Use of enrichment real-time PCR to enumerate salmonella on chicken parts

Poultry Food Assess Risk Model for Salmonella and Chicken Gizzards: III. Dose Consumed Step

The Dose Consumed step of the Poultry Food Assess Risk Model (PFARM) for Salmonella and chicken gizzards was presented and compared to the Exposure Assessment step of Quantitative Microbial Risk Assessment (QMRA). The specific objectives were 1) to demonstrate the dose consumed step of PFARM for Salmonella and chicken gizzards; 2) to compare Salmonella dose consumed from cooked chicken gizzards to that from cross-contaminated and temperature-abused lettuce; 3) to determine if Salmonella dose consumed changed over time in a production chain; and 4) to compare PFARM and QMRA predictions of Salmonella dose consumed. The PFARM and QMRA were developed in an Excel notebook and simulated with @Risk. Salmonella prevalence and number data (P = 100) for chicken gizzards (56 g) and scenario analysis were used to address objectives 1, 2, and 4, whereas running windows of 60 consecutive chicken gizzard samples and scenario analysis were used to address objective 3. A lot size of 1,000 kg of chicken gizzards was simulated. Mean portion size was 168 g resulting in the simulation of 5,952 meals per lot. Of these, 3.69 ± 0.32% and 0.49 ± 0.07% (mean ± SD) resulted in Salmonella dose consumed of ≥1 per meal from cooked chicken gizzards and lettuce, respectively. However, the total Salmonella dose consumed per lot from cooked chicken gizzards (272 ± 27) was less (P ≤ 0.05) than from lettuce (6,050 ± 4,929) because of a few highly contaminated (>310 Salmonella) lettuce portions at consumption. Over time in the production chain, Salmonella prevalence and total dose consumed per lot changed (P ≤ 0.05) but the patterns differed. The QMRA predicted higher (P ≤ 0.05) Salmonella dose consumed per meal than PFARM. In part, this was because QMRA only simulated contaminated grams, whereas PFARM simulated contaminated and non-contaminated meals. However, other factors, which are discussed, also contributed to the overestimation of Salmonella dose consumed by QMRA.

Poultry Food Assess Risk Model for Salmonella and Chicken Gizzards: I. Initial Contamination

The Poultry Food Assess Risk Model (PFARM) project was initiated in 1995 to develop data collection and modeling methods for simulating the risk of salmonellosis from poultry food produced by individual production chains. In the present study, the Initial Contamination (IC) step of PFARM for Salmonella and chicken gizzards (CG) was conducted as a case study. Salmonella prevalence (Pr), number (N), and serotype/zoonotic potential (ZP) data (n = 100) for one sample size (56 g) of CG were collected at meal preparation (MP), and then Monte Carlo simulation (MCS) was used to obtain data for other sample sizes (112, 168, 224, 280 g). The PFARM was developed in Excel and was simulated with @Risk. Data were simulated using a moving window of 60 samples to determine how Salmonella Pr, N, and ZP changed over time in the production chain. The ability of Salmonella to survive, grow, and spread in the production chain and food, and then cause disease in humans was ZP, which was based on U. S. Centers for Disease Control and Prevention data for salmonellosis. Of 100 CG samples tested, 35 were contaminated with Salmonella with N from 0 to 0.809 (median) to 2.788 log per 56 g. Salmonella serotype Pr per 56 g was 16% for Kentucky (ZP_mode = 1.1), 9% for Infantis (ZP_mode = 4.4), 6% for Enteritidis (ZP_mode = 5.0), 3% for Typhimurium (ZP_mode = 4.9), and 1% for Thompson (ZP_mode = 3.7). Results from MCS indicated that Salmonella Pr, N, and ZP among portions of CG at MP changed (P ≤ 0.05) over time in the production chain. Notably, the main serotype changed from Kentucky (low ZP) to Infantis (high ZP). However, the pattern of change for Salmonella Pr, N, and ZP differed over time in the production chain and by the statistic used to characterize it. Thus, a performance standard (PS) based on Salmonella Pr, N, or ZP at testing or MP will likely not be a good indicator of poultry food safety or risk of salmonellosis.

