Quantitative Modeling of Recovery in the Human Pulmonary Alveolus

T.J. Sego, PhD

How the lung alveolus recovers from damage is poorly understood, both in the context of the alveolar microenvironment and epithelial phenotype. Experimental evidence has implicated a variety of biochemical mechanisms that contribute to regulation of epithelial proliferation and their differentiation into terminal alveolar epithelial types, though how those mechanisms fit into the broader picture of alveolar recovery and resulting homeostasis has yet to be tested. This project develops three-dimensional simulations of injury and recovery in lung epithelial tissues by combining subcellular state dynamics with agent-based modeling of epithelial cells and reaction-diffusion modeling of soluble signals. The project seeks to integrate knowledge gained from in vitro experiment to produce a holistic quantitative model that predicts the biochemical and biomechanical conditions of epithelial recovery in the alveolar microenvironment.

Publications

Sego TJ, Sluka JP, Sauro HM, Glazier JA. Tissue Forge: Interactive Biological and Biophysics Simulation Environment. 2022 Nov 29. bioRxiv, doi: 10.1101/2022.11.28.518300

Sego, T. J., Aponte-Serrano, J. O., Ferrari Gianlupi, J., Heaps, S. R., Breithaupt, K., Brusch, L., … & Glazier, J. A. (2020). A modular framework for multiscale, multicellular, spatiotemporal modeling of acute primary viral infection and immune response in epithelial tissues and its application to drug therapy timing and effectiveness. PLoS¬†computational biology, 16(12), e1008451.¬†

Sego, T. J., Mochan, E. D., Ermentrout, G. B., & Glazier, J. A. (2022). A multiscale multicellular spatiotemporal model of local influenza infection and immune response. Journal of Theoretical Biology, 532, 110918.