Quantifying and Validating Immune Response Dynamics for Influenza and Viral-Bacterial Pneumonias

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Project Summary Influenza A virus (IAV) and secondary bacterial infections (SBI) are responsible for a significant number of illnesses and deaths each year. Management of these diseases is difficult, in part due to a lack of understanding of complex interplay of host-pathogen interactions. To advance the goal of developing effective therapeutics, new microbiologic tools that can assess how host immune responses work to limit viral burden and enhance bacterial invasion quantitative detail is essential. This grant aims to address the gap in biological knowledge of IAV and SBIs by exploiting predictive mathematical models that are calibrated and subsequently validated with quantitative experimental data. The proposed studies integrate rigorous kinetic modeling with targeted experimental studies to: (1) quantify the killing of virus-infected cells to explain a plateau-shaped viral peak and a rapid viral decline, and determine if the killing is density dependent and how CD8+ T cells contribute to viral decay; (2) quantify the production of IFN-α/βs from epithelial cells and immune cells during influenza to explain a double peak in IFN-β and a sustained plateau of IFN-α, and determine how they function to limit virus infection; (3) identify how AMs become depleted during influenza by quantifying their decay, and determine how viral loads and SBIs are altered by the loss of these cells. In each of these studies, we will develop and analyze mechanistic mathematical models together with quantitative infection data, test specific model predictions experimentally, and use the generated data to refine and extend the models. This iterative model-driven experimental approach will result in a detailed and quantitative understanding of the immune responses to influenza and how these contribute to viral-bacterial coinfection pathogenicity. This investigative approach is key to understanding the complex feedbacks in immune responses and in viral-bacterial interactions and reveal new targets for treatment and prevention of influenza and related bacterial infections.