Synergistic interaction between pH and NaCl in the limits of germination and outgrowth of Clostridium sporogenes and Group I Clostridium botulinum vegetative cells and spores after heat treatment.

Group I Clostridium botulinum and Clostridium sporogenes are physiologically and genetically closely related. Both are widely distributed in the environment and can cause foodborne botulism. In this work, a physiological study was conducted with 37 isolates from spoiled canned food and five referenced strains of C. sporogenes (three isolates) and Group I C. botulinum (two isolates). Growth limits of vegetative cells were established as a function of pH and NaCl concentration in PYG modified medium (PYGm) at 30 °C for 48 days. The heat resistance of the spores was studied for 2 min and 10 min at 102 °C and 110 °C. This physiological study (pH, NaCl growth limits and heat resistance) allowed the selection of 14 isolates of C. sporogenes (twelve isolates) and Group I C. botulinum (two isolates) representative of the diversity found. This panel of 14 selected isolates (11 isolated from spoiled canned food and three reference strains), were whole genome sequenced, but no association of physiological and genetic characteristics could be detected. Finally, we studied the ability of spores to germinate and grow from 5 isolates (four C. sporogenes and one Group I C. botulinum), under stress conditions generated by pH and NaCl following a low intensity heat treatment. The accumulation of these 3 stresses creates synergies that will strongly reduce the probability of spore growth in pH and salt conditions where they usually proliferate. The effect is progressive as the conditions become drastic: the number of decimal reduction observed increases translating a probability of growth which decreases. This study provides a better understanding of the behaviour of C. sporogenes and Group I C. botulinum isolates and shows how the combination of pH, NaCl and heat treatment can help prevent or minimise foodborne botulism outbreaks.

Shelf-life boundaries of Listeria monocytogenes in cold smoked salmon during refrigerated storage and temperature abuse.

Cold smoked salmon (CSS) is a high-value ready-to-eat product, but it generally has a short shelf-life even under refrigeration and can support the growth of Listeria monocytogenes. Therefore, the objective of this study was to examine the growth and survival of L. monocytogenes in CSS during refrigerated storage and temperature abuse. The growth and survival data of L. monocytogenes (116 records, 465 data points) were retrieved from ComBase (https://www.combase.cc). All records contained storage time and temperature, but other information (aw, pH, and salt) was not fully documented. Each data point, normalized with the initial population to calculate relative growth (RG, log CFU/g), was used to classify the probability of growth. Eighty percent (80%) of the data were randomly sampled for examining the effect of storage time and temperature on growth of L. monocytogenes, while the remaining 20% were set aside for model validation. Logistic regression was used to develop a model for classifying L. monocytogenes growth according to 7 different control thresholds (CT), ranging from 0 to 3 log CFU/g in RG. A probability threshold was set to judge if the bacterial growth has exceeded a CT. The validation showed > 89% of true negative rate for not exceeding the control thresholds. A dynamic method was then developed and demonstrated to predict the growth probabilities under fluctuating temperature conditions. The result of this study suggested that storage time and temperature could be used to predict the growth of L. monocytogenes in CSS and to control listeriosis using a risk-based strategy. It can be used by the retailers and consumers to determine if a packaged product is safe to consume based on its time and temperature history.

Growth and No-Growth boundary of Listeria monocytogenes in beef - A logistic modeling.

