Mapping the complete influenza A virus infection cycle through single vRNP imaging

Abstract Cell-to-cell heterogeneity is a common feature of viral infection that can generate enormous complexity, complicating understanding of infection progression and interpretation of differences between viral variants. To overcome these challenges, we developed a technology to visualize the infection cycle of human influenza A virus (IAV) from start-to-finish in individual living cells with unprecedented spatial and temporal resolution, which identified numerous distinct pathways through which infection can progress. We show that heterogeneous viral gene expression drives infection cycle heterogeneity, and identified genome packaging, vRNP transcriptional activation and host cell division as major determinants of gene expression variability. Our work maps out the complete IAV infection cycle, identifies the origin of infection heterogeneity and provides a broadly-applicable technology for studying IAV and other viruses.