A comprehensive systematic review and meta-analysis of Listeria monocytogenes prevalence in food products in South Korea

Listeria monocytogenes is a foodborne pathogen that can cause deadly severe listeriosis. While systematic review and meta-analysis are powerful tools for comprehensive analysis by pooling every related study, these approaches to L.monocytogenes contamination food have yet to be studied in South Korea. We aimed to identify high-risk L.monocytogenes foods in South Korea through a prevalence survey of retail food products for the first time. A total of 13,684 samples of 59 articles were used for meta-analysis through the systematic review, and the results were synthesized using a random-effects model considering the heterogeneity. The overall pooled prevalence was 2.26 % (95 % CI: 1.44-3.52 %). Among nine food categories, meat exhibited the highest prevalence at 8.32 % (95 % CI: 4.42-12.14 %) after sample size restriction. Specifically, a post-hoc sensitivity analysis was conducted to identify the prevalence difference among subgroups and the source of heterogeneity. Intriguingly, the analysis revealed chicken as the primary contributor to the elevated prevalence of L.monocytogenes, a key factor deriving the observed heterogeneity. This study carries significant implications for public health and food safety in Korea. Furthermore, knowledge of differences in prevalence levels in various foods will be able to be used as a predictive guideline for foodborne outbreaks.

Predictive model for growth of Pseudomonas spp. on fresh duck breast as a function of temperature

This study was performed to develop a predictive growth model of Pseudomonas spp. to ensure the safety of fresh duck breast. Sterile fresh duck breasts were inoculated with Pseudomonas spp. and stored at 4°C, 10°C, 15°C, 20°C, 25°C, and 30°C to measure the microbial change. The Baranyi primary model was used to simulate the growth changes of Pseudomonas spp. at different temperatures. The square root type model and hyperbolic function as secondary models were used to model the effect of temperature on the maximum specific growth rate and lag phase duration. The results showed that the primary models fitted the growth data well (all R2 > 0.900 and RMSE were close to 0). In validation study of secondary model, R2 were 0.987 and 0.925, RMSE were 0.017 and 1.825, respectively, indicating that the parameters of primary models were accurately predicted by secondary models. The validation experiments at tested temperatures proved that the changes of Pseudomonas spp. could be predicted accurately by the developed models combining primary and secondary models both at constant and variable temperatures. The model could be applied to predict the growth of Pseudomonas spp. in logistics for avoiding microbial spoilage on fresh duck breast.

Virulence Factors of Staphylococcus aureus Isolated from Korean Pork bulgogi: Enterotoxin Production and Antimicrobial Resistance

The aim of this study was to investigate the antimicrobial resistance profiles of and the enterotoxin gene distribution in 4 strains of Staphylococcus aureus (S10-2, S10-3, S12-2, and S13-2) isolated from 90 bulgogi samples. The S. aureus enterotoxin H gene (seh) was found in all the strains, while the S. aureus enterotoxin A gene (sea) was found only in 3 of the 4 strains. The S10-2 strain expressed a combination of enterotoxin genes - seg, seh, sei, sej, selm, and seln. The strains S10-2 and S13-2 were resistant to ampicillin and penicillin G, and all the isolated strains were resistant to tetracycline. The S10-2 strain was the only mecA-positive strain; it was also resistant to β-lactam antibiotics. Thus, genes encoding enterotoxin as well as those conferring antibiotic resistance were identified in the S. aureus strains isolated from pork bulgogi. These results represents the potential occurrence of MRSA in pork bulgogi, and the need for a monitoring system for pork bulgogi in order to prevent an outbreak of staphylococcal food poisoning.

Predictive model for the growth kinetics of Staphylococcus aureus in raw pork developed using Integrated Pathogen Modeling Program (IPMP) 2013

A predictive model was performed to describe the growth of Staphylococcus aureus in raw pork by using Integrated Pathogen Modeling Program 2013 and a polynomial model as a secondary predictive model. S. aureus requires approximately 180 h to reach 5-6 log CFU/g at 10 °C. At 15 °C and 25 °C, approximately 48 and 20 h, respectively, are required to cause food poisoning. Predicted data using the Gompertz model was the most accurate in this study. For lag time (LT) model, bias factor (Bf) and accuracy factor (Af) values were both 1.014, showing that the predictions were within a reliable range. For specific growth rate (SGR) model, Bf and Af were 1.188 and 1.190, respectively. Additionally, both Bf and Af values of the LT and SGR models were close to 1, indicating that IPMP Gompertz model is more adequate for predicting the growth of S. aureus on raw pork than other models.