IDEAS home Printed from https://ideas.repec.org/a/nat/natcom/v16y2025i1d10.1038_s41467-025-61473-y.html
   My bibliography  Save this article

Development and application of GlycanDIA workflow for glycomic analysis

Author

Listed:
  • Yixuan Xie

    (Fudan University
    Washington University School of Medicine
    Davis)

  • 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
    Cambridge)

  • Carlito B. Lebrilla

    (Washington University School of Medicine
    Davis)

  • Ryan A. Flynn

    (Boston
    Cambridge)

  • Benjamin A. Garcia

    (Washington University School of Medicine)

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.

Suggested Citation

  • 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 & Benjamin A. Garcia, 2025. "Development and application of GlycanDIA workflow for glycomic analysis," Nature Communications, Nature, vol. 16(1), pages 1-13, December.
  • Handle: RePEc:nat:natcom:v:16:y:2025:i:1:d:10.1038_s41467-025-61473-y
    DOI: 10.1038/s41467-025-61473-y
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/s41467-025-61473-y
    File Function: Abstract
    Download Restriction: no

    File URL: https://libkey.io/10.1038/s41467-025-61473-y?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Yi Yang & Guoquan Yan & Siyuan Kong & Mengxi Wu & Pengyuan Yang & Weiqian Cao & Liang Qiao, 2021. "GproDIA enables data-independent acquisition glycoproteomics with comprehensive statistical control," Nature Communications, Nature, vol. 12(1), pages 1-15, December.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Siyuan Kong & Pengyun Gong & Wen-Feng Zeng & Biyun Jiang & Xinhang Hou & Yang Zhang & Huanhuan Zhao & Mingqi Liu & Guoquan Yan & Xinwen Zhou & Xihua Qiao & Mengxi Wu & Pengyuan Yang & Chao Liu & Weiqi, 2022. "pGlycoQuant with a deep residual network for quantitative glycoproteomics at intact glycopeptide level," Nature Communications, Nature, vol. 13(1), pages 1-17, December.
    2. Klemens Fröhlich & Eva Brombacher & Matthias Fahrner & Daniel Vogele & Lucas Kook & Niko Pinter & Peter Bronsert & Sylvia Timme-Bronsert & Alexander Schmidt & Katja Bärenfaller & Clemens Kreutz & Oliv, 2022. "Benchmarking of analysis strategies for data-independent acquisition proteomics using a large-scale dataset comprising inter-patient heterogeneity," Nature Communications, Nature, vol. 13(1), pages 1-13, December.
    3. He Zhu & Zheng Fang & Lei Liu & Yan Wang & Hongqiang Qin & Yongzhan Nie & Mingming Dong & Mingliang Ye, 2025. "Library-based virtual match-between-runs quantification in GlyPep-Quant improves site-specific glycan identification," Nature Communications, Nature, vol. 16(1), pages 1-17, December.
    4. Yi Yang & Qun Fang, 2024. "Prediction of glycopeptide fragment mass spectra by deep learning," Nature Communications, Nature, vol. 15(1), pages 1-12, December.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:nat:natcom:v:16:y:2025:i:1:d:10.1038_s41467-025-61473-y. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.nature.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.