Suchergebnisse

peer-reviewed ; Listeria monocytogenes is a foodborne pathogen that causes a relatively rare foodborne disease called listeriosis, with a high mortality rate of 20%-30% and an undefined dose response. Current European Union regulations permit up to 100 colony-forming units (cfu)/g in food at the end of its shelf life, where the food has been shown not to support the growth of this pathogenic bacterium. Therefore, enumeration of L. monocytogenes at low numbers in food is important. The objective of this study was to reduce the detection limit of L. monocytogenes in food by a factor of 10. The International Organisation for Standardisation (ISO) 11290-2 method for enumeration of L. monocytogenes in food recommends spreading 0.1 mL of a 1:10 dilution of the food on the surface of an agar plate (detection limit 100 cfu/g), or 1.0 mL spread in equal parts on the surface of three agar plates (detection limit: 10 cfu/g). The pour-plate method (using 1 or 10 mL of an appropriate dilution) was compared to the spread-plate method using the ISO-approved chromogenic medium Agar Listeria according to Ottaviani and Agosti (ALOA). Using the pour-plate method, the colony morphology and halo formation were similar to the spread-plate method from pure cultures and inoculated foods. Using the pour-plate method in a 140 mm Petri dish, 10 mL of a 1:10 dilution of food allowed determination of numbers as low as 1 cfu/g. Applying this method, L. monocytogenes in naturally contaminated food samples were enumerated at numbers as low as 1-9 cfu/g. ; This work was supported by The Irish Department of Agriculture, Food and the Marine under the Food Institutional Research Measure, project 11/F/008, and by the Dairy Processing Technology Centre, supported by Enterprise Ireland and the Irish Dairy Industry, project number TC 2014 0016.

Listeria monocytogenes is a foodborne pathogen that causes listeriosis, a relatively rare, but potentially fatal, disease, with a mortality rate of 20–30%. In general, European Regulations require the absence of L. monocytogenes in five samples of 25 g before the food has left the producer, but if the food has been demonstrated not to support the growth of L. monocytogenes, up to 100 cfu g−1 are allowed in the food (except for foods for infants or medical purposes) during its shelf-life under reasonably foreseeable storage conditions. It is important for food producers to determine if their food supports the growth of L. monocytogenes. The European Union Reference Laboratory for L. monocytogenes published a Technical Guidance document for conducting shelf-life studies on L. monocytogenes in ready-to-eat foods in June 2014. Primarily based on the EURL guidance document for conducting challenge studies, the ability of cheese (feta and soft goat's milk cheese), cold-smoked salmon, coleslaw, and pork pate to support the growth of L. monocytogenes was determined using a starting inoculum of approximately 100 cfu g−1. The cheese and pork pate were incubated at 8 °C for 14 days; the smoked salmon was incubated at 6 °C for 5 days and 8 °C for 9 days; and the coleslaw was incubated at 8 °C for 7 days and 12 °C for 14 days. The results showed that the smoked salmon and pork pate supported growth, while coleslaw and cheese did not. From this study, it is evident that there are factors in food other than pH, water activity, and total bacterial count (TBC) that can inhibit the ability of L. monocytogenes to grow in food.

Surface-ripened cheeses are matured by means of manual or mechanical technologies posing a risk of cross-contamination, if any cheeses are contaminated with Listeria monocytogenes. In predictive microbiology, primary models are used to describe microbial responses, such as growth rate over time and secondary models explain how those responses change with environmental factors. In this way, primary models were used to assess the growth rate of L. monocytogenes during ripening of the cheeses and the secondary models to test how much the growth rate was affected by either the pH and/or the water activity (aw) of the cheeses. The two models combined can be used to predict outcomes. The purpose of these experiments was to test three primary (the modified Gompertz equation, the Baranyi and Roberts model, and the Logistic model) and three secondary (the Cardinal model, the Ratowski model, and the Presser model) mathematical models in order to define which combination of models would best predict the growth of L. monocytogenes on the surface of artificially contaminated surface-ripened cheeses. Growth on the surface of the cheese was assessed and modeled. The primary models were firstly fitted to the data and the effects of pH and aw on the growth rate (μmax) were incorporated and assessed one by one with the secondary models. The Logistic primary model by itself did not show a better fit of the data among the other primary models tested, but the inclusion of the Cardinal secondary model improved the final fit. The aw was not related to the growth of Listeria. This study suggests that surface-ripened cheese should be separately regulated within EU microbiological food legislation and results expressed as counts per surface area rather than per gram.