Listeria monocytogenes is a potentially fatal foodborne pathogen. Its growth in ready-to-eat (RTE) foods must be strictly controlled to protect public food safety. This study was conducted to define the growth and no-growth boundary of L. monocytogenes with sodium tripolyphosphate (STPP), sodium lactate (NaL), sodium diacetate (NaDiAc), sodium chloride (NaCl), sodium nitrite (NaNO2), and pH as control factors. The growth of L. monocytogenes was first examined using a solid medium incubated under 37 °C for 48 h in 96-well microtiter plates. NaNO2 (1,800 ppm) and NaDiAc (2,500 ppm) were found not effective in preventing the growth when applied alone. STPP was shown highly effective in preventing the growth of L. monocytogenes. Its growth was unhindered at pH 6-7 but was increasingly inhibited beyond the neutral range. High concentrations of NaL and NaCl were needed to inhibit the growth of L. monocytogenes. A multifactor logistic regression model (LRM) was developed to calculate the growth probability (p) and then define the growth boundary using 2 thresholds. With Threshold 1 (p = 0.0104), the Accuracy of classification for growth events is 0.686, with a True positive rate (TPR) of 0.776 (or False negative rate (FNR) of 0.234), True negative rate (TNR) of 0.455 (or False positive rate (FPR) of 0.545), and Precision of 0.803, in PALCAM agar. However, with Threshold 2 (p = 0.04), the Accuracy becomes 0.826, with a TPR of 0.955 (or FNR of 0.045), a TNR of 0.690 (or FPR of 0.310), and Precision of 0.764. For validation in ground beef, the Accuracy of prediction of growth was 0.85, with a TPR of 0.9, TNR of 0.8, and Precision of 0.818 for Threshold 1. With Threshold 2, the Accuracy, TPR, TNR, and Precision are all 0.8, with both FNR and FPR of 0.2. Both thresholds and LRM may be used to formulate RTE products that may prevent the growth of L. monocytogenes even stored under the optimum temperature.

A microscopy-based approach for determining growth probability and lag time of individual bacterial cells.

The development of relevant predictive models for single-cell lag time and growth probability near growth limits is of critical importance for predicting pathogen behavior in foods. The classical methods for data acquisition in this field are based on turbidity measurements of culture media in microplate wells inoculated with approximately one bacterial cell per well. Yet, these methods are labour intensive and would benefit from higher throughput. In this study, we developed a quantitative experimental method using automated microscopy to determine the single-cell growth probability and lag time. The developed method consists of the use of direct cell observation with phase-contrast microscopy equipped with a 100× objective and a high-resolution device camera. The method is not a time-lapse method but is based on the observation of high numbers of colonies for a given time. Automation of image acquisition and image analysis was used to reach a high throughput. The single-cell growth probabilities and lag times of four strains of Listeria monocytogenes were determined at 4 °C. The microscopic method was shown to be a promising method for the determination of individual lag times and growth probability at the single-cell level.

Growth parameters of Penicillium expansum calculated from mixed inocula as an alternative to account for intraspecies variability.

The aim of this work was to compare the radial growth rate (µ) and the lag time (λ) for growth of 25 isolates of Penicillium expansum at 1 and 20 ºC with those of the mixed inoculum of the 25 isolates. Moreover, the evolution of probability of growth through time was also compared for the single strains and mixed inoculum. Working with a mixed inoculum would require less work, time and consumables than if a range of single strains has to be used in order to represent a given species. Suitable predictive models developed for a given species should represent as much as possible the behavior of all strains belonging to this species. The results suggested, on one hand, that the predictions based on growth parameters calculated on the basis of mixed inocula may not accurately predict the behavior of all possible strains but may represent a percentage of them, and the median/mean values of µ and λ obtained by the 25 strains may be substituted by the value obtained with the mixed inoculum. Moreover, the predictions may be biased, in particular, the predictions of λ which may be underestimated (fail-safe). Moreover, the prediction of time for a given probability of growth through a mixed inoculum may not be accurate for all single inocula, but it may represent 92% and 60% of them at 20 and 1 ºC, respectively, and also their overall mean and median values. In conclusion, mixed inoculum could be a good alternative to estimate the mean or median values of high number of isolates, but not to account for those strains with marginal behavior. In particular, estimation of radial growth rate, and time for 0.10 and 0.50 probability of growth using a cocktail inoculum accounted for the estimates of most single isolates tested. For the particular case of probability models, this is an interesting result as for practical applications in the food industry the estimation of t10 or lower probability may be required.