans, G., 208 Muzio, V., 301 Myung, C. S., 245 N Nakajima, H., 149 Nakashima, K., 21 Nakata, H., 255, 259 Nakatsu, S., 149 Nakayama, T., 322 Nakayama-Hamada, M., 23 Napier, C., 175, 274 Naruse, K., 52 Nash, G. B., 314 Nasman, J., 245 Nathan, C., 380 Natori, Y., 52

Navarro, G., 116, 118 Navenot, J.-M., 275 Neal, M. J., 181 Neldon, D., 238 Nelson, D. J., 253 Nelson, R. D., 335 Neote, K., 192, 193, 198 Nesmelova, I. V., 34, 43, 53 Ness, T. L., 381 Neubig, R., 233, 234, 237, 238, 240, 242, 245 Neubig, R. R., 234, 238, 240, 245 Neumann, A. U., 208 New, D. C., 107 Newman, W., 149 Newton, G., 328 Neylan, J. F., 193 Neyts, J., 23 Nguyen, C. M., 341, 343, 344 Nguyen, Q. T., 352 Nicholson-Dykstra, S., 327 Nicola´s, E., 21 Niehrs, C., 149 Niijima, S., 174 Nishikawa, Y., 274 Nishimura, O., 265, 274 Nitta, N., 345 Nolan, J. P., 229, 230, 231, 236, 240 Nomura, H., 4 Nomura, Y., 345 Noppen, S., 4, 5, 13, 21 Norcross, M. A., 107, 209 Norman, R., 255, 259 Notake, M., 4 Nourshargh, S., 312, 314, 335, 381, 383 Nusrat, A., 324, 326 Nygaard, R., 175, 176, 179, 180, 181, 255 O Oades, Z. G., 234, 240 Oakes, P. W., 324 Obin, M. S., 5 O’Brien, T. R., 208 Ochs, H. D., 313, 325, 327 Oerlecke, I., 176 Ogata-Aoki, H., 255, 259 Ogawa, Y., 265 Ohsaka, M., 23 Okada, T., 138, 174, 176, 177, 259, 260, 261, 351, 352, 374 Okamoto, M., 265, 274 Okonogi, K., 265 Okuno, Y., 174 Oldham, W. M., 229, 240, 243 Oliani, S. M., 393 Olson, B. J., 12 Olson, W. C., 154, 155 Olszyna, D. P., 198

425

Author Index

Omann, G. M., 234 Ono, M., 23 Ooms, M., 282, 297 Opdenakker, G., 4, 5, 6, 7, 8, 9, 10, 13, 16, 21, 23 Oppenheim, J. J., 4, 174, 297, 384 Orlikowsky, T. W., 199 Osborne, D. A., 275 Osmond, R. I., 89, 90 Ottino, J. M., 231, 232 Ouyang, Y., 149 Overall, C. M., 281, 282, 283, 285, 286, 294, 297, 301, 304 Owen, D. A., 381 Owen, P., 16, 283 Owens, C. M., 153 Oyamada, Y., 4 Ozbun, M. A., 230, 236, 237 P Paavola, C. D., 33, 37, 39, 88, 90, 93 Packman, L. C., 21 Page, C., 301 Painter, R. G., 234, 240 Pakianathan, D. R., 251 Palani, A., 254 Palczewski, K., 138, 174, 176, 177, 178, 208, 259, 260, 261 Palmer, A. G. III, 57 Panneels, V., 153 Paoletti, S., 33 Papadopoulus, E. J., 107 Paralin, C., 149 Pardo, L., 177 Parenty, G., 208, 209, 213, 214, 217, 220 Parish, C. R., 24 Park, C. K., 139 Park, J., 283 Park, J. H., 174, 176 Park, J. W., 345 Parker, I., 349 Parkos, C. A., 324, 326 Parks, E., 107 Parmentier, M., 23, 24, 177, 208, 213, 250, 251, 282 Parrill, A. L., 275 Parrillas, V., 116 Parsons, J. T., 312 Pastuszyn, A., 236, 237 Pasvolsky, R., 313, 322 Patchett, A. A., 176 Patel, A. B., 178 Patel, D. D., 150, 153 Patel, K. D., 314 Patterson, A. M., 24 Paul-Clark, M. J., 381 Pausch, F., 314 Pavia, J., 178

Paxton, W. A., 208 Pease, J. E., 250, 251, 252, 253, 269, 282 Pediani, J., 213 Pediani, J. D., 219, 222 Pedroso, E., 21 Peiper, S. C., 193, 275 Pello, O. M., 116 Peltier, W. R., 231, 232 Pepperkok, R., 116 Percherancier, Y., 107, 209, 213 Perez, S., 34, 46 Periasami, A., 113, 114 Perkins, B. N., 328 Perretti, M., 303, 381, 383, 393 Perros, M., 259 Perroy, J., 111 Persuh, M., 154 Petasis, N. A., 381, 383 Peters, N. C., 350, 351, 364 Peterson, F. C., 51, 54, 57, 65, 72, 74, 76, 158 Petit, S. J., 250 Pfirstinger, J., 381 Pfleger, K. D., 111, 224 Phillips, R. M., 252, 269 Phillipson, M., 312 Piali, L., 313 Pierini, L. M., 328 Piliponsky, A. M., 380 Pin, J. P., 221 Pineyro, G., 112 Pinho, V., 86 Piston, D. W., 213, 360 Pitchford, S. C., 381 Pitman, M. R., 283 Piyasena, M. E., 231 Pless, R., 349 Plytycz, B., 383 Pollok, B. A., 113 Polsky, I., 175, 253 Ponath, P. D., 149, 282 Poo, M., 335 Pope, A. J., 112 Posner, R. G., 229 Poubelle, P., 382, 383 Pouyani, T., 148 Power, C., 282, 283, 285, 286, 294, 297, 304 Power, C. A., 24, 174, 176, 297 Poznansky, M. C., 335 Prahl, A., 47 Prasher, D. C., 219 Preissner, W. C., 5 Premack, B., 282 Preobrazhensky, A. A., 150 Prezeau, L., 221 Proost, P., 3, 4, 5, 6, 7, 8, 9, 10, 13, 16, 21, 23, 24, 84 Prossnitz, E. R., 229, 230, 233, 234, 237, 238, 239, 240, 241, 242, 243, 244, 245

