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A Reproducible and Tunable Synthetic Soil Microbial Community Provides New Insights into Microbial Ecology

Microbial soil communities form commensal relationships with plants to promote the growth of both parties. The optimization of plant-microbe interactions to advance sustainable agriculture is an important field in agricultural research. However, investigation in this field is hindered by a lack of m...

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Autores principales: Coker, Joanna, Zhalnina, Kateryna, Marotz, Clarisse, Thiruppathy, Deepan, Tjuanta, Megan, D’Elia, Gavin, Hailu, Rodas, Mahosky, Talon, Rowan, Meagan, Northen, Trent R., Zengler, Karsten
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Society for Microbiology 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9765266/
https://www.ncbi.nlm.nih.gov/pubmed/36472419
http://dx.doi.org/10.1128/msystems.00951-22
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author Coker, Joanna
Zhalnina, Kateryna
Marotz, Clarisse
Thiruppathy, Deepan
Tjuanta, Megan
D’Elia, Gavin
Hailu, Rodas
Mahosky, Talon
Rowan, Meagan
Northen, Trent R.
Zengler, Karsten
author_facet Coker, Joanna
Zhalnina, Kateryna
Marotz, Clarisse
Thiruppathy, Deepan
Tjuanta, Megan
D’Elia, Gavin
Hailu, Rodas
Mahosky, Talon
Rowan, Meagan
Northen, Trent R.
Zengler, Karsten
author_sort Coker, Joanna
collection PubMed
description Microbial soil communities form commensal relationships with plants to promote the growth of both parties. The optimization of plant-microbe interactions to advance sustainable agriculture is an important field in agricultural research. However, investigation in this field is hindered by a lack of model microbial community systems and efficient approaches for building these communities. Two key challenges in developing standardized model communities are maintaining community diversity over time and storing/resuscitating these communities after cryopreservation, especially considering the different growth rates of organisms. Here, a model synthetic community (SynCom) of 16 soil microorganisms commonly found in the rhizosphere of diverse plant species, isolated from soil surrounding a single switchgrass plant, has been developed and optimized for in vitro experiments. The model soil community grows reproducibly between replicates and experiments, with a high community α-diversity being achieved through growth in low-nutrient media and through the adjustment of the starting composition ratios for the growth of individual organisms. The community can additionally be cryopreserved with glycerol, allowing for easy replication and dissemination of this in vitro system. Furthermore, the SynCom also grows reproducibly in fabricated ecosystem devices (EcoFABs), demonstrating the application of this community to an existing in vitro plant-microbe system. EcoFABs allow reproducible research in model plant systems, offering the precise control of environmental conditions and the easy measurement of plant microbe metrics. Our results demonstrate the generation of a stable and diverse microbial SynCom for the rhizosphere that can be used with EcoFAB devices and can be shared between research groups for maximum reproducibility. IMPORTANCE Microbes associate with plants in distinct soil communities to the benefit of both the soil microbes and the plants. Interactions between plants and these microbes can improve plant growth and health and are therefore a field of study in sustainable agricultural research. In this study, a model community of 16 soil bacteria has been developed to further the reproducible study of plant-soil microbe interactions. The preservation of the microbial community has been optimized for dissemination to other research settings. Overall, this work will advance soil microbe research through the optimization of a robust, reproducible model community.
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spelling pubmed-97652662022-12-21 A Reproducible and Tunable Synthetic Soil Microbial Community Provides New Insights into Microbial Ecology Coker, Joanna Zhalnina, Kateryna Marotz, Clarisse Thiruppathy, Deepan Tjuanta, Megan D’Elia, Gavin Hailu, Rodas Mahosky, Talon Rowan, Meagan Northen, Trent R. Zengler, Karsten mSystems Research Article Microbial soil communities form commensal relationships with plants to promote the growth of both parties. The optimization of plant-microbe interactions to advance sustainable agriculture is an important field in agricultural research. However, investigation in this field is hindered by a lack of model microbial community systems and efficient approaches for building these communities. Two key challenges in developing standardized model communities are maintaining community diversity over time and storing/resuscitating these communities after cryopreservation, especially considering the different growth rates of organisms. Here, a model synthetic community (SynCom) of 16 soil microorganisms commonly found in the rhizosphere of diverse plant species, isolated from soil surrounding a single switchgrass plant, has been developed and optimized for in vitro experiments. The model soil community grows reproducibly between replicates and experiments, with a high community α-diversity being achieved through growth in low-nutrient media and through the adjustment of the starting composition ratios for the growth of individual organisms. The community can additionally be cryopreserved with glycerol, allowing for easy replication and dissemination of this in vitro system. Furthermore, the SynCom also grows reproducibly in fabricated ecosystem devices (EcoFABs), demonstrating the application of this community to an existing in vitro plant-microbe system. EcoFABs allow reproducible research in model plant systems, offering the precise control of environmental conditions and the easy measurement of plant microbe metrics. Our results demonstrate the generation of a stable and diverse microbial SynCom for the rhizosphere that can be used with EcoFAB devices and can be shared between research groups for maximum reproducibility. IMPORTANCE Microbes associate with plants in distinct soil communities to the benefit of both the soil microbes and the plants. Interactions between plants and these microbes can improve plant growth and health and are therefore a field of study in sustainable agricultural research. In this study, a model community of 16 soil bacteria has been developed to further the reproducible study of plant-soil microbe interactions. The preservation of the microbial community has been optimized for dissemination to other research settings. Overall, this work will advance soil microbe research through the optimization of a robust, reproducible model community. American Society for Microbiology 2022-12-06 /pmc/articles/PMC9765266/ /pubmed/36472419 http://dx.doi.org/10.1128/msystems.00951-22 Text en Copyright © 2022 Coker et al. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International license (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Research Article
Coker, Joanna
Zhalnina, Kateryna
Marotz, Clarisse
Thiruppathy, Deepan
Tjuanta, Megan
D’Elia, Gavin
Hailu, Rodas
Mahosky, Talon
Rowan, Meagan
Northen, Trent R.
Zengler, Karsten
A Reproducible and Tunable Synthetic Soil Microbial Community Provides New Insights into Microbial Ecology
title A Reproducible and Tunable Synthetic Soil Microbial Community Provides New Insights into Microbial Ecology
title_full A Reproducible and Tunable Synthetic Soil Microbial Community Provides New Insights into Microbial Ecology
title_fullStr A Reproducible and Tunable Synthetic Soil Microbial Community Provides New Insights into Microbial Ecology
title_full_unstemmed A Reproducible and Tunable Synthetic Soil Microbial Community Provides New Insights into Microbial Ecology
title_short A Reproducible and Tunable Synthetic Soil Microbial Community Provides New Insights into Microbial Ecology
title_sort reproducible and tunable synthetic soil microbial community provides new insights into microbial ecology
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9765266/
https://www.ncbi.nlm.nih.gov/pubmed/36472419
http://dx.doi.org/10.1128/msystems.00951-22
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