U01 EB024501-01: Modular Design of Multiscale Models

Project Summary

Increased availability of biomedical data sets across spatial and temporal scales makes it possible to calibrate complex models that capture integrated processes from the molecular to the whole organism level. This complexity poses multiple challenges related to mathematical modeling, software design, validation, reproducibility, and extensibility. Visualization of model features and dynamics is a key factor in the usability of models by domain experts, such as experimental biologists and clinicians. The proposed project addresses these challenges in the context of the immune response to an important respiratory fungal infection. Its goal is to develop a novel modular approach to model architecture, using a recently introduced technology of lightweight virtual machines and our user-friendly open-source platform for the construction and linking of these so-called “Docker containers” to create complex modular models in a transparent fashion. A key benefit of software containers is that they can encompass the entire computational environment of a model, enabling unprecedented reproducibility of computational results. The overarching computational goal is to develop a novel approach to the modular design of multiscale models. While broadly applicable, this novel computational modeling approach will be focused on the development of a multiscale model capturing the early stages of invasive aspergillosis, an important health problem.

Invasive aspergillosis is one of the most common fungal infections in immunocompromised hosts and carries a poor prognosis. The spores of the causative organism, Aspergillus fumigatus, are ubiquitously distributed in the environment. Healthy hosts clear the inhaled spores without developing disease, but individuals with impaired immunity are susceptible to a life-threatening respiratory infection that can then disseminate to other organs. The increasing use of immunosuppressive therapies in transplantation and cancer has dramatically increased suffering and death from this infection, and this trend is expected to continue. Current therapeutic approaches have been focused primarily on the pathogen, but a better understanding of the components of host defense in this infection may lead to the development of new treatments. In particular, restricting iron availability is a critical mechanism of antimicrobial host defense; conversely, successful pathogens have evolved potent mechanisms for scavenging iron from the host. These mechanisms have the potential to be harnessed therapeutically. The biological focus of the proposed project is the battle over iron between the fungus and the host. The overarching biomedical goal is to develop a simulation tool to explore the role of iron in invasive aspergillosis across biochemical and biophysical conditions.

Project Narrative

Multiscale mathematical and computational models are an important technology in biomedicine. This project addresses the need for further technology development, in the context of an important health problem, respiratory fungal infections with high mortality levels in populations of immunocompromised patients.

Publications

Masison, J., J. Beezley, Y. Mei, H. a. L. Ribeiro, A. C. Knapp, L. Sordo Vieira, B. Adhikari, et al. “A Modular Computational Framework for Medical Digital Twins.” Proceedings of the National Academy of Sciences 118, no. 20 (May 18, 2021). https://doi.org/10.1073/pnas.2024287118.

Cagnina, R. Elaine, Kathryn R. Michels, Alexandra M. Bettina, Marie D. Burdick, Yogesh Scindia, Zhimin Zhang, Thomas J. Braciale, and Borna Mehrad. “Neutrophil-Derived TNF Drives Fungal Acute Lung Injury in Chronic Granulomatous Disease.” The Journal of Infectious Diseases, April 5, 2021. https://doi.org/10.1093/infdis/jiab188.

Wooten, David J., Jorge Gómez Tejeda Zañudo, David Murrugarra, Austin M. Perry, Anna Dongari-Bagtzoglou, Reinhard Laubenbacher, Clarissa J. Nobile, and Réka Albert. “Mathematical Modeling of the Candida Albicans Yeast to Hyphal Transition Reveals Novel Control Strategies.” Preprint. Systems Biology, January 20, 2021. https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1008690

E. Paul, G. Pogudin, W. Qin and R. Laubenbacher, The dynamics of canalizing Boolean networks, Complexity, https://doi.org/10.1155/2020/3687961, 2020.

L. Sordo Vieira, R. Laubenbacher, and D. Murrugarra, Control of Intracellular Molecular Networks Using Algebraic Methods, Bull. Math. Biol., 82(2), 2019.

Aguilar, Boris, Pan Fang, Reinhard Laubenbacher, and David Murrugarra. 2020. “A Near-Optimal Control Method for Stochastic Boolean Networks”. Letters in Biomathematics 7 (1), 67–80.

E. Paul, G. Pogudin, W. Qin and R. Laubenbacher, The dynamics of canalizing Boolean networks, Complexity, https://doi.org/10.1155/2020/3687961, 2020.

Michels KR, Solomon AL, Scindia Y, Vaulont S, Burdick MD, Laubenbacher R, Mehrad B. Aspergillus utilizes heme as an iron source during invasive pneumonia. Submitted to mBio (revising manuscript to resubmit).

Solomon A, Michels K, Laubenbacher R, Scindia Y, Mehrad B. The role of heme uptake and hemopexin in invasive pulmonary aspergillosis. American Thoracic Society Virtual Conference, 2020.

Qu G, Solomon A, Yang N, Lin C, Scindia Y, Mehrad B. Alveolar macrophages protect against acute lung injury. American Thoracic Society Virtual Conference, 2020.