Project Team: Christopher Marx (PI), Andreas Vasdekis (Co-PI), Chris Remien, Siavash Riazi, Denis Liyu

Multidrug antibiotic persistence, which allows some cells that lack genetic resistance to survive antibiotic stresses by becoming dormant, is a major public health concern. This exploratory project will use data from state-of-the-art image cytometry and single-cell analysis in combination with mechanistic mathematical modeling to study the formaldehyde-sensing network that was recently discovered in Methylobacterium by the Marx Lab. The formaldehyde-sensing network in Methylobacterium shares many characteristics with antibiotic persistence, but has the advantage of allowing us to externally manipulate factors governing the transition from growth to stasis, and all the cells in a population go dormant. The research team wishes to develop mathematical models in combination with relevant experimentation 1) to study the ability the biochemical network to allow for distinct cell fate outcomes as a function of key parameters such as protein levels of EfgA 2) to analyze how stochasticity in the form of spontaneous fluctuations in protein levels, which can lead to a potentially toxic pulse of formaldehyde, influences cell transitions between phenotypes such as growth, death, or persistence. This pilot grant will position the researchers to explore fundamental processes associated with antimicrobial resistance, which if eventually manipulated could prevent disease and promote health.

Project Team: Tao Xing (PI), Gordon Murdoch (Co-PI), Michelle Wiest, Loel Fenwick, Rabijit Dutta

Without adequate respiration, life ceases in as little as three minutes. The failure of effective spontaneous respiration requires immediate intervention to preserve life. However, lungs are far more complicated than simple bags at the ends of tubes. Life support or therapeutic treatment of injured or diseased lungs is frequently needed. However, the current understanding of the most effective reliable and safe pulmonary ventilation methodology is sorely lacking, for either conventional mechanical ventilator (closed-circuit) or the more recent flow ventilation (open-circuit) by Percussionaire Corp. The goal of this project is to develop and validate a multi-scale model for understanding and optimizing the interaction between lungs and pulmonary ventilations, including the key mechanisms impacting the effectiveness of pulmonary ventilation at the organ, tissue, cellular, and molecular scales.

Additionally, the incorporation and integration of hardware can reliably yield empirical experimental data throughout the conducting components of the respiratory anatomy (buccal cavity, trachea, bronchi, bronchioles) as well as the respiratory anatomy responsible for effective gas exchange (inferior bronchioles and alveoli). The model, once validated using the experimental data, will provide a reliable simulation based design toolbox to evaluate comparative profiles of various methods of rescue/supplemental ventilation, which are critical for extrapolating the efficacy of biomedical instrumentation that are designed to reduce mortality associated with respiratory diseases and/or damaged or physiologically compromised lungs. It will provide a virtual three-dimensional laboratory for in silico study of various lung diseases that facilitates a personalized flow ventilation technologies. It will fundamentally change the way current researchers design respiration devices such that simulation-based modeling is applied toward the next generation expert system for the optimization of pulmonary ventilation.

If successful, the proposed innovation would contribute to the saving of lives of those with acute respiratory distress and extend and improve the lives of those with chronic pulmonary conditions. Moreover, it will generate scientific data that can be utilized to provide patient and condition specific therapy. Tackling Critical Issues in the Ebola Epidemic through Modeling Viral Evolution.