1. P174: Enumeration of Salmonella with the Polymerase Chain Reaction BAX System and Simulation Modeling Thomas P. Oscar, Agricultural Research Service, USDA, 1124 Trigg Hall, University of Maryland Eastern Shore, Princess Anne, MD 21853 410-651-6062; 410-651-6568 (fax); toscar@umes.edu INTRODUCTION With the advent of molecular methods such as polymerase chain reaction (PCR) detection that have high specificity for pathogens, it is now possible to develop enumeration methods for pathogens that only require pre-enrichment of the food sample and thus, are more rapid than traditional most probable number (MPN) enumeration methods. In 1998, Bailey evaluated a commercial PCR system (BAX, Qualicon, Inc., Wilmington, DE) for its ability to detect Salmonella in poultry samples relative to the conventional culture method. Using serial dilutions, he demonstrated that the size of the PCR band in the electrophoresis gel was related to the density of Salmonella in the pre-enrichment sample. In fact, the PCR band increased from a faint band at 10 2 CFU per ml to a full band at 10 7 CFU per ml. A visual scoring system based on PCR band size was developed for semi-quantitative enumeration of Salmonella in pre-enrichment samples. In the current study, a modified version of the PCR band size scoring system of Bailey (1998) was used to develop a simulation model for predicting the initial contamination of chicken with Salmonella as a function of PCR detection time score (PCR DTS ) and sample size. The method combines concepts of microbial growth kinetics, PCR detection of pathogens and simulation modeling to form a new method of enumeration for risk assessment. MATERIALS AND METHODS Challenge studies. Salmonella Typhimurium 14028 from ATCC and Salmonella Worthington from broiler ceca were used to develop the model. Stationary phase cultures grown at 37°C for 23 h were used to inoculate chicken homogenates consisting of 25 g of sterile chicken or 25 g of naturally contaminated chicken and 225 ml of sterile buffered peptone water. The initial density of Salmonella ranged from 10 0 to 10 6 CFU per 25 g of chicken. At 0, 2, 4, 6, 8, 10, 12 and 24 h of incubation at 37°C, a one ml subsample was collected for PCR analysis using the Qualicon BAX system. PCR analysis. One gel was run per chicken homogenate sample. For the eight lanes in the gel corresponding to the eight subsamples, a score of zero for no band, one for a faint band, two for a less than full band, and three for a full band was assigned. Thus, each chicken homogenate sample received a PCR DTS from zero to 24 by summing the scores for the eight subsample lanes in the gel. Standard curve. The PCR DTS for six or 12 chicken homogenate samples per experiment were graphed as a function of initial CFU of inoculated Salmonella per 25 g of chicken and the resulting curve was fit to a first or second order polynomial using GraphPad Prism (Figure 1). Simulation modeling. A simulation model for predicting the incidence and distribution of Salmonella among contaminated chicken samples as a function of PCR DTS and sample size was created in an Excel spreadsheet and was simulated with @Risk (Figure 2). The PCR DTS of 12 naturally contaminated 25 g samples of chicken were used to define the frequency of occurrence of PCR DTS in the simulation model. The scenario depicted in Figure 2 was simulated for chicken samples that ranged in size from 25 to 500 g to determine the effect of sample size on the distribution of Salmonella contamination (Table 1). RESULTS AND DISCUSSION A linear relationship between PCR DTS and the initial density of Salmonella inoculated was observed for sterile chicken homogenates (results not shown). In contrast, a non-linear relationship was observed for non-sterile chicken homogenates (Figure 1) and could be explained by inhibition of Salmonella growth by competing microorganisms at low but not at high initial density of inoculated Salmonella. Type of sterile chicken meat and serotype did not affect the shape of the standard curve. The simulation model (Figure 2) was created from the standard curve for non-sterile chicken homogenates (Figure 1) and was simulated for sample sizes from 25 to 500 g (Table 1). Results of the simulation demonstrated that the incidence and number of Salmonella among contaminated samples of chicken increased in a non-linear manner (Table 1). Thus, linear extrapolation of enumeration results, a common practice in risk assessment, is not appropriate. The outputs of the model can serve as inputs in a risk assessment model developed using the method of Oscar (1997) or other similar methods. REFERENCES Bailey, J. S. 1998. Detection of Salmonella cells within 24 to 26 hours in poultry samples with the polymerase chain reaction BAX system. J. Food Prot. 61:792-795. Oscar, T. P., 1997. Predictive modeling for risk assessment of microbial hazards, Reciprocal Meat Conference Proceedings, 50:98-103. Figure 2 Figure 1