Glycoproteomic data are often very complex, reflecting the high structural diversity of peptide and glycan portions. The use of glycopeptide-centered glycoproteomics by mass spectrometry is rapidly evolving in many research areas, leading to a demand in reliable data analysis tools. In recent years, several bioinformatic tools were developed to facilitate and improve both the identification and quantification of glycopeptides. Here, a selection of these tools was combined and evaluated with the aim of establishing a robust glycopeptide detection and quantification workflow targeting enriched glycoproteins. For this purpose, a tryptic digest from affinity-purified immunoglobulins G and A was analyzed on a nano-reversed-phase liquid chromatography–tandem mass spectrometry platform with a high-resolution mass analyzer and higher-energy collisional dissociation fragmentation. Initial glycopeptide identification based on MS/MS data was aided by the Byonic software. Additional MS1-based glycopeptide identification relying on accurate mass and retention time differences using GlycopeptideGraphMS considerably expanded the set of confidently annotated glycopeptides. For glycopeptide quantification, the performance of LaCyTools was compared to Skyline, and GlycopeptideGraphMS. All quantification packages resulted in comparable glycosylation profiles but featured differences in terms of robustness and data quality control. Partial cysteine oxidation was identified as an unexpectedly abundant peptide modification and impaired the automated processing of several IgA glycopeptides. Finally, this study presents a semiautomated workflow for reliable glycoproteomic data analysis by the combination of software packages for MS/MS- and MS1-based glycopeptide identification as well as the integration of analyte quality control and quantification.

中文翻译：

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半自动化糖蛋白组学数据分析工作流程，可最大限度地实现糖肽鉴定和可靠定量

糖蛋白质组数据通常非常复杂，反映了肽和聚糖部分的高度结构多样性。通过质谱分析以糖肽为中心的糖蛋白质组学的应用在许多研究领域迅速发展，导致对可靠数据分析工具的需求。近年来，开发了几种生物信息学工具来促进和改进糖肽的鉴定和定量。在这里，对这些工具的选择进行了组合和评估，目的是建立针对富集糖蛋白的稳健的糖肽检测和定量工作流程。为此，在纳米反相液相色谱-串联质谱平台上对亲和纯化的免疫球蛋白 G 和 A 的胰蛋白酶消化物进行了分析，该平台配有高分辨率质量分析器和更高能量的碰撞解离碎片。Byonic 软件协助基于 MS/MS 数据进行初步糖肽鉴定。其他基于 MS1 的糖肽鉴定依赖于使用 GlycopeptideGraphMS 的精确质量和保留时间差异，大大扩展了可靠注释的糖肽集。对于糖肽定量，将 LaCyTools 的性能与 Skyline 和 GlycopeptideGraphMS 进行了比较。所有定量包都产生了可比较的糖基化谱，但在稳健性和数据质量控制方面存在差异。部分半胱氨酸氧化被鉴定为意外丰富的肽修饰，并损害了几种 IgA 糖肽的自动加工。最后，本研究提出了一种半自动化工作流程，通过结合基于 MS/MS 和 MS1 的糖肽鉴定软件包以及分析物质量控制和定量的集成，进行可靠的糖蛋白组数据分析。