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

Reta Birhanu Kitata, Jhih‐Ci Yang, Yu‐Ju Chen

2022Mass Spectrometry Reviews158 citationsDOIOpen Access PDF

Abstract

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.

Topics & Concepts

Profiling (computer programming)ProteomicsChemistryMass spectrometryData acquisitionFragmentation (computing)ProteomeComputer scienceData miningComputational biologyChromatographyOperating systemBiochemistryBiologyGeneAdvanced Proteomics Techniques and ApplicationsMass Spectrometry Techniques and ApplicationsMetabolomics and Mass Spectrometry Studies
Advances in data‐independent acquisition mass spectrometry towards comprehensive digital proteome landscape | Litcius