Hybrid Agent-Based Modeling of Aspergillus fumigatus Infection to Quantitatively Investigate the Role of Pores of Kohn in Human Alveoli

Abstract

The healthy state of an organism is constantly threatened by external cues. Due to the daily inhalation of hundreds of particles and pathogens, the immune system needs to constantly accomplish the task of pathogen clearance in order to maintain this healthy state. However, infection dynamics are highly influenced by the peculiar anatomy of the human lung. Lung alveoli that are packed in alveolar sacs are interconnected by so called Pores of Kohn. Mainly due to the lack of in vivo methods, the role of Pores of Kohn in the mammalian lung is still under debate and partly contradicting hypotheses remain to be investigated. Although it was shown by electron microscopy that Pores of Kohn may serve as passageways for immune cells, their impact on the infection dynamics in the lung is still unknown under in vivo conditions. In the present study, we apply a hybrid agent-based infection model to quantitatively compare three different scenarios and discuss the importance of Pores of Kohn during infections of Aspergillus fumigatus. A. fumigatus is an airborne opportunistic fungus with rising incidences causing severe infections in immunocompromised patients that are associated with high mortality rates. Our hybrid agent-based model incorporates immune cell dynamics of alveolar macrophages - the resident phagocytes in the lung - as well as molecular dynamics of diffusing chemokines that attract alveolar macrophages to the site of infection. Consequently, this model allows a quantitative comparison of three different scenarios and to study the importance of Pores of Kohn. This enables us to demonstrate how passaging of alveolar macrophages and chemokine diffusion affect A. fumigatus infection dynamics. We show that Pores of Kohn alter important infection clearance mechanisms, such as the spatial distribution of macrophages and the effect of chemokine signaling. However, despite these differences, a lack of passageways for alveolar macrophages does impede infection clearance only to a minor extend. Furthermore, we quantify the importance of recruited macrophages in comparison to resident macrophages.

Keywords: Aspergillus fumigatus lung infection; Pores of Kohn; human model; hybrid agent-based computer simulations; virtual infection modeling.

FIGURE 1

Visualization of a to-scale human alveolus in the hybrid agent-based model. The alveolar entrance ring (left) and Pores of Kohn (black) represent entry/exit points for alveolar macrophages (green) and chemokine flow (white isolines) induced by the alveolar epithelial cell where the conidium (red) is located. Alveolar surface is covered with epithelial cells of type 1 (yellow) and type 2 (blue). The pole of the alveolus is indicated by the arrow.

FIGURE 2

Spatial AM distribution. Mean AM count after equilibration of system dynamics along the main axis of the alveolus from the entrance ring (at 59 μm) to the pole (at -116.5 μm). Each data point refers to an average over ring segments with equal area of 25,583 μm².

FIGURE 3

The infection score represented in a color-coded fashion as a function of all scanned combinations of chemokine parameters. Numbers represent the respective infection scores. A black circle around the point indicates significant differences between the three models as tested with a log-rank test.

FIGURE 4

Infection scores along the main axis of the alveolus from the entrance ring (at 59 μm) to the pole (at -116.5 μm) for various diffusion coefficients and secretion rate s_AEC = 15,000min⁻¹. Each data point refers to an average over ring segments with equal area of 25,583 μm².

FIGURE 5

(A) Boxplot of mean chemokine concentration across the whole alveolar surface in the simulations at t = 200min for various secretion rates s_AEC and a fixed diffusion coefficient of D = 600μm²min⁻¹ for all three models. N = 1000. Each box represents to 25–75% quantile and central line represents the mean. (B) Boxplot of total sum of alveolar macrophages in the simulations at t = 360min for various secretion rates s_AEC and a fixed diffusion coefficient of D = 20μm²min⁻¹ for all three models. N = 1000. Each box represents to 25–75% quantile and central line represents the mean.

FIGURE 6

Asphericity (A) and confinement (B) ratio as a measurement of track straightness of each AM_success in relation to the track length for each of the three models for diffusion coefficient D = 20μm²min⁻¹ and secretion rate s_AEC = 1500min⁻¹. Regression line represents LOESS fit and the shaded area represents the estimations standard error.

FIGURE 7

(A) Probability of an alveolar macrophage to migrate biased toward the chemokine gradient and (B) accumulation of alveolar macrophages along the main axis of the alveolus from entrance ring (59 μm) to pole (-116.5 μm) for the PoK+/+ model and the PoK−/− model for selected secretion rates and diffusion coefficient D = 20μm²min⁻¹. Each data point refers to an average over ring segments with equal area of 25,583 μm².