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A metabolomics pipeline for the mechanistic interrogation of the gut microbiome

Author

Listed:
  • Shuo Han

    (Stanford University School of Medicine)

  • Will Treuren

    (Stanford University School of Medicine
    Stanford University School of Medicine)

  • Curt R. Fischer

    (ChEM-H, Stanford University
    Chan Zuckerberg Biohub)

  • Bryan D. Merrill

    (Stanford University School of Medicine
    Stanford University School of Medicine)

  • Brian C. DeFelice

    (Chan Zuckerberg Biohub)

  • Juan M. Sanchez

    (Chan Zuckerberg Biohub)

  • Steven K. Higginbottom

    (Stanford University School of Medicine)

  • Leah Guthrie

    (Stanford University School of Medicine)

  • Lalla A. Fall

    (ChEM-H, Stanford University
    Stanford University School of Medicine)

  • Dylan Dodd

    (Stanford University School of Medicine
    Stanford University School of Medicine)

  • Michael A. Fischbach

    (Chan Zuckerberg Biohub
    Stanford University)

  • Justin L. Sonnenburg

    (Stanford University School of Medicine
    Chan Zuckerberg Biohub
    Center for Human Microbiome Studies)

Abstract

Gut microorganisms modulate host phenotypes and are associated with numerous health effects in humans, ranging from host responses to cancer immunotherapy to metabolic disease and obesity. However, difficulty in accurate and high-throughput functional analysis of human gut microorganisms has hindered efforts to define mechanistic connections between individual microbial strains and host phenotypes. One key way in which the gut microbiome influences host physiology is through the production of small molecules1–3, yet progress in elucidating this chemical interplay has been hindered by limited tools calibrated to detect the products of anaerobic biochemistry in the gut. Here we construct a microbiome-focused, integrated mass-spectrometry pipeline to accelerate the identification of microbiota-dependent metabolites in diverse sample types. We report the metabolic profiles of 178 gut microorganism strains using our library of 833 metabolites. Using this metabolomics resource, we establish deviations in the relationships between phylogeny and metabolism, use machine learning to discover a previously undescribed type of metabolism in Bacteroides, and reveal candidate biochemical pathways using comparative genomics. Microbiota-dependent metabolites can be detected in diverse biological fluids from gnotobiotic and conventionally colonized mice and traced back to the corresponding metabolomic profiles of cultured bacteria. Collectively, our microbiome-focused metabolomics pipeline and interactive metabolomics profile explorer are a powerful tool for characterizing microorganisms and interactions between microorganisms and their host.

Suggested Citation

  • Shuo Han & Will Treuren & Curt R. Fischer & Bryan D. Merrill & Brian C. DeFelice & Juan M. Sanchez & Steven K. Higginbottom & Leah Guthrie & Lalla A. Fall & Dylan Dodd & Michael A. Fischbach & Justin , 2021. "A metabolomics pipeline for the mechanistic interrogation of the gut microbiome," Nature, Nature, vol. 595(7867), pages 415-420, July.
  • Handle: RePEc:nat:nature:v:595:y:2021:i:7867:d:10.1038_s41586-021-03707-9
    DOI: 10.1038/s41586-021-03707-9
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    Cited by:

    1. Qi Zhao & Man-Yun Dai & Ruo-Yue Huang & Jing-Yi Duan & Ting Zhang & Wei-Min Bao & Jing-Yi Zhang & Shao-Qiang Gui & Shu-Min Xia & Cong-Ting Dai & Ying-Mei Tang & Frank J. Gonzalez & Fei Li, 2023. "Parabacteroides distasonis ameliorates hepatic fibrosis potentially via modulating intestinal bile acid metabolism and hepatocyte pyroptosis in male mice," Nature Communications, Nature, vol. 14(1), pages 1-18, December.
    2. Juan Salazar & Pablo Durán & María P. Díaz & Maricarmen Chacín & Raquel Santeliz & Edgardo Mengual & Emma Gutiérrez & Xavier León & Andrea Díaz & Marycarlota Bernal & Daniel Escalona & Luis Alberto Pa, 2023. "Exploring the Relationship between the Gut Microbiota and Ageing: A Possible Age Modulator," IJERPH, MDPI, vol. 20(10), pages 1-24, May.
    3. Kali M. Pruss & Haoqing Chen & Yuanyuan Liu & William Treuren & Steven K. Higginbottom & John B. Jarman & Curt R. Fischer & Justin Mak & Beverly Wong & Tina M. Cowan & Michael A. Fischbach & Justin L., 2023. "Host-microbe co-metabolism via MCAD generates circulating metabolites including hippuric acid," Nature Communications, Nature, vol. 14(1), pages 1-12, December.

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