The HPMI 2.0 aims to unravel the basic mechanisms of pathogenesis of respiratory diseases caused by the bacterium Mtb as well as respiratory viruses (SARS-CoV-2 and VOCs, IAV and IBV, HPIV-3, and RSV-A). We will apply a suite of systems biology approaches combined with microbiological assays as well as computational and structural biology to systematically characterize host factors important for infection, with the goal of discovering therapeutically actionable targets for HDTs. We will integrate our proteomics, genetic, and structural data with clinical datasets, followed by using the resulting network maps to create computational models for the identification of combinatorial biomarkers in which not one but multiple genes/features are evaluated to predict disease outcomes. Models that predict disease state (risk, severity, resistance, tolerance) given a set of genetic mutations, mRNA expression levels, protein abundances, and clinical parameters will be assessed on our innovative Mtb-infected cohort in Vietnam and COVID-19 patients at UCSF.
Our unbiased approaches studying two of the most important human pathogens, benefiting from the tools in the integrated HPMI Cores, will uncover novel common pathways by which bacterial and viral pathogens synergize and reveal new targets for host-directed therapeutics.