The Power of Metabolism for Predicting Microbial Community Dynamics

ABSTRACT Quantitative understanding and prediction of microbial community dynamics are an outstanding challenge. We test the hypothesis that metabolic mechanisms provide a foundation for accurate prediction of dynamics in microbial systems. In our research, metabolic models have been able to accurat...

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Autores principales:	Jeremy M. Chacón, William R. Harcombe
Formato:	article
Lenguaje:	EN
Publicado:	American Society for Microbiology 2019
Materias:	metabolism antibiotics bacteriophage ecology evolution genome-scale modeling Microbiology QR1-502
Acceso en línea:	https://doaj.org/article/9abd17139dd247dca0b7e624057123ac
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spelling	oai:doaj.org-article:9abd17139dd247dca0b7e624057123ac2021-12-02T18:44:39ZThe Power of Metabolism for Predicting Microbial Community Dynamics10.1128/mSystems.00146-192379-5077https://doaj.org/article/9abd17139dd247dca0b7e624057123ac2019-06-01T00:00:00Zhttps://journals.asm.org/doi/10.1128/mSystems.00146-19https://doaj.org/toc/2379-5077ABSTRACT Quantitative understanding and prediction of microbial community dynamics are an outstanding challenge. We test the hypothesis that metabolic mechanisms provide a foundation for accurate prediction of dynamics in microbial systems. In our research, metabolic models have been able to accurately predict species interactions, evolutionary trajectories, and response to perturbation in simple synthetic consortia. However, metabolic models have many constraints and often serve best as null models to identify additional processes at play. We anticipate that major advances in metabolic systems biology will involve scaling bottom-up approaches to complex communities and expanding the processes that are incorporated in a metabolic perspective. Ultimately, cellular metabolism will inform predictive ecology that enables precision management of microbial systems.Jeremy M. ChacónWilliam R. HarcombeAmerican Society for Microbiologyarticlemetabolismantibioticsbacteriophageecologyevolutiongenome-scale modelingMicrobiologyQR1-502ENmSystems, Vol 4, Iss 3 (2019)
institution	DOAJ
collection	DOAJ
language	EN
topic	metabolism antibiotics bacteriophage ecology evolution genome-scale modeling Microbiology QR1-502
spellingShingle	metabolism antibiotics bacteriophage ecology evolution genome-scale modeling Microbiology QR1-502 Jeremy M. Chacón William R. Harcombe The Power of Metabolism for Predicting Microbial Community Dynamics
description	ABSTRACT Quantitative understanding and prediction of microbial community dynamics are an outstanding challenge. We test the hypothesis that metabolic mechanisms provide a foundation for accurate prediction of dynamics in microbial systems. In our research, metabolic models have been able to accurately predict species interactions, evolutionary trajectories, and response to perturbation in simple synthetic consortia. However, metabolic models have many constraints and often serve best as null models to identify additional processes at play. We anticipate that major advances in metabolic systems biology will involve scaling bottom-up approaches to complex communities and expanding the processes that are incorporated in a metabolic perspective. Ultimately, cellular metabolism will inform predictive ecology that enables precision management of microbial systems.
format	article
author	Jeremy M. Chacón William R. Harcombe
author_facet	Jeremy M. Chacón William R. Harcombe
author_sort	Jeremy M. Chacón
title	The Power of Metabolism for Predicting Microbial Community Dynamics
title_short	The Power of Metabolism for Predicting Microbial Community Dynamics
title_full	The Power of Metabolism for Predicting Microbial Community Dynamics
title_fullStr	The Power of Metabolism for Predicting Microbial Community Dynamics
title_full_unstemmed	The Power of Metabolism for Predicting Microbial Community Dynamics
title_sort	power of metabolism for predicting microbial community dynamics
publisher	American Society for Microbiology
publishDate	2019
url	https://doaj.org/article/9abd17139dd247dca0b7e624057123ac
work_keys_str_mv	AT jeremymchacon thepowerofmetabolismforpredictingmicrobialcommunitydynamics AT williamrharcombe thepowerofmetabolismforpredictingmicrobialcommunitydynamics AT jeremymchacon powerofmetabolismforpredictingmicrobialcommunitydynamics AT williamrharcombe powerofmetabolismforpredictingmicrobialcommunitydynamics
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The Power of Metabolism for Predicting Microbial Community Dynamics

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