CAREER: Algorithm and Software Development for MS-Based Glycomics

职业：基于 MS 的糖组学的算法和软件开发

• 批准号: 0642897
• 负责人: Haixu Tang
• 金额: $ 59.36万
• 依托单位: Indiana University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-06-01 至 2013-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0642897&HistoricalAwards=false
• 关键词: CAREER; Algorithm; Software; Development; MS

Indiana University is given a CAREER award for Dr. Haixu Tang to pursue algorithm and software development for Mass-Spectra-based glycomics, the study of identifying and characterizing all functional oligosaccharides inside a cell. Currently there are three typical protocols to analyze glycoproteins: oligosaccharides are released from proteins and then are analyzed by tandem or even higher MS to elucidate their structures; glycoproteins are enriched and then identified by tandem MS using typical proteomics methodologies without addressing glycans explicitly; and glycoproteins are purified and analyzed by MS/MS to characterize and profile the microheterogeneity of site-specific glycosylations. Glycomics projects require intensive computational analysis of the MS spectra. The objective of this proposal is to develop computational methods for solving several fundamental problems emerging from MS-based glycomics projects, and to develop urgently needed courses and tutorials for educating students and researchers in glycoinformatics. It consists of three specific aims: (1) to continue developing algorithms and software for characterizing oligosaccharide structures, including their sequences, branchings and linkages, from tandem mass spectra; (2) to develop algorithms and software for characterizing site-specific glycosylations in glycoproteins from their LC/MS/MS analyses; and (3) to develop new courses in glycoinformatics and proteome informatics. The success of these goals will provide useful software tools and teaching materials to the glycomics community. Furthermore, it will enable the automation of glycoproteomics analysis of complex sample. The proposed research is highly related to the PI's efforts for the multidisciplinary training for graduate students, particularly in the areas of glycome and proteome informatics, in the School of Informatics at Indiana University.

美国印第安纳大学授予唐海旭博士终身成就奖，表彰他致力于基于质谱的糖组学的算法和软件开发，该研究旨在识别和表征细胞内所有功能性低聚糖。目前分析糖蛋白有三种典型的方法：从蛋白质中释放低聚糖，然后通过串联或更高的质谱分析来阐明其结构；糖蛋白富集，然后通过串联质谱使用典型的蛋白质组学方法进行鉴定，而不明确地定位多糖；通过MS/MS对糖蛋白进行纯化和分析，以表征和描述位点特异性糖基化的微观异质性。糖组学项目需要对质谱进行密集的计算分析。本提案的目标是开发计算方法来解决基于ms的糖组学项目中出现的几个基本问题，并开发迫切需要的课程和教程来教育糖信息学的学生和研究人员。它包括三个具体目标：(1)继续开发用于表征低聚糖结构的算法和软件，包括它们的序列，分支和连接，从串联质谱；(2)开发算法和软件，通过LC/MS/MS分析来表征糖蛋白的位点特异性糖基化；(3)开设糖信息学和蛋白质组学新课程。这些目标的成功将为糖组学社区提供有用的软件工具和教学材料。此外，它将使复杂样品的糖蛋白组学分析自动化。这项拟议的研究与PI在印第安纳大学信息学学院为研究生提供多学科培训的努力高度相关，特别是在糖和蛋白质组信息学领域。