# Methods for measuring matrisome molecule similarity during disease processes

> **NIH NIH R35** · BOSTON UNIVERSITY MEDICAL CAMPUS · 2022 · $165,000

## Abstract

Project Summary/Abstract:
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.

## Key facts

- **NIH application ID:** 10582128
- **Project number:** 3R35GM144090-01S1
- **Recipient organization:** BOSTON UNIVERSITY MEDICAL CAMPUS
- **Principal Investigator:** JOSEPH ZAIA
- **Activity code:** R35 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $165,000
- **Award type:** 3
- **Project period:** 2022-03-01 → 2027-02-28

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10582128

## Citation

> US National Institutes of Health, RePORTER application 10582128, Methods for measuring matrisome molecule similarity during disease processes (3R35GM144090-01S1). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10582128. Licensed CC0.

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