Shaping MSn Technology for High Impact Glycan Sequencing

项目总结/摘要 基于离子阱顺序质谱（IT-MSn）的测序已被证明是一种有效的方法。 强大的技术，用于详细的碳水化合物结构表征。不同于许多 传统的寡糖分析策略，MSn测序不依赖于聚糖 生物合成规则或推断数据。这一独特的功能在学习中特别有益 疾病中的异常糖基化，或工程糖治疗糖基化机制， 非常规表达系统，因为这些系统中的糖基化研究较少， 从模型系统建立的生物合成规则可能不再适用。的 对MSn测序所提供的价值的认识在学术界和 行业尽管如此，MSn测序的陡峭学习曲线一直阻碍着 技术的广泛适应。这个实验室开创了聚糖测序 技术，并处于独特的地位，以推进和传播这种方法， 糖生物学社区为了使学习曲线变平，我们提出了四个具体的建议。 应用目的：（一）扩大MSn图书馆馆藏，建立门户网站， （B）开发用于自动化MSn糖表位的集成软件系统 （C）寻求与传统寡糖结构分析策略的协同作用; (D)扩展详细的MSn测序，以涵盖糖胺聚糖（GAG）相关聚合物。 拟议项目的交付成果将是一套软件工具和已建立的实验室 协议，使非专业的生物医学实验室进行详细的碳水化合物 使用MSn测序进行表征。我们认为，拟议的发展符合 RFA-RM-16-023，并将加速该技术的推广。

Project Summary/Abstract Ion Trap Sequential Mass Spectrometry (IT-MSn) based sequencing has been proven a powerful technology for detailed carbohydrate structural characterization. Different from many traditional oligosaccharide analysis strategies, MSn sequencing does not depend on glycan biosynthesis rules, or inferential data. This unique feature is particularly beneficial in studying abnormal glycosylation in diseases, or engineering glycotherapeutics glycosylation machinery in non-conventional expression systems, because glycosylation in these systems are less studied, biosynthesis rules established from model systems may not be applicable any more. The appreciation of the value provided by MSn sequencing keeps growing in both academia and industry. Nevertheless, the steep learning curve of MSn sequencing has been hindering the wide adaptation of the technology. This laboratory has pioneered this glycan sequencing technology and is uniquely positioned to advance and disseminate this approach to the glycobiology community. In an attempt to flatten the learning curve, we propose four Specific Aims in the application: (A) to expand MSn library collection and build a web portal to enable web access; (B) to develop an integrated software system for automating MSn glyco-epitope identification; (C) to seek synergy with traditional oligosaccharide structural analysis strategies; (D) to extend detailed MSn sequencing to cover glycosaminoglycan (GAG) related polymers. The deliverables of the proposed projects will be a set of software tools and established lab protocols that enable non-specialized biomedical labs to conduct detailed carbohydrate characterization using MSn sequencing. We believe the proposed developments are in line with the RFA-RM-16-023, and will accelerate the diffusion of the technology.