Department of Microbiology and Immunology, University of Melbourne at the Peter Doherty Institute for Infection and Immunity, Melbourne, Australia.
Department of Microbiology and Immunology, University of Melbourne at the Peter Doherty Institute for Infection and Immunity, Melbourne, Australia.
Mol Cell Proteomics. 2020 Sep;19(9):1561-1574. doi: 10.1074/mcp.TIR120.002100. Epub 2020 Jun 23.
Mass spectrometry has become an indispensable tool for the characterization of glycosylation across biological systems. Our ability to generate rich fragmentation of glycopeptides has dramatically improved over the last decade yet our informatic approaches still lag behind. Although glycoproteomic informatics approaches using glycan databases have attracted considerable attention, database independent approaches have not. This has significantly limited high throughput studies of unusual or atypical glycosylation events such as those observed in bacteria. As such, computational approaches to examine bacterial glycosylation and identify chemically diverse glycans are desperately needed. Here we describe the use of wide-tolerance (up to 2000 Da) open searching as a means to rapidly examine bacterial glycoproteomes. We benchmarked this approach using -linked glycopeptides of as well as -linked glycopeptides of and revealing glycopeptides modified with a range of glycans can be readily identified without defining the glycan masses before database searching. Using this approach, we demonstrate how wide tolerance searching can be used to compare glycan use across bacterial species by examining the glycoproteomes of eight Burkholderia species (). Finally, we demonstrate how open searching enables the identification of low frequency glycoforms based on shared modified peptides sequences. Combined, these results show that open searching is a robust computational approach for the determination of glycan diversity within bacterial proteomes.
质谱分析已成为在生物系统中对糖基化进行特征分析的不可或缺的工具。在过去十年中,我们对糖肽进行丰富片段化的能力得到了显著提高,但我们的信息学方法仍然落后。尽管使用聚糖数据库的糖蛋白质组学信息学方法引起了相当大的关注,但数据库独立的方法却没有。这极大地限制了对不常见或非典型糖基化事件(如细菌中观察到的事件)的高通量研究。因此,迫切需要计算方法来检查细菌糖基化并识别化学多样性的聚糖。在这里,我们描述了使用宽容忍度(高达 2000 Da)开放搜索作为快速检查细菌糖蛋白组的方法。我们使用 的 O-连接糖肽和 的 N-连接糖肽对这种方法进行了基准测试,结果表明,无需在数据库搜索前定义聚糖质量,就可以轻松识别用各种聚糖修饰的糖肽。使用这种方法,我们展示了宽容忍度搜索如何通过检查 8 种伯克霍尔德氏菌()的糖蛋白组来比较细菌物种之间的聚糖使用情况。最后,我们展示了开放搜索如何能够根据共享修饰肽序列来鉴定低频糖型。综上所述,这些结果表明,开放搜索是一种强大的计算方法,可用于确定细菌蛋白质组中的聚糖多样性。