Application of a Commercial Salmonella Real-Time PCR Assay for the Detection and Quantitation of Salmonella enterica in Poultry Ceca

ABSTRACT

Foodborne salmonellosis is commonly associated with poultry and poultry products, necessitating continued development of pre- and postharvest food safety interventions and risk management strategies. Evaluation of technologies and strategies is limited by availability of cost-effective, rapid laboratory methods. The objective of this study was to evaluate a commercial qualitative PCR assay and its novel quantitative application to detect and enumerate Salmonella in poultry ceca as an analytical matrix. Ceca were collected at harvest, the contents were homogenized, and paired samples were evaluated with buffered peptone water (BPW) and BAX MP + Supplement (MPS) preenrichment broths followed by PCR screening with a BAX System Q7 PCR and by culture isolation. Additional ceca were inoculated with Salmonella to develop a standard curve for the BAX System SalQuant quantitative PCR application (QA), and estimates were obtained by the QA and most-probable-number (MPN) methods. For preenrichment media, PCR outcomes were equivalent to those of culture isolation for detecting Salmonella in ceca with 95.65 and 87.88% sensitivity and 82.00 and 100.00% specificity (P = 0.074) for BPW and MPS, respectively. However, at the sample level, BPW performed significantly worse (47.92%) than did MPS (68.75%) for overall isolation of Salmonella (P < 0.0001). After standard curve development, the mean QA estimates obtained for the inoculated samples were 1.14 (95% confidence interval [CI]: 0.62 to 1.66), 1.79 (1.50 to 2.08), 2.91 (2.65 to 3.17), and 3.76 (3.26 to 4.25) log CFU/mL for each targeted inoculation of 1.0, 2.0, 3.0, and 4.0 log CFU/mL, respectively, and were within or comparable to the 95% CI values of paired MPN estimates. These data support the use of MPS for the detection and isolation of Salmonella enterica from poultry ceca when screening with PCR and indicate that QA may be useful as an alternative tool to estimate Salmonella loads in poultry ceca, which may support preharvest food safety interventions.

HIGHLIGHTS

Monte Carlo Simulation Model for Predicting Salmonella Contamination of Chicken Liver as a Function of Serving Size for Use in Quantitative Microbial Risk Assessment

ABSTRACT

The first step in quantitative microbial risk assessment (QMRA) is to determine the distribution of pathogen contamination among servings of the food in question at some point in the farm-to-table chain. In the present study, the distribution of Salmonella contamination among servings of chicken liver for use in the QMRA was determined at meal preparation. Salmonella prevalence (P), most probable number (MPN, N), and serotype for different serving sizes were determined by use of a combination of five methods: (i) whole sample enrichment; (ii) quantitative PCR; (iii) culture isolation; (iv) serotyping; and (v) Monte Carlo simulation. Epidemiological data also were used to convert serotype data to virulence (V) values for use in the QMRA. A Monte Carlo simulation model based in Excel and simulated with @Risk predicted Salmonella P, N, serotype, and V as a function of a serving size of one (58 g) to eight (464 g) chicken livers. Salmonella P of chicken livers was 72.5% (58 of 80) per 58 g. Four Salmonella serotypes were isolated from chicken livers: (i) Infantis (P = 28%, V = 4.5); (ii) Enteritidis (P = 15%, V = 5); (iii) Typhimurium (P = 15%, V = 4.8); and (iv) Kentucky (P = 15%, V = 0.8). Salmonella N was 1.76 log MPN/58 g (median) with a range of 0 to 4.67 log MPN/58 g, and the median Salmonella N was not affected (P > 0.05) by serotype. The model predicted a nonlinear increase (P ≤ 0.05) of Salmonella P from 72.5%/58 g to 100%/464 g, a minimum N of 0 log MPN/58 g to 1.28 log MPN/464 g, and a median N from 1.76 log MPN/58 g to 3.22 log MPN/464 g. Regardless of serving size, predicted maximum N was 4.74 log MPN per serving, mean V was 3.9 per serving, and total N was 6.65 log MPN per lot (10,000 chicken livers). The data acquired and modeled in this study address an important data gap in the QMRA for Salmonella and whole chicken liver.

