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通过电子转移解离对 O-连接糖肽进行表征:碎裂规则及其在数据分析中的应用。

Characterizing O-linked glycopeptides by electron transfer dissociation: fragmentation rules and applications in data analysis.

机构信息

The Ralph N. Adams Institute for Bioanalytical Chemistry and Department of Chemistry, University of Kansas, Lawrence, Kansas 66047, USA.

出版信息

Anal Chem. 2013 Sep 3;85(17):8403-11. doi: 10.1021/ac401814h. Epub 2013 Aug 22.

Abstract

Studying protein O-glycosylation remains an analytical challenge. Different from N-linked glycans, the O-glycosylation site is not within a known consensus sequence. Additionally, O-glycans are heterogeneous with numerous potential modification sites. Electron transfer dissociation (ETD) is the method of choice in analyzing these glycopeptides since the glycan side chain remains intact in ETD, and the glycosylation site can be localized on the basis of the c and z fragment ions. Nonetheless, new software is necessary for interpreting O-glycopeptide ETD spectra in order to expedite the analysis workflow. To address the urgent need, we studied the fragmentation of O-glycopeptides in ETD and found useful rules that facilitate their identification. By implementing the rules into an algorithm to score potential assignments against ETD-MS/MS data, we applied the method to glycopeptides generated from various O-glycosylated proteins including mucin, erythropoietin, fetuin, and an HIV envelope protein, 1086.C gp120. The site-specific O-glycopeptide composition was correctly assigned in every case, proving the merits of our method in analyzing glycopeptide ETD data. The algorithm described herein can be easily incorporated into other automated glycomics tools.

摘要

研究蛋白质 O-糖基化仍然是一个分析上的挑战。与 N-连接的聚糖不同,O-糖基化位点不在已知的共有序列内。此外,O-聚糖具有许多潜在的修饰位点,具有异质性。电子转移解离(ETD)是分析这些糖肽的首选方法,因为在 ETD 中聚糖侧链保持完整,并且可以根据 c 和 z 片段离子定位糖基化位点。然而,为了加速分析工作流程,有必要开发新的软件来解释 O-糖肽 ETD 光谱。为了解决这一迫切需求,我们研究了 ETD 中 O-糖肽的断裂,并找到了有助于鉴定它们的有用规则。通过将规则实施到算法中,根据 ETD-MS/MS 数据对潜在分配进行评分,我们将该方法应用于从各种 O-糖基化蛋白(包括粘蛋白、促红细胞生成素、胎球蛋白和 HIV 包膜蛋白 1086.C gp120)生成的糖肽。在每种情况下,都正确地分配了特定位置的 O-糖肽组成,证明了我们的方法在分析糖肽 ETD 数据方面的优势。本文描述的算法可以很容易地集成到其他自动化糖组学工具中。

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