Development of a real-time nucleic acid sequence-based amplification assay for the rapid detection of Salmonella spp. from food.

Journal: Brazilian journal of microbiology : [publication of the Brazilian Society for Microbiology]
PMID:

Abstract

Salmonella spp. is one of the most common foodborne infectious pathogen. This study aimed to develop a real-time nucleic acid sequence-based amplification (NASBA) assay for detecting Salmonella in foods. Primers and a molecular beacon targeting the Salmonella-specific xcd gene were designed for mRNA transcription, and 48 Salmonella and 18 non-Salmonella strains were examined. The assay showed a high specificity and low detection limit for Salmonella (7 × 10 CFU/mL) after 12 h of pre-enrichment. Importantly, it could detect viable cells. Additionally, the efficacy of the NASBA assay was examined in the presence of pork background microbiota; it could detect Salmonella cells at 9.5 × 10 CFU/mL. Lastly, it was successfully used to detect Salmonella in pork, beef, and milk, and its detection limit was as low as 10 CFU/25 g (mL). The real-time NASBA assay developed in this study may be useful for rapid, specific, and sensitive detection of Salmonella in food of animal origin.

Authors

  • Ligong Zhai
    College of Food Science and Technology, Key Laboratory of Food Processing and Quality Control, Ministry of Agriculture of China, Nanjing Agricultural University, Nanjing, 210095, People's Republic of China.
  • Hongxia Liu
    College of Food Science and Technology, Key Laboratory of Food Processing and Quality Control, Ministry of Agriculture of China, Nanjing Agricultural University, Nanjing, 210095, People's Republic of China.
  • Qiming Chen
    College of Food Science and Technology, Key Laboratory of Food Processing and Quality Control, Ministry of Agriculture of China, Nanjing Agricultural University, Nanjing, 210095, People's Republic of China.
  • Zhaoxin Lu
    College of Food Science and Technology, Key Laboratory of Food Processing and Quality Control, Ministry of Agriculture of China, Nanjing Agricultural University, Nanjing, 210095, People's Republic of China.
  • Chong Zhang
    Department of Big Data Management and Application, School of International Economics and Management, Beijing Technology and Business University, Beijing 100048, China.
  • Fengxia Lv
    College of Food Science and Technology, Key Laboratory of Food Processing and Quality Control, Ministry of Agriculture of China, Nanjing Agricultural University, Nanjing, 210095, People's Republic of China.
  • Xiaomei Bie
    College of Food Science and Technology, Key Laboratory of Food Processing and Quality Control, Ministry of Agriculture of China, Nanjing Agricultural University, Nanjing, 210095, People's Republic of China. bxm43@njau.edu.cn.