Identification of Parameters of Host Cell Vulnerability during Salmonella Infection by Quantitative Image Analysis and Modeling

Abstract

<i>Salmonella</i> targets and enters epithelial cells at permissive entry sites: some cells are more likely to be infected than others. However, the parameters that lead to host cell heterogeneity are not known. Here, we quantitatively characterized host cell vulnerability to <i>Salmonella</i> infection based on imaged parameters. We performed successive infections of the same host cell population followed by automated high-throughput microscopy and observed that infected cells have a higher probability of being reinfected. Establishing a predictive model, we identified two combined origins of host cell vulnerability: pathogen-induced cellular vulnerability emerging from <i>Salmonella</i> uptake and persisting at later stages of the infection and host cell-inherent vulnerability. We linked the host cell-inherent vulnerability with its morphological attributes, such as local cell crowding, and with host cell cholesterol content. This showed that the probability of <i>Salmonella</i> infection success can be forecast from morphological or molecular host cell parameters.