Table of Contents
International Journal of Proteomics
Volume 2013, Article ID 654356, 8 pages
Research Article

Additions to the Human Plasma Proteome via a Tandem MARS Depletion iTRAQ-Based Workflow

1Department of Chemistry, University of Pittsburgh, Pittsburgh, PA 15260, USA
2The Clinical Research, Investigation, and Systems Modeling of Acute Illness (CRISMA) Laboratory Center and Department of Critical Care Medicine, University of Pittsburgh, Pittsburgh, PA 15260, USA

Received 5 October 2012; Accepted 10 January 2013

Academic Editor: Visith Thongboonkerd

Copyright © 2013 Zhiyun Cao et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Robust platforms for determining differentially expressed proteins in biomarker and discovery studies using human plasma are of great interest. While increased depth in proteome coverage is desirable, it is associated with costs of experimental time due to necessary sample fractionation. We evaluated a robust quantitative proteomics workflow for its ability (1) to provide increased depth in plasma proteome coverage and (2) to give statistical insight useful for establishing differentially expressed plasma proteins. The workflow involves dual-stage immunodepletion on a multiple affinity removal system (MARS) column, iTRAQ tagging, offline strong-cation exchange chromatography, and liquid chromatography tandem mass spectrometry (LC-MS/MS). Independent workflow experiments were performed in triplicate on four plasma samples tagged with iTRAQ 4-plex reagents. After stringent criteria were applied to database searched results, 689 proteins with at least two spectral counts (SC) were identified. Depth in proteome coverage was assessed by comparison to the 2010 Human Plasma Proteome Reference Database in which our studies reveal 399 additional proteins which have not been previously reported. Additionally, we report on the technical variation of this quantitative workflow which ranges from ±11 to 30%.