426

Author Index

Proudfoot, A. E., 4, 20, 24, 33, 34, 35, 53, 71, 72, 74, 76, 81, 82, 83, 86, 88, 90, 93, 106, 250, 251, 282, 285, 301, 302, 381 Provenzano, M. D., 12 Provitera, P., 229 Pruenster, M., 194, 201 Pruijn, G. J., 21 Puente, X. S., 282, 283 Put, W., 4, 5, 21, 23, 24 Puzon, W., 326 Q Qiu, H., 256 Quie, P. G., 335 Quillan, M., 335 R Rainger, G. E., 314 Rajakariar, R., 384 Ramagali, L. S., 9 Ramirez-Weinhouse, M. M., 265 Ramos, C. D., 86 Ramsay, D., 112, 213 Ramsay, G., 128, 129 Rankin, S. M., 381 Ransnas, L. A., 239 Ransohoff, R. M., 31 Rao, R. M., 324, 326 Rao, T. S., 381 Rappsilber, J., 289 Rasmussen, S. G., 174, 177, 259, 260, 267 Ratnala, V. R., 174 Raz, E., 106 Rees, S., 112, 213 Rehfeld, J. F., 149 Reichner, J. S., 324, 394 Reid, D. M., 382 Ren, D., 220 Rhee, S. W., 335, 345 Ribeiro, S., 179 Rickett, G., 175, 274 Ridley, A. J., 312, 313 Riemann, D., 23 Rietdorf, J., 116 Ritchie, D. W., 277 Rittirsch, D., 381 Rives, M. L., 221 Roberts, C. R., 283, 285, 301 Robey, E. A., 350 Robinson, E. A., 4, 5 Robinson, J. E., 153, 154, 155, 159 Robishaw, J. D., 228 Rocheleau, J. V., 360 Roderiquez, G., 107 Rodriguez, L. V., 9 Rodrı´guez-Frade, J. M., 105, 107, 108, 109, 116, 208, 209

Roeske, W. R., 139 Rogers, K. A., 313 Rogers, T. J., 209 Rollins, B., 149 Roncal, F., 107 Ronsse, I., 4, 5, 13, 21, 23, 24 Rosas, M., 382 Rose, M., 301 Rose, S. S., 313 Rosen, S. D., 107 Rosenbaum, D. M., 174, 259, 260, 267 Rosenberg, E. S., 153, 159 Rosenkilde, M. M., 173, 174, 175, 176, 177, 178, 179, 180, 181, 252, 255, 256, 259 Rosenthal, W., 178 Rosignoli, G., 381, 383 Rosser, M., 175, 180 Rossi, D., 106 Rot, A., 191, 194, 200, 201, 313 Roth, C. B., 174 Roth, J. T., 285 Roth, S. J., 313 Rothstein, E. C., 360 Rotstein, D., 254, 272, 273 Roughley, P. J., 294 Rousseau, R. F., 53 Rouzer, C. A., 382 Rucker, J., 208 Rudin, D. O., 131 Ruffing, N., 149 Ruiz-Arguello, M. B., 73 Rusconi, S., 195 Russ, A., 381, 383, 384, 385 Ryden, L., 7, 8, 9, 10 Ryu, E. K., 47 Ryu, Y., 155 S Saadi, W., 335, 341, 343, 344, 345 Sabio, M., 275 Sackstein, R., 314, 315 Sadir, R., 74 Saeki, H., 107 Saetta, M., 405 Saffroy, M., 139, 140 Sagan, S., 139, 140 Sage, P. T., 313, 325, 327 Sagiv, A., 314, 324 Sakakibara, Y., 149 Sakmar, T. P., 148, 154, 158 Sako, D., 148 Salahpour, A., 108, 213 Salamon, Z., 123, 124, 125, 126, 127, 128, 129, 131, 132, 133, 134, 135, 137, 138, 139, 140, 141, 143, 144 Salas, A., 313, 314, 324, 328 Saldanha, J. W., 252, 269

Author Index

Salgado, G. F., 139, 143 Sallusto, F., 106, 250 Samadani, A., 335 Samson, M., 208 Samson, T., 328 Sanchez-Madrid, F., 312, 313, 315, 327, 328 Sandig, M., 313 Sanfiz, A., 158 Sanishvili, R., 174 Sankuratri, S., 254, 272, 273 Santella, J. B. III, 259 Santo, N. V., 149 Saperstein, D. A., 208 Saraf, M. A., 107 Saragosti, S., 208 Sarantos, M. R., 322 Sasisekharan, R., 75 Sassetti, C., 107 Sato, M., 21 Sato, T., 345 Saunders, J., 265 Sauty, A., 403, 405 Savino, B., 106 Savino, Y., 245 Savitsky, A. P., 219 Sawada, H., 265, 274 Sax, B., 21 Scarlata, S., 229 Schaff, U. Y., 322 Schagger, H., 8 Schall, T. J., 107, 282 Scheer, A., 178 Scheerens, H., 52 Scheerer, P., 174, 176 Scheiermann, C., 314 Schenauer, M. R., 93 Schenkel, A. R., 312 Scherle, P. A., 253 Schertler, G. F. X., 174, 260 Schiller, P. W., 112 Schioth, H. B., 176 Schlyer, S., 252, 269, 270, 271, 275 Schmidt, R. A., 131 Schmitzler, C. E., 154, 155 Schmutz, C., 24 Schneider, K., 21 Schnitzler, C. E., 153, 154, 156 Scholondorff, D., 381 Schols, D., 256 Schrader, N. L., 382, 383 Schreiber, T. H., 314, 315 Schro¨der, J. M., 5 Schuck, P., 88 Schultz, P. G., 155, 161, 162 Schutyser, E., 4, 5, 6, 13, 21, 23, 24 Schwab, J. M., 382 Schwartz, C., 128, 129 Schwartz, M. A., 312

