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GlycoGenius: a streamlined high-throughput glycan composition identification tool

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  • Hector F. Loponte

    (University of Groningen, Analytical Biochemistry, Groningen Research Institute of Pharmacy
    Federal University of Rio de Janeiro, Carlos Chagas Filho Biophysics’ Institute
    Federal University of Rio de Janeiro, Paulo de Góes Microbiology Institute)

  • Jing Zheng

    (University of Groningen, Analytical Biochemistry, Groningen Research Institute of Pharmacy)

  • Yajie Ding

    (University of Groningen, Analytical Biochemistry, Groningen Research Institute of Pharmacy)

  • Isadora A. Oliveira

    (Federal University of Rio de Janeiro, Carlos Chagas Filho Biophysics’ Institute)

  • Kristoffer Basse

    (University of Groningen, Analytical Biochemistry, Groningen Research Institute of Pharmacy)

  • Adriane R. Todeschini

    (Federal University of Rio de Janeiro, Carlos Chagas Filho Biophysics’ Institute
    Federal University of Rio de Janeiro, Paulo de Góes Microbiology Institute)

  • Peter L. Horvatovich

    (University of Groningen, Analytical Biochemistry, Groningen Research Institute of Pharmacy)

  • Guinevere S. M. Lageveen-Kammeijer

    (University of Groningen, Analytical Biochemistry, Groningen Research Institute of Pharmacy)

Abstract

Mass spectrometry is recognized as the gold standard for glycan analysis, yet the complexity of the generated data hampers progress in glycobiology, as existing tools lack full automation, requiring extensive manual effort. We introduce GlycoGenius, an open-source program offering an automated workflow for glycomics data analysis, featuring an intuitive graphical interface. With algorithms tailored to reduce manual workload, it allows for data visualization and automatically constructs search spaces, identifies, scores, and quantifies glycans, filters results, and annotates fragment spectra of N- and O-glycans, glycosaminoglycans and more. It seamlessly guides researchers of all expertise levels from raw data to publication-ready figures. Our findings demonstrate that GlycoGenius achieves results comparable to manual analysis or competing tools, identifying more glycans, including novel ones, while significantly reducing processing time. This groundbreaking tool represents a significant advancement in the study of glycoconjugates, empowering researchers to focus on insights rather than data processing.

Suggested Citation

  • Hector F. Loponte & Jing Zheng & Yajie Ding & Isadora A. Oliveira & Kristoffer Basse & Adriane R. Todeschini & Peter L. Horvatovich & Guinevere S. M. Lageveen-Kammeijer, 2025. "GlycoGenius: a streamlined high-throughput glycan composition identification tool," Nature Communications, Nature, vol. 16(1), pages 1-17, December.
    • Handle: RePEc:nat:natcom:v:16:y:2025:i:1:d:10.1038_s41467-025-65265-2
    DOI: 10.1038/s41467-025-65265-2
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