Bacteria have evolved numerous defence strategies to survive in adverse environments and, over the years, increasingly sophisticated mechanisms have been discovered (Brauner et al., 2016; Ciofu et al., 2022). Although, individually, bacteria may appear to be fragile organisms, as a population they are able to adapt rapidly through specific and coordinated genotypic and phenotypic changes (Ayrapetyan et al., 2018). One of the most fascinating survival strategies, whose mechanisms are still not fully understood, concerns the ability of bacteria to enter a state of dormancy (Arvaniti and Skandamis, 2022). Bacteria spend most of their life in a state of low metabolic activity with little or no growth, but they are able to resume active replication when the environmental conditions permit (Ayrapetyan et al., 2018; Mu et al., 2021).

Bacterial persistence is one of the dormancy states that has aroused great interest from the scientific community. 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 (Kaplan et al., 2021). In this regard, the hallmark of persistent bacteria is the biphasic killing curve, a sign that, within a microbial population, there are two subpopulations inactivated at different rates (Balaban et al., 2019). When transferred into a fresh medium, persistent cells still have the metabolic competencies to resume active replication although they spend more time adapting to the new conditions remaining in the lag phase longer (Balaban et al., 2004; Brauner et al., 2016). Therefore, exploring the lag time distribution at the single-cell level can allow determining the fraction of persistent cells in a bacterial population (Levin-Reisman and Balaban, 2016).

Persistent bacteria stochastically originate in a bacterial population in response to environmental stressors or spontaneously without external signals following overexpression of genes encoding specific toxin-antitoxin systems that seem to play a key role in decreasing microbial metabolism (Balaban et al., 2019; Curtis et al., 2017; Fisher et al., 2017). This phenomenon should not be intended as on/off switch but rather a concerted process between all the cells of the population that dynamically and stochastically evolves over time (Ayrapetyan et al., 2018). The stochastic nature of several biological phenomena has been widely explored since it is well-recognized that natural systems are a typical example of open systems where the continuous occurrence of deterministic and stochastic forces affect the population dynamics (Spagnolo et al., 2022). Particularly, the random fluctuations of intrinsic or extrinsic parameters, defined as “noise”, have been studied in order to understand the stability of ecological systems showing the presence of counterintuitive phenomena (Spagnolo et al., 2015). The application of stochastic predictive models has been recently proposed to the food microbial systems to understand the complexity of the interactions among environmental parameter fluctuations and bacterial behaviour (Ciofu et al., 2022; Giarratana et al., 2022). However, the role of “intrinsic noise” on the formation of microbial persistence appears to be a still unexplored field.

What is most worrying about persistent cells is their ability to elude bactericidal treatments that are normally able to inactivate them (Defraine et al., 2018). There is evidence that persistent bacteria can tolerate high doses of bactericidal drugs and can survive lethal levels of pH, osmotic conditions and heat treatments (Manina et al., 2015; Nabone et al., 2023). This major resistance seems to be related to adaptive responses involving not inheritable metabolic and structural changes that induce cross-protection against different bactericidal treatments (Dewachter et al., 2019; Harms et al., 2016).

On this background, persistent bacteria raise concerns also about food safety since the most common preservation techniques (refrigeration, freezing, salting, drying, etc.) may act as stressors that trigger the formation of persistent bacteria able to survive subsequent bactericidal treatments and grow later in foods during storage. In this regard, in our recent study, we observed that Listeria monocytogenes grown in broth with additional 6 % NaCl survived longer when exposed to heat treatment at 51 °C due to the formation of persistent cells characterized by a longer lag phase (Nalbone et al., 2023). The greater heat resistance observed after the growth in a saline environment suggested the formation of a subpopulation of persistent rather than stressed cells which, instead, would have been more sensitive to bactericidal heat treatment.

Persistent bacteria have been 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 (Eisenreich et al., 2022).

This study aimed to investigate a possible relationship between exposure to different salt concentrations (osmotic stress) and the amount of persistent cells triggered in a strain of L. monocytogenes. Furthermore, to provide further insight into the dynamics of persistence, we describe this phenomenon from a mathematical perspective through predictive microbiology models commonly used to reproduce the growth curves of bacterial populations in the food field.