Exploring the Human Plasma Proteome

by Editor: Gilbert S. Omenn (University of Michigan, Ann Arbor, USA)

• ISBN13: 9783527317578
• ISBN10: 3527317570
• Edition: 1st
• Format: Hardcover
• Copyright: 2006-12-01
• Publisher: Blackwell Pub

Summary

On the cutting edge of medical diagnostics, plasma proteomics promises to generate a new wave of technologies to help identify many different diseases and disease risks.Plasma and serum are the preferred non-invasive specimens to test normal individuals, at-risk groups, and patients for protein biomarkers discovered and validated to reflect physiological, pathological, and pharmacological phenotypes. These specimens present enormous challenges due to extreme complexity, huge dynamic range in protein concentrations, non-standardized methods of sample processing, and intra- and inter-individual variation from genetics, diet, smoking, hormones, and other sources. This book presents the major findings from the collaborative Plasma Proteome Project organized by the international Human Proteome Organization (HUPO). The chapters are drawn from a larger set of publications in the journal PROTEOMICS. This book provides a valuable foundation for development and applications of proteomics.

Author Biography

Gilbert S. Omenn is Professor of Internal Medicine, Human Genetics, and Public Health and director of the Center for Computational Medicine and Biology at the University of Michigan. Since 2002 he has led the international Human Proteome Organization (HUPO) Human Plasma Proteome Project and the Michigan Proteomics Alliance for Cancer Research. Omenn is the author of 425 research papers and scientific reviews and author/editor of 18 books. A longtime director of Amgen, Inc, and of Rohm & Haas Company, he chaired the Presidential/Congressional Commission on Risk Assessment and Risk Management ("Omenn Commission") and the NAS/NRC/IOM Committee on Science, Engineering and Public Policy, and served as president of the American Association for the Advancement of Science (AAAS).

