Genomic profiling of influenza infections to identify biomarkers of disease severity

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This project sets out to use an integrative systems-level approach to discover how obesity affects (a) the evolution and transmission of influenza virus, (b) specific host responses to infection, and (c) microbial communities in the respiratory tract, to reveal key signatures that could be targeted in novel therapeutics. Obese people and animals have delayed viral clearance, which can impact the complex interactions between virus, bacteria, and the host. These interactions involve many effector mechanisms. For example, influenza A virus infection was shown to alter bacterial adhesions and TLR expression on epithelial cells, increasing susceptibility of the lungs to secondary bacterial pneumonia. The initial phase of this study has focused on developing methods for effective analyses of the metagenome and metatranscriptome from nasopharyngeal swabs to characterize the functional gene potential and activity of the microbial community. We will perform similar analyses in the obese ferret model. In support of the proposed studies, our previous analyses of nasal washes from ferrets infected with H1N1pdm2009 demonstrated a significant change in the respiratory microbiome. In a network analysis of microbial interactions before and after infection, we observe a clear change of the microbial dynamics. We will also model the evolution of the viruslooking at intra-host and inter-host virus genetic diversityover the course of the infection. Recently our focus has been on defective virus genomes (DVGs) as certain defective genomes are thought to modulate disease severity and pathogenicity of the influenza infection. We also aim to analyze the host systemic response to infection by transcriptomic profiling using whole blood and glycomic profiling using serum. After multiscale analyses, we will compare the key drivers of disease severity in obese ferrets and obese humans, and integrate data across both systems (human and ferret) to determine if other drivers are identified.