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GutLogo: Agent-based modeling framework to investigate spatial and temporal dynamics in the gut microbiome
Knowledge of the spatial and temporal dynamics of the gut microbiome is essential to understanding the state of human health, as over a hundred diseases have been correlated with changes in microbial populations. Unfortunately, due to the complexity of the microbiome and the limitations of in vivo a...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6226173/ https://www.ncbi.nlm.nih.gov/pubmed/30412640 http://dx.doi.org/10.1371/journal.pone.0207072 |
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author | Lin, Charlie Culver, Joshua Weston, Bronson Underhill, Evan Gorky, Jonathan Dhurjati, Prasad |
author_facet | Lin, Charlie Culver, Joshua Weston, Bronson Underhill, Evan Gorky, Jonathan Dhurjati, Prasad |
author_sort | Lin, Charlie |
collection | PubMed |
description | Knowledge of the spatial and temporal dynamics of the gut microbiome is essential to understanding the state of human health, as over a hundred diseases have been correlated with changes in microbial populations. Unfortunately, due to the complexity of the microbiome and the limitations of in vivo and in vitro experiments, studying spatial and temporal dynamics of gut bacteria in a biological setting is extremely challenging. Thus, in silico experiments present an excellent alternative for studying such systems. In consideration of these issues, we have developed a user-friendly agent-based model, GutLogo, that captures the spatial and temporal development of four representative bacterial genera populations in the ileum. We demonstrate the utility of this model by simulating population responses to perturbations in flow rate, nutrition, and probiotics. While our model predicts distinct changes in population levels due to these perturbations, most of the simulations suggest that the gut populations will return to their original steady states once the disturbance is removed. We hope that, in the future, the GutLogo model is utilized and customized by interested parties, as GutLogo can serve as a basic modeling framework for simulating a variety of physiological scenarios and can be extended to capture additional complexities of interest. |
format | Online Article Text |
id | pubmed-6226173 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-62261732018-11-19 GutLogo: Agent-based modeling framework to investigate spatial and temporal dynamics in the gut microbiome Lin, Charlie Culver, Joshua Weston, Bronson Underhill, Evan Gorky, Jonathan Dhurjati, Prasad PLoS One Research Article Knowledge of the spatial and temporal dynamics of the gut microbiome is essential to understanding the state of human health, as over a hundred diseases have been correlated with changes in microbial populations. Unfortunately, due to the complexity of the microbiome and the limitations of in vivo and in vitro experiments, studying spatial and temporal dynamics of gut bacteria in a biological setting is extremely challenging. Thus, in silico experiments present an excellent alternative for studying such systems. In consideration of these issues, we have developed a user-friendly agent-based model, GutLogo, that captures the spatial and temporal development of four representative bacterial genera populations in the ileum. We demonstrate the utility of this model by simulating population responses to perturbations in flow rate, nutrition, and probiotics. While our model predicts distinct changes in population levels due to these perturbations, most of the simulations suggest that the gut populations will return to their original steady states once the disturbance is removed. We hope that, in the future, the GutLogo model is utilized and customized by interested parties, as GutLogo can serve as a basic modeling framework for simulating a variety of physiological scenarios and can be extended to capture additional complexities of interest. Public Library of Science 2018-11-09 /pmc/articles/PMC6226173/ /pubmed/30412640 http://dx.doi.org/10.1371/journal.pone.0207072 Text en © 2018 Lin 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 Lin, Charlie Culver, Joshua Weston, Bronson Underhill, Evan Gorky, Jonathan Dhurjati, Prasad GutLogo: Agent-based modeling framework to investigate spatial and temporal dynamics in the gut microbiome |
title | GutLogo: Agent-based modeling framework to investigate spatial and temporal dynamics in the gut microbiome |
title_full | GutLogo: Agent-based modeling framework to investigate spatial and temporal dynamics in the gut microbiome |
title_fullStr | GutLogo: Agent-based modeling framework to investigate spatial and temporal dynamics in the gut microbiome |
title_full_unstemmed | GutLogo: Agent-based modeling framework to investigate spatial and temporal dynamics in the gut microbiome |
title_short | GutLogo: Agent-based modeling framework to investigate spatial and temporal dynamics in the gut microbiome |
title_sort | gutlogo: agent-based modeling framework to investigate spatial and temporal dynamics in the gut microbiome |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6226173/ https://www.ncbi.nlm.nih.gov/pubmed/30412640 http://dx.doi.org/10.1371/journal.pone.0207072 |
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