Mouse glycoproteome: Heart - pGlyco 2

Precise and large-scale characterization of glycoproteome is critical for understanding the biological functions of glycoproteins. Due to the complexity of glycosylation, the overall throughput, data quality and accessibility of site-specific glycosylation analysis are overwhelmingly lower than those of routine proteomic studies. Here, we introduce a workflow that robustly identifies intact glycopeptides at a proteome scale using stepped-energy mass-spectrometry (MS) and pGlyco 2.0, a dedicated search engine for large-scale glycopeptide analysis with comprehensive quality control (false discovery rate evaluation on the glycan, peptide and glycopeptide matches).

精准且大规模的糖蛋白质组（glycoproteome）表征，对于解析糖蛋白的生物学功能至关重要。受限于糖基化修饰的复杂性，位点特异性糖基化分析的整体通量、数据质量与可及性，均远低于常规蛋白质组学研究。本研究提出一种分析流程，可通过阶梯能量质谱（stepped-energy mass-spectrometry，MS）与pGlyco 2.0实现全蛋白质组规模下完整糖肽的可靠鉴定；其中pGlyco 2.0是一款专为大规模糖肽分析设计的搜索引擎，可对聚糖、肽段及糖肽的匹配结果开展全面质量控制，涵盖假发现率评估。