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Formation, characterization and modeling of emergent synthetic microbial communities()

Microbial communities colonize plant tissues and contribute to host function. How these communities form and how individual members contribute to shaping the microbial community are not well understood. Synthetic microbial communities, where defined individual isolates are combined, can serve as val...

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Autores principales: Wang, Jia, Carper, Dana L., Burdick, Leah H., Shrestha, Him K., Appidi, Manasa R., Abraham, Paul E., Timm, Collin M., Hettich, Robert L., Pelletier, Dale A., Doktycz, Mitchel J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Research Network of Computational and Structural Biotechnology 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8079826/
https://www.ncbi.nlm.nih.gov/pubmed/33995895
http://dx.doi.org/10.1016/j.csbj.2021.03.034
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author Wang, Jia
Carper, Dana L.
Burdick, Leah H.
Shrestha, Him K.
Appidi, Manasa R.
Abraham, Paul E.
Timm, Collin M.
Hettich, Robert L.
Pelletier, Dale A.
Doktycz, Mitchel J.
author_facet Wang, Jia
Carper, Dana L.
Burdick, Leah H.
Shrestha, Him K.
Appidi, Manasa R.
Abraham, Paul E.
Timm, Collin M.
Hettich, Robert L.
Pelletier, Dale A.
Doktycz, Mitchel J.
author_sort Wang, Jia
collection PubMed
description Microbial communities colonize plant tissues and contribute to host function. How these communities form and how individual members contribute to shaping the microbial community are not well understood. Synthetic microbial communities, where defined individual isolates are combined, can serve as valuable model systems for uncovering the organizational principles of communities. Using genome-defined organisms, systematic analysis by computationally-based network reconstruction can lead to mechanistic insights and the metabolic interactions between species. In this study, 10 bacterial strains isolated from the Populus deltoides rhizosphere were combined and passaged in two different media environments to form stable microbial communities. The membership and relative abundances of the strains stabilized after around 5 growth cycles and resulted in just a few dominant strains that depended on the medium. To unravel the underlying metabolic interactions, flux balance analysis was used to model microbial growth and identify potential metabolic exchanges involved in shaping the microbial communities. These analyses were complemented by growth curves of the individual isolates, pairwise interaction screens, and metaproteomics of the community. A fast growth rate is identified as one factor that can provide an advantage for maintaining presence in the community. Final community selection can also depend on selective antagonistic relationships and metabolic exchanges. Revealing the mechanisms of interaction among plant-associated microorganisms provides insights into strategies for engineering microbial communities that can potentially increase plant growth and disease resistance. Further, deciphering the membership and metabolic potentials of a bacterial community will enable the design of synthetic communities with desired biological functions.
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spelling pubmed-80798262021-05-13 Formation, characterization and modeling of emergent synthetic microbial communities() Wang, Jia Carper, Dana L. Burdick, Leah H. Shrestha, Him K. Appidi, Manasa R. Abraham, Paul E. Timm, Collin M. Hettich, Robert L. Pelletier, Dale A. Doktycz, Mitchel J. Comput Struct Biotechnol J Research Article Microbial communities colonize plant tissues and contribute to host function. How these communities form and how individual members contribute to shaping the microbial community are not well understood. Synthetic microbial communities, where defined individual isolates are combined, can serve as valuable model systems for uncovering the organizational principles of communities. Using genome-defined organisms, systematic analysis by computationally-based network reconstruction can lead to mechanistic insights and the metabolic interactions between species. In this study, 10 bacterial strains isolated from the Populus deltoides rhizosphere were combined and passaged in two different media environments to form stable microbial communities. The membership and relative abundances of the strains stabilized after around 5 growth cycles and resulted in just a few dominant strains that depended on the medium. To unravel the underlying metabolic interactions, flux balance analysis was used to model microbial growth and identify potential metabolic exchanges involved in shaping the microbial communities. These analyses were complemented by growth curves of the individual isolates, pairwise interaction screens, and metaproteomics of the community. A fast growth rate is identified as one factor that can provide an advantage for maintaining presence in the community. Final community selection can also depend on selective antagonistic relationships and metabolic exchanges. Revealing the mechanisms of interaction among plant-associated microorganisms provides insights into strategies for engineering microbial communities that can potentially increase plant growth and disease resistance. Further, deciphering the membership and metabolic potentials of a bacterial community will enable the design of synthetic communities with desired biological functions. Research Network of Computational and Structural Biotechnology 2021-04-09 /pmc/articles/PMC8079826/ /pubmed/33995895 http://dx.doi.org/10.1016/j.csbj.2021.03.034 Text en © 2021 The Authors. Published by Elsevier B.V. on behalf of Research Network of Computational and Structural Biotechnology. https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Research Article
Wang, Jia
Carper, Dana L.
Burdick, Leah H.
Shrestha, Him K.
Appidi, Manasa R.
Abraham, Paul E.
Timm, Collin M.
Hettich, Robert L.
Pelletier, Dale A.
Doktycz, Mitchel J.
Formation, characterization and modeling of emergent synthetic microbial communities()
title Formation, characterization and modeling of emergent synthetic microbial communities()
title_full Formation, characterization and modeling of emergent synthetic microbial communities()
title_fullStr Formation, characterization and modeling of emergent synthetic microbial communities()
title_full_unstemmed Formation, characterization and modeling of emergent synthetic microbial communities()
title_short Formation, characterization and modeling of emergent synthetic microbial communities()
title_sort formation, characterization and modeling of emergent synthetic microbial communities()
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8079826/
https://www.ncbi.nlm.nih.gov/pubmed/33995895
http://dx.doi.org/10.1016/j.csbj.2021.03.034
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