Stochastic Individual-Based Modeling of Bacterial Growth and Division Using Flow Cytometry - García, Míriam R.; Vázquez, José A.; Teixeira, Isabel G.; Alonso, Antonio A. (Frontiers in Microbiology, 2018)
A realistic description of the variability in bacterial growth and division is critical to produce reliable predictions of safety risks along the food chain. Individual-based modelling of bacteria provides the theoretical framework to deal with this variability, but it requires information about the individual behaviour of bacteria inside populations. In this work, we overcome this problem by estimating the individual behaviour of bacteria from population statistics obtained with flow cytometry. For this objective, a stochastic individual-based modelling framework is defined based on standard assumptions during division and exponential growth. The unknown single-cell parameters required for running the individual-based modelling simulations, such as cell size growth rate, are estimated from the flow cytometry data. Instead of using directly the individual-based model, we make use of a modified Fokker-Plank equation. This only equation simulates the population statistics in function of the unknown single-cell parameters. We test the validity of the approach by modelling the growth and division of Pediococcus acidilactici within the exponential phase. Estimations reveal the statistics of cell growth and division using only data from flow cytometry at a given time. From the relationship between the mother and daughter volumes, we also predict that Pediococcus acidilactici divide into two successive parallel planes.