Literature DB >> 24828403

Deep proteomic profiling of human carotid atherosclerotic plaques using multidimensional LC-MS/MS.

Piliang Hao1, Yan Ren, Gerard Pasterkamp, Frans L Moll, Dominique P V de Kleijn, Siu Kwan Sze.   

Abstract

PURPOSE: To increase the proteome coverage of human atherosclerotic plaques and identify low-abundance proteins that may have important functions during the development and progression of atherosclerosis. EXPERIMENTAL
DESIGN: Thirty-eight human carotid atherosclerotic plaques were pooled into two samples and analyzed in triplicate using offline multidimensional LC-MS/MS. The collected fractions of trypsin-digested peptides from Electrostatic Repulsion-Hydrophilic Interaction Chromatography (ERLIC) were analyzed by LC-MS/MS on a Q Exactive (Thermo Fisher, MA, USA).
RESULTS: A total of 4702 proteins were identified from atherosclerotic plaques at a false discovery rate (FDR) of 1%, of which 3846 were identified with at least 2 unique peptides. Many pathways related to the development and progression of atherosclerosis were identified, such as atherosclerosis signaling, toll receptor signaling pathway and inhibition of matrix metalloproteases. Many low-abundance proteins with important functions in atherosclerosis that were previously unidentifiable using mass spectrometry based proteomics methods, such as TGF-β, interleukins and other growth factors, were identified confidently from plaques. CONCLUSIONS AND CLINICAL RELEVANCE: This study has substantially increased the coverage of the atherosclerotic plaque proteome which represents a leap forward in understanding of plaque composition, development and progression. The identification of many low-abundance proteins may also facilitate biomarker discovery.
© 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Entities:  

Keywords:  Atherosclerotic plaques; Biomarkers; Carotid arteries

Mesh:

Year:  2014        PMID: 24828403     DOI: 10.1002/prca.201400007

Source DB:  PubMed          Journal:  Proteomics Clin Appl        ISSN: 1862-8346            Impact factor:   3.494


  6 in total

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