GlycoNote search engine

Mass spectrometry is a central technique in glycomic analysis. However, there is no generic software tool for automated, confident analysis of tandem-mass spectrometry based glycomic data. Here, we propose GlycoNote – a generic and reliable search engine for tandem-mass spectrometry based glycomics. A false discovery rate analysis based on iterative decoy searching was specifically designed for glycomic data analysis. We apply GlycoNote to the analyses of distinct glycomic samples, including human milk oligosaccharides, N/O-glycome from human cell line and polysaccharides from plant. To further demonstrate the general utility of GlycoNote, automated analyses of nonnative glycomes (N-glycome labeled with aniline and permethylated N-glycome) or atypical glycans (O-glycome with N-acetylneuraminic acid / N-glycome from C. elegans) were performed. More importantly, an open-search mode was introduced for the elucidation of component heterogeneity in samples. GlycoNote could be an important tool in the rapidly growing efforts toward comprehensive glycomic analysis.

质谱法（mass spectrometry）是糖组学分析的核心技术。然而目前尚无通用软件工具，可对基于串联质谱（tandem-mass spectrometry）的糖组学数据开展自动化且可靠的分析。本研究提出GlycoNote——一款面向基于串联质谱的糖组学分析的通用且可靠的搜索引擎。研究专门针对糖组学数据分析设计了基于迭代诱饵搜索的错误发现率（false discovery rate, FDR）分析方法。我们将GlycoNote应用于多种不同糖组学样本的分析，包括人乳寡糖、人细胞系来源的N/O糖组以及植物来源的多糖。为进一步验证GlycoNote的通用实用性，本研究还对非天然糖组（苯胺标记的N糖组与全甲基化N糖组）或非典型聚糖（含N-乙酰神经氨酸的O糖组/秀丽隐杆线虫（C. elegans）来源的N糖组）开展了自动化分析。更为重要的是，该工具引入了开放搜索模式，用于解析样本中的组分异质性。在日益蓬勃发展的全面糖组学分析研究中，GlycoNote或将成为一款至关重要的分析工具。