Survey for Listeria monocytogenes in and on Ready-to-Eat Foods from Retail Establishments in the United States (2010 through 2013): Assessing Potential Changes of Pathogen Prevalence and Levels in a Decade.

A multiyear interagency Listeria monocytogenes Market Basket Survey was undertaken for selected refrigerated ready-to-eat foods purchased at retail in four FoodNet sites in the United States. Food samples from 16 food categories in six broad groups (seafood, produce, dairy, meat, eggs, and combination foods) were collected weekly at large national chain supermarkets and independent grocery stores in California, Maryland, Connecticut, and Georgia for 100 weeks between December 2010 and March 2013. Of the 27,389 total samples, 116 samples tested positive by the BAX PCR system for L. monocytogenes , and the pathogen was isolated and confirmed for 102 samples. Among the 16 food categories, the proportion of positive samples (i.e., without considering clustering effects) based on recovery of a viable isolate of L. monocytogenes ranged from 0.00% (95% confidence interval: 0.00, 0.18) for the category of soft-ripened and semisoft cheese to 1.07% (0.63, 1.68) for raw cut vegetables. Among the 571 samples that tested positive for Listeria-like organisms, the proportion of positive samples ranged from 0.79% (0.45, 1.28) for soft-ripened and semisoft cheese to 4.76% (2.80, 7.51) for fresh crab meat or sushi. Across all 16 categories, L. monocytogenes contamination was significantly associated with the four states (P < 0.05) but not with the packaging location (prepackaged by the manufacturer versus made and/or packaged in the store), the type of store (national chain versus independent), or the season. Among the 102 samples positive for L. monocytogenes , levels ranged from <0.036 most probable number per g to 6.1 log CFU/g. For delicatessen (deli) meats, smoked seafood, seafood salads, soft-ripened and semisoft cheeses, and deli-type salads without meat, the percentage of positive samples was significantly lower (P < 0.001) in this survey than that reported a decade ago based on comparable surveys in the United States. Use of mixed logistic regression models to address clustering effects with regard to the stores revealed that L. monocytogenes prevalence ranged from 0.11% (0.03, 0.34) for sprouts (prepackaged) to 1.01% (0.58, 1.74) for raw cut vegetables (prepackaged).

A mathematical model of inactivation kinetics for a four-strain composite of Salmonella Enteritidis and Oranienburg in commercial liquid egg yolk.

The goal of this study was to develop a general model of inactivation of salmonellae in commercial liquid egg yolk for temperatures ranging from 58°C to 66°C by studying the inactivation kinetics of Salmonella in liquid egg yolk. Heat-resistant salmonellae (three serovars of Enteritidis [two of phage type 8 and one PT 13] and one Oranienburg) were grown to stationary phase in Tryptic Soy Broth and concentrated 10-fold by centrifugation. Each inoculum was added to liquid egg yolk and mixed thoroughly, resulting in a final population of ca. 7 log CFU/ml egg yolk. Inoculated yolk was injected into sterile glass capillary tubes, flame-sealed and heated in a water bath at 58, 60, 62, 64, and 66°C. Capillary tubes were ethanol sanitized, rinsed, and contents were extracted. Yolk was diluted, surface plated onto Tryptic Soy Agar+0.1% sodium pyruvate and 50 µg/ml nalidixic acid and incubated at 37°C for 24 h before colonies were enumerated. Decimal reduction values were calculated from survivor curves with a minimum inactivation of 6 log CFU/ml at each temperature. Survival curves (except for 66°C) featured initial lag periods before first order linear inactivation. Estimated asymptotic D-values were 1.83 min at 58°C, 0.69 min at 60°C, 0.26 min at 62°C, 0.096 min at 64°C and 0.036 min at 66°C. The estimate of the asymptotic z-value was ca. 4.7°C with standard error of 0.07°C. A linear relationship between the log(10) of the lag times and temperature was observed. A general kinetic model of inactivation was developed. The results of the study provide information that can be used by processors to aid in producing safe pasteurized egg yolk products and for satisfying pasteurization performance standards and developing industry guidance.

Enumeration of Escherichia coli cells on chicken carcasses as a potential measure of microbial process control in a random selection of slaughter establishments in the United States.

To evaluate whether the number of Escherichia coli bacteria in carcass rinses from chicken slaughter establishments could be monitored for the purpose of microbial process control, we drew a random sample from 20 of 127 large USDA-inspected operations. In 2005, every 3 months, two sets of 10 carcass rinses, 100 ml each, were collected from establishments, netting 80 sample sets from the rehang and postchill stages. E. coli and Campylobacter numbers and Salmonella prevalence were measured. Mixed-effect models were used to estimate variance of mean log(10) E. coli cell numbers of 10-carcass rinse sample sets. Relationships between E. coli and Campylobacter and Salmonella were examined. For 10-carcass rinse sets, at both the rehang and postchill stages the mean log(10) E. coli CFU/ml fit the logistic distribution better than the normal distribution. The rehang overall mean log(10) E. coli was 3.3 CFU/ml, with a within-sample set standard deviation of 0.6 CFU/ml. The overall postchill mean log(10) E. coli was 0.8 CFU/ml, with 13 establishments having mean log(10) E. coli CFU/ml values of less than 1.0 and 7 having mean values of 1.2 or more. At the midpoint separating these establishments, a mean log(10) E. coli CFU/ml of 1.1, the within-sample set standard deviation was 0.5 CFU/ml, with smaller standard deviations as means increased. Postchill sample sets with mean log(10) E. coli counts less than or equal to 1.1 CFU/ml had lower overall prevalence of Salmonella and mean log(10) Campylobacter CFU/ml than sample sets with higher means. These findings regarding reductions in E. coli numbers provide insight relevant to microbial process control.