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In Search of Model Ecological Systems for Understanding Specialized Metabolism

Microbes occupy diverse habitats, forming interconnected, dynamic communities. Elucidating the principles of microbial community function is a grand challenge for microbiology, and it will entail experiments that engage microbiomes across multiple levels of complexity. For example, community-level h...

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Detalles Bibliográficos
Autores principales: Pessotti, Rita C., Hansen, Bridget L., Traxler, Matthew F.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Society for Microbiology 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5881028/
https://www.ncbi.nlm.nih.gov/pubmed/29629421
http://dx.doi.org/10.1128/mSystems.00175-17
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author Pessotti, Rita C.
Hansen, Bridget L.
Traxler, Matthew F.
author_facet Pessotti, Rita C.
Hansen, Bridget L.
Traxler, Matthew F.
author_sort Pessotti, Rita C.
collection PubMed
description Microbes occupy diverse habitats, forming interconnected, dynamic communities. Elucidating the principles of microbial community function is a grand challenge for microbiology, and it will entail experiments that engage microbiomes across multiple levels of complexity. For example, community-level hypotheses often require testing at the mechanistic and/or genetic levels, while mechanistic relationships require community-level evaluation to understand their importance in context. In this Perspective, we articulate the need for model microbiome systems that enable experimentation in both community and reductionist frameworks, with an emphasis on understanding the role of specialized metabolites in microbial communities. We consider essential criteria for developing such model microbiome systems and discuss potential future models that address the ecology of specialized metabolism.
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spelling pubmed-58810282018-04-06 In Search of Model Ecological Systems for Understanding Specialized Metabolism Pessotti, Rita C. Hansen, Bridget L. Traxler, Matthew F. mSystems Perspective Microbes occupy diverse habitats, forming interconnected, dynamic communities. Elucidating the principles of microbial community function is a grand challenge for microbiology, and it will entail experiments that engage microbiomes across multiple levels of complexity. For example, community-level hypotheses often require testing at the mechanistic and/or genetic levels, while mechanistic relationships require community-level evaluation to understand their importance in context. In this Perspective, we articulate the need for model microbiome systems that enable experimentation in both community and reductionist frameworks, with an emphasis on understanding the role of specialized metabolites in microbial communities. We consider essential criteria for developing such model microbiome systems and discuss potential future models that address the ecology of specialized metabolism. American Society for Microbiology 2018-03-27 /pmc/articles/PMC5881028/ /pubmed/29629421 http://dx.doi.org/10.1128/mSystems.00175-17 Text en Copyright © 2018 Pessotti 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 Perspective
Pessotti, Rita C.
Hansen, Bridget L.
Traxler, Matthew F.
In Search of Model Ecological Systems for Understanding Specialized Metabolism
title In Search of Model Ecological Systems for Understanding Specialized Metabolism
title_full In Search of Model Ecological Systems for Understanding Specialized Metabolism
title_fullStr In Search of Model Ecological Systems for Understanding Specialized Metabolism
title_full_unstemmed In Search of Model Ecological Systems for Understanding Specialized Metabolism
title_short In Search of Model Ecological Systems for Understanding Specialized Metabolism
title_sort in search of model ecological systems for understanding specialized metabolism
topic Perspective
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5881028/
https://www.ncbi.nlm.nih.gov/pubmed/29629421
http://dx.doi.org/10.1128/mSystems.00175-17
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