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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.
Afiliação
  • Vila JCC; Department of Ecology and Evolutionary Biology, Yale University, New Haven, CT USA.
  • Goldford J; Microbial Sciences Institute, Yale University, West Haven, CT, USA.
  • Estrela S; Department of Biology, Stanford University, Stanford, CA, USA.
  • Bajic D; Division of Geophysical and Planetary sciences,California Institute of Technology, Pasadena, CA, USA.
  • Sanchez-Gorostiaga A; Department of Ecology and Evolutionary Biology, Yale University, New Haven, CT USA.
  • Damian-Serrano A; Microbial Sciences Institute, Yale University, West Haven, CT, USA.
  • Lu N; Department of Bioengineering, Stanford University, Stanford, CA, USA.
  • Marsland R; Department of Ecology and Evolutionary Biology, Yale University, New Haven, CT USA.
  • Rebolleda-Gomez M; Microbial Sciences Institute, Yale University, West Haven, CT, USA.
  • Mehta P; Section of Industrial Microbiology, Department of Biotechnology, Technical University Delft, Delft, The Netherlands.
  • Sanchez A; Department of Ecology and Evolutionary Biology, Yale University, New Haven, CT USA.
bioRxiv ; 2023 Oct 28.
Article em En | MEDLINE | ID: mdl-37961608
ABSTRACT
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.

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: BioRxiv Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: BioRxiv Ano de publicação: 2023 Tipo de documento: Article