427 Schwartz, T. W., 174, 175, 176, 177, 178, 179, 180, 181, 252, 255, 256, 259 Sciuto, T., 315, 328 Sciuto, T. E., 313, 325, 327 Scott, G. J., 16 Scott, W. A., 382 Seamer, L. C., 229 Sedgwick, A. D., 303 Seeber, R. M., 111 Seed, B., 148 Sehrawat, S., 328 Seibert, C., 53, 148, 158, 254 Seitz, M., 107 Sekar, R. B., 113 Seligmann, B. E., 242 Seljelid, R., 383 Sellars, D. D., 383 Serhan, C. N., 381, 382, 383, 393 Serrador, J. M., 313, 315, 327, 328 Serrano, A., 107, 116 Serrano-Vega, M. J., 174, 260 Seto, M., 274 Sexton, P. M., 181 Seyfried, N. T., 96 Shabanowitz, J., 4 Shaffer, A. F., 381 Shahrara, S., 35 Shahzidi, S., 383 Shakhar, G., 351, 361 Shakri, R., 153 Shamri, R., 312, 313, 314, 321, 323 Shan, L., 61 Shaner, N. C., 219 Sharma, A., 196 Sharma, S., 252, 269, 270, 271, 275 Shaw, G. D., 148 Shaw, J. P., 47 Shaw, S. K., 324, 326, 328 Shen, H., 193 Sheppard, H. W., 224 Sheppard, R. C., 16 Sherman, N. E., 8, 11 Sherman, W., 264 Sheves, M., 178 Shi, L., 177, 178 Shi, M., 233, 234, 237, 238, 240, 245 Shillito, H., 175, 253, 265, 266, 267, 268 Shimaoka, M., 314, 324 Shimizu, T., 21 Shimonaka, M., 322 Shin, H. S., 345 Shinder, V., 312, 313, 314, 315, 320, 327 Shiota, T., 265 Shiraishi, M., 265, 274 Short, R. D., 24 Showalter, S. D., 5 Shriver, N. T., 76 Shuler, M. L., 345

428 Shulman, Z., 311, 313, 314, 322, 324 Shyu, Y. J., 222 Sielaff, I., 71, 82, 86, 87, 95 Sikorski, E. E., 322 Silva, C., 282, 297 Siminovitch, K. A., 327 Simmons, G., 176 Simmons, R. L., 335 Simon, S. I., 322 Simonis, C., 381 Simons, P. C., 229, 230, 232, 233, 234, 236, 237, 238, 239, 240, 241, 243, 244, 245 Singh, A. P., 153 Singh, S., 195 Sipe, J. D., 381 Sixt, M., 314, 324 Skeel, A., 5 Skelton, N. J., 251 Skerlj, R. T., 256, 259 Sklar, L. A., 227, 229, 230, 231, 232, 233, 234, 236, 237, 238, 239, 240, 241, 242, 243, 244, 245 Slight, I., 107, 209, 213 Slocombe, P. M., 107 Smailbegovic, A., 301 Smider, V. V., 162 Smit, M. J., 178 Smith, A., 313, 324 Smith, M. W., 208 Smith, P. K., 12 Smith, S. O., 178, 254 Smith-Burchnell, C., 175, 259, 274 Smits, G., 153 Snyderman, R., 383 So, P. T., 350, 351 Sodek, J., 286 Sodroski, J. G., 149, 150, 153, 154, 155, 156, 159, 213 Sogah, D., 149 Sohy, D., 208 Solomon, K. A., 253 Soriano, A., 222 Soriano, S. F., 107 Sorokin, L. M., 314 Soto, H., 106 Soulages, J. L., 138, 139 Sozzani, S., 5 Sprang, S. R., 228, 229 Springael, J. Y., 177, 208, 213 Springer, T. A., 4, 313, 314, 317, 324, 325, 327, 328 Spurrell, J. C., 405 Stanfield, R. L., 154 Stangassinger, M., 381 Stanley, P., 313, 324 Starr, A. E., 281, 282, 283 Steeber, D. A., 383 Steele, C., 382

Author Index

Stein, J. V., 107 Steinbach, P. A., 219 Stenkamp, R. E., 138, 174, 176, 177, 259, 260, 261 Stevens, R. C., 174, 259, 260, 267 Sticherling, M., 5 Stockdale, M., 259 Stone, M. J., 250 Strader, C. D., 176 Streaty, R. A., 178 Strieter, R. M., 107, 381 Stroock, A. D., 338 Stropova, D., 139 Strupat, K., 289 Struyf, S., 4, 5, 13, 21, 23, 24 Struyf, T. A., 6 Stuart, A. C., 57 Stuhlmann, H., 208 Stults, J. T., 289 Sudo, M., 265 Sugg, E. E., 176 Suiko, M., 149 Sullivan, N., 149 Sun, Y., 149 Sunahara, R. K., 229 Sutcliffe, J. G., 181 Suzuki, A., 23 Suzuki, S., 211 Swaminathan, G. J., 33, 47 Sweeney, W. V., 21 Sykes, B. D., 43 Szabo, C., 383 Szabo, I., 209 T Tagat, J. R., 254 Takada, Y., 326 Takahashi, A., 300 Takamoto, K., 96, 97 Takaoka, Y., 255, 259 Takazawa, T., 23 Tam, J. P., 21 Tamamura, H., 107, 209, 213 Tamatani, T., 345 Tamon, A., 174 Tanaka, S., 4 Tang, J. X., 324 Tang, M., 154 Tang, Q. Z., 352 Tang, W. J., 238, 240 Taniuchi, I., 122 Tate, C. G., 174, 260 Taveras, A., 256 Taylor, P. R., 382, 390 Tebben, A. J., 249, 263 Tejedor, R., 313, 315, 327, 328 Teller, D. C., 138, 174, 176, 177, 259, 260, 261

