P174: Enumeration of Salmonella with the Polymerase Chain
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); [email protected]
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 102 CFU per ml to a full
band at 107 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 (PCRDTS) 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
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 37C 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 100 to 106 CFU per 25 g of chicken.
At 0, 2, 4, 6, 8, 10, 12 and 24 h of incubation at 37C, a one ml
subsample was collected for PCR analysis using the Qualicon
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 PCRDTS from
zero to 24 by summing the scores for the eight subsample lanes
in the gel.
Standard curve. The PCRDTS 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 PCRDTS and sample size was
created in an Excel spreadsheet and was simulated with @Risk
(Figure 2). The PCRDTS of 12 naturally contaminated 25 g
samples of chicken were used to define the frequency of
occurrence of PCRDTS 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 PCRDTS 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.
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,
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