Kothlow Kathryn, Schramm Haley M, Markuson Kayla A, Russell Jacob H, Sutherland Emmajay, Veth Tim S, Zhang Ruby, Duboff Anna G, Tejus Vishnu R, McDermott Leah E, Dräger Laura S, Riley Nicholas M
Department of Chemistry, University of Washington, Seattle, WA, 98195.
bioRxiv. 2025 Mar 25:2025.03.24.645139. doi: 10.1101/2025.03.24.645139.
Glycopeptide tandem mass spectra typically contain numerous glycan-specific fragments that can inform several features of glycan modifications, including glycan class, composition, and structure. While these fragment ions are often straightforward to observe by eye, few tools exist to systemically explore these common glycopeptide spectral features or explore their relationships to each other. Instead, most studies rely on manual inspection to understand glycan-informative ion content in their data, or they are restricted to evaluating the presence of these ions only in the small fraction of spectra that are identified by glycopeptide search algorithms. Here we introduce GlyCounter as a freely available, open-source tool to rapidly extract oxonium, Y-type, and custom ion information from raw data files. We highlight GlyCounter's utility by evaluating glycan-specific fragments in a diverse selection of publicly available datasets to demonstrate how others in the field can make immediate use of this software. In several cases, we show how conclusions drawn in these publications are evident simply through GlyCounter's extracted ion information without requiring database searches or experiment-specific programs. Although one of our goals is to decouple spectral evaluation from glycopeptide identification, we also show that evaluating oxonium ion content with GlyCounter can supplement a database search as valuable spectral evidence to validate conclusions. In all, we present GlyCounter as a user-friendly platform that can be easily incorporated into most glycoproteomic workflows to refine sample preparation, data acquisition, and post-acquisition identification methods through straightforward evaluation of the glycan content of glycoproteomic data. Software and instructions are available at https://github.com/riley-research/GlyCounter.
糖肽串联质谱通常包含大量聚糖特异性片段，这些片段可以反映聚糖修饰的几个特征，包括聚糖类别、组成和结构。虽然这些碎片离子通常很容易肉眼观察到，但很少有工具能够系统地探索这些常见的糖肽光谱特征或它们之间的相互关系。相反，大多数研究依靠人工检查来了解数据中聚糖信息离子的含量，或者仅限于评估这些离子仅在糖肽搜索算法识别的一小部分光谱中的存在情况。在这里，我们介绍GlyCounter，这是一个免费的开源工具，用于从原始数据文件中快速提取氧鎓离子、Y型离子和自定义离子信息。我们通过评估各种公开可用数据集中的聚糖特异性片段来突出GlyCounter的实用性，以展示该领域的其他人如何立即使用此软件。在几个案例中，我们展示了这些出版物中得出的结论如何仅通过GlyCounter提取的离子信息就显而易见，而无需数据库搜索或特定于实验的程序。虽然我们的目标之一是将光谱评估与糖肽鉴定脱钩，但我们还表明，使用GlyCounter评估氧鎓离子含量可以作为有价值的光谱证据补充数据库搜索，以验证结论。总之，我们将GlyCounter展示为一个用户友好的平台，通过直接评估糖蛋白质组数据的聚糖含量，可以轻松地将其纳入大多数糖蛋白质组工作流程中，以优化样品制备、数据采集和采集后鉴定方法。软件和说明可在https://github.com/riley-research/GlyCounter上获取。
