BSL3 and BSL4 Agents: Proteomics, Glycomics, and Antigenicity

Edited by Jiri Stulik, Rudolf Toman, Patrick Butaye, and Robert G. Ulrich BSL3 and BSL4 Agents

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Edited by Jiri Stulik, Rudolf Toman, Patrick Butaye, and Robert G. Ulrich

BSL3 and BSL4 Agents Proteomics, Glycomics, and Antigenicity

The Editors Prof. Jiri Stulik Ministry of Defence Faculty of Military Health Service Trebesska 1575 500 01 Hradec Králové Czech Republic Prof. Rudolf Toman Slovak Academy of Sciences Institute of Virology Dubravska cesta 9 845 05 Bratislava 45 Slovak Republic Prof. Patrick Butaye Veterimary and Agrochemical Research Centre Department of Bacteriology and Immunology Groeselenberg 99 1180 Bruxelles Belgium Dr. Robert G. Ulrich Army Medical Research Inst. of Infectious Diseases 1425 Porter Street Frederick, MD 21702 USA Cover Section of a lung from a cynomolgus macaque exposed to aerosolized Yersinia pestis. The bacteria (red) are apparent throughout the lung, which is stained for fibrin (green). Cell nuclei are shown in blue. Courtesy of Derron Alves (staining by Christine Mech, microscopy by Gordon Ruthel).

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V

Contents Preface XIII List of Contributors XV 1

1.1 1.2 1.3 1.4 1.5

Introduction: Application of Proteomic Technologies for the Analysis of Microbial Infections 1 Jiri Stulik and Patrick Butaye Introduction 1 Search for New Factors of Virulence and Potential Diagnostic Markers 2 Search for New Vaccine Candidates 3 Analysis of Post-Translational Modifications of Bacterial Proteins and Protein–Protein Interactions 3 Conclusions 5 References 5

Part One 2 2.1 2.1.1 2.1.1.1 2.1.1.2 2.1.1.3 2.1.1.4 2.1.2 2.1.3 2.1.3.1 2.1.3.2 2.1.3.3 2.1.3.4 2.1.3.5

Basic Proteomic Methods 7

Separation of Proteins and Peptides 9 Ludovit Skultety Introduction 9 Gel-Based Separation 11 One-Dimensional Electrophoresis 11 Two-Dimensional Electrophoresis 11 Protein Staining and Image Analysis 13 2-DE Limitations 16 In Solution – “Gel Free” Proteomics 16 Column Chromatography 17 Size Exclusion Chromatography 18 Reversed-Phase Liquid Chromatography 18 Hydrophilic Interaction Liquid Chromatography Ion Exchanger Chromatography 20 Affinity Chromatography 21

20

VI

Contents

2.1.3.6 2.1.4 2.1.5

Multidimensional Chromatography 21 Liquid Phase IEF and Electrophoresis 23 Alternative Separation Technologies 23 Acknowledgment 24 References 24

3

Basic Mass Spectrometric Approaches 29 Lenka Hernychova and Martin Hubalek Introduction 29 Ionization 30 Matrix-Assisted Laser Desorption/Ionization 30 Electrospray Ionization 31 Mass Analyzers 32 Time of Flight 33 Reflectron TOF 34 Quadrupole and Ion Trap 35 Fourier Transformation Ion Cyclotron 35 Tandem Mass Analyzers 35 Ion Detection 36 Protein Identification 37 Combination of 2-DE and MS 37 Peptide Mass Fingerprinting 37 Peptide Sequencing (PMF) 38 Shotgun Proteomics 39 Conclusion 39 Acknowledgments 40 References 40

3.1 3.2 3.2.1 3.2.2 3.3 3.3.1 3.3.2 3.3.3 3.3.4 3.3.5 3.3.6 3.4 3.4.1 3.4.2 3.4.3 3.4.4 3.5

4 4.1 4.1.1 4.1.2 4.1.3 4.1.3.1 4.1.3.2 4.1.3.3 4.2 4.2.1 4.2.2 4.2.3 4.2.4 4.2.5

Quantitative Mass Spectrometric Approaches 43 Juraj Lenco and Vojteˇch Tambor Introduction 43 Gel-Based Quantitative Proteomic Methods 43 Shotgun Quantitative Proteomic Methods 44 Labeling Methods 44 Metabolic Incorporation of Stable Isotopes 45 Enzymatic Incorporation of Stable Isotopes 46 Chemical Incorporation of Stable Isotopes 46 iTRAQ Analysis of Bacterial Pathogens 47 Bacterial Cell Disruption and Protein Extraction 48 Determination of Protein Concentration 50 Protein Digestion 50 Peptide Labeling with iTRAQ Tags 51 Protocol for iTRAQ Analysis of Bacterial Proteins 51 References 52

Contents

5 5.1 5.2 5.3 5.3.1 5.3.1.1 5.3.1.2 5.3.1.3 5.3.2 5.3.3 5.4 5.4.1 5.4.1.1 5.4.1.2 5.4.1.3 5.4.2 5.4.3 5.4.4 5.5 5.6

6 6.1 6.2 6.2.1 6.2.1.1 6.2.1.2 6.3 6.4 6.4.1 6.4.1.1 6.4.1.2 6.4.2 6.4.2.1 6.4.2.2 6.4.2.3 6.4.2.4 6.5

BN-PAGE of Microbial Protein Complexes 55 Jiri Dresler and Jana Klimentova Introduction 55 Methods for Studying Protein–Protein Interactions 55 Blue Native Polyacrylamide Gel Electophoresis 56 Sample Preparation 57 Non-Denaturing Conditions 57 Selection of Detergent and Its Optimal Concentration 58 Membrane and Cytosolic Fraction Separation 58 1D BN-PAGE 59 2D BN/SDS-PAGE 59 Evaluation of BN-PAGE – Staining, MS, Western Blotting 60 Staining 60 Silver Staining 60 Fluorescent Staining 60 Coomassie Staining 60 Mass Spectrometry 61 Western Blotting 61 Other Methods of Visualization 61 BN/SDS-PAGE of ATP Synthase of Francisella tularensis 62 Conclusion 63 Acknowledgment 63 References 64 Analysis of Francisella tularensis Glycoproteins 67 Lucie Balonova and Lenka Hernychova Introduction to Post-Translational Modifications in Prokaryotes 67 Methodology 68 Analysis of Glycosylation 68 Glycoproteomics 68 Glycomics 69 Bioinformatics 70 Application of Glycoproteomic Approach Utilizing ProQ-Emerald and DIG Glycan Kits to Francisella tularensis (F. tularensis) 70 Bacterial Cultures and Sample Preparation 71 Preparation of Whole-Cell Lysates 71 Preparation of Membrane-Enriched Fractions 71 Analysis of Glycoproteins in Fractions Enriched in Membrane Proteins 71 Mini Two-Dimensional Gel Electrophoresis 71 Glycoprotein Detection Using DIG Glycan Differentiation Kit 72 Glycoprotein Detection Using Pro-Q Emerald 300 Glycoprotein Stain Kit 72 Glycoprotein Identification by Mass Spectrometry 72 Results 73

VII

VIII

Contents

6.5.1 6.5.2 6.6

Glycoprotein Detection Using DIG Glycan Differentiation Kit 73 Glycoprotein Detection Using Pro-Q Emerald 300 Glycoprotein Stain Kit 73 Conclusion 74 Acknowledgments 76 References 76

Part Two Identification of Proteins and Glycans from Microorganisms as Candidate Molecules for Use in Detection/Diagnosis, Therapy, and Prophylaxis 79 7

7.1 7.2 7.3 7.3.1 7.3.2 7.4

8 8.1 8.2 8.2.1 8.2.2 8.2.3 8.2.4 8.2.5 8.2.6 8.3 8.3.1 8.3.2 8.4

9 9.1 9.2 9.3 9.4

Comparative Proteome Analysis of Strains with Differential Virulence 81 Martin Hubalek and Ivona Pávková Introduction 81 Methods 82 Results 84 Whole-Cell Lysates 84 Membrane-Associated Proteins 86 Discussion 86 References 91 Analysis of Francisella tularensis Acetonitrile Extracts 95 Lenka Hernychova, Martin Hubalek, and Jana Udrzalova Introduction 95 Material and Methods 96 Materials 96 Microorganism 96 Preparation of Cell-Free Acetonitrile Extract 96 Enzymatic Digestion 97 MALDI-TOF MS 97 LC-MS/MS 98 Results 98 MALDI-TOF MS Analysis 98 LC-MS/MS Analysis 99 Conclusions 102 Acknowledgments 103 References 103 Analysis of Culture Filtrate Proteins of Francisella tularensis Klara Konecna, Martin Hubalek, and Lenka Hernychova Introduction 107 Materials and Methods 108 Results 109 Discussion 112

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Contents

Acknowledgments 113 References 113 10

10.1 10.2 10.2.1 10.2.2 10.2.3 10.3

11

11.1 11.2 11.2.1 11.2.2 11.2.3 11.3 11.3.1 11.3.2 11.3.3

12

12.1 12.2 12.2.1 12.2.2 12.2.3 12.2.4 12.3 12.3.1 12.3.2

Lipopolysaccharides of Coxiella burnetii: Chemical Composition and Structure, and Their Role in Diagnosis of Q Fever 115 Rudolf Toman and Pavol Vadovicˇ Introduction 115 Lipopolysaccharides of C. burnetii 116 Chemical Composition and Structure of LPS I 118 Chemical Composition and Structure of LPS II 120 The Role of LPS I in Diagnosis of Q Fever 120 Conclusion 121 Acknowledgments 121 References 121 Mimivirus Possesses Anonymous and Unique Gene Products Endowed for Antigenic Properties 125 Patricia Renesto and Didier Raoult Introduction 125 Material and Methods 126 Sample Preparation 126 2D-PAGE and Matrix-Assisted Laser Desorption/Ionization Time of Flight Mass Spectrometry 126 Immunization and Western Blot 126 Results 127 Proteomic Analysis of Mimivirus Particle 127 Antigenic Properties of ORFan-Encoded Mimivirus Proteins 128 Concluding Remarks 128 References 128 Detection of Differentially Modified Pathogen Proteins by Western Blot after 2D Gel Electrophoresis and Identification by MALDI-TOF/TOF 131 Fred Fack, Julia Kessler, Patrick Pirrotte, Jacques Kremer, Dominique Revets, Wim Ammerlaan, and Claude P. Muller Introduction 131 Materials and Methods 132 Protein Sample Preparation and Fluorescence Labeling for DIGE Analysis 132 2D Electrophoresis and Gel Imaging 133 2D Western Blotting 133 Protein Identification by MALDI-TOF/TOF Analysis of In-Gel Tryptic Digests 134 Results 134 2D-DIGE Analysis of Measles Virus Infected THP1 Cells 134 Detection of Different Protein Forms by 2D Western Blot 135

IX

X

Contents

12.3.3 12.4

13

13.1 13.2 13.3 13.4

14 14.1 14.2 14.3

15

15.1 15.2 15.3 15.4 15.5 15.6 15.7 15.8 15.9

16 16.1 16.2 16.3

Monitoring Viral Replication and Cellular Response by Antibody Multiplexing 136 Discussion 137 References 138 Composition and Structure of Lipid A of the Intracellular Bacteria Piscirickettsia salmonis and Coxiella burnetii 139 Pavol Vadovicˇ, Robert Ihnatko, and Rudolf Toman Introduction 139 Composition and Structure of Lipid A of P. salmonis 140 Composition and Structure of Lipid A of C. burnetii 141 Conclusion 143 Acknowledgments 144 References 144 Proteins of Coxiella burnetii and Analysis of Their Function 145 Robert Ihnatko, Pavol Vadovicˇ, and Rudolf Toman Introduction 145 Proteins of C. burnetii and Their Functions 146 Conclusion and Perspectives 149 Note Added in Proof 149 Acknowledgments 150 References 150 Subtype and Toxin Variant Identification of Botulinum Neurotoxin Type A Using Proteomics Techniques 153 Suzanne R. Kalb, Jakub Baudys, Theresa J. Smith, James L. Pirkle, and John R. Barr Introduction 153 Botulinum Neurotoxins 153 Differentiation of Botulinum Neurotoxins 154 Amino Acid Sequence Identification Using Proteomics 155 Extraction of BoNT from Complex Matrices 157 Identification of BoNT Serotype with Proteomics 157 Identification of BoNT/A Subtype with Proteomics 159 Identification of BoNT/A1 Strain with Proteomics 161 Conclusions 163 Disclaimer 164 References 164 Protein Microarrays for Antigen Discovery 167 Mohan Natesan, Sarah Keasey, and Robert G. Ulrich Introduction 167 Microarray Assembly 168 Antibody Assays 170

Contents

16.4 16.5 16.6

Antigens and Proteomes of Viruses 171 Antigens and Proteomes of Pathogenic Bacteria Conclusions 176 Acknowledgment 177 References 177

17

MALDI-TOF Mass Spectrometry for Rapid Identification of Highly Pathogenic Microorganisms 179 Peter Lasch and Dieter Naumann Introduction 179 Microbial Identification by MALDI-TOF Mass Spectrometry 180 Basic Principles of MALDI-TOF Mass Spectrometry 180 Preparation of Microbial Samples for MALDI-TOF MS 181 Spectral Data Analysis: Preprocessing, Calibration, Peak Detection, and Data Visualization 182 Multivariate Classification Analysis – Pattern Recognition Methods 184 Identification of Taxon-Specific Biomarkers 186 Inactivation of Highly Pathogenic Microorganisms for MALDI-TOF Mass Spectrometry 187 Time and Concentration Dependence of TFA Inactivation 188 Centrifugation – Reduction of the Supernatant’s Cell Concentration 189 Sterile Filtration 189 Molecular and Structural Aspects of Spore Treatment by TFA 190 Identification of Important Bacterial Pathogenes Using MALDI-TOF MS 192 Bacillus anthracis 192 Burkholderia mallei/pseudomallei 196 Yersinia pestis 199 Concluding Remarks 207 Acknowledgments 208 References 208

17.1 17.2 17.2.1 17.2.2 17.2.3 17.2.4 17.2.5 17.3 17.3.1 17.3.2 17.3.3 17.3.4 17.4 17.4.1 17.4.2 17.4.3 17.5

Part Three 18

18.1 18.2 18.2.1 18.2.2 18.2.3

174

Analysis of Host–Pathogen Interactions 213

Quantitative Proteomic Profiling of the Interaction of Francisella tularensis LVS with Macrophages Using J774.2 Cell Line 215 Anetta Hartlova, Marek Link, Juraj Lenco, and Jiri Stulik Introduction 215 Material and Methods 216 Bacterial Strain, Cell Line, and Growth Conditions 216 Infection Assay 216 Preparation of Lysate and Isolation of Detergent-Insoluble Membrane Fractions 216

XI

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Contents

18.2.4 18.2.5 18.2.6 18.2.7 18.3 18.3.1 18.3.2 18.3.3

TRYPTIC Digestion and iTRAQ Labeling 217 Mass Spectrometric Analysis 218 Protein Identification and Database Search 218 Classification of iTRAQ Identified Proteins 218 Results 218 Characterization of DRM Isolation 218 Classification of 57 Identified Proteins of Both iTRAQ Labeling Significant Differentially Regulated Proteins 219 References 221

19

Proteome Analysis of Bacterial Protein Expression after Ingestion of Microbes by Macrophages 223 Martin Brychta and Ivona Pávková Introduction 223 Material and Methods 224 Bacterial Strains, Cell Lines, and Cultivation 224 Intracellular Growth of Francisella tularensis in Macrophages and Radiolabeling of Bacterial Proteins 224 Two-Dimensional Gel Electrophoresis (2-DE) and Autoradiography 225 Image Acquisition and Software Analysis 225 Protein Identification 225 Results 226 Discussion 228 Acknowledgment 230 References 230

19.1 19.2 19.2.1 19.2.2 19.2.3 19.2.4 19.2.5 19.3 19.4

Index

233

219

XIII

Preface The research initiatives and interests of COST B28 partners are organized in five working packages/groups (WGs):

• • • • •

WG1: Technology platform (including flow cytometry and microarrays) WG2: Antigenicity WG3: Proteomics and glycomics WG4: Genomics WG5: Microbiology (bacteriology, virology, mycology)

Research groups involved in WG2 and WG3 possess an extensive fundamental knowledge and expertise in the fields of proteomics, glycomics, and antigenicity of both bacteria and viruses. A mutual collaboration in these fields is of importance since the interconnection between the three research disciplines is obvious. The aim of this booklet is to summarize the present knowledge on proteomics, glycomics, and the structure/function of antigens in general, and to provide insights into the latest developments and applications of these scientific fields with regard to BSL3 and BSL4 agents. Contributions to the booklet illustrate a considerable broadness and variability of these applications on the agents investigated within the framework of this COST B28 action. The first part of this booklet deals with the general applications of proteomic and glycomic techniques in the analysis of microbial infections. These are then elaborated further, and for some techniques basic protocols are given. Many of them have also been demonstrated in a training school held within this COST Action B28 action organized by the main partners in these two working groups. The second part focuses on applications of these techniques in the identification and characterization of proteins and glycans from microorganisms and on the rapid and accurate detection and identification of them. Moreover, the diagnosis, therapy, and prophylaxis of the diseases caused by these microorganisms are discussed. This concerns mainly Francisella tularensis, the obligate intracellular gram-negative bacteria Coxiella burnetii and Piscirickettsia salmonis, mimivirus, and measels virus. Although the number of examples is limited, they still give a good insight into the respective fields. The third part is devoted to host–pathogen interactions, dealing with both prokaryote and eukaryote expressions of proteins.

XIV

Preface

This booklet has no ambitions to be a complete and final “manual” as it deals with an area in which new findings, techniques, and methodologies are being brought on nearly on a daily basis, thus making it almost impossible to give a real up to date overview. Nevertheless, it gives the reader an interesting insight into these new and rapidly developing fields. The information presented here may be helpful to students and researchers interested in proteomics, glycomics, and the structure/function of antigens and their further, so far unknown research fields and applications. For additional reading, we recommend references provided by the authors. More information on WG2 and WG3, and also on other WGs, can be found on the COST Action B28 website: http://www.cost-b28.be/. June 2011

Jiri Stulik Rudolf Toman Patrick Butaye Robert G. Ulrich

XV

List of Contributors Wim Ammerlaan Institute of Immunology Centre de Recherche Public de la Santé/National Public Health Institute 20A, rue Auguste Lumière 1950 Luxembourg Luxembourg Lucie Balonova Institute of Molecular Pathology Faculty of Military Health Science University of Defence Trebesska 1575 500 01 Hradec Králové Czech Republic John R. Barr Centers for Disease Control and Prevention National Center for Environmental Health Division of Laboratory Sciences 4770 Buford Hwy, N.E. Atlanta, GA 30341 USA

Jakub Baudys Centers for Disease Control and Prevention National Center for Environmental Health Division of Laboratory Sciences 4770 Buford Hwy, N.E. Atlanta, GA 30341 USA Martin Brychta Institute of Molecular Pathology Faculty of Military Health Sciences University of Defence Trebesska 1575 500 01 Hradec Králové Czech Republic and Charles University in Prague Faculty of Medicine in Hradec Králové Department of Medical Biology and Genetics 500 01 Hradec Králové Czech Republic

XVI

List of Contributors

Patrick Butaye Department of Bacteriology and Immunology Veterinary and Agrochemical Research Centre VAR-CODA-CERVA Groeselenberg 99 1180 Brussels Belgium and Ghent University Faculty of Veterinary Medicine Department of Pathology, Bacteriology and Poultry Diseases Salisburylaan 133 9820 Merelbeke Belgium Jiri Dresler Institute of Molecular Pathology University of Defence Faculty of Military Health Sciences Trebesska 1575 500 01 Hradec Králové Czech Republic Fred Fack Institute of Immunology Centre de Recherche Public de la Santé/National Public Health Institute 20A, rue Auguste Lumière 1950 Luxembourg Luxembourg Anetta Hartlova Centre of Advanced Studies Faculty of Military Health Sciences Trebesska 1575 500 01 Hradec Králové Czech Republic

Lenka Hernychova Institute of Molecular Pathology Faculty of Military Health Science University of Defence Trebesska 1575 500 01 Hradec Králové Czech Republic Martin Hubalek Institute of Molecular Pathology Faculty of Military Health Sciences University of Defence Trebesska 1575 500 01 Hradec Králové Czech Republic Robert Ihnatko Institute of Virology Slovak Academy of Sciences Laboratory for Diagnosis and Prevention of Rickettsial and Chlamydial Infections Dubravska cesta 9 845 05 Bratislava 45 Slovak Republic Suzanne R. Kalb Centers for Disease Control and Prevention National Center for Environmental Health Division of Laboratory Sciences 4770 Buford Hwy, N.E. Atlanta, GA 30341 USA Sarah Keasey United States Army Medical Research Institute of Infectious Diseases Department of Immunology 1425 Porter Street Frederick, MD 21702 USA

List of Contributors

Julia Kessler Institute of Immunology Centre de Recherche Public de la Santé/National Public Health Institute 20A, rue Auguste Lumière 1950 Luxembourg Luxembourg Jana Klimentova Institute of Molecular Pathology Faculty of Military Health Sciences University of Defence Trebesska 1575 500 01 Hradec Králové Czech Republic Klara Konecna Institute of Molecular Pathology Faculty of Military Health Sciences University of Defence Heyrovskeho 1203 500 05 Hradec Králové Czech Republic and Charles University in Prague Pharmaceutical Faculty in Hradec Kralove 500 05 Hradec Králové Czech Republic Jacques Kremer Institute of Immunology Centre de Recherche Public de la Santé/National Public Health Institute 20A, rue Auguste Lumière 1950 Luxembourg Luxembourg Peter Lasch Robert Koch-Institut Biomedical Spectroscopy (P25) Nordufer 20 13353 Berlin Germany

Juraj Lenco Centre of Advanced Studies Faculty of Military Health Sciences Trebesska 1575 500 01 Hradec Králové Czech Republic and Institute of Molecular Pathology FMHS UO Trebesska 1575 500 01 Hradec Králové Czech Republic Marek Link Centre of Advanced Studies Faculty of Military Health Sciences Trebesska 1575 500 01 Hradec Králové Czech Republic Claude P. Muller Institute of Immunology Centre de Recherche Public de la Santé/National Public Health Institute 20A, rue Auguste Lumière 1950 Luxembourg Luxembourg Mohan Natesan United States Army Medical Research Institute of Infectious Diseases Department of Immunology 1425 Porter Street Frederick, MD 21702 USA Dieter Naumann Robert Koch-Institut Biomedical Spectroscopy (P25) Nordufer 20 13353 Berlin Germany

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List of Contributors

Ivona Pávková Institute of Molecular Pathology Faculty of Military Health Sciences University of Defence Trebesska 1575 500 01 Hradec Králové Czech Republic

Dominique Revets Institute of Immunology Centre de Recherche Public de la Santé/National Public Health Institute 20A, rue Auguste Lumière 1950 Luxembourg Luxembourg

James L. Pirkle Centers for Disease Control and Prevention National Center for Environmental Health Division of Laboratory Sciences 4770 Buford Hwy, N.E. Atlanta, GA 30341 USA

Ludovit Skultety Institute of Virology Slovak Academy of Sciences Dubravska cesta 9 845 05 Bratislava Slovak Republic and Center for Molecular Medicine Vlarska 3-7 831 01 Bratislava Slovak Republic

Patrick Pirrotte Institute of Immunology Centre de Recherche Public de la Santé/National Public Health Institute 20A, rue Auguste Lumière 1950 Luxembourg Luxembourg Didier Raoult Unité des Rickettsies IRD-CNRS UMR 6236 Faculté de Médecine 27 Bd Jean Moulin 13385 Marseille France Patricia Renesto Unit of Virus Host Cell Interactions UMI 3265 Université Joseph Fourier-EMBL-CNRS 6, rue Jules Horowitz 38042 Grenoble France

Theresa J. Smith United States Army Medical Research Institute of Infectious Diseases Integrated Toxicology Ft. Detrick, MD 21702 USA Jiri Stulik Institute of Molecular Pathology FMHS UO Trebesska 1575 500 01 Hradec Králové Czech Republic and Centre of Advanced Studies Faculty of Military Health Sciences Trebesska 1575 500 01 Hradec Králové Czech Republic

List of Contributors

Vojteˇch Tambor Institute of Molecular Pathology FMHS UO Trebesska 1575 500 01 Hradec Králové Czech Republic Rudolf Toman Slovak Academy of Sciences Institute of Virology Laboratory for Diagnosis and Prevention of Rickettsial and Chlamydial Infections Dubravska cesta 9 845 05 Bratislava 45 Slovak Republic Jana Udrzalova Institute of Molecular Pathology Faculty of Military Health Sciences University of Defence Trebesska 1575 500 01 Hradec Králové Czech Republic

Robert G. Ulrich United States Army Medical Research Institute of Infectious Diseases Department of Immunology 1425 Porter Street Frederick, MD 21702 USA Pavol Vadovicˇ Institute of Virology Slovak Academy of Sciences Laboratory for Diagnosis and Prevention of Rickettsial and Chlamydial Infections Dubravska cesta 9 845 05 Bratislava 45 Slovak Republic

XIX

1

1 Introduction: Application of Proteomic Technologies for the Analysis of Microbial Infections Jiri Stulik and Patrick Butaye

1.1 Introduction

Proteomics belongs to the group of so-called “omics” technologies that are preferentially exploited for the global analysis of temporal or conditional alterations in gene expression, on either the gene or protein level. Proteomics is focused on proteins and provides information about their abundances, post-translational modifications, localization and mutual interactions. Current proteomic procedures combine efficient electrophoretic or chromatographic separation techniques with identification approaches based on mass spectrometry (MS) and computer technologies for bioinformatic analysis. It can be said that MS is now the major driving force in the field of proteomics and the quantitative shotgun tandem MS represents a large-scale high-throughput technology commonly employed for comparative identification and quantification protein studies [1]. The major benefit of the “omics” approaches is the ability to analyze a large number of genes or proteins simultaneously, enabling a more realistic view of a complex cell response to stimuli. The analysis of the global changes in protein profiling during the interactions between microbial pathogens and their hosts, so-called “infectomics”, is very attractive area within proteomics. It feeds the study of the fundaments of infections. It solves molecular mechanisms of microbial pathogenesis, helps in the efficient and rapid diagnosis of infectious disease and the development of novel prophylaxis and treatment strategies. Here, infectomics involves the study of proteins uniquely expressed or up-regulated in virulent clinical strains, proteins produced under stress conditions and, finally, proteins with immunostimulatory properties. Going deeper into infectomics one deals with structural studies of microbial proteins (to characterize potential post-translational modifications) and the analysis of protein–protein interactions, the so-called “interactome” [2]. In this publication we first give an overview on basic proteomic techniques. This introduces the reader into the more specialized studies performed on BSL3 and

BSL3 and BSL4 Agents: Proteomics, Glycomics, and Antigenicity, First Edition. Edited by Jiri Stulik, Rudolf Toman, Patrick Butaye, Robert G. Ulrich. © 2011 Wiley-VCH Verlag GmbH & Co. KGaA. Published 2011 by Wiley-VCH Verlag GmbH & Co. KGaA.

2

1 Introduction: Application of Proteomic Technologies for the Analysis of Microbial Infections

BSL 4 agents. These organisms are difficult to handle and specialized laboratories are necessary to work with them. However, the safe preparation of materials for protein researchers can allow substantial progress in the understanding of these microorganisms.

1.2 Search for New Factors of Virulence and Potential Diagnostic Markers

Matching the protein patterns extracted from nonvirulent attenuated strains with their fully virulent counterparts is a common procedure to detect potential virulence factors and/or new diagnostic markers. This has been demonstrated in the comparative proteome study of exoproteins released by different enterotoxigenic Staphylococcus aureus strains. Using a gel-based approach different known enterotoxins and other possible virulence factors were revealed by comparing the protein profiles of two isolates, a food-derived strain with a prevalent enterotoxin gene cluster and a nonenterotoxigenic reference strain [3]. Another example of the gel-based approach is the protein profiling of two cystic fibrosis isolates of Pseudomonas aeruginosa strains associated with the initial and chronic infection process. These two genetically identical strains secrete several proteins uniquely expressed in the different stages of the disease [4]. Gel-based approaches utilizing preferentially two-dimensional gel electrophoresis (2-DE) for the study of enriched membrane proteins are typically exploited for the host–pathogen interactions. However, this method suffers from the loss of most of the hydrophobic membrane proteins due to their inefficient solubilization during isoelectric focusing, and therefore, the nonelectrophoretic approaches gradually replace gel-based techniques for such studies. An example of this is the study of the cell wall proteome of Listeria monocytogenes and Listeria innocua [5]. Here 30 proteins residing in the membrane were identified in both strains. Outer membrane vesicles (OMV) that are assumed to play an important role in cell to cell communication, for example, toxins or in the transfer of proteins and genetic materials between microbes represent potential virulence factors and proteins with immunostimulatory properties. The purification of sufficient OMV is, however, a serious problem [6]. Intracellular infectious microbes have to cope with the hostile intracellular milieu. Basically, their success for survival and multiplication depends on the coordinated reprogramming of their gene expression under the influence of stimuli, such as acid pH, iron depletion, oxidative stress, nitrogen radicals and heat. In-depth proteome analysis of the changing microbial protein profiles is very challenging since it informs us about protein-virulence factors that may serve as new targets for treatment. Unfortunately, progress in this area is still hampered by the inability of proper protein extraction methods. They lack efficacy through low gain and are too much contaminated with eukaryotic material. One way to avoid this could be the direct purification of bacteria-containing vacuoles and to identify the proteins uniquely expressed within this compartment [7].

1.4 Post-Translational Modifications of Bacterial Proteins and Protein–Protein Interactions

1.3 Search for New Vaccine Candidates

The application of proteomics for a search for vaccine candidates has been driven by the current need for a new type of safe and efficient subunit vaccines. The classical approach, called serological proteome (SERPA), is used for the identification of perspective proteins. This technology is based on the separation of complex protein mixtures by gel-based technology, mostly by 2-DE, followed by blotting of separated proteins to a membrane where the transferred proteins are probed by human or animal immune sera. The detected spots are then identified by MS after their excision from the matched preparative 2-DE gel. This approach is still routinely used but, instead of separating the whole-cell lysates, just the membrane proteins, secreted proteins or proteins located in outer membrane vesicles are being examined [8–10]. As already mentioned, 2-DE separation has strong limitations, and therefore, new nongel-based approaches are being examined. Protein microarray chips probed with sera from infected individuals overcome this problem, allowing protein solubilization and enabling the analysis of the whole proteome in an unbiased manner. This procedure was examined in the screening process for the identification of Francisella tularensis immunoreactive proteins. Probing a chip containing 1741 F. tularensis antigens with the sera from 46 patients diagnosed as tularemia patients led to the detection of 244 antigens exhibiting a high intensity signal [11]. Bioinformatics is an invaluable tool for the discovery of vaccine candidates because the human brain can hardly contain all information generated by the current high-throughput techniques. They allow us to focus on a significantly restricted number of proteins and to select those proteins that are likely to induce a good immune response. McMurry et al. [12] used a combination of different softwares for the detection of possible Mycobacterium tuberculosis immunodominant epitopes. First at the DNA level, open reading frames containing signal sequences featuring secreted proteins were detected, and then, the selected proteins were screened for matches to a list of MHC II binding motifs. Based on this selection, 17 peptides were synthesized and their immunostimulatory potential was verified by in vitro T-cell assays. Overall 15 epitopes gave acceptable results and are now candidates for the construction of new TB vaccine.

1.4 Analysis of Post-Translational Modifications of Bacterial Proteins and Protein– Protein Interactions

Post-translational modification adds an additional level of complexity to the current “omics” technologies. It is estimated that more than 100 different post-translational modifications exist in eukaryotic cells and the most widely distributed ones are glycosylation and phosphorylation. Highly sophisticated proteomic approaches are being developed to detect and quantify these modifications, but these procedures

3

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1 Introduction: Application of Proteomic Technologies for the Analysis of Microbial Infections

are still far from being a routine technology. Surprisingly, the recent data document that both types of modifications occur also in prokaryotes and their biological significance is starting to be unveiled. Regarding prokaryotes, both N- and O-glycosylations were detected and orthologs of the genes encoding members of both glycosylation pathways in eukaryotes were found in mucosal pathogens [13]. Glycosylation concerns mainly membrane and secreted bacterial proteins and most of them are known virulence factors. Hence, this modification might serve a specific function in the molecular mechanism of pathogenesis. This assumption was, for example, confirmed for the Toxoplasma gondii N-glycoproteins that are involved in several biological functions associated with the parasite’s intracellular development. Exposing cells to tunicamycin (which disrupts the glycosylation of newly synthesized proteins) then abrogated host cell invasion and parasite growth [14]. Unfortunately, the identification of glycoproteins is a highly intricate matter and encompasses laborious methods aimed at the detection of glycan modification(s). This and the methods of glycosidic linkage determination and identification of carbohydrate residues are still in their infancy in this area. The glycosylation of bacterial proteins and the reversible phosphorylation of serine, threonine and tyrosine residues were thought to be restricted to eukaryotic cells. However, in the last decade several prokaryotic tyrosine and serine/threonine kinases together with phosphatases have been described [15]. In contrast to eukaryotic kinases, the majority of these prokaryotic enzymes appear to be transmembrane proteins, and thus, it is anticipated that these kinases may function as prokaryotic receptors. Nevertheless, the ligands for these receptors and signaling pathways triggered by receptor occupation have to be unraveled. The extensive systematic prokaryotic phosphoproteome analyses require a good experience and skill in both phosphoprotein enrichment and in the following MS and bioinformatic analyses. Up to now, two indepth phosphorylation studies of a gram-positive bacterium Bacillus subtilis and a gram-negative bacterium Escherichia coli have been performed [16, 17]. They proved that a significantly lower number of prokaryotic proteins was phosphorylated in comparison to the mammalian or yeast proteins. Furthermore, phosphorylation on the serine and threonine residues prevailed and proteins were frequently multiphosphorylated but again their number was low in comparison to that found in eukaryotes. The kind of virulence factors either localized in the outer membrane or actively secreted is prone to direct interplay with the host cell biological system. A physical contact between microbes and target cells leads to significant alteration of the host cell proteomes on various levels, resulting in the modulation of cell signaling pathways, membrane ruffling, cytoskeleton rearrangement, endosomal traffficking, host cell protein modification and the induction of cell death programs. The combination of various fractionation procedures and gel- or nongel-based proteomic approaches enables us to study the changes in host proteomes on the level of individual subcellular compartments directly targeted by the microbe. Another approach is focused on the identification of interaction of the host and microbial virulence factors. However, despite the application of multiple tag and

References

pull-down procedures for the isolation of protein complexes, relatively few host proteins have been identified as the targets of microbial proteins until now. There is also a problem to distinguish nonspecific from specific binding partners of the isolated protein complexes. In this case, it appears that the recent developments in quantitative proteomics could help to solve this problem. One particular quantitative technique exploits metabolically incorporated isotopic labels into proteins. Using this approach, two cell cultures are differentially labeled. Then affinity purification isolates the bait from one population and a control from the other population. When the isolated complexes are analyzed, a mixed nonspecific interaction is characterized by an equal binding of the background proteins to the bait, while specific interactions with the bait result in differential ratios. This protocol was successfully used for the identification of the small G-protein Cdc42 as the host target of the SPI-1 effector, SopB/SigD in Salmonella [18].

1.5 Conclusions

The enormous progress in the proteomic methodologies will allow us to gradually describe the entire proteomes of pathogens. Likewise, it can be expected that new virulence factors will be identified and their biological role in the pathogenesis of diseases will be uncovered. These findings together with improvements in bioinformatics should then substantially speed up the design of new therapeutic and prophylactic agents. This COST Action B28 gathers excellence in these fields. In line with a microarray platform, a combination of genomics, proteomics, glycomics and antigenicity substantiated by a bioinformatics knowledge will allow us to make noticeable progress towards a better understanding of the agents under investigation and the diseases they cause. Of course, the input of bacteriologists and virologists dealing with these infections in the field and their efforts to understand their importance for humans, animals and environment cannot be omitted.