HIGHLIGHTS

Prevalence of Salmonella and Campylobacter spp. in Alternative and Conventionally Produced Chicken in the United States: A Systematic Review and Meta-Analysis

ABSTRACT

The burden of foodborne illness linked to the consumption of contaminated broiler meat is high in the United States. With the increase in popularity of alternative poultry rearing and production systems, it is important to identify the differences in food safety risks presented by alternative systems compared with conventional methods. Although many studies have been conducted that surveyed foodborne pathogen prevalence along the broiler supply chain, a systematic overview of all of the results is lacking. In the current study, a systematic review and meta-analysis were conducted to quantify the differences in prevalence of Salmonella and Campylobacter spp. in farm environment, rehang, prechill, postchill, and retail samples between conventional and alternative production systems. A systematic search of Web of Science and PubMed databases was conducted to identify eligible studies. Studies were then evaluated by inclusion criteria, and the included studies were qualitatively and quantitatively analyzed. In total, 137 trials from 72 studies were used in the final meta-analysis. Meta-analysis models were individually constructed for subgroups that were determined by sample type, pathogen, and production type. All subgroups possessed high amounts of heterogeneity (I2 > 75%). For environmental sample subgroups, Campylobacter prevalence was estimated to be 15.8 and 52.8% for conventional and alternative samples, respectively. Similar prevalence estimates for both production types were observed for Salmonella environmental samples and all retail samples. For conventional samples, Campylobacter and Salmonella prevalence was highest in prechill samples followed by rehang and postchill samples, respectively. The results herein will be useful in future quantitative microbial risk assessments for characterizing the differences in foodborne illness risks presented by different broiler production systems.

HIGHLIGHTS

Assessing the relationship between organic farming practices and microbiological characteristics of organic lettuce varieties (Lactuca sativa L.) grown in Sao Paulo, Brazil

AIMS

This study aimed to gather information on farming practices employed in organic lettuce fields in Sao Paulo, Brazil and associate these practices with the microbiological characteristics of the products.

METHODS AND RESULTS

Practices were surveyed using a questionnaire applied in ten farms, where 200 heads of lettuce were collected and submitted to enumeration of total coliforms and generic Escherichia coli and tested for Salmonella spp. using culture and molecular (qPCR) methods. Based on the responses, the farms could be clustered in two groups: group 1, comprised by six farms, where chicken manure was used as fertilizer in most of them and the composting process was not performed on site; and group 2, comprised by four farms, where other types of fertilizer were used, and the composting process was performed on site. Generic E. coli was detected in 56 (28%) samples, with an average of 1·1 ± 0·7 log MPN per g. Salmonella DNA was detected in two (1%) samples by qPCR.

CONCLUSIONS

The prevalence and bacterial loads of generic E. coli, and the occurrence of Salmonella, even at low populations undetectable by conventional culture methods, highlight the need for control measures during farming practices to reduce microbial contamination and risks of foodborne illnesses. These measures include the use of properly composted manure and appropriate washing procedures for leafy vegetables before consumption.

SIGNIFICANCE AND IMPACT OF THE STUDY

The obtained data contribute to a better understanding of the farming practices of organically grown lettuces in Sao Paulo, Brazil.

Risk of Salmonellosis from Chicken Parts Prepared from Whole Chickens Sold in Flow Pack Wrappers and Subjected to Temperature Abuse

The flow pack wrapper is a popular packaging choice for retail sale of whole chickens. However, it may provide a favorable environment for growth and spread of Salmonella within the package, leading to an outbreak of salmonellosis. To investigate this possibility, a process risk model was developed that predicted the risk of salmonellosis from chicken parts prepared from whole chickens sold in flow pack wrappers and subjected to proper storage (6 h at 4°C) or improper storage (72 h at 15°C) before preparation. The model had four unit operations (pathogen events): (i) preparation (contamination), (ii) cooking (death), (iii) serving (cross-contamination), and (iv) consumption (dose-response). Data for prevalence, number, and serotype of Salmonella on chicken parts were obtained by whole sample enrichment, real-time PCR. Improper storage increased (P < 0.05) prevalence of Salmonella on raw chicken parts from 10.6% (17 of 160) to 41.2% (66 of 160) and incidence of cross-contamination of cooked chicken from 10% (4 of 40) to 52.2% (24 of 46). Improper storage also increased (P < 0.05) the number (mean ± standard deviation) of Salmonella from 0.017 ± 0.030 to 3.51 ± 1.34 log per raw chicken part and from 0.048 ± 0.089 to 3.08 ± 1.50 log per cooked chicken part. The predominant serotypes isolated (n = 111) were Typhimurium (34.2%), Typhimurium var 5- (20.7%), Kentucky (12.6%), Enteritidis (11.7%), and Heidelberg (8.1%). When chicken was properly stored before preparation, the model predicted that risk of salmonellosis was low and sporadic with only six cases per 100 simulations of 10⁵ chicken parts. However, when 0.1 to 1% of chickens were improperly stored before preparation, the model predicted that salmonellosis would increase (P < 0.05) linearly from a median of 7 (range, 1 to 15) to a median of 72 (range, 52 to 93) cases per 10⁵ chicken parts. These results indicated that the flow pack wrapper provided a favorable environment for growth and spread of Salmonella within the package and that even when only a small percentage of packages were subjected to improper storage before preparation, the risk and size of an outbreak of salmonellosis from chicken parts increased significantly.

