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.