Protein glycosylation is a heterogeneous post-translational modification with great diversity and gives rise to functional variance. Highly precise characterization of protein glycosylation at site-specific level and the proteome scale is critical. In our recent work, we proposed a series of identification strategies and searching engines: pGlyco1.0, pGlcyo2.0, pGlyco3.0 and pGlycoQuant. pGlyco 1.0 is a pipeline for the identification of intact glycopeptides by integrating HCD, CID-MS/MS and MS3, and using a novel target-decoy method to estimate the false discovery rate of the glycan identification. pGlyco 2.0 is a one-step tandem MS strategy for intact glycopeptide identification with optimized stepped-energy fragmentation and a dedicated search engine. pGlyco 2.0 is the first search engine to conduct comprehensive quality control including false discovery rate evaluation at all three levels of matches to glycans, peptides and glycopeptides, improving the current level of accuracy of intact glycopeptide identification. With pGlyco 2.0, we reported a large-scale glycoproteome dataset consisting of 10,009 distinct site-pecific N-glycans on 1988 glycosyltaion sites from 955 glycoproteins in five mouse tissues.
We then developed pGlyco 3.0, a glycan database-free algorithm. pGlyco 3.0 is the first pipeline to achieve large-scale, universal glycopeptide analysis on diverse model organisms. We have identified a total of 44,261 distinct intact glycopeptides in seven model organisms (Budding yeast, Fission yeast, Fruit fly, Nematode, Zebrafish, Mouse and Arabidopsis). pGlycoQuant was proposed to be a robust intact glycopeptide quantification tool. It enables quantification of intact glycopeptides with chemical labeling, metabolic labeling and label free method. Accurate, comprehensive quantification was conducted using pGlycoQuant and routine proteomic methods. We achieved quantification of 9140 proteins, 5384 N-glycosylation sites and 5806 intact glycopeptide in three hepatocellular carcinoma cell lines. The series glycopeptide analysis strategies enables us to be highly efficient profiling of intact glycopeptides, and provides insight into the N-glycosylation status in biological organism.