Journal article
Rapid detection of Salmonella enterica in food samples by a novel approach with combination of sample concentration and direct PCR
National Food Institute, Technical University of Denmark1
Department of Health Technology, Technical University of Denmark2
Research Group for Analytical and Predictive Microbiology, National Food Institute, Technical University of Denmark3
Department of Biotechnology and Biomedicine, Technical University of Denmark4
Foodborne salmonellosis remains a major economic burden worldwide and particularly for food industries. The diverse and complexity of food matrices pose great challenges for rapid and ultra-sensitive detection of Salmonella in food samples. In this study, combination of pathogen pre-concentration with rapid molecular identification is presented to overcome these challenges.
This combination enabled effective real-time PCR detection of low levels of Salmonella enterica serovar Typhimurium without culture enrichment. Anti-salmonella antibody, immobilized on protein AG-magnetic beads, could efficiently concentrate Salmonella Typhimurium with a capturing efficiency of 95%.
In the direct PCR, a strong linear relationship between bacteria concentration and the number of cycles was observed with a relative PCR efficiency of ∼92% resulting in a limit of detection (LoD) of ∼2 CFU/mL. Analysis of spiked food samples that include vegetable salad, egg yolk, egg white, whole egg and minced pork meat has validated the precision of the method.
A relative accuracy of 98.3% with a sensitivity of 91.6% and specificity of 100% was achieved in the Salmonella spiked food samples. The use of a Phusion hot start DNA polymerase with a high tolerance to possible PCR inhibitors allowed the integration of direct PCR, and thereby reducing the duration of analysis to less than 3 hours.
The Cohen's kappa index showed excellent agreement (0.88) signifying the capability of this method to overcome the food matrix effects in rapid and ultra-sensitive detection of Salmonella in food. This approach may lay a future platform for the integration into a Lab-on-a-chip system for online monitoring of foodborne pathogens.
Language: | English |
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Year: | 2019 |
Pages: | 224-230 |
ISSN: | 18734235 and 09565663 |
Types: | Journal article |
DOI: | 10.1016/j.bios.2018.09.078 |
ORCIDs: | Chidambara, Vinayaka Aaydha , Ngo Anh, Tien , Dave, Vivek Priy , Wolff, Anders , Bang, Dang Duong and 0000-0003-2948-9471 |