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Modelling the invasion of human small intestinal epithelial‐like cells by Salmonella enterica Typhimurium and Listeria monocytogenes using Bayesian inference

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To develop a mechanistic bacterial dose–response model, based on the concept of Key Events Dose–Response Framework (KEDRF), this study aimed to investigate the invasion of intestinal model cells (Caco‐2) by… Click to show full abstract

To develop a mechanistic bacterial dose–response model, based on the concept of Key Events Dose–Response Framework (KEDRF), this study aimed to investigate the invasion of intestinal model cells (Caco‐2) by Salmonella Typhimurium and Listeria monocytogenes and described the behaviour of both pathogens as a mathematical model using Bayesian inference. Monolayer‐cultured Caco‐2 cells (approximately 105 cells) were co‐cultured with various concentrations (103–107 colony forming unit [CFU] ml−1) of Salm. Typhimurium and L. monocytogenes for up to 9 h to investigate the invasion of the pathogens into the Caco‐2 cells. While an exposure of ≥103 CFU ml−1 of Salm. Typhimurium initiated the invasion of Caco‐2 cells within 3 h, much less exposure (102 CFU ml−1) of L. monocytogenes was sufficient for invasion within the same period. Furthermore, while the maximum number of invading Salm. Typhimurium cells reached by approximately 103 CFU cm−2 for 6‐h exposure, the invading maximum numbers of L. monocytogenes cells increased by approximately 106 CFU cm−2 for the same exposure period. The invasion kinetics of both the pathogens was successfully described as an asymptotic exponential mathematical model using Bayesian inference. The developed pathogen invasion model allowed the estimation of probability of Salm. Typhimurium and L. monocytogenes infection, based on the physiological natures of digestion process, which was comparable to the published dose–response relationship. The invasion models developed in the present study will play a key role in the development of an alternative pathogen dose–response model based on KEDRF concept.

Keywords: using bayesian; bayesian inference; invasion; model; typhimurium

Journal Title: Letters in Applied Microbiology
Year Published: 2022

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