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Journal of food protection

Evaluation of Rapid Molecular Detection Assays for Salmonella in Challenging Food Matrices at Low Inoculation Levels and Using Difficult-to-Detect Strains.


PMID 26319716

Abstract

Assays for detection of foodborne pathogens are generally initially evaluated for performance in validation studies carried out according to guidelines provided by validation schemes (e.g., AOAC International or the International Organization for Standardization). End users often perform additional validation studies to evaluate the performance of assays in specific matrices (e.g., specific foods or raw material streams of interest) and with specific pathogen strains. However, these types of end-user validations are typically not well defined. This study was conducted to evaluate a secondary end user validation of four AOAC-validated commercial rapid detection assays (an isothermal nucleic acid amplification, an immunoassay, and two PCR-based assays) for their ability to detect Salmonella in two challenging matrices (dry pet food and dark chocolate). Inclusivity was evaluated with 68 diverse Salmonella strains at low population levels representing the limit of detection (LOD) for each assay. One assay detected all strains at the LOD, two assays detected multiple strains only at 10 times the LOD, and the fourth assay failed to detect two strains (Salmonella bongori and S. enterica subsp. houtenae) even at 1,000 times the LOD; this assay was not further evaluated. The three remaining assays were subsequently evaluated for their ability to detect five selected Salmonella strains in food samples contaminated at fractional levels. Unpaired comparisons revealed no significant difference between the results for each given assay and the results obtained with the reference assay. However, analysis of paired culture-confirmed results revealed assay false-negative rates of 4 to 26% for dry pet food and 12 to 16% for dark chocolate. Overall, our data indicate that rapid assays may have high false-negative rates when performance is evaluated under challenging conditions, including low-moisture matrices, strains that are difficult to detect, injured cells, and low inoculum levels.