429

Author Index

Tesmer, J. J., 229 Tester, A. M., 282, 283 Tharp, W. G., 335 Thelen, M., 107 Thian, F. S., 174, 259, 260, 267 Thiele, C., 149, 163 Thiele, S., 175, 179, 180, 181, 252, 255 Thomas, E. A., 181 Thomay, A. A., 394 Thompson, D. A., 154 Tho¨rnqvist, S., 21 Thornton, J. M., 177 Thurlow, R., 213 Tian, Y., 107 Tien, H. T., 131 Tigyi, G., 275 Tikhonov, I., 52 Tilg, H., 199 Timsit, J., 381 Tinel, N., 221 Tjonahen, E., 381, 383, 393 Tojo, Y., 255 Tollin, G., 123, 124, 125, 126, 127, 128, 129, 131, 132, 133, 134, 135, 137, 138, 139, 140, 141, 143, 144 Tollinger, M., 58 Toner, M., 335, 336 Tonkinson, N., 259 Tonomura, K., 174 Toomre, D., 313 Topiol, S., 275 Toran, J. L., 107, 209 Torchia, D. A., 43 Toro, M. J., 116 Torrens, Y., 139, 140 Toth, P. T., 220 Tournamille, C., 192 Trabanino, R. J., 252, 269, 270, 271, 275 Tran, D. N., 155 Tran, M., 314 Trettel, F., 209 Trieter, R. M., 106 Trinquet, E., 216, 221 Trivedi, S., 384 Tsai, M., 380 Tsamis, F., 254 Tsao, M. L., 162 Tsien, R. Y., 219 Tsoni, S. V., 382 Tsuchiya, K., 255, 259 Tsuruo, T., 322 Tsutsumi, T., 265 Tucek, S., 184 Tuinstra, R. L., 33, 53, 54, 57, 58, 60, 61, 64 Twomey, B. M., 107

U Ulven, T., 181, 252 Upadhyaya, A., 335 Urizar, E., 208 V Vahidi, B., 345 Vaidehi, N., 252, 269, 270, 271, 275 Valencia, A., 107 Valente, A. J., 4 Vallie`res, M., 112 Van, D. J., 177 Van Beeumen, J., 4 van Berkel, T. J. C., 381 van Berkel, V., 73 Van Brocklyn, J. R., 275 van Buul, J. D., 328 Van Cao, T., 381 Van Damme, J., 4, 5, 6, 7, 8, 9, 10, 16, 21, 23, 24 Van de Borne, K., 5 Vandercappellen, J., 23, 24 van der Graaf, P. H., 111 Van Dyke, T. E., 383 van Es, T., 381 Van Leuven, P., 16, 21 Van Lommen, G., 253 Vannier, C., 149 van Oudenaarden, A., 335 van Rooijen, N., 383 van Venrooij, W. J., 21 van Wanrooij, E. J. A., 381 Van Wauwe, J. P., 253 Varga, E., 135, 138, 139, 140, 141, 144 Vargo, B. J., 259 Vasilieva, N., 150, 153, 154, 155, 156, 159 Vassart, G., 153, 208, 213, 250, 251, 282 Vauquelin, G., 245 Velasquez, J., 174 Veldkamp, C. T., 34, 35, 36, 37, 39, 40, 41, 43, 44, 45, 53, 54, 57, 158 Velo, G. P., 381 Velzing-Aarts, F. V., 199 Venturi, M., 153, 159 Vergara, C., 193 Verghese, M. W., 383 Vergote, D., 282, 297 Verhofstede, C., 208 Verity, A., 381, 383 Verpoest, S., 5 Vicente-Manzanares, M., 312, 313, 315, 327, 328 Vidi, P. A., 222 Vielhauer, V., 381 Vila-Coro, A. J., 107, 108, 109, 208, 209 Vilardaga, J. P., 229 Vilven, J., 238 Vincent, P., 328 Vink, C., 178

430

Author Index

Vintersten, K., 360 Viola, A., 250 Virag, L., 383 Vittinghoff, E., 208 Vives, R. R., 34, 89 Vlahov, D., 208 Vo, L., 16, 283 Voisin, M. B., 314 Volkman, B. F., 51, 158 Volkmer-Engert, R., 107, 209, 213 von Andrian, U. H., 313, 322, 361 von Arnim, A. G., 213 von Hundelshausen, P., 33, 313, 314, 321 von Jagow, G., 8 Vorherr, T., 21 Vossenaar, E. R., 21 Vuust, J., 149 Vynckier, A. K., 5 W Wacker, D. A., 259 Wada, H. G., 186 Wagner, C., 285 Wagner, S. N., 106 Wahl, S. M., 382 Walker, M. D., 275 Wallace, J. L., 282 Waller, A., 229, 230, 234, 238, 239, 240, 245 Walz, A., 4, 16 Wang, D. A., 275 Wang, J., 107, 209, 282 Wang, J. D., 52 Wang, L., 153, 159, 200 Wang, Q., 245 Wang, S., 314, 341, 343, 344 Wang, S.-J., 335, 343, 344 Wang, Y., 131, 138, 139, 282 Wang, Z., 259 Wara, D., 322 Ward, P. A., 381 Warne, T., 174, 260 Water, L. V. D., 335, 336 Watson, C., 175, 254, 259 Watson, R. J., 381 Watts, V. J., 222 Weatherhead, G. S., 175, 253 Webb, L. M., 75 Weber, C., 313, 314, 321 Weber, K. S., 313, 314, 321 Weber, P. C., 313, 314, 321 Webster, R., 175, 274 Wei, S. H., 371 Weiler, P., 21 Weis, W. I., 174, 259, 260, 267 Welch, P. K., 259 Wells, T. N., 24, 176, 282, 285, 301, 302 Wendler, O., 314 Weng, Y., 255

