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Virtual infection model of Aspergillus fumigatus in a human alveolus
Version 1

This model comprises a hybrid agent-based model of a single human alveolus. The alveolus is represented in a realistic to-scale representation and contains the cell types of alveolar epithelial cells (AEC) of type 1 and 2 as well as the pores of Kohn (PoK). A single A. fumigatus conidium in inserted into the alveolus and the AEC, where the conidium is located secretes chemokines. Chemokine secretion is modelled using the partial differential equation of the diffusion equation and numerically simulated using the forward Euler approach. Chemokine gradients can be sensed by the alveolar macrophages by an internal Ordinary differential equation model for receptor-ligand binding. This leads to a directed migration of alveolar macrophages towards the conidium.

SEEK ID: https://funginet.hki-jena.de/models/26?version=1

0 items (and an image) are associated with this Model:

Organism: Aspergillus fumigatus

Model type: Agent based modelling

Model format: Not specified

Execution or visualisation environment: Not specified

Model image: (Click on the image to zoom)

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Johannes Pollmächer
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Creative Commons Attribution 4.0
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Views: 1372

Created: 18th Feb 2021 at 08:39

Last updated: 18th Feb 2021 at 08:39

Last used: 7th Jun 2023 at 10:43

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Public web page: http://www.funginet.de/project-b4.html

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Abstract (Expand)

Aspergillus fumigatus is a ubiquitous opportunistic fungal pathogen that can cause severe infections in immunocompromised patients. Conidia that reach the lower respiratory tract are confronted with … alveolar macrophages, which are the resident phagocytic cells, constituting the first line of defense. If not efficiently removed in time, A. fumigatus conidia can germinate causing severe infections associated with high mortality rates. Mice are the most extensively used model organism in research on A. fumigatus infections. However, in addition to structural differences in the lung physiology of mice and the human host, applied infection doses in animal experiments are typically orders of magnitude larger compared to the daily inhalation doses of humans. The influence of these factors, which must be taken into account in a quantitative comparison and knowledge transfer from mice to humans, is difficult to measure since in vivo live cell imaging of the infection dynamics under physiological conditions is currently not possible. In the present study, we compare A. fumigatus infection in mice and humans by virtual infection modeling using a hybrid agent-based model that accounts for the respective lung physiology and the impact of a wide range of infection doses on the spatial infection dynamics. Our computer simulations enable comparative quantification of A. fumigatus infection clearance in the two hosts to elucidate (i) the complex interplay between alveolar morphometry and the fungal burden and (ii) the dynamics of infection clearance, which for realistic fungal burdens is found to be more efficiently realized in mice compared to humans.

Authors: M. Blickensdorf, Sandra Timme, Marc Thilo Figge

Date Published: 27th Feb 2019

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

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.

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