Assessing the relevance of different sources of variability on the survival of foodborne pathogensstress adaptation against genetic heterogeneities
- GEORGALIS, LEONIDAS
- Alberto Garre Pérez Director
- Pablo Salvador Fernández Escámez Codirector
- Anna Psaroulaki Codirector/a
Universidad de defensa: Universidad Politécnica de Cartagena
Fecha de defensa: 05 de julio de 2023
- Alfredo Palop Gómez Presidente
- Arícia Mara Melo Possas Secretario/a
- Dimosthenis Chochlakis Vocal
Tipo: Tesis
Resumen
Microbial risk assessment is crucial for protecting public health and the food supply chain. Sources of variability in microorganisms, such as stress adaptation and genetic heterogeneities, can affect the survival, growth and virulence of microorganisms, and their ability to cause disease or food spoilage. There are currently large knowledge gaps regarding variability of the microbial response, and understanding it is essential for accurately estimating potential risks and to develop effective control measures. In light of this, this PhD thesis aims to compare and evaluate the importance of stress adaptation and genetic heterogeneities in microorganisms for the survival of bacteria to thermal treatments. Chapter I discusses the thermal inactivation of two Salmonella strains (Salmonella Enteritidis CECT4300 and Salmonella Senftenberg CECT4565) under both isothermal and dynamic conditions. For isothermal treatments, S. Senftenberg was found to be much more resistant than S. Enteritidis (by approximately a factor of 10). We also observed qualitative differences, with the inactivation models used to describe the response of S. Senftenberg were weibullian, while the Bigelow model was successful in describing the isothermal response of S. Enteritidis. Models based on isothermal experiments were able to describe dynamic inactivation of S. Senftenberg, while S. Enteritidis required a dynamic model that considered stress acclimation. The study highlights that, besides quantitative, variability in microbial inactivation is also qualitative. This underlies importance of considering different model hypotheses for both isothermal and dynamic conditions. Chapter II goes further in the thermal inactivation of Salmonella spp. focusing on the importance of phenotypic variability in microbial risk assessment, which refers to the physiological differences of cells of the same bacterial species due to prior exposure to different environments. The impact of sub-optimal pre-culture conditions or the application of an acid shock on the thermal resistance of the same two Salmonella strains was studied, founding that phenotypic variability is also strain-dependent. For the highly resistant strain (S. Senftenberg), the conditions tested resulted in a reduction of thermal resistance with respect to optimal incubation conditions. On the other hand, sub-optimal incubation conditions had the opposite effect on the reference strain (S. Enteritidis), increasing its thermal resistance through the induction of cross-resistance mechanisms. The study suggests that phenotypic variability should be a main focus in predictive microbiology and risk assessment, and illustrates a hypothetical example of how this could be achieved in practice by linking pre-incubation conditions to the origin of bacterial contamination. Chapter III uses a common model organism (Bacillus subtilis) to further study the differences between isothermal and dynamic bacterial inactivation. To link differences in the response to molecular mechanisms, experiments were made using both a wild type strain and a marker-free sigB null mutant. Survivor curves with an upward curvature were observed, which is often attributed to heterogeneity in thermal resistance (vitalistic hypothesis). However, a pretreatment resulted in log-linear survivor curves, indicating dynamic stress adaptation during the isothermal treatment as a possible explanation for the upward curvature. Based on this hypothesis, bounds were defined based on isothermal experiments to account for acclimation under dynamic conditions. The study provides an alternative interpretation for survivor curves, which can improve predictions of microbial response during pasteurization treatments.