Development and application of GlycanDIA workflow for glycomic analysis

Yixuan Xie (), Xingyu Liu, Li Yi, Shunyang Wang, Zongtao Lin, Chenfeng Zhao, Siyu Chen, Faith M. Robison, Benson M. George, Carlito B. Lebrilla, Ryan A. Flynn () and Benjamin A. Garcia ()
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Yixuan Xie: Fudan University
Xingyu Liu: Washington University School of Medicine
Li Yi: Fudan University
Shunyang Wang: Davis
Zongtao Lin: Washington University School of Medicine
Chenfeng Zhao: Washington University
Siyu Chen: Davis
Faith M. Robison: Washington University School of Medicine
Benson M. George: Boston
Carlito B. Lebrilla: Washington University School of Medicine
Ryan A. Flynn: Boston
Benjamin A. Garcia: Washington University School of Medicine

Nature Communications, 2025, vol. 16, issue 1, 1-13

Abstract: Abstract Glycans modify protein, lipid, and even RNA molecules to form the regulatory outer coat on cells called the glycocalyx. The changes in glycosylation have been linked to the initiation and progression of many diseases. Herein, we report a DIA-based glycomic workflow, termed GlycanDIA, to identify and quantify glycans with high sensitivity and precision. The GlycanDIA workflow combines higher energy collisional dissociation (HCD)-MS/MS and staggered windows for glycomic analysis, which facilitates the sensitivity in identification and precision in quantification compared to conventional glycomic methods. To facilitate its use, we also develop a generic search engine, GlycanDIA Finder, incorporating an iterative decoy searching for confident glycan identification from DIA data. Our results demonstrate that GlycanDIA can distinguish glycan composition and isomers from N-glycans, O-glycans, and human milk oligosaccharides (HMOs), while it also reveals information on low-abundant modified glycans. With the improved sensitivity and precision, we perform experiments to profile N-glycans from RNA samples, which have been underrepresented due to their low abundance. Using this integrative workflow to unravel the N-glycan profile in cellular and tissue glycoRNA samples, we find that RNA-glycans have different abundant forms as compared to protein-glycans and there are also tissue-specific differences, suggesting their distinct functions in biological processes.

Date: 2025
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DOI: 10.1038/s41467-025-61473-y

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