State of the human proteome in 2013 as viewed through PeptideAtlas: comparing the kidney, urine, and plasma proteomes for the biology- and disease-driven Human Proteome Project.

The kidney, urine, and plasma proteomes are intimately related: proteins and metabolic waste products are filtered from the plasma by the kidney and excreted via the urine, while kidney proteins may be secreted into the circulation or released into the urine. Shotgun proteomics data sets derived from human kidney, urine, and plasma samples were collated and processed using a uniform software pipeline, and relative protein abundances were estimated by spectral counting. The resulting PeptideAtlas builds yielded 4005, 2491, and 3553 nonredundant proteins at 1% FDR for the kidney, urine, and plasma proteomes, respectively - for kidney and plasma, the largest high-confidence protein sets to date. The same pipeline applied to all available human data yielded a 2013 Human PeptideAtlas build containing 12,644 nonredundant proteins and at least one peptide for each of ∼14,000 Swiss-Prot entries, an increase over 2012 of ∼7.5% of the predicted human proteome. We demonstrate that abundances are correlated between plasma and urine, examine the most abundant urine proteins not derived from either plasma or kidney, and consider the biomarker potential of proteins associated with renal decline. This analysis forms part of the Biology and Disease-driven Human Proteome Project (B/D-HPP) and is a contribution to the Chromosome-centric Human Proteome Project (C-HPP) special issue.

[1]  Kevin C. Dorff,et al.  Urine proteomics for profiling of human disease using high accuracy mass spectrometry , 2009, Proteomics. Clinical applications.

[2]  David G Camp,et al.  Shotgun proteomics identifies proteins specific for acute renal transplant rejection , 2010, Proteomics. Clinical applications.

[3]  C. Overall,et al.  Absolute proteomic quantification of the activity state of proteases and proteolytic cleavages using proteolytic signature peptides and isobaric tags. , 2014, Journal of proteomics.

[4]  N. Anderson,et al.  The Human Plasma Proteome , 2002, Molecular & Cellular Proteomics.

[5]  E. Marcotte,et al.  Absolute protein expression profiling estimates the relative contributions of transcriptional and translational regulation , 2007, Nature Biotechnology.

[6]  Y. Oka,et al.  Human plasma epidermal growth factor/beta-urogastrone is associated with blood platelets. , 1983, The Journal of clinical investigation.

[7]  J. Buhmann,et al.  Protein Identification False Discovery Rates for Very Large Proteomics Data Sets Generated by Tandem Mass Spectrometry* , 2009, Molecular & Cellular Proteomics.

[8]  E. Avner,et al.  Segment-specific c-ErbB2 expression in human autosomal recessive polycystic kidney disease. , 2001, Journal of the American Society of Nephrology : JASN.

[9]  Cathy H. Wu,et al.  The Human Proteome Project: Current State and Future Direction , 2011, Molecular & Cellular Proteomics.

[10]  R. Aebersold,et al.  Mass spectrometry-based proteomics , 2003, Nature.

[11]  M. Mann,et al.  Quantitative analysis of the intra- and inter-individual variability of the normal urinary proteome. , 2011, Journal of proteome research.

[12]  Ruedi Aebersold,et al.  Using the Human Plasma PeptideAtlas to study human plasma proteins. , 2011, Methods in molecular biology.

[13]  B. Comte,et al.  Detection of bile salt-dependent lipase, a 110 kDa pancreatic protein, in urines of healthy subjects. , 2006, Kidney international.

[14]  Tadashi Yamamoto,et al.  Profiling and annotation of human kidney glomerulus proteome , 2013, Proteome Science.

[15]  Robert Stevens,et al.  Developing a kidney and urinary pathway knowledge base , 2011, J. Biomed. Semant..

[16]  R. Aebersold,et al.  A uniform proteomics MS/MS analysis platform utilizing open XML file formats , 2005, Molecular systems biology.

[17]  R. Harris Potential physiologic roles for epidermal growth factor in the kidney. , 1991, American journal of kidney diseases : the official journal of the National Kidney Foundation.

[18]  R. Aebersold,et al.  A High-Confidence Human Plasma Proteome Reference Set with Estimated Concentrations in PeptideAtlas* , 2011, Molecular & Cellular Proteomics.

[19]  Akhilesh Pandey,et al.  A comprehensive map of the human urinary proteome. , 2011, Journal of proteome research.

[20]  Ling Zhang,et al.  An Attempt to Understand Kidney's Protein Handling Function by Comparing Plasma and Urine Proteomes , 2009, PLoS ONE.

[21]  Eric W Deutsch,et al.  The state of the human proteome in 2012 as viewed through PeptideAtlas. , 2013, Journal of proteome research.

[22]  Patrick G. A. Pedrioli Trans-Proteomic Pipeline: A Pipeline for Proteomic Analysis , 2010, Proteome Bioinformatics.

[23]  Eugene A. Kapp,et al.  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 , 2005, Proteomics.