References 1 Chen, G., and Pramanik, B.N. (2008)

LC-MS for protein characterization: current capabilities and future trends. Expert Rev. Proteomics, 5, 435–444. 2 Charbonnier, S., Gallego, O., and Gavin, A.C. (2008) The social network of a cell: recent advances in interactome mapping. Biotechnol. Annu. Rev., 14, 1–28. 3 Pocsfalvi, G., Cacace, G., Cuccurullo, M., Serluca, G., Sorrentino, A., Schlosser, G., Blaiotta, G., and Malorni, A. (2008)

Proteomic analysis of exoproteins expressed by enterotoxigenic Staphylococcus aureus strains. Proteomics, 8, 2462–2476. 4 Hanna, S.L., Sherman, N.E., Kinter, M.T., and Goldberg, J.B. (2000) Comparison of proteins expressed by Pseudomonas aeruginosa strains representing initial and chronic isolates from a cystic fibrosis patient: an analysis by 2-D gel electrophoresis and capillary column liquid chromatography-tandem

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mass spectrometry. Microbiology, 146, 2495–2508. Calvo, E., Pucciarelli, M.G., Bierne, H., Cossart, P., Albar, J.P., and García-Del Portillo, P. (2005) Analysis of the Listeria cell wall proteome by two-dimensional nanoliquid chromatography coupled to mass spectrometry. Proteomics, 5, 433–443. Nally, J.E., Whitelegge, J.P., Aguilera, R., Pereira, M.M., Blanco, D.R., and Lovett, M.A. (2005) Purification and proteomic analysis of outer membrane vesicles from a clinical isolate of Leptospira interrogans serovar Copenhageni. Proteomics, 5, 144–152. Mattow, J., Siejak, F., Hagens, K., Becher, D., Albrecht, D., Krah, A., Schmidt, F., Jungblut, P.R., Kaufmann, S.H., and Schaible, U.E. (2006) Proteins unique to intraphagosomally grown Mycobacterium tuberculosis. Proteomics, 6, 2485–2494. Williams, J.N., Skipp, P.J., Humphries, H.E., Christodoulides, M., O’Connor, C.D., and Heckels J.E. (2007) Proteomic analysis of outer membranes and vesicles from wild-type serogroup B Neisseria meningitidis and a lipopolysaccharidedeficient mutant. Infect. Immun., 75, 1364–1372. Morsczeck, C., Prokhorova, T., Sigh, J., Pfeiffer, M., Bille-Nielsen, M., Petersen, J., Boysen, A., Kofoed, T., FrimodtMøller, N., Nyborg-Nielsen, P., and Schrotz-King, P. (2008) Streptococcus pneumoniae: proteomics of surface proteins for vaccine development. Clin. Microbiol. Infect., 14, 74–81. Chitlaru, T., Gat, O., Grosfeld, H., Inbar, I., Gozlan, Y., and Shafferman, A. (2007) Identification of in vivo-expressed immunogenic proteins by serological proteome analysis of the Bacillus anthracis secretome. Infect. Immun., 75, 2841–2852. Sundaresh, S., Randall, A., Unal, B., Petersen, J.M., Belisle, J.T., Hartley,

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M.G., Duffield, M., Titball, R.W., Davies, D.H., Felgner, P.L., and Baldi, P. (2007) From protein microarrays to diagnostic antigen discovery: a study of the pathogen Francisella tularensis. Bioinformatics, 23, 508–518. McMurry, J., Sbai, H., Gennaro, M.L., Carter, E.J., Martin, W., and De Groot, A.S. (2005) Analyzing Mycobacterium tuberculosis proteomes for candidate vaccine epitopes. Tuberculosis (Edinb), 85, 95–105. Hitchen, P.G., and Dell, A. (2006) Bacterial glycoproteomics. Microbiology, 152, 1575–1580. Fauquenoy, S., Morelle, W., Hovasse, A., Bednarczyk, A., Slomianny, C., Schaeffer, C., Van Dorsselaer, A., and Tomavo, S. (2008) Proteomics and glycomics analyses of N-glycosylated structures involved in Toxoplasma gondii–host cell interactions. Mol. Cell. Proteomics, 7, 891–910. Bakal, C.J., and Davies, J.E. (2000) No longer exclusive club: eukaryotic signalling domains in bacteria. Trends Cell. Biol., 10, 32–38. Macek, B., Mijakovic, I., Olsen, J.V., Gnad, F., Kumar, C., Jensen, P.R., and Mann, M. (2007) The serine/threonine/ tyrosine phosphoproteome of the model bacterium Bacillus subtilis. Mol. Cell. Proteomics, 6, 697–707. Macek, B., Gnad, F., Soufi, B., Kumar, C., Olsen, J.V., Mijakovic, I., and Mann, M. (2008) Phosphoproteome analysis of E. coli reveals evolutionary conservation of bacterial Ser/Thr/Tyr phosphorylation. Mol. Cell. Proteomics, 7, 299–307. Rogers, L.D., Kristensen, A.R., Boyle, E.C., Robinson, D.P., Ly, F.T., Finlay, B.B., and Foster, L.J. (2008) Identification of cognate host targets and specific ubiquitylation sites on the Salmonella SPI-1 effector SopB/SigD. J. Proteomics, 71, 97–108.

7

Part One Basic Proteomic Methods

9

2 Separation of Proteins and Peptides Ludovit Skultety

2.1 Introduction

Separating and analyzing each tiny plant on a meadow would be a ridiculously difficult task. Shrink these plants to submicroscopic size and you will begin to understand the challenge of proteomics to characterize every protein. Although new technologies have arrived on the scene, separation of one protein from another is usually the most laborious and limiting aspect of proteomics. Thus, reliable and effective methods of sample preparation and separation are the keys to the success of proteomic research. Biological materials usually do not contain just proteins of interest. They include also interfering substances, such as salts, small ionic molecules, ionic detergents, saccharides, lipids and other nonprotein components. Thus, the proteins of interest must be isolated by the appropriate step in the purification procedure, while the interfering substances are depleted or removed entirely. Their presence in the sample may result in difficulty in the further protein separation and also disturb the detection and identification of proteins in proteome studies. Depending on the type of sample, there are various ways to prepare a protein sample for further separation [1]. Basic methods include protein precipitation, dialysis, ultrafiltration and ultracentrifugation. In bulk protein purification, a common first step to isolate proteins is precipitation that may rely on different chemical principles. Precipitation can be obtained by ammonium sulfate, trichloroacetic acid (TCA), TCA in acetone, ethanol, acetone [2] or methylethylketone at acid pH in the case of hemeproteins [3]. Although many such methods have the advantage of concentrating and eliminating contamination, they also have the disadvantage of irreversible protein denaturation and protein insolubility. Dialysis is an old established procedure for reducing the salt concentration in samples. The separation is based on principles of diffusion that allows the low

BSL3 and BSL4 Agents: Proteomics, Glycomics, and Antigenicity, First Edition. Edited by Jiri Stulik, Rudolf Toman, Patrick Butaye, Robert G. Ulrich. © 2011 Wiley-VCH Verlag GmbH & Co. KGaA. Published 2011 by Wiley-VCH Verlag GmbH & Co. KGaA.

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2 Separation of Proteins and Peptides

molecular weight contaminant removal from sample solutions. Using dialysis, the maximal interfering substances can be reduced. However, it may cause loss of the proteins in the sample, consume large volumes of interchanged buffer and require more time than other desalting techniques [4]. In the meanwhile, ultrafiltration and ultracentrifugation can remove high or low molecular weight interfering substances in a relatively short time by using selective permeable membranes [4–6] or centrifugal force [7], respectively. Although the removal of these interferences can concentrate the proteins, some of the interfering proteins with a molecular weight similar to the protein(s) of interest are also concentrated. This means that each purification method has its own set of advantages and disadvantages. Therefore, alternative or multistep methods might be necessary for protein concentration and/or desalting in order to get a high quality sample. The proteome of any organism is usually very complex and may consist of thousands protein species each with its unique chemical and physical properties. Because of the limited resolution of analytical separation techniques presently applied in protein profiling and expression analysis, only the most abundant proteins are usually identified by subsequent mass spectrometric (MS) analysis. Since the relative amounts of protein species present within any proteome of a living organism may differ by 7–10 orders of magnitude, the relatively less abundant proteins are usually masked by the more abundant ones, such as those needed for housekeeping or required structurally. This makes it difficult to relate the results of proteome profiling to the biology of the system. Low copy number regulatory proteins such as kinases, phosphatases or GTPases can be detected only after applying additional fractionation strategies to reduce sample complexity [8]. To gain a better understanding of the inner workings of any living organism, initial prefractionation methods must be employed in proteomics [9–12]. In order to find a suitable procedure that exhibits a satisfactory yield and purification factor (the number that represents how much “enrichment” you achieved or how well you removed all extraneous proteins), it is desirable to try more than three fractionation/separation methods. If possible all the procedures should have a purification factor of five or more and a yield of at least 30%. The time required to effect the procedure should be also considered. Nevertheless, the activity of the protein of interest may disappear because of, for example, irreversible adsorption of protein to the column materials, unstable conformation and/or proteolytic digestion. Thus, in order to slow down proteolysis, it is usually desirable to proceed as quickly as possible, adding a cocktail of protease inhibitors and keeping the protein mixture cooled during the purification. Based on the separation strategy, proteomic experiments can be divided into gel-based and gel-free approaches. Gel-based proteomics accomplish protein separation by one- or two-dimensional plate gel electrophoresis. Then, protein bands/ spots are usually analyzed by software and excised out. The “in gel” digested protein bands/spots are further fractionated and analyzed by MS. The gel-free proteomic experiment means “in solution” proteomics and is usually based on protein digestion and separation of resulting peptides by chromatographic or electrophoretic methods prior to MS analysis.

2.1 Introduction

2.1.1 Gel-Based Separation 2.1.1.1 One-Dimensional Electrophoresis Gel electrophoresis is a common laboratory technique that can be used both as preparative and analytical method. The principle of electrophoresis relies on the movement of a charged ion in an electric field. In practice, the proteins are usually denatured in a solution containing a detergent (typically sodium dodecyl sulfate; SDS) especially after prior reduction of disulfide bonds with mercaptoethanol or dithiothreitol. In these conditions, protein–protein interactions are prevented, proteins are unfolded and negatively charged SDS–protein complexes are formed. The amount of detergent bound is so large that any differences in native charge of the different proteins are swamped. The bigger the macromolecule, the more SDS is bound, so that all macromolecules treated with SDS have the same ratio of charge to mass. Thus, the force per unit mass in an electric field is the same, and all molecules should have the same velocity if there is no frictional drag. But electrophoresis with SDS is nearly always carried out in gels. The gels: (i) suppress connective currents produced by small temperature gradients and (ii) serve as molecular sieves. During SDS gel electrophoresis, the SDS–protein complex moves in an electric field toward the positive pole. Molecules that are small compared with the pores in the gel move readily through the gel, whereas molecules much larger than the pores are almost immobile. Intermediate-size molecules move through the gel with various degrees of facility. Polyacrylamide gels are the choice supporting media for electrophoresis because they are chemically inert and are readily formed by the polymerization of acrylamide. Moreover, their pore sizes can be controlled by choosing various concentrations of acrylamide and a cross-linking reagent (piperazine, methylenebisacrylamide) at the time of polymerization. The various SDS–polyacrylamide gel electrophoresis (SDS-PAGE) systems differ among other things in the buffers they use. The discontinuous Lämmli [13] system with Tris-glycine buffers is the most widely used. A stacking gel (Tris-glycine buffer pH 6.8; 3–4% acrylamide) is poured over a separation/running gel (Trisglycine buffer pH 8.8; 5–20% acrylamide). The longer the running gel the better the separation. The thinner the gel the nicer the bands. For proteins of a molecular weight (MW) of 10–60 kDa, separation gels containing 15% of acrylamide are well suited, gels with 10% acrylamide are used for proteins of MW of 30–120 kDa and 8% gels for proteins of MW of 50–200 kDa. To separate mixtures of small proteins and peptides of MW of 1.5–10.0 kDa, 18% gels with 7–8 M of urea can be used [14]. The alternative is a Tris-tricine system [15] that separate peptides of 1–100 kDa and does not require urea. Gradient gels (e.g., 8–15%) have a broader separation range and bands that are slightly better defined. 2.1.1.2 Two-Dimensional Electrophoresis It quickly became apparent that SDS-PAGE is not able to separate complex protein mixtures. Consequently, two-dimensional electrophoresis (2-DE) was introduced

11

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2 Separation of Proteins and Peptides Isoelectric focusing

–

–

OH–

OH

OH–

10 pl

+

H+

H+

H+

3

Inoubation SDS-PAGE

–

high MW

+ Figure 2.1 Schematic diagram of twodimensional electrophoresis. The technique sorts proteins according to two independent properties in two discrete steps: in the first dimension, isoelectric focusing separates

low proteins according to their isoelectric point (pI); in the second dimension, polyacrylamide gel electrophoresis in the presence of SDS separates proteins according to their MWs.

independently by O’Farrell and Klose in 1975. This technique sorts proteins according to two independent properties in two discrete steps: the first-dimension step (isoelectric focusing; IEF) separates proteins according to their isoelectric point (pI); the second-dimension step (SDS-PAGE) separates proteins according to their molecular weights (Figure 2.1). The result is reminiscent of a Dalmatian’s coat with spots corresponding usually to a single protein species in the sample. Thousands of different proteins and their isoforms can thus be separated, and information such as the protein pI, the apparent molecular weight and the amount of each protein can be obtained. However, for a long time 2-DE suffered a wallflower-like existence. It did deliver impressive pictures, but that was it. This was due to the fact that 2-DE was not able to reproduce consistently. Not only from laboratory to laboratory but also in the hands of the same experimenter. This sad state improved with the introduction of immobilized pH gradient (IPG) strips. The pH gradient fixed in the gel increased the reproducibility as well as the resolution of 2-DE by an order of magnitude [16]. Commonly used IPG strips are 18- to 24-cm long and available commercially in broad (pH 3–10) and narrow (e.g., pH 5.5–6.5, 7–11) pH ranges. The purchased

2.1 Introduction

strip is rehydrated overnight in a rehydration cassette. For rehydration solution, the Expasy home page [17] recommends 25 ml 8 M urea, 2% (w/v) CHAPS, 10 mM dithiothreitol (DTT) and 2% (v/v) IPG buffer of the relevant pH range together with a trace of bromophenol blue. The completely soaked strips are then transferred into the IEF chamber and covered with paraffin oil to prevent water from evaporating during the focusing. For loading, the sample could be either directly added to the rehydration solution or applied through a cup at the cathodic or anodic end during the focusing. The presence of a pH gradient inside the IPG strip is crucially important. Under the influence of an electric field, a protein as an amphoteric molecule moves to the position in the pH gradient where its net charge is zero. A protein with a negative net charge migrates toward the anode, becoming less negatively charged until it reaches zero net charge. A positively charged protein moves at the same time through the pH gradient until it also reaches its pI. If a protein diffuses away from its pI, it immediately gains charge and migrates back. This is the focusing effect of IEF, which concentrates proteins at their pIs and allows proteins to be separated on the basis of very small charge differences. After focusing, the proteins in the IPG strip have to be saturated with SDS. For that, the focused strips are first incubated for 10–15 min in an equilibration buffer [e.g., 40 mM Tris-HCl, pH 6.8, 6 M urea, 30% (v/v) glycerin, 2% (w/v) SDS] containing 2% (w/v) DTT (or dithioerythritol, β-mercaptoethanol). Afterward, the free SH groups are blocked with 2.5% (w/v) iodoacetamide in the incubating solvent for 5 min. Each strip is then transferred onto a SDS-PAGE gel and the electrophoresis is performed [18]. 2.1.1.3 Protein Staining and Image Analysis With the development of gel-based proteomics, an additional burden is placed on the methods used for protein detection. Besides the classical requirements, such as sensitivity, homogeneity from one protein to another, linearity throughout a wide dynamic range, speed, convenience and low cost, detection methods must now take into account another aspect, namely their compatibility with digestion and MS. This compatibility is evidenced by two different and complementary aspects. These are: (i) the absence of adducts and artefactual modifications of the peptides obtained after protease digestion of a protein detected and digested in gel and (ii) the quantitative yield of peptides recovered after digestion and analyzed by the MS instrument. While this quantitative yield is not very important per se, it is a crucial parameter as it strongly influences the signal to noise ratio of the mass spectrum and thus the number of peptides that can be detected from a given protein input, especially at low protein concentrations. This influences in turn the sequence coverage and thus the analysis provided by the MS instrument. Up to now, no protein detection method in the three families of methods that are of current use in proteomics perfectly matches these prerequisites. The most popular method is probably colloidal Coomassie blue staining [19]. Although this method is not very sensitive, it affords a very good compatibility with MS. It has also gained popularity in the early days of proteomics, when its sensitivity matched

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almost exactly the needs of protein amounts required for a decent analysis by MS. With improvement of the MS instruments, associated robotics and so on, this is no longer the case, and detection by colloidal Coomassie either requires unnecessary consumption of sample or results in significant numbers of potentially analyzable proteins that are undetected. Fluorescent detection methods offer an interesting alternative, and metal chelate-based methods [20, 21] have become increasingly popular. In their most recent versions [22], these methods offer an increased sensitivity allied with a very good compatibility with MS analysis. These methods are however not easy to use in small proteomics laboratories. Besides the expensive laser scanners or CCD cameras required for quantitative analysis, spot excision must be performed under UV light. It induces in turn collateral problems such as safety and photobleaching, both increasing when large numbers of spots are to be excised in comprehensive proteomics studies. Last but not least, silver staining still offers the maximal sensitivity and all the ancillary advantages associated with light absorption-based methods, such as easy visualization and quantitation (although the linear dynamic range of silver staining is not very good) and easy spot excision. However, in the proteomics context, the most important problem lies in its limited compatibility with MS. Although this aspect has been improved by optimization of the staining procedure [23, 24], destaining of the spots or bands after silver staining [25], or by development of silver–ammonia methods [26], the compatibility with MS remains far below that which can be achieved with fluorescent probes or colloidal Coomassie. This low compatibility has been attributed to the use of formaldehyde [27], which also induces artefactual formylations. [28]. It was therefore of great interest to have available a sensitive silver staining method totally formaldehyde-free. However, to date, the only formaldehyde-free silver staining methods use carbohydrazide [27] or reducing sugars in alkaline borate buffer [29] as developing agents. To take full advantage of the 2-DE separation, multiplex quantitative analysis of the component proteins of related but different protein samples might be performed. This technique is known as two-dimensional difference in-gel electrophoresis (2D-DIGE) which allows labeling protein mixtures with different fluorescent cyanine dyes, such as Cy2, Cy3 and Cy5 maleimides [30]. These CyDyes are structurally similar, but spectrally different (Cy2, λem = 520 nm; Cy3, λem = 580 nm; Cy5, λem = 670 nm). Compared to conventional 2-DE, 2D-DIGE has the major advantage that both the control (labeled with Cy3) and experimental (labeled with Cy5) sample are run in the same gel. These samples are then imaged separately but because they were run in the same gel, the images can be perfectly overlaid (Figure 2.2). This reduces the number of gels that must be run to make statistically valid comparisons and raises the confidence with which protein changes between samples can be detected and quantified. Use of a third dye (Cy2) permits an internal standard to be created by pooling an equal aliquot of all biological samples in the experiment. The internal standard is then run on every gel in the experiment. This means that every protein spot from all samples will be represented in the internal standard. This in turn allows more accurate quantification and spot statistics between gels.

2.1 Introduction

Image analysis Pooled internal standard labeled with Cy2 Cy2 Cy3 Protein extract 1 labeled with Cy3

Mix labeled extracts

Two-dimensional electrophoresis

Cy5

Protein extract 2 labeled with Cy5 Figure 2.2 Schematic diagram of the DIGE technology platform. Two different samples are derivatized with two different fluorophores, combined and then run on a single 2D gel. Proteins are detected using a dual laser scanning device or xenon arc-based instrument equipped with different excitation/ emission filters in order to generate two separate images. The images are then

matched by a computer-assisted overlay method, signals are normalized, and spots are quantified. Differences in protein expression are identified by evaluation of a pseudo-colored image and data spreadsheet. DIGE technology can maximally evaluate three different samples using Cy2-, Cy3- and Cy5-based chemistries.

In addition, the post-translational modifications of phosphoproteins and glycoproteins can be directly detected by different staining methods [31]. While the MS methods used to identify the protein(s) in a spot from a 2D gel are excellent, they have some serious disadvantages when it comes to determining if a protein is either modified or not. The presence of, or neutral loss of, unique mass unit “signatures” from a peptide fragment can be used as positive confirmation of the presence of a specific modification. Unfortunately it is almost impossible to determine with any degree of certainty that a protein in a spot is not modified. An alternative approach for determining whether a protein spot on a 2D gel is modified is to stain only the protein altered by individual types of post-translational modification with specific dyes. A new phosphoprotein-specific fluorescence dye called “Pro-Q™ Diamond” recently became available from Molecular Probes (Eugene, Ore., USA) and can be used to detect phosphorylated tyrosine, serine or threonine residues of proteins on SDS-PAGE and 2-DE [32]. Otherwise, Pro-Q™ Emerald 300 and Pro-Q™ Emerald 488 glycoprotein gel stains were recently developed for the detection of glycosylated proteins which relies upon the utilization of a fluorescent hydrazide. Thus, they provide an attractive alternative to the labeling with radioactive sugars that

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conjugated to glycoprotein by periodic acid Schiff’s mechanism [33]. Gels stained with both Pro-Q™ Diamond phosphoprotein stain and Pro-Q™ Emerald glycoprotein stain can also be post-stained with SYPRO® Ruby dye, which allows sequential detection of total protein profile in the same gel [33]. For immunochemical detection of specific proteins, determination of derivatization (phosphate group, sugar residues), exposure to enzyme substrate, binding of protein ligand or chemical microsequencing, it is better to transfer the separated proteins from the gel, onto a membrane. Nitrocellulose, polyvinylidene difluoride (PVDF), positively charged nylon or polybrene-coated glass fiber can be used [34]. The membrane in comparison to the gel is easily manipulable, and reactions or washing processes run faster, unhindered by diffusion problems. Furthermore, the adsorbed proteins on the membrane might be visualized by reversible stains [35, 36] before letting a blot react with antibodies, lectins, substrate or protein ligands. Evaluation of two visualized high-resolution 2-DE gels or blots by manual comparison is not an easy task. In large studies with patterns containing several hundreds or even thousands spots, it may be almost impossible to detect the appearance of a few new spots or the disappearance of single spot. Image collection hardware and image evaluation software are necessary to detect these differences as well as to obtain maximum information from the gel patterns. The systems that are commonly available commercially (Image Master 2D Platinum from GEH, Melanie from GeneBio, PDQuest from BioRad, Dymension from Syngene, Delta 2D from Decodon, Progenesis from Nonlinear Dynamic, etc.) seamlessly perform both classical and DIGE gel analysis. These systems provide powerful solutions from data acquisition to protein spot information. The spot detection and matching algorithms facilitate the extraction of statistically valid differences between groups of 2D gels, while requiring minimal user intervention. The applications integrate filtering, querying, reporting, statistical and graphing options so that you can easily view, compare, analyze and present the results. 2.1.1.4 2-DE Limitations As analytical 2-DE is remarkably well suited to studying protein expression in biological systems, it is used in most laboratories where proteomics are performed. However, this separation technique has some drawbacks that can severely limit the investigator’s ability to monitor protein expression on a truly global scale. Proteins that are notably difficult to separate using 2-DE are membrane, low copy number, large (>150 kDa) and highly basic proteins. Driven by the need to study these “difficult” proteins together with their less challenging counterparts, some alternative separation methods have to be applied. 2.1.2 In Solution – “Gel Free” Proteomics

However, methods that perform protein/peptide separations in the liquid phase generally have a lower ability to resolve complex mixtures and provide inferior

2.1 Introduction Table 2.1

Nomenclature for HPLC columns in cylindrical formats.

Description of columns

Diameter

Approximate typical flow rate (velocity 1–10 mm/s)

Open tubular liquid Nanobore Capillary Microbore Narrow (small) bore Normal bore Semipreparative Preparative

>25 μm i.d. 25 μm > i.d. > 100 μm 100 μm > i.d. > 1 mm 1 mm > i.d. > 2.1 mm 2.1 mm > i.d. > 4 mm 4 mm > i.d. > 5 mm 5 mm > i.d. > 10 mm i.d. < 10 mm

25 nl/min 25–4000 nl/min 0.4–200 μl/min 50–1000 μl/min 0.3–3.0 ml/min 1.0–10.0 ml/min 5.0–40 ml/min 20 ml/min

visualization of proteomes, as compared to 2-DE. Their advantages are analysis of “difficult” proteins, flexibility, relative speed, ease of automation of sample handling and direct connection to MS. Liquid phase separations are faster than their in-gel counterparts (two-dimensional separation can be achieved in just a few hours). Thus, it also shortens the time between sample preparation and protein identification. Liquid phase separations can be performed using chromatography, electrophoresis, or a combination of these methods. However, it is not necessary to limit protein separation only to these approaches. Any combination may be tried and can be especially useful for a particular biological system [37, 38]. Column chromatography is one of the most common methods of protein purification. Many types of available matrices used for column chromatography are usually packed in a column of different dimensions (Table 2.1) in the form of small beads. 2.1.3 Column Chromatography

It has often been stated that the column is the heart of the chromatograph. Without the correct choice of column and appropriate operating conditions, separation can be both frustrating and unrewarding. Nowadays, the increased need for highthroughput and high-sensitivity assays are the driving forces for new developments, including rectangular, square or other perimeter-shaped column (e.g., on chips) and, in particular, in particle designs such as perfusive packings, poroshell particles, inorganic/organic hybrids, monoliths and sub-2 μm nonporous particles. Advances are still being made in column technology with even smaller porous particles (1–2 μm in diameter), high-temperature (up to 200 °C) columns, nanocolumns with diameters under 100 μm and rapid-separation columns enabling highresolution separations in seconds. Some of the more common chromatographic columns used in proteomics include: (i) size exclusion chromatography (gel filtration), (ii) reverse phase liquid

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chromatography, (iii) hydrophobic interaction liquid chromatography, (iv) ion exchange chromatography and (v) affinity chromatography. 2.1.3.1 Size Exclusion Chromatography Size exclusion chromatography (SEC), also known as gel permeation chromatography or gel filtration chromatography, is generally considered the premier method for determining: (i) the molar mass averages of polydisperse macromolecules, (ii) separation of target protein in a mixture and (iii) salt removal or buffer exchange. The dissolved analyte is injected onto a column packed with porous, inert material (porous gels, other rigid inorganic packing particles) and is carried through the column by the solvent. Both molecular weight and shapes of proteins contribute to the degree of retention. Smaller molecules diffuse further into the pores of the beads and therefore move through the bed more slowly, while larger molecules enter less or not at all and thus move through the bed more quickly (Figure 2.3a). The process has been described as an inverse molecular sieving mechanism that depends on hydrodynamic volume of a dissolved molecule with respect to the average pore size of the column packing material [39]. Although it is widely used, low-pressure SEC is not suitable for protein purification for several reasons: (i) pouring and running the column is time-consuming, (ii) the resolution is poor, (iii) the sample volume is limited, (iv) the chromatography takes a long time because the flow rate is limited, and finally, (v) the sample is diluted by at least a factor of three. 2.1.3.2 Reversed-Phase Liquid Chromatography Reversed-phase liquid chromatography (RPLC) is the most frequently used method for peptide separation. However, it can also efficiently separate small, stable proteins (e.g., toxins). Peptides and/or proteins adsorb to the hydrophobic surface that consists of porous silica particles coated in general with n-alkyl chains (Figure 2.3b). For peptides, silica particles with pore dimensions of 100–300 Å are used. For proteins, the pore diameter should be 10 times larger. The n-alkyl chains are 2-, 4-, 8- or 18-C long, and their length unpredictably changes the separating properties of the RPLC. Two peptides that show two separate peaks on C18 columns may exhibit only one peak on C4 columns (or vice versa). The sample is almost exclusively eluted with a rising acetonitrile gradient. For separation of large or very hydrophobic proteins the mixture of 2-propanol with acetonitrile serve well. The quality of the separation depends not only on the beads but also on the steepness of the gradient and the temperature. The temperature is in play because peptides can maintain their secondary structure (α-helix, β-fold), which influences the adsorption (high temperature denatures secondary structures). Regarding the column length (typically 10–20 cm), the separation of peptides and smaller proteins improves with longer columns. In contrast, larger proteins should be separated on shorter columns, otherwise the yield becomes too small. However, RPLC is rarely used to separate larger proteins because they tend to denature under these conditions [34].

2.1 Introduction (a)

-

(b)

-

-

-Si-(C2-C18)

-

-

-

(C2-C18)-Si-

-Si-(C2-C18)

-

-

(C2-C18)-Si-

H2O

(c)

H2O

H2O

H2O H2O

H2O

H2 O H2 O

H2O H2O

H2O

H2O

H2O

H2O

(d)

(e)

Figure 2.3 Schematic diagram of chromato-

graphic separations. (a) Size exclussion chromatography. The columns separate proteins according to their size. The matrix consists of tiny porous beads. Protein molecules that are small enough to enter the holes in the beads are delayed and travel more slowly through the column. (b) Reverse phase chromatography. Peptides and/or proteins adsorb to the hydrophobic surface that consists of porous silica particles coated in general with n-alkyl chains (2-, 4-, 8-, or 18-C). The sample is normally eluted with an increasing acetonitrile gradient. (c) Hydrophilic interaction liquid chromatography. The mobile phase forms an aqueous layer on the surface of the polar stationary phase creating a liquid/liquid extraction system. The analyte is distributed between the

water reach stationary layer and the mobile phase with low water contents. Elution is obtained through increasing the hydrophilicity of the mobile phase by increasing the water content. (d) Ion exchange chromatography. The column is packed with small beads that carry positive or negative charges that retard proteins of the opposite charge. The association between a protein and the matrix depends on the pH and ionic strength of the solution passing down the column. (e) Affinity chromatography. The columns contain a matrix covalently coupled to a molecule that interacts specifically with the protein of interest (e.g., antibody, immobilized metal ions, lectins or an enzyme substrate, etc.). Protein that binds specifically to such a column can finally be released by a pH change or by concentrated salt solutions.

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2.1.3.3 Hydrophilic Interaction Liquid Chromatography The separation of peptides with many acidic and basic residues has always proved to be problematic with RPLC gradient elution. A rival technique for separating polar peptides is hydrophilic interaction LC (HILIC) that can be simply seen as a form of normal phase (NP) chromatography. However, the acronym HILIC was suggested to distinguish it from NP, as NP is typically performed with nonaqueous solvent buffers, while HILIC is performed with water-miscible solvents. In recent years, several stationary phases have emerged that are specifically developed for HILIC approaches. Popular phases include underivatized silica that contains functional groups such as siloxanes, silanols with (or without) a small quantity of metals or derivatized silica (various cation, anion or zwitterionic exchangers). Each of these materials display different retention characteristics and separation selectivities and require distinct buffer compositions for optimal results [40]. The typical mobile phase for HILIC includes acetonitrile (more than 70%) with a small amount of water [41]. It is commonly believed that in HILIC, the mobile phase forms a water rich layer on the surface of the polar stationary phase creating a liquid/liquid extraction system (Figure 2.3c). The analyte is distributed between the aqueous stationary layer and the mobile phase with low water content. More polar compounds will have a higher affinity (stronger polar interaction) for the stationary layer than less polar compounds. Elution is obtained through increasing the hydrophilicity of the mobile phase by increasing the water content. The final separation mechanism of elution, however, is most probably a superpositioning of partitioning and electrostatic interactions or hydrogen bonding to the stationary phase [42]. 2.1.3.4 Ion Exchanger Chromatography Ion exchanger chromatography (IEC) might be applied to both peptide and protein separation. It is based on the charge of the proteins that are separated via electrostatic interaction with a matrix (Figure 2.3d). Proteins with a high positive charge are bound to a column with a negative charge (cation exchanger) that often uses carboxymethyl groups (weak cation exchanger) or sulfopropyl groups (strong cation exchanger; SCX). The positive charge on the column (anion exchanger; AX) including the strong anion exchanger Q (quaternary resin) and the weak anion exchanger diethylaminoethane (DEAE) binds the negatively charged proteins [43]. The charged sample is loaded on the column which is equilibrated with a buffer of low ionic strength (e.g., 20 mM salt). Unbound proteins are washed out and the captured protein is eluted through increasing the salt concentration or changing the pH. The easiest way is to perform chromatography at a constant pH. The captured protein is then eluted through changes in ionic strength. Because the IEC column has a higher attraction for the charge of salts than for the charged protein, it will release the protein in favor of binding the salts. Proteins with weaker ionic interactions will elute at a lower salt concentration and thus different proteins will elute at different salt concentrations. Be aware that changes in pH alter the charge of a protein. Therefore, ensure that the pH of the system is adjusted and buffered accordingly.

2.1 Introduction

2.1.3.5 Affinity Chromatography Selective separation of a specific protein or group of proteins can be achieved using affinity chromatography (AC) which is based on the ability of a biologically active molecule to bind specifically and reversibly to a complementary molecule. The binding sites of the immobilized substances must be sterically accessible after their coupling to the solid support and should not be deformed by immobilization. In the case of specific proteins, an affinant is attached to the active surface of the column packing material or column surface. The sample is injected onto the column and the protein(s) of interest is captured by the affinant [9]. Compounds that do not possess a complementary binding site for the bound ligand will either pass directly through the column or be eluted by a subsequent washing step (Figure 2.3e). The bound protein(s) is then recovered by washing the column with a competitive substrate or a solution that disrupts the interaction between protein and affinant (e.g., denaturants). While the use of antibodies directed to a specific protein remains the most popular affinity-based separation method, many other affinity techniques for isolating a specific class of proteins or peptides have been developed. These methods include immobilized metal ion affinity chromatography (IMAC) containing nickel or copper ions, to capture histidine-containing peptides [44, 45] or gallium [46] and alternatively zirconium [47] to isolate phosphopeptides. In addition, affinity methods have been developed to isolate peptides containing specific types of residues such as cysteine, tryptophan or methionine [48]. There are, as well, a variety of different lectins that have been used to selectively isolate glycoproteins based on the composition of the carbohydrate side chain [49]. 2.1.3.6 Multidimensional Chromatography Since the resolving power of a single chromatographic step is very limited and because of use of different types of columns and solvent systems naturally leads to different protein or peptide separation, efforts have been made to develop multidimensional approaches. This concept was described first by Giddings (1984) [65] as an orthogonal system of two or more coupled separations based on different retention mechanisms that effectively create another opportunity for resolving analytes. Two main issues that must be considered at the beginning are the way columns are coupled, online or offline, and whether to perform separations at the peptide or protein level. Thus, the investigator may chosen to perform the proteolytic digestion of the whole protein sample and separate the peptides using 2D LC (“shotgun”, online approach), or to separate intact proteins on the first column, followed by a proteolytic digestion (offline approach). The main advantage of online multidimensional LC techniques is the possibility of full automation of the complete comprehensive 2D-LC process without handling or transfer of samples. However, this shotgun approach results in very complex samples consisting of several hundred thousand peptides with concentrations varying by 10 or more orders of magnitude. Other shortcomings are the loss of post-translational modifications and the difficulty of proper assignment. Separating the intact proteins of a complex sample prior to digestion has the advantage of: (i) reduced sample complexity, (ii) more efficient separations, (iii) higher flexibility with respect to

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column dimensions and mobile phase selection and (iv) more straightforward method development and troubleshooting. Thus, the protein identification, posttranslational modification assessments and the dynamic range are improved by several orders of magnitude. A variety of multidimensional combinations has been reported [50, 51]. These methods may use a wide variety of chromatographic techniques and number of dimensions, but practical considerations of interfacing the method with MS limit the utility of many combinations. For large-scale MS characterization of proteins, reversed-phase nanoLC is usually the last step and it is most often combined with capillary electrophoresis, IEF, IEC, RPLC or AC. While the latter approach is mainly applied to more specific functional proteomics, on line 2D LC using a SCX column in series with a RP column (e.g., with the multidimensional protein identification technology; MudPIT) is performed for analysis of comprehensive protein expression profiles of the whole proteome. The tryptic peptides are eluted from the SCX column by incremental increases of salt in the first dimension. In the second dimension these peptides are first trapped on a RP enrichment column and finally separated on an analytical RP column [52, 53] (Figure 2.4).

Trap charged peptide on SCX column Trap uncharged petides on RP trap column Complex peptide mixture

Wash RP gradient

Process data

Proteases Higher salt concentration Salt injection Total lysate Release peptides from SCX column Database search Trap peptides on RP trap Figure 2.4 Schematic diagram of the MudPIT approach. The protein mixture is divided in aliquots, which are each digested by a protease. After protease inactivation, the aliquots are pooled and acidified. The peptide mixture is then loaded on a strong cation exchanger (SCX) column, followed by a reverse phase column (RP) coupled by a nanoelectrospray device to a tandem mass

spectrometer. The SCX column is eluted by incremental increases of salt. This transfers a population of peptides in the RP column, where they bind. Using a reverse phase gradient, the separated peptides are eluted into a tandem mass spectrometer. Peptide fragmentation data is then obtained to identify the peptides and hence the proteins from which they are derived.

