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Stochastic dynamics of Francisella tularensis infection and replication

We study the pathogenesis of Francisella tularensis infection with an experimental mouse model, agent-based computation and mathematical analysis. Following inhalational exposure to Francisella tularensis SCHU S4, a small initial number of bacteria enter lung host cells and proliferate inside them,...

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Autores principales: Carruthers, Jonathan, Lythe, Grant, López-García, Martín, Gillard, Joseph, Laws, Thomas R., Lukaszewski, Roman, Molina-París, Carmen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7304631/
https://www.ncbi.nlm.nih.gov/pubmed/32479491
http://dx.doi.org/10.1371/journal.pcbi.1007752
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author Carruthers, Jonathan
Lythe, Grant
López-García, Martín
Gillard, Joseph
Laws, Thomas R.
Lukaszewski, Roman
Molina-París, Carmen
author_facet Carruthers, Jonathan
Lythe, Grant
López-García, Martín
Gillard, Joseph
Laws, Thomas R.
Lukaszewski, Roman
Molina-París, Carmen
author_sort Carruthers, Jonathan
collection PubMed
description We study the pathogenesis of Francisella tularensis infection with an experimental mouse model, agent-based computation and mathematical analysis. Following inhalational exposure to Francisella tularensis SCHU S4, a small initial number of bacteria enter lung host cells and proliferate inside them, eventually destroying the host cell and releasing numerous copies that infect other cells. Our analysis of disease progression is based on a stochastic model of a population of infectious agents inside one host cell, extending the birth-and-death process by the occurrence of catastrophes: cell rupture events that affect all bacteria in a cell simultaneously. Closed expressions are obtained for the survival function of an infected cell, the number of bacteria released as a function of time after infection, and the total bacterial load. We compare our mathematical analysis with the results of agent-based computation and, making use of approximate Bayesian statistical inference, with experimental measurements carried out after murine aerosol infection with the virulent SCHU S4 strain of the bacterium Francisella tularensis, that infects alveolar macrophages. The posterior distribution of the rate of replication of intracellular bacteria is consistent with the estimate that the time between rounds of bacterial division is less than 6 hours in vivo.
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spelling pubmed-73046312020-06-22 Stochastic dynamics of Francisella tularensis infection and replication Carruthers, Jonathan Lythe, Grant López-García, Martín Gillard, Joseph Laws, Thomas R. Lukaszewski, Roman Molina-París, Carmen PLoS Comput Biol Research Article We study the pathogenesis of Francisella tularensis infection with an experimental mouse model, agent-based computation and mathematical analysis. Following inhalational exposure to Francisella tularensis SCHU S4, a small initial number of bacteria enter lung host cells and proliferate inside them, eventually destroying the host cell and releasing numerous copies that infect other cells. Our analysis of disease progression is based on a stochastic model of a population of infectious agents inside one host cell, extending the birth-and-death process by the occurrence of catastrophes: cell rupture events that affect all bacteria in a cell simultaneously. Closed expressions are obtained for the survival function of an infected cell, the number of bacteria released as a function of time after infection, and the total bacterial load. We compare our mathematical analysis with the results of agent-based computation and, making use of approximate Bayesian statistical inference, with experimental measurements carried out after murine aerosol infection with the virulent SCHU S4 strain of the bacterium Francisella tularensis, that infects alveolar macrophages. The posterior distribution of the rate of replication of intracellular bacteria is consistent with the estimate that the time between rounds of bacterial division is less than 6 hours in vivo. Public Library of Science 2020-06-01 /pmc/articles/PMC7304631/ /pubmed/32479491 http://dx.doi.org/10.1371/journal.pcbi.1007752 Text en © 2020 Carruthers 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
Carruthers, Jonathan
Lythe, Grant
López-García, Martín
Gillard, Joseph
Laws, Thomas R.
Lukaszewski, Roman
Molina-París, Carmen
Stochastic dynamics of Francisella tularensis infection and replication
title Stochastic dynamics of Francisella tularensis infection and replication
title_full Stochastic dynamics of Francisella tularensis infection and replication
title_fullStr Stochastic dynamics of Francisella tularensis infection and replication
title_full_unstemmed Stochastic dynamics of Francisella tularensis infection and replication
title_short Stochastic dynamics of Francisella tularensis infection and replication
title_sort stochastic dynamics of francisella tularensis infection and replication
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7304631/
https://www.ncbi.nlm.nih.gov/pubmed/32479491
http://dx.doi.org/10.1371/journal.pcbi.1007752
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