Glycan, Glycoconjugate, and Glycogene Technology Research and Development
Many significant challenges remain for achieving the broad dissemination of robust technologies for analyses of glycans, glycoconjugates, and glycogenes expressed in complex cellular systems. Most of the glycomic methods currently deployed in the field require specialized techniques, standards, and equipment, as well as operators with high levels of expertise in implementing analytic (front-end) and interpretive (back-end) strategies. Further, many of the most sensitive methods in current use are cumbersome, prone to interpreter bias, and primarily qualitative in nature. These limitations have severely restricted wide-dissemination and adoption of approaches as well as progress towards understanding underlying mechanisms that regulate glycan synthesis, presentation, and degradation within the framework of complex biosynthetic pathways.
While MS-based glycomics has made major strides over the past decade toward method harmonization and enhanced back-end interpretation strategies, significant obstacles still remain. A major limitation of current technology is that the deep information provided by MS/MS and MSn analysis of permethylated structures has not yet been effectively merged with the sensitivity, quantifiability, and isomeric resolving power of LC-based approaches. The successful implementation of LC-MSn analysis of permethylated glycans, and of appropriate back-end data interpretation tools, would provide unprecedented opportunities for high throughput, high resolution, high-sensitivity glycomics that could be implemented by mass spectrometry/proteomic core facilities throughout the U.S. For glycoproteomic analyses, major hurdles include lack of robust methods for enrichment of glycopeptides, inability to achieve charge states on glycopeptides sufficient to bring them into appropriate m/z ranges for existing instrumentation, limited fragmentation strategies to simultaneously determine glycan structures and sites of attachment, and limitations of post-translational modification database-searching algorithms. Optimization of nascent methods to increase charge states (super-charging LC-MS), coupled with the development of middle-down proteomic techniques and application of combined step-HCD, neutral-loss triggered MSn, and EThcD fragmentation strategies, would provide new routes for analysis of glycoprotein microheterogeniety and structural diversity. Current glycomic and glycoproteomic analyses are also not well suited to distinguish mature, cell-surface glycoproteins from intracellular biosynthetic intermediates. Robust, easily implemented solutions for capturing cell surface and secreted glycoproteins and for analyzing the turnover of cell surface and secreted glycans would allow targeted investigations of the stability and structural heterogeneity of mature glycoconjugates. Glycan and glycoconjugate structural analyses provide insight into the products of the glycan biosynthetic machinery, which are encoded in glycogenes. Therefore, profiling of transcripts encoding the glycan-related biosynthetic machinery by RNA-Seq and high-throughput qPCR approaches can probe the mechanisms of regulated glycan structural changes and complement the characterization of glycan and glycoconjugate diversity.
To achieve our over-arching goal of disseminating broadly adoptable glycomic methodologies, we propose the following specific aims that will be applied to hESC and derived lineages of wild type and targeted, glycosyltransferase knock-out cells as proof-of-concept and to populate searchable databases:
Specific Aim 1: Automated Glycan Analysis. Combine LC separations, MSn, and intelligent consecutive reaction monitoring (iCRM) to establish quantitative, high-throughput glycomics of permethylated glycans.
A. Develop robust LC methods for separation of isomers of N- and O-linked glycans.
B. Develop automated fragmentation rules for N- and O-linked glycans to drive iCRM.
C. Expand quantification approaches to include methods for assessing turnover and remodeling of glycans.
Specific Aim 2: Glycoconjugate Analysis. Using enrichment strategies, supercharging LC separations, and novel fragmentation combinations, generate quantitative high-throughput
strategies for bottom-up and middle-down analysis of total and cell-surface glycoproteins, glycosphingolipids, and GPI anchors.
A. Develop enhanced site-mapping and LC-MSn protocols for bottom-up and middle-down glycoproteomic approaches and implement software solutions for automated analysis of glycoproteomic data.
B. Develop MS-compatible quantitative cell-surface enrichment technologies (SEEL) and isotopic tagging (iDAWG) for enhanced recovery and quantification of glycoconjugates.
C. Extend glycomic analysis to assess structural diversity of glycosylphosophatidylinositol anchors and glycosphingolipids, understudied classes of glycoconjugates with significant impact on cell signaling.
Specific Aim 3: Glycogene Analysis. Transcript abundance profiles will be acquired by RNA-Seq and focused qPCR for analysis of glycan-related genes. Workflows will be developed to generate, process, and filter RNA-Seq data sets in combination with focused qPCR analyses to directly integrate quantitative transcriptome data into frameworks for pathway analysis.
A. Develop multiplexed RNA Seq analysis and high-throughput qRT-PCR approaches to provide replicate analysis at statistically significant depth for transcript quantitation from cell samples.
B. Establish filtering of sample data for glycan-related genes as input into GRITS and pathway visualization analysis for integrating glycan structural data and transcriptome analysis in a single portal.