2.1 Introduction

2.1.4 Liquid Phase IEF and Electrophoresis

Analytical 2-DE combined with MS is a powerful procedure that allows the high resolution of proteins and their rapid identification. However, analytical 2-DE procedures are rarely capable of supplying sufficient amounts of low abundance proteins for further characterization by MS without first recovery of proteins from several gels; liquid phase IEF and electrophoresis might be the methods of choice. The Rotofor cell (Bio-Rad) has been developed for preparative scale IEF in the liquid phase. This technique has the unique ability to enrich low-abundance proteins up to 500-fold at their respective isoelectric points [54, 55]. The individual proteins are then isolated on the basis of their size differences in liquid phase continuous SDS-PAGE [56, 57]. The Prep cell (Bio-Rad) has been designed for that purpose. Two-dimensional preparative liquid phase electrophoresis (2DLPE) allows high protein loads (up to 1 g) and large volumes (up to 55 ml), thus yielding sufficient amounts of low abundance proteins for further characterization by MS [58]. 2.1.5 Alternative Separation Technologies

A novel approach, similar to 2-DE, is under development at Lynx Therapeutics (Hayward, Calif., USA). As in 2-DE systems, the Lynx Protein Profiler uses separation by charge, combined with separation by mass. However, the gels are replaced by flat plates that contain multiple channels. In the first dimension, electrophoresis in an cross-linked polymer sieving solution is performed for separation based upon mass. In this system, proteins are not complexed with SDS but are fluorescently prelabeled for detection. The separation range is 6000– 200 000 MW. After the first-dimension separation, the separated proteins are electrically driven orthogonally into 100 parallel channels, which are coated with covalently attached buffers. Applying an electric field to these channels generates a stable pH gradient within which proteins are resolved based on their isoelectric points [59]. An alternative approach for complex mixture analysis has been developed also by Ciphergen Biosystems, Inc. (Fremont, Calif., USA). This technology, marketed as the Protein-Chip system, selectively captures the proteins of interest using an aluminum strip with eight domains that carry different affinity adsorbents. The adsorbents might be nonspecific, such as cationic, anionic, hydrophobic or hydrophilic materials, or highly specific, such as antibodies or receptors. Proteins are adsorbed from a complex mixture, unbound material and interferences are washed away, and bound species are analyzed by MS systems [60, 61]. In addition, microscale lab-on-a-chip devices have been developed for performing chemical reactions and separations [62–64]. Several versions of this technology have been commercialized, but all rely on similar principles of microfluidics [34]. Reagents and chemicals are transported electrically using electro-osmotic flow or,

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in some cases, by hydrodynamic flow using pressure or vacuum. Analytes are separated by electromigration using electrophoresis and electroosmosis.

Acknowledgment

The author thanks Dr. Graham Palmer from Rice University (Houston, Tex., USA) for language revision and critical reading of the manuscript.

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3 Basic Mass Spectrometric Approaches Lenka Hernychova and Martin Hubalek

3.1 Introduction

Proteomics in principle is technology dealing with mixtures of proteins at a given time and condition and the aim is the characterization of the protein quality and quantity. Such studies typically pose challenges owing to the high degree of complexity of cellular proteomes that necessitates highly sensitive analytical techniques. Mass spectrometry has increasingly become the method of choice for the analysis of complex protein samples. Mass spectrometric measurements are carried out in the gas phase on ionized analytes. By definition, a mass spectrometer consists of an ion source, a mass analyzer that measures the mass to charge ratio (m/z) of the ionized analytes and a detector that registers the number of ions at each m/z value (Figure 3.1). One of the biggest recent discoveries in the methodology of biomolecular analysis was certainly the invention of soft ionization techniques prior to mass spectrometry analysis. Two techniques very different in principle were developed: (i) matrix-assisted laser desorption/ionization (MALDI) by Koichi Tanaka [1] and Karas with Hilenkampf [2–4] and (ii) electrospray ionization (ESI) by John Bennett Fenn [5, 6]. Since the invention of these new ionization techniques, mass spectrometry of biomolecules recorded an unprecedented boom in improvements of sensitivity, resolution, robustness and comprehensibility and established itself as one of the most potent and reliable bioanalytical techniques. The Nobel price for chemistry in 2002 was not surprisingly awarded for these efforts.

BSL3 and BSL4 Agents: Proteomics, Glycomics, and Antigenicity, First Edition. Edited by Jiri Stulik, Rudolf Toman, Patrick Butaye, Robert G. Ulrich. © 2011 Wiley-VCH Verlag GmbH & Co. KGaA. Published 2011 by Wiley-VCH Verlag GmbH & Co. KGaA.

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3 Basic Mass Spectrometric Approaches Ion source

Mass analyzer

Detector

Figure 3.1 Simplified schematic of a mass spectrometer.

MALDI spot

+

Pulsed laser

+ [M+H]

+20 kV

+

Ground Variable Grid Grid

Figure 3.2 Matrix-assisted laser desorption ionization depicted with matrix in yellow and analyte in gray.

3.2 Ionization 3.2.1 Matrix-Assisted Laser Desorption/Ionization

MALDI is a soft ionization technique used in mass spectrometry that deals well with thermolabile, nonvolatile organic compounds, especially those of high molecular mass (e.g., polymers, other macromolecules). Moreover this ionization is used successfully in biochemical areas for the analysis of biopolymers (e.g., proteins, peptides, glycoproteins, oligosaccharides, oligonucleotides). It is similar in character to electrospray ionization in relative softness and the ions produced, although MALDI causes many fewer multiply charged ions. Nevertheless MALDI ionization is relatively straightforward to use and reasonably tolerant to buffers and other additives and it is usually coupled to a time of flight (TOF) mass analyzer. The ionization is triggered by a laser beam (e.g., a nitrogen laser, Nd:YAG, Er:YAG, CO2). The laser is fired at the crystals on the MALDI spot (Figure 3.2) when the matrix absorbs the laser energy and it is thought that primarily the matrix is ionized by this event. The matrix is then thought to transfer part of its charge to the analyte molecules (e.g., mix of peptides), thus ionizing the molecules while

3.2 Ionization

still protecting them from the disruptive energy of the laser. Ions observed after this process consist of a neutral molecule [M] and an added or removed ion. Together, they form a quasimolecular ion, for example [M+H]+ in the case of an added proton, [M+Na]+ in the case of an added sodium ion, or [M-H]− in the case of a removed proton. MALDI is capable of creating singly charged ions, but multiply charged ions ([M+nH]n+) can also be created. Note that these are all evenelectron species. Ion signals of radical cations can be observed, for example, in the case of matrix molecules and other stable molecules. The matrix consists of crystallized small organic molecules, usually acidic, of which the three most commonly used are 3,5-dimethoxy-4-hydroxycinnamic acid (sinapinic acid; SA), α-cyano-4-hydroxycinnamic acid (alpha-cyano; CHCA) and 2,5-dihydroxybenzoic acid (DHB). A solution of one of these molecules is made, often in a mixture of highly purified water and an organic solvent [e.g., acetonitrile (ACN) or ethanol]. Trifluoroacetic acid (TFA) may also be added. For example a matrix-solution would be 20 mg/ml sinapinic acid in ACN:water:TFA (50 : 50 : 0.5). 3.2.2 Electrospray Ionization

ESI is the primary ion source used in liquid chromatography–mass spectrometry because it is a liquid–gas interface capable of coupling liquid chromatography with mass spectrometry. In ESI (Figure 3.3), the sample is dissolved in a polar, volatile solvent and pumped through a narrow, stainless steel capillary. A high voltage of 3 or 4 kV is applied to the tip of the capillary. The lens voltages are optimized individually for each sample. A flow rate is between 1 μl/min and 1 ml/min. The sample emerging from the tip is dispersed into an aerosol of highly charged droplets. The aerosol is at least partially produced by a process involving the formation of a Taylor cone. An uncharged carrier gas such as nitrogen is sometimes used to help nebulize the liquid and assists to direct the spray emerging from the capillary tip towards the mass analyzer. The charged droplets diminish in size by solvent evaporation, assisted by a warm flow of nitrogen know as the drying gas which passes across the front of the ionization source. The analyte molecules are forced closer together, repel each other and break up the droplets. This process is called Coulombic fission because it is driven by repulsive Coulombic forces between charged molecules. The process repeats until the analyte is free of solvent and is a lone ion. These ions enter through the orifice into an intermediate vacuum region and from there through a small aperture into the analyzer of mass spectrometer, which is held under high vacuum. In electrospray processes, the ions observed may be quasimolecular ions the same as described in MALDI ionization (see above). For large macromolecules, there can be many charge states, occurring with different frequencies; the charge can be as great as [M+20H]20+, for example. All these are even-electron ion species: electrons (alone) are not added or removed, unlike in some other ionizations. The

31

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3 Basic Mass Spectrometric Approaches Coulombic fission Capillary +

+ – –

+

– +

+

–

+ +

+

+

–

+

+

+

+

+

+

–

–

–

+ –

++++ ++++ ++++

+ –

+

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+ + +

+

+

+

+

–

+ –

+ ++ + ++ +

–

+ ++ + + ++ +

+

+

+++ ++++ +++

+ –

+ ++ + + ++ +

Taylor cone

–

+ + ++++ ++++ ++++

+ +

++++ ++++ ++++

+++ ++++ +++

+ + + + + +

Electrons

Oxidation

+

+

Diminishing size of charged droplets by solvent evaporation

+

–

Source of high tension

Electrons

Reduction

Figure 3.3 The mechanism of electrospray ionization.

formation of ions in electrospray is somewhat homologous to acid–base reactions. Redox reactions do occur and a circuit with measurable current flow exists, but atomic and molecular ions are the primary carriers of charge in the solution and gas phases. There are many variations on the basic electrospray technique that generally offer better sensitivity [7]. Two important versions are microspray (μ-spray) and nanospray (n-spray) [8]. The primary difference is in the reduced flow rate of the analyte containing liquid (μl/min and nl/min, respectively); this allows the application of micro- or nanoscale chromatography that yield much wanted sensitivity in proteomic experiments. This change causes adjustments in setup such as the reduced internal diameter of the tubing or lack of nebulization gas.

3.3 Mass Analyzers

The mass analyzer is central to the mass spectrometry instrument (Figure 3.1). In the context of proteomics, its key parameters are sensitivity, resolution, mass accuracy and ability to generate information-rich ion mass spectra from peptides (MS/MS spectra). There are four basic types of mass analyzers currently used in proteomics research that differ in principal applied to measure a mass of the analyte (Figure 3.4). These are time of flight (TOF), quadrupole (Q); ion trap (IT)

3.3 Mass Analyzers (a)

(d)

Pulsed laser

Reflector time-of-flight (TOF)

Q1

q2

33

TOF

Quadrupole time-of-flight Sample plate

TOF Reflector

(b)

Reflector

Time-of-flight time-of-flight (TOF-TOF)

(e) TOF1

Ion trap

TOF2

Collision cell

(c) Triple quadrupole or linear ion trap

Q1

q2

Q3

(f) Fourier transform ion cyclotron resonance mass spectrometer (FT-MS)

Q1

Super conducting magnet

Figure 3.4 Mass analyzers and their instrumental configuration used in proteome research.

This figure was kindly provided by Aebersold R. et al. [9].

and Fourier transform ion cyclotron analyzers (FT ICR). They are very different in design and performance, each with its own strength and weakness. These analyzers can stand alone or, in some cases, be put together to take advantage of the strengths of each. 3.3.1 Time of Flight

In TOF analyzers, the mass to charge ratio is deduced from its flight time through a tube of specified length that is under vacuum. The performance of the TOF analyzers has greatly improved, in particular in terms of resolution and mass accuracy. TOF mass analyzers are basis for analytical platforms operated with both ESI and MALDI ionizations. TOF is a method of mass spectrometry in which ions are accelerated by an electric field of known strength [10]. This acceleration results in an ion having the same kinetic energy as any other ion that has the same charge. The velocity of the ion depends on the mass to charge ratio. The time that the particle subsequently needs for to reach a detector at a known distance is measured. From this time and the known experimental parameters the mass to charge ratio of the ion can be calculated. The resolution in MALDI-TOF can be improved with delayed extraction. This refers to a prolonged onset of the extraction potential by a defined short time after the ionization event [11]. A TOF analyzer can work at least in two different modes: linear and reflectron. The linear mode has a higher ion transmission, thus making it possible to measure larger molecular ions such as intact proteins. The ions in this mode enter the flight tube and travel directly to the detector without additional focusing by reflectron. This, however, causes a loss of resolution as compare to reflectron mode. The result of this type of measurement is a linear mass spectrum (Figure 3.5).

34

3 Basic Mass Spectrometric Approaches 5816

100

1.0E+4

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70 60 50 40 30

1828 2086

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15273 15400.2

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25001.0

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Figure 3.5 Mass spectrum of Coxiella burnetii strain RSA 439 (phase I) acetonitrile extract

measured on MALDI-TOF mass spectrometer in linear positive mode.

1030.5552

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842.5131 1550.8820 980.5414 1337.7818 1743.9587 1090.5320 2127.2062 2945.6239 1196.6668 1885.0298 2212.1331 2639.2293 1163.6821 1424.8441 815.3812 1907.0844 2161.1719 2626.2539 2928.2491 763.4511 1211.6884 1500.6995 2388.3261 1716.9937

0 699.0

1259.2

1819.4

2379.6

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3500.0

Mass (m/z)

Figure 3.6 Mass spectrum of peptides from human protein, alpha crystallin B chain (accession number P02511). The protein was digested by trypsin and measured on MALDITOF mass spectrometer in reflectron positive mode.

3.3.2 Reflectron TOF

The kinetic energy distribution in the direction of ion flight can be corrected by using a reflectron [12]. The reflectron setting of a TOF analyzer uses an electrostatic field to reflect the ion beam towards the detector (Figure 3.4a). The more energetic ions penetrate deeper into the reflectron and take a slightly longer path to the detector. Less energetic ions of the same charge and mass penetrate only a short distance into the reflectron and take a shorter path to the detector. The detector is placed at the focal point, so the ions of different energies focused by the reflectron strike the detector at the same time The result of this type of measurement is a reflectron mass spectrum (see Figure 3.6).

3.3 Mass Analyzers

3.3.3 Quadrupole and Ion Trap

These types of mass analyzer despite performing differently are based on the same physical principle. Both quadrupoles and ion traps (Figure 3.4c,e) constrain ions to circular orbits under the influence of combined direct current (DC) and radiofrequency (RF) potentials. For any combination of DC and RF fields, only ions of a selected m/z follow stable orbits. The fundamental difference is that ions in a 3D QIT have virtually no component of linear translation, whereas in a linear quadrupole, made up of four parallel rods, ions travel along spiral paths, emerging to be detected or diverted into a further mass analyzer. The basic mode of measurement of both analyzers is the scanning through the possible DC and RF field combinations; IT can on top trap the ion inside of the analyzer, making the analyzer able to perform fragmentation of the selected ion. A few years ago a hybrid between the two analyzers emerged. The so-called linear ion trap (LIT) adds the component of linear translation into the LIT, thus enhancing the performance, especially in terms of capacity. This feature expands the dynamic range and the overall sensitivity and LITs have been replacing classical quadrupole trapping devices. 3.3.4 Fourier Transformation Ion Cyclotron

At a fixed magnetic field, all ions of the same m/z value have the same cyclotron frequency and move together in a coherent ion packet (Figure 3.4f). This cyclotron motion of ions is responsible for the induction of an electric current in coils surrounding the cell, m/z being determined from the cyclotron frequency that is calculated by Fourier transformation. The development of a robust instrument of such type with an external source represented a breakthrough in terms of resolving power and mass accuracy. 3.3.5 Tandem Mass Analyzers

Tandem mass spectrometry is an effective method to obtain information that leads to determination of the amino acid sequence of the peptide. The selected peptide ion is exposed to a condition inducing fragmentation and the resulting spectrum represents the amino acid composition. Based on physical characteristics, only ion trap and FT ICR analyzers are able to gain tandem mass spectra without the need of a second mass analyzer due to their trapping functionality. The ion selection, fragmentation and mass analysis take place in one space where the events are separated into specified time periods. The events can also be separated in space when more than one analyzer is coupled together. The different geometry follows the advantages of each analyzer and forms an instrument of various possibilities. The popular triple quadrupole (Q-Q-Q; Figure 3.4c) was developed a long time ago

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3 Basic Mass Spectrometric Approaches

and still has very potent usage thanks to various modes of measurement. It can be set to follow, for example, only subsets of the peptides that contain specific functional groups, such as phosphorylation or glycosylation in so-called precursor ion or neutral loss scans. In a typical experiment, the precursor or neutral loss scan detects the components of interest and then triggers a conventional MS/MS (product ion scan) to identify the amino acid sequence and localize the modification. Triple quadrupole derived instruments are also capable of detection of specific transitions between the precursor and one fragment of a given peptide, so-called multiple reaction monitoring (MRM) [13]. The selectivity resulting from two stages of analyzer combined with the high duty cycle results in quantitative analyses of unmatched sensitivity. A recent upgrade to the geometry where the last quadrupole has been replaced by a linear ion trap, forming Q-Q-LIT, strengthens the performance and enlarges the capabilities. A TOF analyzer can be mounted inside mass spectrometers as a single unit or combined in tandem either with a second TOF analyzer to form a TOF-TOF instrument (Figure 3.4b) or following quadrupole ion geometry to form a quadrupole time of flight (QqTOF) instrument (Figure 3.4d). The later two combinations produce tandem mass spectrometry data that are of high mass accuracy. The result of this type of measurement is a MS/MS mass spectrum of the selected peptide with a definite m/z mass (see Figure 3.7). The comparison of the instrument performance is potentially a controversial subject, because specification depends on the type of application, the sample analyzed and the experimental setup. The y-series of fragments (see Figure 3.8) is indicated by vertical bars, with the difference corresponding to a given amino acid residual mass. 3.3.6 Ion Detection

In an instrument that produces and transmits a continuous ion beam, the ions arriving at a detector represent an electrical current. This current can be amplified K

100

T

V

D

E

G G

E

I

A

V

IN

'

%

0

0

100 200 300 400 500 600 700 800 900 1000 1100 1200 1300

m/z

Figure 3.7 Illustrative mass spectrum of peptide fragments as measured on QqTOF mass spectrometer. NIVAIEGGEDVTK, doubly charged ion, [M+2H]2+ = 672.8545, was fragmented by collision induced dissociation.

3.4 Protein Identification x3 y3 z3

R1 O H2N

C H

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H

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H+

R4 N

C

H

H

COOH

a3 b3 c3

Figure 3.8 The nomenclature for fragment ions in a MS/MS spectrum of peptides.

and recorded (e.g., as a function of m/z in a conventional scan, or at selected m/z values in a multiple ion monitoring experiment). The first stage of amplification is usually achieved with an electron multiplier.

3.4 Protein Identification

No method or instrument exists that is capable of identifying and quantifying the components of a complex protein sample in a simple, single-step operation. Out of a bewildering multitude of techniques and instruments, two main tracks can be identified. The first is a combination of 2-DE and MS. The second track combines limited protein purification with techniques of automated MS/MS measurement, so-called shotgun proteomics. 3.4.1 Combination of 2-DE and MS

In the first track the proteins are separated by 2-DE (see Chapter 1). Selected spots are excised, digested and analyzed by MS. The proteins can be identified either by peptide mass fingerprinting (PMF) or by peptide sequencing. 3.4.2 Peptide Mass Fingerprinting

PMF is an analytical technique for protein identification [14–18]. A necessary condition of this method is the known genome of the analyzed organism. The unknown protein of interest is first experimentally cleaved into smaller peptides, whose absolute masses can be accurately measured with a mass spectrometer [19]. These masses are then in silico compared to either a database containing known protein or the gene sequences. This is achieved by using computer programs that translate the known genome of the organism into proteins, then theoretically cut the proteins into peptides and calculate the absolute masses of the peptides from

37

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3 Basic Mass Spectrometric Approaches

each protein. The software then compares the masses of the peptides of the unknown protein to the theoretical peptide masses of each protein encoded in the genome. The results are statistically analyzed to find the best match. The presence of multiple proteins in the sample can significantly complicate the analysis and potentially compromise the results. Thus the method has gained a great popularity when applied to the identification of proteins separated by two-dimensional electrophoresis. In this case the protein mixture is purified into distinct spots containing usually only one or a few proteins. 3.4.3 Peptide Sequencing (PMF)

An alternative means of protein identification not only relies on the masses of the peptides resulting from the protein digest but also utilizes tandem mass spectrometry to select a specific peptide ion in the first part of the instrument (or in the first moment of the analysis) and then the condition of the fragmentation induces the peptide ion to break into fragments. For example, during collision-induced dissociation, peptides collide with a gas within the mass spectrometer. The resulting fragment ions occurring as a result of peptide bond fragmentation (called, e.g., b-ions and y-ions) have mass differences corresponding to the residual masses of the respective amino acids. The accepted nomenclature for fragment ions was first proposed by Roepstorff and Fohlman [20] and subsequently modified by Johnson et al. [21] (see Figure 3.8). The types of fragment ions observed in a MS/MS spectrum depend on many factors, including primary sequence, the amount of internal energy, the means of energy transfer, the charge state and so on. The important feature is the fact that the tandem mass spectrum contains partial information about the amino acid sequence of the peptide. There is more than one strategy to use this experimental spectral information for peptide/protein identification [22, 23]. The strategies can be classified into three categories. 1)

Database searching, where peptide sequences are identified by correlating acquired fragment ion spectra with theoretical spectra predicted for each peptide contained in a protein sequence database. This approach follows the same principle as searching with peptide mass fingerprinting differing only in the data loaded for search.

2)

De novo sequencing is the second approach, where peptide sequences are explicitly read directly from fragment ion spectra.

3)

The third approach merges both previous possibilities and usually starts with extraction of short sequence tags of 3–5 residues, followed by error tolerant database search [24].

The database searching approach is nowadays the most popular method for largescale proteomic data and is implemented in many popular search engines such as Sequest, MASCOT or Phenyx. However, the other strategies provide attractive

3.5 Conclusion

alternatives in specific situations. The last approach has been implemented recently into search engine called ProteinPilot and is gaining popularity also for large-scale proteomic datasets. Peptide mass fingerprinting by MALDI-TOF and peptide sequencing by ESI-MS/ MS have become highly efficient at the identification of gel-separated proteins. Gel separation, however, leads typically to identification of the most abundant proteins. Incremental improvements in 2-DE technology have alleviated, but not eliminated, these and other shortcomings of the 2-DE/MS approach. 3.4.4 Shotgun Proteomics

The possibility of getting specific peptide information that can be linked to protein sequences without the need of having a purified protein led to the development of an approach called shotgun proteomics [25–27]. In this approach, the whole protein mixture in complex sample is digested; the resulting peptides are separated by electrophoretic or chromatographic principles and analyzed by tandem mass spectrometry. A number of technical issues had to be addressed before the method could be used both for the identification of protein mixtures and for quantitative proteomic experiments. First, single-dimension peptide chromatography does not provide sufficient peak capacity to separate complex peptide mixtures. Second, mass spectrometers are inherently poor quantitative devices. Third, the amount of data collected by the method is huge and its analysis daunting. Substantial progress has been achieved in each of these areas, resulting in the emergence of increasingly robust and productive platforms. To provide more peak capacity, various combinations of protein and peptide separation schemes have been explored. Twodimensional or three-dimensional chromatographic separation of peptide mixtures generated by tryptic digestion of protein sample is probably the most popular at present. Several studies suggest that, in principle, these methods are capable of detecting proteins of very low abundance, although considerable effort is required and a sufficient amount of starting protein sample must be available.

3.5 Conclusion

The primary technique employed for the identification of peptides and proteins from biological sources is mass spectrometry. The instrumentation of mass spectrometry has seen incredible growth over the past 25 years and its sensitivity has increased approximately fivefold every three years [28]. The recent development of a novel mass spectrometer (Orbitrap) and new dissociation methods such as electron transfer dissociation (ETD) has made possible the new means of proteomic application. Although bottom-up proteomics (analysis of enzymatically produced peptides) remains the workhorse for proteomic analysis, middle-down and topdown strategies (analysis of longer peptides and intact proteins, respectively)

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should allow more complete characterization of protein isoforms and posttranslational modifications.

Acknowledgments

This work was financially supported by the Ministry of Education, Youth and Sport, Czech Republic (ME08105), and the Ministry of Defence, Czech Republic (FVZ0000604).

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Yoshida, Y., and Yoshida, T. (1988) Protein and polymer analyses up to m/z 100 000 by laser ionization time of flight mass spectrometry. Rapid Commun. Mass. Spectrom., 2 (20), 151–153. Karas, M., Bachman, D., Bahr, U., and Hillenkamp, F. (1987) Matrix-assisted ultraviolet laser desorption of non-volatile compounds. Int. J. Mass Spectrom. Ion Process., 78, 53–68. Karas, M., and Hillenkamp, F. (1988) Laser desorption ionization of proteins with molecular masses exceeding 10 000 daltons. Anal. Chem., 60 (20), 2299–2301. Hillenkamp, F., Karas, M., Beavis, R.C., and Chait, B.T. (1991) Matrix-assisted laser desorption/ionization mass spectrometry of biopolymers. Anal. Chem., 63 (24), 1193A–1203A. Fenn, J.B., Mann, M., Meng, C.K., Wong, S.F., and Whitehouse, C.M. (1989) Electrospray ionization for mass spectrometry of large biomolecules. Science, 246, 64–71. Fenn, J.B., Mann, M., Meng, C.K., Wong, S.F., and Whitehouse, C.M. (1990) Electrospray ionization-principles and practice. Mass. Spectrom. Rev., 9 (1), 37–70. Grace, J.M., and Marijnissen, J.C.M. (1994) A review of liquid atomization by electrical means. J. Aerosol Sci., 25 (6), 1005–1019. Wilm, M., and Mann, M. (1996) Analytical properties of the nanoelectrospray ion source. Anal. Chem., 68 (1), 1–8.

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spectrometry-based proteomics. Nature, 422 (6928), 198–207. Stephens, W.E. (1946) A pulsed mass spectrometer with time dispersion. Phys. Rev., 69, 691. Brown, R.S., and Lennon, J.J. (1995) Mass resolution improvement by incorporation of pulsed ion extraction in a matrix-assisted laser desorption/ionization linear time-of-flight mass spectrometer. Anal. Chem., 67, 1998. Mamyrin, B.A., Karataev, V.I., Shmikk, D.V., and Zagulin, V.A. (1973) The mass-reflectron, a new nonmagnetic time-of-flight mass spectrometer with high resolution. Sov. Phys. JETP, 37, 45. Hiller, S., Krock, B., Cembella, A., and Luckas, B.J. (2007) Rapid detection of cyanobacterial toxins in precursor ion mode by liquid chromatography tandem mass spectrometry. Mass Spectrom., 42, 1238–1250. Pappin, D.J., Hojrup, P., and Bleasby, A.J. (1993) Rapid identification of proteins by peptide-mass fingerprinting. Curr. Biol., 3 (6), 327–332. Henzel, W.J., Billeci, T.M., Stults, J.T., Wong, S.C., Grimley, C., and Watanabe, C. (1993) Identifying proteins from two-dimensional gels by molecular mass searching of peptide fragments in protein sequence databases. Proc. Natl. Acad. Sci. U.S.A., 90 (11), 5011–5015. Mann, M., Højrup, P., and Roepstorff, P. (1993) Use of mass spectrometric

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4 Quantitative Mass Spectrometric Approaches Juraj Lenco and Vojteˇch Tambor

4.1 Introduction

Along with an expanding interest in proteomics in recent years, there has been a strong desire to develop methods permitting not only protein identification but also quantitation. Indeed, the quantitation of proteins in biological samples prepared upon different physiological states has become maybe the most important task in proteomics. Despite the progress, in mass spectrometry in particular, there is still no ideal method for protein quantitation because even the latest methods suffer from certain drawbacks. Currently, there are two main streams in quantitative proteomic: (i) the classical gel-based approach relies on protein staining in gel matrices, (ii) the second one, known as shotgun proteomics, employs mass spectrometry as a major tool for acquiring quantitative information. The latter utilizes mainly incorporation of stable isotopes into proteins or peptides, which are subsequently analyzed by mass spectrometry. However, one can take also advantage of label-free methods for shotgun proteomics. 4.1.1 Gel-Based Quantitative Proteomic Methods

In the gel-based approach, proteins are separated either by 1D or 2D polyacrylamide gel electrophoresis (PAGE) into protein bands or protein spots, followed by their visualization. The intensity of the staining is consequently used for quantitation; however digital images must be acquired first. Specialized software tools (e.g., Melanie, PDQuest, Delta2D, Progenesis) are used in order to compare the intensities of protein bands or protein spots among the gels [1]. At present, there is a wide range of protein staining methods, differing in several aspects, for example, sensitivity, mode of detection, and compatibility with subsequent mass spectrometric (MS) analysis [2]. Conventional staining protocols include Coomassie™ Blue G-250 and R-250 dyes, or a color reaction based on silver ion reduction of ionic to metallic silver onto the protein surface. Increasingly popular fluorescent dyes (e.g., Sypro™ Ruby, Deep Purple™ formerly known as BSL3 and BSL4 Agents: Proteomics, Glycomics, and Antigenicity, First Edition. Edited by Jiri Stulik, Rudolf Toman, Patrick Butaye, Robert G. Ulrich. © 2011 Wiley-VCH Verlag GmbH & Co. KGaA. Published 2011 by Wiley-VCH Verlag GmbH & Co. KGaA.

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4 Quantitative Mass Spectrometric Approaches

Lightning Fast) offer ameliorated sensitivity and linearity for quantification, compared to classic staining agents. The most important aspect in quantitative analysis is, however, the linearity of the dynamic range. From this point of view, fluorescent dyes seem to be the most appropriate type of staining in the case of quantitative studies. Also, when considering the main drawback of 2D electrophoresis (i.e., the low gel-to-gel reproducibility), differential gel electrophoresis (DIGE) may be a method of choice for such kind of analyses. DIGE is based on covalent preelectrophoresis staining of protein samples with structurally similar Cy2, Cy3 or Cy5 fluorescent dyes. After labeling, proteins are mixed and resolved on a single gel. Since each dye has a specific excitation and emission wavelength, three different images are therefore acquired, which are subsequently easily comparable [3]. It must be stressed that the gel-based approach, more specifically 2D-PAGE, is currently the only method able to distinguish and quantify protein isoforms resulting from post-translation modifications. However, 2D-PAGE is a time- and labordemanding method and suffers from poor resolution of proteins with extreme physicochemical properties. 4.1.2 Shotgun Quantitative Proteomic Methods

The most significant difference, as compared to the gel-based approach, lies in the nature of the sample to be analyzed. Whereas in the gel-based approach the separation occurs at protein level and peptides resulting from a single protein are analyzed by mass spectrometry, in the shotgun experiments a vast mixture of peptides resulted from a digest of a complex protein sample must be separated, followed by mass spectrometric analysis. This brings specific requirements on analytical platforms, especially high-performance liquid chromatography (HPLC) or LC and tandem mass spectrometry (MSMS), resulting in a combination of various protein and peptide separation schemes and in the development of robust and productive mass spectrometric platforms. Moreover, the progress in the field of shotgun proteomics achieved during the last 10 years allowed the addition of a quantitative dimension to data acquired via LC-MS/MS instruments. Due to the wide range of physicochemical properties of peptides, their mass spectrometric analysis is not inherently quantitative. Hence, for accurate quantification it is necessary to compare individual peptides among experiments. This can be carried out in two different ways: labeled and label-free methods. In this brief review we focus on labeling methods only. 4.1.3 Labeling Methods

Most of the currently employed methods utilize the differential incorporation of stable isotopes into proteins or peptides. The most used stable isotopes are 13C, 15 N, 18O and 2D. Since they have physicochemical properties identical to their

4.1 Introduction

native counterparts 12C, 14N, 16O 1H, the peptides labeled with them also behave identically during chromatographic separation, but owing to a specific mass difference in their m/z, they can be simply recognized by a mass spectrometer. The stable isotopes may be introduced into the analyte in three different ways. 4.1.3.1 Metabolic Incorporation of Stable Isotopes Generally, in order to avoid accidental errors caused during sample preparation prior to mass spectrometric analysis, the labeled samples to be compared are recommended to be mixed as soon as possible in the proteomic workflow. From this point of view, the metabolic labeling during cell growth is the earliest possible point for introducing stable isotopes. The first work involving metabolic labeling of proteins for shotgun quantitative analysis employed 15N-enriched cell culture media. One pool of cells was grown in a medium containing natural isotope 14N, whereas the second pool was grown in a 15N-enriched medium [4]. However, an approach named stable isotope labeling with amino acids in cell culture (SILAC), which used only certain aminoacids, became much more popular. Although [1H3]-Leu and its heavy counterpart [2D3]-Leu were used in the work which introduced SILAC for the first time [5], the most commonly used isotope-coded amino acids nowadays are light and heavy lysine and arginine: [12C6]-Lys/[13C6]-L-Lys, [12C6]-Arg/[13C6]-Arg. These amino acids ensure that all tryptic peptides carry at least one specific isotope tag [6]. Besides the aforementioned versions of arginine, which both carry the natural isotope 14N, even a third channel [13C6, 15N4]-Arg may be added, permitting quantification of three different samples in one single run. As mentioned above, the main advantage of the metabolic approach lies in the level at which the samples can be mixed together. Therefore, it is possible to mix the differentially treated samples just after finishing the in vitro experiment, even without determining the protein concentration. As a result, all sources of possible quantification errors introduced during sample preparation are expelled. However, it is obvious that this approach cannot be routinely applied to in vivo experiments. One should also take into account a specific requirement linked to SILAC. Prior to the SILAC experiment, the amino acids with naturally light isotopes must be replaced by heavy amino acids in one pool of cells. This can be achieved in at least six division times in the appropriate medium. In the case of metabolic labeling in general, quantitative information is acquired from the MS spectra. As a consequence, it brings about a twofold increase (and if three channels are used even a threefold increase) in spectral complexity. Recently, a quantitative ISIS method has been introduced (isobaric SILAC with immonium ion splitting) employing metabolic labeling, which in contrast to SILAC enables quantitation after peptide fragmentation in MSMS mode, and thus does not increase the spectral complexity [7]. The method is based on isobaric isotope-coded pairs of amino acids readily producing immonium ions: leucine, isoleucine and valine. In MS mode the labeled peptides occur as the same peak, while under fragmentation in MSMS mode, light and heavy immonium ions are produced, differing in 1 amu.

45

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4 Quantitative Mass Spectrometric Approaches

4.1.3.2 Enzymatic Incorporation of Stable Isotopes Although several studies of metabolic labeling at the level of whole higher multicellular organisms have been reported, for example, Drosophila melanogaster [8], generally post-biosynthesis labeling is a more practical way for incorporating stable isotopes in such cases, especially when the samples are of human origin. The next point in the shotgun proteomics workflow suitable for labeling is the enzymatic digestion of proteins into peptides, since certain proteases, for example, trypsin, Glu-C and Lys-C, catalyze the exchange of two oxygen atoms at the C-termini of the peptides by two oxygen atoms coming from solvent water during the reaction [9]. When two protein samples to be compared are digested in H216O and H218O separately, the resulting peptides differ in 4 amu, which is sufficient to recognize peptide pairs properly by mass spectrometry [10, 11]. The most important stumbling block of this approach remains the variable incorporation of either one or two 18O atoms into the peptides. In addition, isotope envelopes of the higher m/z pairs may overlap, hence specialized software is needed in order to distinguish the isotopic contribution of the 16O-labeled peptide to the 18O-labeled peptide peak. 4.1.3.3 Chemical Incorporation of Stable Isotopes The most common way for introducing the stable isotopes is a chemical reaction. In practice, amino groups at N-termini and lysine side chains followed by thiol groups of cysteines are primarily used for this purpose. The isotope-coded affinity tags (ICAT) method represents the first chemical method ever [12]. It is based on labeling cysteine residues with tags carrying a thiol reactive part, a mass-coded part containing either eight 1H or eight 2D, followed by biotin. After ICAT labeling, the proteins are digested and peptides carrying the tags are purified on avidin resins. Thus, only peptides containing cysteine are subsequently analyzed, resulting in a significant decrease in complexity of the analyzed sample, while maintaining a high proteome coverage. This method suffers from slight shifts in retention times of light peptides in comparison to their heavy counterparts because of the high number of deuterium atoms. Therefore, second generation ICAT uses 12C and 13C instead of hydrogen isotopes [13]. Moreover, the new version allows cleavage of the biotin moiety from the tags after affinity purification, resulting in a lower mass of analyzed peptides. In contrast to the thiol groups, at least one amino group is present in each proteolytic peptide. The wide range of currently available methods aimed at labeling via amino groups thus represent an appropriate alternative for those who consider analysis of only cysteine-containing peptides unsatisfactory. Mostly, the amino group is targeted by N-hydroxysuccinimide chemistry; for example, global internal standard technology (GIST) is based on labeling mediated by Nacetoxysuccinimide [14], and isotope-coded protein label (ICPL), offering three channels, is based on labeling mediated by N-nicotinoyloxysuccinimide [15]. In most chemical techniques, the quantitative information is acquired in MS mode by comparison of heavy and light labeled peptides. As mentioned in the paragraph addressing metabolic labeling, this approach brings a higher spectral

4.2 iTRAQ Analysis of Bacterial Pathogens

complexity and permits only quantification of a limited number of samples. These drawbacks have been overcome by isobaric techniques in which relative quantification is acquired from MS/MS spectra. The isobaric tags consist of a reactive part mediating the chemical reaction, a reporter group and a balancer group. The sum of molecular weight of reporter and balancer group is constant in all the tags. Labeled peptides are initially detected as a single peak in MS spectrum. However, under fragmentation in MS/MS mode the peptides release the reporter group, producing specific signals that provide quantitative information. The first isobaric method ever was tandem mass tags (TMT) [16]. It, however, has not gained widespread application yet. In contrast, isobaric tag for relative and absolute quantitation (iTRAQ) after commercialization became very popular [17]. iTRAQ is based on labeling mediated by methylpiperazine acetic acid Nhydroxysuccinimide ester. It provides up to four different channels for quantification, and the latest version provides even eight channels [18]. Under fragmentation the tags release reporter groups detectable as peaks 114.1, 115.1, 116.1 and 117.1. This however means that a tandem mass spectrometer covering also the lower segment of the MS/MS spectra is absolutely essential for the iTRAQ analysis. Even though the reporter segment of the MS/MS spectrum was proved to be peak free, fragments not originated from iTRAQ could be detected in a limited number of spectra. Therefore, another essential requirement on tandem mass spectrometer is a resolution high enough to be able to resolve the iTRAQ reporter peaks from incidental ballast. Though most of the methods have been developed for peptide labeling, in general, the reaction may be performed at protein level as well, as shown by ICPL [15] and iTRAQ [19]. This may be advantageous, since after labeling the protein samples may be mixed and processed as one sample. Moreover, when 1D electrophoresis or isoelectric focusing is involved in the shotgun proteomics experiments, it is possible to detect protein cleavage and posttranslational modification respectively. However, one should keep in mind which amino acid is targeted by the labeling, because altered amino acids may no longer be recognized by the protease. Although chemical labeling represents the most frequently used approach for isotope coding, challenging issues typical for all chemical reactions still remain: the efficiency of the reaction and the side reactions (Table 4.1, Figure 4.1).

