Abstract：
:Traditional predictive microbiology is not suited for cell growth predictions for low-level contamination, where individual cell heterogeneity becomes apparent. Accordingly, we simulated a stochastic birth process of bacteria population using kinetic parameters. We predicted the variation in behavior of Salmonella enterica serovar Typhimurium cells at low inoculum density. The modeled cells were grown in tryptic soy broth at 25 °C. Kinetic growth parameters were first determined empirically for an initial cell number of 104 cells. Monte Carlo simulation based on the growth kinetics and Poisson distribution for different initial cell numbers predicted the results of 50 replicate growth experiments with the initial cell number of 1, 10, and 64 cells. Indeed, measured behavior of 85% cells fell within the 95% prediction area of the simulation. The calculations link the kinetic and stochastic birth process with Poisson distribution. The developed model can be used to calculate the probability distribution of population size for exposure assessment and for the evaluation of a probability that a pathogen would exceed critical contamination level during food storage.
journal_name
J Theor Bioljournal_title
Journal of theoretical biologyauthors
Koyama K,Hiura S,Abe H,Koseki Sdoi
10.1016/j.jtbi.2021.110758keywords:
["Exponential distribution","Pure birth process","Time between division of a cell","Variability"]subject
Has Abstractpub_date
2021-09-21 00:00:00pages
110758eissn
0022-5193issn
1095-8541pii
S0022-5193(21)00180-6journal_volume
525pub_type
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