Seasonal H3N2 influenza virus evolves rapidly, readily accumulating mutations in the hemagglutinin (HA) surface protein. These mutations confer escape from host immunity and necessitate frequent vaccine updates. Current approaches for selecting a vaccine strain rely on characterizing the antigenic properties of circulating strains using the hemagglutination inhibition (HAI) assay. This is a low-throughput and labor- intensive process. Additionally, HAI assays use ferret sera, a surrogate which do not fully reflect the epitope- targeting of antibodies in human sera. Therefore, better strategies are needed to characterize the effects of mutations on antigenicity of HA. The proposed work will use high-throughput approaches to comprehensively profile antigenic selection on all single amino-acid mutants of a recent H3 HA. These high-resolution profiles will determine the extent by which mutations change antigenicity and thereby confer escape from host immunity. To establish an approach for immune selection, the first component of this proposal will involve creating diverse libraries of mutant viruses carrying all single amino-acid mutations of H3 HA, and imposing selection on the mutant viruses with a panel of human monoclonal antibodies. Accurate deep sequencing and computational analyses will quantify the frequency of every mutation from immune selection and an unselected control condition. These methods will enable comprehensive profiling of the effects of mutations on antibody escape. Next, the approach will be extended to polyclonal immune selection of the mutant virus libraries with ferret and human sera. In particular, human sera are expected to provide evolutionarily relevant measures of antigenic selection on hemagglutinin mutations. Finally, computational approaches will be used to forecast the evolutionary trajectories of circulating influenza strains based on the antigenic properties of these strains. This will allow an assessment of the accuracy of implementing ferret and human sera mutational antigenic profiles to characterize the antigenic properties and evolutionary trajectories of circulating strains. Overall, this work will provide insight into immune selection on mutations to H3 HA, and will facilitate more effective antigenic characterization that can inform selection of vaccine strains.
Understanding how mutations affect the antigenicity of seasonal influenza viruses is essential for identifying viral strains that can escape host immunity. This study will use high-throughput methods to comprehensively identify mutations to the HA of H3N2 influenza virus that enable escape from antibodies in sera. These results can be used to map changes in antigenicity, and will be useful for vaccine strain selection.
