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Reverse metabolomics for the discovery of chemical structures from humans

Abstract

Determining structure and phenotypic context of molecules detected in untargeted metabolomics experiments remains challenging. Here, we present reverse metabolomics as a discovery strategy, where MS/MS spectra are acquired from newly synthesized compounds and searched for in public metabolomics data to uncover phenotypic associations. To demonstrate the concept, we broadly synthesized and explored multiple classes of metabolites in humans – N-acyl amides, fatty acid esters of hydroxy fatty acids, bile acid esters and conjugated bile acids. Using repository scale analysis,15,16 we discovered that some conjugated bile acids were associated with inflammatory bowel disease (IBD). Using four distinct human IBD cohorts for validation, we found that Glu, Ile/Leu, Phe, Thr, Trp and Tyr conjugated cholic acids were elevated in Crohn’s disease. Several of these compounds and related structures were shown to affect pathways associated with inflammatory bowel disease, such as interferon-gamma production in CD4+ T cells40 and PXR agonism.41 Bacteria belonging to the Bifidobacterium, Clostridium, and Enterococcus genera were able to produce these bile amidates when cultured. Because searching repositories with MS/MS spectra has only recently become possible, reverse metabolomics approach can now be employed as a general strategy to discover other molecules from human and animal ecosystems.

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Authors and Affiliations

  1. Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, San Diego, CA, USA

    Emily C. Gentry, Morgan Panitchpakdi, Simone Zuffa, Allegra T. Aron, Mingxun Wang, Alan K. Jarmusch, Dionicio Siegel & Pieter C. Dorrestein

  2. Collaborative Mass Spectrometry Innovation Center, Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, CA, USA

    Emily C. Gentry, Morgan Panitchpakdi, Simone Zuffa, Allegra T. Aron, Mingxun Wang, Alan K. Jarmusch & Pieter C. Dorrestein

  3. Department of Pediatrics, University of California San Diego, La Jolla, CA, USA

    Pedro Belda-Ferre & Rob Knight

  4. Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA

    Julian Avila-Pacheco, Damian R. Plichta, Hera Vlamakis, Clary B. Clish & Ramnik J. Xavier

  5. Center for Microbiome Informatics and Therapeutics, Massachusetts Institute of Technology, Cambridge, MA, USA

    Hera Vlamakis & Ramnik J. Xavier

  6. Center for Computational and Integrative Biology Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA

    Ramnik J. Xavier

  7. Department of Molecular Biology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA

    Ramnik J. Xavier

  8. Department of Chemistry, North Carolina State University, Raleigh, NC, USA

    Allison K. Stewart & Erin S. Baker

  9. Department of Chemistry, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA

    Erin S. Baker

  10. Center for Molecular Toxicology and Carcinogenesis, Department of Veterinary and Biomedical Sciences, The Pennsylvania State University, University Park, PA, USA

    Fuhua Hao & Andrew D. Patterson

  11. Department of Computer Science, Jacobs School of Engineering, University of California, San Diego, California, USA

    Pedro Belda-Ferre & Rob Knight

  12. Center for Microbiome Innovation, Jacobs School of Engineering, University of California, San Diego, California, USA

    Rob Knight

  13. Department of Bioengineering, University of California, San Diego, California, USA

    Rob Knight

  14. Immunity, Inflammation, and Disease Laboratory, Division of Intramural Research, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, NC, USA

    Alan K. Jarmusch

  15. Department of Biochemistry and Molecular Biology, The Pennsylvania State University, University Park, PA, USA

    Stephanie L. Collins

  16. Division of Gastroenterology, Massachusetts General Hospital, Boston, MA, USA

    Ashwin N. Ananthakrishnan

  17. Division of Gastroenterology, Department of Pediatrics, Rady Children’s Hospital University of California, San Diego, La Jolla, California, USA

    Mashette Syrkin-Nikolau & Amy Hemperly

  18. Division of Gastroenterology, University of California, San Diego, La Jolla, California, USA

    Brigid Boland & Niels Vande Casteele

  19. Department of Pathology, University of California, San Diego, La Jolla, California, USA

    Marvic Carrillo Terrazas, Hsueh-han Lu & Hiutung Chu

  20. CU-UCSD, Center for Mucosal Immunology, Allergy and Vaccine Development, University of California, San Diego, La Jolla, California, USA

    Hiutung Chu

  21. Laboratory of Metabolism, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA

    Tingting Yan & Frank J. Gonzalez

  22. Department of Chemistry, Virginia Tech, Blacksburg, VA, USA

    Emily C. Gentry

Authors

  1. Emily C. Gentry
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  29. Dionicio Siegel
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  30. Pieter C. Dorrestein
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Corresponding author

Correspondence to
Pieter C. Dorrestein.

Supplementary information

Supplementary Information

The Supporting Information provides synthetic methods and characterization data for pure compounds as text and includes 27 display items showing 1H and 13C NMR spectra. It also contains tables displaying counts of spectral matches and a figure showing gating strategy for flow cytometry.

Reporting Summary

Supplementary Table 4

The collision values used for the MS/MS data acquisition on the QToF.

Supplementary Table 5

Universal Spectrum Identifiers (USIs) and MASST job IDs for all synthesized compounds.

Supplementary Table 6

Precursor masses, mass accuracies and retention times for conjugated bile acids detected in iHMP2 stool samples on a Thermo QE Orbitrap in negative mode.

Supplementary Table 7

Relative abundances of conjugated bile acids across bacterial strains.

Supplementary Table 8

Precursor masses, mass accuracies and retention times for conjugated bile acids detected in bacterial cultures on a Bruker Q-ToF in positive mode.

Supplementary Table 9

Representative precursor values, ppm mass accuracies, retention times, CCS values and key confirmatory MS/MS fragments from conjugated bile acids detected in bacterial cultures on Agilent 6560 IM-QTOF MS instrument in negative mode.

Supplementary Table 10

Precursor masses, mass accuracies and retention times for conjugated bile acids detected in human IBD fecal samples on a Bruker Q-ToF in positive mode.

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Gentry, E.C., Collins, S.L., Panitchpakdi, M. et al. Reverse metabolomics for the discovery of chemical structures from humans.
Nature (2023). https://doi.org/10.1038/s41586-023-06906-8

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  • Received: 16 August 2021

  • Accepted: 28 November 2023

  • Published: 05 December 2023

  • DOI: https://doi.org/10.1038/s41586-023-06906-8

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