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Detection and Enumeration of Food Pathogens with the BAX® PCR System Thomas P. Oscar, Ph.D. Research Food Technologist Welcome……thank you for coming!

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Presentation on theme: "Detection and Enumeration of Food Pathogens with the BAX® PCR System Thomas P. Oscar, Ph.D. Research Food Technologist Welcome……thank you for coming!"— Presentation transcript:

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2 Detection and Enumeration of Food Pathogens with the BAX® PCR System Thomas P. Oscar, Ph.D. Research Food Technologist Welcome……thank you for coming!

3 Detection and Enumeration of Food Pathogens with the BAX® PCR System Thomas P. Oscar, Ph.D. Research Food Technologist Welcome……thank you for coming!

4 University of Delaware (1978-1982) Undergraduate Research Assistant Undergraduate Research Assistant  B.S. in Animal Science  Pre-Veterinary Medicine “Interaction of Tiamulin and Monensin in Chickens”

5 Pennsylvania State University (1982-1984) Graduate Research Assistant  M.S. in Animal Nutrition  Minor in Biochemistry “Characterization of the Bovine Mammary Insulin Receptor”

6 North Carolina State University (1984-1987) Graduate Research & Teaching Assistant Graduate Research & Teaching Assistant  Ph.D. in Animal Science  Ruminant Nutrition “Role of Nickel in Methane Production”

7 University of Tennessee, Memphis (1987-1988) NIH Post-Doctoral Research Associate  Type II Diabetes  Rat Fat Cell Model

8 West Virginia University (1988-1992) Assistant Professor of Animal Science Assistant Professor of Animal Science  Growth & Development  Meat Technology “Hormonal Regulation of Lipolysis in Chicken Fat Cells”

9 ARS, Poultry Research Laboratory Georgetown, DE (1992-1994) Research Physiologist (Poultry)  Growth & Development Delmarva Poultry Industry “Improve the Lean-to-Fat Ratio of Broiler Chickens” UMES

10 ARS, Nutrient Conservation & Metabolism Lab Beltsville, MD (1994-1995) Research Dairy Scientist Research Dairy Scientist  Ruminant Nutrition Beltsville Agricultural Research Center

11 ARS, Microbial Food Safety Research Unit UMES, Princess Anne, MD (1995-present) Research Food Technologist  Predictive Microbiology  Outreach

12 Feature Presentation

13 Current Food Safety Approach Jack-in-the-Box HACCP HACCP  No testing Performance Standards Performance Standards  Detection  Enumeration  C. jejuni To test or not to test, that is the question

14 Traditional Culture Method Detection and Enumeration Pre-enrichment Pre-enrichment Selective enrichment Selective enrichment Selective plating Selective plating Confirmation Confirmation 5 to 7 Days

15 Rapid Detection Method BAX ® PCR system 24 to 30 h 10 2 10 3 10 4 10 5 10 6 10 7 10 1 10 0 Bailey, J.S. 1998. J. Food Prot. 61:792-795.

16 Sample Incubation Important Factors Target pathogen (< 1/ml) Food Factors Inhibitors Competition Pathogen Factors Injury Strain PCR Sensitivity 10 4 cells/ml PCR Detection Time

17 Sample Size Chicken carcass rinse Salmonella Incidence  4.9% for 10 ml  20.5% for 270 ml Surkiewicz et al., 1969. Food Tech.23:80-85.

18 Monte Carlo Simulation Extrapolation to other sample sizes Pathogen Incidence = 10/100 or 10% 100, 10 g Samples

19 Monte Carlo Simulation Extrapolation to other sample sizes Pathogen Incidence = 6/10 or 60% 10, 100 g Samples

20 Objectives To develop a standard curve for enumerating food pathogens as a function of PCR detection time. To develop a standard curve for enumerating food pathogens as a function of PCR detection time. To determine the effects of strain variation, meat type and microbial competition on the shape of the standard curve. To determine the effects of strain variation, meat type and microbial competition on the shape of the standard curve. To develop a Monte Carlo simulation model for enumeration of food pathogens as a function of sample size. To develop a Monte Carlo simulation model for enumeration of food pathogens as a function of sample size.

21 Materials and Methods Salmonella Salmonella  Typhimurium 14028  Worthington Starter cultures Starter cultures  37°C for 23 h at 150 opm  Brain heart infusion broth

22 Inoculated Pack Study Pre-enrichment Samples Sample Sample  25 g of chicken + 225 ml of buffered peptone water Inoculum Inoculum  10 0.7 to 10 6 CFU Incubation Incubation  37°C without shaking Sampling Sampling  0, 2, 4, 6, 8, 10, 12, 24 h

23 PCR Detection Time Score PCR Analysis PCR Analysis  BAX® System  One gel per sample Scoring System  0 = no band  1 = faint band  2 = < full band  3 = full band

24 02468101224MWSubsample (h) Score00123333 Example Total Score 15

25 Dataset Sterile breast meat and Typhimurium 14028

26 Type of Chicken Meat Sterile cooked (autoclaved) chicken meat

27 Previous Study Salmonella Typhimurium 14028 Oscar, 2002. Int. J. Food Microbiol. 76:177-190.

28 Previous Study Salmonella Typhimurium 14028 Oscar, 2002. Int. J. Food Microbiol. 76:177-190.

29 Conclusion Dilution may minimize effects of the food matrix on PCR detection time score. Dilution may minimize effects of the food matrix on PCR detection time score.

30 Strain Variation 117 Salmonella Isolates Chicken Operations

31 Strain variation at 40°C in brain heart infusion broth Oscar, 1998. J. Food Prot. 61:964-968. Typhimurium Worthington Previous Study

32 Results Naturally contaminated breast skin

33 Generation Time Variation among 45 strains of S. Enteritidis was: Variation among 45 strains of S. Enteritidis was:  22% at 9°C  4% at 37°C Fehlhaber and Kruger, 1998. J. Appl. Microbiol. 84: 945-949.

34 Conclusion Strain variation may not greatly affect PCR detection time score under optimal growth conditions. Strain variation may not greatly affect PCR detection time score under optimal growth conditions.

35 Microbial Competition

36 Microbial Competition Salmonella Typhimurium DT104

37 Microbial Competition Green fluorescent protein

38 Conclusion Microbial competition affected PCR detection time score and thus, needs to be incorporated into the standard curve. Microbial competition affected PCR detection time score and thus, needs to be incorporated into the standard curve.

39 Monte Carlo Simulation Modeling

40 Final Standard Curve 95% Prediction Interval

41 Simulation Model Excel + @Risk

42 Naturally Contaminated Chicken Not inoculated with Salmonella

43 Effect of Sample Size Simulation results

44 Conclusion Linear extrapolation of detection and enumeration results is not appropriate. Linear extrapolation of detection and enumeration results is not appropriate.

45 Future Research Enumeration Automated BAX® System Automated BAX® System  Cycle threshold rather than band width score. Other Pathogens and Foods Other Pathogens and Foods

46 The End Thank you for your attention! I will be glad to answer your questions

47 The End Thank you for your attention! I will be glad to answer your questions


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