Surface-ripened cheeses are matured by means of manual or mechanical technologies posing a risk of cross-contamination, if any cheeses are contaminated with Listeria monocytogenes. In predictive microbiology, primary models are used to describe microbial responses, such as growth rate over time and secondary models explain how those responses change with environmental factors. In this way, primary models were used to assess the growth rate of L. monocytogenes during ripening of the cheeses and the secondary models to test how much the growth rate was affected by either the pH and/or the water activity (aw) of the cheeses. The two models combined can be used to predict outcomes. The purpose of these experiments was to test three primary (the modified Gompertz equation, the Baranyi and Roberts model, and the Logistic model) and three secondary (the Cardinal model, the Ratowski model, and the Presser model) mathematical models in order to define which combination of models would best predict the growth of L. monocytogenes on the surface of artificially contaminated surface-ripened cheeses. Growth on the surface of the cheese was assessed and modeled. The primary models were firstly fitted to the data and the effects of pH and aw on the growth rate (mumax) were incorporated and assessed one by one with the secondary models. The Logistic primary model by itself did not show a better fit of the data among the other primary models tested, but the inclusion of the Cardinal secondary model improved the final fit. The aw was not related to the growth of Listeria. This study suggests that surface-ripened cheese should be separately regulated within EU microbiological food legislation and results expressed as counts per surface area rather than per gram. ; Peer reviewed

Listeriosis is a foodborne disease, with a high mortality rate, that predominantly affects the elderly. Under European Union legislation, EC 2073/2005, food business operators are encouraged to undertake sampling to ensure that the food processing environment, and required to ensure that food products, are free of Listeria monocytogenes. To determine the prevalence of L. monocytogenes in smaller food processing facilities in Northern Ireland, 24 companies submitted six processing environment swabs and two food samples every two months for eighteen months (July 2015 to November 2016) for L. monocytogenes examination. The prevalence of L. monocytogenes was 4.6% in food samples, and 6.3% in processing environment swabs. Over the duration of the study, 96 isolates of L. monocytogenes were obtained, one from each positive sample, except for two meat samples that had >100 cfu/g, where two isolates were obtained from each sample. No seasonality in occurrence of L. monocytogenes was seen for food isolates but significantly higher numbers of positive processing environment swabs were found in the warmer months of May, July and September (p =.007). Pulsed Field Gel Electrophoresis (PFGE) analysis revealed the presence of 27 pulsotypes; 9 pulsotypes were shared between different facilities and 9 were persistent. Based on a Combase predictive growth model, 77.5% (n = 130) of the foods tested were predicted to support the growth of L. monocytogenes. All of the isolates carried the pathogenicity genes inlA and actA and 71.4% carried qacH, which confers resistance to quaternary ammonium compounds which are frequently used in sanitizers. Whole genome sequencing of the isolates allowed multi-locus sequence typing to be undertaken. The data indicated that the sequence types identified included those with disease-causing ability, highlighting the disease-causing potential of the isolates.

peer-reviewed ; Listeriosis is a foodborne disease, with a high mortality rate, that predominantly affects the elderly. Under European Union legislation, EC 2073/2005, food business operators are encouraged to undertake sampling to ensure that the food processing environment, and required to ensure that food products, are free of Listeria monocytogenes. To determine the prevalence of L. monocytogenes in smaller food processing facilities in Northern Ireland, 24 companies submitted six processing environment swabs and two food samples every two months for eighteen months (July 2015 to November 2016) for L. monocytogenes examination. The prevalence of L. monocytogenes was 4.6% in food samples, and 6.3% in processing environment swabs. Over the duration of the study, 96 isolates of L. monocytogenes were obtained, one from each positive sample, except for two meat samples that had >100 cfu/g, where two isolates were obtained from each sample. No seasonality in occurrence of L. monocytogenes was seen for food isolates but significantly higher numbers of positive processing environment swabs were found in the warmer months of May, July and September (p = .007). Pulsed Field Gel Electrophoresis (PFGE) analysis revealed the presence of 27 pulsotypes; 9 pulsotypes were shared between different facilities and 9 were persistent. Based on a Combase predictive growth model, 77.5% (n = 130) of the foods tested were predicted to support the growth of L. monocytogenes. All of the isolates carried the pathogenicity genes inlA and actA and 71.4% carried qacH, which confers resistance to quaternary ammonium compounds which are frequently used in sanitizers. Whole genome sequencing of the isolates allowed multi-locus sequence typing to be undertaken. The data indicated that the sequence types identified included those with disease-causing ability, highlighting the disease-causing potential of the isolates.

The objective of this study was to model and quantify the level of Listeria monocytogenes in raw milk cheese (RMc) and pasteurized milk cheese (PMc) from farm to fork using a Bayesian inference approach combined with a quantitative risk assessment. The modeling approach included a prediction of contamination arising from the farm environment as well from cross‐contamination within the cheese‐processing facility through storage and subsequent human exposure. The model predicted a high concentration of L. monocytogenes in contaminated RMc (mean 2.19 log10 CFU/g) compared to PMc (mean −1.73 log10 CFU/g). The mean probability of illness (P1 for low‐risk population, LR) and (P2 for high‐risk population, HR, e.g., immunocompromised) adult Irish consumers following exposure to contaminated cheese was 7 × 10−8 (P1) and 9 × 10−4 (P2) for RMc and 7 × 10−10 (P1) and 8 × 10−6 (P2) for PMc, respectively. In addition, the model was used to evaluate performance objectives at various stages, namely, the cheese making and ripening stages, and to set a food safety objective at the time of consumption. A scenario analysis predicted various probabilities of L. monocytogenes contamination along the cheese‐processing chain for both RMc and PMc. The sensitivity analysis showed the critical factors for both cheeses were the serving size of the cheese, storage time, and temperature at the distribution stage. The developed model will allow food processors and policymakers to identify the possible routes of contamination along the cheese‐processing chain and to reduce the risk posed to human health.