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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...

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Autores principales: 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
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cold Spring Harbor Laboratory 2023
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.
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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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