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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...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Portland Press Ltd.
2018
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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. |
format | Online Article Text |
id | pubmed-5906705 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Portland Press Ltd. |
record_format | MEDLINE/PubMed |
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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