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A substrate-multiplexed platform for profiling enzymatic potential of plant family 1 glycosyltransferases

Author

Listed:
  • Sasilada Sirirungruang

    (University of California
    Joint BioEnergy Institute
    Lawrence Berkeley National Laboratory
    Suranaree University of Technology)

  • Vincent Blay

    (Joint BioEnergy Institute)

  • Elys P. Rodriguez

    (University of California
    University of California)

  • Yasmine F. Scott

    (Joint BioEnergy Institute
    University of California)

  • Khanh M. Vuu

    (Joint BioEnergy Institute)

  • Collin R. Barnum

    (University of California
    University of California)

  • Paul H. Opgenorth

    (Joint BioEnergy Institute)

  • Fanzhou Kong

    (University of California
    University of California)

  • Yuanyue Li

    (University of California)

  • Oliver Fiehn

    (University of California
    University of California)

  • Patrick M. Shih

    (University of California
    Joint BioEnergy Institute
    Lawrence Berkeley National Laboratory
    University of California)

Abstract

Plants have expanded various biosynthetic enzyme families to produce a wide diversity of natural products; however, most enzymes encoded in plant genomes remain uncharacterized, highlighting the need for new functional genomic approaches. Here, we report a platform enabling the rapid functional characterization of plant family 1 glycosyltransferases, which serve important roles in plant development, defense, and communication. Using substrate-multiplexed reactions, mass spectrometry, and automated analysis, we screen 85 enzymes against a diverse library of 453 natural products, for a total of nearly 40,000 possible reactions. The resulting dataset reveals a widespread promiscuity and a strong preference for planar, hydroxylated aromatic substrates among family 1 glycosyltransferases. We also characterize glycosyltransferases with an unusually wide substrate scope and with a non-canonical Cys-Asp catalytic dyad. This work establishes a widely-applicable enzymatic screening pipeline, reflects the immense glycosylation capability of plants, and has implications in biocatalysis, metabolic engineering, and gene discovery.

Suggested Citation

  • Sasilada Sirirungruang & Vincent Blay & Elys P. Rodriguez & Yasmine F. Scott & Khanh M. Vuu & Collin R. Barnum & Paul H. Opgenorth & Fanzhou Kong & Yuanyue Li & Oliver Fiehn & Patrick M. Shih, 2025. "A substrate-multiplexed platform for profiling enzymatic potential of plant family 1 glycosyltransferases," Nature Communications, Nature, vol. 16(1), pages 1-12, December.
  • Handle: RePEc:nat:natcom:v:16:y:2025:i:1:d:10.1038_s41467-025-61530-6
    DOI: 10.1038/s41467-025-61530-6
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    References listed on IDEAS

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    1. John Jumper & Richard Evans & Alexander Pritzel & Tim Green & Michael Figurnov & Olaf Ronneberger & Kathryn Tunyasuvunakool & Russ Bates & Augustin Žídek & Anna Potapenko & Alex Bridgland & Clemens Me, 2021. "Highly accurate protein structure prediction with AlphaFold," Nature, Nature, vol. 596(7873), pages 583-589, August.
    2. Kerstin Scheubert & Franziska Hufsky & Daniel Petras & Mingxun Wang & Louis-Félix Nothias & Kai Dührkop & Nuno Bandeira & Pieter C. Dorrestein & Sebastian Böcker, 2017. "Significance estimation for large scale metabolomics annotations by spectral matching," Nature Communications, Nature, vol. 8(1), pages 1-10, December.
    3. Kathryn Tunyasuvunakool & Jonas Adler & Zachary Wu & Tim Green & Michal Zielinski & Augustin Žídek & Alex Bridgland & Andrew Cowie & Clemens Meyer & Agata Laydon & Sameer Velankar & Gerard J. Kleywegt, 2021. "Highly accurate protein structure prediction for the human proteome," Nature, Nature, vol. 596(7873), pages 590-596, August.
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