A real-time PCR for the detection of Salmonella Enteritidis in poultry meat and consumption eggs
- PMID: 17512995
- DOI: 10.1016/j.mimet.2007.04.013
A real-time PCR for the detection of Salmonella Enteritidis in poultry meat and consumption eggs
Abstract
A robust duplex 5' nuclease (TaqMan) real-time PCR was developed and in-house validated for the specific detection of Salmonella enterica subspecies enterica serovar Enteritidis in whole chicken carcass rinses and consumption eggs. The assay uses specifically designed primers and a TaqMan probe to target the Prot6e gene located on the S. Enteritidis specific 60-kb virulence plasmid. As an internal amplification control to monitor Salmonella DNA in the sample, a second primer/TaqMan probe set detects simultaneously the Salmonella specific invA gene. The assay identified correctly 95% of the 79 Salmonella Enteritidis strains tested comprising 19 different phage types. None of the 119 non-Enteritidis strains comprising 54 serovars was positive for the Prot6e gene. The assay detection probability was for 10(2) or more genome equivalents 100% and for 10 equivalents 83%. A pre-PCR sample preparation protocol including a pre-enrichment step in buffered peptone water, followed by DNA extraction was applied on low levels of artificially contaminated whole chicken carcass rinses and eggs from hens as well as 25 potentially naturally contaminated chickens. The detection limit was less than three CFU per 50 ml carcass rinse or 10 ml egg. The sensitivity and specificity compared to the traditional culture-based detection method and serotyping were both 100%. Twenty-five potentially naturally contaminated chickens were compared by the real-time PCR and the traditional cultural isolation method resulting in four Salmonella positive samples of which two were positive for the Prot6e gene and serotyped as S. Enteritidis. We show also that Salmonella isolates which have a rough lipopolysaccharide structure could be assigned to the serovar Enteritidis by the real-time PCR. This methodology can contribute to meet the need of fast identification and detection methods for use in monitoring and control measures programmes.
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