4.2 iTRAQ Analysis of Bacterial Pathogens

On the basis of our own experience, in this part we would like to emphasize practical aspects of the iTRAQ analysis of protein samples originating from bacterial pathogens. Though all the steps described in the protocol provided with the iTRAQ kit by the manufacturer are comprehensible and correct, they cannot cover all the challenging issues that may emerge during the workflow. The sample preparation for an iTRAQ shotgun proteomic experiment consists of several essential steps: bacterial cell disruption and protein extraction,

47

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4 Quantitative Mass Spectrometric Approaches

Table 4.1 Summary of the mentioned methods for incorporating stable isotopes into proteins/peptides.

SILAC

ISIS

16

O/18O

ICAT cICAT

GIST

ICPL

TMT

iTRAQ

Labeling

Metabolic Metabolic Enzymatic Chemical Chemical

Chemical

Chemical

Chemical

Level of labeling

Proteins

Proteins

Peptides

Proteins

Peptides

Proteins/ peptides

Peptides

Proteins/ peptides

Targeted amino acids

R, K, (L)

I, L, V

C-termini

C

N-termini, N-termini, N-termini, N-termini, K K K K

Increase in spectral complexity

Yes

No

Yes

Yes

Yes

Yes

No

No

Decrease of sample complexity

No

No

No

Yes

No

No

No

No

Number of channels

2/3

2

2

2

2

2/3

2/6

4/8

MS/MS

MS

MS

MS

MS

MS/MS

MS/MS

Mode for MS quantification

determination of protein concentration, protein digestion and peptide labeling with iTRAQ tags. It must be stressed that all the aforementioned steps must be adjusted in order to avoid possible incompatibilities that might significantly impair the whole experiment. Moreover, in the case of dangerous virulent bacterial strains, special requirements on cell lysis and sample handling must be employed in order to avoid potential contamination of the working environment. 4.2.1 Bacterial Cell Disruption and Protein Extraction

These two steps are mostly done simultaneously, because the composition of the lysis buffer is designed to both dissolve and denature proteins. The preferred lysis buffer is 8 M urea since this agent can be simply separated from proteins. Yet, one should keep in mind that samples dissolved in urea must not be heated over 37 °C since elevated temperatures cause urea to modify proteins by carbamylation. This brings about the incomplete labeling by amino groups targeting iTRAQ tags. Detergents should be avoided in lysis buffer because they may decrease the trypsin activity or the separation efficiency of HPLC. In addition, they are generally hard to remove. Nevertheless, cleavable detergents have emerged on the market recently (e.g., RapiGest from Waters [20], PPS Silent Surfactant from Protein Discovery [21] and ProteasMAX from Promega) which improve proteolytic digestion and can

4.2 iTRAQ Analysis of Bacterial Pathogens (a)

(b)

Metabolic labeling

(c)

49

Enzymatic labeling

Chemical labeling on protein level

(d) Chemical labeling on peptide level

Digest

Labeling

Digest

Digest

Labeling Digest

Tandem mass spectrometry Figure 4.1 Schematic representation of four

different methods utilized for incorporation of stable isotopes into proteins or peptides. (a) Proteins are labeled metabolically using isotope-coded aminoacids. Application of coded lysine or arginine ensures that each correctly cleaved peptide carries an isotope tag. In case of others aminoacid the number of isotope tags in peptides is not defined. (b) Trypsin digestion in H218O leads to formation of tryptic peptides with two 18O atoms at the C-terminus. The protein C-terminus is labeled as well even if this site

does not undergo the enzymatic cleavage. (c) Mostly, chemical labeling at protein level targets free amino groups, at the side chain of lysine and at the N-terminus in particular. This brings about the formation of larger tryptic peptides, as trypsin does not recognize the modified lysine anymore. In addition, not each peptide carries coding tags. (d) Chemical labeling on peptide level ensures that each peptide is labeled, however the samples to be compared are mixed together at the last possible step of the workflow.

be removed prior to HPLC separation by incubation under acidic pH or are directly degraded during the trypsin digestion. The main stumbling block of using these agents is their price. As far as bacterial cells are concerned, the best method for bacterial disruption in the authors’ hands seems to be the French pressure cell. The equipment is

50

4 Quantitative Mass Spectrometric Approaches

however quite expensive and thus it is not common in microbiological laboratories. Freeze–thaw lysis in liquid nitrogen or sonication represent good alternatives. For gram-positive bacteria, enzymatic lysis using lysozyme may be also employed. In the case of dangerous virulent bacteria the cells are recommended to be disrupted by detergent lysis either in SDS buffer or in the presence of cleavable detergents, followed by inactivation of residual bacteria by incubation at 95 °C. In general, the best way to protect the samples against native proteolysis is by supplementing the lysis buffer with protease inhibitors. However, it must be stressed that, without their removal before digestion, these might also decrease the activity of trypsin. Keeping the samples on ice until digestion and the denaturing environment itself are often sufficient to protect the samples from native proteolysis. 4.2.2 Determination of Protein Concentration

Nowadays, there is a wide range of colorimetric as well as fluorescent methods for protein determination. From the view of susceptibility to chemicals used in lysis buffer, the bicinchoninic acid assay (BCA) seems to be superior over other techniques (limit 5% SDS or 3 M urea) [22]. Thus, it is not necessary to perform protein precipitation before BCA assay, which results in more accurate results and time savings. 4.2.3 Protein Digestion

Trypsin is the most used protease to digest proteins into peptides. Prior to digestion, agents interfering with the enzymatic activity must be removed, or at least diluted to a non-interfering concentration (1–2 M urea, 0.05% SDS). For instance, SDS may be removed using gel filtration devices (e.g., Extracti-Gel D detergent removing gel from Pierce, Detergent-OUT kit from Millipore) or by lowering the SDS amount under its critical micelle concentration (0.173–0.230%) followed by ultrafiltration using a 5 kDa cutoff membrane. Although only nonprotein-bound SDS is removed, the residual concentration should not impair trypsin activity. Many protocols encourage investigators to precipitate the proteins. Unfortunately, this method brings problems with poor dissolution of the protein precipitate. In contrast to SDS, urea is easily removable by ultrafiltration or dialysis. As the trypsin digestion is followed by iTRAQ peptide labeling, the digestion buffer must not contain chemicals carrying free amino groups. Thus, instead of commonly used Tris-HCl or ammonium bicarbonate buffers, we strongly encourage investigators to perform the trypsin digestion in triethylammonium bicarbonate (TEAB) solution that ensures both a mild basic pH and compatibility with iTRAQ labeling. Prior to adding trypsin to the samples, proteins should be incubated with reducing agent in order to disrupt disulfide bonds. Dithiothreitol (DTT) or tris(2-

4.2 iTRAQ Analysis of Bacterial Pathogens

carboxyethyl)phosphine hydrochloride (TCEP) may be used for this purpose. Subsequently, free thiol groups are blocked irreversibly by iodoacetamide (IAM), or reversibly by methyl methanethiosulfonate (MMTS). 4.2.4 Peptide Labeling with iTRAQ Tags

After digestion, the peptides are ready for labeling. The drawback of N-hydroxysuccinimide chemistry is a low stability in aqueous environments. The reaction is carried out in presence of ethanol or propanol with just a moderate content of water. Providing that the digestion was performed in a large volume of aqueous buffer, the water content must be reduced in a Speed-Vac. The iTRAQ tags are allowed to react with the peptides for 60 min. Afterwards, the remaining tags are quenched by adding excess water and additionally incubating for 60 min. 4.2.5 Protocol for iTRAQ Analysis of Bacterial Proteins

The protocol described here was optimized and successfully used for the gramnegative bacterium Francisella tularensis; it can be used for other microbes, even microbes classified as BSL 3 and BSL 4 pathogens. 1)

After spindown, resuspend the bacterial cells in the lysis buffer composed of 0.1–0.3% SDS in Milli-Q water. Note: Use as low a concentration of SDS as possible, because the higher the concentration is, the more demanding is its removal.

2)

Immerse the sample tubes in boiling water bath for 5 min. Note: In the case of pathogenic bacteria, prolong this step in order to ensure the inactivation of nondisrupted cells.

3)

Spindown the samples at 14 000 g.

4)

Determine the protein concentration in the supernatant using the BCA kit (Sigma Aldrich).

5)

Dilute the samples containing 200 μg of protein 10–20 times with Milli-Q water. Note: The final concentration of SDS must be sharply under the level of the critical micelle concentration.

6)

Concentrate the samples using spin filters Amicon MWCO 3000 (Millipore) to 50 μl. This step should lead to a dramatic reduction in SDS concentration.

7) Determine the protein concentration in the concentrate using the BCA kit again. 8)

Dilute the samples containing 100 μg once with 1 M triethylammonium bicarbonate buffer pH 8.5 (Sigma Aldrich).

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4 Quantitative Mass Spectrometric Approaches

9)

Reduce the disulfide bonds with TCEP at 5 mM for 60 min at 60 °C.

10) Block free thiol groups with MMTS at 10 mM at room temperature for 10 min. 11)

Digest the proteins overnight at 37 °C using trypsin (Promega) in 1 : 50 ratio.

12) Dry the peptides in a vacuum centrifuge and redissolve them in 30 μl of 50 mM triethylammonium bicarbonate buffer, pH 8.5. 13) Modify the peptides using iTRAQ labels dissolved in 70 μl of absolute ethanol (Applied Biosystems). 14)

Stop the reaction by adding 300 μl of water. After 60 min of incubation, mix the samples in 1 : 1 : 1 : 1 ratio.

15)

Dry the mixture in a vacuum centrifuge.

16)

Reconstitute the peptides in 100 μl of mobile phase A for strong cation exchange (SCX) chromatography (50 mM KH2PO4, pH 3.0 in water). For elution of peptides use 50 mM KH2PO4, pH 3.5, 250 mM KCl. SCX chromatography allows the removal of residual SDS prior to reversed-phase HPLC and can be also used to fractionate the bacterial digest into several peptidecontaining fractions.

References 1 Berth, M., Moser, F.M., Kolbe, M., and

2

3

4

5

Bernhardt, J. (2007) The state of the art in the analysis of two-dimensional gel electrophoresis images. Appl. Microbiol. Biotechnol., 76, 1223–1243. Miller, I., Crawford, J., and Gianazza, E. (2006) Protein stains for proteomic applications: which, when, why? Proteomics, 6, 5385–5408. Unlu, M., Morgan, M.E., and Minden, J.S. (1997) Difference gel electrophoresis: a single gel method for detecting changes in protein extracts. Electrophoresis, 18, 2071–2077. Oda, Y., Huang, K., Cross, F.R., Cowburn, D., and Chait, B.T. (1999) Accurate quantitation of protein expression and site-specific phosphorylation. Proc. Natl. Acad. Sci. U.S.A., 96, 6591–6596. Ong, S.E., Blagoev, B., Kratchmarova, I., Kristensen, D.B., Steen, H., Pandey, A., and Mann, M. (2002) Stable isotope labeling by amino acids in cell culture,

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SILAC, as a simple and accurate approach to expression proteomics. Mol. Cell. Proteomics, 1, 376–386. Blagoev, B., Ong, S.E., Kratchmarova, I., and Mann, M. (2004) Temporal analysis of phosphotyrosine-dependent signaling networks by quantitative proteomics. Nat. Biotechnol., 22, 1139–1145. Colzani, M., Schutz, F., Potts, A., Waridel, P., and Quadroni, M. (2008) Relative protein quantification by isobaric SILAC with immonium ion splitting (ISIS). Mol. Cell. Proteomics, 7, 927–937. Krijgsveld, J., Ketting, R.F., Mahmoudi, T., Johansen, J., Artal-Sanz, M., Verrijzer, C.P., Plasterk, R.H., and Heck, A.J. (2003) Metabolic labeling of C. elegans and D. melanogaster for quantitative proteomics. Nat. Biotechnol., 21, 927–931. Schnolzer, M., Jedrzejewski, P., and Lehmann, W.D. (1996) Protease-catalyzed incorporation of 18O into peptide fragments and its application for protein sequencing by electrospray and matrix-

References

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16

assisted laser desorption/ionization mass spectrometry. Electrophoresis, 17, 945–953. Mirgorodskaya, O.A., Kozmin, Y.P., Titov, M.I., Korner, R., Sonksen, C.P., and Roepstorff, P. (2000) Quantitation of peptides and proteins by matrix-assisted laser desorption/ionization mass spectrometry using (18)O-labeled internal standards. Rapid Commun. Mass Spectrom., 14, 1226–1232. Heller, M., Mattou, H., Menzel, C., and Yao, X. (2003) Trypsin catalyzed 16O-to-18O exchange for comparative proteomics: tandem mass spectrometry comparison using MALDI-TOF, ESI-QTOF, and ESI-ion trap mass spectrometers. J. Am. Soc. Mass Spectrom., 14, 704–718. Gygi, S.P., Rist, B., Gerber, S.A., Turecek, F., Gelb, M.H., and Aebersold, R. (1999) Quantitative analysis of complex protein mixtures using isotope-coded affinity tags. Nat. Biotechnol., 17, 994–999. Yi, E.C., Li, X.J., Cooke, K., Lee, H., Raught, B., Page, A., Aneliunas, V., Hieter, P., Goodlett, D.R., and Aebersold, R. (2005) Increased quantitative proteome coverage with (13)C/(12)C-based, acid-cleavable isotope-coded affinity tag reagent and modified data acquisition scheme. Proteomics, 5, 380–387. Chakraborty, A., and Regnier, F.E. (2002) Global internal standard technology for comparative proteomics. J. Chromatogr. A, 949, 173–184. Schmidt, A., Kellermann, J., and Lottspeich, F. (2005) A novel strategy for quantitative proteomics using isotopecoded protein labels. Proteomics, 5, 4–15. Thompson, A., Schafer, J., Kuhn, K., Kienle, S., Schwarz, J., Schmidt, G., Neumann, T., Johnstone, R., Mohammed, A.K., and Hamon, C. (2003) Tandem mass tags: a novel quantification

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strategy for comparative analysis of complex protein mixtures by MS/MS. Anal. Chem., 75, 1895–1904. Ross, P.L., Huang, Y.N., Marchese, J.N., Williamson, B., Parker, K., Hattan, S., Khainovski, N., Pillai, S., Dey, S., Daniels, S., Purkayastha, S., Juhasz, P., Martin, S., Bartlet-Jones, M., He, F., Jacobson, A., and Pappin, D.J. (2004) Multiplexed protein quantitation in Saccharomyces cerevisiae using amine-reactive isobaric tagging reagents. Mol. Cell. Proteomics, 3, 1154–1169. Pierce, A., Unwin, R.D., Evans, C.A., Griffiths, S., Carney, L., Zhang, L., Jaworska, E., Lee, C.F., Blinco, D., Okoniewski, M.J., Miller, C.J., Bitton, D.A., Spooncer, E., and Whetton, A.D. (2007) Eight-channel iTRAQ enables comparison of the activity of 6 leukaemogenic tyrosine kinases. Mol. Cell. Proteomics, 7: 853–863. Wiese, S., Reidegeld, K.A., Meyer, H.E., and Warscheid, B. (2007) Protein labeling by iTRAQ: a new tool for quantitative mass spectrometry in proteome research. Proteomics, 7, 340–350. Ross, A.R., Lee, P.J., Smith, D.L., Langridge, J.I., Whetton, A.D., and Gaskell, S.J. (2002) Identification of proteins from two-dimensional polyacrylamide gels using a novel acid-labile surfactant. Proteomics, 2, 928–936. Norris, J.L., Porter, N.A., and Caprioli, R.M. (2003) Mass spectrometry of intracellular and membrane proteins using cleavable detergents. Anal. Chem., 75, 6642–6647. Brown, R.E., Jarvis, K.L., and Hyland, K.J. (1989) Protein measurement using bicinchoninic acid: elimination of interfering substances. Anal. Biochem., 180, 136–139.

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5 BN-PAGE of Microbial Protein Complexes Jiri Dresler and Jana Klimentova

5.1 Introduction

The genomic era has brought many challenging data for proteomics. The availability of completed genomes of many organisms enables the investigation of protein expression levels, structures and modifications. However, the analysis of protein structures alone is not sufficient for the complex knowledge about them. Natural compartmentization facilitates proteome analysis of cells, cell organelles and organelle subfractions and the protein complexes are the basis for the next level of compartmentization. Since many complex cellular processes (e.g., metabolic, developmental, regulatory pathways) are accomplished by sophisticated multiprotein machines, the investigation of protein interactions becomes far more important. This integrative view could lead to deeper insight into their physiological as well as pathologic function and cell behavior. Thus the new comprehensive study of the complexome, that is, all the proteins involved in different protein complexes, has arisen.

5.2 Methods for Studying Protein–Protein Interactions

The first widely used method to study protein–protein interactions was the twohybrid yeast system, discovered in 1989; and it became the workhorse for the analysis of protein–protein interactions in vivo [1, 2]. However, this method is limited by its accuracy and labor-intensive nature [1]. Another possibility for large-scale protein interaction analysis are protein chips [3], but technical problems (e.g., denaturation, substrate biocompatibility) must be surmounted in order to scale-up this method for high-throughput analysis. To date, these technologies have generated large interaction networks for bacteria [4], yeast [5], fruit fly [6] and nematodes [7].

BSL3 and BSL4 Agents: Proteomics, Glycomics, and Antigenicity, First Edition. Edited by Jiri Stulik, Rudolf Toman, Patrick Butaye, Robert G. Ulrich. © 2011 Wiley-VCH Verlag GmbH & Co. KGaA. Published 2011 by Wiley-VCH Verlag GmbH & Co. KGaA.

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5 BN-PAGE of Microbial Protein Complexes

Other methods to study protein–protein interactions are represented by tandem affinity purification (TAP) [8] and immunoprecipitation [9]. These complementary methods are frequently used to confirm interactions previously detected by other approaches. However, all these methods are laborious and, in addition, they suffer from false positive and/or negative results. On the contrary, blue native polyacrylamide gel electrophoresis (BN-PAGE), the method described here, is a relatively simple and sensitive method to study protein–protein interactions.

5.3 Blue Native Polyacrylamide Gel Electophoresis

BN-PAGE is a special electrophoretic approach developed by Schägger and von Jagow [10] originally used for the analysis of mitochondrial protein complexes. This method can be applied to protein complexes in the molecular weight range of 10–10 000 kDa [11]. However, a modified method using agarose instead of polyacrylamide was introduced in order to study protein complexes of approximate molecular weight greater than 1200 kDa [12]. This approach has been used in combination with other techniques to determine the oligomeric state, stoichiometry, enzymatic activity and molecular structure of various multiprotein complexes [13–15]. Since many samples can be separated in one electrophoretic run, direct comparison of protein complexes readily allows the identification of differences in their composition and stoichiometry. The conventional 2D IEF/SDS PAGE system is able to separate hundreds to thousands of proteins according to their pI and molecular weight [16]. However, hydrophobic (e.g., membrane) proteins are hardly detectable or are underrepresented by this approach [17]. This could be one of the reasons that hindered deeper analysis of the membrane proteome despite its importance for living cells [18]. BN-PAGE presents an alternative strategy to separate membrane proteins with high resolution while maintaining their enzymatic function [19]. This method is based on several common principles, including the following statements: non-denaturing conditions must be kept throughout the sample preparation and electrophoresis, mild non-ionic detergents are used for the solubilization and an anionic dye Coomassie brilliant blue G-250 (CBB G-250; Figure 5.1) is used during electrophoresis. This dye binds to protein surfaces, preferentially to aromatic residues and arginine, and the binding of a large number of negatively charged dye molecules to protein complexes facilitates their migration in BNPAGE. Moreover, the tendency of protein aggregation is thus decreased considerably [11]. After the separation of native complexes by BN-PAGE in the first dimension, these complexes can be denatured (broken down to individual subunits) and separated according to their size in the second dimension using “classical” SDS PAGE. In this approach proteins belonging to the same complex are aligned vertically in the second SDS dimension [20].

5.3 Blue Native Polyacrylamide Gel Electophoresis

O

O– O

H

S

O

N+

N

N

O S O

O– Na+

Figure 5.1 Coomassie brilliant blue G-250.

In practical proteomics the goal is to identify all proteins present in a defined functional state and to characterize their qualitative and quantitative changes in response to various environmental changes. Regarding this, BN-PAGE could be one of the candidates to standardize the first step during the sequential highresolution fractionation of the proteome [21]. 5.3.1 Sample Preparation

For BN-PAGE, protein complexes have to be extracted from the lipid phase retaining their native state. The aim is to: (i) solubilize the complexes (which is of high importance especially in membrane protein complexes) and (ii) retain their native state and keep it intact during electrophoresis [22]. Long-term storage of native protein samples is not recommended because of the danger of protein aggregation and complex dissociation. 5.3.1.1 Non-Denaturing Conditions As stated before, native conditions must be preserved during the whole sample preparation and electrophoresis. This includes: neutral pH, low salt concentration, no reducing and denaturing agent (SDS, urea), all manipulations at 4 °C, no heating and ideally no freezing, because repeated freezing and thawing of the sample may cause the formation of artificial aggregates and/or break-up of existing protein complexes, leading to false results [18].

57

58

5 BN-PAGE of Microbial Protein Complexes H

H

O O

H

O

O

H O H H

H

O

O O

O

H

O

H

O

H O

O O

O

O

H

H

O

H

O

O

O

O

O O

H

Digitonin

H O

O

O

H

H O

O

H

O

H

O

H

H

H

O

O

O O

O H

H

O O

H

H

O

H

O O H

DDM

Figure 5.2 Digitonin and DDM.

5.3.1.2 Selection of Detergent and Its Optimal Concentration In BN-PAGE only mild non-ionic detergents are used, because anionic, cationic and zwitterionic detergents typically disrupt the protein–protein interactions. Moreover, ionic detergents are more sensitive to pH, ionic strength and can interfere with charge-based analytical methods. In contrast, non-ionic detergents are often mild and less effective in disrupting protein aggregation [23]. For BN-PAGE, n-dodecyl-β-D-maltosid (DDM), digitonin, Triton X-100 and Brij96 have proven to be useful [23, 24]. Among them DDM and digitonin (Figure 5.2) are the most frequently used [25] and are good starting points for the optimization of solubilization strategy. However, correct detergent type and its concentration are determined strictly on the basis of experiments in order to maintain protein–protein interaction on the one hand and to ensure sufficient solubilization on the other hand. There is no general rule of detergent type and concentration selection optimal for every sample [26]. If the aim of the investigation is to study super complexes (of higher molecular mass), it is advisable to use milder detergent like digitonin or a lower concentration of DDM that preserve intermolecular interactions. A higher concentration or stronger detergent may be useful, when focused on particular complexes of lower molecular mass. Nevertheless, determining the right detergent concentration for the solubilization of protein sample of interest requires carrying out a dilution series with different detergent content [26]. 5.3.1.3 Membrane and Cytosolic Fraction Separation In bacterial protein samples it appeared to be useful to subfractionate membranes and cytosole first prior to solubilization because of the very different nature of these two compartments [27, 28]. After bacterial cell lysis (e.g., mechanically by high pressure in a French pressure cell), the membranes are pelleted by centrifugation at high speed (ca. 100 000 g) and consequently solubilized as described. The cytosolic fraction (the supernatant after centrifugation) can further be desalted by dialysis or on a desalting column [29] or used readily for BN-PAGE.

5.3 Blue Native Polyacrylamide Gel Electophoresis

5.3.2 1D BN-PAGE

Prior to BN-PAGE, the protein sample must be supplemented with CBB G-250 to a final concentration of ca. 0.2% (w/v) [22]. The gel composition differs from the classical Laemli system. For 1D BN-PAGE gradient gels are usually prepared in gel buffers based on Bis-Tris and amino caproic acid, whereas the electrophoresis buffers contain Bis-Tris and Tricine at pH 7.0 [30]. The cathode buffer is further supplemented by 0.02% CBB G-250. For this reason, 1D native gels immediately after the electrophoretic run are constantly blue. For the purposes of Western blotting or silver staining it is recommended to exchange the blue cathode buffer for a transparent one (without CBB G-250) after about the half-time of the electrophoretic run [31]. It is of high importance to conduct BN-PAGE at 4 °C to prevent protein complex denaturation caused by overheating. After the first dimension BN-PAGE the protein complexes are separated as bands and can be further studied by various methods. The complexes can be visualized by a variety of techniques, excised and analyzed by MS regarding that each band contains an entire complex. Their enzymatic activity can be studied. They can be transferred to a membrane and detected by immunoblotting [32]. One of the approaches is also in-gel denaturation to individual subunits and their 2D separation. 5.3.3 2D BN/SDS-PAGE

SDS electrophoresis in the second dimension is usually employed as a following method for resolving the protein complex composition and also gives molecular mass information for these subunits. Theoretically, all the proteins released from one complex should be positioned in a straight vertical line on a 2D gel [18]. Typically, the line of interest in the native gel is excised and denaturation is provided by its incubation in SDS solution containing a reducing agent (e.g., βmercaptoethanol or dithiothreitol). Alternatively, equilibration of the gel strip can also comprise alkylation (by iodoacetamide or N,N′-dimethylacrylamide). The equilibrated strip is then directly transferred onto the top of a standard SDS gel in a horizontal position [30] and surrounded by focusing gel or agarose. An alternative approach is to cut out single bands from the 1D stripe, equilibrate them individually as described and arrange them within wells of focusing gel in the same direction as they ran in the first dimension. This improves resolution, sharpens the resulting bands and reduces smearing in the second dimension [33].

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5.4 Evaluation of BN-PAGE – Staining, MS, Western Blotting

The separating gels can be used for different applications, typically staining and subsequent MS analysis or gel-blot analysis. Moreover, these gels can be used for “in gel” activity assay, for example, measuring the activity of mitochondrial enzyme complexes. 5.4.1 Staining 5.4.1.1 Silver Staining Silver staining is considered to be extremely sensitive in comparison with other techniques. The most frequently used techniques involve fast silver staining according to Schevchenko [34], permanganate [35] and ammoniac silver staining [36]. The disadvantages of silver staining are that it is time-consuming and it immobilizes proteins in the gel due to cross linking. Such “fixation” of proteins disables protein complexes from transferring to a gel-blot. The subsequent MS analysis of silver stained proteins is feasible only when they are fast silver stained and destained immediately after excision of spots/bands. However, native fast silver staining is less sensitive than ammoniac silver staining [32]. 5.4.1.2 Fluorescent Staining In BN-PAGE, labeling of proteins for high sensitivity can also be achieved before loading on 1D BN-PAGE. Fluorescent dyes CyDye (Cy2, Cy3, Cy5) bind to the protein complexes via lysine side groups. Visualization is then possible in the second dimension [37]. This approach provides the possibility to compare the protein complex composition of two or more different samples. Samples of interest are labeled after solubilization (each one by a different dye), before 1D BNPAGE they are mixed and in 1D and subsequent 2D they run together. The different protein composition is then visualized by scanning these gels under the wavelengths specific for the dyes used. However, utilization of this kind of visualization is limited to 2D because the blue color in BN-PAGE quenches fluorescence emission. During the denaturing step between BN-PAGE and SDS-PAGE, Coomassie is replaced by SDS and the blue dye is shifted to the mobility front. Therefore the visualization of proteins by CyDye labeling is favorable only on the level of protein subunits [26]. A similar problem is encountered with Sypro staining. The putative principle is the binding of a ruthenium-containing dye to SDS fixed to separated protein. Sufficient staining is thus achieved only in 2D or in 1D native gels after their long equilibration in SDS solution. 5.4.1.3 Coomassie Staining In spite of the high sensitivity of silver staining and the wide dynamic range of various fluorescent detection methods, CBB G-250 staining [38] is still the most

5.4 Evaluation of BN-PAGE – Staining, MS, Western Blotting

widely used protein detection technique for proteins separated by polyacrylamide gel electrophoresis. The advantages of this approach are low costs, naked eye visibility, mass spectrometry compatibility and the possible adaptations for fast or highly sensitive staining [32]. 5.4.2 Mass Spectrometry

Protein identification by MS can be carried out well after both the first and second dimensions [27, 37, 39]. The treatment of native 1D gels and SDS 2D gels differs. In the case of 1D native gels, the excised bands have to be denatured (usually by high concentration of urea), reduced and alkylated prior to trypsin digestion and extraction [40]. In 2D SDS gels the treatment depends on whether they were alkylated after 1D or not. The digestion of proteins and following extraction of peptide mixture is then identical. After BN-PAGE, the peptide mixtures are usually analyzed by online HPLC-MS. In online electrospray (ESI) analysis, HPLC separation before MS or MS/MS analysis improves both the quantity and quality of identified proteins. Offline ESI or matrix-assisted laser desorption ionization (MALDI) analysis is less suitable due to the fact that one band usually contains more than one protein subunit. After the second dimension SDS-PAGE, the analysis by offline ESI or MALDI is much easier and does not differ from the MS analysis of “classical” gels. 5.4.3 Western Blotting

Identification of proteins after BN- or BN/SDS-PAGE can be also accomplished by gel blot and subsequent antibody detection. However, this method has some further aspects in the non-denaturing mode that have to be taken into account. If the native gel is to be transferred onto the blot, exchange of cathode buffer after one half of the run of the electrophoresis is advisable. Coomassie blocks the hydrophobic binding sites on gel blot and affects antigen detection in a negative way [18]. Moreover, many antibodies are not able to recognize the antigen in the native structure of the protein complex. That is the reason why some antibodies are utilizable well only after SDS-PAGE, where proteins are denatured. 5.4.4 Other Methods of Visualization

Two other suitable methods of protein visualization are zinc-reverse [41] and copper-reverse [42] staining. In addition, the expression and concomitant assembly of the protein subunits of protein complexes can be studied by radiolabeling methods. Following the chronological sequence of the assembly/disassembly of synthesized complex subunits, 35S-methionine is often used [43]. Another possible approach to visualize protein complexes with enzymatic activity uses assays

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delivering colored products. Nevertheless, this method does not enable identification of one specific enzyme and therefore the use of antibody detection or mass spectrometry is inevitable for their unambiguous identification [37].

5.5 BN/SDS-PAGE of ATP Synthase of Francisella tularensis

The principle of BN- and BN/SDS-PAGE is demonstrated here on a membrane protein complex, the ATP synthase of bacterium F. tularensis. This F1F0-ATP synthase is a well described multiprotein complex, which is part of the respiratory chain and performs ATP synthesis/hydrolysis connected with the transport of protons across the membrane. The complex consists of two discrete sectors (subcomplexes), designated as F0 and F1. The F0 subcomplex is membrane-embedded and provides the pathway for the passage of protons through the membrane, down the electrochemical gradient. The F1 subcomplex is membrane-extrinsic and contains catalytic sites for ATP synthesis. In bacteria F1 consists of five subunits: alpha, beta, gamma, delta and epsilon in a stoichiometry α3β3γδε; F0 consists of subunits A, B and C in a stoichiometry AB2C9–12 [37]. The ATP synthase complex and its fragments were detected in bands on BNPAGE and in corresponding spots on SDS-PAGE. In Figure 5.3, on BN-PAGE, F1F0-ATP synthase represents one of the most intensive bands, in which all of the subunits were detected by MS analysis except for one – the delta subunit. On the second dimension gel, a vertical set of spots corresponding to this band were identified as subunits alpha, beta, gamma and B; the remaining subunits delta, epsilon, A and C were not detected again. Non-detection of the mentioned subunits could result from their low molecular mass (as in the subunit C – 10 kDa – which probably ran out of the 2D gel) and/or their low molecular ratio (as in the subunits A, delta and epsilon, that are only one molecule per supercomplex). The second band on 1D gel and also the second allied set of spots on 2D represented the released F1 subcomplex. This subcomplex seems to be further decomposed into individual subunits. In the third band depicted in Figure 5.3 the subunits alpha and beta were detected. These form together a circle where three subunits alpha alternate regularly with three subunits beta. This arrangement may lead to higher stability of their interaction in comparison with the interaction of other subunits. In lower molecular weights subunits alpha and beta were found as well, but these bands corresponded to individual subunits from the broken complexes (their position on the gel corresponded well to their respective MWs). The protein complex breakdown probably resulted from instability due to the detergent type and/or concentration. This example demonstrated that it is possible to analyze membrane protein complexes such as F1F0-ATP synthase under described conditions. However, the absence of the delta subunit on 1D and several others on 2D as well as the appearance of fragments on positions with lower MW than the entire complex shows also weak points of this method. The researcher must be cautious about reproduc-

Acknowledgment

BN-PAGE and BN/SDS-PAGE of membrane proteins of F. tularensis. Sample preparation: bacteria were cultivated in liquid medium, broken in French pressure cell, membranes were pelleted by centrifugation at

Figure 5.3

100 000 g and solubilized by 1% (w/v) digitonin. 1D is a 4–15% native gel, 2D is 12% SDS gel. The proteins were visualized by Coomassie brilliant blue G-250.

tion of his results and rather repeat the same procedure under different conditions (especially using several types and concentrations of detergents).

5.6 Conclusion

The presented method of BN-PAGE as well as BN/SDS-PAGE provides a simple complementary method for the investigation of protein–protein interactions. This method is especially suitable for the analysis of membrane protein complexes. The feasibility of this approach was demonstrated by the analysis of F1F0-ATP synthase, a typical membrane embedded supercomplex. This technology applies not only to multiprotein complexes involved in energy metabolism but also to protein complexes essential for other cellular functions.

Acknowledgment

This study was financially supported by Ministry of Education, Youth and Sports, Czech Republic (OC151).

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6 Analysis of Francisella tularensis Glycoproteins Lucie Balonova and Lenka Hernychova

6.1 Introduction to Post-Translational Modifications in Prokaryotes

Post-translational modifications (PTMs) of proteins play crucial roles in the assembly, degradation, structure, and function of expressed genes. PTMs of bacterial pathogenic proteins strongly influence the nature of interaction with the host cell system. However, little is known about the character and function of such modifications in intracellular bacteria. Glycosylation, together with phosphorylation, represent the most common posttranslational modifications of proteins. Over 50% of today’s known proteins, as well as 80% of membrane proteins, are estimated to be modified with glycans [1]. The commonly accepted theory limited the ability of organisms to glycosylate their proteins to eukaryotes. This false conclusion originated from the fact that the most frequently studied prokaryotes, such as Escherichia coli, Bacillus subtilis, and Salmonella species were identified as nonglycosylated [2–4]. However, advances in analytical technologies and genome sequencing enabled the discovery of glycosylation in prokaryotes, such as bacteria. The existence of prokaryotic glycoproteins is no longer considered to be novel and is well documented, as rapid progress has been made in the past few years [5–7]. The first report on the occurrence of glycosylation in prokaryotes already appeared in 1976 by the discovery of surface-layer glycoproteins in the gram-negative Halobacterium salinarum [8]. Despite this breakthrough, limited interest in prokaryotic glycoprotein research may have been initially caused by the fact that archeal surface-layer glycoproteins originate from nonpathogenic organisms with no medical relevance. However, intensive medical research has demonstrated that some of the prokaryotes synthesizing glycoproteins are important pathogens, including a species of Mycobacterium, Campylobacter, Streptococcus, and Neisseria. Current enhanced interest in glycoprotein discovery in bacteria can be explained by a proven correlation between the presence of glycosylation and bacterial pathogenicity [9–14]. To date, a noticeable number of membrane-associated, surfaceassociated, exoenzymes, and even secreted glycoproteins from diverse bacterial species have been characterized. BSL3 and BSL4 Agents: Proteomics, Glycomics, and Antigenicity, First Edition. Edited by Jiri Stulik, Rudolf Toman, Patrick Butaye, Robert G. Ulrich. © 2011 Wiley-VCH Verlag GmbH & Co. KGaA. Published 2011 by Wiley-VCH Verlag GmbH & Co. KGaA.

