Large-scale quantification of single amino-acid variations by a variation-associated database search strategy

Global quantification of the single amino-acid variations (SAAVs) is essential to investigate the roles of SAAVs in disease progression. However, few efforts have been made on this issue due to the lack of high -throughput approach. Here we presented a strategy by integration of the stable isotope dimethyl labeling with variation-associated database search to globally quantify the SAAVs at the first time. A protein database containing 87,745 amino acid variant sequences and 73,910 UniProtKB/Swiss-Prot canonical protein entries was constructed for database search, and higher energy collisional dissociation combined with collision-induced dissociation fragmentation modes were applied to improve the quantification coverage of SAAVs. Compared with target proteomics in which only a few sites could be quantified, as many as 282 unique SAAVs sites were quantified between hepatocellular carcinoma (HCC) and normal human liver tissues by our strategy. The variation rates in different samples were evaluated, and some interesting SAAVs with significant increase normalized quantification ratios, such as T1406N in CPS1 and S197R in HTATIP2, were observed to highly associate with HCC progression. Therefore, the newly developed strategy enables the large-scale comparative analysis of variations at the protein level and holds a promising future in the research related to variations.