In the last several years, a large number of studies have produced significant insights into influenza A virus, making it one of the best studied human pathogens. Nevertheless, we are still far from a complete understanding of influenza virus infection dynamics. For instance, we have only begun to unravel the various drivers that impact the markedly different morbidity and mortality observed among infections with different virus strains. While important genetic factors have been noted, it is clear that these genes interact with the host in a complicated, nonlinear and dynamical way to generate the overall observed phenotype. It is therefore crucial to understand in a detailed, quantitative manner the kinetic characteristics of diverse virus-host interactions. Carefully controlled experiments, in conjunction with mathematical and computational approaches, are a promising strategy for disentangling the many components that are part of the infection dynamics, and for producing insights into how various mechanisms interact to produce emergent properties of such a complex system. Here, we plan to follow such an integrated experimental and mathematical modeling program to quantify the interactions of different influenza A virus strains with various host target cells and components of the host cell innate response. Our central hypothesis is that differences between virus strains can be quantified by measuring the dynamical interactions between virus, target cells and host responses. These interactions lead to variations in the infection dynamics, which in turn determine overall traits such as morbidity and mortality. Since our level of knowledge and our experimental and computational tools are currently still too limited to successfully tackle this problem in vivo, we will address this hypothesis through a thorough and comprehensive study of influenza A infection dynamics using in vitro experiments and in silico computational modeling. We will use two approaches: A disseminated, population-level approach will allow us to study the dynamics of the infected culture in total, and a spatially explicit, individual-level approach that localizes the infection and associated response. The complementary nature of the two approaches allows for a much more thorough quantification of the infection dynamics. Our interdisciplinary, comprehensive multi-scale approach will provide with unprecedented, detailed information of the viral and host factors determining overall influenza A infection dynamics. This knowledge is crucial for unraveling the complex interactions between virus and host that lead to compound phenotypes such as mortality and morbidity. This in turn will have direct bearing on improved design of treatment strategies and is an important stepping stone toward a comprehensive investigation of in vivo infection.
Influenza A is an important pathogen for human health. Different influenza strains lead to striking differences in morbidity and mortality. The reason for those differences is not well known. Our proposed project will investigate the drivers that lead to the observed differences in morbidity and mortality. The information obtained from this project will be important for the design of novel treatment strategies.
