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| Funder | NATIONAL INSTITUTE OF GENERAL MEDICAL SCIENCES |
|---|---|
| Recipient Organization | Ohio State University |
| Country | United States |
| Start Date | Jan 01, 2021 |
| End Date | Dec 31, 2023 |
| Duration | 1,094 days |
| Number of Grantees | 1 |
| Roles | Principal Investigator |
| Data Source | NIH (US) |
| Grant ID | 10312126 |
Project Abstract Protein glycosylation plays important roles in various human diseases, including cancer, inflammatory, and neurodegenerative diseases. Glycoproteins, therefore, are important targets for disease diagnosis, prognosis, and therapeutics. Correct glycosylation of therapeutic proteins is required for optimal efficacy and safety.
However, analysis of glycosylation is challenging due to the enormous complexity of glycan variability. The current state of art technique is mass spectrometry (MS), which has been a powerful approach for glycosylation analysis; however, there are classes of glycans that present challenges for MS analysis, such as
the numerous component monosaccharides with the same mass. This project seeks to develop surface enhanced Raman scattering (SERS) as online detection method for glycosylation analysis at the levels of small glycopeptides and released glycans. This proposal leverages recent advances incorporating a novel SERS detector online with chemical separations for highly sensitive and
selective characterization. Published results have successfully shown online separation, identification and quantification of phosphorylated monosaccharides, demonstrating the tremendous potential of SERS for qualitative and quantitative analysis of carbohydrates that serve as glycans and glycopeptides.
The specific aims of this project are as follows: Aim 1. Demonstrate the utility of the sheath-flow SERS detector for structural analysis of glycopeptides. We will use a set of structurally similar glycopeptide analogues to demonstrate the capability of the SERS flow detector for identification and quantification of glycopeptides.
Aim 2. Qualitative and quantitative analysis of glycans and peptides released from glycoproteins using LC- SERS. This aim will provide evidence for the capability of our SERS technology to identify and quantify glycans and glycopeptides with similar chemical structure (e.g. isomers) in complex mixtures,
demonstrating its potential, as a complementary technique to MS, for comprehensive glycosylation analysis of the levels of glycopeptides and released glycans. The development of new technologies that provide unique chemical specific information will provide an alternative tool for increased coverage of the glycoproteome, facilitating the progress in glycobiology.
Ohio State University
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