糖蛋白组学
糖基化
糖肽
聚糖
糖蛋白
串联质谱法
质谱法
化学
串联质量标签
计算生物学
色谱法
蛋白质组学
生物化学
定量蛋白质组学
生物
基因
抗生素
作者
Meizhe Wang,Asif Shajahan,Lauren E. Pepi,Parastoo Azadi,Joseph Zaia
摘要
Abstract Identification of N ‐ and O ‐glycosylation on specific sites of proteins, along with glycan structural information, is necessary to determine the roles glycoproteins play in normal and pathologic cellular functions. Because such glycosylation is macro‐ and micro‐heterogeneous and alters the dissociation behavior of glycopeptides, specific sample preparation, mass spectrometry, and data analysis techniques are required. Advanced tandem mass spectrometry–based glycoproteomics coupled with powerful data mining algorithms are key elements for characterization of protein glycosylation. This article includes the detailed, streamlined sample preparation method for liquid chromatography–mass spectrometry data acquisition and subsequent bioinformatics‐based data annotation using the publicly available GlycReSoft program for highly efficient identification and quantification of glycoprotein glycosylation. © 2021 Wiley Periodicals LLC. This article was corrected on 25 July 2022. See the end of the full text for details. Basic Protocol 1 : Characterization of glycans and site occupancy on purified glycoprotein Support Protocol 1 : In‐gel digestion of glycoproteins Support Protocol 2 : Detection of glycoproteins from cells/tissue through glycopeptide enrichment Basic Protocol 2 : Acquisition of glycopeptides through high‐resolution nano‐LC‐MS/MS Basic Protocol 3 : Identification and quantification of glycopeptides using GlycReSoft
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