Invasive aspergillosis is among the most common fungal infection in immunocompromised hosts and carries a poor outcome. 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 against this infection, possibly in combination with antifungal drugs. Iron is essential to all living organisms, and restricting iron availability is a critical mechanism of
antimicrobial host defense against many microorganisms; conversely, successful pathogens have evolved potent mechanisms for scavenging iron from the host. These mechanisms have the potential to be harnessed therapeutically, for example with drugs that enhance the host’s iron sequestration mechanisms. The overarching goal of this project is to develop a multi-scale mathematical model that can serve as a simulation tool of the role of iron in invasive aspergillosis. The model will integrate mechanisms at the molecular scale with tissue-level events and a whole-body scale capturing the role of the liver. The project brings an innovative approach to the study of this infection, and introduces innovative features to multiscale modeling through a novel modular software design that improves flexibility, reproducibility, and model sharing.
Invasive aspergillosis represents a major and growing health problem in the U.S. and around the world. The growing population of immunocompromised patients, combined with increased resistance to recently introduced antifungal drugs makes it urgent to develop new therapeutics, in particular those targeting the host immune response. The proposed project will develop and use advanced mathematical and computational tools, calibrated to extensive experimental data, in order to explore new potential therapeutic targets to treat this disease.
Laubenbacher R, Niarakis A, Helikar T, An G, Shapiro B, Malik-Sheriff RS, Sego TJ, Knapp A, Macklin P, Glazier JA. Building digital twins of the human immune system: toward a roadmap. npj Digit. Med. 2022 May 20;5,64. doi: 10.1038/s41746-022-00610-z.
Sordo Vieira L, Laubenbacher R. Computational models in systems biology: standards, dissemination, and best practices. Curr Opin Biotechnol. 2022 Jun;75:102702. doi: 10.1016/j.copbio.2022.102702. Epub ahead of print.
Knapp AC, Sordo Vieira L, Laubenbacher R, Chifman J. SteadyCellPhenotype: A web-based tool for the modeling of biological networks with ternary logic. Bioinformatics. 2022 Feb 18. doi: 10.1093/bioinformatics/btac097. Epub ahead of print.
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
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.