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.
The proposed projects are designed to streamline glycan sequencing via sequential mass spectrometry (MSn) by expanding MSn library collection and building a web portal to enable public web access; developing an integrated software system for automating MSn glyco-epitope identification; cross-validating the MSn sequencing approach with the traditional oligosaccharide structural analysis strategies; and extending detailed MSn sequencing to cover glycosaminoglycan (GAG) related polymers. The proposed software tools, expanded MSn library, spectrum matching web portal, and GAG MSn sequencing protocols would be publicly available to academic scientists. Enhanced glyco-analysis capabilities can provide insights into a number of biological and biomedical research areas where glycans play a significant role, including cancer biomarker discovery, vaccine discovery, biopharmaceutical glycoprotein characterization, parasite-host and microbe-host interactions.