Wengner, A. M., 381 Wescott, W. C., 131 Wess, J., 178, 186 Westby, M., 175, 259, 274 Westrich, G. L., 382, 383 White, G. E., 379 White, J. G., 368 White, R. J., 294 Whitesides, G. M., 335, 336, 338, 339 Whittle, J. D., 24 Wilhelm, R., 175, 253 Wilkinson, G., 107, 209, 210, 217, 220 Williams, D. L., 382 Williams, T. J., 251, 252, 253, 269, 381, 382 Williamson, M. J., 4 Willment, J. A., 382 Willoughby, D. A., 303, 381 Wilson, C. H., 283 Wilson, I. A., 154 Wilson, S., 107, 112, 209, 210, 217, 220 Winkler, C., 208 Winter, E., 321, 323 Wise, E. L., 253 Withka, J. M., 57 Witt, C. M., 351 Witt, D. P., 34 Wokosin, D. L., 349, 353 Wolf, M., 283 Wolinsky, S. M., 208 Wong, J. P., 282 Wong, R. S., 256 Wong, S. Y. C., 382 Wong, Y. H., 107 Woolf, E., 313, 314, 322, 324 Wreggett, K. A., 254, 259 Wright, P. L., 150, 153, 156, 159 Wright, T., 259 Wu, L., 149 Wu, M., 345 Wu, P., 212 Wu, Y., 227, 229, 230, 231, 232, 234, 236, 237, 238, 239, 240, 241, 242, 243, 244, 245 Wuyts, A., 5, 6, 7, 8, 9, 10, 16, 21, 23 Wyatt, R., 149, 150, 154 Wyman, J., 178 X Xiang, S. H., 154 Xiong, K., 313 Xu, G., 96 Xu, R., 178 Xu, Y., 213 Y Yabuuchi, H., 174 Yacono, P., 328 Yadav, R., 335

431

Author Index

Yamada, M., 4, 21 Yamada, N., 107 Yamammura, H. I., 135, 138, 140 Yamamoto, K., 23 Yamamoto, M., 138, 174, 176, 177, 259, 260, 261 Yamamura, H. I., 138, 139, 140, 141, 144 Yanez-Mo, M., 313, 315, 327, 328 Yang, G., 253 Yang, K., 176 Yang, L., 315, 324, 326, 328 Yang, W., 324 Yang, Y., 21 Yao, Z., 139 Yaqoob, M. M., 384 Yasuda, H., 245 Yau, P., 211 Yazdanbakhsh, K., 208 Yeh, A. T., 364 Yin, P. D., 255, 259 Ying, W., 254 Yip, Y. K., 5 Yona, S., 381, 383, 393 Yoshida, M., 381, 383 Yoshida, T., 52, 345 Yoshie, O., 322 Yoshimura, T., 4, 5, 384 Young, L., 345 Young, R. E., 381, 383 Yu, Y., 34, 42, 92 Yuan, W., 106 Yukhayeva, L., 155

Yung, L. Y., 107 Yuste, R., 350 Z Zaballos, A., 150 Zagorski, J., 382 Zampella, G., 255, 259 Zaraisky, A. G., 219 Zaratin, P., 301 Zendman, A. J., 21 Zeng, F. Y., 186 Zhang, H., 322 Zhang, J., 254, 272, 273, 327 Zhang, L., 4, 208 Zhang, W.-B., 275 Zheng, C., 259 Zhou, P., 345 Zhu, G., 175, 179, 180, 181, 255 Zhuang, T., 93 Zicha, D., 335, 398 Zigmond, S. H., 335, 398 Zimmermann, T., 116, 118 Zinselmeyer, B. H., 349, 350, 364, 370, 371 Zlotnik, A., 106 Zoffmann, S., 282 Zou, Y., 122 Zoumi, A., 360 Zrike, J. M., 382 Zwartz, G., 231, 232, 238, 242, 243 Zwick, M. B., 153, 159

Subject Index

A b2-Adrenergic receptor homology modeling CCR1 modeling, 269–271, 272 CCR2 antagonist modeling, 267–269 CCR5 modeling, 272–274 prospects, 274–275 protocol development, 260–261, 263–265 sequence alignment with rhodopsin and chemokine receptors, 262 Allosteric binding, chemokine receptor antagonists, 251–259 Aminopeptidase N, chemokine substrate identification, 23–24 Analytical ultracentrifugation chemokine oligomerization, 35–39 glycosaminoglycan–chemokine interaction characterization, 78, 90–91 AUC, see Analytical ultracentrifugation B Bimolecular fluorescence complementation, chemokine receptor heterodimerization studies, 222 Bioluminescence resonance energy transfer chemokine receptor dimerization characterization, 112–113 chemokine receptor heterodimerization studies data analysis, 215 examples, 213 saturation BRET2, 214–215 single-point BRET2, 213–214 sequential bioluminescence–fluorescence resonance energy transfer, 118–119 BRET, see Bioluminescence resonance energy transfer C Calcium flux chemokine receptor activation by cleaved chemokines, 300–301 G protein-coupled receptor signaling assay, 187 CCL2, oligomerization, 32 CCR1 allosteric binding of antagonists, 252

allosteric modulators, 181–183 homology modeling with b2-adrenergic receptor, 269–271, 273 transmembrane segments, 182 CCR2 allosteric binding of antagonists, 253 antagonists, 175 homology modeling b2-adrenergic receptor, 267–269 rhodopsin balloon expansion approach, 265–267 CCR3, allosteric binding of antagonists, 253 CCR4, allosteric binding of antagonists, 254 CCR5 allosteric binding of antagonists, 254–255, 259 antagonists, 175 homology modeling with b2-adrenergic receptor, 272–274 tyrosine sulfation antibody tyrosine sulfation, 153–154 overview, 149–150 peptide studies applications of peptides, 159–160 cell-free sulfation, 158, 165–166 modulation of sulfation, 158–159 production in mammalian cells, 156, 158 synthetic peptides, 155–156 sites, 151–152 virulence significance, 154–155 CCR8 agonists and activation, 175, 179–181 allosteric binding of antagonists, 255 Cecal ligation and puncture model, acute inflammation, 381 Chemokine oligomerization analytical ultracentrifugation, 35–39 dynamic light scattering, 36, 40–41 fluorescence polarization, 36, 41 Fourier transform ion cyclotron resonance mass spectrometry, 36, 42 functional overview, 33–35 nuclear magnetic resonance heteronuclear single quantum correlation spectroscopy, 36, 43–44, 46 nitrogen-15 heteronuclear relaxation, 43 nuclear Overhauser effect, 36, 44–45, 47 pulsed-field gradient diffusion, 36, 39–40 size exclusion chromatography, 42–43 structural overview, 32–33

