Glycosylation is one of the most prevalent and important post-translational modifications of proteins, yet it is also one of the most difficult to study. No single method nor analytical platform can give complete information about the glycosylation in a protein sample, and the analytical methods in current use include both ESI and MALDI single and tandem mass spectrometry, at least four types of liquid chromatography, iterative enzyme analysis, glycan-binding experiments with fluorescence read-out, and new methods such as ion mobility spectrometry. There is currently no software platform that can integrate even two of these different data channels. In this project we propose to build a software product called GlycoForm that will be capable of analyzing, visualizing, and integrating glycosylation data over multiple channels. GlycoForm will be able to identify released glycans to the level of detail warranted by the evidence and quantify them using either mass spectrometry or fluorescence signals. The software will include both an interactive user interface for expert inspection, and also customized and automated glycosylation reports for sharing and archiving. The initial release of GlycoForm will handle single and tandem mass spectrometry, chromatographic elution time, and glycan-binding experiments; other data channels will be added later in response to customer demand.

Public Health Relevance

In this Phase II STTR project, we propose to develop a commercial software product called GlycoForm for integrating glycomics and glycoproteomics data from multiple analytical methods. The expected markets for GlycoForm include academic research laboratories and biopharmaceutical companies engaged in basic research, biomarker discovery, early drug development, and protein therapeutic characterization. The proposed project has the potential for great impact on human health in areas such as vaccine and drug development and cancer biomarker discovery.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Small Business Technology Transfer (STTR) Grants - Phase II (R42)
Project #
5R42GM112750-05
Application #
9769771
Study Section
Special Emphasis Panel (ZRG1)
Program Officer
Krepkiy, Dmitriy
Project Start
2014-09-22
Project End
2020-08-31
Budget Start
2019-09-01
Budget End
2020-08-31
Support Year
5
Fiscal Year
2019
Total Cost
Indirect Cost
Name
Protein Metrics, Inc.
Department
Type
DUNS #
967100921
City
Cupertino
State
CA
Country
United States
Zip Code
95014
Klamer, Zachary; Staal, Ben; Prudden, Anthony R et al. (2017) Mining High-Complexity Motifs in Glycans: A New Language To Uncover the Fine Specificities of Lectins and Glycosidases. Anal Chem 89:12342-12350