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6.2 Methodology 6.2.1 Analysis of Glycosylation

A significant breakthrough in the analysis of glycosylation has been achieved by combining chromatographic or electrophoretic separations with mass spectrometric approaches [15–17]. Over the past decade, mass spectrometry has emerged as a powerful tool for the analysis of large biomolecules, including glycoproteins. Both matrix-assisted laser desorption/ionization mass spectrometry and electrospray ionization mass spectrometry have become popular methods in the analysis of glycoproteins [18]. 6.2.1.1 Glycoproteomics General glycoproteomic approaches first involve: (i) the specific detection of putative glycoproteins or (ii) the isolation or enrichment of a glycoprotein pool.

1)

In order to determine the presence of glycosylation, the use of gel electrophoresis followed by carbohydrate-specific staining remains a highly desirable method of choice. The technique utilizes the ability of gel-based separation to resolve protein entities into separate spots that can be further analyzed individually. Currently, many carbohydrate-specific detection kits that are based on a reaction between the glycan moiety of separated glycoproteins and a fluorophore, a chromophore or a tag, are commercially available [19]. As an example, the Pro-Q Emerald glycoprotein stain (available from Molecular Probes) reacts with periodate-oxidized carbohydrate groups, creating a bright green fluorescent signal on glycoproteins. Another alternative glycosylationdetecting system is an immunoblotting-like approach utilizing a variety of lectins. Lectins comprise a group of proteins that enable not only the isolation of glycoproteins, but they also provide insight into the structure of glycan moieties due to the unique specificities toward various oligosaccharide patterns. For instance, the DIG glycan differentiation kit, available from Roche Diagnostics, utilizes five different lectins: Galanthus nivalis agglutinin, Sambucus nigra agglutinin, Maackia amurensis agglutinin, Peanut agglutinin, and Datura stramonium agglutinin. Each lectin has a different specificity towards the glycan moiety of a glycoprotein.

2)

The isolation of low-abundant glycoproteins from the highly abundant remainder of the nonglycosylated proteome is an essential step in the analysis of glycoproteins [20]. To date, several chromatographic separation techniques have been developed for this purpose. Among them, lectin affinity chromatography is best employed. The most frequently used lectins, Con A and wheat germ agglutinin, possess broad specificities towards the majority of eukaryotic glycoproteins [21, 22]. As bacterial glycosylations can be unique, they may not be recognized by either the above-mentioned lectins, which

6.2 Methodology

may possess different recognizable glycan patterns. The use of lectins, moreover, suffers from the limitation of trapping O-glycostructures. Therefore, formerly developed chemical isolation strategies, allowing the capture and isolation of the entire glycoprotein pool, regardless of the glycan structure, are desirable. Some of those strategies have been recently summarized by Bond and Kohler [23]. For instance, the hydrazide-derivatized magnetic beads have been introduced for glycoprotein enrichment. This two-step method utilizes the oxidation of cis-diol groups of carbohydrates to aldehydes with periodate described by Bobbitt [24] followed by the reaction of aldehydes with immobilized hydrazide groups to form covalent hydrazon bonds, reviewed by O’Shannessy [25]. The use of an aminophenylboronic acid (APBA) also appears to be useful for selective trapping glycoproteins. APBA covalently binds galactose, and mannose-equipped glycans containing cis-diol groups to form boronic diesters that are stable under alkaline conditions. In contrast to the hydrazide chemistry, this method enables the effective elution of the entire glycoprotein from magnetic beads under acidic conditions due to the reversible nature of the diesters [26–29]. On-gel/blot detected (i) or on-column isolated (ii) putative glycoproteins are then subjected to in-gel or in-solution proteolytic digestion, respectively. The resulting (glyco)peptides are subsequently either analyzed by mass spectrometry or, if analyzing a complex mixture, separated using nano-high-performance liquid chromatography followed by mass spectrometry as a means for the identification of putative glycoproteins. The use of mass spectrometry as an effective tool in glycoproteomics has been described in comprehensive reviews by Mechref and Novotny [18], Harvey [30], and Hitchen and Dell [31]. 6.2.1.2 Glycomics The structures of the oligosaccharide moieties of glycosylated proteins are investigated after their enzymatic or chemical release by glycomics [18]. Peptide-Nglycosidase F (PNGase F), the most commonly used enzyme to release the glycans, liberates intact N-glycans from eukaryotic peptide backbones by cleavage of the amidic bond between the terminal N-acetylglucosamine of a sugar moiety and an asparagine of a protein. As the carbohydrate–peptide linkages in bacteria are often different from those in eukaryotes, PNGase F may not be useful for this purpose. Similarly, other endoglycosidases, such as PNGase A and endoglycosidase H, may not be applicable. As a universal glycan-releasing method in the analysis of bacterial glycosylations that enables the removal of both N- and O-glycosylations [32], chemical cleavage may be generally useful. Among these chemical approaches, β-elimination has been successfully performed in eukaryotes as well as in bacteria [33]. However, the carbohydrate chains containing the unusual monosaccharide as a linker to protein moiety may not always be affected by β-elimination, as demonstrated in Campylobacter jejuni [34]. Once the glycans are released, their subsequent characterization such as sequencing and linkage analysis can be addressed [31].

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The complex mixture of released glycans has to be separated from the deglycosylated and nonglycosylated protein/peptide residues. For this purpose, various chromatographic techniques including hydrophilic interaction chromatography [35], reversed-phase liquid chromatography, size-exclusion chromatography, and HPLC on graphitized carbon [36] are widely used. Glycans are then identified by mass spectrometry. For their structural analysis, matrix-assisted laser desorption/ iozination (MALDI) has been proven useful [32]. The most widely used matrix in the analysis of neutral glycans is 2,5-dihydroxybenzoic acid (DHB). This matrix, however, is not ideal for acidic glycans as the detection limit is poor compared to neutral glycans. Also fragmentation can occur with losses of acidic groups. Hence, for the analysis of acidic glycans, 2,4,6-trihydroxyacetophenone (THAP) is a widely used matrix [37]. Measurements should be performed in both positive- and negative-ion mode when analyzing native glycans, with respect to their neutral or acidic nature (i.e., the presence of sialic acids). The other mass spectrometric technique that has the potential to be utilized in the analysis of native glycans is ESI/MS [38–40]. As a first pioneering work on that field, Duffin et al. [38] detected sialylated glycans in the negative ion mode while asialylated glycans were detected in the positive ion mode. By using tandem MS, the structures of studied oligosaccharides were investigated.

6.3 Bioinformatics

In the glycoproteomic approach, analogous to protein identification, putative glycoproteins are identified by searching the peptide masses obtained by mass spectrometry against sequence databases. In the glycomic approach, the determination of glycan structures from acquired MS spectra is achieved through the GlycoMod Tool, an ExPASy software tool of the Swiss Institute of Bioinformatics (http:// expasy.org/tools/glycomod/). This software can predict all possible oligosaccharide structures that occur on proteins from their experimentally obtained masses. The monosaccharide composition of glycans, however, should be confirmed by either exoglycosidase sequencing [41] or tandem mass spectrometry (MALDI-PSD and MALDI-CID). New software that enables us to predict the structure of glycans from the MS/MS data is available as SimGlycan (http://www.premierbiosoft.com/ glycan/index.html).

6.4 Application of Glycoproteomic Approach Utilizing ProQ-Emerald and DIG Glycan Kits to Francisella tularensis (F. tularensis)

The present study is focused on the comparative glycoproteomic analysis of three F. tularensis bacterial strains: live vaccine strain (LVS), strain FSC200, and a highly virulent strain, SCHU S4. The outermost surface of bacteria and both extra- and

6.4 ProQ-Emerald and DIG Glycan Kits to Francisella tularensis (F. tularensis)

intra-cellular membranes are considered to be glycosylated rather than cellular proteins. Moreover, the membrane-localized proteins primarily mediate many fundamental biological cellular processes including host–parasite interactions, invasiveness, cell signaling, or induction of the immune response of infected organisms. Therefore, our study is focused on the analysis of fractions enriched in membrane proteins. 6.4.1 Bacterial Cultures and Sample Preparation

Three subspecies of F. tularensis were analyzed. F. tularensis strains LVS and FSC200 were acquired from the Francisella strain collection (Sweden) and F. tularensis strain SCHU S4 was acquired from the Collection of Animal Pathogenic Microorganisms, Veterinary Research Institute (Brno, Czech Republic). Highly virulent SCHU S4 strain bacteria were grown, harvested, and lysed within a BioSafety level 3 containment facility. All strains were cultured in Chamberlain medium (12 h, 36.6 °C, 200 rpm) until the late logarithmic growth phase of bacteria. Bacterial cultures were harvested by centrifugation and pellets were washed three times with PBS, pH 7.5. 6.4.1.1 Preparation of Whole-Cell Lysates The bacteria of strain SCHU S4 were lysed by freeze–thawing repeatedly in liquid nitrogen vapors and cell debris along with undisrupted microbes were removed by centrifugation. In case of LVS and FSC200 strains, bacteria were lysed using a FrenchPress (16 000 psi). Undisrupted microbes were eliminated by centrifugation. 6.4.1.2 Preparation of Membrane-Enriched Fractions Fractions enriched in membrane proteins were prepared by sodium carbonate extraction according to method described by Molloy et al. [42]. Briefly, the supernatant was diluted with ice-cold 0.1 M sodium carbonate, pH 11. The resulting solution was gently stirred at 4 °C for 1 h. Carbonate-treated membranes were collected by ultracentrifugation at 46 000 rpm for 1 h at 4 °C. The supernatant was discarded and the membrane pellet was resuspended in ice-cold 50 mM Tris/HCl, pH 8.0, to remove contaminants, and then collected by centrifugation at 46 000 rpm for 30 min. The final membrane protein-containing pellet was solubilized in rehydration buffer for 2D electrophoresis. 6.4.2 Analysis of Glycoproteins in Fractions Enriched in Membrane Proteins 6.4.2.1 Mini Two-Dimensional Gel Electrophoresis For solubilization of sparingly soluble membrane proteins a rehydration buffer was used containing 7 M urea, 2 M thiourea, 1% (w/v) ASB-14, 4% (w/v) CHAPS, 1% (w/v) DTT, 1% Ampholytes pH 3–10 (Bio-Rad; Hercules, Calif., USA), and

71

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6 Analysis of Francisella tularensis Glycoproteins

0.5% Pharmalytes pH 8–10.5 (Amersham Biosciences; Uppsula, Sweden). Typically, proteins differing in their pI values were separated using polyacrylamide gel strips with an immobilized pH gradient pH 3–10 (GE Healthcare; Uppsala, Sweden) in the first dimension. Following IEF, the IPG strips were equilibrated in equilibration buffer containing 2% SDS, 50 mM Tris/HCl, pH 8.8, 6 M urea, 30% glycerol, and 1% DTT. This was immediately followed by a second equilibration of strip in the same solution containing 4% iodoacetamide in the place of DTT. In the second dimension, the IPG strips were embedded onto 12% homogeneous polyacrylamide gels, thus allowing protein separation according to their molecular weight. 6.4.2.2 Glycoprotein Detection Using DIG Glycan Differentiation Kit The separated proteins were transferred onto a BioTrace NT (Gelman Sciences) 0.45 μm nitrocellulose membrane and stained with the Ponceau S solution to visualize the success of protein transfer. Several lectins, Sambuccus nigra agglutinin (SNA), Peanut agglutinin (PNA), Datura stramonium agglutinin (DSA), and Maackia amurensis agglutinin (MAA), were utilized in this study for the detection of glycoproteins. Transferrin, asialofetuin, and fetuin were used as positive controls for SNA, PNA, and DSA and MAA lectins, respectively. As a negative control, recombinant FTT Igl C protein from E. coli was used. To avoid nonspecific binding, the nitrocellulose membrane was incubated in blocking solution overnight. After washing, the membrane was incubated in the digoxigenin-labeled lectin solution for 1 h. Unbound lectins were removed by washing. The lectin-retained membrane glycoproteins were then incubated with anti-digoxigenin-labeled alkaline phosphatase for 1 h. Following repeated washes, a staining solution containing the substrate NBT/BCIP was used to visualize the presence of glycoproteins. 6.4.2.3 Glycoprotein Detection Using Pro-Q Emerald 300 Glycoprotein Stain Kit In-gel separated proteins were oxidized for 30 min. After washing to remove residual periodate, the gels were incubated in Pro-Q Emerald 300 staining buffer for 2 h and consequently washed. Stained gels were visualized using a CCD camera Image station 2000R (Estman Kodak). After detection of glycoproteins, gels were stained with SYPRO Ruby protein gel stain. 6.4.2.4 Glycoprotein Identification by Mass Spectrometry Protein spots corresponding to in-gel (Pro-Q Emerald staining) or on-blot (DIG Glycan kit) detected putative glycoproteins were excised from the representative gels and were subjected to in-gel tryptic digestion. The mass spectra were recorded in reflectron mode on a 4800 MALDI-TOF/TOF mass spectrometer (Applied Biosystems) with CHCA as the matrix. Acquired data were processed using GPS Explorer™ Software ver. 3.6 (Applied Biosystems). Database searching was performed using the same software platform against the F. tularensis genome databases.

6.5 Results

6.5 Results 6.5.1 Glycoprotein Detection Using DIG Glycan Differentiation Kit

Three subspecies of F. tularensis were analyzed: the highly virulent subspecies tularensis strain SCHU S4, a less virulent subspecies holarctica strain LVS, and FSC200. We found differences in the detection of membrane-localized glycoproteins among the strains. Representative lectin-specific putative glycoproteins identified in F. tularensis strain LVS are summarized in Table 6.1. Thus, the use of lectins with different selectivities provided some insight into the type of carbohydrate residues likely to be present in the glycan moiety (Figure 6.1). 6.5.2 Glycoprotein Detection Using Pro-Q Emerald 300 Glycoprotein Stain Kit

The presence of glycoproteins was detected by carbohydrate-specific fluorescent staining. In this study, two subspecies of F. tularensis were analyzed: the less Table 6.1

Putative glycoproteins found in F. tularensis strain LVS.

Identified putative glycoprotein

Gene name

Lectin specificity

Molecular weight (kDa)

pI

Intracellular growth locus, subunit B

FTL0112

SNA

57.8

4.76

H(+)-transporting two-sector ATPase

FTH1734

SNA

55.4

4.94

Glycerophosphodiester phosphodiesterase

FTH1463

SNA, DSA, PNA, MAA

38.9

5.39

Ribose-phosphate pyrophosphokinase

FTL0949

SNA, DSA, PNA, MAA

34.8

5.68

Recombinase A protein

FTH1750

PNA, MAA

38.7

5.97

Fatty acid/phospholipid synthesis protein lsX

FTH1117

PNA

37.7

9.17

Membrane protease subunit HflC

FTH0887

PNA

34.5

9.35

Succinate dehydrogenase iron–sulfur protein

FTL1785

PNA

26.4

8.42

50S ribosomal protein L5

FTL0248

PNA

19.9

9.75

Outer membrane associated protein

FTL1328

MAA

41.3

5.59

73

74

6 Analysis of Francisella tularensis Glycoproteins

FTL0112

FTL1734 FTL0949

FTL1463

FTL0112 FTL0949

LVS Figure 6.1 SNA-specific putative glycoproteins of F. tularensis strain LVS.

FTL1096

FTL0112 FTL0325 FTL0073 FTT0583

Sypro Ruby

LVS

Figure 6.2 Representative mini 2-D gel of membrane proteins isolated from F. tularensis strain LVS with detected glycosylation.

virulent subspecies holarctica strain LVS (Figure 6.2) and the highly virulent subspecies F. tularensis strain SCHU S4 (Figure 6.3). We found differences in the detection of putative glycoproteins between the strains. Tables 6.2 and 6.3 summarize the identified putative glycoproteins.

6.6 Conclusion

Studying bacterial glycoproteins has gained importance due to the recently revealed role of these proteins in the host–pathogen interactions. Innovative proteomic and

6.6 Conclusion

FTT1103

FTT0831

Sypro Ruby

FTT0583

SCHU

Figure 6.3 Representative mini 2-D gels of membrane proteins isolated from F. tularensis

strain SCHU with detected glycoproteins.

Table 6.2

Putative glycoproteins found in F. tularensis strain LVS.

Identified putative glycoprotein

Gene name

MW (kDa)

pI

Conserved hypotetical lipoprotein OMPA family protein Intracellular growth locus, subunit B Outer membrane associated protein FopA Hypothetical membrane protein

FTL1096 FTL0325 FTL0112 FTT0583 FTL0073

38.7 46.8 58.9 41.3 27.6

5.23 6.27 4.69 5.13 4.89

Table 6.3

Putative glycoproteins found in F. tularensis strain SCHU.

Identified putative glycoprotein

Gene name

MW (kDa)

pI

Conserved hypotetical lipoprotein OMPA family protein Outer membrane associated protein FopA

FTT1103 FTT0831 FTT0583

38.7 46.8 41.3

5.23 6.27 5.13

glycomic technologies, combining separation methodology such as twodimensional gel electrophoresis and lectin affinity or carbohydrate-specific detection with mass spectrometric analysis, have provided sufficient capabilities for the identification and characterization of putative glycosylated proteins in the gramnegative pathogenic bacterium F. tularensis. In our study, the presence of glycoproteins in F. tularensis was investigated using two glycoproteomic approaches. First, a variety of lectins to detect a presence of

75

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6 Analysis of Francisella tularensis Glycoproteins

glycosylations were used. Second, the presence of glycoproteins was detected by carbohydrate-specific fluorescent staining. Thus far, the analysis of F. tularensis proteins has revealed differences in presence of membrane-associated glycoproteins among three analyzed bacterial subspecies (subsp. holarctica, strains LVS and FSC200; subsp. tularensis, strain SCHU). Further studies are planned to characterize the glycan composition and the structural elucidation of the detected proposed glycoproteins.

Acknowledgments

This work was financially supported by the Ministry of Education, Youth and Sport, Czech Republic (ME08105 and MSMT 0021627502), and the Ministry of Defence, Czech Republic (FVZ0000604).

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39 Weiskopf, A.S., Vouros, P., and Harvey,

Heck, A.J. (2008) Hydrophilic interaction liquid chromatography (HILIC) in proteomics. Anal. Bioanal. Chem., 391 (1), 151–159. 36 Ninonuevo, M., An, H., Yin, H., et al. (2005) Nanoliquid chromatography-mass spectrometry of oligosaccharides employing graphitized carbon chromatography on microchip with a high-accuracy mass analyzer. Electrophoresis, 26 (19), 3641–3649. 37 Papac, D.I., Wong, A., and Jones, A.J. (1996) Analysis of acidic oligosaccharides and glycopeptides by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry. Anal. Chem., 68 (18), 3215–3223. 38 Duffin, K.L., Welply, J.K., Huang, E., and Henion, J.D. (1992) Characterization of N-linked oligosaccharides by electrospray and tandem mass spectrometry. Anal. Chem., 64 (13), 1440–1448.

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Part Two Identification of Proteins and Glycans from Microorganisms as Candidate Molecules for Use in Detection/Diagnosis, Therapy, and Prophylaxis

81

7 Comparative Proteome Analysis of Strains with Differential Virulence Martin Hubalek and Ivona Pávková

7.1 Introduction

In comparative or quantitative proteomics the expression of proteins and their expression levels from different biological states are compared to understand various biological processes such as normal and diseased cells or tissues. It is widely used to find new diagnosis markers and to discover novel molecular targets of drugs. The number of methodologies suitable for comparative proteomics can be divided into two major categories: gel-based and gel-free methods [1, 2]. In gel-based methods, the proteins are separated by means of gel techniques, namely two-dimensional gel electrophoresis (2-DE). Commercially available software programs (e.g., Melanie, ImageMaster, PDQ) enable us to carry out an automated quantitative comparison of protein spots on 2-DE images. Today, the differential staining of gels with fluorescent dyes (difference gel electrophoresis; DIGE) is preferred to highlight differences in the spot pattern, as the protein labeling prior to running 2-DE and the addition of an internal standard eliminate gel to gel variations and reproducibility problems [3, 4]. Owing to its high resolution and the ability to separate proteins with distinct post-translational modifications, 2-DE remains a valuable method for comparative proteomic analyses. However, in spite of these advantages, it has a number of limitations and disadvantages, like the inability to detect low-abundant proteins, or proteins with extreme pI values and high molecular weight, or to separate hydrophobic membrane proteins with more than three transmembrane domains [1, 5]. To overcome the limitations of conventional 2-DE technology, gel-free proteomic approaches have been developed over the past years. For comparative proteomics, shotgun peptide sequencing, also referred to as shotgun proteomics, has been combined with stable isotope labeling techniques. Chemical labeling techniques with isotope-coded affinity tags (ICAT) and isobaric tags for relative and absolute quantitation (iTRAQ) and the metabolic method called stable isotope labeling by amino acids in cell culture (SILAC) are the most frequently used gel-free methods [6, 7].

BSL3 and BSL4 Agents: Proteomics, Glycomics, and Antigenicity, First Edition. Edited by Jiri Stulik, Rudolf Toman, Patrick Butaye, Robert G. Ulrich. © 2011 Wiley-VCH Verlag GmbH & Co. KGaA. Published 2011 by Wiley-VCH Verlag GmbH & Co. KGaA.

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7 Comparative Proteome Analysis of Strains with Differential Virulence

According to the study of Kubota et al. [1], the coverage of the whole proteome analyzed by 2-DE looks similar to that obtained using shotgun sequencing. However, the ratio of overlap of identified proteins was relatively small (35% for 2-DE; 42% for ICAT analysis). Comparative proteomics have become a very popular tool in discovering proteins in relation to the pathogenicity of bacteria by comparing the protein patterns of non- or less-virulent strains and their pathogenic counterparts. The virulence factors in a number of pathogenic bacteria such as Neisseria meningitidis, Yersinia pestis, Mycobacterium tuberculosis, Pseudomonas aeruginosa, Chlamydia and Staphylococcus aureus have been elucidated. Most of the bacterial comparative studies are performed by 2-DE combined with MS. There are only limited studies based on the shotgun sequencing [8]. In the case of Francisella tularensis we attempted to map and compare proteins across the available subspecies and isolates. First, the comparative proteomic analysis of whole-cell lysates isolated from three subspecies of F. tularensis (subspp. tularensis, holarctica, mediaasiatica) using the 2-DE approach was performed in order to identify proteins that differ among these three individual subspecies [9]. As the known virulence factors are largely membrane proteins and membraneassociated proteins that are in general lower-abundant and hydrophobic compared to the cytosolic proteins, fractions enriched for membrane-associated proteins from F. tularensis subsp. tularensis and holarctica strains of different virulence were prepared and compared [10]. Both studies led to the identification of a number of differentially expressed proteins across the selected strains.

7.2 Methods

Both studies applied the same strategy of comparison. The protein samples were separated by isoelectric focusing in the first dimension using 18 cm IPG strips with a pH gradient of either pH 3–10 or pH 6–11. In the second dimension, a 9–16% gradient SDS-PAGE was used. Proteins were visualized by sensitive ammoniacal silver staining for comparative analysis or by Coomassie G-250 for MS identifications. The gels were scanned by a CCD camera and the data were analyzed by the Melanie III package. Statistical analysis was performed. Relative spot volumes (% vol) were used for spot quantitations. Normalized data for the matched spots were analyzed by Student’s t-test. Spots with a P value ≤ 0.01 were accepted as significantly different. When a spot was present in all images, only those groups showing relative spot volume differences more than twofold were accepted. For the identification, protein spots visualized by Coomassie staining were excised, destained, and digested with trypsin. Protein identification by peptide mass fingerprinting was performed on a MALDI-TOF mass spectrometer VoyagerDE STR (Perseptive Biosystems; Framingham, Mass., USA). The translated F. tularensis open reading frames were identified using the MS-FIT algorithm of the

7.2 Methods

Protein-Prospector program. A mass accuracy of 100 ppm was applied. A successful match required a minimum of four peptides, a MOWSE score > 1000, and MALDI-TOF coverage > 25%. For proteins not identified by MALDI-TOF-MS, LC-nanoESI-MS/MS was performed on CapLC QTOF Ultima API (Waters; Manchester, UK). Data were processed using the ProteinLynx Global Server 2.1. A 100% probability of match and a minimum two unique peptides matching fragmentation spectra were required for successful protein identification. Several online available databases or programs were used for the further characterization of selected proteins: B-PSORT v. 2.0.4. (www.psort.org) for the prediction of protein localization in bacteria, LipoP 1.0 server (http://www.cbs.dtu.dk/ services/LipoP) for the prediction of lipoproteins, Interproscan (http://www.ebi. ac.uk/InterProScan), Pfam database (http://www.sanger.ac.uk/Software/Pfam), protein–protein BLAST and PSI-BLAST programs in the nr database at NCBI to search for protein homologs in other bacterial genomes (http://www.ncbi. nlm.nih.gov/BLAST). The difference between the study of whole-cell lysates and the membraneassociated protein fraction lays mainly in the sample preparation prior to IEF. In both cases the cells were disintegrated using repeated cycles of freeze–thawing in liquid nitrogen. The whole-cell lysate samples were precipitated overnight in 20% TCA in acetone (−18 °C) containing 0.2% dithiothreitol, then solubilized in IEF buffer containing 9 M urea, 4% w/v CHAPS, and 70 mM DTT. The membrane fraction was obtained by ultracentrifugation at 115 000 g for 1 h at 4 °C after treatment with ice-cold sodium carbonate (pH 11). The pellet was solubilized in rehydration buffer containing 7 M urea, 2 M thiourea, 1% (w/v) ASB-14, 1% Triton-X100, 40 mM Tris, 2 mM triphosphine. The difference in sample preparation reflects the hydrophobic property of membrane proteins that form membrane vesicles after cell lysis. The treatment with sodium carbonate was used to convert closed membrane vesicles into open sheets, concomitantly stripping loosely attached peripheral proteins [11]. The membrane proteins were then recovered by ultracentrifugation and resolved in a rehydration buffer containing a different ratio of urea and thiourea and also a detergent cocktail to help proteins enter the gel strips for isoelectric focusing. The second difference between the studies was in the scope of the selected strains: 13 different isolates of Francisella tularensis representing three F. tularensis subspp. (tularensis, mediaasiatica, holarctica) were used for comparative proteome analysis (see Table 7.1). Four strains were analyzed in a membrane-associated proteins study: the highly virulent F. tularensis subsp. tularensis strain SCHU S4, the virulent subsp. holarctica strain 130, and the two avirulent subsp. holarctica strains 2062 and LVS.

83

84

7 Comparative Proteome Analysis of Strains with Differential Virulence Table 7.1 Francisella tularensis strains included in comparative proteome analysis of whole-cell

lysates. FSC no.a)

Subspecies

Strain information

Alternative strain designation

13 33 41 199 237 35 74 200 247 257 147 148 149

tularensis tularensis tularensis tularensis tularensis holarctica holarctica holarctica holarctica holarctica mediaasiatica mediaasiatica mediaasiatica

Isolated by Eigelsbach Squirrel, CDC standard, Georgia, USA Tick, British Columbia, Canada,1935 Mite, Slovakia, 1988 Human ulcer, Ohio, 1941 Beaver, Hamilton, Montana, 1976 Hare, Sweden, 1974 Human, Ljusdal, Sweden, 1998 Human, Vosges, France, 1993 Tick, Moscow area, Russia, 1949 Miday gerbil, Kazakhstan, 1965 Ticks, Central Asia, 1982 Hare, Central Asia, 1965

FAM standard SnMF Vavenby SE-221-38 Schu-S4 B423 A SVA T7 Rem nr 3001 SVA T20 503/840 543 240 120

a)

Francisella strain collection number at Swedish defense research agency.

7.3 Results 7.3.1 Whole-Cell Lysates

The silver-stained patterns of proteins resolved along the nonlinear pH 3–10 gradients yielded about 1800 distinct spots; the basic protein patterns then encompassed approximately 500 spots that were partially overlapped with a wide pH range protein spectrum. We observed evident differences in the protein spectra of individual F. tularensis subspecies that comprised both qualitative changes (mostly due to a presence of charge variants) and quantitative changes (Table 7.2, Figure 7.1). However, there was almost no variation observed within subspecies. This was reported also by Broekhuijsen et al. [12] on the genomic level. The detected alterations in protein expression among subspecies were classified as groups of spots specifically detected in individual F. tularensis subspecies and groups of spots common for subspp. tularensis and mediaasiatica (TM), subspp. tularensis and holarctica (TH), and subspp. mediaasiatica and holarctica (MH). In total, we identified 27 protein spots either specifically present or at significantly higher abundance in subspecies tularensis strains, 22 spots in subspecies mediaasiatica strains, and 26 spots in subspecies holarctica strains. The presence of these groups of spots on 2-DE maps of F. tularensis lysates enables unambiguous discrimination of individual F. tularensis subspecies. Furthermore, 27 identified proteins occurred specifically or were at higher abundance in group TM, 19 proteins characterized group

7.3 Results Table 7.2 Summary of the whole-cell lysate comparative study of F. tularensis subspp. Groups of spots characteristic for the subspp. tularensis, mediaasiatica and holarctica (T, M, H), or common to two subspp. (TM, HM, TH) are presented. The first column lists the number of detected spots, the second column contains the number of unique protein sequences as translated from the genome. The number of spots containing the same proteins found in different position due to a different charge (charge variants) and of spots that are more abundant in given group (differentially present) are listed in the following columns. The number of unique characteristic proteins (specifically present) is listed in last column.

Subspp.

Number of spots

Number of ORFs

Charge variants

Differentially present

Uniquely present

T M H TM HM TH Total

27 22 26 27 19 9 130

21 20 24 22 15 10 81

17 12 15 15 17 9 43

7 4 3 4 0 0 16

3 6 5 8 2 1 22

kDa WCL A

kDa WCL B 1769 1369

69 54

1539

1377

35 22

75 1241

0316 0373 0896

5.5

5.8

1674

16 11

14 6.6

pI

Figure 7.1 Representative silver-stained 2-D

map of the whole cell lysate proteins from F. tularensis subsp. tularensis strain SCHU S4: separated on (WCL A) wide pH gradient 3–10

0075

1157

21

1357

4.8 5.1

0607 1181 1229

0611

32

0435

1794

1241

48

0142 0336

6.0

6.7

8.4

8.8

0327

9.2 9.6 pI

and (WCL B) basic pH gradient 6–11. The proteins are labeled by their FTT numbers (corresponding to the FTT numbers in the first column in Table 7.4).

MH and nine proteins fell into group TH encompassing spots missing or diminished in mediaasiatica strains. For a summary of protein spot comparison see Table 7.2. Each row in Table 7.2 contains detailed information about specific spots for each group. To keep the article concise only the protein spots that were found characteristic for subspecies tularensis are listed in Table 7.4.

85

86

7 Comparative Proteome Analysis of Strains with Differential Virulence

7.3.2 Membrane-Associated Proteins

For all the analyzed strains, approximately 880 distinct spots could be observed after separation on pH 3–10 nonlinear gradients and subsequent silver-staining. The basic protein separation (pH 6–11) produced approximately 480 spots, partially overlapping the wide pH range protein spectrum. The most pronounced and most interesting differences were found in the comparison between the most virulent F. tularensis subsp. tularensis strain SCHU S4 and the three other subsp. holarctica strains where both quantitative and qualitative differences in expression of specific proteins could be detected (Table 7.3). In summary, six proteins were observed uniquely for the SCHU S4 strain and three identified proteins were significantly more abundant in the SCHU S4 strain. Several proteins were also found to have different mass and charge variants on the 2-DE gel images. Among these, five proteins showed different charge and mass variants and seven additional proteins showed only an acidic or basic shift in the SCHU S4 strain compared to the subsp. holarctica strains. The expression of nine identified proteins was significantly lower in the SCHU S4 strain and the spots for six other proteins could be found only in subsp. holarctica strains (Figure 7.2).

7.4 Discussion

F. tularensis subspecies exhibit marked differences in their virulence, but they display a very close phylogenetic relationship and genomic similarity [13]. In both presented studies the aim was to find proteins that differ between the subtypes and possibly relate the findings to the virulence. The proteins specifically expressed in tularensis subspecies strains are the most noticeable as they could significantly contribute to enhanced virulence of these strains (Tables 7.4 and 7.5). With the analysis methods used in our studies, we were able to identify 27 protein spots specifically presented in whole-cell lysates and 21 protein spots specifically preTable 7.3 Differential membrane-associated proteins of F. tularensis subsp.

tularensis SCHU S4 in comparison with the subsp. holarctica strains 130, 2062 and LVS. Category

Number of differential proteins

Specifically present in SCHU S4 At higher abundance in SCHU S4 Charge and mass variants Charge variants At lower abundance in SCHU S4 Not found in SCHU S4

6 3 5 7 9 6

7.4 Discussion MP A

75

1484

MP B

69 54

48

1483

0380

0380

1103 1676

32

1591

35 0209

21

1666

1157

0373

16 11 kDa

1260

3

1346,1701

1651 0903

1359,1714

0245 0365 1357,1712

22

14 kDa

1043 0018

0503

pI

Figure 7.2 Representative silver-stained 2-D

map of the fraction enriched in membraneassociated proteins from F. tularensis subsp. tularensis strain SCHU S4: separated on wide pH gradient 3–10 (MP A) and basic pH

6

pI

11

10

gradient 6–11 (MP B). The proteins are labeled by their FTT numbers (corresponding to the FTT numbers in the first column in Table 7.5).

sented in fractions enriched for membrane-associated proteins isolated from subsp. tularensis strains. Three proteins from whole-cell lysates and six proteins from fractions enriched in membrane proteins composed a group of subsp. tularensis which specifically present spots whose counterparts in less virulent subspecies were not detected (labeled as SP in Tables 7.4 and 7.5). These proteins might be responsible for the graduated virulence of subsp. tularensis strains and might provide novel targets for vaccine development and antigens that could be used for subspecies-specific diagnosis. 4-Hydroxy-3-methylbut-2-en-1-yl diphosphate synthase is involved in a nonmevalonate terpenoid biosynthesis pathway [14]. From this point of view it is interesting to note that in vivo infection with F. tularensis leads to a significant increase in levels of Vgamma9 Vdelta2 cells within 7–18 days after the onset of disease. Powerful stimuli of these cells are nonpeptidic pyrophosphorylated molecules [15]. The FTT1157 type IV pili lipoprotein homologous to PilP proteins is believed to function as chaperone in the assembly of the outer membrane secretin, a component necessary for type IV pili biogenesis [16]. These proteins are also known to be directly linked to virulence, for example, in Pseudomonas aeruginosa, Neisseria gonorrhoeae, and other pathogens [17]. In F. tularensis the mutation of pilin building block proteins was shown to impair the ability of a subsp. holarctica strain to disseminate the infection to the spleen in mice [18]. The function and significance of the 3-hydroxyisobutyrate dehydrogenase homolog (FTT1666) is uncertain, although the unexpected signature common for serine/threonine and tyrosine protein kinases could indicate a role in a signaling pathway for this

87

88

7 Comparative Proteome Analysis of Strains with Differential Virulence

Differential proteins of subsp. tularensis from whole-cell lysate study as compared to proteins in subspp. holarctica and mediaasiatica. This table contains identification data of protein spots listed in row 1 of Table 7.2.

