PROJECT SUMMARY: The mammalian lung has the capacity to repair itself following various injuries. Alveolar repair is a dynamic and coordinated process whereby stem/progenitor cells in the lung undergo differentiation into specialized cells to repair the damaged epithelium. Recent studies have uncovered a distinct intermediate progenitor cell state that exists during the transition between stem/progenitor cells and these specialized cells; however, the dynamic cellular behaviors and molecular regulatory landscape that drives intermediate progenitor cell transitions toward repair is poorly understood. Here, we propose two aims to dissect the cellular and molecular mechanisms that control alveolar repair in vivo in the regenerating mammalian lung. First (Aim 1) we will utilize a permanent lung imaging window system to track the emergence, live behaviors and terminal differentiation of individual intermediate progenitor cells over time during alveolar repair. Second (Aim 2) we will utilize combined scRNA-seq and scATAC-seq together with advanced dynamical analysis and machine learning techniques to define the cellular state space (gene expression and chromatin accessibility), cellular trajectories and regulatory landscape of transitioning intermediate progenitor cells. We will perform both aims using complimentary in vivo lung injury models and fluorescent report mice in order to track the mechanisms that are unique to intermediate progenitor cells and potentially dependent on their cellular origin and/or injury context. This project will generate extensive, high quality datasets to enable quantitative and predictive models of the key regulatory mechanisms that mammalian drive alveolar repair in vivo. Given that many of the cellular and molecular mechanisms of lung biology are conserved between mouse and human, our findings have the potential to uncover putative targets for modulating alveolar repair in the context of human disease.