小柯机器人

美国密歇根大学Alexey I. Nesvizhskii研究团队开发出新的N-和O-糖蛋白组学分析方法。该项研究成果于2020年10月5日在线发表在《自然—方法学》杂志上。

Title: Fast and comprehensive N - and O -glycoproteomics analysis with MSFragger-Glyco

Author: Daniel A. Polasky, Fengchao Yu, Guo Ci Teo, Alexey I. Nesvizhskii

Issue&Volume: 2020-10-05

Abstract: 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. MSFragger-Glyco allows identification of N- and O-linked glycopeptides using the localization-aware open search strategy of the MSFragger search engine.

DOI: 10.1038/s41592-020-0967-9

Source: https://www.nature.com/articles/s41592-020-0967-9

Nature Methods：《自然—方法学》，创刊于2004年。隶属于施普林格·自然出版集团，最新IF：47.99
官方网址：https://www.nature.com/nmeth/
投稿链接：https://mts-nmeth.nature.com/cgi-bin/main.plex