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MS2Query: reliable and scalable MS2 mass spectra-based analogue search

Author

Listed:
  • Niek F. de Jonge

    (Wageningen University & Research)

  • Joris J. R. Louwen

    (Wageningen University & Research)

  • Elena Chekmeneva

    (Digestion and Reproduction, Faculty of Medicine, Imperial College London, Hammersmith Hospital Campus)

  • Stephane Camuzeaux

    (Digestion and Reproduction, Faculty of Medicine, Imperial College London, Hammersmith Hospital Campus)

  • Femke J. Vermeir

    (Radboud University)

  • Robert S. Jansen

    (Radboud University)

  • Florian Huber

    (University of Applied Sciences Düsseldorf)

  • Justin J. J. van der Hooft

    (Wageningen University & Research
    University of Johannesburg, Auckland Park)

Abstract

Metabolomics-driven discoveries of biological samples remain hampered by the grand challenge of metabolite annotation and identification. Only few metabolites have an annotated spectrum in spectral libraries; hence, searching only for exact library matches generally returns a few hits. An attractive alternative is searching for so-called analogues as a starting point for structural annotations; analogues are library molecules which are not exact matches but display a high chemical similarity. However, current analogue search implementations are not yet very reliable and relatively slow. Here, we present MS2Query, a machine learning-based tool that integrates mass spectral embedding-based chemical similarity predictors (Spec2Vec and MS2Deepscore) as well as detected precursor masses to rank potential analogues and exact matches. Benchmarking MS2Query on reference mass spectra and experimental case studies demonstrate improved reliability and scalability. Thereby, MS2Query offers exciting opportunities to further increase the annotation rate of metabolomics profiles of complex metabolite mixtures and to discover new biology.

Suggested Citation

  • Niek F. de Jonge & Joris J. R. Louwen & Elena Chekmeneva & Stephane Camuzeaux & Femke J. Vermeir & Robert S. Jansen & Florian Huber & Justin J. J. van der Hooft, 2023. "MS2Query: reliable and scalable MS2 mass spectra-based analogue search," Nature Communications, Nature, vol. 14(1), pages 1-12, December.
    • Handle: RePEc:nat:natcom:v:14:y:2023:i:1:d:10.1038_s41467-023-37446-4
    DOI: 10.1038/s41467-023-37446-4
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    References listed on IDEAS

    as
    1. Florian Huber & Lars Ridder & Stefan Verhoeven & Jurriaan H Spaaks & Faruk Diblen & Simon Rogers & Justin J J van der Hooft, 2021. "Spec2Vec: Improved mass spectral similarity scoring through learning of structural relationships," PLOS Computational Biology, Public Library of Science, vol. 17(2), pages 1-18, February.
    2. Boran Kartal & Wouter J. Maalcke & Naomi M. de Almeida & Irina Cirpus & Jolein Gloerich & Wim Geerts & Huub J. M. Op den Camp & Harry R. Harhangi & Eva M. Janssen-Megens & Kees-Jan Francoijs & Hendrik, 2011. "Molecular mechanism of anaerobic ammonium oxidation," Nature, Nature, vol. 479(7371), pages 127-130, November.
    3. Robert S. Jansen & Lungelo Mandyoli & Ryan Hughes & Shoko Wakabayashi & Jessica T. Pinkham & Bruna Selbach & Kristine M. Guinn & Eric J. Rubin & James C. Sacchettini & Kyu Y. Rhee, 2020. "Aspartate aminotransferase Rv3722c governs aspartate-dependent nitrogen metabolism in Mycobacterium tuberculosis," Nature Communications, Nature, vol. 11(1), pages 1-13, December.
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