Glycosylation is one of the most common post-translational modifications of proteins; over half of mammalian proteins are glycosylated. Patients with several autoimmune disorders, chronic inflammatory diseases, and some infectious diseases exhibit abnormal glycosylation of serum immunoglobulins and other glycoproteins. The biological functions of these modifications in health and disease continue to be a significant area of interest in biomedical research. Specifically, the task of defining site-specific glycoprotein heterogeneity is recognized as an area that still needs a considerable amount of effort to fully understand the role of glycan heterogeneity. We have developed robust workflows for the analysis of the IgA1 clustered O-glycan heterogeneity in clinical samples from patients with a chronic kidney disease, IgA nephropathy (IgAN), the most predominant form of glomerulonephritis in the world. Our outcome-based approach for profiling the entire range of IgA1 O-glycoforms from clinical samples has made significant contributions to the field of IgAN research, but also to the broader field of profiling protein glycosylation heterogeneity. Our findings have provided a means of detecting shifts in glycan heterogeneity through the application of relative quantitative, label-free analysis of the entire population of IgA1 glycofors in a single serum sample. Based on our novel workflows, we have identified subsets of IgA1 O-glycoforms in patients with IgAN that are significantly increased/decreased in their relative abundance compared to healthy controls. Going forward, absolute quantitation of individual O-glycoforms is needed. There are no established methods for the quantitative analysis of intact clustered O-glycopeptides or O-glycoproteins with Core 1 type O-glycans. Current quantitative immunoassays for detection of aberrant Core 1 glycans (Tn and sialyl-Tn antigens) are not well defined in terms of what protein, amino acid, or adjacent O-glycan context they recognize. In this proposal, we will adapt our existing methods for relative quantitative profiles into absolute quantitative strategies with O-glycopeptide reference standards. We hypothesize that this approach will provide a needed tool for heavily O-glycosylated proteins to become reliable clinical biomarkers. We have successfully synthesized in-house a series of complex clustered O-glycopeptides to serve as reference standards and novel reagents for the analysis of clustered O-glycan-specific epitopes. We will apply our quantitative strategies to the analysis of two IgAN patient cohorts to identify specific Tn antigen-presenting IgA1 O-glycoforms that lead to the formation of nephritogenic immune complexes. We will also make use of our accumulated knowledge of clustered O-glycan heterogeneity in tandem repeat amino acid sequences to characterize the accessible Tn antigen epitopes for recognition by naturally occurring and commercially available antibodies.

Public Health Relevance

This proposal seeks to continue to develop analytical tools for the analysis of glycoproteins with clustered O-glycans in clinical samples. This work includes the development of strategies for the absolute quantitation of the range of differentially glycosylated within a single sample. We will also make use of our accumulated tools for clustered O-glycan analysis to map epitopes of naturally occurring and commercially developed antibodies that recognize the Tn antigen as an isolated or clustered protein modification.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Project (R01)
Project #
5R01GM098539-07
Application #
9455692
Study Section
Enabling Bioanalytical and Imaging Technologies Study Section (EBIT)
Program Officer
Marino, Pamela
Project Start
2011-09-15
Project End
2020-03-31
Budget Start
2018-04-01
Budget End
2019-03-31
Support Year
7
Fiscal Year
2018
Total Cost
Indirect Cost
Name
University of Alabama Birmingham
Department
Biochemistry
Type
Schools of Medicine
DUNS #
063690705
City
Birmingham
State
AL
Country
United States
Zip Code
35294
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