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Deciphering chemokine properties by a hybrid agent-based model of Aspergillus fumigatus infection in human alveoli.

Pollmächer J, Figge MT - Front Microbiol (2015)

Bottom Line: To this end, the rule-based implementation of chemokine diffusion in the initial agent-based model is revised by numerically solving the spatio-temporal reaction-diffusion equation in the complex structure of the alveolus.Performing simulations for more than a million virtual infection scenarios, we find that the ratio of secretion rate to the diffusion coefficient is the main indicator for the success of pathogen detection.Moreover, a subdivision of the parameter space into regimes of successful and unsuccessful parameter combination by this ratio is specific for values of the migration speed and the directional persistence time of alveolar macrophages, but depends only weakly on chemokine degradation rates.

View Article: PubMed Central - PubMed

Affiliation: Applied Systems Biology, Leibniz-Institute for Natural Product Research and Infection Biology - Hans Knöll Institute Jena, Germany ; Faculty of Biology and Pharmacy, Friedrich Schiller University Jena Jena, Germany.

ABSTRACT
The ubiquitous airborne fungal pathogen Aspergillus fumigatus is inhaled by humans every day. In the lung, it is able to quickly adapt to the humid environment and, if not removed within a time frame of 4-8 h, the pathogen may cause damage by germination and invasive growth. Applying a to-scale agent-based model of human alveoli to simulate early A. fumigatus infection under physiological conditions, we recently demonstrated that alveolar macrophages require chemotactic cues to accomplish the task of pathogen detection within the aforementioned time frame. The objective of this study is to specify our general prediction on the as yet unidentified chemokine by a quantitative analysis of its expected properties, such as the diffusion coefficient and the rates of secretion and degradation. To this end, the rule-based implementation of chemokine diffusion in the initial agent-based model is revised by numerically solving the spatio-temporal reaction-diffusion equation in the complex structure of the alveolus. In this hybrid agent-based model, alveolar macrophages are represented as migrating agents that are coupled to the interactive layer of diffusing molecule concentrations by the kinetics of chemokine receptor binding, internalization and re-expression. Performing simulations for more than a million virtual infection scenarios, we find that the ratio of secretion rate to the diffusion coefficient is the main indicator for the success of pathogen detection. Moreover, a subdivision of the parameter space into regimes of successful and unsuccessful parameter combination by this ratio is specific for values of the migration speed and the directional persistence time of alveolar macrophages, but depends only weakly on chemokine degradation rates.

No MeSH data available.


Related in: MedlinePlus

Probabilities of directed AM migration over the geodesic distance from the AEC associated with the conidium. The mean and standard deviation of the probability pdirected are shown in the absence of chemokine degradation for the diffusion coefficient D = 60 μm2/min with AM directional persistence time tp = 1 min. In (A) AM migrate with speed v = 2 μm/min and in (B) with speed v = 4 μm/min. Averages and standard deviations were determined using the probabilities of directed AM migration that were drawn over the whole simulation time in all simulation runs. The present results are compared to the probabilistic rule for directed migration (solid black line) used in Pollmächer and Figge (2014).
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Figure 5: Probabilities of directed AM migration over the geodesic distance from the AEC associated with the conidium. The mean and standard deviation of the probability pdirected are shown in the absence of chemokine degradation for the diffusion coefficient D = 60 μm2/min with AM directional persistence time tp = 1 min. In (A) AM migrate with speed v = 2 μm/min and in (B) with speed v = 4 μm/min. Averages and standard deviations were determined using the probabilities of directed AM migration that were drawn over the whole simulation time in all simulation runs. The present results are compared to the probabilistic rule for directed migration (solid black line) used in Pollmächer and Figge (2014).

Mentions: Interestingly, we observed a minimum of p(FPT > 6 h) as a function of the secretion rate for various diffusion coefficients in the case of AM migration speed v = 2 μm/min and persistence time tp = 1 min (see Figure 4A). This system behavior reflects the fact that an optimal concentration of chemokines exists for an efficient guidance of AM. The value of the optimal concentration is determined by the interplay of several factors, e.g., the secretion rate, diffusion coefficient and degradation rate of the chemokine as well as the number of AM receptors and their dynamics of binding, internalization and re-expression. For example, a too high chemokine concentration is associated with a low number of unbound AM receptors limiting the adaptation of AM migration along the chemokine gradient. We further analyzed this situation by computing the probability of directed AM migration for different secretion rates and for AM migration speeds v = 2 μm/min and v = 4 μm/min. The resulting probability distributions are shown in Figure 5 as a function of the geodesic distance of AM from the AEC associated with the conidium. We found that optimal values of p(FPT > 6 h) in Figure 4A correspond to probability distributions with a narrow and peaked maximum (see red curves in Figure 5). For a constant diffusion coefficient, lower secretion rates were associated with less prominent maxima in the probability distribution (see blue curves in Figure 5), which in turn increased p(FPT > 6 h). On the other hand, higher secretion rates were associated with extended and flat maxima at relatively large geodesic distances from the boundary of the secreting AEC (see green curves in Figure 5). It should be noted that the profiles of the determined probability distributions are the results of various factors, such as the chemokine concentration and the receptor dynamics of AM. For example, in the case of high secretion rates, many AM receptors were already bound to the chemokine at early time points due to its relatively high concentration in the alveolus. As a result, AM were guided to the AEC associated with the conidium relatively early in time. However, the relatively high concentration of chemokines also had the adverse effect that the number of free AM receptors was decreased at distances close to the secreting AEC. Consequently, fewer events of receptor-ligand binding lead to relatively low probabilities for directed AM migration and ultimately increased p(FPT > 6 h).


