Agent-Based Model of Human Alveoli Predicts Chemotactic Signaling by Epithelial Cells during Early Aspergillus fumigatus Infection

Abstract

Aspergillus fumigatus is one of the most important human fungal pathogens, causing life-threatening diseases. Since humans inhale hundreds to thousands of fungal conidia every day, the lower respiratory tract is the primary site of infection. Current interaction networks of the innate immune response attribute fungal recognition and detection to alveolar macrophages, which are thought to be the first cells to get in contact with the fungus. At present, these networks are derived from in vitro or in situ assays, as the peculiar physiology of the human lung makes in vivo experiments, including imaging on the cell-level, hard to realize. We implemented a spatio-temporal agent-based model of a human alveolus in order to perform in silico experiments of a virtual infection scenario, for an alveolus infected with A. fumigatus under physiological conditions. The virtual analog captures the three-dimensional alveolar morphology consisting of the two major alveolar epithelial cell types and the pores of Kohn as well as the dynamic process of respiration. To the best of our knowledge this is the first agent-based model of a dynamic human alveolus in the presence of respiration. A key readout of our simulations is the first-passage-time of alveolar macrophages, which is the period of time that elapses until the first physical macrophage-conidium contact is established. We tested for random and chemotactic migration modes of alveolar macrophages and varied their corresponding parameter sets. The resulting first-passage-time distributions imply that randomly migrating macrophages fail to find the conidium before the start of germination, whereas guidance by chemotactic signals derived from the alveolar epithelial cell associated with the fungus enables a secure and successful discovery of the pathogen in time.

Quantitative Analysis of Proteome Modulations in Alveolar Epithelial Type II Cells in Response to Pulmonary Aspergillus fumigatus Infection

“…N are extremely effective in phagocytosing conidia (8,9), which is the reason why especially lack or dysfunction of N is associated with a highly increased risk for IA development (10 -12). Although these phagocytotic members of the lung-associated immune system are all well studied, it is obvious, that alveolar epithelial cells (AEC), that make up the entire more than 100 m 2 large respiratory surface of the lung (12) have a much higher likelihood of physically engaging freshly inhaled conidia before any other cell of the immune system (13). However, the effects of this interaction are not known.…”

The geographical region of origin determines the phagocytic vulnerability of Lichtheimia strains

“…Yet, the interplay of Mucorales fungi, especially Lichtheima species, with the innate immune system, for example, alveolar macrophages, is poorly understood. The innate immune system is the body's first line of defence, within which the alveolar macrophages play a vital role in combating pulmonary infections (Blickensdorf et al, 2019;Espinosa and Rivera, 2016;Pollmächer et al, 2016;Pollmächer and Figge, 2015;Pollmächer and Figge, 2014;Tokarski et al, 2012). At the focus of our study were the two most common species of Lichtheimia causing human and animal disease -L. corymbifera and L. ramosawith the goal of investigating the differential behaviour of MH-S macrophages confronted in vitro with various strains.…”

Trends in mathematical modeling of host–pathogen interactions

“…Some famous examples are iDynoMics [78], MASON [82], Net-Logo [132], and BSim [48,85] which are user-friendly and can also be used by non-modelers. In addition, frameworkindependent implementations are used for ABM to simulate HPI [23,102,123]. NetLogo [21,132] is one example for a modeling framework with its own programming language, with 'turtles' that represent agents and 'patches' that represent points in the simulation space.…”

“…In another ABM, the movement of human alveolar macrophages searching A. fumigatus spores on the lung epithelium was modeled [102]. The model predicted that randomly migrating macrophages fail to find the spore before the start of germination, whereas guidance by chemotactic signals enables a safe and successful discovery of the pathogen in time (for an extended model, see [9,103]).…”