Amino acid-coded tagging approaches in quantitative proteomics

被引:64
作者
Chen, Xian
Sun, Liwei
Yu, Yanbao
Xue, Yan
Yang, Pengyuan
机构
[1] Fudan Univ, Inst Biomed Sci, Dept Chem, Shanghai 20003, Peoples R China
[2] Univ N Carolina, Dept Biochem & Biophys, Chapel Hill, NC 27599 USA
关键词
AACT/SILAC; comparative proteomics; dual-tagging proteomics; ICAT; iTRAQ (TM); post-translational modification; protein-protein interaction; quantitative proteomics;
D O I
10.1586/14789450.4.1.25
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
To improve the efficiency, accuracy, reproducibility, throughput and proteome coverage of mass spectrometry-based quantitative approaches, both in vitro and in vivo tagging of particular amino acid residues of cellular proteins have been introduced to assist mass spectrometry for global-scale comparative studies of differentially expressed proteins/modifications between different biologically relevant cell states or cells at different pathological states. The basic features of these methods introduce pair-wise isotope signals of each individual peptide containing a particular type of tagged amino acid (amino acid-coded mass tagging) that originated from different cell states. In this review, the applications of major amino acid-coded mass tagging-based quantitative proteomics approaches, including isotope-coded affinity tag, isobaric tags for relative and absolute quantification (iTRAQ (TM)) and stable isotope labeling by amino acids in cell culture are summarized in the context of their respective strengths/weakness in identifying those differentially expressed or post-translational modified proteins regulated by particular cellular stress on a genomic scale in a high-throughput manner. Importantly, these gel-free, in-spectra quantitative mechanisms have been further explored to identify/characterize large-scale protein-protein interactions involving various functional pathways. Taken together, the information about quantitative proteome changes, including multiple regulated proteins and their interconnected relationships, will provide an important insight into the molecular mechanisms, where novel targets for diagnosis and therapeutic intervention will be identified.
引用
收藏
页码:25 / 37
页数:13
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