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Spatio-temporal modeling of the crowding conditions and metabolic variability in microbial communities
The metabolic capabilities of the species and the local environment shape the microbial interactions in a community either through the exchange of metabolic products or the competition for the resources. Cells are often arranged in close proximity to each other, creating a crowded environment that u...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8297787/ https://www.ncbi.nlm.nih.gov/pubmed/34292935 http://dx.doi.org/10.1371/journal.pcbi.1009140 |
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author | Angeles-Martinez, Liliana Hatzimanikatis, Vassily |
author_facet | Angeles-Martinez, Liliana Hatzimanikatis, Vassily |
author_sort | Angeles-Martinez, Liliana |
collection | PubMed |
description | The metabolic capabilities of the species and the local environment shape the microbial interactions in a community either through the exchange of metabolic products or the competition for the resources. Cells are often arranged in close proximity to each other, creating a crowded environment that unevenly reduce the diffusion of nutrients. Herein, we investigated how the crowding conditions and metabolic variability among cells shape the dynamics of microbial communities. For this, we developed CROMICS, a spatio-temporal framework that combines techniques such as individual-based modeling, scaled particle theory, and thermodynamic flux analysis to explicitly incorporate the cell metabolism and the impact of the presence of macromolecular components on the nutrients diffusion. This framework was used to study two archetypical microbial communities (i) Escherichia coli and Salmonella enterica that cooperate with each other by exchanging metabolites, and (ii) two E. coli with different production level of extracellular polymeric substances (EPS) that compete for the same nutrients. In the mutualistic community, our results demonstrate that crowding enhanced the fitness of cooperative mutants by reducing the leakage of metabolites from the region where they are produced, avoiding the resource competition with non-cooperative cells. Moreover, we also show that E. coli EPS-secreting mutants won the competition against the non-secreting cells by creating less dense structures (i.e. increasing the spacing among the cells) that allow mutants to expand and reach regions closer to the nutrient supply point. A modest enhancement of the relative fitness of EPS-secreting cells over the non-secreting ones were found when the crowding effect was taken into account in the simulations. The emergence of cell-cell interactions and the intracellular conflicts arising from the trade-off between growth and the secretion of metabolites or EPS could provide a local competitive advantage to one species, either by supplying more cross-feeding metabolites or by creating a less dense neighborhood. |
format | Online Article Text |
id | pubmed-8297787 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-82977872021-07-31 Spatio-temporal modeling of the crowding conditions and metabolic variability in microbial communities Angeles-Martinez, Liliana Hatzimanikatis, Vassily PLoS Comput Biol Research Article The metabolic capabilities of the species and the local environment shape the microbial interactions in a community either through the exchange of metabolic products or the competition for the resources. Cells are often arranged in close proximity to each other, creating a crowded environment that unevenly reduce the diffusion of nutrients. Herein, we investigated how the crowding conditions and metabolic variability among cells shape the dynamics of microbial communities. For this, we developed CROMICS, a spatio-temporal framework that combines techniques such as individual-based modeling, scaled particle theory, and thermodynamic flux analysis to explicitly incorporate the cell metabolism and the impact of the presence of macromolecular components on the nutrients diffusion. This framework was used to study two archetypical microbial communities (i) Escherichia coli and Salmonella enterica that cooperate with each other by exchanging metabolites, and (ii) two E. coli with different production level of extracellular polymeric substances (EPS) that compete for the same nutrients. In the mutualistic community, our results demonstrate that crowding enhanced the fitness of cooperative mutants by reducing the leakage of metabolites from the region where they are produced, avoiding the resource competition with non-cooperative cells. Moreover, we also show that E. coli EPS-secreting mutants won the competition against the non-secreting cells by creating less dense structures (i.e. increasing the spacing among the cells) that allow mutants to expand and reach regions closer to the nutrient supply point. A modest enhancement of the relative fitness of EPS-secreting cells over the non-secreting ones were found when the crowding effect was taken into account in the simulations. The emergence of cell-cell interactions and the intracellular conflicts arising from the trade-off between growth and the secretion of metabolites or EPS could provide a local competitive advantage to one species, either by supplying more cross-feeding metabolites or by creating a less dense neighborhood. Public Library of Science 2021-07-22 /pmc/articles/PMC8297787/ /pubmed/34292935 http://dx.doi.org/10.1371/journal.pcbi.1009140 Text en © 2021 Angeles-Martinez, Hatzimanikatis https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Angeles-Martinez, Liliana Hatzimanikatis, Vassily Spatio-temporal modeling of the crowding conditions and metabolic variability in microbial communities |
title | Spatio-temporal modeling of the crowding conditions and metabolic variability in microbial communities |
title_full | Spatio-temporal modeling of the crowding conditions and metabolic variability in microbial communities |
title_fullStr | Spatio-temporal modeling of the crowding conditions and metabolic variability in microbial communities |
title_full_unstemmed | Spatio-temporal modeling of the crowding conditions and metabolic variability in microbial communities |
title_short | Spatio-temporal modeling of the crowding conditions and metabolic variability in microbial communities |
title_sort | spatio-temporal modeling of the crowding conditions and metabolic variability in microbial communities |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8297787/ https://www.ncbi.nlm.nih.gov/pubmed/34292935 http://dx.doi.org/10.1371/journal.pcbi.1009140 |
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