Department of Pathology, University of Michigan, Ann Arbor, Michigan, USA.
Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan, USA.
Mol Cell Proteomics. 2022 Mar;21(3):100205. doi: 10.1016/j.mcpro.2022.100205. Epub 2022 Jan 26.
Rapidly improving methods for glycoproteomics have enabled increasingly large-scale analyses of complex glycopeptide samples, but annotating the resulting mass spectrometry data with high confidence remains a major bottleneck. We recently introduced a fast and sensitive glycoproteomics search method in our MSFragger search engine, which reports glycopeptides as a combination of a peptide sequence and the mass of the attached glycan. In samples with complex glycosylation patterns, converting this mass to a specific glycan composition is not straightforward; however, as many glycans have similar or identical masses. Here, we have developed a new method for determining the glycan composition of N-linked glycopeptides fragmented by collisional or hybrid activation that uses multiple sources of information from the spectrum, including observed glycan B-type (oxonium) and Y-type ions and mass and precursor monoisotopic selection errors to discriminate between possible glycan candidates. Combined with false discovery rate estimation for the glycan assignment, we show that this method is capable of specifically and sensitively identifying glycans in complex glycopeptide analyses and effectively controls the rate of false glycan assignments. The new method has been incorporated into the PTM-Shepherd modification analysis tool to work directly with the MSFragger glyco search in the FragPipe graphical user interface, providing a complete computational pipeline for annotation of N-glycopeptide spectra with false discovery rate control of both peptide and glycan components that is both sensitive and robust against false identifications.
糖蛋白质组学的快速发展方法使对复杂糖肽样品进行越来越大规模的分析成为可能，但以高置信度注释由此产生的质谱数据仍然是一个主要瓶颈。我们最近在我们的 MSFragger 搜索引擎中引入了一种快速而灵敏的糖蛋白质组学搜索方法，该方法将糖肽报告为肽序列和附着聚糖质量的组合。在具有复杂糖基化模式的样品中，将此质量转换为特定的聚糖组成并不简单；然而，许多聚糖具有相似或相同的质量。在这里，我们开发了一种新方法，用于确定通过碰撞或混合激活碎片化的 N-连接糖肽的聚糖组成，该方法利用来自光谱的多种信息源，包括观察到的聚糖 B 型（氧鎓）和 Y 型离子以及质量和前体单同位素选择错误，以区分可能的聚糖候选物。结合糖基分配的假发现率估计，我们表明该方法能够在复杂糖肽分析中特异性和灵敏地识别聚糖，并有效地控制假聚糖分配的速率。新方法已被纳入 PTM-Shepherd 修饰分析工具中，可直接与 FragPipe 图形用户界面中的 MSFragger 糖搜索配合使用，为具有肽和聚糖成分的假发现率控制的 N-糖肽光谱注释提供了一个完整的计算流程，该流程既灵敏又能抵抗假识别。
