A high-confidence human plasma proteome reference set with estimated concentrations in PeptideAtlas

TY - JOUR

T1 - A high-confidence human plasma proteome reference set with estimated concentrations in PeptideAtlas

AU - Farrah, Terry

AU - Deutsch, Eric W

AU - Omenn, Gilbert S

AU - Campbell, David S

AU - Sun, Zhi

AU - Bletz, Julie A

AU - Mallick, Parag

AU - Katz, Jonathan E

AU - Malmström, Johan

AU - Ossola, Reto

AU - Watts, Julian D

AU - Lin, Biaoyang

AU - Zhang, Hui

AU - Moritz, Robert L

AU - Aebersold, Ruedi

PY - 2011/9

Y1 - 2011/9

N2 - Human blood plasma can be obtained relatively noninvasively and contains proteins from most, if not all, tissues of the body. Therefore, an extensive, quantitative catalog of plasma proteins is an important starting point for the discovery of disease biomarkers. In 2005, we showed that different proteomics measurements using different sample preparation and analysis techniques identify significantly different sets of proteins, and that a comprehensive plasma proteome can be compiled only by combining data from many different experiments. Applying advanced computational methods developed for the analysis and integration of very large and diverse data sets generated by tandem MS measurements of tryptic peptides, we have now compiled a high-confidence human plasma proteome reference set with well over twice the identified proteins of previous high-confidence sets. It includes a hierarchy of protein identifications at different levels of redundancy following a clearly defined scheme, which we propose as a standard that can be applied to any proteomics data set to facilitate cross-proteome analyses. Further, to aid in development of blood-based diagnostics using techniques such as selected reaction monitoring, we provide a rough estimate of protein concentrations using spectral counting. We identified 20,433 distinct peptides, from which we inferred a highly nonredundant set of 1929 protein sequences at a false discovery rate of 1%. We have made this resource available via PeptideAtlas, a large, multiorganism, publicly accessible compendium of peptides identified in tandem MS experiments conducted by laboratories around the world.

AB - Human blood plasma can be obtained relatively noninvasively and contains proteins from most, if not all, tissues of the body. Therefore, an extensive, quantitative catalog of plasma proteins is an important starting point for the discovery of disease biomarkers. In 2005, we showed that different proteomics measurements using different sample preparation and analysis techniques identify significantly different sets of proteins, and that a comprehensive plasma proteome can be compiled only by combining data from many different experiments. Applying advanced computational methods developed for the analysis and integration of very large and diverse data sets generated by tandem MS measurements of tryptic peptides, we have now compiled a high-confidence human plasma proteome reference set with well over twice the identified proteins of previous high-confidence sets. It includes a hierarchy of protein identifications at different levels of redundancy following a clearly defined scheme, which we propose as a standard that can be applied to any proteomics data set to facilitate cross-proteome analyses. Further, to aid in development of blood-based diagnostics using techniques such as selected reaction monitoring, we provide a rough estimate of protein concentrations using spectral counting. We identified 20,433 distinct peptides, from which we inferred a highly nonredundant set of 1929 protein sequences at a false discovery rate of 1%. We have made this resource available via PeptideAtlas, a large, multiorganism, publicly accessible compendium of peptides identified in tandem MS experiments conducted by laboratories around the world.

KW - Algorithms

KW - Biomarkers

KW - Blood Proteins

KW - Chromatography, Liquid

KW - Databases, Protein

KW - Humans

KW - Mass Spectrometry

KW - Peptides

KW - Plasma

KW - Proteome

KW - Proteomics

KW - Reference Standards

KW - Software

KW - Trypsin

KW - Journal Article

KW - Research Support, N.I.H., Extramural

KW - Research Support, Non-U.S. Gov't

U2 - 10.1074/mcp.M110.006353

DO - 10.1074/mcp.M110.006353

M3 - Article

C2 - 21632744

VL - 10

SP - M110.006353

JO - Molecular and Cellular Proteomics

JF - Molecular and Cellular Proteomics

SN - 1535-9484

IS - 9

ER -