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Design of synthetic bacterial communities for predictable plant phenotypes.
Herrera Paredes, Sur; Gao, Tianxiang; Law, Theresa F; Finkel, Omri M; Mucyn, Tatiana; Teixeira, Paulo José Pereira Lima; Salas González, Isaí; Feltcher, Meghan E; Powers, Matthew J; Shank, Elizabeth A; Jones, Corbin D; Jojic, Vladimir; Dangl, Jeffery L; Castrillo, Gabriel.
Afiliação
  • Herrera Paredes S; Department of Biology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America.
  • Gao T; Howard Hughes Medical Institute, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America.
  • Law TF; Curriculum in Bioinformatics and Computational Biology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America.
  • Finkel OM; Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America.
  • Mucyn T; Department of Biology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America.
  • Teixeira PJPL; Howard Hughes Medical Institute, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America.
  • Salas González I; Department of Biology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America.
  • Feltcher ME; Howard Hughes Medical Institute, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America.
  • Powers MJ; Department of Biology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America.
  • Shank EA; Howard Hughes Medical Institute, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America.
  • Jones CD; Department of Biology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America.
  • Jojic V; Howard Hughes Medical Institute, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America.
  • Dangl JL; Department of Biology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America.
  • Castrillo G; Howard Hughes Medical Institute, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America.
PLoS Biol ; 16(2): e2003962, 2018 02.
Article em En | MEDLINE | ID: mdl-29462153
ABSTRACT
Specific members of complex microbiota can influence host phenotypes, depending on both the abiotic environment and the presence of other microorganisms. Therefore, it is challenging to define bacterial combinations that have predictable host phenotypic outputs. We demonstrate that plant-bacterium binary-association assays inform the design of small synthetic communities with predictable phenotypes in the host. Specifically, we constructed synthetic communities that modified phosphate accumulation in the shoot and induced phosphate starvation-responsive genes in a predictable fashion. We found that bacterial colonization of the plant is not a predictor of the plant phenotypes we analyzed. Finally, we demonstrated that characterizing a subset of all possible bacterial synthetic communities is sufficient to predict the outcome of untested bacterial consortia. Our results demonstrate that it is possible to infer causal relationships between microbiota membership and host phenotypes and to use these inferences to rationally design novel communities.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Ano de publicação: 2018 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Ano de publicação: 2018 Tipo de documento: Article