Molecular Systems Biology (Sep 2023)

Predictability of the community‐function landscape in wine yeast ecosystems

  • Javier Ruiz,
  • Miguel deCelis,
  • Juan Diaz‐Colunga,
  • Jean CC Vila,
  • Belen Benitez‐Dominguez,
  • Javier Vicente,
  • Antonio Santos,
  • Alvaro Sanchez,
  • Ignacio Belda

DOI
https://doi.org/10.15252/msb.202311613
Journal volume & issue
Vol. 19, no. 9
pp. n/a – n/a

Abstract

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Abstract Predictively linking taxonomic composition and quantitative ecosystem functions is a major aspiration in microbial ecology, which must be resolved if we wish to engineer microbial consortia. Here, we have addressed this open question for an ecological function of major biotechnological relevance: alcoholic fermentation in wine yeast communities. By exhaustively phenotyping an extensive collection of naturally occurring wine yeast strains, we find that most ecologically and industrially relevant traits exhibit phylogenetic signal, allowing functional traits in wine yeast communities to be predicted from taxonomy. Furthermore, we demonstrate that the quantitative contributions of individual wine yeast strains to the function of complex communities followed simple quantitative rules. These regularities can be integrated to quantitatively predict the function of newly assembled consortia. Besides addressing theoretical questions in functional ecology, our results and methodologies can provide a blueprint for rationally managing microbial processes of biotechnological relevance.

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