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Quinn-Bohmann N, Freixas-Coutin JA, Seo J, Simmons R, Diener C, Gibbons SM. Meta-analysis of the human upper respiratory tract microbiome reveals robust taxonomic associations with health and disease. BMC Biol 2024; 22:93. [PMID: 38654335 PMCID: PMC11040984 DOI: 10.1186/s12915-024-01887-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2023] [Accepted: 04/15/2024] [Indexed: 04/25/2024] Open
Abstract
BACKGROUND The human upper respiratory tract (URT) microbiome, like the gut microbiome, varies across individuals and between health and disease states. However, study-to-study heterogeneity in reported case-control results has made the identification of consistent and generalizable URT-disease associations difficult. RESULTS In order to address this issue, we assembled 26 independent 16S rRNA gene amplicon sequencing data sets from case-control URT studies, with approximately 2-3 studies per respiratory condition and ten distinct conditions covering common chronic and acute respiratory diseases. We leveraged the healthy control data across studies to investigate URT associations with age, sex, and geographic location, in order to isolate these associations from health and disease states. CONCLUSIONS We found several robust genus-level associations, across multiple independent studies, with either health or disease status. We identified disease associations specific to a particular respiratory condition and associations general to all conditions. Ultimately, we reveal robust associations between the URT microbiome, health, and disease, which hold across multiple studies and can help guide follow-up work on potential URT microbiome diagnostics and therapeutics.
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Affiliation(s)
- Nick Quinn-Bohmann
- Institute for Systems Biology, Seattle, WA, 98109, USA.
- Molecular Engineering Graduate Program, University of Washington, Seattle, WA, 98195, USA.
| | | | - Jin Seo
- Reckitt Health US LLC, 1 Philips Pkwy, Montvale, NJ, 07645, USA
| | - Ruth Simmons
- Reckitt Benckiser Healthcare Ltd, 105 Bath Road, Slough, Berkshire, SL1 3UH, UK
| | | | - Sean M Gibbons
- Institute for Systems Biology, Seattle, WA, 98109, USA.
- Molecular Engineering Graduate Program, University of Washington, Seattle, WA, 98195, USA.
- Department of Bioengineering, University of Washington, Seattle, WA, 98195, USA.
- Department of Genome Sciences, University of Washington, Seattle, WA, 98195, USA.
- eScience Institute, University of Washington, Seattle, WA, 98195, USA.
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Quinn-Bohmann N, Wilmanski T, Sarmiento KR, Levy L, Lampe JW, Gurry T, Rappaport N, Ostrem EM, Venturelli OS, Diener C, Gibbons SM. Microbial community-scale metabolic modeling predicts personalized short chain fatty acid production profiles in the human gut. bioRxiv 2023:2023.02.28.530516. [PMID: 36909644 PMCID: PMC10002715 DOI: 10.1101/2023.02.28.530516] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/06/2023]
Abstract
Microbially-derived short chain fatty acids (SCFAs) in the human gut are tightly coupled to host metabolism, immune regulation, and integrity of the intestinal epithelium. However, the production of SCFAs can vary widely between individuals consuming the same diet, with lower levels often associated with disease. A systems-scale mechanistic understanding of this heterogeneity is lacking. We present a microbial community-scale metabolic modeling (MCMM) approach to predict individual-specific SCFA production profiles. We assess the quantitative accuracy of our MCMMs using in vitro, ex vivo, and in vivo data. Next, we show how MCMM SCFA predictions are significantly associated with blood-derived clinical chemistries, including cardiometabolic and immunological health markers, across a large human cohort. Finally, we demonstrate how MCMMs can be leveraged to design personalized dietary, prebiotic, and probiotic interventions that optimize SCFA production in the gut. Our results represent an important advance in engineering gut microbiome functional outputs for precision health and nutrition.
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Affiliation(s)
- Nick Quinn-Bohmann
- Institute for Systems Biology, Seattle, WA 98109, USA
- Molecular Engineering Graduate Program, University of Washington, Seattle, WA 98195, USA
| | | | | | - Lisa Levy
- Fred Hutchinson Cancer Center, Seattle, WA 98109, USA
| | | | - Thomas Gurry
- Pharmaceutical Biochemistry Group, School of Pharmaceutical Sciences, University of Geneva, Switzerland
- Myota GmbH, Berlin, Germany
| | - Noa Rappaport
- Center for Phenomic Health, Buck Institute for Research on Aging, Novato, CA 94945, USA
| | - Erin M. Ostrem
- Department of Biochemistry, University of Wisconsin-Madison, Madison, WI 53706, USA
| | - Ophelia S. Venturelli
- Department of Biochemistry, University of Wisconsin-Madison, Madison, WI 53706, USA
- Department of Biomedical Engineering, University of Wisconsin-Madison, Madison, WI 53706, USA
- Department of Chemical & Biological Engineering, University of Wisconsin-Madison, Madison, WI 53706, USA
- Department of Bacteriology, University of Wisconsin-Madison, Madison, WI 53706, USA
| | | | - Sean M. Gibbons
- Institute for Systems Biology, Seattle, WA 98109, USA
- Molecular Engineering Graduate Program, University of Washington, Seattle, WA 98195, USA
- Department of Bioengineering, University of Washington, Seattle, WA 98195, USA
- Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA
- eScience Institute, University of Washington, Seattle, WA 98195, USA
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