433

434 Chemokine proteolytic processing cleavage assay in vitro incubation conditions, 285 materials, 283–284 endogenous protease cleavage assay, 286–287 functional characterization calcium flux assay of receptor activation, 300–301 chemotaxis in vivo air pouch model, 303–304 peritonitis model, 303–304 subdermal injection, 304 glycosaminoglycan binding, 301–303 overview, 295, 297 transwell migration assay, 297–300 mass spectrometry analysis of cleavage sites, 289–294 neo-epitope antibody detection of processed chemokines, 294–297 proteases, 282 TRIS-tricine polyacrylamide gel electrophoresis analysis, 287–288 Chemokine receptor dimerization confocal microscopy, 109–110 immunoprecipitation and Western blot, 108–109 overview, 106–107 resonance energy transfer techniques bioluminescence resonance energy transfer, 111 fluorescent resonance energy transfer, 113–118 overview, 111 sequential bioluminescence–fluorescent resonance energy transfer, 118–119 Chemokine receptor heterodimerization bimolecular fluorescence complementation, 222 coimmunoprecipitation epitope tags, 209, 221 incubation, centrifugation, and gel electrophoresis, 211–212 principles, 208–209 human immunodeficiency virus coreceptors, 208 overview, 207–208 resonance energy transfer bioluminescence resonance energy transfer data analysis, 215 examples, 213 saturation BRET2, 214–215 single-point BRET2, 213–214 fluorescence resonance energy transfer data analysis, 218 living cell studies, 218–221 time-resolved measurements, 216–218 principles, 212–213 Chemotaxis assays

Subject Index

chemokine proteolysis characterization air pouch model, 303–304 peritonitis model, 303–304 subdermal injection, 304 transwell migration assay, 297–300 leukocyte trafficking overview, 334 lymphocyte transendothelial migration, see Lymphocyte transendothelial migration microfluidics analysis of leukocyte migration in chemoattractant gradients cell loading, 341 data analysis chemotactic index, 343 effective chemotactic index, 344 image processing, 343 motility calculations, 343–344 subregion analysis, 344–345 environmental controls, 341 gradient generation measurement in microfluidic devices, 339 principles, 338–339 human blood leukocyte preparation, 339–340 microfluidics devices applications, 335–336 assembly, 340–341 design, 336–337 fabrication, 337 substrate preparation, 337–338 time-lapse optical microscopy, 341–342 T-cell chemokine-mediated recruitment assay in vivo adoptive transfer of T lymphocytes, 404–405 antagonist and inhibitory antibody testing, 410–411 bronchial alveolar lavage and analysis, 406–407 chemokine intrathecal administration, 405–406 chemokine mutant analysis, 408–409 chemokine receptor mutant analysis, 409–410 two-photon microscopy, see Two-photon microscopy zymosan-induced peritonitis model, see Zymosan-induced peritonitis Coimmunoprecipitation, chemokine receptor heterodimerization studies epitope tags, 209, 221 incubation, centrifugation, and gel electrophoresis, 211–212 principles, 208–209 Complement receptors, tyrosine sulfation, 150 Confocal microscopy, chemokine receptor dimerization characterization, 109–110

435

Subject Index

Controlled pore glass, protein concentration, 6 CXCL8 dimerization, 32 isoform isolation adsorption to controlled pore glass, 6 cation-exchange chromatography, 9–10 citrullination, 21, 23 denaturing gel electrophoresis, 8–9 Edman degradation sequencing, 11–12 enzyme-linked immunosorbent assay, 7–8 heparin affinity chromatography, 7 heparin binding characterization, 24–25 mass spectrometry, 10–11 overview, 5 peripheral blood mononuclear cell isolation and stimulation, 5–6 posttranslational modification characterization, 13–14 protein quantification assays, 12 reverse-phase high-performance liquid chromatography, 10 CXCL10 glycosaminoglycan binding, 74–75 isoform isolation adsorption to controlled pore glass, 6 cation-exchange chromatography, 9–10 citrullination, 21, 23 denaturing gel electrophoresis, 8–9 Edman degradation sequencing, 11–12 enzyme-linked immunosorbent assay, 7–8 heparin affinity chromatography, 7 heparin binding characterization, 24–25 mass spectrometry, 10–11 overview, 5 peripheral blood mononuclear cell isolation and stimulation, 5–6 protein quantification assays, 12 reverse-phase high-performance liquid chromatography, 10 oligomerization, 33 CXCL11, aminopeptidase N processing, 23–24 CXCR1, allosteric binding of antagonists, 255 CXCR2 allosteric binding of antagonists, 256 opioid receptor heterodimerization, 208–209, 213, 216, 220 CXCR3, Global Toggle Switch Model, 180–181, 184 CXCR4 allosteric binding of antagonists, 256 tyrosine sulfation, 149–150 CXL7, posttranslational modification, 4–5 D DARC, see Duffy antigen receptor for chemokines DLS, see Dynamic light scattering Duffy antigen receptor for chemokines

chemokine sink assays, 198–199 chemokine transcytosis assay, 200–202 enzyme-linked immunosorbent assay antagonist high throughput screening, 195–196 erythrocyte isolation and assay, 199–200 human immunodeficiency virus infection effects, 193 inflammation role, 194 ligands, 193 malaria receptor antagonist screening, 195–198 deficiency and resistance, 192 prostate cancer studies in knockout mice, 193–194 tyrosine sulfation, 153 Dynamic light scattering, chemokine oligomerization studies, 36, 40–41 E Edman degradation, chemokine sequencing, 11–12 ELISA, see Enzyme-linked immunosorbent assay Enzyme-linked immunosorbent assay chemokine isoforms, 7–8 Duffy antigen receptor for chemokines antagonist high throughput screening, 195–196 erythrocyte isolation and assay, 199–200 glycosaminoglycan–chemokine interaction characterization with enzyme-linked immunosorbent saturation binding assay, 77, 84–85 Equilibrium competition binding, glycosaminoglycan–chemokine interaction characterization, 77, 81–83 F Flow cytometry G protein-coupled receptor ternary complex dynamics analysis with rapid mix flow cytometry data standardization with fluorescence calibration beads, 230–231 instrumentation, 232–233 materials, 232–233 modular assembly on beads formyl peptide receptor solubilization, 235 G protein-coated bead preparation, 236–238 materials, 234 ternary complex assembly, 238–239 modular disassembly analysis G protein subunit disassembly, 243 guanine nucleotide-induced disassembly, 242–243 ligand dissociation, 244