Neural Network Model for Thermal Inactivation of Salmonella Typhimurium to Elimination in Ground Chicken: Acquisition of Data by Whole Sample Enrichment, Miniature Most-Probable-Number Method

Predictive models are valuable tools for assessing food safety. Existing thermal inactivation models for Salmonella and ground chicken do not provide predictions above 71°C, which is below the recommended final cooked temperature of 73.9°C for chicken. They also do not predict when all Salmonella are eliminated without extrapolating beyond the data used to develop them. Thus, a study was undertaken to develop a model for thermal inactivation of Salmonella to elimination in ground chicken at temperatures above those of existing models. Ground chicken thigh portions (0.76 cm³) in microcentrifuge tubes were inoculated with 4.45 ± 0.25 log most probable number (MPN) of a single strain of Salmonella Typhimurium (chicken isolate). They were cooked at 50 to 100°C in 2 or 2.5°C increments in a heating block that simulated two-sided pan frying. A whole sample enrichment, miniature MPN (WSE-mMPN) method was used for enumeration. The lower limit of detection was one Salmonella cell per portion. MPN data were used to develop a multiple-layer feedforward neural network model. Model performance was evaluated using the acceptable prediction zone (APZ) method. The proportion of residuals in an APZ (pAPZ) from -1 log (fail-safe) to 0.5 log (fail-dangerous) was 0.911 (379 of 416) for dependent data and 0.910 (162 of 178) for independent data for interpolation. A pAPZ ≥0.7 indicated that model predictions had acceptable bias and accuracy. There were no local prediction problems because pAPZ for individual thermal inactivation curves ranged from 0.813 to 1.000. Independent data for interpolation satisfied the test data criteria of the APZ method. Thus, the model was successfully validated. Predicted times for a 1-log reduction ranged from 9.6 min at 56°C to 0.71 min at 100°C. Predicted times for elimination ranged from 8.6 min at 60°C to 1.4 min at 100°C. The model will be a valuable new tool for predicting and managing this important risk to public health.

Neural Network Model for Survival and Growth of Salmonella enterica Serotype 8,20:-:z6 in Ground Chicken Thigh Meat during Cold Storage: Extrapolation to Other Serotypes

Mathematical models that predict the behavior of human bacterial pathogens in food are valuable tools for assessing and managing this risk to public health. A study was undertaken to develop a model for predicting the behavior of Salmonella enterica serotype 8,20:-:z6 in chicken meat during cold storage and to determine how well the model would predict the behavior of other serotypes of Salmonella stored under the same conditions. To develop the model, ground chicken thigh meat (0.75 cm(3)) was inoculated with 1.7 log Salmonella 8,20:-:z6 and then stored for 0 to 8 -8 to 16°C. An automated miniaturized most-probable-number (MPN) method was developed and used for the enumeration of Salmonella. Commercial software (Excel and the add-in program NeuralTools) was used to develop a multilayer feedforward neural network model with one hidden layer of two nodes. The performance of the model was evaluated using the acceptable prediction zone (APZ) method. The number of Salmonella in ground chicken thigh meat stayed the same (P > 0.05) during 8 days of storage at -8 to 8°C but increased (P < 0.05) during storage at 9°C (+0.6 log) to 16°C (+5.1 log). The proportion of residual values (observed minus predicted values) in an APZ (pAPZ) from -1 log (fail-safe) to 0.5 log (fail-dangerous) was 0.939 for the data (n = 426 log MPN values) used in the development of the model. The model had a pAPZ of 0.944 or 0.954 when it was extrapolated to test data (n = 108 log MPN per serotype) for other serotypes (S. enterica serotype Typhimurium var 5-, Kentucky, Typhimurium, and Thompson) of Salmonella in ground chicken thigh meat stored for 0 to 8 days at -4, 4, 12, or 16°C under the same experimental conditions. A pAPZ of ≥0.7 indicates that a model provides predictions with acceptable bias and accuracy. Thus, the results indicated that the model provided valid predictions of the survival and growth of Salmonella 8,20:-:z6 in ground chicken thigh meat stored for 0 to 8 days at -8 to 16°C and that the model was validated for extrapolation to four other serotypes of Salmonella.