Predictive model of growth kinetics for Staphylococcus aureus in raw beef under various packaging systems

A predictive growth model of Staphylococcus aureus during temperature abuse conditions

The primary contributing factor leading to Staphylococcus aureus food poisoning is that some foods are not cooked after handling or are not appropriately refrigerated during storage. A predictive model for S. aureus was developed and validated using growth kinetic data. The growth data were collected in the Tryptic Soy Broth at isothermal temperatures from 7 to 48.9 °C. Baranyi model was fitted to the growth data, and Ratkowsky's secondary model was fitted to the growth rates with respect to temperature. Both primary and secondary models fitted the growth data well, as depicted by the goodness of fit measures (high R2, low RMSE/SSE). The average h0 value was 5.06 across all growth temperatures (10 to 45 °C). The maximum growth temperature was 47.3 °C, while the minimum was 5.7 °C. Bacteria growth was estimated under dynamic temperature profiles by solving the differential form of the Baranyi model in combination with the Ratkowsky model equation for rate constants using the fourth-order Runge-Kutta method. The dynamic model was developed and validated using growth data obtained with two sinusoidal temperature profiles, 10-30 °C and 25-45 °C for 30 h and 24 h. Data for these two profiles were assessed using acceptable prediction zone analysis; >70 % of the observed growth observations were within the acceptable prediction zone (-1.0 to 0.5 log10 CFU/mL), although the model may overestimate or underestimate at some points, generally <1 log. The model will assist in estimating the growth of S. aureus in temperature abuse conditions.

Growth Effects as a Function of pH and Temperature of Salmonella enterica serovar Choleraesuis in In Vitro Tests and Chicken Meat: Prediction and Modeling

The present study aimed to predict and model the growth of Salmonella enterica serovar Choleraesuis as a function of pH and temperature in in vitro tests and raw chicken meat. To describe the growth, the data were adjusted by the Modified Gompertz primary model. After comparison, they presented R2 values > 0.9799 and an RMSE of 0.092 to 0.274. With the values of µmax obtained by the primary model, it was possible to evaluate the influence of temperature using the secondary Gamma model. Comparing the results obtained experimentally with those predicted by the ComBase tertiary model, it was possible to verify that the analyses carried out in the laboratory show that Salmonella did not multiply for a longer time. At pH 5, 6, and 7 at 12 °C, ComBase presented a λ of 43, 31, and 28 h, while the experimental λ was 109, 63, and 85 h, respectively. A correlation was observed between rising temperatures and pH, leading to an increase in μmax and a decrease in λ. However, no correlation was found concerning ymax.

Growth and Non-Thermal Inactivation of Staphylococcus aureus in Sliced Dry-Cured Ham in Relation to Water Activity, Packaging Type and Storage Temperature

Dry-cured ham (DCH) could support the growth of Staphylococcus aureus as a halotolerant bacterium, which may compromise the shelf-stability of the product according to the growth/no growth boundary models and the physicochemical parameters of commercial DCH. In the present study, the behavior of S. aureus is evaluated in sliced DCH with different water activity (a_w 0.861-0.925), packaged under air, vacuum, or modified atmosphere (MAP), and stored at different temperatures (2-25 °C) for up to 1 year. The Logistic and the Weibull models were fitted to data to estimate the primary kinetic parameters for the pathogen Log₁₀ increase and Log₁₀ reduction, respectively. Then, polynomial models were developed as secondary models following their integration into the primary Weibull model to obtain a global model for each packaging. Growth was observed for samples with the highest a_w stored at 20 and 25 °C in air-packaged DCH. For lower a_w, progressive inactivation of S. aureus was observed, being faster at the lowest temperature (15 °C) for air-packaged DCH. In contrast, for vacuum and MAP-packaged DCH, a higher storage temperature resulted in faster inactivation without a significant effect of the product a_w. The results of this study clearly indicate that the behavior of S. aureus is highly dependent on factors such as storage temperature, packaging conditions and product a_w. The developed models provide a management tool for evaluating the risk associated with DCH and for preventing the development of S. aureus by selecting the most appropriate packaging according to a_w range and storage temperature.

