High dynamic range characterization of the trauma patient plasma proteome

Tao Liu, Wei Jun Qiant, Marina A. Gritsenko, Wenzhong Xiao, Lyle L. Moldawer, Amit Kaushal, Matthew E. Monroe, Susan M. Varnum, Ronald J. Moore, Samuel O. Purvine, Ronald V. Maier, Ronald W. Davis, Ronald G. Tompkins, David G. Camp, Richard D. Smith, Henry V. Baker, Paul E. Bankey, Timothy R. Billiar, Bernard H. Brownstein, Steve E. CalvanoCeleste Campbell-Finnerty, George Casella, Irshad H. Chaudry, Mashkoor Choudhry, J. Perren Cobb, Asit De, Constance Elson, Bradley Freeman, Richard L. Gamelli, Nicole S. Gibran, Brian G. Harbrecht, Douglas L. Hayden, David N. Herndon, Jureta W. Horton, William Hubbard, John Lee Hunt, Jeffrey L. Johnson, Matthew B. Klein, James A. Lederer, Tanya Logvinenko, Stephen F. Lowry, John A. Mannick, Philip H. Mason, Grace P. McDonald-Smith, Bruce McKinley, Carol L. Miller-Graziano, Michael Mindrinos, Joseph P. Minei, Ernest E. Moore, Fredrick A. Moore, Avery B. Nathens, Grant E. O'Keefe, Laurence G. Rahme, Daniel G. Remick, David Schoenfeld, Michael B. Shapiro, Martin Schwacha, Geoffrey M. Silver, John Storey, Mehmet Toner, H. Shaw Warren, Michael A. West

Research output: Contribution to journalArticle

123 Scopus citations

Abstract

Although human plasma represents an attractive sample for disease biomarker discovery, the extreme complexity and large dynamic range in protein concentrations present significant challenges for characterization, candidate biomarker discovery, and validation. Herein we describe a strategy that combines immunoaffinity subtraction and subsequent chemical fractionation based on cysteinyl peptide and N-glycopeptide captures with two-dimensional LC-MS/MS to increase the dynamic range of analysis for plasma. Application of this "divide-and-conquer" strategy to trauma patient plasma significantly improved the overall dynamic range of detection and resulted in confident identification of 22,267 unique peptides from four different peptide populations (cysteinyl peptides, non-cysteinyl peptides, N-glycopeptides, and non-glycopeptides) that covered 3654 different proteins with 1494 proteins identified by multiple peptides. Numerous low abundance proteins were identified, exemplified by 78 "classic" cytokines and cytokine receptors and by 136 human cell differentiation molecules. Additionally a total of 2910 different N-glycopeptides that correspond to 662 N-glycoproteins and 1553 N-glycosylation sites were identified. A panel of the proteins identified in this study is known to be involved in inflammation and immune responses. This study established an extensive reference protein database for trauma patients that provides a foundation for future high throughput quantitative plasma proteomic studies designed to elucidate the mechanisms that underlie systemic inflammatory responses.

Original languageEnglish
Pages (from-to)1899-1913
Number of pages15
JournalMolecular and Cellular Proteomics
Volume5
Issue number10
DOIs
StatePublished - Oct 1 2006
Externally publishedYes

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    Liu, T., Qiant, W. J., Gritsenko, M. A., Xiao, W., Moldawer, L. L., Kaushal, A., Monroe, M. E., Varnum, S. M., Moore, R. J., Purvine, S. O., Maier, R. V., Davis, R. W., Tompkins, R. G., Camp, D. G., Smith, R. D., Baker, H. V., Bankey, P. E., Billiar, T. R., Brownstein, B. H., ... West, M. A. (2006). High dynamic range characterization of the trauma patient plasma proteome. Molecular and Cellular Proteomics, 5(10), 1899-1913. https://doi.org/10.1074/mcp.M600068-MCP200