Developing live cell, super-resolution imaging of virus infection at scale

My research will combine my expertise in live-cell, high-content microscopy to develop and advance imaging and analysis platforms to investigate the spatiotemporal regulation of the intracellular lifecycle of individual viral particles. I will use this to provide key mechanistic insights into HIV infection of human primary CD4+ T-cells and determine how the virus hijacks the host cell machinery to drive successful infection. Key goals are: - Advance high-content, super-resolution, live-cell imaging and deep learning analysis to track the molecular phenotypes associated with successful virus infection of cells at a population scale. - Dissect the cell biology of key stages of the HIV viral life cycle at single-particle resolution (entry, uncoating, nuclear import) in primary T-cells, mapping the kinetics and contributions of molecular interactions between virus and host cell cofactors. - Determine the cell biology dynamics that underpin heterogeneity in infection outcome and molecular determinants of host cell permissivity. By pioneering the use of super-resolution microscopy and machine learning to investigate the cell biology of virus infection at the single-virion and single-cell level I will deliver an integrated mechanistic model of the relationship between molecular virus-host interactions and infection outcomes. Exploiting HIV as a paradigm virus, I will innovate approaches transferable to other viruses.