436

Subject Index

Flow cytometry (cont.) overview, 239–240 receptor dissociation from G proteins, 243–244 spectrofluorometric measurement of ligand-receptor and G protein dissociation, 240–242 optimization, 231–232, 234 overview, 228–230 prospects, 245 T-cell activation assay, 402–404 zymosan-induced peritonitis and fluorescenceactivated cell sorting, 386–387 Fluorescence polarization, chemokine oligomerization studies, 36, 41 Fluorescence resonance energy transfer chemokine receptor dimerization characterization, 113–118 chemokine receptor heterodimerization studies data analysis, 218 living cell studies, 218–221 time-resolved measurements, 216–218 sequential bioluminescence–fluorescence resonance energy transfer, 118–119 Formyl peptide receptor, see G protein-coupled receptors Fourier transform ion cyclotron resonance mass spectrometry, see Mass spectrometry FRET, see Fluorescence resonance energy transfer G Gel filtration, see Size exclusion chromatography Glycosaminoglycan–chemokine interactions binding epitopes on chemokines, 74–75 challenges for study, 75–76 characterization analytical ultracentrifugation, 78, 90–91 cellular recruitment in vivo, 78, 85–86 comparison of techniques, 76–79 enzyme-linked immunosorbent saturation binding assay, 77, 84–85 equilibrium competition binding, 77, 81–83 fluorescence titration, 78, 87–88 heparin affinity chromatography, 77, 80–81 mass spectrometry Fourier transform ion cyclotron resonance mass spectrometry, 79, 93–95 hydrogen/deuterium exchange, 96–97 proteolytic footprinting of binding epitopes, 79, 95–96 radiolytic oxidation mapping, 96–97 nuclear magnetic resonance heteronuclear single quantum correlation spectroscopy, 79, 91–92 surface plasmon resonance, 78, 88–90 tritiated heparin binding assay, 77, 83–84

chemokine oligomerization role, 33–34 chemokine proteolytic processing characterization, 301–303 glycosaminoglycan types for study, 76 heparin binding characterization of chemokine isoforms, 24–25 history of study, 72–73 lymphotactin conformational equilibrium and binding effects, 61–67 pathophysiology, 73 viral immunomodulation, 73 GPCRs, see G protein-coupled receptors G protein-coupled receptors, see also specific receptors activation models, 176–178 chemokine two-site interaction hypothesis, 250–251 classification, 174 conformational diversity, 143–144 constitutive activity, 178–179 crystal structures, 174, 176 dimerization, see Chemokine receptor dimerization; Chemokine receptor heterodimerization G proteins in activation screening, 185–186 homology modeling, see b2-Adrenergic receptor; Rhodopsin plasmon waveguide resonance and signaling studies ligand and G protein binding analysis, 138–142 limitations, 143 lipid bilayer deposition, 131–132 membrane protein insertion, 136–138 spectral data analysis, 132–136 signaling assays calcium flux, 187 inositol trisphosphate assay in transiently transfected cells, 187–188 ternary complex dynamics analysis with rapid mix flow cytometry data standardization with fluorescence calibration beads, 230–231 instrumentation, 232–233 materials, 232–233 modular assembly on beads formyl peptide receptor solubilization, 235 G protein-coated bead preparation, 236–238 materials, 234 ternary complex assembly, 238–239 modular disassembly analysis G protein subunit disassembly, 243 guanine nucleotide-induced disassembly, 242–243 ligand dissociation, 244 overview, 239–240

437

Subject Index

receptor dissociation from G proteins, 243–244 spectrofluorometric measurement of ligand-receptor and G protein dissociation, 240–242 optimization, 231–232, 234 overview, 228–230 prospects, 245 therapeutic targeting, 124, 194 H Heparin binding characterization of chemokine isoforms, 24–25 CXCL10 binding characterization, 24–25 CXCL8 binding characterization, 24–25 tritiated heparin binding assay, 77, 83–84 Heparin affinity chromatography chemokine isoform purification, 7 glycosaminoglycan–chemokine interaction characterization, 77, 80–81 Heteronuclear single quantum correlation spectroscopy, see Nuclear magnetic resonance High-performance liquid chromatography, chemokine isoform reverse-phase chromatography, 10 HIV, see Human immunodeficiency virus HPLC, see High-performance liquid chromatography Human immunodeficiency virus coreceptors, see CCR5; CXCR4 Duffy antigen receptor for chemokines and infection effects, 193 I Immunoprecipitation, chemokine receptor dimerization characterization, 108–109 Inflammation, see Zymosan-induced peritonitis Inositol trisphosphate, chemokine receptor signaling assay in transiently transfected cells, 187–188 Interferon-g-inducible protein-10, see CXCL10 Interleukin-8, see CXCL8 IP3, see Inositol trisphosphate IP-10, see CXCL10 L Lymphocyte transendothelial migration immunofluorescent staining of integrins/ ligands and cytoskeletal adapters, 324–327 inflammatory cytokine activation, 312–313 live fluorescence imaging, 323–324 live imaging microscopy human T-cells

