Accurate Precursor Mass Assignment Improves Peptide Identification in Data-Independent Acquisition Mass Spectrometry.

Proteomics research today no longer simply seeks exhaustive protein identification; increasingly, it is also desirable to obtain robust, large-scale quantitative information. To accomplish this, data-independent acquisition (DIA) has emerged as a promising strategy largely owing to developments in advanced mass spectrometers and sophisticated data analysis methods. Nevertheless, the highly complex multiplexed MS/MS spectra produced by DIA remain challenging to interpret. Here, we present a novel strategy to analyze DIA data, based on unambiguous precursor mass assignment through the mPE-MMR (multiplexed post-experimental monoisotopic mass refinement) procedure and combined with complementary multistage database searching. Compared to conventional spectral library searching, the accuracy and sensitivity of peptide identification were significantly increased by incorporating precise precursor masses in DIA data. We demonstrate identification of additional peptides absent from spectral libraries, including sample-specific mutated peptides and post-translationally modified peptides using MS-GF+ and MODa/MODi multistage database searching. This first use of unambiguously determined precursor masses to mine DIA data demonstrates considerable potential for further exploitation of this type of experimental data.