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Kryazhimskiy S. A simple rule for predicting function of microbial communities. Cell 2024; 187:2905-2906. [PMID: 38848675 DOI: 10.1016/j.cell.2024.04.024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2024] [Revised: 04/18/2024] [Accepted: 04/19/2024] [Indexed: 06/09/2024]
Abstract
Microbial communities perform many important functions, such as carbon sequestration, decomposition, pathogen resistance, etc., but quantitatively predicting functions of new communities remains a major challenge. In this issue of Cell, Diaz-Colunga et al. report a new simple statistical regularity that enables such predictions.
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Affiliation(s)
- Sergey Kryazhimskiy
- Department of Ecology, Behavior, and Evolution, University of California, San Diego, La Jolla, CA, USA.
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Diaz-Colunga J, Skwara A, Vila JCC, Bajic D, Sanchez A. Global epistasis and the emergence of function in microbial consortia. Cell 2024; 187:3108-3119.e30. [PMID: 38776921 DOI: 10.1016/j.cell.2024.04.016] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2023] [Revised: 12/06/2023] [Accepted: 04/16/2024] [Indexed: 05/25/2024]
Abstract
The many functions of microbial communities emerge from a complex web of interactions between organisms and their environment. This poses a significant obstacle to engineering microbial consortia, hindering our ability to harness the potential of microorganisms for biotechnological applications. In this study, we demonstrate that the collective effect of ecological interactions between microbes in a community can be captured by simple statistical models that predict how adding a new species to a community will affect its function. These predictive models mirror the patterns of global epistasis reported in genetics, and they can be quantitatively interpreted in terms of pairwise interactions between community members. Our results illuminate an unexplored path to quantitatively predicting the function of microbial consortia from their composition, paving the way to optimizing desirable community properties and bringing the tasks of predicting biological function at the genetic, organismal, and ecological scales under the same quantitative formalism.
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Affiliation(s)
- Juan Diaz-Colunga
- Department of Ecology & Evolutionary Biology, Yale University, New Haven, CT 06511, USA; Microbial Sciences Institute, Yale University, New Haven, CT 06511, USA; Department of Microbial Biotechnology, National Center for Biotechnology CNB-CSIC, 28049 Madrid, Spain; Institute of Functional Biology and Genomics IBFG-CSIC, University of Salamanca, 37007 Salamanca, Spain.
| | - Abigail Skwara
- Department of Ecology & Evolutionary Biology, Yale University, New Haven, CT 06511, USA; Microbial Sciences Institute, Yale University, New Haven, CT 06511, USA
| | - Jean C C Vila
- Department of Ecology & Evolutionary Biology, Yale University, New Haven, CT 06511, USA; Microbial Sciences Institute, Yale University, New Haven, CT 06511, USA; Department of Biology, Stanford University, Stanford, CA 94305, USA
| | - Djordje Bajic
- Department of Ecology & Evolutionary Biology, Yale University, New Haven, CT 06511, USA; Microbial Sciences Institute, Yale University, New Haven, CT 06511, USA; Department of Biotechnology, Delft University of Technology, Delft 2628 CD, the Netherlands.
| | - Alvaro Sanchez
- Department of Ecology & Evolutionary Biology, Yale University, New Haven, CT 06511, USA; Microbial Sciences Institute, Yale University, New Haven, CT 06511, USA; Department of Microbial Biotechnology, National Center for Biotechnology CNB-CSIC, 28049 Madrid, Spain; Institute of Functional Biology and Genomics IBFG-CSIC, University of Salamanca, 37007 Salamanca, Spain.
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Kempes CP. The sparse macroecology of microbiology. Proc Natl Acad Sci U S A 2024; 121:e2318518120. [PMID: 38252826 PMCID: PMC10835028 DOI: 10.1073/pnas.2318518120] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/24/2024] Open
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Doran BA, Chen RY, Giba H, Behera V, Barat B, Sundararajan A, Lin H, Sidebottom A, Pamer EG, Raman AS. An evolution-based framework for describing human gut bacteria. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.12.04.569969. [PMID: 38105970 PMCID: PMC10723311 DOI: 10.1101/2023.12.04.569969] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/19/2023]
Abstract
The human gut microbiome contains many bacterial strains of the same species ('strain-level variants'). Describing strains in a biologically meaningful way rather than purely taxonomically is an important goal but challenging due to the genetic complexity of strain-level variation. Here, we measured patterns of co-evolution across >7,000 strains spanning the bacterial tree-of-life. Using these patterns as a prior for studying hundreds of gut commensal strains that we isolated, sequenced, and metabolically profiled revealed widespread structure beneath the phylogenetic level of species. Defining strains by their co-evolutionary signatures enabled predicting their metabolic phenotypes and engineering consortia from strain genome content alone. Our findings demonstrate a biologically relevant organization to strain-level variation and motivate a new schema for describing bacterial strains based on their evolutionary history.
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Affiliation(s)
- Benjamin A. Doran
- Duchossois Family Institute, University of Chicago, Chicago, IL, 60637
- Pritzker School of Molecular Engineering, University of Chicago, Chicago, IL, 60637
| | - Robert Y. Chen
- Department of Psychiatry, University of Washington, Seattle, WA, 98195
| | - Hannah Giba
- Duchossois Family Institute, University of Chicago, Chicago, IL, 60637
- Department of Pathology, University of Chicago, Chicago, IL, 60637
| | - Vivek Behera
- Department of Medicine, University of Chicago, Chicago, IL, 60637
| | - Bidisha Barat
- Duchossois Family Institute, University of Chicago, Chicago, IL, 60637
| | | | - Huaiying Lin
- Duchossois Family Institute, University of Chicago, Chicago, IL, 60637
| | - Ashley Sidebottom
- Duchossois Family Institute, University of Chicago, Chicago, IL, 60637
| | - Eric G. Pamer
- Duchossois Family Institute, University of Chicago, Chicago, IL, 60637
- Department of Medicine, University of Chicago, Chicago, IL, 60637
| | - Arjun S. Raman
- Duchossois Family Institute, University of Chicago, Chicago, IL, 60637
- Department of Pathology, University of Chicago, Chicago, IL, 60637
- Center for the Physics of Evolving Systems, University of Chicago, Chicago, IL, 60637
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