Methods for measuring matrisome molecule similarity during disease processes

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Project Summary/Abstract: The application responds to NIGMS PAR-19-367 “Maximizing Investigators' Research Award (R35 - Clinical Trial Optional)” My research group focused initially on analytical methods for glycosaminoglycans (GAGs). These linear, sulfated polysaccharides are attached to serine residues of proteoglycan molecules found on cellular surfaces, in intracellular granules and in extracellular matrices. Binding interactions between GAGs and proteins are central to aspects of animal physiology including cellular signaling, the cellular microenvironment, and host- host, and host-pathogen recognition. My group developed methods for liquid chromatography-mass spectrometry analysis and sequencing of GAGs, extraction of GAGs from wet tissue and tissue slides, and bioinformatics programs for interpretation of GAG MS and tandem MS data. We then pioneered methods to acquire glycomics (GAGs and N-glycans) and proteomics from biospecimen tissue slides. We applied these methods to study of neurological aging, cancer, neurodevelopmental, and neurodegenerative diseases. As funded through NIGMS R01GM133963 “Methods for determination of glycoprotein glycosylation similarities among disease states”, my group is developing analytical and bioinformatics methods for glycoproteomics of the extracellular matrix molecules (known as the matrisome) of brain. The primary focus has been on glycoproteomics MS acquisition methods and bioinformatics for rigorous statistical determination of molecular similarities for matrisome molecules and how these change during normal aging versus disease processes. I now propose to expand our brain glycoproteomics molecular similarity scope to include characterization of GAGs that modify specific matrisome molecules. Our goals will be to provide information on the pathophysiological changes to matrisome molecules that escape detection using traditional antibody-based detection methods. We will employ a new Omnitrap platform to characterize multiply glycosylated peptides and peptides modified with GAG chains. We will also exploit the capabilities of ion mobility for measuring molecular similarities from glycoproteomics data using a Waters Cyclic ion mobility-mass spectrometry instrument. We will demonstrate these approaches by comparing matrisome molecular similarity among brain regions and as a function of age.