[24]  N. Tsuji,et al.  Olfactomedin 4 promotes S‐phase transition in proliferation of pancreatic cancer cells , 2007, Cancer science.

[25]  S. Chen,et al.  Olfactomedin 4, a novel marker for the differentiation and progression of gastrointestinal cancers. , 2011, Neoplasma.

[26]  Tadashi Yamamoto Proteomics database in chronic kidney disease. , 2010, Advances in chronic kidney disease.

[27]  Nichole L. King,et al.  Development and validation of a spectral library searching method for peptide identification from MS/MS , 2007, Proteomics.

[28]  Zerihun T. Dame,et al.  The Human Urine Metabolome , 2013, PloS one.

[29]  Andrew R. Jones,et al.  ProteomeXchange provides globally co-ordinated proteomics data submission and dissemination , 2014, Nature Biotechnology.

[30]  Jon W. Huss,et al.  BioGPS: an extensible and customizable portal for querying and organizing gene annotation resources , 2009, Genome Biology.

[31]  Nichole L. King,et al.  Human Plasma PeptideAtlas , 2005, Proteomics.

[32]  Gary D Bader,et al.  The biology/disease-driven human proteome project (B/D-HPP): enabling protein research for the life sciences community. , 2013, Journal of proteome research.

[33]  Robertson Craig,et al.  Open source system for analyzing, validating, and storing protein identification data. , 2004, Journal of proteome research.

[34]  M. Mann,et al.  A high confidence , manually validated human blood plasma protein reference set , 2008 .

[35]  Robertson Craig,et al.  TANDEM: matching proteins with tandem mass spectra. , 2004, Bioinformatics.

[36]  Rong Zeng,et al.  A comprehensive and non-prefractionation on the protein level approach for the human urinary proteome: touching phosphorylation in urine. , 2010, Rapid communications in mass spectrometry : RCM.

[37]  A. Vlahou,et al.  Analysis of the urine proteome via a combination of multi‐dimensional approaches , 2012, Proteomics.

[38]  W. Alkema,et al.  BioVenn – a web application for the comparison and visualization of biological lists using area-proportional Venn diagrams , 2008, BMC Genomics.

[39]  Robert Gentleman,et al.  Using GOstats to test gene lists for GO term association , 2007, Bioinform..

[40]  R. Aebersold,et al.  A statistical model for identifying proteins by tandem mass spectrometry. , 2003, Analytical chemistry.

[41]  S. Hanash,et al.  Challenges in deriving high-confidence protein identifications from data gathered by a HUPO plasma proteome collaborative study , 2006, Nature Biotechnology.

[42]  Bo Xu,et al.  In-depth proteomic profiling of the normal human kidney glomerulus using two-dimensional protein prefractionation in combination with liquid chromatography-tandem mass spectrometry. , 2007, Journal of proteome research.

[43]  A. Bairoch,et al.  neXtProt: organizing protein knowledge in the context of human proteome projects. , 2013, Journal of proteome research.

[44]  M. Mann,et al.  The human urinary proteome contains more than 1500 proteins, including a large proportion of membrane proteins , 2006, Genome Biology.

[45]  Uwe Völker,et al.  New loci associated with kidney function and chronic kidney disease , 2010, Nature Genetics.

[46]  E. Birney,et al.  The International Protein Index: An integrated database for proteomics experiments , 2004, Proteomics.

[47]  Natalie I. Tasman,et al.  A guided tour of the Trans‐Proteomic Pipeline , 2010, Proteomics.

[48]  Lennart Martens,et al.  The Protein Identifier Cross-Referencing (PICR) service: reconciling protein identifiers across multiple source databases , 2007, BMC Bioinformatics.

[49]  Trairak Pisitkun,et al.  Large-scale proteomics and phosphoproteomics of urinary exosomes. , 2009, Journal of the American Society of Nephrology : JASN.

[50]  G. Omenn,et al.  A first step toward completion of a genome-wide characterization of the human proteome. , 2013, Journal of proteome research.

[51]  A. Schmidtchen,et al.  Injury-induced innate immune response in human skin mediated by transactivation of the epidermal growth factor receptor. , 2006, The Journal of clinical investigation.

[52]  Nichole L. King,et al.  The PeptideAtlas Project , 2010, Proteome Bioinformatics.

[53]  B. McManus,et al.  The Human Serum Metabolome , 2011, PloS one.

[54]  Rong-Fong Shen,et al.  Identification and proteomic profiling of exosomes in human urine. , 2004, Proceedings of the National Academy of Sciences of the United States of America.

[55]  Eric W. Deutsch,et al.  Combining Results of Multiple Search Engines in Proteomics* , 2013, Molecular & Cellular Proteomics.

[56]  C. Schaefer,et al.  Analysis of the human serum proteome , 2004, Clinical Proteomics.

[57]  F. Bianchi,et al.  Immunohistochemical localization of the epidermal growth factor, transforming growth factor α, and their receptor in the human mesonephros and metanephros , 1996, Developmental dynamics : an official publication of the American Association of Anatomists.