Quantitative proteomics: challenges and opportunities in basic and applied research

被引:174
作者
Schubert, Olga T. [1 ]
Rost, Hannes L. [2 ]
Collins, Ben C. [3 ]
Rosenberger, George [3 ]
Aebersold, Ruedi [3 ,4 ]
机构
[1] Univ Calif Los Angeles, Dept Human Genet, Los Angeles, CA USA
[2] Stanford Univ, Dept Genet, Stanford, CA 94305 USA
[3] ETH, Inst Mol Syst Biol, Dept Biol, Zurich, Switzerland
[4] Univ Zurich, Fac Sci, Zurich, Switzerland
基金
瑞士国家科学基金会;
关键词
DATA-INDEPENDENT ACQUISITION; MASS-SPECTROMETRY; LIQUID-CHROMATOGRAPHY; PROTEIN COMPLEXES; ABSOLUTE QUANTIFICATION; PEPTIDE IDENTIFICATION; BIOMARKER SIGNATURES; TARGETED ANALYSIS; CROSS-LINKING; CELL;
D O I
10.1038/nprot.2017.040
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
Proteins constitute a large part of the molecular machinery of the cell and are the major class of biomolecules targeted by drugs. Organized in functional modules and networks, they carry out cellular functions and determine phenotypes by means of coordinated activities of a multitude of molecular species(1). Traditional biochemical methods for studying proteins have been highly biased toward a relatively small subset of proteins for which high-quality, mainly antibody-based assays have been available(2). Over the past two decades, mass spectrometry (MS)-based methods have emerged as the method of choice for the confident and near-exhaustive identification and quantification of the proteins contained in a biological sample, and have significantly contributed to the unraveling of cellular signaling networks, elucidation of the dynamics of protein-protein interactions in different cellular states, and improved diagnosis and molecular understanding of disease mechanisms. Overall, MS-based proteomics can reveal the quantitative state of a proteome, and thereby provides insights into the biochemical state of the relevant cell or tissue. In the following paragraphs, we discuss important concepts and developments in proteomics technology and explore the current and future roles of quantitative proteomics in molecular systems biology as well as in clinical research and personalized medicine.
引用
收藏
页码:1289 / 1294
页数:6
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