Development of an interactive online tool for genome sequence-based influenza vaccine strain selection
Seasonal influenza viruses in humans infect approximately 5 [percent] to 15 [percent] of the population and cause an estimated half-million deaths worldwide per year. Among the four co-circulating seasonal influenza viruses, subtype H3N2 and H1N1 influenza A viruses have rapid mutations and frequent antigenic drift events, leading to frequent updates of vaccine strains in the seasonal influenza vaccine. Seasonal influenza vaccination is the primary option to prevent and control influenza epidemics, and the selection of an antigenic matched vaccine strain is one of the keys to the success of seasonal influenza vaccination. Thus, it is critical to have robust and rapid antigenic analyses of epidemic strains and estimates of their genetic and antigenic relationship with the vaccine strain in use. In this study, we present vaccineEvol, an interactive and user-friendly web visualization tool that allows researchers to comprehend large sequence datasets into antigenic and genetic analyses. With the integration of the genomic sequences from the public database, the tool enables the users to track and analyze both genetic and antigenic evolutionary dynamics of seasonal influenza viruses. Primarily, our application can quantify both genetic and antigenic distances among seasonal H3N2 influenza A viruses and display genetic and antigenic variants using phylogenetic tree and antigenic cartography, respectively. The users can also interactively analyze genetic and antigenic variants between the phylogenetic tree and antigenic cartography. The application performs machine learning based computations in the backend, which was previously developed in our lab, and efficient construction of trees and maps in the frontend. In summary, in this study, an interactive web server was developed for rapid antigenic and genetic analyses of seasonal influenza viruses and thus facilitate seasonal influenza vaccine strain selection.