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

Abstract

Salmonella 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 Salmonella 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 Salmonella 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 Salmonella infection success can be forecast from morphological or molecular host cell parameters.

Keywords: Salmonella enterica serovar Typhimurium; cell vulnerability; cooperative behavior; mathematical modeling; single-cell heterogeneity.