GlyPick - a computational tool to facilitate mining of LC-MS/MS data for glycomic identification of terminal epitopes based on MS2/MS3 characteristic fragment ions.
Date Issued
2014
Date
2014
Author(s)
Wang, Po-Wei
Abstract
Mass spectrometry (MS) is one of the most useful tools for analyzing unknown chemical molecules and structures including glycans. Current glycomic analysis has gradually moved from matrix-assisted laser desorption/ionization (MALDI)-based offline analysis to online liquid chromatography (LC)-electrospray ionization (ESI)-based MS/MS applications, in order to cope with the sample complexity and the need to do as many MS2 and MS3 as possible for each of the detected glycan precursors. Generally speaking, the datasets acquired by LC-MSn are much larger than the ones of MALDI-MS. This makes manual identification and annotation of glycans quite tedious, time-consuming, and not amenable to non-experts. Therefore, efficient softwares are urgently needed to automate part or all of the data analysis process in LC-MSn-based glycomics.
In this thesis work, a software for comprehensive, efficient glycosyl epitope/fragment ions discovery and glycosyl composition annotation was developed using C# .net framework for better integration with Thermo Raw API, and the easy-to-maintain object-oriented concept. Applied to LC-MSn datasets acquired on the permethylated glycans derived from a gastric adenocarcinoma cell line AGS, we demonstrated the utilities of this computational tool, named GlyPick. GlyPick can recognize and discover specific fragment ions or epitopes in MS2 spectra, tracking back to MS1 spectra to locate the monoisotopic precursor, assign its glycosyl composition so as to confirm the fragment ions/epitopes indeed derived from glycans, and then tracking forward to MS3 spectra for more information on linkages. By integrating the data, the most plausible glycan structures consistent with the deduced monoisotopic precursor peaks will be assigned in accordance with the MS2-detected epitopes/fragment ions, complete with linkage determination in cases where MS3 were productively acquired. GlyPick also groups the fitted glycosyl compositions by retention times for better visualization and further data mining. Applications of GlyPick to datasets of N-glycans, O-glycan and glycolipids from AGS indicated differences of epitopes/fragment ions and glycosyl compositions in these samples. Finally, we also compared GlyPick with other published tools, MultiGlycan, GlycReSoft and SimGlycan, to evaluate their performance differences.
Subjects
質譜儀
醣質結構
醣質譜數據分析工具
醣斷片/末端表位
液相層析電噴灑離子化(LC-ESI-MS/MS)串聯質譜分析
胃癌細胞甲基化醣質
Type
thesis
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