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Incorporating Cellular Stochasticity in Solid–Fluid Mixture Biofilm Models

The dynamics of cellular aggregates is driven by the interplay of mechanochemical processes and cellular activity. Although deterministic models may capture mechanical features, local chemical fluctuations trigger random cell responses, which determine the overall evolution. Incorporating stochastic...

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Detalles Bibliográficos
Autores principales: Carpio, Ana, Cebrián, Elena
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7516608/
https://www.ncbi.nlm.nih.gov/pubmed/33285963
http://dx.doi.org/10.3390/e22020188
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author Carpio, Ana
Cebrián, Elena
author_facet Carpio, Ana
Cebrián, Elena
author_sort Carpio, Ana
collection PubMed
description The dynamics of cellular aggregates is driven by the interplay of mechanochemical processes and cellular activity. Although deterministic models may capture mechanical features, local chemical fluctuations trigger random cell responses, which determine the overall evolution. Incorporating stochastic cellular behavior in macroscopic models of biological media is a challenging task. Herein, we propose hybrid models for bacterial biofilm growth, which couple a two phase solid/fluid mixture description of mechanical and chemical fields with a dynamic energy budget-based cellular automata treatment of bacterial activity. Thin film and plate approximations for the relevant interfaces allow us to obtain numerical solutions exhibiting behaviors observed in experiments, such as accelerated spread due to water intake from the environment, wrinkle formation, undulated contour development, and the appearance of inhomogeneous distributions of differentiated bacteria performing varied tasks.
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spelling pubmed-75166082020-11-09 Incorporating Cellular Stochasticity in Solid–Fluid Mixture Biofilm Models Carpio, Ana Cebrián, Elena Entropy (Basel) Article The dynamics of cellular aggregates is driven by the interplay of mechanochemical processes and cellular activity. Although deterministic models may capture mechanical features, local chemical fluctuations trigger random cell responses, which determine the overall evolution. Incorporating stochastic cellular behavior in macroscopic models of biological media is a challenging task. Herein, we propose hybrid models for bacterial biofilm growth, which couple a two phase solid/fluid mixture description of mechanical and chemical fields with a dynamic energy budget-based cellular automata treatment of bacterial activity. Thin film and plate approximations for the relevant interfaces allow us to obtain numerical solutions exhibiting behaviors observed in experiments, such as accelerated spread due to water intake from the environment, wrinkle formation, undulated contour development, and the appearance of inhomogeneous distributions of differentiated bacteria performing varied tasks. MDPI 2020-02-06 /pmc/articles/PMC7516608/ /pubmed/33285963 http://dx.doi.org/10.3390/e22020188 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Carpio, Ana
Cebrián, Elena
Incorporating Cellular Stochasticity in Solid–Fluid Mixture Biofilm Models
title Incorporating Cellular Stochasticity in Solid–Fluid Mixture Biofilm Models
title_full Incorporating Cellular Stochasticity in Solid–Fluid Mixture Biofilm Models
title_fullStr Incorporating Cellular Stochasticity in Solid–Fluid Mixture Biofilm Models
title_full_unstemmed Incorporating Cellular Stochasticity in Solid–Fluid Mixture Biofilm Models
title_short Incorporating Cellular Stochasticity in Solid–Fluid Mixture Biofilm Models
title_sort incorporating cellular stochasticity in solid–fluid mixture biofilm models
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7516608/
https://www.ncbi.nlm.nih.gov/pubmed/33285963
http://dx.doi.org/10.3390/e22020188
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