Deciphering chemokine properties by a hybrid agent-based model of Aspergillus fumigatus infection in human alveoli.

Pollmächer J, Figge MT - Front Microbiol (2015)

Probabilities of directed AM migration over the geodesic distance from the AEC associated with the conidium. The mean and standard deviation of the probability pdirected are shown in the absence of chemokine degradation for the diffusion coefficient D = 60 μm2/min with AM directional persistence time tp = 1 min. In (A) AM migrate with speed v = 2 μm/min and in (B) with speed v = 4 μm/min. Averages and standard deviations were determined using the probabilities of directed AM migration that were drawn over the whole simulation time in all simulation runs. The present results are compared to the probabilistic rule for directed migration (solid black line) used in Pollmächer and Figge (2014).
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4446573&req=5

Figure 5: Probabilities of directed AM migration over the geodesic distance from the AEC associated with the conidium. The mean and standard deviation of the probability pdirected are shown in the absence of chemokine degradation for the diffusion coefficient D = 60 μm2/min with AM directional persistence time tp = 1 min. In (A) AM migrate with speed v = 2 μm/min and in (B) with speed v = 4 μm/min. Averages and standard deviations were determined using the probabilities of directed AM migration that were drawn over the whole simulation time in all simulation runs. The present results are compared to the probabilistic rule for directed migration (solid black line) used in Pollmächer and Figge (2014).
Mentions: Interestingly, we observed a minimum of p(FPT > 6 h) as a function of the secretion rate for various diffusion coefficients in the case of AM migration speed v = 2 μm/min and persistence time tp = 1 min (see Figure 4A). This system behavior reflects the fact that an optimal concentration of chemokines exists for an efficient guidance of AM. The value of the optimal concentration is determined by the interplay of several factors, e.g., the secretion rate, diffusion coefficient and degradation rate of the chemokine as well as the number of AM receptors and their dynamics of binding, internalization and re-expression. For example, a too high chemokine concentration is associated with a low number of unbound AM receptors limiting the adaptation of AM migration along the chemokine gradient. We further analyzed this situation by computing the probability of directed AM migration for different secretion rates and for AM migration speeds v = 2 μm/min and v = 4 μm/min. The resulting probability distributions are shown in Figure 5 as a function of the geodesic distance of AM from the AEC associated with the conidium. We found that optimal values of p(FPT > 6 h) in Figure 4A correspond to probability distributions with a narrow and peaked maximum (see red curves in Figure 5). For a constant diffusion coefficient, lower secretion rates were associated with less prominent maxima in the probability distribution (see blue curves in Figure 5), which in turn increased p(FPT > 6 h). On the other hand, higher secretion rates were associated with extended and flat maxima at relatively large geodesic distances from the boundary of the secreting AEC (see green curves in Figure 5). It should be noted that the profiles of the determined probability distributions are the results of various factors, such as the chemokine concentration and the receptor dynamics of AM. For example, in the case of high secretion rates, many AM receptors were already bound to the chemokine at early time points due to its relatively high concentration in the alveolus. As a result, AM were guided to the AEC associated with the conidium relatively early in time. However, the relatively high concentration of chemokines also had the adverse effect that the number of free AM receptors was decreased at distances close to the secreting AEC. Consequently, fewer events of receptor-ligand binding lead to relatively low probabilities for directed AM migration and ultimately increased p(FPT > 6 h).

Bottom Line: To this end, the rule-based implementation of chemokine diffusion in the initial agent-based model is revised by numerically solving the spatio-temporal reaction-diffusion equation in the complex structure of the alveolus.Performing simulations for more than a million virtual infection scenarios, we find that the ratio of secretion rate to the diffusion coefficient is the main indicator for the success of pathogen detection.Moreover, a subdivision of the parameter space into regimes of successful and unsuccessful parameter combination by this ratio is specific for values of the migration speed and the directional persistence time of alveolar macrophages, but depends only weakly on chemokine degradation rates.

View Article: PubMed Central - PubMed

Affiliation: Applied Systems Biology, Leibniz-Institute for Natural Product Research and Infection Biology - Hans Knöll Institute Jena, Germany ; Faculty of Biology and Pharmacy, Friedrich Schiller University Jena Jena, Germany.

ABSTRACT
The ubiquitous airborne fungal pathogen Aspergillus fumigatus is inhaled by humans every day. In the lung, it is able to quickly adapt to the humid environment and, if not removed within a time frame of 4-8 h, the pathogen may cause damage by germination and invasive growth. Applying a to-scale agent-based model of human alveoli to simulate early A. fumigatus infection under physiological conditions, we recently demonstrated that alveolar macrophages require chemotactic cues to accomplish the task of pathogen detection within the aforementioned time frame. The objective of this study is to specify our general prediction on the as yet unidentified chemokine by a quantitative analysis of its expected properties, such as the diffusion coefficient and the rates of secretion and degradation. To this end, the rule-based implementation of chemokine diffusion in the initial agent-based model is revised by numerically solving the spatio-temporal reaction-diffusion equation in the complex structure of the alveolus. In this hybrid agent-based model, alveolar macrophages are represented as migrating agents that are coupled to the interactive layer of diffusing molecule concentrations by the kinetics of chemokine receptor binding, internalization and re-expression. Performing simulations for more than a million virtual infection scenarios, we find that the ratio of secretion rate to the diffusion coefficient is the main indicator for the success of pathogen detection. Moreover, a subdivision of the parameter space into regimes of successful and unsuccessful parameter combination by this ratio is specific for values of the migration speed and the directional persistence time of alveolar macrophages, but depends only weakly on chemokine degradation rates.

No MeSH data available.


Related in: MedlinePlus