Recent advances in methods for enrichment and mass spectrometric analysis of intact glycopeptides have produced large-scale glycoproteomics datasets, but interpreting these data remains challenging. We present MSFragger-Glyco, a glycoproteomics mode of the MSFragger search engine, for fast and sensitive identification of N- and O-linked glycopeptides and open glycan searches. Reanalysis of recent N-glycoproteomics data resulted in annotation of 80% more glycopeptide spectrum matches (glycoPSMs) than previously reported. In published O-glycoproteomics data, our method more than doubled the number of glycoPSMs annotated when searching the same glycans as the original search, and yielded 4- to 6-fold increases when expanding searches to include additional glycan compositions and other modifications. Expanded searches also revealed many sulfated and complex glycans that remained hidden to the original search. With greatly improved spectral annotation, coupled with the speed of index-based scoring, MSFragger-Glyco makes it possible to comprehensively interrogate glycoproteomics data and illuminate the many roles of glycosylation.

完整糖肽的富集和质谱分析方法的最新进展已经产生了大规模的糖蛋白组学数据集，但是解释这些数据仍然具有挑战性。我们提出了MSFragger-Glyco，一种MSFragger搜索引擎的糖蛋白质组学模式，用于快速灵敏地鉴定N-和O-连接的糖肽并进行开放式聚糖搜索。重新分析最近的N-糖代谢组学数据导致注释的糖肽谱匹配数（glycoPSM）比以前报道的多80％。在已出版的O中-glycoproteomics数据，当我们搜索与原始搜索相同的聚糖时，我们的方法所标注的glycoPSM的数量增加了一倍以上，而当扩展搜索以包括其他聚糖组成和其他修饰时，我们的方法将生成的PSPS增加了4至6倍。扩大的搜索范围还显示出许多硫酸化和复杂的聚糖，它们仍然保留在原始搜索范围内。MSFragger-Glyco极大地改善了光谱注释，并结合了基于索引的评分速度，从而可以全面询问糖蛋白组学数据并阐明糖基化的许多作用。