Development of a rapid method to quantify Salmonella Typhimurium using a combination of MPN with qPCR and a shortened time incubation

Food Microbiol. 2017 Aug:65:7-18. doi: 10.1016/j.fm.2017.01.013. Epub 2017 Jan 30.

Abstract

A novel method was developed for the specific quantification of S. Typhimurium using a most-probable-number (MPN) combined with qPCR and a shortened incubation time (MPN-qPCR-SIT). For S. Typhimurium enumeration, dilutions of samples were transferred into three wells on a microtiter plate and the plate was incubated for 4 h. The S. Typhimurium presence in the wells was identified using a qPCR and populations were determined based on an MPN calculation. The R2 between the MPN-qPCR-SIT and conventional MPN exhibited a high level of correlation (0.9335-0.9752), suggesting that the MPN-qPCR-SIT offers a reliable alternative method for S. Typhimurium quantification. Although plating and qPCR were limited in their ability to detect low levels of S. Typhimurium (e.g. 0.18 log MPN/ml), these levels could be successfully detected with the MPN-qPCR-SIT. Chicken breast samples inoculated with S. Typhimurium were incubated at 0, 4, and 24 h and incubated samples were subjected to microbiome analysis. Levels of Salmonella and Enterobacteriaceae increased significantly with incubation time. The obvious benefits of the MPN-qPCR-SIT are: 1) a further confirmation step is not required, 2) the detection limit is as low as conventional MPN, but 3) is more rapid, requiring approximately 7 h to simultaneously complete quantification.

Keywords: Detection; Quantification; Rapid; Salmonella Typhimurium; Simple.

Publication types

  • Evaluation Study

MeSH terms

  • Animals
  • Bacterial Load
  • Colony Count, Microbial
  • Food Microbiology / methods*
  • Limit of Detection
  • Microbiota
  • Poultry / microbiology
  • Real-Time Polymerase Chain Reaction / methods*
  • Salmonella typhimurium / genetics
  • Salmonella typhimurium / growth & development*
  • Salmonella typhimurium / isolation & purification*
  • Sensitivity and Specificity
  • Time Factors