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Agent Based Models of Polymicrobial Biofilms and the Microbiome—A Review

The human microbiome has been a focus of intense study in recent years. Most of the living organisms comprising the microbiome exist in the form of biofilms on mucosal surfaces lining our digestive, respiratory, and genito-urinary tracts. While health-associated microbiota contribute to digestion, p...

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Autores principales: Koshy-Chenthittayil, Sherli, Archambault, Linda, Senthilkumar, Dhananjai, Laubenbacher, Reinhard, Mendes, Pedro, Dongari-Bagtzoglou, Anna
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7922883/
https://www.ncbi.nlm.nih.gov/pubmed/33671308
http://dx.doi.org/10.3390/microorganisms9020417
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author Koshy-Chenthittayil, Sherli
Archambault, Linda
Senthilkumar, Dhananjai
Laubenbacher, Reinhard
Mendes, Pedro
Dongari-Bagtzoglou, Anna
author_facet Koshy-Chenthittayil, Sherli
Archambault, Linda
Senthilkumar, Dhananjai
Laubenbacher, Reinhard
Mendes, Pedro
Dongari-Bagtzoglou, Anna
author_sort Koshy-Chenthittayil, Sherli
collection PubMed
description The human microbiome has been a focus of intense study in recent years. Most of the living organisms comprising the microbiome exist in the form of biofilms on mucosal surfaces lining our digestive, respiratory, and genito-urinary tracts. While health-associated microbiota contribute to digestion, provide essential nutrients, and protect us from pathogens, disturbances due to illness or medical interventions contribute to infections, some that can be fatal. Myriad biological processes influence the make-up of the microbiota, for example: growth, division, death, and production of extracellular polymers (EPS), and metabolites. Inter-species interactions include competition, inhibition, and symbiosis. Computational models are becoming widely used to better understand these interactions. Agent-based modeling is a particularly useful computational approach to implement the various complex interactions in microbial communities when appropriately combined with an experimental approach. In these models, each cell is represented as an autonomous agent with its own set of rules, with different rules for each species. In this review, we will discuss innovations in agent-based modeling of biofilms and the microbiota in the past five years from the biological and mathematical perspectives and discuss how agent-based models can be further utilized to enhance our comprehension of the complex world of polymicrobial biofilms and the microbiome.
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spelling pubmed-79228832021-03-03 Agent Based Models of Polymicrobial Biofilms and the Microbiome—A Review Koshy-Chenthittayil, Sherli Archambault, Linda Senthilkumar, Dhananjai Laubenbacher, Reinhard Mendes, Pedro Dongari-Bagtzoglou, Anna Microorganisms Review The human microbiome has been a focus of intense study in recent years. Most of the living organisms comprising the microbiome exist in the form of biofilms on mucosal surfaces lining our digestive, respiratory, and genito-urinary tracts. While health-associated microbiota contribute to digestion, provide essential nutrients, and protect us from pathogens, disturbances due to illness or medical interventions contribute to infections, some that can be fatal. Myriad biological processes influence the make-up of the microbiota, for example: growth, division, death, and production of extracellular polymers (EPS), and metabolites. Inter-species interactions include competition, inhibition, and symbiosis. Computational models are becoming widely used to better understand these interactions. Agent-based modeling is a particularly useful computational approach to implement the various complex interactions in microbial communities when appropriately combined with an experimental approach. In these models, each cell is represented as an autonomous agent with its own set of rules, with different rules for each species. In this review, we will discuss innovations in agent-based modeling of biofilms and the microbiota in the past five years from the biological and mathematical perspectives and discuss how agent-based models can be further utilized to enhance our comprehension of the complex world of polymicrobial biofilms and the microbiome. MDPI 2021-02-17 /pmc/articles/PMC7922883/ /pubmed/33671308 http://dx.doi.org/10.3390/microorganisms9020417 Text en © 2021 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 Review
Koshy-Chenthittayil, Sherli
Archambault, Linda
Senthilkumar, Dhananjai
Laubenbacher, Reinhard
Mendes, Pedro
Dongari-Bagtzoglou, Anna
Agent Based Models of Polymicrobial Biofilms and the Microbiome—A Review
title Agent Based Models of Polymicrobial Biofilms and the Microbiome—A Review
title_full Agent Based Models of Polymicrobial Biofilms and the Microbiome—A Review
title_fullStr Agent Based Models of Polymicrobial Biofilms and the Microbiome—A Review
title_full_unstemmed Agent Based Models of Polymicrobial Biofilms and the Microbiome—A Review
title_short Agent Based Models of Polymicrobial Biofilms and the Microbiome—A Review
title_sort agent based models of polymicrobial biofilms and the microbiome—a review
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7922883/
https://www.ncbi.nlm.nih.gov/pubmed/33671308
http://dx.doi.org/10.3390/microorganisms9020417
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