Impact of multiple hurdles on Listeria monocytogenes dispersion of survivors.

Pathogen exposure to multiple hurdles could result in variation in the number of survivors, which needs to be carefully considered using appropriate regression models for dealing with survivor dispersion. The aim of this study was to evaluate the impact of the hurdles on the random component of the measured variation and on its unexplained part (over or under-dispersion) representing the departure from randomness, i.e. non-randomness, in survivors of a multi-strain mixture of L. monocytogenes. The pathogen inactivation curves were fitted to the Weibull model within the Conway-Maxwell-Poisson process. In all the 20 hurdle combinations, the surviving cells, whether they showed an upward curvature or linear kinetics, displayed the randomness revealed by the degree of dispersion of the inactivation parameters (-b and p). In 15 combinations, a significant dispersion coefficient (c0), which reflected the non-random component of variation was evident, denoting either over-dispersion (c0 > 0 in 13 combinations) or under-dispersion (c0 < 0 in 2 combinations). The observed dependence of the under- and over-dispersion conditions on the inactivation rate was confirmed by a Monte Carlo simulation based on the inactivation parameter -b. Including both randomness and non-randomness provides a more accurate estimation of survivors, which certainly impacts on intervention practices.

The COM-Poisson Process for Stochastic Modeling of Osmotic Inactivation Dynamics of Listeria monocytogenes.

Controlling harmful microorganisms, such as Listeria monocytogenes, can require reliable inactivation steps, including those providing conditions (e.g., using high salt content) in which the pathogen could be progressively inactivated. Exposure to osmotic stress could result, however, in variation in the number of survivors, which needs to be carefully considered through appropriate dispersion measures for its impact on intervention practices. Variation in the experimental observations is due to uncertainty and biological variability in the microbial response. The Poisson distribution is suitable for modeling the variation of equi-dispersed count data when the naturally occurring randomness in bacterial numbers it is assumed. However, violation of equi-dispersion is quite often evident, leading to over-dispersion, i.e., non-randomness. This article proposes a statistical modeling approach for describing variation in osmotic inactivation of L. monocytogenes Scott A at different initial cell levels. The change of survivors over inactivation time was described as an exponential function in both the Poisson and in the Conway-Maxwell Poisson (COM-Poisson) processes, with the latter dealing with over-dispersion through a dispersion parameter. This parameter was modeled to describe the occurrence of non-randomness in the population distribution, even the one emerging with the osmotic treatment. The results revealed that the contribution of randomness to the total variance was dominant only on the lower-count survivors, while at higher counts the non-randomness contribution to the variance was shown to increase the total variance above the Poisson distribution. When the inactivation model was compared with random numbers generated in computer simulation, a good concordance between the experimental and the modeled data was obtained in the COM-Poisson process.

Involvement of alanine racemase in germination of Bacillus cereus spores lacking an intact exosporium.

The L-alanine mediated germination of food isolated Bacillus cereus DSA 1 spores, which lacked an intact exosporium, increased in the presence of D-cycloserine (DCS), which is an alanine racemase (Alr) inhibitor, reflecting the activity of the Alr enzyme, capable of converting L-alanine to the germination inhibitor D-alanine. Proteomic analysis of the alkaline extracts of the spore proteins, which include exosporium and coat proteins, confirmed that Alr was present in the B. cereus DSA 1 spores and matched to that encoded by B. cereus ATCC 14579, whose spore germination was strongly affected by the block of conversion of L- to D-alanine. Unlike ATCC 14579 spores, L-alanine germination of B. cereus DSA 1 spores was not affected by the preincubation with DCS, suggesting a lack of restriction in the reactant accessibility.

Survival strategies of Bacillus spores in food.

Control of bacterial spores is one of the major problem in the food preservation. Spores of Bacillus genus are commonly present in different environments, including soil and the gut of insects and animals and, as a result, they can be spread to all kind of foods. Due to their high resistance properties, their complete inactivation in food is often impossible without changing the product characteristics. Surviving spores can germinate and grow out to vegetative cells, with the consequent great risk of food spoilage and food poisoning after consumption. Spores have evolved various mechanisms, including phenotypic variability, to protect themselves from a wide range of damage resulting from food preservation treatments. Even if the phenotypic heterogeneity contributes to increase the chances of survival of Bacillus spore to conventional preservation treatments, in some specific instances, an homogeneous response could be the result of a strategy adopted by the spores to increase resistance to those treatments.

A simplified approach for modelling the bacterial growth/no growth boundary.

A simplified growth/no growth (G/NG) model, conceptually derived from the Gamma model and making direct and explicit use of growth limits of bacteria through a normalization constant (η), was proposed. The η value, which quantifies the product of the cardinal optimal distances for growth probability, is a species-independent constant. This is of importance when experimental data is missing or insufficient. The simplified G/NG model was developed including the effect of temperature, pH and water activity, and was expanded incorporating the preservative effects. As a practical application, the model was investigated for its ability to describe published data. The successful validation of the simplified G/NG model is discussed in regard to its potential applicability as a first estimate method for the development of safe food products.

Glassy state in Bacillus subtilis spores analyzed by differential scanning calorimetry.

Thermal properties of dried spores of Bacillus subtilis, investigated by differential scanning calorimetry (DSC), were studied. A reversible heat capacity shift ascribable to glass-rubber transition was observed at 90-115 degrees C. The transition was found to be a pressure-inhibited volume-activated event. The decoated spores and the extracted peptidoglycan material exhibited glass transition, suggesting that the cortex could be involved in the event. Furthermore, the glass transition was evident when spores were treated with strong acid, and when the isogenic strain PS578 was scanned, indicating that core integrity and core components are not involved in the occurrence of the event. These results suggest that in the dried B. subtilis spores an amorphous biomaterial, possibly the cortex peptidoglycan, is present as a glass.

Growth of Listeria monocytogenes as influenced by viscosity and water activity.

The effects of osmotic stress on Listeria monocytogenes growth parameters was examined in relation to the viscosity of the growth media. In low-viscosity systems, growth of L. monocytogenes in glucose-supplemented media was comparable to growth in sucrose-supplemented media. The relative lag time (RLT: the lag time divided by the generation time) responses were found to increase in the more restrictive water activity conditions. In high-viscosity systems containing polyvinylpyrrolidone (PVP), growth rate was reduced, whereas lag time showed no discernible modification. Osmotic stress in medium- and high-viscosity media supplemented with glucose resulted in approximately exponential increasing of the RLT values. Thus, the biological effects of osmotic stress on L. monocytogenes could be affected by the physical properties of the system, such as viscosity and diffusivity.