@article{Geissert2022,
  author   = {Gei{\ss}ert, Janina K. and Bohn, Erwin and Mostolizadeh, Reihaneh and
    Dr\"ager, Andreas and Autenrieth, Ingo B. and Beier, Sina and Deusch, Oliver and
    Renz, Alina and Eichner, Martin and Sch\"utz, Monika S.},
  title    = {{A Computational Model of Bacterial Population Dynamics in Gastrointestinal
    \emph{Yersinia enterocolitica} Infections in Mice}},
  journal  = {Biology},
  volume   = {11},
  year     = {2022},
  month    = feb,
  number   = {2},
  issue    = {297},
  publisher= {Multidisciplinary Digital Publishing Institute},
  url      = {https://www.mdpi.com/2079-7737/11/2/297},
  issn     = {2079-7737},
  doi      = {10.3390/biology11020297},
  pdf      = {https://www.mdpi.com/2079-7737/11/2/297/pdf},
  pmid     = {35205164},
  abstract = {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.},
}