Table 7.4

FTTa)

Protein nameb)

MW/pIc)

pH (IPG)d)

Profilee)

0435

Carbon/nitrogen hydrolase family protein

32/5.6

3–10

SP

0607

4-Hydroxy-3-methylbut-2-en-1-yl diphosphate synthase

43/8.6

6–11

SP

1157

Type IV pili lipoprotein

20/9.0

6–11

SP

1769

ClpB protein

69/5.3

3–10

DP

1369

Transketolase

65/5.6; 64/5.7

3–10

DP, DP

0611

Beta-lactamase

32/7.4

6–11

DP

1229

Thymidylate synthase

31/8.4

6–11

DP

0327

50S ribosomal protein L23

11/9.2

6–11

DP

0142

50S ribosomal protein L10

17/8.8

6–11

DP

1539

Putative uncharacterized protein

54/5.1; 54/5.2

3–10

CV, CV

1377

3-Oxoacyl-[acyl-carrier-protein] synthase II

52/5.6

3–10

CV

1354, 1712

Intracellular growth locus, subunit C

22/5.7; 22/5.9

3–10

CV, CV

0316

Ribosome recycling factor

21/5.1

3–10

CV

0373

Nucleoside diphosphate kinase

17/5.7

3–10

CV

0896

Phosphoribosylaminoimidazole carboxylase,catalytic subunit

16/5.7

3–10

CV

1794

Heat shock protein

15/5.5; 14/5.3

3–10

CV, CV

1241

Serine hydroxymethyltransferase

48/6.2; 48/6.5; 48/6.7

3–10 6–11

CV, CV, CV

1181

Gamma-glutamyltranspeptidase

40/8.6

6–11

CV

0075

Succinate dehydrogenase putative iron sulfur subunit

30/8.6

6–11

CV

1674

6,7-Dimethyl-8-ribityllumazine synthase (Riboflavin synthase)

16/8.0

6–11

CV

0336

50 S ribosomal protein L24

12/9.1

6–11

CV

a) Loci correspond to locus tag designations for predicted coding sequences in the SCHU S4 genome sequence. b) Name of the protein. c) Theoretical molecular weight (kDa) and pI. d) pH range of IPG strip where protein was identified; if there are two strips enclosed in record, protein was found as overlapping on both 2DE maps. e) Differential profile of variable protein spots; SP – proteins specifically present in subspecies or in combination of subspecies and not detected elsewhere, CV – charge variant of protein identified in different subspecies at different position on gel, DP – differentially present spots detected at higher abundance than in other subspecies or combination of subspecies (all spots belong to the category of significantly different at P < 0.01 and minimally twofold different in value of normalized volume).

7.4 Discussion

89

Differential membrane-associated proteins of F. tularensis subsp. tularensis in comparison with the subsp. holarctica strains.

Table 7.5

FTTa)

Protein nameb)

MW/pIc)

pH (IPG)d)

Profilee)

1260

Hypothetical lipoprotein

16 042/5.79

3–10

SP

1666

3-Hydroxyisobutyrate dehydrogenase

33 478/6.59

3–10

SP

0018

Secretion protein

40 039/9.18

6–11

SP

1651

Conserved hypothetical protein

23 098/9.35

6–11

SP

0903

Hypothetical protein

19 351/9.40

6–11

SP

1157

Type IV pili lipoprotein

23 007/9.58

6–11

SP

1346, 1701

Hypothetical protein

14 503/8.41

3–10

DP

0380

NAD-specific glutamate dehydrogenase

49 108/6.49

3–10 6–11

DP

1043

FKBP-type peptidyl-prolyl cis-trans isomerase family protein

29 327/8.94

6–11

DP

1103

Conserved hypothetical lipoprotein

38 720/5.23

3–10

CV

1676

Hypothetical membrane protein

37 469/6.56

3–10

CV

1591

Lipoprotein

41 624/4.58

3–10

CV

0365

Phenol hydroxylase

27 712/5.63

3–10

CV

1484

Pyruvate dehydrogenase, E2 component

67 252/4.77

3–10

CV

1483

Dihydrolipoamide dehydrogenase

50 485/5.62

3–10

CV

0209

Periplasmic solute binding family protein

33 766/5.46

3–10

CV

0245

Universal stress protein

30 187/5.52

3–10

CV

1354, 1712

Intracellular growth locus, subunit C, IglC

22 433/5.94

3–10

CV

0503

Succinyl-CoA synthetase, subunit α

30 095/6.10

3–10

CV

0373

Nucleoside diphosphate kinase

15 527/5.94

3–10

CV

1359, 1714

Intracellular growth locus, subunit A, IglA

22 419/8.84

6–11

CV

a) Loci correspond to locus tag designations for predicted coding sequences in the SCHU S4 genome sequence. b) Name of the protein. c) Theoretical molecular weight (kDa) and pI. d) pH range of IPG strip where protein was identified; if there are two strips enclosed in record, protein was found as overlapping on both 2DE maps. e) Differential profile of variable protein spots; SP – proteins specifically present in subspecies or in combination of subspecies and not detected elsewhere; CV – charge variant of protein identified in different subspecies at different position on gel; DP – differentially present spots detected at higher abundance than in other subspecies or combination of subspecies (all spots belong to the category of significantly different at P < 0.01 and minimally twofold different in value of normalized volume).

90

7 Comparative Proteome Analysis of Strains with Differential Virulence

protein [19]. The protein encoded by FTT1651 was found to be a homolog of a group of putative heme-binding proteins and could be therefore involved in iron uptake. The secretion protein FTT0018 is homologous to the membrane fusion proteins that function as components in efflux pumps that might export substances which are toxic to the bacterium. Other subsp. tularensis-specific protein spots were found at a significantly higher amount in comparison to their counterparts detected in mediaasiatica and holarctica strains (labeled as DP in Tables 7.4 and 7.5). The beta-lactamase precursor exhibits a broad spectrum of hydrolytic activity, recognizing cephalosporins, penicillins, monobactams, and carbapenems as substrates [20], like thymidylate synthase which is necessary for intracellular growth and survival of Salmonella typhimurium in vitro in both professional phagocytes and epithelial cells [21]. The ClpB protein was found to be essential for intramacrophage growth of F. tularensis novicida [22]. A predicted lipoprotein is encoded by the two identical genes FTT1346 and FTT1701 localized in the 33.9-kb duplicated Francisella pathogenicity island [23]. The FKBP-type peptidyl-prolyl cis-trans isomerase family protein FTT1043 has a homology to a macrophage infectivity potentiator which is a virulence factor for several pathogens, including Legionella pneumophila [24]. Another 17 whole-cell lysate protein spots and 12 protein spots from fractions enriched in membrane proteins had their mass and/or charge variant counterparts in less virulent subspecies and therefore represented tularensis specific protein species (labeled as CV in Tables 7.4 and 7.5). Such heterogeneity can result from amino acid substitutions or differential post-translational protein modifications. These proteins can also contribute to graded virulence, as the existence of proteins differing in electrophoretic mobility was previously reported in comparative proteomic analyses of virulent and attenuated Mycobacterium tuberculosis strains [25] and invasive and cytotoxic strains of Pseudomonas aeruginosa [26]. Several F. tularensis proteins are related to virulence factors in other pathogens: serine hydroxymethyltransferase is upregulated during an integral response to signals eliciting curli formation. Curli are fimbrial structures expressed by Escherichia coli and Salmonella enteritidis that specifically interact with matrix proteins such as fibronectin and laminin. A simultaneous binding of fibrinolytic proteins and matrix proteins to fimbriae could provide these pathogens with both adhesive and invasive properties [27, 28]. Gamma-glutamyltranspeptidase was recently shown to play a significant role in H. pylori-mediated apoptosis [29, 30]. Nucleoside diphosphate kinase belongs to ATP-utilizing enzymes that convert external ATP, presumably effluxed from macrophages, to various adenine nucleotides, which then activate purinergic receptors such as P2Z, leading to enhanced macrophage cell death [31]. Mutation of beta subunit of riboflavin synthase abrogates fatal pleuropneumonia in swine induced by Actinobacillus pleuropneumoniae [32]. Protection against oxygen radicals mediated by peroxidase/catalase is required by intracellular pathogen Legionella pneumonia for its multiplication inside pulmonary macrophages. The lipoprotein FTT1103 has a domain common for the disulfide oxidoreductase DsbA family, which includes known virulence factors in several gram-negative bacteria, for example, Pseudomonas aeruginosa [33], Salmo-

References

nella enterica [34], Shigella flexneri [35]. The lipoprotein FTT1591 is similar to the VacJ lipoproteins, essential for virulence in Shigella flexneri [36]. The E2 component of pyruvate dehydrogenase was found to play an important role in the intracellular growth of the intracytosolic pathogen Listeria monocytogenes [37]; and the flavoprotein dihydrolipoamide dehydrogenase is known to be essential for the survival of Streptococcus pneumoniae in a host organism [38]. The two proteins IglA and IglC, which are encoded in the duplicated Francisella pathogenicity island, also differed [23]. Both proteins are required for intramacrophage microbial multiplication, which is a prerequisite for the induction of programmed host cell death. In conclusion, the methods used in the presented comparative proteome analysis enabled us to detect several differentially expressed proteins in whole-cell lysates and fractions enriched for membrane-associated proteins from the highly virulent F. tularensis subsp. tularensis strains and the less virulent subsp. holarctica and/or subsp. mediaasiatica strains. Most of the differentially expressed membraneassociated proteins were not detected in analyses of whole-cell lysates. This underlines the importance of sample prefractionation to visualize less abundant proteins. Moreover many virulence factors known from other species belong to the class of membrane-associated proteins. This facilitates the necessity to apply several methods to unravel biological processes such as pathogenesis. Proteomics has the advantage to look at the status of many proteins at once, but the methodology is still limited. Even in experiments that utilize similar principles, such as the analysis of whole-cell lysate and membrane-associated proteins by 2-DE, the results are complementary. By the number of identified proteins and the ratio of membrane proteins with more than one transmembrane domain, it is obvious that what has been seen is still just a part of the whole proteome. Possibly, an application of the shotgun approach with the involvement of an appropriate quantitation strategy such as stable isotope labeling can add unseen proteins on the list of interest.

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Francisella tularensis, the causative agent of tularemia. Nat. Genet., 37, 153–159. Cianciotto, P., and Fields, B.S. (1992) Legionella penumophila mip gene potentiates intracellular infection of protozoa and human macrophages. Proc. Natl. Acad. Sci. U.S.A., 89, 5188–5191. Mattow, J., Schaible, U.E., Schmidt, F., Hagens, K., Siejak, F., Brestrich, G., Haeselbarth, G., Muller, E.C., Jungblut, P.R., and Kaufmann, S.H. (2003) Comparative proteome analysis of culture supernatant proteins from virulent Mycobacterium tuberculosis H37Rv and attenuated M. bovis BCG Copenhagen. Electrophoresis, 24, 3405–3420. Nouwens, A.S., Willcox, M.D.P., Walsh, B.J., and Cordwell, S.J. (2002) Proteomic comparison of membrane and extracellular proteins from invasive (PAO1) and cytotoxic (6206) strains of Pseudomonas aeruginosa. Proteomics, 1, 1325–1346. Chirwa, N.T., and Herrington, M.B. (2003) CsgD, a regulator of curli and cellulose synthesis, also regulates serine hydroxymethyltransferase synthesis in Escherichia coli K-12. Microbiology, 149, 525–535. Sjobring, U., Pohl, G., and Olsen, A. (1994) Plasminogen, absorbed by Escherichia coli expressing curli or by Salmonella enteritidis expressing thin aggregative fimbriae, can be activated by simultaneously captured tissue-type plasminogen activator (t-PA). Mol. Microbiol., 14, 443–452. Busiello, I., Acquaviva, R., Di Popolo, A., Blanchard, T.G., Ricci, V., Romano, M., and Zarrilli, R. (2004) Helicobacter pylori gamma-glutamyltranspeptidase upregulates COX-2 and EGF-related peptide expression in human gastric cells. Cell. Microbiol., 6, 255–267. Shibayama, K., Kamachi, K., Nagata, N., Yagi, T., Nada, T., Doi, Y., Shibata, N., Yokoyama, K., Yamane, K., Kato, H., Iinuma, Y., and Arakawa, Y. (2003) A novel apoptosis-inducing protein from Helicobacter pylori. Mol. Microbiol., 47, 443–451.

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M., Kostal, J., Holder, I.A., and Chakrabarty, A.M. (2000) Secreted products of a nonmucoid Pseudomonas aeruginosa strain induce two modes of macrophage killing: external-ATPdependent, P2Z-receptor-mediated necrosis and ATP-independent, caspase-mediated apoptosis. Microbiology, 146, 2521–2530. Fuller, T.E., Thacker, B.J., and Mulks, M.H. (1996) A riboflavin auxotroph of Actinobacillus pleuropneumoniae is attenuated in swine. Infect. Immun., 64, 4659–4664. Ha, U.H., Wang, Y., and Jin, S. (2003) DsbA of Pseudomonas aeruginosa is essential for multiple virulence factors. Infect. Immun., 71, 1590–1595. Miki, T., Okada, N., and Danbara, H. (2004) Two periplasmic disulfide oxidoreductases, DsbA and SrgA, Target outer membrane protein SpiA, a component of the Salmonella pathogenicity island 2 type III secretion system. J. Biol. Chem., 279, 34631–34642. Yu, J. (1998) Inactivation of DsbA, but not DsbC and DsbD, affects the intracellular survival and virulence of Shigella flexneri. Infect. Immun., 66, 3909–3917. Suzuki, T., Murai, T., Fukuda, I., Tobe, T., Yoshikawa, M., and Sasakawa, C. (1994) Identification and characterization of a chromosomal virulence gene, vacJ, required for intercellular spreading of Shigella flexneri. Mol. Microbiol., 11, 31–41. O’Riordan, M., Moors, M.A., and Portnoy, D.A. (2003) Listeria intracellular growth and virulence require host-derived lipoic acid. Science, 17, 462–464. Smith, A.W., Roche, H., Trombe, M.C., Briles, D.E., and Hakansson, A. (2002) Characterization of the dihydrolipoamide dehydrogenase form Streptococcus pneumoniae and its role in pneumococcal infection. Mol. Microbiol., 44, 431–448.

93

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8 Analysis of Francisella tularensis Acetonitrile Extracts Lenka Hernychova, Martin Hubalek, and Jana Udrzalova

8.1 Introduction

Accurate and rapid detection, identification and typing of clinically relevant bacteria is very important for efficient infection disease therapy [1–4]. Moreover, the permanent threat of bioterrorism acts worldwide still represents a major security problem. National and international organizations have created rules concerning public health emergencies. Fast and easy detection and identification of biological warfare (BW) agents is extremely important. For this purpose various mass spectrometric approaches became very popular in the last several years. Matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) mass spectrometry (MS) of intact bacterial cells provides characteristic and reproducible mass spectral fingerprints containing unique biomarker profiles [5–7] that might be exploited to improve the identification and typing of gram-negative and gram-positive bacterial strains. In order to characterize these proteins in more detail electrospray ionization tandem mass spectrometry (ESI-MS/MS) has been employed [8–13]. Many different strategies for analyzing intact bacterial cells have been published [6, 8, 14]. Most of them are based on bacterial mass fingerprints obtained by linear mode MALDI-TOF MS accompanied by different biostatistical analyses [6, 15–20] or phylogenetic grouping [21]. For security reasons a cell-free acetonitrile (ACN) extraction procedure for MS analysis of BW agents has been developed [5, 7, 15, 22]. Rapid screening and characterization of bacteria has been the main objective of countless numbers of various software products and databases. They may employ an improved data analysis [23] that generates a database of microorganisms containing biomarker masses derived from ribosomal protein sequences and N-terminal Met losses [23]. Our investigations have focused on both detection and reliable identification and typing of specific F. tularensis proteins. In order to obtain unique protein peaks, we prepared cell-free ACN extracts from the bacteria and the samples were

BSL3 and BSL4 Agents: Proteomics, Glycomics, and Antigenicity, First Edition. Edited by Jiri Stulik, Rudolf Toman, Patrick Butaye, Robert G. Ulrich. © 2011 Wiley-VCH Verlag GmbH & Co. KGaA. Published 2011 by Wiley-VCH Verlag GmbH & Co. KGaA.

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8 Analysis of Francisella tularensis Acetonitrile Extracts

subjected to MALDI-TOF MS analyses. Fingerprints of the linear MS spectra and the m/z values of characteristic peaks were used for the initiation of an integrated database as an approach for the tentative recognition of F. tularensis strains/ isolates. The specific proteins were identified in the tryptic digest of the cell-free ACN extracts by MS/MS techniques.

8.2 Material and Methods 8.2.1 Materials

Sinapinic acid (SA), 2, 5-dihydroxybenzoic acid (DHB), Protein calibration mix2, and Peptide calibration mix1 were purchased from LaserBio Labs (SophiaAntipolis, France). Trifluoroacetic acid (TFA), formic acid (FA), trichloracetic acid (TCA), and Tris-HCl were obtained from Sigma-Aldrich (St. Louis, Mo., USA). Trypsin was purchased from Promega (Madison, USA) and Microcon centrifugal filter device YM-10 was obtained from Millipore (Bedford, Mass., USA). Acetonitrile (LiChrosolv quality), water (LiChrosolv quality), thiomersal, and dithiotreithol (DTT) were furnished by Merck (Darmstadt, Germany). Guanidine-HCl and EDTA were purchased from Janssen (Geel, Belgium). Sodium 2-iodoacetate and hydrogen ammonium carbonate (NH4HCO3) were obtained from Fluka (Buchs, Switzerland). 8.2.2 Microorganism

Francisella tularensis subsp. holarctica live vaccine strain (LVS) was acquired from the Francisella strain collection (Sweden). F. tularensis subsp. tularensis strain Schu S4 was acquired from the Collection of Animal Pathogenic Microorganisms, Veterinary Research Institute (Brno, Czech Republic). Highly virulent Schu S4 strain bacteria were grown, harvested and lysed within a BioSafety level 3 containment facility while bacteria of the less virulent LVS strain were prepared in a BioSafety level 2 laboratory by the same methodology as the Schu S4 strain. All strains were cultured in Chamberlain medium [24] under standard conditions until the late logarithmic growth phase of bacteria. 8.2.3 Preparation of Cell-Free Acetonitrile Extract

Bacterial cultures were harvested by centrifugation (5 000 rpm, 20 min, 4 °C) and pellets were washed two times with PBS, pH 7.5. The cellular material (5 mg) was resuspended in 1.5 ml of solution containing 70% acetonitrile, 0.5% TFA, and water. After vigorous extraction by vortexing (5 min), the cells were sedimented by

8.2 Material and Methods

centrifugation (12 000 rpm, 15 min, 10 °C) and the supernatant, ACN extract, was stored at −20 °C before MS analysis. 8.2.4 Enzymatic Digestion

The ACN extracts of F. tularensis strains LVS and Schu S4 were separately reduced, alkylated, and digested on a Microcon centrifugal device (YM-10, MWCO 10000; Millipore) as follows. The concentrated cell-free extract (5 μl) was diluted by denaturing freshly prepared buffer (300 μl) containing 6 M guanidine-HCl, 100 mM Tris-HCl, and 5 mM EDTA. The volume of the mixture was reduced on a Microcon filter (12 000 rpm, 4 °C, 1 h) to approximately 50 μl. DTT (100 μl of 100 mM) in 100 mM ammonium hydrogen carbonate was added, mixed, and incubated for 1 h at 56 °C. The volume was reduced again to approximately 50 μl and alkylated with iodoacetamide (100 μl of 300 mM) in the same solvent for 30 min at 25 °C in the dark. The sample was concentrated and washed twice with 200 μl of cleavage buffer (50 mM ammonium hydrogen carbonate, 5% ACN). Sequence grade trypsin (0.2 μg) in cleavage buffer (100 μl) was added and the proteins were digested in a thermomixer at 37 °C overnight. The peptides were recovered by spinning at 12 000 rpm for 1 h at 15 °C into a clean vial followed by washing the filter unit with 50 μl of 0.1% FA containing 30% ACN and 50 μl of 60% ACN. The peptides were vacuum-dried and reconstituted in 30 μl of sample buffer containing 0.1% FA and 2% ACN. 8.2.5 MALDI-TOF MS

A concentrated ACN extract (1 μl) was spotted on MALDI target sample plate with hydrophobic surface (2 × 96 well positions) and allowed to air-dry at room temperature. Matrix solution (1 μl) containing SA (10 mg/ml) in aqueous 30% ACN with 0.5% TFA was dropped onto each sample spot. The sample plate was inserted into the MALDI-TOF instrument after solvent evaporation. Mass spectra were acquired using a Voyager DE STR MALDI-TOF MS (Applied Biosystems; Framingham, Mass., USA) equipped with a delayed extraction and UV nitrogen laser (337 nm, 3 ns pulse width). Analyses were performed in a linear positive ion mode at accelerating voltage 25 kV, 93% grid voltage, 0.15% guide wire, extraction delay time 320 ns, and low mass gate 1000 m/z. The mass range was set from 1000 to 25 000 m/z. The instrument was calibrated before each analysis with a mixture of both Protein calibration mix1 and Protein calibration mix2. The mass accuracy for each standard was within 500 ppm of the corresponding average molecular weight. Each mass spectrum was obtained by averaging 200 laser shots. The Data Explorer program (Matrix Science) was used to view and process data files from the instrument. Processing parameters were as follows: advanced baseline correction 32, 0.5, 0.1; noise filter/smooth, Gaussian smooth at filter width 15.

97

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8 Analysis of Francisella tularensis Acetonitrile Extracts

8.2.6 LC-MS/MS

Protein identification in the acetonitrile extracts was performed on a tandem mass spectrometer coupled to a nanoscale HPLC. The extracted peptide mixture was separated on a CapLC system (Waters; USA) using precolumn concentration (Atlantis dC18, 5 μm NanoEase Trap column; Waters) and gradient elution on analytical nano-column Atlantis dC18 75 μm × 150 mm, 3 μm NanoEase at a flow rate of 250 nl/min. The gradient of buffer B (80% acetonitrile, 0.1% formic acid) consisted of a linear increase from 5 to 35% in 60 min. The column was connected to PicoTip emitters (New Objective; USA) mounted into the nanospray of a Qtof Ultima API (Waters; UK). Data acquisition was performed in a datadependent manner for the time of the separation collecting up to five MS/MS events at the same time. Data were processed by Peptideauto script of MassLynx 4.0 that provided background subtraction (polynomial order 99 and 10% below curve), smoothing (Savitzky Golay, twice, over three channels), and centroiding (top, 80%, minimal peak width at half height 4). The resulting pkl file was searched against bacterial genomes in the NCBI nr database using Phenyx 2.5. (GeneBio; Geneva, Switzerland) with the following criteria in two rounds. Round 1: fixed carbamidomethylation of Cys, variable Met oxidation, tryptic fragments with one miscleavage, parent mass tolerance 50 ppm, peptide score threshold ≥5, peptide P value ≥ 1 e–6. Round 2: fixed carbamidomethylation of Cys, variable Met oxidation, varriable Pyroglutamate of Gln, variable deamidation of Gln and Asn, tryptic fragments with two miscleavages, halved cleaved fragments allowed, parent mass tolerance 80 ppm, peptide score threshold ≥5, peptide P value ≥ 1 e–5.

8.3 Results 8.3.1 MALDI-TOF MS Analysis

The linear MALDI-TOF mass spectra of the ACN cell-free extracts from quintuple preparations were acquired in positive ion mode. The mass spectral data were normalized, baseline-corrected, and de-noised. The extraction procedures were optimized with respect to the signal to noise ratios, reproducibility, and the number of proteins extracted. Figures 8.1 and 8.2 show the representative mass spectra of F. tularensis strain LVS ACN extract and F. tularensis strain Schu ACN extract, respectively. The linear MALDI-TOF mass spectra of bacterial ACN extracts gave homogeneous and reproducible spectral profile. Moreover the different spectral profile with unique peak values characterized by their m/z was measured for each F. tularensis strain.

% Intensity

8.3 Results

100 90 80 70 60 50 40 30 1102 20 1033 1246 10 0 999.0

Voyager Spec #1=>AdvBC(32,0.5,0.1)=>SM15[BP = 9474.3, 7345] 9475

99

7345.4

8132 7464

5144

7386 6740 7546

10241 17239

3046

10293 4738 6142 7073 8188 9679 11029 5799.4

15990

10599.8

15400.2

20200.6

0 25001.0

Mass (m/z)

Figure 8.1 The mass spectrum of F. tularensis strain LVS acetonitrile extract measured in

positive linear mode MALDI-TOF mass spectrometer.

Voyager Spec #1=>BC=>SM15=>AdvBC(32,0.5,0.1)[BP = 7384.6, 18429] 7385

100

1.8E+4

90 8131

% Intensity

80 70 3251 3511

60 50 40 30 20

3335 2672 3903 1936 1409 2483

5607

10 0 999.0

10241

5772

5799.4

7259

10986 8338

12835 17187

11028 10599.8

15400.2

20200.6

0 25001.0

Mass (m/z)

The mass spectrum of F. tularensis strain Schu acetonitrile extract measured in positive linear mode MALDI-TOF mass spectrometer.

Figure 8.2

8.3.2 LC-MS/MS Analysis

In addition, bacterial ACN extracts were analyzed by a LC-MS/MS approach for detailed protein characterization. This shotgun procedure was chosen as more informative for the identification and typing of bacteria. The proteins of the ACN extract of the bacterium were cleaved with trypsin and the resulting peptides were separated by reverse-phase chromatography and analyzed by MS/MS. The experiment was repeated either with four (LVS strain) or five (Schu S4 strain) freshly prepared ACN extracts of the strains. We chose the following criteria for successful identification: protein has to be repeatedly identified in all analyzed samples, total z-score for protein has to be higher than 10, more than two identified unique peptides. Based on the MS/MS data and the highest z-score, ten representative proteins of F. tularensis strain LVS (Table 8.1) and ten representative proteins of

100

8 Analysis of Francisella tularensis Acetonitrile Extracts Table 8.1 List of selected F. tularensis strain LVS proteins identified by LC-MS/MS approach.

The proteins in the table are described by their accession number, name, mass, and number of identified unique peptides in each measurement. Accession number

Name of protein

Mass (Da)

Number of peptides

89255458 89256252 89255967 89256014 89256686 89256983 89257193 89256792 89257048 89257020

Outer membrane protein Histone-like protein HU form B Hypothetical protein FTL_0569 Hypothetical protein FTL_0617 Peptidyl-prolyl cis-trans isomerase Chaperone protein, groEL Heat shock protein Peroxidase/catalase Succinate dehydrogenase iron-sulfur protein Elongation factor Tu (EF-Tu)

19 346 9 494 19 654 16 809 10 241 57 403 16 740 81 227 26 566 43 391

6, 10, 4, 11 9, 10 7, 8 6, 10, 7, 5 10, 9, 12, 14 9, 8, 8, 7 7, 4, 6, 9 6, 7, 8, 7 12, 14, 17, 11 10, 8, 9, 8 14, 13, 13, 20

Table 8.2 List of selected F. tularensis strain Schu S4 proteins identified by LC-MS/MS

approach. The proteins in the table are described by their accession number, name, mass, and number of identified unique peptides in each measurement. Accession number

Name of protein

Mass (Da)

Number of peptides

56708414 56708483 56708764 56708500 56707529 56708524 56708705 56707839 56707643 56707307

Intracellular growth locus, subunit B Hypothetical protein FTT1441 ClpB protein NAD-dependent epimerase Glutamate dehydrogenase Pyruvate dehydrogenase, E1 component Chaperone protein, groEL Peroxidase/catalase Succinyl-CoA synthetase subunit beta Elongation factor Tu (EF-Tu)

58 869 18 507 95 929 36 378 49 108 100 228 57 429 82 501 41 542 43 405

11, 10, 17, 11, 12 11, 12, 6, 8, 6 9, 10, 11, 12, 12 4, 5, 4, 3, 3 12, 14, 11, 9, 9 5, 7, 12, 10, 5 6, 6, 5, 6, 6 15, 21, 20, 16, 19 7, 9, 10, 7, 8 22, 25, 25, 24, 19

F. tularensis strain Schu S4 (Table 8.2) were chosen from list of all proteins identified by LC-MS/MS approach. Selected proteins showed in Tables 8.1 and 8.2 represent most likely the highly expressed F. tularensis proteins presented in acetonitrile extracts. These proteins can be divided into four groups according to their localization and function: (i) membrane proteins, (ii) proteins involved in carbohydrate metabolism and posttranslation modification, (iii) proteins with oxidoreductase activity, and (iv) DNAbinding, elongation factor, and heat shock proteins. It is well known that the membrane proteins (MPs) associated with disease progression show promise as detection tools in public health and biodefense and

8.3 Results

can guide drug and vaccine designers in their quest to disrupt the ability of the microbe to infect. Due to the important role of MPs in cell adhesion, invasion, and intracellular survival of pathogens in the host, they are potential biomarkers or drug targets. Consequently, it is highly probable that the identified MPs may serve for reliable detection, identification, and typing of the bacterium. The outer membrane protein (OMP; F. tularensis protein from Table 8.1 with accession number 89255458) contains the OmpH domain. This type of protein forms in P. multocida a transmembrane porin that plays a key role as a molecular sieve, allowing the diffusion of small hydrophilic solutes through the outer membrane, and it also acts as a receptor for bacteriophages and bacteriocins. Antibodies raised against porins such as OmpH provide strong protection against P. multocida [25]. Moreover, OmpH and Skp in E. coli form a complex that acts as a periplasmic chaperone for newly synthesized OMPs and protects them from aggregation during passage through the bacterial periplasm [26, 27]. The second group forms proteins which are involved in carbohydrate metabolism and post-translation modification (F. tularensis proteins from Table 8.2 with accession numbers 56708500 and 56707643). NAD-dependent epimerase belongs to a family of proteins which utilize NAD as a cofactor. The proteins in this family use nucleotide–sugar substrates for a variety of chemical reactions [28]. One of the best studied proteins in this family of NAD-dependent epimerases/hydratases is UDP-galactose 4-epimerase which catalyzes the conversion of UDP-galactose to UDP-glucose during galactose metabolism [29]. Succinyl-CoA synthetase share a catalytic mechanism, which involves phosphorylation by ATP (or GTP) of a specific histidine residue in the active site [30]. The primary structure of this protein from E. coli has been described [31]. The third group contains proteins with oxidoreductase activity (F. tularensis proteins from Tables 8.1 and 8.2 with accession numbers 56707529, 56708524, 89256014, 56708483, 89257048). Glutamate dehydrogenase is an enzyme which reductively aminates 2-oxoglutarate to glutamate in many bacteria [32]. This enzyme plays a role in glutamate synthesis when E. coli bacterial cells are under energy restriction [33]. The pyruvate dehydrogenase complex catalyzes the overall conversion of pyruvate to acetyl-CoA and CO2. It contains multiple copies of three enzymatic components: pyruvate dehydrogenase (E1), dihydrolipoamide acetyltransferase (E2), and lipoamide dehydrogenase (E3) [34]. The pyruvate dehydrogenase component (E1) catalyzes the reductive acetylation of the E2-bound lipoyl groups. The enzyme shows high specificity for its oxo acid substrate and for the folded lipoylated lipoyl domain [35]. The gene organization of pyruvate dehydrogenase complexes was studied in various gram-negative bacteria [36]. Four genes that encode the protein subunits comprising the succinate dehydrogenase enzyme complex were characterized either in the rickettsia C. burnetii [37] or in B. subtilis [38]. Succinate dehydrogenases from bacteria and archaea using menaquinone as an electron acceptor contain two heme-B groups in the membrane-anchoring protein or proteins, located close to opposite sides of the membrane [39]. The remaining group of identified proteins presents DNA-binding, elongation factor, and heat shock proteins. Bacteria synthesize a set of small, usually basic

101

102

8 Analysis of Francisella tularensis Acetonitrile Extracts

proteins of about 90 residues that bind DNA and are known as histone-like proteins [40]. HU-type proteins were found as the DNA-binding proteins HU (F. tularensis protein from Table 8.1 with accession number 89256252) in a variety of eubacteria, cyanobacteria, and archaebacteria, and are also encoded in the chloroplast genome of some algae [41]. The exact function of these proteins is not known with certainty but they are capable of wrapping DNA and stabilizing it from denaturation under the extreme environmental conditions. DNA-binding proteins are primarily located in the cytoplasm but it appears that these proteins could also be present at the surface of bacterial cells, as the cells need to be competent for DNA uptake from the external milieu [42]. Elongation factor Tu (F. tularensis proteins with accession numbers 89257020 and 56707307) was identified in this study. Other proteome analyses confirmed that elongation factor Tu (EF-Tu) is associated with the cytoplasmic membranes of gram-positive bacteria and the outer membranes of gram-negative bacteria [43, 44]. Moreover, Barel M. et al. [45] described the interaction between F. tularensis elongation factor and the surface nucleolin of monocyte-like THP-I cells and demonstrated that bacterial ligand EF-Tu plays an important role in F. tularensis adhesion and the entry process and may therefore facilitate the invasion of host tissues [45]. The heat shock proteins groEL and ClpB (F. tularensis proteins from Tables 8.1 and 8.2 with accession numbers 89256983, 56708705, 56708764) belong among abundant bacterial proteins. The protein groEL is a “helper” molecule that is referred to as a molecular chaperone, a subfamily of which is the chaperonins. Their functions are well understood at present. The groES protein binds to the groEL protein and they prevent misfolding and promote the refolding of proteins and the proper assembly of unfolded polypeptides generated under stress conditions. It was found that the 60-kDa protein groEL is the immunodominant antigen in several bacteria (Legionella ssp., Ch. pneumoniae, S. typhi, Y. enterocolitica, F. tularensis, etc.); it plays a role in protection from oxygen radicals within infected macrophages and has the potential for inducing the immune response against unrelated bacterial species. Both proteins groEL and groES are located in the bacterial cytoplasm but can appear in the periplasmic space [46] or on the surface of bacteria [47]. The next protein ClpB embodies chaperone activity too. The E. coli ClpB protein is a member of the highly conserved Hsp100/Clp protein family. The combined action of ClpB and the DnaK, DnaJ, and GrpE chaperones leads to the activation of DNA replication [48]. Further, the ClpB protein involves the noncovalent folding, assembly, and/ or disassembly of other polypeptides or RNA molecules, including any transport and oligomerization processes they may undergo, and the refolding and reassembly of protein and RNA molecules denatured by stress.

8.4 Conclusions

Two separate but complementary methods were used for the determination of bacterial proteins in acetonitrile extracts. The first method was focused on the

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Acknowledgments

This work was financially supported by the Ministry of Education, Youth and Sport, Czech Republic (ME08105), and the Ministry of Defence, Czech Republic (FVZ0000604).

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9 Analysis of Culture Filtrate Proteins of Francisella tularensis Klara Konecna, Martin Hubalek, and Lenka Hernychova

9.1 Introduction

Secreted proteins and secretion pathways are essential for bacterial life and the pathogenesis of infections opens up possibilities of screening novel drugs for antimicrobial therapy, compounds specifically able to inhibit the secretory pathways of pathogens, target molecules for novel diagnostic approaches and immunoprotective secreted proteins for the construction of subcellular vaccines. In bacteria target molecules for secretion must be exported across the cell envelope and for the process of protein secretion, specific molecular machineries are necessary. The secreted proteins act outside of the bacterial cell, either bound to the bacterial cell surface, or freely in the extracellular milieu (host cell); and they are often implicated in the pathogenesis of infections and are involved in virulence. The cell wall of gram-negative bacteria is a double membrane complex structure, enclosing the periplasmic space. These bacteria contain numerous apparently independent systems for exporting proteins across or insertion into the inner cytoplasmic membrane and the outer lipopolysaccharide membrane. Eight translocation systems using different mechanisms and different sources of energy to catalyze the export of proteins across or insertion into the outer membranes are known in gram-negative bacteria [1]. Analysis of the fully sequenced genome of the virulent Francisella tularensis (F. tularensis) strain SCHU S4 has revealed the presence of genes encoding ATPbinding cassette systems [2], a TolC ortholog [3] and type IV pili components [4]. F. tularensis homologs to proteins encoded by the IAHP cluster (the gene cluster encoding the components of a type VI secretion system) were found within the Francisella pathogenicity island [5]. Type IV pili (Tfp) structures are complex adhesins participating in important host cell interactions; they mediate a surface motility and have been shown to be involved in biofilm formation and cell signaling [6]. Several F. tularensis genes required for Tfp expression are homologous to four genes required for type II secretion system (T2SS). The possibility that

BSL3 and BSL4 Agents: Proteomics, Glycomics, and Antigenicity, First Edition. Edited by Jiri Stulik, Rudolf Toman, Patrick Butaye, Robert G. Ulrich. © 2011 Wiley-VCH Verlag GmbH & Co. KGaA. Published 2011 by Wiley-VCH Verlag GmbH & Co. KGaA.

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9 Analysis of Culture Filtrate Proteins of Francisella tularensis

the Tfp clusters of Francisella is served in T2SS cannot be excluded. Hager’s group published the characterization of seven F. tularensis subsp. novicida proteins secreted via the type IV pilus secretion system [7]. The identification of some culture filtrate proteins isolated from another two subspecies of F. tularensis (subsp. tularensis, subsp. holarctica) was reported in a recently published study by Lee et al. [8]. In this study proteomic tools such as high-resolution 2-DE and MS/MS analysis were used for the analysis of F. tularensis culture filtrate proteins.

