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Metabolic similarity and the predictability of microbial community assembly
When microbial communities form, their composition is shaped by selective pressures imposed by the environment. Can we predict which communities will assemble under different environmental conditions? Here, we hypothesize that quantitative similarities in metabolic traits across metabolically simila...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Cold Spring Harbor Laboratory
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10634833/ https://www.ncbi.nlm.nih.gov/pubmed/37961608 http://dx.doi.org/10.1101/2023.10.25.564019 |
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author | Vila, Jean C.C. Goldford, Joshua Estrela, Sylvie Bajic, Djordje Sanchez-Gorostiaga, Alicia Damian-Serrano, Alejandro Lu, Nanxi Marsland, Robert Rebolleda-Gomez, Maria Mehta, Pankaj Sanchez, Alvaro |
author_facet | Vila, Jean C.C. Goldford, Joshua Estrela, Sylvie Bajic, Djordje Sanchez-Gorostiaga, Alicia Damian-Serrano, Alejandro Lu, Nanxi Marsland, Robert Rebolleda-Gomez, Maria Mehta, Pankaj Sanchez, Alvaro |
author_sort | Vila, Jean C.C. |
collection | PubMed |
description | When microbial communities form, their composition is shaped by selective pressures imposed by the environment. Can we predict which communities will assemble under different environmental conditions? Here, we hypothesize that quantitative similarities in metabolic traits across metabolically similar environments lead to predictable similarities in community composition. To that end, we measured the growth rate and by-product profile of a library of proteobacterial strains in a large number of single nutrient environments. We found that growth rates and secretion profiles were positively correlated across environments when the supplied substrate was metabolically similar. By analyzing hundreds of in-vitro communities experimentally assembled in an array of different synthetic environments, we then show that metabolically similar substrates select for taxonomically similar communities. These findings lead us to propose and then validate a comparative approach for quantitatively predicting the effects of novel substrates on the composition of complex microbial consortia. |
format | Online Article Text |
id | pubmed-10634833 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Cold Spring Harbor Laboratory |
record_format | MEDLINE/PubMed |
spelling | pubmed-106348332023-11-13 Metabolic similarity and the predictability of microbial community assembly Vila, Jean C.C. Goldford, Joshua Estrela, Sylvie Bajic, Djordje Sanchez-Gorostiaga, Alicia Damian-Serrano, Alejandro Lu, Nanxi Marsland, Robert Rebolleda-Gomez, Maria Mehta, Pankaj Sanchez, Alvaro bioRxiv Article When microbial communities form, their composition is shaped by selective pressures imposed by the environment. Can we predict which communities will assemble under different environmental conditions? Here, we hypothesize that quantitative similarities in metabolic traits across metabolically similar environments lead to predictable similarities in community composition. To that end, we measured the growth rate and by-product profile of a library of proteobacterial strains in a large number of single nutrient environments. We found that growth rates and secretion profiles were positively correlated across environments when the supplied substrate was metabolically similar. By analyzing hundreds of in-vitro communities experimentally assembled in an array of different synthetic environments, we then show that metabolically similar substrates select for taxonomically similar communities. These findings lead us to propose and then validate a comparative approach for quantitatively predicting the effects of novel substrates on the composition of complex microbial consortia. Cold Spring Harbor Laboratory 2023-10-28 /pmc/articles/PMC10634833/ /pubmed/37961608 http://dx.doi.org/10.1101/2023.10.25.564019 Text en https://creativecommons.org/licenses/by/4.0/This work is licensed under a Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/) , which allows reusers to distribute, remix, adapt, and build upon the material in any medium or format, so long as attribution is given to the creator. The license allows for commercial use. |
spellingShingle | Article Vila, Jean C.C. Goldford, Joshua Estrela, Sylvie Bajic, Djordje Sanchez-Gorostiaga, Alicia Damian-Serrano, Alejandro Lu, Nanxi Marsland, Robert Rebolleda-Gomez, Maria Mehta, Pankaj Sanchez, Alvaro Metabolic similarity and the predictability of microbial community assembly |
title | Metabolic similarity and the predictability of microbial community assembly |
title_full | Metabolic similarity and the predictability of microbial community assembly |
title_fullStr | Metabolic similarity and the predictability of microbial community assembly |
title_full_unstemmed | Metabolic similarity and the predictability of microbial community assembly |
title_short | Metabolic similarity and the predictability of microbial community assembly |
title_sort | metabolic similarity and the predictability of microbial community assembly |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10634833/ https://www.ncbi.nlm.nih.gov/pubmed/37961608 http://dx.doi.org/10.1101/2023.10.25.564019 |
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