The Innate Immune Response to Invasive Pulmonary Aspergillosis: A Systems Modeling Approach

Invasive aspergillosis is a fungal respiratory infection that poses an increasingly serious health risk with the rise in the number of immunocompromised patients and the emergence of fungal strains resistant to first-line anti-fungal drugs. Consequently, there is a pressing need for host-centric therapeutics for this infection, which motivated the work presented in this paper. Given the multi-scale nature of the immune response, computational models are a key technology for capturing the dynamics of the battle between the pathogen and the immune system. We describe such a multi-scale computational model, focused on the mechanisms for iron regulation, a key element for fungal virulence in the pathogen Aspergillus fumigatus. A key feature of the model is that its parameters have been derived from an extensive literature search rather than data fitting. The model is shown to reproduce a wide range of published time course data, as well as custom validation data generated for this purpose. It also accurately reproduces many qualitative features of the initial course of infection.The battle between the immune system and invading pathogens is highly dynamic, involving mechanisms from the intracellular and tissue scales to the whole-body scale. Medical interventions aim to change the dynamic trajectory of the infection in the patient’s favor. Computational models that capture the system dynamics can play an important role in understanding the mechanisms determining the course of infection and discovering possible interventions. The model described here focuses on a well-defined and complex mechanism, the “battle over iron” between the host and a respiratory fungal pathogen, a crucial virulence factor. It includes several cell types, cytokines, and other molecules involved in the immune response. A key feature of the model is its broad validity, resulting from efforts to find information about numerical values for all of the many model parameters in the literature, rather than determining them by fitting the model to one or more time courses of experimental data. Consequently, the model can form the basis for investigating host-centric interventions in the course of the disease, as well as for expanding it to study other pathogens and inflammatory lung diseases.