Table of Contents

Overview of the HUPO Plasma Proteome Project: Results from the pilot phase with 35 collaborating laboratories and multiple analytical groups, generating a core dataset of 3020 proteins and a publicly-available database	p. 1
Introduction	p. 2
PPP reference specimens	p. 4
Bioinformatics and technology platforms	p. 5
Constructing a PPP database for human plasma and serum proteins	p. 5
Analysis of confidence of protein identifications	p. 14
Quantitation of protein concentrations	p. 15
Comparing the specimens	p. 17
Choice of specimen and collection and handling variables	p. 17
Depletion of abundant proteins followed by fractionation of intact proteins	p. 19
Comparing technology platforms	p. 22
Alternative search algorithms for peptide and protein identification	p. 23
Independent analyses of raw spectra or peaklists	p. 24
Comparisons with published reports	p. 25
Direct MS (SELDI) analyses	p. 27
Annotation of the HUPO PPP core dataset(s)	p. 27
Identification of novel peptides using whole genome ORF search	p. 30
Identification of microbial proteins in the circulation	p. 30
Discussion	p. 31
References	p. 33
Data management and preliminary data analysis in the pilot phase of the HUPO Plasma Proteome Project	p. 37
Introduction	p. 37
Materials and methods	p. 39
Development of the data model	p. 39
Laboratory	p. 39
Experimental protocol	p. 39
Protein identification data set	p. 39
Peak list	p. 41
Summary of technologies and resources	p. 41
MS/MS spectra	p. 41
SELDI peak list	p. 42
Data submission process	p. 42
Design of the data repository	p. 42
Receipt of the data	p. 43
Inference from peptide level to protein level	p. 44
Summary of contributed data	p. 46
Cross-laboratory comparison, confidence of the identifications	p. 49
False-positive identifications	p. 51
Data dissemination	p. 56
Discussion	p. 57
Concluding remarks	p. 58
Computer technologies applied	p. 60
References	p. 61
HUPO Plasma Proteome Project specimen collection and handling: Towards the standardization of parameters for plasma proteome samples	p. 63
Introduction	p. 63
Materials and methods	p. 65
HUPO reference sample collection protocol	p. 65
Differential peptide display	p. 66
Stability studies and SELDI analysis	p. 66
SDS-Page analysis for stability studies	p. 67
2-DE for stability studies	p. 67
SELDI-TOF analysis for protease inhibitor studies	p. 67
2-DE for plasma protease inhibition studies	p. 68
Tryptic digestion and protein identification for protease inhibition studies	p. 69
Antibody microarray analysis using two-color rolling circle amplification	p. 69
Results	p. 69
Comparisons of specimen types	p. 71
Analysis of serum	p. 71
Analysis of plasma	p. 71
Evaluation of storage and handling conditions	p. 71
Evaluations of the use of protease inhibitors	p. 73
Analysis with SELDI-TOF MS of "time zero" effects of protease inhibitors in plasma	p. 73
Analysis by 2-DE	p. 73
Analysis with antibody arrays	p. 76
Discussion	p. 77
Other pre-analytical variables and control considerations	p. 83
Reference materials	p. 84
Concluding remarks	p. 87
References	p. 88
Immunoassay and antibody microarray analysis of the HUPO Plasma Proteome Project reference specimens: Systematic variation between sample types and calibration of mass spectrometry data	p. 91
Introduction	p. 92
Materials and methods	p. 93
Reference specimens	p. 93
DB immunoassays	p. 93
Antibody arrays at GNF	p. 94
Antibodies, reagents, microarray printing, and platform	p. 94
Microarray layout and processing	p. 94
Array imaging and data analysis	p. 95
Antibody microarrays at MSI	p. 95
Chip manufacture	p. 95
Rolling circle amplification (RCA) immunoassay	p. 96
Conversion of mean fluorescent intensity to concentration	p. 96
Antibody microarrays at VARI	p. 96
Fabrication of antibody microarrays	p. 96
Serum labeling	p. 97
Processing of antibody microarrays	p. 97
Analysis	p. 97
Retrieval and matching of IPI numbers for the analytes	p. 97
Results	p. 98
Antibody-based measurements of the HUPO reference specimens	p. 98
Systematic variation between the preparation methods of the PPP reference specimens	p. 100
Consistent alterations in specific protein abundances	p. 107
Linkage of MS data and antibody-based measurements	p. 108
Discussion	p. 110
References	p. 113
Depletion of multiple high-abundance proteins improves protein profiling capacities of human serum and plasma	p. 115
Introduction	p. 116
Materials and methods	p. 117
Serum/plasma collection	p. 117
MARS	p. 118
Multiple affinity removal spin cartridge	p. 118
Microscale solution IEF (MicroSol IEF) (ZOOM-IEF) fractionation	p. 118
2-DE	p. 119
LC-MS/MS	p. 119
Results	p. 120
Depletion of major proteins to enhance detection of lower abundance proteins	p. 120
Evaluation of high-abundance protein removal using 2-DE	p. 121
Specificity of major protein depletion	p. 123
Impact of Top-6 protein depletion on detection of lower abundance proteins using 2-D gels	p. 125
Combining Top-6 protein depletion with microSol IEF prefractionation and narrow pH range gels	p. 125
Analysis of Top-6 depleted serum and plasma using protein array pixelation	p. 128
Discussion	p. 130
References	p. 134
A novel four-dimensional strategy combining protein and peptide separation methods enables detection of low-abundance proteins in human plasma and serum proteomes	p. 135
Introduction	p. 135
Materials and methods	p. 138
Materials	p. 138
Top six protein depletion	p. 138
