Project 2 - Ex Vivo Analysis of Coronavirus Tropism, Adaptation, Replication, and Host Response

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PROJECT 2: Ex Vivo Analysis of Coronavirus Tropism, Adaptation, Replication, and Host Response In this proposal, we hypothesize that multiple and discrete virus-host interactions and host responses to infection dictate the pathogenic outcome and host tropism of SARS-CoV-2. We further hypothesize that these critical circuits can be dissected through network-based modeling of system-level measurements offering the potential for the development of novel antiviral therapies. In Project 2, we propose to utilize leading edge OMICs- based measurements to define virus-host interactions and networks that control viral replication, viral tropism/adaptation and host responses across bat coronaviruses, SARS-CoV-1, and SARS-CoV-2 variants. In Aim 1, we will conduct proteomics (AP-MS, protein abundance and post-translational modifications), transcriptomics (RNA-seq and scRNA-seq), epigenomics (ATAC-seq, Hi-C and ChiP-seq) and genetic and chemical compound screens using ex vivo primary epithelial cells and iPSC-derived pneumocytes derived both from human and bats and a lung epithelial cell line (A549). In Aim 2, these data will be integrated and modeled with in vivo and clinical data collected in Project 1 using network-based predictive modeling approaches to identify host proteins, networks, and pathways that correlate with disease severity and host adaptation (‘driver genes’). Reiterative modeling of data generated in Aim 1 and Project 1 will be employed to refine these predictions. In Aim 3, CRISPR-editing approaches will be used in concert with targeted OMICs measurements (CRISPR-OMICs), including transcriptional, epigenetic, proteomic analyses, to validate the impact of these ‘driver genes’ on disease outcome and host tropism. Additional molecular, cellular, biochemical, and in vivo studies will be conducted to further characterize nodes that determine disease outcome as potential therapeutic targets. Overall, these studies will enable us to correlate in vivo and clinical biomarkers predictive of COVID-19 severity (Project 1) to specific genes and networks that impact viral infection, cellular host responses, and interspecies transmission.