Evaluation of a 5-Nuclease (TaqMan) Assay for the Detection of Virulent Strains of Yersinia enterocolitica in Raw Meat and Tofu Samples

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Abstract:

Culture methods for detecting virulent Yersinia enterocolitica require selective enrichment and a series of confirmatory tests that are time-consuming, costly, and laborious. The objective of this study was to evaluate a fluorogenic 5′-nuclease assay for detecting the enterotoxin yst gene of virulent Y. enterocolitica in pure cultures, inoculated ground pork samples, and naturally contaminated food samples. These results were then compared with ''gold standard'' methods recommended by the U.S. Food and Drug Administration in the Bacteriological Analytical Manual for detecting pathogenic Y. enterocolitica. The 5′-nuclease assay was able to identify the organism in 100% of the repetitions when 102 CFU/ml or more organisms were present in pure cultures and 103 CFU/g or more organisms were present in ground pork. Similar recovery efficiency on cefsulodin-irgasan-novobiocin (CIN) agar plates was only evident when 105 CFU/ml or more organisms were present in pure culture and 106 CFU/g or more organisms were present in inoculated ground pork. The 5′-nuclease assay indicated a contamination rate of 35.5% (94/265) in various meats and tofu, whereas the CIN plating method indicated a contamination rate of 28.3% (75/265). This resulted in 100% sensitivity and 64.5% specificity for the 5′-nuclease assay when compared with the standard culture recovery method. Only 75% (60/80) of the Yersinia spp. isolated on CIN was identified as containing a virulence plasmid by autoagglutination and crystal violet binding tests. These results indicate that the true rate of contamination of virulent Y. enterocolitica in pork and other processed meats and foods is being underestimated using current detection methods. This study demonstrates the potential of the 5′-nuclease assay for rapidly and specifically detecting virulent Y. enterocolitica in processed foods with the added advantage of being an automated detection system with high-throughput capability.

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Document Type: Research Article

Affiliations: 1: Department of Animal Sciences and Industry, Kansas State University, Manhattan, Kansas 66506, USA 2: Food Animal Health and Management Center, Kansas State University, Manhattan, Kansas 66506, USA 3: Department of Diagnostic Medicine and Pathobiology, Kansas State University, Manhattan, Kansas 66506, USA

Publication date: March 1, 2001

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