# Capturing Low-Abundance Glycopeptides for Decoding the Glycoproteome

> **NIH NIH R01** · GEORGIA INSTITUTE OF TECHNOLOGY · 2022 · $292,732

## Abstract

SUMMARY
Glycosylation is one of the most common protein modifications and is essential for cell survival. Glycoproteins
contain a wealth of valuable information regarding the development and disease statuses of cells. Global
analysis of protein glycosylation aids in a better understanding of glycoprotein functions and the molecular
mechanisms of disease, and leads to the identification of glycoproteins as biomarkers. However, it is
extraordinarily challenging to comprehensively analyze glycoproteins because of the heterogeneity of glycans
and the low abundance of many glycoproteins. The objective of this project is to develop an innovative and
effective method to enrich glycopeptides with diverse glycan structures, especially those with low abundance,
and apply this method to globally and site-specifically analyze protein N- and O-glycosylation by mass
spectrometry (MS). Guided by strong preliminary data, this objective will be fulfilled by pursuing four specific
aims. 1) Effective enrichment of glycopeptides through the synergistic interactions using different types of
dendrimers. Based on the common feature that every glycan contains multiple hydroxyl groups, a novel method
benefiting from the synergistic interactions between a glycan and multiple boronic acid (BA) molecules
conjugated to one dendrimer will be developed to capture low-abundance glycopeptides. Different types of
dendrimers will be synthesized and tested, especially from monomers containing the 1→3 branching motif that
will increase the density of BA at the dendrimer surface and enhance the interactions with a glycan. 2)
Enhancement of the synergistic interactions by minimizing the steric effect and forming the ternary complex.
Different kinds of BAs will be studied, especially vinylboronic acids with a small size. This will decrease the steric
hindrance and strengthen the overall interaction between one glycan and BAs. Moreover, the formation of the
ternary complex will be studied to further enhance the interactions. 3) Global and site-specific analysis of O-
glycoproteins with glycan structure information. Through reversible covalent interactions, enriched glycopeptides
contain intact glycans, allowing for site-specific analysis of O-glycoproteins with glycan structure information.
This is especially important for O-glycosylation due to the lack of an enzyme to universally cleave O-glycans and
generate a common tag. 4) Comprehensive analysis of glycoproteins in tissues and sera from patients with
ovarian cancer. Combining the proposed method with multiplexed proteomics, glycoproteins in clinical samples
will be systematically and quantitatively analyzed. The results will provide insights into the molecular
mechanisms of the disease and lead to the discovery of biomarkers for early detection. Eventually, the best
dendrimer conjugated with the right BA will enable us to effectively capture low-abundance glycopeptides.
Because of the ease of operation and no sample restrictions, t...

## Key facts

- **NIH application ID:** 10440467
- **Project number:** 5R01GM127711-03
- **Recipient organization:** GEORGIA INSTITUTE OF TECHNOLOGY
- **Principal Investigator:** Ronghu Wu
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $292,732
- **Award type:** 5
- **Project period:** 2020-09-20 → 2024-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10440467

## Citation

> US National Institutes of Health, RePORTER application 10440467, Capturing Low-Abundance Glycopeptides for Decoding the Glycoproteome (5R01GM127711-03). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10440467. Licensed CC0.

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