MicroSol-IEF fractionation	p. 139
Protein array pixelation	p. 139
LC-ESI-MS/MS methods	p. 140
Data analysis	p. 140
Results and discussion	p. 141
Protein array pixelation strategy	p. 141
Optimization of protein array pixelation	p. 143
Total analysis time for protein array pixelation of human plasma proteome	p. 146
Systematic protein array pixelation of the human plasma proteome	p. 147
Systematic protein array pixelation of the human serum proteome	p. 150
Analyses of human plasma and serum proteomes using HUPO filter criteria	p. 153
Concluding remarks	p. 157
References	p. 157
A study of glycoproteins in human serum and plasma reference standards (HUPO) using multilectin affinity chromatography coupled with RPLC-MS/MS	p. 159
Introduction	p. 159
Materials and methods	p. 160
Materials	p. 160
Isolating glycoproteins using multilectin affinity columns	p. 161
Analysis of glycoproteins on LC-LCQ MS	p. 161
Analysis of glycoproteins on LC-LTQ MS	p. 162
Protein database search	p. 162
Results and discussion	p. 162
Protein IDs from the plasma and serum samples	p. 162
Comparison between serum and plasma glycoproteomes	p. 179
Comparison of the glycoproteins present in the samples collected from three ethnic groups	p. 179
Concluding remarks	p. 182
References	p. 183
Evaluation of prefractionation methods as a preparatory step for multidimensional based chromatography of serum proteins	p. 185
Introduction	p. 185
The HUPO Plasma Proteome Project (PPP) goals and the serum as a complex sample	p. 185
The scope of this manuscript	p. 187
Materials and methods	p. 187
Depletion from serum albumin and antibodies	p. 187
MudPIT and mass segmentation	p. 187
Protein separation by SDS-PAGE	p. 188
SCX separation of intact proteins followed by MudPIT	p. 188
Liquid-phase IEF followed by MudPIT	p. 188
Capillary RP-LC-MS/MS	p. 189
MS data processing and peptide/protein identifications	p. 189
Results	p. 189
Comparisons between the prefractionation methods	p. 190
Identification of different protein subsets	p. 191
Proteins identified by only one prefractionation method	p. 193
Different methods resulted in diverse peptide coverage	p. 193
Discussion	p. 196
Giving every peptide a chance	p. 196
How to identify more of the marginal proteins	p. 197
Clustering and comparing raw data	p. 197
High throughput and ruggedness versus high sensitivity	p. 197
The cost effectiveness of the different methods	p. 198
Concluding remarks	p. 198
References	p. 199
Efficient prefractionation of low-abundance proteins in human plasma and construction of a two-dimensional map	p. 201
Introduction	p. 202
Materials and methods	p. 203
Plasma sample preparation	p. 203
Depletion of major abundance proteins with an immunoaffinity column	p. 203
2-DE	p. 204
Identification of proteins by MS	p. 204
Fractionation of the plasma samples by FFE	p. 204
LC-MS/MS	p. 205
Bioinformatics	p. 206
Results and discussion	p. 206
2-DE map of human plasma devoid of high-abundance proteins	p. 206
Expression of different anticoagulant-treated plasma	p. 214
FFE/1-DE/nanoLC-MS/MS and 2-DE/MALDI-TOF	p. 215
Concluding remarks	p. 239
References	p. 219
Comparison of alternative analytical techniques for the characterisation of the human serum proteome in HUPO Plasma Proteome Project	p. 221
Introduction	p. 222
Materials and methods	p. 223
Materials	p. 223
Human serum samples	p. 223
Integrated strategy for characterising analytical approaches	p. 223
Depletion of the highly abundant serum proteins by MARS	p. 224
Desalting and concentrating the flow-through fractions by centrifugal ultrafiltration	p. 224
Fractionation of depleted serum samples by anion-exchange HPLC	p. 225
Protein fractionation by 2-D HPLC with nonporous RP-HPLC	p. 225
The 2-DE strategy for the analysis of serum proteins	p. 226
2-DE	p. 226
In-gel digestion via automated workstation	p. 227
Protein spot identification by MALDI-TOF-MS/MS	p. 227
Shotgun strategy for the analysis of serum proteins	p. 228
Trypsin digestion of serum proteins	p. 228
Protein identification by micro2-D LC-ESI-MS/MS	p. 228
Data processing	p. 229
Protein fractionation strategy for the analysis of serum proteins	p. 229
2-D LC fractionation of serum proteins	p. 229
Digestion of the 2-D LC separated fractions	p. 229
1-D microRP-HPLC-ESI-MS/MS identification of digested serum proteins	p. 230
Offline shotgun strategy for the analysis of serum proteins	p. 230
Offline SCX for first-dimension chromatographic separation of peptides	p. 230
1-D capillary RP-HPLC/microESI-IT-MS/MS analysis for the SCX-separated peptide fractions	p. 231
Optimised nanoRP-HPLC-nanoESI-IT-MS/MS for the reanalysis of offline SCX-separated peptides (offline-nanospray strategy)	p. 231
Integrated analysis of the whole data sets	p. 231
Protein grouping analysis	p. 231
Sequence clustering	p. 232
Results and discussion	p. 233
Depletion of the highly abundant serum proteins	p. 233
The 2-DE strategy for the analysis of serum proteins	p. 233
2-D HPLC fractionation for the analysis of serum proteins	p. 234
Shotgun strategy for the analysis of serum proteins with online SCX	p. 237
Shotgun strategy for the analysis of serum proteins with offline SCX	p. 237
Offline SCX shotgun-nanospray strategy for the analysis of serum proteins	p. 239
Comparison of the five strategies for the analysis of the human serum proteome	p. 241
Concluding remarks	p. 246
References	p. 246
A proteomic study of the HUPO Plasma Proteome Project's pilot samples using an accurate mass and time tag strategy	p. 249
