A Computational Model of Bacterial Population Dynamics in Gastrointestinal Yersinia enterocolitica Infections in Mice.
Autenrieth, Ingo B
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Geißert, J. K., Bohn, E., Mostolizadeh, R., Dräger, A., Autenrieth, I. B., Beier, S., Deusch, O., et al. (2022). A Computational Model of Bacterial Population Dynamics in Gastrointestinal Yersinia enterocolitica Infections in Mice.. Biology (Basel), 11 (2) https://doi.org/10.3390/biology11020297
The complex interplay of a pathogen with its virulence and fitness factors, the host's immune response, and the endogenous microbiome determine the course and outcome of gastrointestinal infection. The expansion of a pathogen within the gastrointestinal tract implies an increased risk of developing severe systemic infections, especially in dysbiotic or immunocompromised individuals. We developed a mechanistic computational model that calculates and simulates such scenarios, based on an ordinary differential equation system, to explain the bacterial population dynamics during gastrointestinal infection. For implementing the model and estimating its parameters, oral mouse infection experiments with the enteropathogen, Yersinia enterocolitica (Ye), were carried out. Our model accounts for specific pathogen characteristics and is intended to reflect scenarios where colonization resistance, mediated by the endogenous microbiome, is lacking, or where the immune response is partially impaired. Fitting our data from experimental mouse infections, we can justify our model setup and deduce cues for further model improvement. The model is freely available, in SBML format, from the BioModels Database under the accession number MODEL2002070001.
infection, systems biology, computational modeling, population dynamics, gastrointestinal infection, ordinary differential equations, parameter estimation, Yersinia enterocolitica
Deutsche Forschungsgemeinschaft (AU 102/16-1, EXC 2124–390838134)
German Center for Infection Research (8020708703)
Federal Ministry of Education and Research (031 A535A)
External DOI: https://doi.org/10.3390/biology11020297
This record's URL: https://www.repository.cam.ac.uk/handle/1810/333987