An NGS-Independent Strategy for Proteome-Wide Identification of Single Amino Acid Polymorphisms by Mass Spectrometry

Detection
of proteins containing single amino acid polymorphisms
(SAPs) encoded by nonsynonymous SNPs (nsSNPs) can aid researchers
in studying the functional significance of protein variants. Most
proteogenomic approaches for large-scale SAPs mapping require construction
of a sample-specific database containing protein variants predicted
from the next-generation sequencing (NGS) data. Searching shotgun
proteomic data sets against these NGS-derived databases allowed for
identification of SAP peptides, thus validating the proteome-level
sequence variation. Contrary to the conventional approaches, our study
presents a novel strategy for proteome-wide SAP detection without
relying on sample-specific NGS data. By searching a deep-coverage
proteomic data set from an industrial thermotolerant yeast strain
using our strategy, we identified 337 putative SAPs compared to the
reference genome. Among the SAP peptides identified with stringent
criteria, 85.2% of SAP sites were validated using whole-genome sequencing
data obtained for this organism, which indicates high accuracy of
SAP identification with our strategy. More interestingly, for certain
SAP peptides that cannot be predicted by genomic sequencing, we used
synthetic peptide standards to verify expression of peptide variants
in the proteome. Our study has provided a unique tool for proteogenomics
to enable proteome-wide direct SAP identification and capture nongenetic
protein variants not linked to nsSNPs.