Issue 38, 2022

Real-time and visual detection of viable Salmonella in milk by a competitive annealing mediated isothermal amplification (CAMP) combined with propidium monoazide (PMA)

Abstract

Salmonella is a common pathogen in raw milk. The conventional isothermal amplification assay cannot distinguish viable bacteria from dead bacteria, which may cause false positive results or overestimate the number of viable bacteria. This study proposed a competitive annealing mediated isothermal amplification (CAMP) combined with propidium monoazide (PMA) for real-time and visual detection of viable Salmonella in milk. Based on the invA gene, specific CAMP primers were constructed. Moreover, the primers for accelerating the CAMP reaction were also designed and added to the reaction system. The real-time PMA-CAMP showed a LOD of 102 CFU mL−1 for quantitative detection of viable Salmonella in spiked milk samples, and the recovery rate was 80–106%. The visual PMA-CAMP can be performed under isothermal conditions using a portable dry bath, and the positive results can be directly observed by the colorimetric change from violet to sky blue. Without enrichment step, viable Salmonella could be detected with a LOD of 102 CFU mL−1. With enrichment step, even if the initial inoculation level is 1 CFU mL−1, the visual PMA-CAMP could still detect the presence of viable Salmonella in milk samples. Therefore, the developed PMA-CAMP assays are suitable for the monitoring of viable Salmonella contamination in milk.

Graphical abstract: Real-time and visual detection of viable Salmonella in milk by a competitive annealing mediated isothermal amplification (CAMP) combined with propidium monoazide (PMA)

Supplementary files

Article information

Article type
Paper
Submitted
17 Jul 2022
Accepted
13 Sep 2022
First published
13 Sep 2022

Anal. Methods, 2022,14, 3773-3779

Real-time and visual detection of viable Salmonella in milk by a competitive annealing mediated isothermal amplification (CAMP) combined with propidium monoazide (PMA)

X. Chen, W. Li and Y. Ma, Anal. Methods, 2022, 14, 3773 DOI: 10.1039/D2AY01150F

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