Development and application of GlycanDIA workflow for glycomic analysis.

Yixuan Xie, Xingyu Liu, Chenfeng Zhao, Siyu Chen, Shunyang Wang, Zongtao Lin, Faith M Robison, Benson M George, Ryan A Flynn, Carlito B Lebrilla, Benjamin A Garcia
Author Information
  1. Yixuan Xie: Department of Biochemistry and Molecular Biophysics, Washington University School of Medicine, St. Louis, Missouri, United States. ORCID
  2. Xingyu Liu: Department of Biochemistry and Molecular Biophysics, Washington University School of Medicine, St. Louis, Missouri, United States. ORCID
  3. Chenfeng Zhao: Department of Computer Science & Engineering, Washington University, St. Louis, Missouri, United States.
  4. Siyu Chen: Department of Chemistry, University of California, Davis, Davis, California, United States. ORCID
  5. Shunyang Wang: Department of Chemistry, University of California, Davis, Davis, California, United States. ORCID
  6. Zongtao Lin: Department of Biochemistry and Molecular Biophysics, Washington University School of Medicine, St. Louis, Missouri, United States. ORCID
  7. Faith M Robison: Department of Biochemistry and Molecular Biophysics, Washington University School of Medicine, St. Louis, Missouri, United States.
  8. Benson M George: Stem Cell Program and Division of Hematology/Oncology, Boston Children's Hospital, Boston, Massachusetts, United States. ORCID
  9. Ryan A Flynn: Stem Cell Program and Division of Hematology/Oncology, Boston Children's Hospital, Boston, Massachusetts, United States. ORCID
  10. Carlito B Lebrilla: Department of Chemistry, University of California, Davis, Davis, California, United States.
  11. Benjamin A Garcia: Department of Biochemistry and Molecular Biophysics, Washington University School of Medicine, St. Louis, Missouri, United States. ORCID

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. Thus, while the significance of glycosylation is well established, a lack of accessible methods to characterize glycans has hindered the ability to understand their biological functions. Mass spectrometry (MS)-based methods have generally been at the core of most glycan profiling efforts; however, modern data-independent acquisition (DIA), which could increase sensitivity and simplify workflows, has not been benchmarked for analyzing glycans. Herein, we developed a DIA-based glycomic workflow, termed GlycanDIA, to identify and quantify glycans with high sensitivity and accuracy. The GlycanDIA workflow combined higher energy collisional dissociation (HCD)-MS/MS and staggered windows for glycomic analysis, which facilitates the sensitivity in identification and the accuracy in quantification compared to conventional data-dependent acquisition (DDA)-based glycomics. To facilitate its use, we also developed a generic search engine, GlycanDIA Finder, incorporating an iterative decoy searching for confident glycan identification and quantification from DIA data. The results showed that GlycanDIA can distinguish glycan composition and isomers from -glycans, -glycans, and human milk oligosaccharides (HMOs), while it also reveals information on low-abundant modified glycans. With the improved sensitivity, we performed experiments to profile -glycans from RNA samples, which have been underrepresented due to their low abundance. Using this integrative workflow to unravel the -glycan profile in cellular and tissue glycoRNA samples, we found that RNA-glycans have specific forms as compared to protein-glycans and are also tissue-specific differences, suggesting distinct functions in biological processes. Overall, GlycanDIA can provide comprehensive information for glycan identification and quantification, enabling researchers to obtain in-depth and refined details on the biological roles of glycosylation.

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Grants

  1. R01 HD106051/NICHD NIH HHS
  2. P01 CA196539/NCI NIH HHS
  3. R01 GM049077/NIGMS NIH HHS
  4. R01 AI118891/NIAID NIH HHS
  5. R01 AG062240/NIA NIH HHS

Word Cloud

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