Introduction	p. 250
Materials and methods	p. 251
Human blood serum and plasma	p. 251
Depletion of Igs and trypsin digestion	p. 252
Peptide cleanup	p. 252
Capillary RP-LC	p. 253
IT-MS	p. 254
SEQUEST identification of peptides	p. 254
Putative mass and time tag database from SEQUEST results	p. 254
FT-ICR-MS	p. 255
cLC-FT-ICR MS data analysis	p. 255
OmniViz cluster and visual analysis	p. 257
Results	p. 257
PuMT tag database	p. 257
Summary of peptide/protein identifications by AMT tags	p. 258
Protein concentration estimates from ion current	p. 260
Global protein analysis	p. 261
Discussion	p. 264
Application of FT-ICR MS as a proteomic technology bridge	p. 264
Confidence in any MS-based proteomic approach	p. 266
Peptide/protein redundancy	p. 267
Identification sensitivity versus specificity	p. 267
Throughput and differential analysis	p. 269
References	p. 270
Analysis of Human Proteome Organization Plasma Proteome Project (HUPO PPP) reference specimens using surface enhanced laser desorption/ionization-time of flight (SELDI-TOF) mass spectrometry: Multi-institution correlation of spectra and identification of biomarkers	p. 273
Introduction	p. 273
Materials and methods	p. 275
Sample preparation	p. 275
Sample preprocessing	p. 275
Target (CM10) chip preparation and sample incubation	p. 275
Scanning protocol	p. 276
Data processing	p. 276
Bioinformatics analysis of data and correlation coefficient matrix	p. 276
Protein purification, SDS-PAGE analysis, and extraction of proteins	p. 276
Peptide mass fingerprinting (PMF)	p. 277
MS/MS analysis	p. 277
Western blot analysis	p. 277
Results	p. 278
Discussion	p. 283
References	p. 286
An evaluation, comparison, and accurate benchmarking of several publicly available MS/MS search algorithms: Sensitivity and specificity analysis	p. 289
Introduction	p. 289
Heuristic algorithms	p. 291
Probabilistic algorithms	p. 292
Materials and methods	p. 292
HUPO-PPP reference specimens	p. 292
Sample preparation and MS analysis	p. 293
Protein sequence databases	p. 293
MS/MS database search strategy	p. 293
SEQUEST and MASCOT workflow performed by the JPSL research group	p. 294
SEQUEST and PeptideProphet workflow performed by the ISB research group	p. 294
Spectrum Mill workflow performed by the Agilent group	p. 295
Sonar and X!Tandem workflow performed by David Fenyo	p. 295
Web interface for data validation, integration, and cross annotation	p. 295
ROC curve generation	p. 297
Results and discussion	p. 298
Comparison of MS/MS search algorithms	p. 299
Sensitivity and concordance between MS/MS search algorithms	p. 299
Specificity and discriminatory power of the primary score statistic for the different MS/MS search algorithms: Distribution of scores and ROC plots	p. 301
Calculation of score thresholds based on specified FP identification error rates	p. 304
Benchmarking of the different MS/MS search algorithms at 1% FP error rate	p. 310
Effect of database size and search strategy	p. 311
Utility of reversed sequence searches	p. 311
Consensus scoring between MS/MS search algorithms	p. 312
Concluding remarks	p. 313
References	p. 314
Human Plasma PeptideAtlas	p. 317
References	p. 322
Do we want our data raw? Including binary mass spectrometry data in public proteomics data repositories	p. 323
References	p. 328
A functional annotation of subproteomes in human plasma
Introduction	p. 330
Materials and methods	p. 330
Coagulation pathway and protein interaction network analysis	p. 331
Gene ontology annotations	p. 331
Analysis of MS-derived data for identification of proteolytic events and post-translational modifications	p. 331
Results and discussion	p. 331
Bioinformatic analyses of the functional subproteomes	p. 332
An interaction map of human plasma proteins	p. 332
Gene Ontology annotation of protein function	p. 334
Proteins involved in the blood coagulation pathway	p. 335
Proteins potentially derived from mononuclar phagocytes	p. 337
Proteins involved in inflammation	p. 338
Analyzing the peptide subproteome of human plasma	p. 339
Liver related plasma proteins	p. 339
Cardiovascular system related plasma proteins	p. 341
Glycoproteins	p. 342
DNA-binding proteins	p. 342
Histones	p. 343
Helicases	p. 344
Zinc finger proteins	p. 345
Annotation through reanalysis of mass spectrometry data	p. 345
Cleavage of signal peptides and transmembrane domains	p. 346
Identification of PTMs	p. 347
Concluding remarks	p. 348
References	p. 349
Cardiovascular-related proteins identified in human plasma by the HUPO Plasma Proteome Project Pilot Phase	p. 353
Introduction	p. 353
HUPO Plasma Proteome Project pilot phase	p. 354
Need for novel insights into cardiovascular disease	p. 354
Materials and methods	p. 355
Groups of cardiovascular-related proteins	p. 356
Markers of inflammation and CVD	p. 356
Vascular and coagulation proteins	p. 357
Signaling proteins	p. 359
Growth- and differentiation-associated proteins	p. 360
Cytoskeletal proteins	p. 360
Transcription factors	p. 361
Channel and receptor proteins	p. 363
Heart failure- and remodeling-related proteins	p. 364
A Functional analyses and implications	p. 365
Organ specific cardiovascular-related proteins in plasma	p. 365
Novel cardiovascular-related proteins identified in plasma	p. 366
Methodology considerations	p. 368
Conclusions and future directions	p. 368
References	p. 370
Table of Contents provided by Ingram. All Rights Reserved.