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A mechanistic Individual-based Model of microbial communities

Accurate predictive modelling of the growth of microbial communities requires the credible representation of the interactions of biological, chemical and mechanical processes. However, although biological and chemical processes are represented in a number of Individual-based Models (IbMs) the intera...

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Autores principales: Jayathilake, Pahala Gedara, Gupta, Prashant, Li, Bowen, Madsen, Curtis, Oyebamiji, Oluwole, González-Cabaleiro, Rebeca, Rushton, Steve, Bridgens, Ben, Swailes, David, Allen, Ben, McGough, A. Stephen, Zuliani, Paolo, Ofiteru, Irina Dana, Wilkinson, Darren, Chen, Jinju, Curtis, Tom
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5542553/
https://www.ncbi.nlm.nih.gov/pubmed/28771505
http://dx.doi.org/10.1371/journal.pone.0181965
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author Jayathilake, Pahala Gedara
Gupta, Prashant
Li, Bowen
Madsen, Curtis
Oyebamiji, Oluwole
González-Cabaleiro, Rebeca
Rushton, Steve
Bridgens, Ben
Swailes, David
Allen, Ben
McGough, A. Stephen
Zuliani, Paolo
Ofiteru, Irina Dana
Wilkinson, Darren
Chen, Jinju
Curtis, Tom
author_facet Jayathilake, Pahala Gedara
Gupta, Prashant
Li, Bowen
Madsen, Curtis
Oyebamiji, Oluwole
González-Cabaleiro, Rebeca
Rushton, Steve
Bridgens, Ben
Swailes, David
Allen, Ben
McGough, A. Stephen
Zuliani, Paolo
Ofiteru, Irina Dana
Wilkinson, Darren
Chen, Jinju
Curtis, Tom
author_sort Jayathilake, Pahala Gedara
collection PubMed
description Accurate predictive modelling of the growth of microbial communities requires the credible representation of the interactions of biological, chemical and mechanical processes. However, although biological and chemical processes are represented in a number of Individual-based Models (IbMs) the interaction of growth and mechanics is limited. Conversely, there are mechanically sophisticated IbMs with only elementary biology and chemistry. This study focuses on addressing these limitations by developing a flexible IbM that can robustly combine the biological, chemical and physical processes that dictate the emergent properties of a wide range of bacterial communities. This IbM is developed by creating a microbiological adaptation of the open source Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS). This innovation should provide the basis for “bottom up” prediction of the emergent behaviour of entire microbial systems. In the model presented here, bacterial growth, division, decay, mechanical contact among bacterial cells, and adhesion between the bacteria and extracellular polymeric substances are incorporated. In addition, fluid-bacteria interaction is implemented to simulate biofilm deformation and erosion. The model predicts that the surface morphology of biofilms becomes smoother with increased nutrient concentration, which agrees well with previous literature. In addition, the results show that increased shear rate results in smoother and more compact biofilms. The model can also predict shear rate dependent biofilm deformation, erosion, streamer formation and breakup.
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spelling pubmed-55425532017-08-12 A mechanistic Individual-based Model of microbial communities Jayathilake, Pahala Gedara Gupta, Prashant Li, Bowen Madsen, Curtis Oyebamiji, Oluwole González-Cabaleiro, Rebeca Rushton, Steve Bridgens, Ben Swailes, David Allen, Ben McGough, A. Stephen Zuliani, Paolo Ofiteru, Irina Dana Wilkinson, Darren Chen, Jinju Curtis, Tom PLoS One Research Article Accurate predictive modelling of the growth of microbial communities requires the credible representation of the interactions of biological, chemical and mechanical processes. However, although biological and chemical processes are represented in a number of Individual-based Models (IbMs) the interaction of growth and mechanics is limited. Conversely, there are mechanically sophisticated IbMs with only elementary biology and chemistry. This study focuses on addressing these limitations by developing a flexible IbM that can robustly combine the biological, chemical and physical processes that dictate the emergent properties of a wide range of bacterial communities. This IbM is developed by creating a microbiological adaptation of the open source Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS). This innovation should provide the basis for “bottom up” prediction of the emergent behaviour of entire microbial systems. In the model presented here, bacterial growth, division, decay, mechanical contact among bacterial cells, and adhesion between the bacteria and extracellular polymeric substances are incorporated. In addition, fluid-bacteria interaction is implemented to simulate biofilm deformation and erosion. The model predicts that the surface morphology of biofilms becomes smoother with increased nutrient concentration, which agrees well with previous literature. In addition, the results show that increased shear rate results in smoother and more compact biofilms. The model can also predict shear rate dependent biofilm deformation, erosion, streamer formation and breakup. Public Library of Science 2017-08-03 /pmc/articles/PMC5542553/ /pubmed/28771505 http://dx.doi.org/10.1371/journal.pone.0181965 Text en © 2017 Jayathilake et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://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
Jayathilake, Pahala Gedara
Gupta, Prashant
Li, Bowen
Madsen, Curtis
Oyebamiji, Oluwole
González-Cabaleiro, Rebeca
Rushton, Steve
Bridgens, Ben
Swailes, David
Allen, Ben
McGough, A. Stephen
Zuliani, Paolo
Ofiteru, Irina Dana
Wilkinson, Darren
Chen, Jinju
Curtis, Tom
A mechanistic Individual-based Model of microbial communities
title A mechanistic Individual-based Model of microbial communities
title_full A mechanistic Individual-based Model of microbial communities
title_fullStr A mechanistic Individual-based Model of microbial communities
title_full_unstemmed A mechanistic Individual-based Model of microbial communities
title_short A mechanistic Individual-based Model of microbial communities
title_sort mechanistic individual-based model of microbial communities
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5542553/
https://www.ncbi.nlm.nih.gov/pubmed/28771505
http://dx.doi.org/10.1371/journal.pone.0181965
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