9.2 Materials and Methods

F. tularensis subsp. holarctica strain FSC 200 (kindly provided by Dr. Ake Forsberg, FOI Swedish Defense Research Agency, Umea, Sweden) was cultivated in chemically defined Chamberlain medium. Overnight cultures were diluted to OD600 0.10 and bacteria were grown under standard conditions till OD600 0.75. To avoid cell lysis and to maximize the protein harvest from the culture filtrate, the late log exponential growth phase was chosen. The eventual lysis was excluded after repeated determination of lactate dehydrogenase in culture filtrates (data not shown). Bacterial cells were removed by centrifugation (7300 rpm, 15 min, 24 °C) and the supernatants were vacuum filtered through a 0.2-μm pore membrane (Millipore Corporation; Bedford, Mass., USA). The filtrates were concentrated by a Centricon Plus-20 tubes membrane (Millipore). The concentrated samples were dialyzed against 40 mM Tris/HCl (pH 7.34), vacuum concentrated on an Eppendorf Vacufuge Concentrator 5301 (Eppendorf), and protein concentrations were determined by a modified bicinchoninic acid assay (Sigma-Aldrich). The culture filtrate proteins (CFPs) were purified by a ReadyPrep 2-D cleanup kit (Bio-Rad) and then solubilized in rehydration buffer for 2D electrophoresis [7 M urea, 2 M thiourea, 1% ASB14, 4% (w/v) CHAPS, 1% (w/v) DTT, 1% Ampholytes pH 3–10, 0.5% Pharmalytes pH 8–10.5]. Proteins were separated by 2D gel electrophoresis using IEF in the pH gradient 3–10 in the first dimension, followed by SDS-PAGE gradient gel electrophoresis (9–16%). Analytical 2-DE gels (for image analysis, visualized by sensitive ammoniacal silver staining) and preparative 2-DE gels (for subsequent MS analysis, visualized by Coomassie G-250) were prepared. Three silver stained gels from three independent experiments were prepared. The 2-DE gel maps were scanned by a CCD camera (Image Station 2000R, Eastman Kodak) and the data were analyzed by ImageMaster 2D Platinum 6.0 software (Uppsala, Sweden). Protein spots were excised from preparative gels, in-gel digested by trypsin and subsequently analyzed and identified by MS (for more details, see [9]). The identified open reading frame (ORF) sequences were sorted into functional categories based on the COG program [10]. The sequences were also analyzed for prediction of signal peptide presence by the program SignalP [11], localization with algorithms in PSORTb v.2.0 [12] and for the prediction of putative nonclassical secretions by the SecretomeP program [13].

9.3 Results

9.3 Results

Image analysis of culture filtrate protein profiles revealed an average of 240 protein spots on 2-DE silver staining maps (see Figure 9.1). Protein candidates for secretion were marked out from the group of identified proteins on the basis of prediction: signal peptide, extracellular or outer membrane localization and the presence of non-classically secreted proteins. The identified proteins with results from bioinformatic analysis together with the presence of immunoreactive activity are shown in Table 9.1. The presence of a signal peptide and localization in the outer bacterial membrane were predicted namely in two proteins: peroxidase/catalase FTL_1504 and pyruvate/2-oxoglutarate dehydrogenase complex FTL_1248. Other proteins (chaperone protein dnaK FTL_1191, superoxide dismutase (Fe) FTL_1791) had a predicted signal peptide and the SecretomeP score was calculated higher than 0.5 (indicative of secretion). As regards induction of antibody response, some of the identified culture proteins were previously presented, such as immunoreactive antigens [14, 15], namely: chaperone protein dnaK, FTL_ 1191, peroxidase/catalase FTL_1504, isocitrate dehyedrogenase FTL_ 0588, chaperone protein groEL FTL_1714, succinyl-CoA synthetase beta chain FTL_1553 and glyceraldehyde-3phosphate dehydrogenase FTL_1146 (see Table 9.1).

MW (kDa)

67

3 1 2 45 70 -

8

9

60 11

50 -

10 12

30 -

13

14

15

20 -

16

17

10 4.7

5.1

5.5

5.8

6.1

pI

Figure 9.1 The representative profile of culture filtrate proteins of F. tularensis strain FSC200.

Silver stained 9–16% gel, pH 3–10 gradient IPG strip. Black arrows denote identified protein spots.

109

ORF number

FTL_1191

FTL_1504

FTL_0588

FTL_1714

FTL_1490

1

2,3,4,5

6,7

8

9

2,3-bisphosphoglycerateindependent phosphoglycerate mutase

Chaperone protein groEL

Isocitrate dehydrogenase

Peroxidase/catalase

Chaperone protein dnaK

Protein name

57.6/5.83

57.4/4.96

83.5/6.51

82.5/5.37

69.3/4.88

Theoretical MW (kDa)/pI

No

No

No

Yes

No

SignalP

Psort

P

OM unknown C

C

Antibody response +

+ + +

−

0.073 860

0.106 307

0.101 530

0.940 072

0.705 830

SecretomeP

G/Carbohydrate transport and metabolism

O/Posttranslational modification, protein turnover, chaperones

C/Energy production and conversion

P/Inorganic ion transport and metabolism

O/Posttranslational modification, protein turnover, chaperones

COG

Identified culture filtrate proteins of F. tularensis strain FSC200; P – periplasmic, OM – outer membrane, C – cytoplasmic, CM – cytoplasmic membrane.

Spot number

Table 9.1

110

9 Analysis of Culture Filtrate Proteins of Francisella tularensis

FTL_1248

FTL_1553

FTL_1146

FTL_1461

FTL_1780

FTL_1791

FTL_0617

10

11

12

13

14

15

16,17

Conserved hypothetical protein

Superoxide dismutase (Fe)

Triosephosphate isomerase

Purine nucleoside phosphorylase

Glyceraldehyde-3phosphate dehydrogenase

Succinyl-CoA synthetase beta chain

Pyruvate/2-oxoglutarate dehydrogenase complex

Protein name

18.5/5.34

21.9/5.39

27.7/4.98

26.9/5.87

21.9/5.39

41.5/5.24

49.5/5.70

Theoretical MW (kDa)/pI

No

No

No

No

No

No

Yes

SignalP

Psort

CM, P C C

Unknown Unknown Unknown C

Antibody response − + +

− − − −

0.239 914

0.893 256

0.069 773

0.162 984

0.300 729

0.053 738

0.066 402

SecretomeP

P/Inorganic ion transport and metabolism

P/Inorganic ion transport and metabolism

G/Carbohydrate transport and metabolism

F/Nucleotide transport and metabolism

G/Carbohydrate transport and metabolism

C/Energy production and conversion

C/Energy production and conversion

COG

SignalP – Prediction of signal peptide; Psort – Prediciton of cellular localization; SecretomeP – Prediction of non-classically secreted proteins (a score above 0.5 is considered indicative of secretion, signal peptide is impaired in score); COG – Prediction of functional category.

ORF number

Spot number

9.3 Results 111

112

9 Analysis of Culture Filtrate Proteins of Francisella tularensis

9.4 Discussion

One of the key roles in the survival ability of microbes within a hostile niche involves secreted proteins which are able to modulate the host cell responses. The extracellular presence of proteins can be induced by active secretion, including the formation of vesicles or by other mechanisms, for example, leakage during bacterial division or lysis/autolysis. This study introduces a proteomic procedure to enable the detection and identification of bacterial culture filtrate proteins, among which could be found candidates for real secreted proteins. The selected secreted proteins can help with the explanation of F. tularensis virulence. Protein candidates for secretion can be marked out from the group of extracelullarly localized proteins on the basis of several factors, such as prediction of signal peptide (secretion via sec dependent pathways), prediction of extracellular or outer membrane localization, or on the basis of homology with well characterized secreted proteins in other bacteria. However, it is difficult to distinguish between true secreted proteins and the proteins released from the cell by other means. Based on the bioinformatic analysis, some proteins from the group of 12 identified Francisella proteins could be designated as the most significant candidates for secretion, namely: chaperone protein dnaK FTL_1191, peroxidase/catalase FTL_1504 and superoxide dismutase (Fe) FTL_1791. Identified peroxidase/catalase together with superoxide dismutase (Fe) are involved in scavenging/detoxification of host-derived reactive oxygen species (ROS). This defense bacterial mechanism seems to be especially critical for intracellular replication and survival in a hostile niche inside host cells. Peroxidase/catalase enzyme is also released in the extracellular space in another bacteria, such as Mycobacterium tuberculosis [16], Helicobacter pylori [17] or Bacillus sp. 13 [18]. Despite the absence of a predicted signal peptide, superoxide dismutase was also found localized extracellularly in some bacterial pathogens [13]. The chaperone protein dnaK belongs to the heat shock proteins. Chaperone proteins are in general cytoplasmic proteins, but recent studies suggest that they can be also membrane associated or secreted [17, 19] in other bacteria. Similar to superoxide dismutase, this protein was predicted to be a non-classically secreted protein. It is interesting to note that 6 out of 12 identified proteins induced a strong antibody response in naturally infected individuals and/or experimentally infected mice. The identification of immunoreactive proteins may also provide candidates for use in a subunit vaccine with protective potential. Some identified proteins were predicted to have a cytoplasmic localization. This fact raises the question as to why these proteins with a predicted cytoplasmic localization leak into cultivation medium and why other abundant cytoplasmic proteins stay inside the bacterial cell (a comparative analysis with whole-cell lysate was done – data not shown). This and other questions will be under further scientific interest.

References

Acknowledgments

This work was financially supported by the Ministry of Defence, Czech Republic (FVZ0000604), and NATO, collaboration linkage grant LST. CLG. 979934.

References 1 Baier, M.H., Jr. (2006) Protein secretion

2

3

4

5

6

7

and membrane insertion systems in gram-negative bacteria. J. Membr. Biol., 214 (2), 75–90. Atkins, S.H., Dassa, E., Walker, N.J., Griffin, K.F., Harland, D.N., Taylor, R.R., Duffield, M.L., and Titball, R.W. (2006) The identification and evaluation of ATP binding cassette systems in the intracellular bacterium Francisella tularensis. Res. Microbiol., 157 (6), 593. Gil, H., Platz, G.J., Forestal, C.A., Monfett, M., Bakshi, C.S., Sellati, T.J., Furie, M.B., Benach, J.L., and Thanassi, D.G. (2006) Deletion of TolC orthologs in Francisella tularensis identifies roles in multidrug resistance and virulence. Proc. Natl. Acad. Sci. U.S.A., 103 (34), 12897. Forslund, A.L., Kuoppa, K., Svensson, K., Salomonsson, E., Johansson, A., Byström, M., Oyston, P.C.F., Michell, S.L., Titball, R.W., Noppa, L., Frithz-Lindsten, E., Forsman, M., and Forsberg, A. (2006) Direct repeat-mediated deletion of a type IV pilin gene results in major virulence attenuation of Francisella tularensis. Mol. Microbiol., 59 (6), 1818. de Bruin, O.M., Ludu, J.S., and Nano, F.E. (2007) The Francisella Pathogenicity Island Protein IglA localizes to the bacterial cytoplasm and is needed for intracellular growth. BMC Microbiol., 7, 1. Sauvonnet, N., Vignon, G., Pugsley, A.P., and Gounon, P. (2000) Pilus formation and protein secretion by the same machinery in Escherichia coli. EMBO J., 19 (10), 2221. Hager, A.J., Bolton, D.L., Pelletier, M.R., Brittnacher, M.J., Gallagher, L.A., Kaul, R., Skerrett, S.J., Miller, S.I., and Guina, T. (2006) Type IV pili-mediated secretion modulates Francisella virulence. Mol. Microbiol., 62 (1), 227.

8 Lee, B.Y., Horwitz, M.A., and Clements,

9

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14

D.L. (2006) Identification, recombinant expression, immunolocalization in macrophages, and T-cell responsiveness of the major extracellular proteins of Francisella tularensis. Infect. Immun., 74 (7), 4002. Pavkova, I., Reichelova, M., Larsson, P., Hubalek, M., Vackova, J., Forsberg, A., and Stulik, J. (2006) Comparative proteome analysis of fractions enriched for membrane-associated proteins from Francisella tularensis subsp. tularensis and F. tularensis subsp. holarctica strains. J. Proteome Res., 5 (11), 3125. Tatusov, R.L., Fedorova, N.D., Jackson, J.D., Jacobs, A.R., Kiryutin, B., Koonin, E.V., Krylov, D.M., Mazumder, R., Mekhedov, S.L., Nikolskaya, A.N., Rao, B.S., Smirnov, S., Sverdlov, A.V., Vasudevan, S., Wolf, Y.I., Yin, J.J., and Natale, D.A. (2003) The COG database: an updated version includes eukaryotes. BMC Bioinformatics, 4, 41. Bendtsen, J.D., Nielsen, H., von Heijne, G., and Brunak, S. (2004) Improved prediction of signal peptides: SignalP 3.0. J. Mol. Biol., 340 (4), 783. Gardy, J.L., Laird, M.R., Chen, F., Rey, S., Walsh, C.J., Ester, M., and Brinkman, F.S. (2005) PSORT v.2.0: expanded prediction of bacterial protein subcellular localization and insights gained from comparative proteome analysis. Bioinformatics, 21 (5), 617. Bendtsen, J.D., Kiemer, L., Fausbøll, A., and Brunak, S. (2005) Non-classical protein secretion in bacteria. BMC Microbiol., 5, 58. Havlasova, J., Hernychova, L., Brychta, M., Hubalek, M., Lenco, J., Larsson, P., Lundqvist, M., Forsman, M., Krocova, Z., Stulik, J., and Macela, A. (2005)

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9 Analysis of Culture Filtrate Proteins of Francisella tularensis Proteomic analysis of anti-Francisella tularensis LVS antibody response in murine model of tularemia. Proteomics, 5 (8), 2090. 15 Janovska, S., Pavkova, I., Hubalek, M., Lenco, J., Macela, A., and Stulik, J. (2007) Identification of immunoreactive antigens in membrane proteins enriched fraction from Francisella tularensis LVS. Immunol. Lett., 108 (2), 151. 16 Raynaud, C., Etienne, G., Peyron, P., Lanéelle, M.A., and Daffé, M. (1998) Extracellular enzyme activities potentially involved in the pathogenicity of Mycobacterium tuberculosis. Microbiology, 144 (Pt 2), 577. 17 Vanet, A., and Labigne, A. (1998) Evidence for specific secretion rather than autolysis in the release of some Helicobacter pylori proteins. Infect. Immun., 66 (3), 1023.

18 Ogawa, J., Sulistyaningdyah, W.T., Li,

Q.S., Tanaka, H., Xie, S.X., Kano, K., Ikeda, T., and Shimizu, S. (2004) Two extracellular proteins with alkaline peroxidase activity, a novel cytochrome c and a catalase-peroxidase, from Bacillus sp. No.13. Biochim. Biophys. Acta, 1699 (1–2), 65. 19 Fossati, G., Izzo, G., Rizzi, E., Gancia, E., Modena, D., Moras, M.L., Niccolai, N., Giannozzi, E., Spiga, O., Bono, L., Marone, P., Leone, E., Mangili, F., Harding, S., Errington, N., Walters, C., Henderson, B., Roberts, M.M., Coates, A.R., Casetta, B., and Mascagni, P. (2003) Mycobacterium tuberculosis chaperonin 10 is secreted in the macrophage phagosome: is secretion due to dissociation and adoption of a partially helical structure at the membrane? J. Bacteriol., 185 (14), 4256.

115

10 Lipopolysaccharides of Coxiella burnetii: Chemical Composition and Structure, and Their Role in Diagnosis of Q Fever Rudolf Toman and Pavol Vadovicˇ

10.1 Introduction

Coxiella burnetii is a highly infectious gram-negative bacterium that causes Q fever, a zoonotic disease, capable of being transmitted from animals to humans [1]. A single organism may initiate infection. Despite the fact that C. burnetii is unable to grow or replicate outside host cells, there is a spore-like form of the bacterium that is extremely resistant to heat, pressure, desiccation, and many standard antiseptic compounds; this allows the microbe to persist in the environment for long periods under harsh conditions. This persistence, coupled with a primary mode of transmission by inhalation of infected aerosols, allows for the development of acute infection following only indirect exposure to an infected source [1]. C. burnetii fulfils all requirements for a potential biological weapon: it consistently causes disability; it can be manufactured on a large scale; it remains stable under production, storage, and transportation conditions; it can be efficiently disseminated; and consequently, it remains viable for years [2]. An easy aerosol dissemination, environmental persistence, and high infectivity [1, 2] make the bacterium a serious threat for military personnel and civilians. The potential of C. burnetii as a biological warfare threat is directly related to its infectivity. It has been estimated that 50 kg of dried, powdered bacterium would produce casualties a rate equal to that of similar amounts of anthrax or tularemia organisms [2, 3]. In humans, the most common acute form of Q fever is characterized as a flue-like illness or atypical pneumonia, or less frequently as granulomatous hepatitis, with a significant incidence of neurologic complications [4]. Persistent infections in humans can lead to a chronic form of Q fever, which may be associated with a fatal endocarditis [4]. Q fever was diagnosed in various animals. In livestock, it is associated with pneumonia and reproductive disorders with abortion, stillbirth, placentitis, endometritis, and infertility [5]. The main route of infection is inhalation of contaminated aerosol or dust containing bacteria shed by infected animals with milk, feces, placenta, or

BSL3 and BSL4 Agents: Proteomics, Glycomics, and Antigenicity, First Edition. Edited by Jiri Stulik, Rudolf Toman, Patrick Butaye, Robert G. Ulrich. © 2011 Wiley-VCH Verlag GmbH & Co. KGaA. Published 2011 by Wiley-VCH Verlag GmbH & Co. KGaA.

116

10 Lipopolysaccharides of Coxiella burnetii

vaginal secretions [5, 6]. Oral trasmission seems less common, but the consumption of contaminated raw milk and dairy products represents a potential source of human infection [5]. As several clinical symptoms of Q fever are similar to commonly occurring infections, an unambiguous diagnosis of the disease is quite difficult [4, 6]. In addition, most laboratories cannot work with this pathogen as the biological protection requirements are very high in this case (biosafety level 3 conditions). Various serological methods are currently used for a rapid and sensitive diagnosis of the disease [4, 7] but ambiguous results have been obtained in several cases. Thus, when bacterial antigens are used in the serological diagnosis, crossreactions have been observed with structurally related antigens of other bacterial species. For example, investigations have shown that C. burnetii cross-reacts with Chlamydia, Legionella, and Bartonella species [8]. Indirect immunofluorescence assay was proposed [8] as a reference serological method and applies purified C. burnetii cells as an antigen which are being propagated in embryonated hen eggs, tissue culture, or animals. Other serological methods include microagglutination, enzyme-linked immunoadsorbent assay (ELISA), complement fixation test, and Western blot. Recently, ELISA has been shown to be the most sensitive and the easiest to perform and its utility for epidemiological screening and diagnosis of acute and chronic forms of Q fever has been confirmed [7, 9]. Polymerase chain reaction is very useful, especially in those cases in which serological tests brought ambiguous results [6]. Its wider application is limited at present by higher costs as compared to other methods used in the field. Various mass spectrometric approaches have been used recently for rapid detection and identification of C. burnetii. Matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) of the intact bacterial cells and their acetonitrile extracts together with electrospray ionization mass spectrometry (ESI-MS) of the latter provided characteristic and reproducible mass spectral fingerprints containing unique biomarker profiles and proteins that can be exploited for rapid detection, identification, and typing of the bacterium [10–13].

10.2 Lipopolysaccharides of C. burnetii

Like other gram-negative bacteria, C. burnetii expresses at its surface various amphophilic macromolecules among which LPSs and proteins are of particular biological, immunological and medical significance [14]. LPSs of all gram-negative bacteria share the common structural features. They consist of an O-polysaccharide chain, a core oligosaccharide region, and a lipid component, termed lipid A [15]. This type of LPS is the classical one, as found in wild-type (S-form) strains of the gram-negative bacteria. The two saccharide regions, the O-chain and core oligosaccharide, may be distinguished by their genetic determination, biosynthesis, chemical structure, and biological properties [16, 17]. Defects in the gene clusters

10.2 Lipopolysaccharides of C. burnetii

responsible for the synthesis of the O-chain (rfb and rfc loci) lead to an LPS containing a highly truncated O-chain or an LPS consisting of lipid A and the core region only. Such mutants are called rough (R) mutants due to the rough appearance of their colony morphology [17]. Their major feature is a noticeably reduced virulence in comparison with their parent S-form strain due to increased susceptibility to complement-mediated serum killing. Nevertheless, in the last decade many (R) LPSs have been found in pathogenic wild-type bacteria, including those colonizing especially the mucosal surfaces of the respiratory and urogenital tracts, such as Neisseria meningitis, N. gonorrhoeae, Haemophilus influenzae, Bordetella pertussis, or Chlamydiaceae. At present, it is not known with certainty whether these bacteria are not able to biosynthetize (S) LPSs or whether the genes encoding synthesis of O-specific chains are suppressed or deleted by regulatory mechanisms induced by environmental cues [18]. However, the occurrence of such (R) type LPSs in the pathogenic wild-type bacteria indicates that the O-chain cannot be considered as the only major factor of pathogenicity in the respective bacterium and that it is dispensable without deleterious effects for it. C. burnetii undergoes a virulent (phase I) to avirulent (phase II) variation upon serial laboratory passages in yolk sacs of embryonated hen eggs [14]. This phase variation is accompanied by modifications in both composition and structure of the LPS macromolecule [14, 19, 20]. In phase I, C. burnetii biosynthesizes (S) LPS I with O-specific chain whereas in phase II, it synthesizes (R) LPS II [19]. This phase variation was assumed [21] to resemble in many aspects the well known smooth to rough variation found with many gram-negative bacteria. It was proposed [22] that the LPS I reduces gradually its O-polysaccharide chain during the phase variation, and in the phase II, a deep (R) LPS II is present in the outer membrane of the C. burnetii cell. When mapping the O antigen-encoding region in several phase II antigenic variants of the Nine Mile strain of C. burnetii, a large group of LPS biosynthetic genes has been deleted [23, 24]. However, other phase II isolates contained no apparent deletions [24]. As there is no molecular evidence of large deletions in the same regions deleted in Nine Mile-derived isolates, these isolates might undergo an LPS drift similar to that observed by Ftacek et al. [20], where mixtures of at least three LPS populations were present in the C. burnetii strain Priscilla, depending on passage history. The LPS molecules extracted from any (S) strain are heterogeneous in size. They include at least some (R) LPS and in some cases variously truncated LPS molecules. Thus, it can be assumed that each strain/isolate has a cell population that expresses multiple LPS structures. The similar phenomenon was also observed [20] in the LPSs isolated during serial passage of C. burnetii in embryonated hen eggs. No noticeable shortening of the O-polysaccharide chains was observed as anticipated previously [22] but a redistribution of the existing LPS populations took place due to an increasing prevalence of those cells in the whole cell population that express LPS molecules with truncated O-chains and those being of (R) type. At present, the molecular mechanisms influencing the LPS modifications during the C. burnetii phase variation remain unclear.

117

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10 Lipopolysaccharides of Coxiella burnetii

10.2.1 Chemical Composition and Structure of LPS I

The LPS I plays an important role in the interaction of C. burnetii with a host, its pathogenicity and immunogenicity; it is capable of inducing antibody response, and it is considered to be a protective immunogen [25, 26]. Despite these facts, knowledge on its primary structure has been insufficient thus far. It was found [21, 27, 28] that the LPS I contains, in addition to the sugar residues found in the LPS II and some frequently occuring sugars, two unusual sugar units in its O-polysaccharide chain, namely virenose (Vir, 6-deoxy-3-C-methylgulose) and dihydrohydroxystreptose [Strep, 3-C-(hydroxymethyl)lyxose]. Both sugars have not been found in other LPSs and are considered unique biomarkers of C. burnetii. The enantiomeric forms and ring conformations of both saccharides were established from the optical rotation and NMR data [28]. Vir was found to be the d-gulo enantiomer with the 4C1 ring conformation and Strep was shown to be the l-lyxo enantiomer also with the 4C1 conformation. A tentative structural analysis of LPS I showed [29] that Strep was present in the parent LPS I in a furanose form. Therefore, it was suggested [28] that a furanose to pyranose tautomerization took place in the course of the isolation procedure. The methylation-linkage analyses of two polysaccharide fractions of the LPS I performed recently [30] revealed the presence of terminal Vir, Strep, and mannose (Man), 4-substituted Vir, 4-substituted Man, and 2,3- and 3,4-disubstituted d-glycero-d-manno-heptose (Hep). Among the amino sugars, 4-substituted glucosamine (GlcN) was detected. The methylation data demonstrated the pyranose form of Vir, Man, Hep, and GlcN, and the furanose form of Strep. From previous studies [31], it could be anticipated that two terminal Man, 2,3- and 3,4-disubstituted Hep were from the core region of LPS I, and thus other terminal and substituted sugars should be located in the O-polysaccharide chain. In previous works [21, 28, 29], it was suggested that Vir and Strep are located almost exclusively in terminal positions. However, these recent findings show that this is probably true only for Strep, as Vir is also (1→4)linked. Similarly, Man is present in terminal position but about 23% of it is also involved in 1→4 linkages (Figure 10.1). Progress in a more detailed characterization of the O-specific chain in the LPS I is hampered by the presence of several O-chain populations differing in size, shape, and chemical composition. Therefore, only a tentative structural arrangement of sugar residues in the LPS I can be given as shown in Figure 10.2. The lipid A portion of an LPS is linked to the core oligosaccharide mostly via 3-deoxy-d-manno-oct-2-ulosonic acid (Kdo) and serves as the hydrophobic anchor of LPS in the outer membrane [32]. Previous reports have suggested [32] that lipid A, as the principal endotoxic component of LPS, plays a major role in the pathogenesis of bacterial infections and is an important contributor to massive inflammation, sepsis, and septic shock, leading to fatalities in gram-negative bacteria infections. It also promotes the activation of the innate immune system via induction of inflammatory cytokines released by human cells. Lipid A usually contains a diglucosamine backbone substituted with both ester- and amide-linked fatty acyl

10.2 Lipopolysaccharides of C. burnetii

Terminal position

Linkage position

4 Vir 1

Vir 1 Man 1

4 Man 1

Strep 1

4 GlcN 1

Figure 10.1 Schematic presentation of sugar linkages found in the O-chain of the LPS I of C. burnetii in virulent phase I. Vir – virenose (6-deoxy-3-C-methyl-d-gulose); Strep – dihydrohydroxystreptose [3-C-(hydroxymethyl)-l-lyxose]; Man – d-mannose; GlcN – d-glucosamine.

O-chain Vir, Strep, Man, Glc, GlcN

Core region outer inner Man

Man, Hep

Hep

Kdo

Lipid A

Tentative structural arrangement of the sugar residues in the LPS I of C. burnetii in virulent phase I. Vir – virenose (6-deoxy-3-C-methyl-d-gulose); Strep – dihydrohydroxystreptose [3-C-(hydroxymethyl)-l-

Figure 10.2

lyxose]; Man – d-mannose; Glc – d-glucose; GlcN – d-glucosamine; Hep – d-glycero-dmanno-heptose; Kdo – 3-deoxy-d-manno-oct-2ulosonic acid. The underlined sugars are prevalent in the O-chain.

side-chains and may carry phosphate groups at O-1 and O-4′. In addition, other substituents or sugar constituents, such as 4-amino-4-deoxy-l-arabinose, have been found. Structural studies of various bacterial LPSs have confirmed that lipid A represents the most conserved region of an LPS [33]. Although the biochemical synthesis of lipid A is a highly conserved process, investigations of the lipid A structures of various bacteria and even the isolates of the same bacterium including C. burnetii show an impressive amount of diversity [32–34]. These differences can be attributed to the action of latent enzymes that modify the canonical lipid A molecule. Variation of the lipid A domain of LPS serves as one strategy utilized [32] by gram-negative bacteria to promote survival by providing resistance to components of the innate immune system and helping to evade recognition by Toll-like receptor 4. Our detailed investigations on structure and function of lipid A isolated from the LPS of C. burnetii are presented in this booklet elsewhere.

119

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10 Lipopolysaccharides of Coxiella burnetii

α-D-Man p 1 α-D-Man p-(1

2)-α-D,D-Hep p-(1

4 3) -α-D,D-Hep p-(1

5)-α-Kdo-(2 4

2 α-Kdo-(4

2) -α-Kdo

Figure 10.3 Structural features of the lipid A proximal region of the LPS II of C. burnetii in

avirulent phase II. Man p – d-mannopyranose; D,D,-Hep p – d-glycero-d-manno-heptopyranose; Kdo – 3-deoxy-d-manno-oct-2-ulosonic acid.

10.2.2 Chemical Composition and Structure of LPS II

Both compositional and structural studies of the LPS II produced a lot of controversy in the past. This subject has been reviewed [19] by Toman recently. Based on the combined results of methylation-linkage analysis, fast atom bombardment-, ESI-, and MALDI-MS [31, 35], a structural model for the LPS II could be proposed. The monosaccharides Man, D,D-Hep, and Kdo were found to be the constituent sugars of the lipid A proximal region in a molar ratio 2 : 2 : 3 with the linkages depicted in Figure 10.3. Most recently, we performed initial studies [36] on the chemical composition and structure of an LPS isolated from the C. burnetii strain Nine Mile, variant “Crazy” (Cr) that was together with the phase II variant investigated [23] in a considerable detail by the methods of molecular biology. In contrast to the LPS I and II, the LPS Cr gave only one band at about 14 kDa on sodium dodecyl sulfate polyacrylamide gel electrophoresis. Sugar analysis revealed the presence of Man, Glc, D,D-Hep, Strep, and GlcN in a molar ratio 3.1 : 0.1 : 1.0 : 1.5 : 1.2, respectively. No Vir was found. MALDI-MS analyzes of lipid A indicated chemical structure similar to that found in the LPS I and II [34–36]. The truncated LPS II structure was shown [23] to be a result of large chromosomal DNA deletions in the phase II cells of strain Nine Mile. The deleted region is characterized by a high number of genes that are predicted to function in LPS or lipooligosaccharide biosynthesis, as well as several that were predicted to function in general carbohydrate and sulfur metabolisms. Deletions in the variant Cr were larger extending on both ends beyond the phase II deletion junctions. However, both chemical composition and structure of the LPS Cr are more complex than those of the LPS II. The reason for this discrepancy remains unknown. 10.2.3 The Role of LPS I in Diagnosis of Q Fever

Phase variation of C. burnetii has a direct impact on the serological diagnosis of Q fever. During acute Q fever, C. burnetii induces antibodies against phase II (protein antigens), while in the later stages of the disease, and especially in its

References

chronic form often manifested as endocarditis, the high titers of antibodies are directed against phase I (LPS I antigen) [4]. The immunoreactive proteins involved in a highly specific and reliable diagnosing acute Q fever have not been established with certainty thus far. Further, there has been achieved some progress in the elucidation of interaction of phase I antibodies with the LPS I antigen. A remarkable decrease in the serological activity of the O-polysaccharide antigen was observed when Vir and Strep were selectively removed from its chain [30]. At present, however, it is not known with certainty whether the immunoreaction proceeds only with both sugars in terminal positions or also with those Vir residues located in the O-polysaccharide backbone. The unique C. burnetii biomarkers Vir and Strep could be used in future for rapid, sensitive and unambiguous detection of the virulent form of C. burnetii (Q fever) and differentiation of the individual isolates/variants. Thus, a monoclonal antibody (mAb, IgG class) has been generated that is highly specific for the presence of Vir in C. burnetii LPS [37]. The immunoblot and ELISA studies have confirmed that only Vir containing C. burnetii cells and LPSs were recognized by the mAb. The intensity of the signals differed depending on the isolate/variant tested. In immunoblot, the most reactive region was about 14–36 kDa. Variability in the immunoreactivity of isolates/variants studied was seen in both distribution of the individual bands and their intensities.

10.3 Conclusion

There is a need to better characterize the relatively poorly understood LPS I as the elucidation of mechanisms of induction and development of various biological activities of the LPS I and its functions at the molecular level requires a detailed knowledge of its chemical composition and structure. This problem appears to be of utmost importance in connection with the future studies on mechanisms of pathogenesis and immunity of Q fever, its early and reliable diagnosis, and effective prophylaxis against the disease.

Acknowledgments

This work was supported in part by grant 2/0127/09 of the Scientific Grant Agency of the Ministry of Education of the Slovak Republic and the Slovak Academy of Sciences.

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virulence, and pathogenicity of Coxiella

burnetii for various hosts, in Q Fever: The Biology of Coxiella burnetii

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(eds J.C. Williams and H.A. Thompson), CRC Press, Boca Raton, FL, pp. 22–71. Madariaga, M.G., Rezai, K., Trenholme, G.M., et al. (2003) Q fever: a biological weapon in your backyard. Lancet Infect. Dis., 3, 709–721. World Health Organization (1970) Health Aspects of Chemical and Biological Weapons: Report of A WHO Group of Consultants, WHO, Geneva, Switzerland. Maurin, M., and Raoult, D. (1999) Q fever. Clin. Microbiol. Rev., 12, 518–553. Arricau-Bouvery, N., and Rodolakis, A. (2005) Is Q fever an emerging or re-emerging zoonis? Vet. Res., 36, 327–349. Choi, E. (2002) Tularemia and Q fever. Med. Clin. North Am., 86, 393–416. Slaba, K., Skultety, L., and Toman, R. (2005) Efficiency of various serological techniques for diagnosing Coxiella burnetii infection. Acta Virol., 49, 123–127. Fournier, P.E., Marrie, T.J., and Raoult, D. (1998) Diagnosis of Q fever. J. Clin. Microbiol., 36, 1823–1834. Uhaa, I.J., Fishbein, D.B., Olson, J.G., et al. (1994) Evaluation of specificiy of indirect enzyme-linked immunosorbent assay for diagnosis of human Q fever. J. Clin. Microbiol., 32, 1560–1565. Shaw, E.I., Moura, H., Woolfitt, A.R., et al. (2004) Identification of biomarkers of whole Coxiella burnetii phase I by MALDI-TOF mass spectrometry. Anal. Chem., 76, 4017–4022. Skultety, L., Hernychova, L., Bereghazyova, E., et al. (2007) Detection of specific spectral markers of Coxiella burnetii isolates by MALDI-TOF mass spectrometry. Acta Virol., 51, 55–58. Pierce, C.Y., Barr, J.R., Woolfitt, A.R., et al. (2007) Strain and phase identification of the U. S. category B agent Coxiella burnetii by matrix assisted laser desorption/ionization time-of-flight mass spectrometry and multivariate pattern recognition. Anal. Chim. Acta, 583, 23–31. Hernychova, L., Toman, R., Ciampor, F., et al. (2008) Detection and identification of Coxiella burnetii based on the mass spectrometric analyses of the extracted proteins. Anal. Chem., 80, 7097–7104.

