Byonic is a new proteomics search engine that can identify peptides carrying N- and O-linked glycans. Byonic offers a number of ways to search for glycopeptides, including preset glycan tables and manually entered glycan masses, and the search strategy affects the quality and quantity of spectrum assignments. Here we show how a progression of searches, from wider to narrower in both proteins and glycans, can improve sensitivity and specificity for glycopeptide identification.
We obtained data from the following samples: Glycophorin-A, PSA, human blood serum enriched for glycoproteins, and secreted proteins from human endothelial cells. All data were acquired on various Thermo Orbitrap instruments and included both HCD and ETD fragmentation. We first searched the data with a full human protein database with contaminants and decoys, and later with smaller databases produced by Byonic's “focused database” option. We started with Byonic's preset glycan search, which allows only one glycan per peptide, and then, guided by prior search results, augmented or replaced these tables with user-defined glycan modifications with appropriate limits on each type of modification.
We found that focused protein databases containing 10 – 200 proteins greatly improve the sensitivity of glycopeptide search relative to full-database searches. We found a database of likely glycoproteins, determined by PNG-ase release of N-glycans in O18 water, helpful for identifying glycopeptides carrying single N-linked glycans in the endothelial secretome. Focused glycan lists also improve sensitivity, and make possible still more complex searches. We have identified glycopeptides carrying up to two N-glycans, one N-glycan and one O-glycan, and up to four O-glycans, with only minor ambiguities in modification placement and mass distribution. More complex searches, for example, five or more O-glycans, will require improvements in completeness of fragmentation and computational methods.