Advances in data-independent acquisition mass spectrometry towards comprehensive digital proteome landscape

被引:80
作者
Kitata, Reta Birhanu [1 ]
Yang, Jhih-Ci [1 ,2 ,3 ,4 ]
Chen, Yu-Ju [1 ,2 ,3 ,5 ]
机构
[1] Acad Sinica, Inst Chem, Taipei 11529, Taiwan
[2] Acad Sinica, Taiwan Int Grad Program, Sustainable Chem Sci & Technol, Taipei, Taiwan
[3] Natl Yang Ming Chiao Tung Univ, Taipei, Taiwan
[4] Natl Yang Ming Chiao Tung Univ, Dept Appl Chem, Hsinchu, Taiwan
[5] Natl Taiwan Univ, Dept Chem, Taipei, Taiwan
关键词
data-independent acquisition (DIA); mass spectrometry; proteomics; RETENTION TIME; TARGETED ANALYSIS; PROCESSING STRATEGIES; AFFINITY PURIFICATION; DIA-MS; QUANTIFICATION; PEPTIDE; IDENTIFICATION; LIBRARY; CANCER;
D O I
10.1002/mas.21781
中图分类号
O433 [光谱学];
学科分类号
0703 ; 070302 ;
摘要
The data-independent acquisition mass spectrometry (DIA-MS) has rapidly evolved as a powerful alternative for highly reproducible proteome profiling with a unique strength of generating permanent digital maps for retrospective analysis of biological systems. Recent advancements in data analysis software tools for the complex DIA-MS/MS spectra coupled to fast MS scanning speed and high mass accuracy have greatly expanded the sensitivity and coverage of DIA-based proteomics profiling. Here, we review the evolution of the DIA-MS techniques, from earlier proof-of-principle of parallel fragmentation of all-ions or ions in selected m/z range, the sequential window acquisition of all theoretical mass spectra (SWATH-MS) to latest innovations, recent development in computation algorithms for data informatics, and auxiliary tools and advanced instrumentation to enhance the performance of DIA-MS. We further summarize recent applications of DIA-MS and experimentally-derived as well as in silico spectra library resources for large-scale profiling to facilitate biomarker discovery and drug development in human diseases with emphasis on the proteomic profiling coverage. Toward next-generation DIA-MS for clinical proteomics, we outline the challenges in processing multi-dimensional DIA data set and large-scale clinical proteomics, and continuing need in higher profiling coverage and sensitivity.
引用
收藏
页码:2324 / 2348
页数:25
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