14 Williams, J.C., and Waag, D.M. (1991)

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Antigens, virulence factors, and biological response modifiers of Coxiella burnetii: strategies for vaccine development, in Q Fever: The Biology of Coxiella burnetii (eds J.C. Williams and H.A. Thompson), CRC Press, Boca Raton, FL, pp. 175–222. Mayer, H., Tharanathan, R.N., and Weckesser, J. (1985) Analysis of lipopolysaccharides of gram-negative bacteria. Methods Microbiol., 18, 157–207. Keenleyside, W.J., and Whitfield, C. (1999) Genetics and biosynthesis of lipopolysaccharide O-antigens, in Endotoxin in Health and Disease (eds H. Brade, S.M. Opal, S.N. Vogel, and D.C. Morrison), Marcel Dekker, New York, pp. 331–358. Heinrichs, D.E., Whitfield, C., and Valvano, M.A. (1999) Biosynthesis and genetics of lipopolysaccharide core, in Endotoxin in Health and Disease (eds H. Brade, S.M. Opal, S.N. Vogel, and D.C. Morrison), Marcel Dekker, New York, pp. 305–330. Preston, A., Mandrell, R.E., Gibson, B.W., et al. (1996) The lipooligosaccharides of pathogenic gram-negative bacteria. Crit. Rev. Microbiol., 22, 139–180. Toman, R. (1999) Lipopolysaccharides from virulent and low-virulent phases of Coxiella burnetii, in Rickettsiae and Rickettsial Diseases at the Turn of the Third Millenium (eds D. Raoult and P. Brouqui), Elsevier, Paris, pp. 84–91. Ftacek, P., Skultety, L., and Toman, R. (2000) Phase variation of Coxiella burnetii strain Priscilla: influence of this phenomenon on biochemical features of its lipopolysaccharide. J. Endotoxin Res., 6, 369–376. Mayer, H., Radziejewska-Lebrecht, J., and Schramek, S. (1988) Chemical and immunochemical studies on lipopolysaccharides of Coxiella burnetii phase I and phase II. Adv. Exp. Med. Biol., 228, 577–591. Diaz, Q.M., and Lukacova, M. (1998) Immunological consequences of Coxiella burnetii phase variation. Acta Virol., 42, 181–185. Hoover, T.A., Culp, D.W., Vodkin, M.H., et al. (2002) Chromosomal DNA deletions

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explain phenotypic characteristics of two antigenic variants, phase II and RSA 514 (Crazy), of the Coxiella burnetii Nine Mile strain. Infect. Immun., 70, 6726–6733. Denison, A.M., Massung, R.F., and Thompson, H.A. (2007) Analysis of the O-antigen biosynthesis regions of phase II isolates of C. burnetii. FEMS Microbiol. Lett., 267, 102–107. Toman, R. (1996) Lipopolysaccharides of Coxiella burnetii, in Rickettsiae and Rickettsial Diseases. Proc. Vth Int. Symp (eds J. Kazár and R. Toman), VEDA, Bratislava, pp. 379–388. Gajdošová, E., Kovácˇová, E., Toman, R., et al. (1994) Immunogenicity of Coxiella burnetii whole cells and their outer membrane components. Acta Virol., 38, 339–344. Skultety, L., Toman, R., and Patoprsty, V. (1998) A comparative study of lipopolysaccharides from two Coxiella burnetii strains considered to be associated with acute and chronic Q fever. Carbohydr. Polym., 35, 189–194. Toman, R., Skultety, L., Ftacek, P., et al. (1998) NMR study of virenose and dihydrohydroxystreptose isolated from Coxiella burnetii phase I lipopolysaccharide. Carbohydr. Res., 306, 291–296. Toman, R. (1991) Basic structural features of a lipopolysaccharide from the Coxiella burnetii strain Nine Mile in the virulent phase I. Acta Virol., 35, 224. Vadovic, P., Slaba, K., Fodorova, M., et al. (2005) Structural and functional characterization of the glycan antigens involved in immunobiology of Q fever. Ann. N.Y. Acad. Sci., 1063, 149–153.

31 Toman, R., and Skultety, L. (1996)

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Structural study on a lipopolysaccharide from Coxiella burnetii strain Nine Mile in avirulent phase II. Carbohydr. Res., 283, 175–185. Alexander, C., and Rietschel, E.T. (2001) Bacterial lipopolysaccharides and innate immunity. J. Endotoxin Res., 7, 167–202. Zähringer, U., Lindner, B., and Rietschel, E.T. (1999) Chemical structure of lipid A: recent advances in structural analysis of biologically active molecules, in Endotoxin in Health and Disease (eds H. Brade, S.M. Opal, S.N. Vogel, and D.C. Morrison), Marcel Dekker, New York, pp. 93–114. Toman, R., Garidel, P., Andra, J., et al. (2004) Physicochemical characterization of the endotoxins from Coxiella burnetii strain Priscilla in relation to their bioactivities. BMC Biochem., 5. http:// www.biomedcentral.com/1471-2191/5/1 (accessed 11 January 2011). Toman, R., Hussein, A., Slabá, K., et al. (2003) Further structural characteristics of the lipopolysaccharide from Coxiella burnetii strain Nine Mile in low virulent phase II. Acta Virol., 47, 129–130. Vadovic, P., Fuleova, A., Ihnatko, R., et al. (2009) Structural studies of lipid A from a lipopolysaccharide of the Coxiella burnetii isolate RSA 514 (Crazy). Clin. Microbiol. Infect., 15, 198–199. Palkovicova, K., Ihnatko, R., Vadovic, P., et al. (2009) A monoclonal antibody specific for a unique biomarker, virenose, in a lipopolysaccharide of Coxiella burnetii. Clin. Microbiol. Infect., 15, 183–184.

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11 Mimivirus Possesses Anonymous and Unique Gene Products Endowed for Antigenic Properties Patricia Renesto and Didier Raoult

11.1 Introduction

Acantamoeba polyphaga mimivirus (Mimivirus) is the largest known virus isolated so far [1]. Recent clinical evidence raised the possibility that Mimivirus might be a human pathogen causing pneumonia [2–4], as suspected when it was first isolated in a cooling tower following an outbreak of pneumonia [1]. Sequencing of its 1.2 Mb genome [5] revealed highly specific characteristics accounting for its classification as the first member of the new Mimiviridae family [6]. Among atypical features are the presence of key translation enzymes, a full complement of DNA repair pathway components, and the presence of three different topoisomerases (types IA, IB, II). Only 23% of the predicted coding genes exhibit a convincing homology to proteins of known function and 39% of them do not exhibit a clear (E < 10−5) sequence database match [5]. Such coding regions without sequence similarity to other genes in databases were considered as orphan open reading frames (ORFs) and termed ORFans [7]. As their number increased with each sequenced genome, the status of these species-specific putative genes became matter of controversy, with opinions ranging from considering them pieces of junk DNA to seeing them as encoding normally expressed functional proteins [8]. Mass spectrometry-based analysis has recently emerged as a technique of choice to identify more comprehensively the set of viral proteins associated to viral particles [9–11]. By using such an approach we investigated the presence of ORFanencoded proteins within Acanthamoeba polyphaga mimivirus particles. In a second step, solubilized proteins separated by two-dimensional polyacrylamide gel electrophoresis (2D-PAGE) were analyzed by Western blot, thus demonstrating the antigenicity of such ORFan-encoded proteins.

BSL3 and BSL4 Agents: Proteomics, Glycomics, and Antigenicity, First Edition. Edited by Jiri Stulik, Rudolf Toman, Patrick Butaye, Robert G. Ulrich. © 2011 Wiley-VCH Verlag GmbH & Co. KGaA. Published 2011 by Wiley-VCH Verlag GmbH & Co. KGaA.

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11.2 Material and Methods 11.2.1 Sample Preparation

Mimivirus grown in Acanthameba polyphaga strain Linc AP-1 (in 75-cm2 cell culture flasks with peptone yeast extract glucose medium) was purified through a sucrose gradient (25%) and washed twice with phosphate buffer saline (PBS) in the presence of protease inhibitors (Complete, Roche). The resulting pellet was solubilized in Tris-HCl 40 mM, pH 7.5, supplemented with SDS 2% (w/v) and DTT 60 mM, followed by 5 min heating at 95 °C. The unsoluble fraction was removed by centrifugation (12 000 g, 4 °C, 10 min) and soluble proteins were precipitated using a PlusOne 2-D clean-up kit (Amersham) to remove SDS. The final pellet was resuspended in solubilization buffer [7 M urea, 2 M thiourea, 4% (w/v) CHAPS] and stored at −80 °C until isoelectric focusing (IEF) was performed. 11.2.2 2D-PAGE and Matrix-Assisted Laser Desorption/Ionization Time of Flight Mass Spectrometry

Mimivirus proteins were resolved on 2D-PAGE as described [12], using Immobiline™ DryStrips in the range pH 4–7 or pH 6–11 (Amersham). Following migration, gels were stained by a method compatible with mass spectrometry [13] and proteins of interest as well as those mainly expressed were excised from the gel. Tryptic peptides obtained following in-gel digestion were extracted from the gel and analyzed on a matrix-assisted laser desorption/ionization time of flight (MALDI-TOF) Bruker Ultraflex mass spectrometer (Bruker Daltonics, Bremen, Germany). The corresponding mass lists were used to identify the proteins, using Mascot software. Searches were performed against all available sequences in public databases, including those for eukaryotes (www.matrixscience.com). For accuracy, the spectra of at least two separate samples of each protein were analyzed and compared. Overall, a successful identification was reached for more than 70% of the spots analyzed. 11.2.3 Immunization and Western Blot

Following transfer onto nitrocellulose membranes, Mimivirus proteins were incubated for 1.5 h with the serum of a BALB/c mouse (1 : 6400) immunized by three intraperitoneal injections of 5 μg of purified viral particles resuspended in CpG as immune adjuvant. Horseradish peroxidase-conjugated goat antimouse antibodies were used as secondary antibodies (1 : 1000, Amersham). Detection was done by chemiluminescence (ECL, Amersham).

11.3 Results

11.3 Results 11.3.1 Proteomic Analysis of Mimivirus Particle

Completion of 2D-PAGE coupled to MALDI-TOF MS allowed us to identify 42 Mimivirus proteins. The diversity of functions represented in the viral particle was quite large, with bona fide “structural” proteins amounting for a small fraction of the number. Based on both the area and intensity of spots corresponding to ORFan gene products observed on 2D-PAGE gels we concluded that such proteins are expressed and contribute to the making of the Mimivirus particle (Figure 11.1). While some proteins appeared hydrolyzed (e.g., that encoded by Mimi_L442), a good correlation between observed and theoretical pI and MW values was observed. Analysis of 2D-PAGE gels also evidenced that most of the Mimivirus proteins were not resolved into single spots but rather as a train of spots. This results from the

111.0 93.0

L425

111.0 93.0

R135

53.5

R135

53.5 L724

L724 36.1 29.5

36.1 29.5 L442

21.3

ORF

b) Silver staining on 2D-PAGE

Protein function

L829

L725

pI3

10

pI3

a) Negative staining

21.3

L725

10

c) Western blot Mass (kDa)

pI

Number of isoforms

MIMI_R135

Choline dehydrogenase or related protein

76948

7.55

4

MIMI_L425

Capsid protein D13L

51377

5.14

4

MIMI_L442

Unknown Orfan

139334

5.88

11

MIMI_L724

Unknown Orfan

24034

7.86

2

MIMI_L725

Unknown Orfan

26538

6.91

5

MIMI_L829

Unknown

49229

6.07

8

Figure 11.1 Proteomic analysis of Acanta-

moeba polyphaga mimivirus particles. Purified viral particles shown by electron microscopy (a) were solubilized and proteins separated by 2D-PAGE (b). Spots were then cut from the gel and subjected to MALDI-TOF MS analysis

for identification. Alternatively, gels were transferred to nitrocellulose membrane and probed with serum from a mouse immunized with the viral particles (c). Predominantly expressed as well as immunoreactive spots identified by MALDI-TOF MS are indicated.

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existence of several isoforms in part due to protein glycosylation [12]. Of note is that, as previously observed [12], no eukaryotic proteins were identified in our samples, confirming their purity and demonstrating that eukaryotic proteins are not encapsidated within Mimivirus particles. 11.3.2 Antigenic Properties of ORFan-Encoded Mimivirus Proteins

Immunoblots performed on samples resolved by 2D-PAGE provided evidence of the antigenicity of Mimivirus proteins (Figure 11.1). Mimivirus proteins, including those encoded by ORFan genes, were indeed specifically recognized with the serum from a mouse immunized with the viral particles. The antigenicity of ORFan-encoded proteins, and most specifically of that encoded by MIMI_L724, was also observed when the membrane was probed with the serum of a patient infected with Mimivirus [2–4]. 11.3.3 Concluding Remarks

Altogether, these results contribute to the ongoing debate on the evolutionary origin of the gene content of large DNA viruses such as Mimivirus and suggest that ORFans may indeed correspond to bona fide viral proteins, the functions and origins of which remain to be discovered.

References 1 La Scola, B., Audic, S., Robert, C.,

2

3

4

5

Jungang, L., de Lamballerie, X., Drancourt, M., Birtles, R., Claverie, J.-M., and Raoult, D. (2003) A giant virus in amoebae. Science, 299, 2033. Berger, P., Papazian, L., Drancourt, M., La Scola, B., Auffray, J.P., and Raoult, D. (2006) Ameba-associated microorganisms and diagnosis of nosocomial pneumonia. Emerg. Infect. Dis., 12, 248–255. La Scola, B., Marrie, T.J., Auffray, J.P., and Raoult, D. (2005) Mimivirus in pneumonia patients. Emerg. Infect. Dis., 11, 449–452. Raoult, D., Renesto, P., and Brouqui, P. (2006) Laboratory infection of a technician by giant Mimivirus. Ann. Int. Med., 144, 702–703. Raoult, D., Audic, S., Robert, C., Abergel, C., Renesto, P., Ogata, H., La Scola, B., Suzan, M., and Claverie, J.-M. (2004) The

6

7

8

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10

1.2-megabase genome sequence of Mimivirus. Science, 306, 1344–1350. Suzan-Monti, M., La Scola, B., and Raoult, D. (2006) Genomic and evolutionary aspects of Mimivirus. Virus Res., 117, 145–155. Fischer, D., and Eisenberg, D. (1999) Finding families for genomic ORFans. (1999) Bioinformatics, 15 May, 759–762. Siew, N., Saini, H.K., and Fischer, D. (2005) A putative novel alpha/beta hydrolase ORFan family in Bacillus. FEBS Lett., 579, 3175–3182. Kattenhorn, L.M., Mills, R., Wagner, M., Lomsadze, A., Makeev, V., Borodovsky, M., Ploegh, H.L., and Kessler, B.M. (2004) Identification of proteins associated with murine cytomegalovirus virions. J. Virol., 78, 11187–11197. O’Connor, C.M., and Kedes, D.H. (2006) Mass spectrometric analyses of purified

References rhesus monkey rhadinovirus reveal 33 virion-associated proteins. J. Virol., 80, 1574–1583. 11 Zachertowska, A., Brewer, D., and Evans, D.H. (2005) Characterization of the major capsid proteins of myxoma virus particles using MALDI-TOF mass spectrometry. J Virol. Methods, 132, 1–12. 12 Renesto, P., Abergel, C., Decloquement, P., Moinier, D., Azza, S., Ogata, H.,

Fourquet, P., Gorvel, J.P., and Claverie, J.-M. (2006) Mimivirus giant particles incorporate a large fraction of anonymous and unique gene products. J. Virol., 80, 11678–11685. 13 Shevchenko, A., Wilm, M., Vorm, O., and Mann, M. (1996) Mass spectrometric sequencing of proteins silver-stained polyacrylamide gels. Anal. Chem., 68, 850–858.

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12 Detection of Differentially Modified Pathogen Proteins by Western Blot after 2D Gel Electrophoresis and Identification by MALDI-TOF/TOF Fred Fack, Julia Kessler, Patrick Pirrotte, Jacques Kremer, Dominique Revets, Wim Ammerlaan, and Claude P. Muller

12.1 Introduction

Viruses have developed complex strategies to exploit host cell mechanisms for efficient replication [1]. Post-translational modifications, such as glycosylation of viral surface proteins, phosphorylation, sumoylation, methylation, acetylation, and so on, of both viral and cellular proteins have been shown to play important roles in virus–host interactions. Post-translational modifications of viral and cellular proteins may also modulate virus virulence and attenuation. They are, for example, essential for the induction of type I interferon, a first line of defense against invading viruses and the induction of adaptive immunity. After viral infection transcription factors, such as interferon regulatory factor 3 (IRF-3), NF-kB, and ATF-2/c-JUN, are activated and induce the expression of beta IFN (IFN-beta) and other antiviral genes [2]. In this process C-terminal serine and threonine residues of IRF3 monomers constitutively expressed in the cytoplasma become hyperphosphorylated. This results in a conformational change necessary for dimerization and translocation of IRF3 to the nucleus where it binds to IRF DNA consensus sites and modulates the transcription of immune response genes such as interferon alpha and beta [2]. This signaling pathway can be disturbed by viral strategies to overcome the host defense. For instance, VP35 of the Ebola virus can interfere with the activation of IRF3 in vitro [3]. These modifications of amino acid side chains affect the isoelectric point (pI) of a protein, reflected in two-dimensional protein gels by distinct spots without a mass shift. Measles virus (MV) can induce host cell responses associated with different levels of virulence. To evaluate both the antiviral response to viral infection and the viral replication appropriate protein markers were chosen. The IFN-inducible MxA proteins are highly conserved, large GTPases with homology to dynamin and have been found in all vertebrate species examined so far [4]. A perinuclear aggregation of MxA and viral proteins and the possible antiviral effect of this sequestration of viral components has been shown for Bunyaviruses [5]. MxA is a good candidate to monitor the induction of a primary interferon regulated antiviral BSL3 and BSL4 Agents: Proteomics, Glycomics, and Antigenicity, First Edition. Edited by Jiri Stulik, Rudolf Toman, Patrick Butaye, Robert G. Ulrich. © 2011 Wiley-VCH Verlag GmbH & Co. KGaA. Published 2011 by Wiley-VCH Verlag GmbH & Co. KGaA.

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response, and MV-NP can serve as an indicator for viral protein synthesis and to a certain extent for viral replication. To compare protein patterns of cells, the 2D-DIGE technology is the method of choice. Protein extracts of infected and uninfected cells are labeled typically with Cy3 and Cy5 dyes to separate them in a same gel and to generate fully superimposable images with a fluorescence scanner [6]. An internal standard containing a mix of the different protein extracts is labeled with a third color, generally Cy2 dye, allowing for relative quantification for comparing and matching different gels. Current equipment and image analysis software resolve thousands of protein spots in 18 or 24 cm 2D gels. However, several hundred micrograms of protein are generally required. We have evaluated small 2D gels and Western blotting for 2D-DIGE analysis of low amounts of biological samples. The detection of protein isoforms by 2D Western blots using flurorescence-labeled secondary antibodies has a number of advantages and can be combined with 2D-DIGE imaging. The availability of secondary antibodies as fluorescent conjugates for several different species has made the simultaneous detection of three specific proteins in a single blotting experiment possible. This multiplexing capacity provides a robust and straightforward detection system of various forms of different target proteins in a single Western blot experiment, and it is particularly attractive when protein quantities are limiting (i.e., 80% expressed the viral hemagglutinine protein at the cell surface and cell mortality was 250 (pox viruses) open reading frames (ORFs) for individual genomes, while the inclusion of genetic variants substantially increases the diversity of the metaproteome. Although there have been many attempts to establish empirical rules for predicting immune responses to polypeptides, there currently is no substitute for experimental evidence. Protein microarrays were developed as a high-throughput method to capture and analyze antibodies resulting from the host response to infection. Robotic microarray spotters rapidly produce planar substrates with many thousands of discrete probe surfaces. The measurement of antibody binding by microarray is possible over a wide dynamic range, with lower limits of nanograms/milliliter based on resolution of protein spots and detection signals. In contrast to ELISA and other assay formats, microarrays require only microliters of serum for analysis, thereby lowering consumption of clinical samples and increasing assay sensitivity. Microarray assays can be semi-automated, require only small quantities of protein probes, and are especially advantageous for high-throughput analysis. Many variations of protein microarrays have been reported, from rapid PCR-to-product approaches with no protein purification [5] to in situ synthesis of proteins on the microarray surface [6]. We use an approach that involves full characterization of gene clones and proteins products prior to assembly of the microarray.

16.2 Microarray Assembly

Annotated genomic sequences for most pathogens are publically available as a source for predicted proteomes. However, we must first note that reconciliations between the theoretical proteome and experimentally confirmed gene products may not available for many sequenced genomes [7, 8]. Cloning of protein-encoding DNA, sequencing and other commonly used molecular biology methods will not be addressed here. The method chosen for production of recombinant proteins should be similar to the host environment of the pathogen to ensure greatest fidelity of folding and post-translational modifications (Figure 16.1). Generally this will mean E. coli expression for bacterial products and either insect cells (baculovirus) or mammalian cells for viral proteins. Alternatively, in vitro translation provides an easily standardized method for more high-throughput applications. Following purification, the inclusion of glycerol in buffers is essential to prevent denaturation during protein spotting, though spotted microarrays can be stored (−20 °C) for short periods of time before use with little impact on quality. A very small amount of protein from concentrated samples (100–200 μg/ml) is deposited on planar surfaces, utilizing the same technology adopted for printing DNA microarrays. The most commonly used pin spotting method is very rapid and relies on capillary forces to release spots on contact with the surface, resulting in 60–600 μm diameter spots, depending on buffer composition and pin diameter. The slower

16.2 Microarray Assembly a)

Yersinia pestis

Vaccinia virus

Genomic + plasmid DNA is olated

ORFs cloned into Gateway Entry plasmid

b)

Transformation of ORF clones into bacmid-containing E. coli vector

ORF clones shuttled to pDEST vector

GST-tagged ORF clone expanded in E. coli

Transfection into Sf9 cells Eukaryotic protein expression

In vitro transcription and translation of individual Y. pestis ORF clones Bacterial (gram -) protein expression

GST-based affinity purification

Array spotting

Pathogen proteome microarrays. (a) General scheme for microarray production, showing vaccinia virus and Yersinia pestis as examples. (b) Confocal laser scanner image of proteins spotted in duplicate onto

Figure 16.1

microarray slides, visualized using a rabbit anti-GST antibody bound to Cy5-labeled anti-rabbit antibody. Vaccinia virus (left); Yersinia pestis (right).

but more accurate dip-pen lithography (DPN) uses atomic force microscopy microcantilevers to deposit spots in the range of 1–60 μm diameter (Nano eNabler, Bioforce Nanosciences, Ames, Ind., USA). Inkjet printers use piezoelectric elements to transfer the protein solution in the form of droplets to the target surface, printing spots with diameters of 80–150 mm. Although inkjet printers are very fast, they tend to have maintenance problems due to the more complicated delivery system. Alternatively, continuous flow microspotters use microfluidic channel networks to circulate dilute or concentrated protein samples over a spot defined by a template, achieving uniform and maximum protein adsorption [9]. Although chemically activated surfaces can be used, we find that nitrocellulosecoated slides (Gentel Biosciences; Whatman) provide the most consistent results for spotting a variety of proteins. Quality control measures should be considered. Unlike oligonucleotides, the highly variable physical properties of proteins impact

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the overall quality of high-content microarrays. Native folding and functionality of all proteins after spotting and during use are difficult to assess, but may not be as critical for polyclonal antibody recognition compared to other applications. Although it is not practical to measure function of all of arrayed proteins, a spot check of enzyme activity or protein–protein interactions for control proteins is beneficial. Further, many proteins fail to express or to form stable products under standard conditions, with success rates of 60–80% for purified products very common. A variety of reasons contribute to these failures, often requiring several independent strategies to increase the recovery rate. For many proteins, the addition of a soluble fusion partner, for example, glutathione-S-transferase (GST) or maltose binding protein (MBP), minimizes aggregation and aids in stable folding. The use of fusion tags linked to the targeted antigens helps in recovery of stably folded products, and can be used as a general marker for quality control. For example, purification schemes employing GST fusions will favor proteins with stable structures and will increase the yield of folded proteins because unfolded glutathione-S-transferase (GST) will not bind to the immobilized glutathione (the GST ligand) used for affinity purification. Before committing printed microarrays to experiments, protein spot densities of representative slides should be measured, for example, by using an anti-GST antibody compared to a dilution series of known quantities of protein also printed on each slide. Intra-slide and intra-lot variability in spot intensity and morphology, the number of missing spots and the presence of control spots should also be evaluated.

16.3 Antibody Assays

Serum IgG and IgM binding to arrayed proteins are independently probed on the same surface by fluorescently labeled secondary antibodies and detected by a confocal laser scanner (such as Genepix, Molecular Devices, Sunnyvale, Calif., USA). The much lower levels of IgA that may be present in a sample require a separate assay for detection. An accurate and rapid screening of thousands of proteins for antibody interactions is possible. Sera that may contain viable virus particles can be γ-irradiated with little harm to antibodies, while filtration removes suspected bacteria. Optimal dilutions of sera must be established to obtain minimal saturation of fluorescent signals while maintaining significant binding events. We find that for most applications, dilutions from 1 : 50–200 are usually sufficient for human sera. Microarray slides are pre-incubated (1 h, 22 °C) with a blocking buffer (1% BSA, 0.1% Tween-20 in PBS). Antibody samples are diluted in probe buffer (1× PBS, 5 mM MgCl2, 0.05% Triton X-100, 1% glycerol, 1% BSA), based on individual titer to optimize the signal above background. Diluted sera are overlaid (120–300 μl) on the slides, covered with glass cover slips, and incubated (1 h, 22 °C) in a humid incubator to prevent sample evaporation. Following incubation, cover slips are removed and the slides are washed with probe buffer. Although manual slide processing is not difficult, we also use a semi-automated hybridization work-

16.4 Antigens and Proteomes of Viruses

station (such as a Tecan HS 400 Pro, Tecan Group Ltd, Switzerland) for all steps through washing of the arrays for increased assay precision. Antibody binding is detected by simultaneous incubation with a dilution of fluorescently labeled (Alexa-647 or Alexa-532) goat antihuman IgG and goat antihuman IgM (Invitrogen, Carlsbad, Calif., USA). Our experience indicates that simultaneous detection of IgG and IgM using probe labels with minimal spectral overlap is accurate and the most efficient method to use. The slides are washed three times following incubation with the secondary antibody and allowed to air dry completely before analysis. Images of microarray surfaces are scanned and data captured using Genepix Pro 6.0 software (Molecular Devices). ProtoArray Prospector (Invitrogen/Life Technologies, Calif., USA) is a comprehensive software ensemble that we use for data analysis to evaluate statistical deviation of antibody binding signals from negative controls and the mean signal. Chebyshev’s Inequality (CI) P value and Z score can be used data comparison across multiple arrays. The Immune Response Biomarker Profiling (IRBP) Toolbox of Protoarray Prospector facilitates comparisons among groups of microarray experiments derived from different categories of samples, for example, disease and control. Fluorescent signals are normalized across the experiments and an M statistics algorithm is applied to identify signal increases in one group compared to another. For each protein spotted, the algorithm counts a number of assays in one group that have a higher signal than the highest signal in another group, then calculates how many assays have a signal bigger than the second largest signal in another group, third largest, and so on. These calculations establish cutoff values defining “hits” and P values that represent the probability that there is no signal increase in one group compared to another. As a result, the proteins of interest are those with the lowest P values that exhibit the biggest difference in number of hits between the groups of comparison. It is also important to visually inspect images of arrays to confirm positive scores, absence of dust particles, stray signals or other potential artifacts. MultiExperiment Viewer (MEV) software developed by TIGR (www.mev.tm4.org) is used to visualize the fluorescent signals across multiple arrays on heat maps. In addition, the MEV program offers a variety of tools including hierarchical clustering and principal component analysis to explore structures in complex datasets. Such structures may confirm the original hypothesis (e.g., difference in antibody response will separate disease and control groups in different clusters) and may illuminate relationships between proteins.

16.4 Antigens and Proteomes of Viruses

Our work with poxviruses is an example of a moderately complex proteome examined by microarray [10]. Of the seven known orthopox species, variola virus causes the most severe disease (smallpox) and various forms of the attenuated vaccinia virus are used for vaccination. To construct an orthopoxvirus proteome microarray,

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Infection Replication

Complement regulatory protein ~100 extracellular proteins

IMV

EEV IMV envelope proteins

EEV envelope proteins

~250 intracellular proteins Cell fusion protein

Summary of antigens EEV envelope proteins IMV envelope proteins DNA binding core protein IV membrane scaffold protein core proteins A-type inclusion protein, fragment Schlafen nucleoside triphosphate phosphohydrolase ribonucleoside reductase

Figure 16.2 The antibody response to poxvirus is directed towards proteomes originating

from intracellular and extracellular protein pools.

open reading frames (ORFs) from monkeypox Zaire-1979_005 (DQ011155; 202 genes), WRAIR7-61 (AY603973; 178 genes), and vaccinia Copenhagen (M35027; 273 genes) were PCR-amplified, cloned, and expressed in insect cells using Gateway baculovirus expression (Invitrogen). Poxviruses replicate in the cytoplasm of host cells from genomes encoding 150–300 proteins (Figure 16.2), while the mature virion is comprised of approximately 100 proteins. Gateway recombination cloning (pDEST20, Invitrogen) was employed to facilitate high-throughput production of proteins from all ORF clones. All DNA clones were sequence-verified through the entire length of their inserts. Baculovirus-based expression was used to produce the recombinant viral proteins as GST-tagged fusions to ensure high yield of properly folded proteins with post-translational modifications that are similar to those encountered in the human host. Isolated bacmid DNA was transfected into Sf9 insect cells to assemble competent virus particles, which were amplified to a high titer by successive rounds of insect cell infection and used to infect insect cell cultures for protein production. Using glutathione-agarose in 96-well plates, the GST-tagged proteins were affinity purified from cell lysates to 90% or greater homogeneity in a single step, as determined by SDS-polyacrylamide gel electrophoresis (PAGE). Purified proteins were analyzed by Western blot assay for correct size and abundance before inclusion in the microarray. The final protein microarray included 92–95% (166–192 proteins) of proteomes from monkeypox viruses and 92% coverage (250 proteins) of the vaccinia virus proteome. Virus particles can also be spotted and included in the assay, and this can be used to compare relative antibody titers to virus versus individual component proteins. For the orthopoxvirus microarray, recombinant pathogen and control proteins were printed onto glass slides coated with a thin layer of nitrocellulose [11, 12]. A standard assay for measuring antibody interactions with the vaccinia proteome microarray was first developed with a pool of therapeutic human sera col-

16.4 Antigens and Proteomes of Viruses

lected from vaccinia-immune individuals (VIg) and these data were compared to results obtained from individuals vaccinated against smallpox. The assay consisted of incubating a dilution of serum on the microarray surface, washes and finally detection with a fluorescently labeled anti-Ig antibody. Images were captured by scanning with a confocal laser (GenePix 4000B; Molecular Devices, Calif., USA) and analyzed (ProtoArray Prospector v3.1). Positive binding events were determined by Z scores [13] and Chebyshev’s Inequality P value (CI-P). Incubating the microarray with VIg identified nine proteins that consistently bound antibody, while antibody interactions with all other proteins were insignificant, requiring no further treatment to suppress nonspecific signals. These antigens were also recognized by antibodies from individual subjects following primary smallpox vaccination and were diverse in function, consisting of regulatory, surface, core, and secreted proteins (Figure 16.2). The validity of the statistical methods used was also confirmed by using an unbiased clustering analysis of the normalized data. Identical vaccinia proteins clustered into proteins recognized by primary and secondary vaccinated subjects based solely on signal intensities. The vaccinia proteins C3L and I1L were newly reported as antibody-recognized antigens. The nine antigenic proteins we identified did not bind antibody from nonvaccinated sera, confirming the specificity of these antibody–antigen interactions. However, O2L and H7R were reactive with antibodies from both VIg and nonvaccinated control sera, suggesting that these were cross-reactive or nonspecific interactions. Our results indicated that only a small subset of proteins present within the complex orthopox proteome was essential for immunity. We also examined the relationship between antibody binding to the arrayed proteins and protective immunity, noting that three antigens (A33R, C3L, I1L) correlated with titers of antibody that significantly neutralized infection in cell culture. In addition, the human response to individual vaccinia proteins was variable: sera from more than half of the vaccinated individuals contained IgG that recognized >4 vaccinia proteins, while the remaining samples recognized 1–3 proteins. Because of the potential for individual variation in immunity, it is essential to examine an expanded panel of unique serum samples to fully capture the antibody response represented within the targeted population. Further, antibodies from most individuals recognized a greater number of viral proteins after a boost vaccination compared to a single vaccination, suggesting that repeated infection may expand the total number of proteins recognized by IgG. The results from smallpox vaccinations identified key antigens associated with human immunity to infection, and defined the minimal number of antigens required for assay development. Whereas a panel of nine proteins will lead to comprehensive coverage of antibody responses to the vaccinia proteome, a single protein will not provide sufficient data to accurately predict a vaccine response. Smallpox vaccination is also effective for monkeypox due to a high degree of similarity between the infecting viruses. Using the expanded Orthopoxvirus protein microarray, we observed that serum IgG from cynomolgus macaques recovering from monkeypox recognized at least 23 separate proteins within the orthopox proteome, while only 14 of these proteins were recognized by IgG from vaccinated

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humans. We also detected specific IgM responses prior to onset of symptoms of monkeypox in nonhuman primates [14], an observation that may be common to other viral infections. By examining antibodies from ZAIRE-infected macaques we observed extensive cross-reactivity between the proteomes of ZAIRE and WRAIR strains, but could not establish any basis for clade-specific immunity. Of the 25 IgG binding proteins identified in this study, 80% were previously identified in virus particles by mass spectrometry methods [15, 16]. While no direct correlation with protein abundance and antigen recognition was found, nine of the 15 most abundant proteins (based on mol%) in IMV were targets of significant antibody binding. Many serological assays based on intact viruses cannot distinguish between closely related species [17, 18]. Our work with monkeypoxvirus demonstrated that it is possible to use microarrays of recombinant viral proteins to distinguish antibody responses to closely related viruses by including multiple probes in the analysis. The inclusion of protein panels to increase specificity of antibody measurements was further supported by studies of dengue virus infection [19]. Dengue is a mosquito-borne infection caused by four distinct serotypes of dengue virus, each comprised of ten proteins in the mature virion. As the most prevalent mosquito-borne viral disease in humans, dengue is a major urban public health problem worldwide. Several worldwide outbreaks of infection with dengue virus occurred in rapid succession over the last few years. In Central America and Mexico, traditional areas of low fatality rates, the number of deaths increased 142% in 2007 (Pan-American Health Organization data). Although several commonly used serological assays readily detect infection, cross-reactivity between strains of dengue virus is extensive. Proteins from isolates of all four dengue virus strains were cloned, baculovirus-expressed and printed in a microarray. Naïve macaques were challenged with wild-type viruses of each serotype and convalescent serum antibodies were examined. Analysis of antibody binding to a subset of dengue virus elements consisting of envelope, membrane, NS1 and NS3, or capsid proteins was sufficient to determine the identity of the infecting strain. We also compared responses of rhesus macaques vaccinated with tetravalent vaccines comprised of inactivated or live-attenuated viruses. We detected temporal increases in antibodies against envelope proteins in response to either combination vaccine, while vaccination with the live attenuated strains resulted in an additional antibody response to capsid proteins. This detailed understanding of the host response to individual components of the viral proteome is important for the overall disease control strategy to identify immune responses to specific strains in circulation and to assess vaccine efficacy in relationship to these strains.

16.5 Antigens and Proteomes of Pathogenic Bacteria

Bacterial proteomes present the greatest challenge based on size alone. For the case of gram-negative bacteria, a microarrayed panel of proteins from a reference

16.5 Antigens and Proteomes of Pathogenic Bacteria

proteome was used to identify antibody-response patterns that were unique to each of eight separate pathogens [14]. The chromosome of Y. pestis CO92 encodes approximately 3885 proteins, while an additional 181 are episomally expressed by pCD1, pMT1, and pPCP1. For comparison, the proteome of Y. pestis KIM contains 4202 individual proteins, 87% in common with CO92, and the closely related enteric pathogen Y. pseudotuberculosis contains approximately 4038 proteins (chromosome plus plasmids). The microarray was printed with over 75% of the 4066 ORFs present within the Y. pestis genome. In a manner similar to the vaccinia microarray, the Y. pestis proteins were produced as full-length polypeptides fused to GST as an affinity isolation tag. An in vitro translation method, based on E. coli lysates, was used to express the proteins in a gram-negative background. The ORF clones were fully sequenced to confirm quality and identity before use, and expressed proteins were characterized by SDS gels and Western blots (probed with anti-GST antibody). Additional proteins were included in the bacterial microarray (Figure 16.3) to aid orientation of a grid for signal measurement, as negative and positive controls, and to provide an IgG standard curve. Different approaches for studying the antibody repertoire against plague were first compared. Up to 40% of the Y. pestis proteins recognized by antibodies from infected rhesus monkeys were also observed in rabbit antibodies produced in response to total protein extracts from Y. pestis, indicating that it was not necessary for the animal model to fully reproduce the human infectious disease. In addition, there was a high degree of similarity between antibody responses to extracted

a)

b)

Alexa647 anti-mouse Ab 1

BSA gradient Anti-GST Ab gradient Calmodulin gradient GST gradient Biotin Ab gradient 2

Figure 16.3 Validation of the Yersinia pestis

protein microarray with protein–protein interaction and rabbit antisera against proteome extracts. (a) Binding of antiproteome Ig. Microarray was incubated with rabbit hyperimmune sera against the whole Y. pestis proteome (diluted 1 : 1000) and

Anti-biotin Ab V5 control gradient Human IgG gradient Y. pestis antigenic protein 1. y1349 2. y2882 bound Ig was detected with an Alexa 647-labeled goat anti-rabbit antibody and a laser confocal scanner. (b) Enlarged image of two subgrids from the microarray illustrating control proteins (colored boxes) and representative antibody binding to arrayed Y. pestis proteins (gray boxes).

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proteomes and intact bacteria. While antibodies directed against only a few antigens on the surface of the bacterium are anticipated to result in neutralization of the pathogen, many proteins are potentially available for recognition by antibodies following release or degradation of bacteria and presentation to the immune system. Yet, proteins recognized by antibodies directed against Y. pestis appear to constitute only a small percentage of the total bacterial proteome. Both categories of antigens are candidate biomarkers of infection. Convalescence sera from nonhuman primates that survived an otherwise lethal aerosol challenge with Y. pestis CO92 (plague) or Bacillus anthracis Ames spores (anthrax) were examined. A small subset of Y. pestis proteins (