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HypoRiPPAtlas as an Atlas of hypothetical natural products for mass spectrometry database search

Author

Listed:
  • Yi-Yuan Lee

    (Carnegie Mellon University
    Cornell University)

  • Mustafa Guler

    (Carnegie Mellon University)

  • Desnor N. Chigumba

    (University of Michigan)

  • Shen Wang

    (Carnegie Mellon University)

  • Neel Mittal

    (Carnegie Mellon University)

  • Cameron Miller

    (Carnegie Mellon University)

  • Benjamin Krummenacher

    (Carnegie Mellon University)

  • Haodong Liu

    (Carnegie Mellon University)

  • Liu Cao

    (Carnegie Mellon University)

  • Aditya Kannan

    (Carnegie Mellon University)

  • Keshav Narayan

    (Carnegie Mellon University)

  • Samuel T. Slocum

    (University of North Carolina)

  • Bryan L. Roth

    (University of North Carolina)

  • Alexey Gurevich

    (Helmholtz Centre for Infection Research
    Saarland University)

  • Bahar Behsaz

    (Carnegie Mellon University)

  • Roland D. Kersten

    (University of Michigan)

  • Hosein Mohimani

    (Carnegie Mellon University)

Abstract

Recent analyses of public microbial genomes have found over a million biosynthetic gene clusters, the natural products of the majority of which remain unknown. Additionally, GNPS harbors billions of mass spectra of natural products without known structures and biosynthetic genes. We bridge the gap between large-scale genome mining and mass spectral datasets for natural product discovery by developing HypoRiPPAtlas, an Atlas of hypothetical natural product structures, which is ready-to-use for in silico database search of tandem mass spectra. HypoRiPPAtlas is constructed by mining genomes using seq2ripp, a machine-learning tool for the prediction of ribosomally synthesized and post-translationally modified peptides (RiPPs). In HypoRiPPAtlas, we identify RiPPs in microbes and plants. HypoRiPPAtlas could be extended to other natural product classes in the future by implementing corresponding biosynthetic logic. This study paves the way for large-scale explorations of biosynthetic pathways and chemical structures of microbial and plant RiPP classes.

Suggested Citation

  • Yi-Yuan Lee & Mustafa Guler & Desnor N. Chigumba & Shen Wang & Neel Mittal & Cameron Miller & Benjamin Krummenacher & Haodong Liu & Liu Cao & Aditya Kannan & Keshav Narayan & Samuel T. Slocum & Bryan , 2023. "HypoRiPPAtlas as an Atlas of hypothetical natural products for mass spectrometry database search," Nature Communications, Nature, vol. 14(1), pages 1-17, December.
    • Handle: RePEc:nat:natcom:v:14:y:2023:i:1:d:10.1038_s41467-023-39905-4
    DOI: 10.1038/s41467-023-39905-4
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    References listed on IDEAS

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    1. Angel Rivera-Calzada & Raquel Arribas-Bosacoma & Alba Ruiz-Ramos & Paloma Escudero-Bravo & Jasminka Boskovic & Rafael Fernandez-Leiro & Antony W. Oliver & Laurence H. Pearl & Oscar Llorca, 2022. "Structural basis for the inactivation of cytosolic DNA sensing by the vaccinia virus," Nature Communications, Nature, vol. 13(1), pages 1-13, December.
    2. Hosein Mohimani & Alexey Gurevich & Alexander Shlemov & Alla Mikheenko & Anton Korobeynikov & Liu Cao & Egor Shcherbin & Louis-Felix Nothias & Pieter C. Dorrestein & Pavel A. Pevzner, 2018. "Dereplication of microbial metabolites through database search of mass spectra," Nature Communications, Nature, vol. 9(1), pages 1-12, December.
    3. Michael A. Skinnider & Chad W. Johnston & Mathusan Gunabalasingam & Nishanth J. Merwin & Agata M. Kieliszek & Robyn J. MacLellan & Haoxin Li & Michael R. M. Ranieri & Andrew L. H. Webster & My P. T. C, 2020. "Comprehensive prediction of secondary metabolite structure and biological activity from microbial genome sequences," Nature Communications, Nature, vol. 11(1), pages 1-9, December.
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