Application of interaction models in predicting the simultaneous growth of Staphylococcus aureus and different concentrations of background microbiota in Chinese-style braised beef

This study aimed to investigate the growth kinetics of S. aureus and different concentrations of background microbiota in Chinese-style braised beef (CBB). A one-step analysis method was applied to develop predictive model to describe the simultaneous growth and interaction of S. aureus with different concentrations of background microbiota in CBB. The results show that a one-step method successfully models the growth of S. aureus and background microbiota in CBB and the competing interactions between the two. In sterile CBB, the estimated minimum growth temperatures (T_min,S) and the maximum growth concentrations (Y_max,S) were 8.76 °C and 9.58 log CFU/g for S. aureus. Under competition, the growth of background microbiota was not affected by S. aureus, the estimated T_min,B and Y_max,B was 4.46 °C and 9.94 log CFU/g. The background microbiota in CBB did not affect the growth rate of S. aureus (α₁ = 1.04), but had an inhibitory effect on the number of S. aureus (α₂ = 0.69) at the later growth stage. The Root Mean Square Error (RMSE) of the modeling data was 0.34 log CFU/g, with 85.5% of the residual errors within ±0.5 log CFU/g of experimental observations. The one-step analysis and dynamic temperatures (8 °C-32 °C) verification indicated that the RMSE of prediction was <0.5 log CFU/g for both S. aureus and background microbiota. This study demonstrates that microbial interaction models are a useful and promising tool for predicting and evaluating the spatiotemporal population dynamics of S. aureus and background microbiota in CBB products.

Microbiological safety of aged meat

The impact of dry-ageing of beef and wet-ageing of beef, pork and lamb on microbiological hazards and spoilage bacteria was examined and current practices are described. As 'standard fresh' and wet-aged meat use similar processes these were differentiated based on duration. In addition to a description of the different stages, data were collated on key parameters (time, temperature, pH and aw) using a literature survey and questionnaires. The microbiological hazards that may be present in all aged meats included Shiga toxin-producing Escherichia coli (STEC), Salmonella spp., Staphylococcus aureus, Listeria monocytogenes, enterotoxigenic Yersinia spp., Campylobacter spp. and Clostridium spp. Moulds, such as Aspergillus spp. and Penicillium spp., may produce mycotoxins when conditions are favourable but may be prevented by ensuring a meat surface temperature of -0.5 to 3.0°C, with a relative humidity (RH) of 75-85% and an airflow of 0.2-0.5 m/s for up to 35 days. The main meat spoilage bacteria include Pseudomonas spp., Lactobacillus spp. Enterococcus spp., Weissella spp., Brochothrix spp., Leuconostoc spp., Lactobacillus spp., Shewanella spp. and Clostridium spp. Under current practices, the ageing of meat may have an impact on the load of microbiological hazards and spoilage bacteria as compared to standard fresh meat preparation. Ageing under defined and controlled conditions can achieve the same or lower loads of microbiological hazards and spoilage bacteria than the variable log10 increases predicted during standard fresh meat preparation. An approach was used to establish the conditions of time and temperature that would achieve similar or lower levels of L. monocytogenes and Yersinia enterocolitica (pork only) and lactic acid bacteria (representing spoilage bacteria) as compared to standard fresh meat. Finally, additional control activities were identified that would further assure the microbial safety of dry-aged beef, based on recommended best practice and the outputs of the equivalence assessment.

Transcriptome analysis of the biofilm formation mechanism of Vibrio parahaemolyticus under the sub-inhibitory concentrations of copper and carbenicillin

Biofilm formation of Vibrio parahaemolyticus enhanced its tolerance to the environment, but caused many serious problems to food safety and human health. In this paper, the effects of copper and carbenicillin (CARB) stress on the formation of the biofilms of V. parahaemolyticus organisms were studied, and RNA sequencing technology was used to compare the differences in transcriptome profiles of the biofilm-related genes of V. parahaemolyticus organisms under different sub-inhibitory stresses. The results proved that V. parahaemolyticus had a large growth difference under the two stresses, copper and CARB at 1/2 minimal inhibitory concentration (MIC), and it could form a stable biofilm under both stress conditions. The amount of biofilm formed under CARB stress was significantly higher than that of copper stress (p < 0.05). Based on the analysis of transcriptome sequencing results 323, 1,550, and 1,296 significantly differential expressed genes were identified in the three treatment groups namely 1/2 MIC CARB, Cu²⁺, and Cu²⁺+CARB. Through COG annotation, KEGG metabolic pathway analysis and gene expression analysis related to biofilm formation, the functional pathways of transcriptome changes affecting V. parahaemolyticus were different in the three treatment groups, and the CARB treatment group was significantly different from the other two groups. These differences indicated that the ABC transport system, two-component system and quorum sensing were all involved in the biofilm formation of the V. parahaemolytic by regulating flagellar motility, extracellular polysaccharides and extracellular polymer synthesis. Exploring the effects of different stress conditions on the transcriptome of V. parahaemolyticus could provide a basis for future research on the complex network system that regulates the formation of bacterial biofilms.

