Mass Spectrometry-based Protein Site-Specific Glycosylation Analysis
Despite significant recent advances in mass spectrometry (MS)-based protein site-specific glycosylation analysis and glycoproteomics, confident identification of glycopeptides is still far from routine. Current practice utilizes high end MS instrument to acquire as many MS2 throughout an LC-MS/MS run and then subject the processed glycopeptide MS2 dataset to database search, followed by scoring and assigning the best matched glycan composition and peptide backbone combination.
Despite significant recent advances in mass spectrometry (MS)-based protein site-specific glycosylation analysis and glycoproteomics, confident identification of glycopeptides is still far from routine. Current practice utilizes high end MS instrument to acquire as many MS2 throughout an LC-MS/MS run and then subject the processed glycopeptide MS2 dataset to database search, followed by scoring and assigning the best matched glycan composition and peptide backbone combination.
- The commercially available computational tool, Byonic, is among the most commonly used software that is applicable to both N- and O-glycopeptides. It can search for N- and O-glycopeptides separately or simultaneously. For N-glycopeptides, Y1 ion is considered and scored but not used as a pre-requisite to fix the peptide backbone, thus allowing variables on both peptide and glycan moieties. Overall, it is powerful and reliable when stringent cut-off criteria is applied, but typcially contains many mis-assignments particularly on the glycan part.
- The newly introduced pGlyco3 is one of those that offers great potentials to complement Byonic by taking a different glycan-first search strategy. It reflects a growing need to better address the accuracy of glycan assignment instead of reporting as many total hits.
- We have set out to investigate how pGlyco3 can be best utilized to corroborate or otherwise refute the positive spectrum matches from search results of Byonic. For O-glycopeptides, we have additionally evaluated O-pair search, which was specifically developed for handling multiply O-glycosylated peptides from mucin, with great emphasis on site localization.
- Features investigated include those contributing to unique positive matches by one but not the other software, discrepancies in assigned glycan/peptide combination for the same MS2 scan, merging of HCD and EThcD spectra derived from the same glycopeptide precursors prior to searching versus post-search/identification pairing, efficiency in handling multiply N- and/or O-glycosylated peptide, and site localization.
- Above all, data analysis workflow was developed to seamlessly incorporate results output from both software for cross validation.
