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A Stochastic Intracellular Model of Anthrax Infection With Spore Germination Heterogeneity

We present a stochastic mathematical model of the intracellular infection dynamics of Bacillus anthracis in macrophages. Following inhalation of B. anthracis spores, these are ingested by alveolar phagocytes. Ingested spores then begin to germinate and divide intracellularly. This can lead to the ev...

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Autores principales: Williams, Bevelynn, López-García, Martín, Gillard, Joseph J., Laws, Thomas R., Lythe, Grant, Carruthers, Jonathan, Finnie, Thomas, Molina-París, Carmen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8420810/
https://www.ncbi.nlm.nih.gov/pubmed/34497601
http://dx.doi.org/10.3389/fimmu.2021.688257
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author Williams, Bevelynn
López-García, Martín
Gillard, Joseph J.
Laws, Thomas R.
Lythe, Grant
Carruthers, Jonathan
Finnie, Thomas
Molina-París, Carmen
author_facet Williams, Bevelynn
López-García, Martín
Gillard, Joseph J.
Laws, Thomas R.
Lythe, Grant
Carruthers, Jonathan
Finnie, Thomas
Molina-París, Carmen
author_sort Williams, Bevelynn
collection PubMed
description We present a stochastic mathematical model of the intracellular infection dynamics of Bacillus anthracis in macrophages. Following inhalation of B. anthracis spores, these are ingested by alveolar phagocytes. Ingested spores then begin to germinate and divide intracellularly. This can lead to the eventual death of the host cell and the extracellular release of bacterial progeny. Some macrophages successfully eliminate the intracellular bacteria and will recover. Here, a stochastic birth-and-death process with catastrophe is proposed, which includes the mechanism of spore germination and maturation of B. anthracis. The resulting model is used to explore the potential for heterogeneity in the spore germination rate, with the consideration of two extreme cases for the rate distribution: continuous Gaussian and discrete Bernoulli. We make use of approximate Bayesian computation to calibrate our model using experimental measurements from in vitro infection of murine peritoneal macrophages with spores of the Sterne 34F2 strain of B. anthracis. The calibrated stochastic model allows us to compute the probability of rupture, mean time to rupture, and rupture size distribution, of a macrophage that has been infected with one spore. We also obtain the mean spore and bacterial loads over time for a population of cells, each assumed to be initially infected with a single spore. Our results support the existence of significant heterogeneity in the germination rate, with a subset of spores expected to germinate much later than the majority. Furthermore, in agreement with experimental evidence, our results suggest that most of the spores taken up by macrophages are likely to be eliminated by the host cell, but a few germinated spores may survive phagocytosis and lead to the death of the infected cell. Finally, we discuss how this stochastic modelling approach, together with dose-response data, allows us to quantify and predict individual infection risk following exposure.
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spelling pubmed-84208102021-09-07 A Stochastic Intracellular Model of Anthrax Infection With Spore Germination Heterogeneity Williams, Bevelynn López-García, Martín Gillard, Joseph J. Laws, Thomas R. Lythe, Grant Carruthers, Jonathan Finnie, Thomas Molina-París, Carmen Front Immunol Immunology We present a stochastic mathematical model of the intracellular infection dynamics of Bacillus anthracis in macrophages. Following inhalation of B. anthracis spores, these are ingested by alveolar phagocytes. Ingested spores then begin to germinate and divide intracellularly. This can lead to the eventual death of the host cell and the extracellular release of bacterial progeny. Some macrophages successfully eliminate the intracellular bacteria and will recover. Here, a stochastic birth-and-death process with catastrophe is proposed, which includes the mechanism of spore germination and maturation of B. anthracis. The resulting model is used to explore the potential for heterogeneity in the spore germination rate, with the consideration of two extreme cases for the rate distribution: continuous Gaussian and discrete Bernoulli. We make use of approximate Bayesian computation to calibrate our model using experimental measurements from in vitro infection of murine peritoneal macrophages with spores of the Sterne 34F2 strain of B. anthracis. The calibrated stochastic model allows us to compute the probability of rupture, mean time to rupture, and rupture size distribution, of a macrophage that has been infected with one spore. We also obtain the mean spore and bacterial loads over time for a population of cells, each assumed to be initially infected with a single spore. Our results support the existence of significant heterogeneity in the germination rate, with a subset of spores expected to germinate much later than the majority. Furthermore, in agreement with experimental evidence, our results suggest that most of the spores taken up by macrophages are likely to be eliminated by the host cell, but a few germinated spores may survive phagocytosis and lead to the death of the infected cell. Finally, we discuss how this stochastic modelling approach, together with dose-response data, allows us to quantify and predict individual infection risk following exposure. Frontiers Media S.A. 2021-08-23 /pmc/articles/PMC8420810/ /pubmed/34497601 http://dx.doi.org/10.3389/fimmu.2021.688257 Text en Copyright © 2021 Williams, López-García, Gillard, Laws, Lythe, Carruthers, Finnie and Molina-París https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Immunology
Williams, Bevelynn
López-García, Martín
Gillard, Joseph J.
Laws, Thomas R.
Lythe, Grant
Carruthers, Jonathan
Finnie, Thomas
Molina-París, Carmen
A Stochastic Intracellular Model of Anthrax Infection With Spore Germination Heterogeneity
title A Stochastic Intracellular Model of Anthrax Infection With Spore Germination Heterogeneity
title_full A Stochastic Intracellular Model of Anthrax Infection With Spore Germination Heterogeneity
title_fullStr A Stochastic Intracellular Model of Anthrax Infection With Spore Germination Heterogeneity
title_full_unstemmed A Stochastic Intracellular Model of Anthrax Infection With Spore Germination Heterogeneity
title_short A Stochastic Intracellular Model of Anthrax Infection With Spore Germination Heterogeneity
title_sort stochastic intracellular model of anthrax infection with spore germination heterogeneity
topic Immunology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8420810/
https://www.ncbi.nlm.nih.gov/pubmed/34497601
http://dx.doi.org/10.3389/fimmu.2021.688257
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