The key elements required for the development of protective immunity and the maintenance of immune homeostasis in the lung are largely unknown. The lung is a dynamic environment composed of resident cells (i.e. epithelial and endothelial cell types) and immune cells (resident and infiltrating). The goal of the proposed U19 Center is to unravel how the functions of these resident and migratory cells are dynamically coordinated to respond to infection by respiratory pathogens. We proposed to examine this dynamic lung response to influenza A virus (IAV) infection and to develop multiscale, computational-based predictive immunological models of the human pulmonary immune response to IAV infection. The underlying hypothesis of our proposed U19 Center is that immune response to IAV infection is an emergent property from many cell types, host processes, and pathogen interference, starting with resident innate immune cells and lung infection site microenvironment. Thus, clinical outcome and long-term immunity results from complex cellular and molecular interactions among pathogen, cells and cytokines. Critical to the success of the program's goals is access to wild-type and recombinant influenza viruses with well-characterized genetic and phenotypic differences that are necessary to study the pulmonary immune response to virus infection. The broad, long-range activities and services of the proposed Core B (Virology) are to establish working stocks of wild-type and recombinant influenza viruses for use by Projects I and II. In addition to providing critical viral reagents, Core B also relates to the experimental (Projects I and II) and computational (Project III) studies by receiving feedback in the form of modeling and transcriptional data that the Virology core will then utilize to develop novel recombinant influenza viruses that encode mutations within motifs mediating protein-protein interactions or post- translational modifications for use by Projects I and II in experiments that will test and refine the networks suggested by the multiscale, computational-based predictive models.
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