(190bq) Spatial and Temporal Imaging Reveals Single-Cell Heterogeneity during Virus Growth and Infection Spread
AIChE Annual Meeting
Monday, October 29, 2018 - 3:30pm to 5:00pm
The progress of a viral infection within a human host may cause mild or severe disease depending on the behavior of the earliest infected cells. For respiratory infections, where very few cells are initially infected, significant heterogeneity in phenotypes of infected cells reflect in part differences in cellular physiology, which can be studied using image-based measurements. As a model system, we used HeLa cells and a human rhinovirus (HRV) strain engineered to express green fluorescent protein (GFP) to analyze the heterogeneity in viral gene expression during infection spread in culture. Fluorescent signal was tracked over both time and space by live-cell imaging, and kinetic parameters of viral gene expression were measured based on reporter expression at single-cell resolution. The heterogeneity in parameters describing cellular morphology can reflect the fitness of the cells, and may be used to predict the susceptibility of the cells to infection. The susceptibility of healthy cells at or near the leading edge of infection spread determine the extent to which infection continues to spread or terminates. Our findings provide an example of single-cell heterogeneity affecting the outcomes of infection spread. Such observations may have correlates with infections in humans and ultimately with the severity of disease.