Development of a Duplex TaqMan Real-Time Polymerase Chain Reaction for Accurate Identification and Quantification of Salmonella Enteritidis from Laboratory Samples and Contaminated Chicken Eggs

开发一种双重 TaqMan 实时聚合酶链式反应,用于准确鉴定和定量实验室样品和受污染鸡蛋中的肠炎沙门氏菌

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Abstract

Salmonella enteritidis is a major causative agent of foodborne illnesses worldwide. As the traditional serotyping and quantification methods are labor-intensive, time-consuming, and expensive, faster and more convenient molecular diagnostic methods are needed. In this study, we developed and validated a rapid duplex TaqMan real-time polymerase chain reaction (PCR) for the accurate identification and quantification of S. enteritidis. The primers and TaqMan probes were designed based on the S. enteritidis-specific gene lygD and the Salmonella genus-specific gene invA. The melt curve and gel electrophoresis analysis showed that the designed primers had potent specificity for the amplification of lygD and invA. The duplex real-time PCR specifically identified S. enteritidis from a panel of 40 Salmonella strains that represented 29 serovars and 12 non-Salmonella organisms. The duplex real-time PCR assay detected four copies of S. enteritidis DNA per reaction. The intra- and inter- assays indicated a high degree of reproducibility. The real-time PCR could accurately detect and quantify S. enteritidis in chicken organs after Salmonella infection. Furthermore, the assay identified 100% of the S. enteritidis and Salmonella genus isolates from chicken egg samples with superior sensitivity after 6 h of pre-enrichment compared to the traditional culture method. Additionally, the most-probable-number (MPN) combined with qPCR and a shortened incubation time (MPN-qPCR-SIT) method was developed for the population determination of S. enteritidis and compared with various enumeration methods. Thus, we have established and validated a new duplex real-time PCR assay and MPN-qPCR-SIT method for the accurate detection and quantification of S. enteritidis, which could contribute to meeting the need for fast detection and identification in prevention and control measures for food safety.

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