A stochastic approach for modelling the in-vitro effect of osmotic stress on growth dynamics and persistent cell formation in Listeria monocytogenes

Persistent bacteria (or persisters) can be defined as a microbial subpopulation that, exposed to bactericidal treatment, is killed more slowly than the rest of the population they are part of. They stochastically originate in response to environmental stressors or spontaneously without external signals. When transferred into a fresh medium, persisters can resume active replication although they spend more time adapting to the new conditions remaining in the lag phase longer. They were studied for decades for their ability to survive antibiotic treatments while studies on their formation in food and potential impact on their safety are lacking. The most common food preservation techniques may act as stressors that trigger the formation of persistent bacteria able to survive bactericidal treatments and grow later in foods during storage. This study aimed to investigate a possible relationship between exposure to different salt concentrations (osmotic stress) and the amount of persisters triggered in a strain of Listeria monocytogenes. Furthermore, we described this phenomenon from a mathematical perspective through predictive microbiology models commonly used in the food field. The lag time distribution of a L. monocytogenes ATCC 7644 strain grown in broth with additional 2 %, 4 % and 6 % NaCl was evaluated using the software ScanLag. It uses office scanners to automatically record the colony growth on agar plates and evaluate the frequency distribution of their appearance times (lag phase) by automated image analysis. The same broth cultures were diluted to equalize salt concentration and transferred into a fresh broth to evaluate how the previous salt exposure impacted their growth kinetics. The observed growth curves were reproduced using predictive models in which the mean duration of the lag phase of the whole population took into account the occurrence of persisters with a longer lag phase. The models were solved first using a deterministic approach and then a stochastic one introducing a stochastic term that mimics the variability of lag phase duration due to the persisters occurrence. Results showed that the growth of L. monocytogenes in broth with additional NaCl might trigger the formation of persistent cells whose number increased consistently with salt concentrations. The proposed predictive approach reproduced the observed real curves in strong agreement, especially through the stochastic resolution of the models. Persistence is currently a neglected bacterial defence strategy in the food sector but the persisters’ formation during production cannot be excluded; therefore, further insights on the topic are certainly desirable.