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Review and perspective on mathematical modeling of microbial ecosystems

Understanding microbial ecosystems means unlocking the path toward a deeper knowledge of the fundamental mechanisms of life. Engineered microbial communities are also extremely relevant to tackling some of today's grand societal challenges. Advanced meta-omics experimental techniques provide cr...

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Detalles Bibliográficos
Autores principales: Succurro, Antonella, Ebenhöh, Oliver
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Portland Press Ltd. 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5906705/
https://www.ncbi.nlm.nih.gov/pubmed/29540507
http://dx.doi.org/10.1042/BST20170265
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author Succurro, Antonella
Ebenhöh, Oliver
author_facet Succurro, Antonella
Ebenhöh, Oliver
author_sort Succurro, Antonella
collection PubMed
description Understanding microbial ecosystems means unlocking the path toward a deeper knowledge of the fundamental mechanisms of life. Engineered microbial communities are also extremely relevant to tackling some of today's grand societal challenges. Advanced meta-omics experimental techniques provide crucial insights into microbial communities, but have been so far mostly used for descriptive, exploratory approaches to answer the initial ‘who is there?’ question. An ecosystem is a complex network of dynamic spatio-temporal interactions among organisms as well as between organisms and the environment. Mathematical models with their abstraction capability are essential to capture the underlying phenomena and connect the different scales at which these systems act. Differential equation models and constraint-based stoichiometric models are deterministic approaches that can successfully provide a macroscopic description of the outcome from microscopic behaviors. In this mini-review, we present classical and recent applications of these modeling methods and illustrate the potential of their integration. Indeed, approaches that can capture multiple scales are needed in order to understand emergent patterns in ecosystems and their dynamics regulated by different spatio-temporal phenomena. We finally discuss promising examples of methods proposing the integration of differential equations with constraint-based stoichiometric models and argue that more work is needed in this direction.
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spelling pubmed-59067052018-05-01 Review and perspective on mathematical modeling of microbial ecosystems Succurro, Antonella Ebenhöh, Oliver Biochem Soc Trans Review Articles Understanding microbial ecosystems means unlocking the path toward a deeper knowledge of the fundamental mechanisms of life. Engineered microbial communities are also extremely relevant to tackling some of today's grand societal challenges. Advanced meta-omics experimental techniques provide crucial insights into microbial communities, but have been so far mostly used for descriptive, exploratory approaches to answer the initial ‘who is there?’ question. An ecosystem is a complex network of dynamic spatio-temporal interactions among organisms as well as between organisms and the environment. Mathematical models with their abstraction capability are essential to capture the underlying phenomena and connect the different scales at which these systems act. Differential equation models and constraint-based stoichiometric models are deterministic approaches that can successfully provide a macroscopic description of the outcome from microscopic behaviors. In this mini-review, we present classical and recent applications of these modeling methods and illustrate the potential of their integration. Indeed, approaches that can capture multiple scales are needed in order to understand emergent patterns in ecosystems and their dynamics regulated by different spatio-temporal phenomena. We finally discuss promising examples of methods proposing the integration of differential equations with constraint-based stoichiometric models and argue that more work is needed in this direction. Portland Press Ltd. 2018-04-17 2018-03-14 /pmc/articles/PMC5906705/ /pubmed/29540507 http://dx.doi.org/10.1042/BST20170265 Text en © 2018 The Author(s) https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article published by Portland Press Limited on behalf of the Biochemical Society and distributed under the Creative Commons Attribution License 4.0 (CC BY-NC-ND) (https://creativecommons.org/licenses/by-nc-nd/4.0/) .
spellingShingle Review Articles
Succurro, Antonella
Ebenhöh, Oliver
Review and perspective on mathematical modeling of microbial ecosystems
title Review and perspective on mathematical modeling of microbial ecosystems
title_full Review and perspective on mathematical modeling of microbial ecosystems
title_fullStr Review and perspective on mathematical modeling of microbial ecosystems
title_full_unstemmed Review and perspective on mathematical modeling of microbial ecosystems
title_short Review and perspective on mathematical modeling of microbial ecosystems
title_sort review and perspective on mathematical modeling of microbial ecosystems
topic Review Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5906705/
https://www.ncbi.nlm.nih.gov/pubmed/29540507
http://dx.doi.org/10.1042/BST20170265
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