Dimensional Analysis Model Predicting the Number of Food Microorganisms

Predicting the number of microorganisms has excellent application in the food industry. It helps in predicting and managing the storage time and food safety. This study aimed to establish a new, simple, and effective model for predicting the number of microorganisms. The dimensional analysis model (DAM) was established based on dimensionless analysis and the Pi theorem. It was then applied to predict the number of Pseudomonas in Niuganba (NGB), a traditional Chinese fermented dry-cured beef, which was prepared and stored at 278 K, 283 K, and 288 K. Finally, the internal and external validation of the DAM was performed using six parameters including R ², R ² _adj , root mean square error (RMSE), standard error of prediction (%SEP), A _f , and B _f . High R ² and R ² _adj and low RMSE and %SEP values indicated that the DAM had high accuracy in predicting the number of microorganisms and the storage time of NGB samples. Both A _f and B _f values were close to 1. The correlation between the observed and predicted numbers of Pseudomonas was high. The study showed that the DAM was a simple, unified and effective model to predict the number of microorganisms and storage time.

Characterization of the Inclusion Complexes of Isothiocyanates with γ-Cyclodextrin for Improvement of Antibacterial Activities against Staphylococcus aureus

The aim of this study was to develop inclusions formed by γ-cyclodextrin (γ-CD) and three isothiocyanates (ITCs), including benzyl isothiocyanate (BITC), phenethyl isothiocyanate (PEITC), and 3-methylthiopropyl isothiocyanate (MTPITC) to improve their controlled release for the inhibition of Staphylococcus aureus (S. aureus). These inclusion complexes were characterized using X-ray diffraction, Fourier-transform infrared, thermogravimetry, and scanning electron microscopy (SEM), providing appropriate evidence to confirm the formation of inclusion complexes. Preliminary evaluation of the antimicrobial activity of the different inclusion complexes, carried out in vitro by agar diffusion, showed that such activity lasted 5–7 days longer in γ-CD-BITC, in comparison with γ-CD-PEITC and γ-CD-MTPITC. The biofilm formation was less in S. aureus treated with γ-CD-BITC than that of BITC by using crystal violet quantification assay and SEM. The expression of virulence genes, including sarA, agr, cp5D, cp8F, clf, nuc, and spa, showed sustained downregulation in S. aureus treated with γ-CD-BITC for 24 h by quantitative real-time polymerase chain reaction (qRT-PCR). Moreover, the growth of S. aureus in cooked chicken breast treated with γ-CD-BITC and BITC was predicted by the Gompertz model. The lag time of γ-CD-BITC was 1.3–2.4 times longer than that of BITC, and correlation coefficient (R²) of the secondary models was 0.94–0.99, respectively. These results suggest that BITC has a more durable antibacterial effect against S. aureus after encapsulation by γ-CD.

Growth interferences between bacterial strains from raw cow's milk and their impact on growth of Listeria monocytogenes and Staphylococcus aureus

AIMS

The purpose of this study was to detect growth enhancing or inhibiting activity between bacterial populations from raw milk under different conditions (temperature, medium).

METHODS AND RESULTS

The interference of 24 raw milk isolates on growth of each other and on Listeria monocytogenes, Staphylococcus aureus, Bacillus subtilis and Micrococcus luteus was screened by drop assay and for selected pairs in co-cultivation experiments. By drop assay, antibacterial activity was observed for 40% of the strains. About 30% of the strains showed growth-enhancing activity on other strains. Most of the isolates were well adapted to cold temperatures and showed consistent or even increased inhibiting or enhancing effects on growth of other strains at 10°C. The growth of L. monocytogenes DSM 20600^T and S. aureus DSM 1104^T was significantly (P < 0·05) reduced in co-cultivation with Pseudomonas protegens JZ R-192.

CONCLUSIONS

Growth interferences between bacterial populations have an impact on the structure of raw milk microbiota, especially when it develops under cold storage, and it may have an effect on the prevalence of certain foodborne pathogens.

SIGNIFICANCE AND IMPACT OF THE STUDY

This study demonstrates growth-inhibiting and also growth-enhancing interactions between raw milk bacteria, which must be considered when predicting bacterial growth and spoilage in food. A Ps. protegens strain isolated from raw milk showed an antagonistic effect on growth of L. monocytogenes in refrigerated raw milk.