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Modeling early events in Francisella tularensis pathogenesis.

Gillard JJ, Laws TR, Lythe G, Molina-París C - Front Cell Infect Microbiol (2014)

Bottom Line: The model is mechanistic and governed by a small number of experimentally verifiable parameters.The mean and variance of these distributions are determined by model parameters with a precise biological interpretation, providing new mechanistic insights into the determinants of immune and bacterial kinetics.Insights into the dynamics of macrophage suppression and activation gained by the model can be used to explore the potential benefits of interventions that stimulate macrophage activation.

View Article: PubMed Central - PubMed

Affiliation: Defence Science and Technology Laboratory Porton Down, Salisbury, UK.

ABSTRACT
Computational models can provide valuable insights into the mechanisms of infection and be used as investigative tools to support development of medical treatments. We develop a stochastic, within-host, computational model of the infection process in the BALB/c mouse, following inhalational exposure to Francisella tularensis SCHU S4. The model is mechanistic and governed by a small number of experimentally verifiable parameters. Given an initial dose, the model generates bacterial load profiles corresponding to those produced experimentally, with a doubling time of approximately 5 h during the first 48 h of infection. Analytical approximations for the mean number of bacteria in phagosomes and cytosols for the first 24 h post-infection are derived and used to verify the stochastic model. In our description of the dynamics of macrophage infection, the number of bacteria released per rupturing macrophage is a geometrically-distributed random variable. When combined with doubling time, this provides a distribution for the time taken for infected macrophages to rupture and release their intracellular bacteria. The mean and variance of these distributions are determined by model parameters with a precise biological interpretation, providing new mechanistic insights into the determinants of immune and bacterial kinetics. Insights into the dynamics of macrophage suppression and activation gained by the model can be used to explore the potential benefits of interventions that stimulate macrophage activation.

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Mechanism of F. tularensis pathogenesis. Top line: A bacterium (blue), ingested by a macrophage (green), escapes from the phagosome to the cytosol. Central line: In the cytosol, bacteria proliferate, eventually (bottom line) provoking rupture and death of the macrophage and release of a large number of bacteria.
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Figure 1: Mechanism of F. tularensis pathogenesis. Top line: A bacterium (blue), ingested by a macrophage (green), escapes from the phagosome to the cytosol. Central line: In the cytosol, bacteria proliferate, eventually (bottom line) provoking rupture and death of the macrophage and release of a large number of bacteria.

Mentions: The basic dynamics of F. tularensis infection are illustrated in Figure 1. The mechanics of deposition in the alveolar space, which precedes infection, are outside the scope of our model. Therefore, the assumed initial state of the system at time t = 0, is that a dose of N free bacteria is located in the alveolar spaces, in proximity of M resting macrophages. Macrophage infection and bacterial replication then take place according to the following rules:


Modeling early events in Francisella tularensis pathogenesis.

Gillard JJ, Laws TR, Lythe G, Molina-París C - Front Cell Infect Microbiol (2014)

Mechanism of F. tularensis pathogenesis. Top line: A bacterium (blue), ingested by a macrophage (green), escapes from the phagosome to the cytosol. Central line: In the cytosol, bacteria proliferate, eventually (bottom line) provoking rupture and death of the macrophage and release of a large number of bacteria.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4263195&req=5

Figure 1: Mechanism of F. tularensis pathogenesis. Top line: A bacterium (blue), ingested by a macrophage (green), escapes from the phagosome to the cytosol. Central line: In the cytosol, bacteria proliferate, eventually (bottom line) provoking rupture and death of the macrophage and release of a large number of bacteria.
Mentions: The basic dynamics of F. tularensis infection are illustrated in Figure 1. The mechanics of deposition in the alveolar space, which precedes infection, are outside the scope of our model. Therefore, the assumed initial state of the system at time t = 0, is that a dose of N free bacteria is located in the alveolar spaces, in proximity of M resting macrophages. Macrophage infection and bacterial replication then take place according to the following rules:

Bottom Line: The model is mechanistic and governed by a small number of experimentally verifiable parameters.The mean and variance of these distributions are determined by model parameters with a precise biological interpretation, providing new mechanistic insights into the determinants of immune and bacterial kinetics.Insights into the dynamics of macrophage suppression and activation gained by the model can be used to explore the potential benefits of interventions that stimulate macrophage activation.

View Article: PubMed Central - PubMed

Affiliation: Defence Science and Technology Laboratory Porton Down, Salisbury, UK.

ABSTRACT
Computational models can provide valuable insights into the mechanisms of infection and be used as investigative tools to support development of medical treatments. We develop a stochastic, within-host, computational model of the infection process in the BALB/c mouse, following inhalational exposure to Francisella tularensis SCHU S4. The model is mechanistic and governed by a small number of experimentally verifiable parameters. Given an initial dose, the model generates bacterial load profiles corresponding to those produced experimentally, with a doubling time of approximately 5 h during the first 48 h of infection. Analytical approximations for the mean number of bacteria in phagosomes and cytosols for the first 24 h post-infection are derived and used to verify the stochastic model. In our description of the dynamics of macrophage infection, the number of bacteria released per rupturing macrophage is a geometrically-distributed random variable. When combined with doubling time, this provides a distribution for the time taken for infected macrophages to rupture and release their intracellular bacteria. The mean and variance of these distributions are determined by model parameters with a precise biological interpretation, providing new mechanistic insights into the determinants of immune and bacterial kinetics. Insights into the dynamics of macrophage suppression and activation gained by the model can be used to explore the potential benefits of interventions that stimulate macrophage activation.

Show MeSH
Related in: MedlinePlus