effector T-cell preparation, 317 endothelial cell preparation and stimulation, 318 materials and equipment, 316 principles, 314–315 shear flow measurements, 318–322 T-cell isolation, 317 murine T-cells materials, 322 shear flow measurements, 323 T-cell isolation, 322–323 overview, 312–314 real-time tracking of fluorescent-tagged proteins on endothelial cells, 327–329 Lymphotactin expression in disease, 52–53 functional overview, 52 purification, 54, 56 receptor, 52 structure conformationally-restricted variant engineering, 60–61 functional analysis of native state conformations, 61–65 glycosaminoglycan-binding residues and conformational equilibrium, 65–67 nuclear magnetic resonance conformational equilibrium interconversion kinetics, 57–60 native folding states, 56–57 overview, 53, 55 M Malaria receptor, see Duffy antigen receptor for chemokines Mass spectrometry chemokine isoforms, 10–11 chemokine oligomerization studies with Fourier transform ion cyclotron resonance mass spectrometry, 36, 42 chemokine proteolytic processing site analysis, 289–294 glycosaminoglycan–chemokine interaction characterization Fourier transform ion cyclotron resonance mass spectrometry, 79, 93–95 hydrogen/deuterium exchange, 96–97 proteolytic footprinting of binding epitopes, 79, 95–96 radiolytic oxidation mapping, 96–97 Microfluidics devices, see Chemotaxis assays Migration assays, see Chemotaxis assays; Lymphocyte transendothelial migration N NMR, see Nuclear magnetic resonance Nuclear magnetic resonance

438

Subject Index

Nuclear magnetic resonance (cont.) chemokine oligomerization studies heteronuclear single quantum correlation spectroscopy, 36, 43–44, 46 nitrogen-15 heteronuclear relaxation, 43 nuclear Overhauser effect, 36, 44–45, 47 pulsed-field gradient diffusion, 36, 39–40 glycosaminoglycan–chemokine interaction characterization with heteronuclear single quantum correlation spectroscopy, 79, 91–92 lymphotactin structure studies conformational equilibrium interconversion kinetics, 57–60 native folding states, 56–57 P Peptide synthesis, see Solid-phase peptide synthesis Plasmon waveguide resonance G protein-coupled receptor signaling studies ligand and G protein binding analysis, 138–142 limitations, 143 lipid bilayer deposition, 131–132 membrane protein insertion, 136–138 spectral data analysis, 132–136 instrumentation, 129–131 principles, 128–129 Prostate cancer, Duffy antigen receptor for chemokines knockout mice, 193–194 Pulsed-field gradient diffusion, see Nuclear magnetic resonance PWR, see Plasmon waveguide resonance R Rapid mix flow cytometry, see Flow cytometry Rhodopsin homology modeling CCR2 antagonist modeling with balloon expansion approach, 265–267 protocol development, 260–261, 263–265 sequence alignment with b2-adrenergic receptor and chemokine receptors, 262 RNA interference, tyrosyl-protein sulfotransferases, 165 S Sedimentation equilibrium, see Analytical ultracentrifugation Size exclusion chromatography, chemokine oligomerization studies, 42–43 Solid-phase peptide synthesis, chemokines chain synthesis, 15–20 deprotection, 19 side reaction control, 21–22 Sulfotyrosine, see Tyrosine sulfation

Surface plasmon resonance, see also Plasmon waveguide resonance glycosaminoglycan–chemokine interaction characterization, 78, 88–90 principles, 125–127 T T-cell, see also Chemotaxis assays; Lymphocyte transendothelial migration activation assay antigen-presenting cell preparation, 399–401 CD8 T lymphocyte purification and culture, 399–402 flow cytometry, 402–404 overview, 399 chemokine-mediated recruitment assay in vivo adoptive transfer of T lymphocytes, 404–405 antagonist and inhibitory antibody testing, 410–411 bronchial alveolar lavage and analysis, 406–407 chemokine intrathecal administration, 405–406 chemokine mutant analysis, 408–409 chemokine receptor mutant analysis, 409–410 trafficking assay limitations, 398 Transendothelial migration, see Lymphocyte transendothelial migration Two-photon microscopy autofluorescence and second harmonic generation signals, 360 explant imaging, 360–363 fluorescent dyes, 358–359 fluorescent proteins, 359–360 image acquisition cell density, 367 laser power and photomultiplier tube gain, 366–367 Z-series acquisition and time resolution, 367–368 image analysis arrest coefficient, 372 cell detection, 368–369 cell migration, 370 cell tracking, 369 cell velocity, 371 cluster and neighbor analysis, 370 displacement plot, 371 meandering index, 373 morphology studies, 369–370 motility coefficient, 371–372 transit rate, 372 turning angle, 372–373 intravital imaging, 363–364

439

Subject Index

laser attenuation and fast shuttering, 356–357 overview, 350–351 peripheral tissue imaging, 364–365 presentation of images cell tracks, 374 three-dimensional rotations and time-lapse movies, 375 two-dimensional images, 373–374 pulse compression, 357–358 sample power control, 357 scan heads and lasers, 352–354 signal detection and optical filters, 355–356 software for image acquisition, 355 Tyrosine sulfation bacterial expression system advantages and applications, 162 general considerations, 166 overview, 161–162 chemokine receptor studies in membranes candidate sulfotyrosine mutagenesis, 161–162 sulfation modulation, 180 complement receptors, 150 discovery, 148–149 Duffy antigen receptor for chemokines, 153 human immunodeficiency virus coreceptors antibody tyrosine sulfation, 153–154 overview, 149–150 peptide studies applications of peptides, 159–160 cell-free sulfation, 158, 165–166 modulation of sulfation, 158–159 production in mammalian cells, 156, 158 synthetic peptides, 155–156 sites, 151–152 virulence significance, 154–155 metabolic radiolabeling reagents and media, 163–164

sulfotyrosine peptide-Fc fusion proteins, 164–165 tyrosyl-protein sulfotransferases identification, 149 RNA interference, 165 W Western blot, chemokine receptor dimerization characterization, 108–109 X XCL1, see Lymphotactin Z ZIP, see Zymosan-induced peritonitis Zymosan-induced peritonitis acute versus chronic inflammation, 380–381 advantages, 382 anti-inflammatory agent pretreatment, 385 applications, 392–384 calculations, 387–388 cell counting and fluorescence-activated cell sorting, 386–387 exclusion criteria, 388 induction of inflammation, 385 inflammatory mediator analysis, 390, 392 lavage, 385–386 leukocyte recruitment analysis, 388–391 materials, 384–385 morphology analysis, 387 peritoneal models of acute inflammation, 381–382 receptor antibody selection for cell staining, 393–394 zymosan dosing, 392–393