Dataset Information

Validation of Droplet Digital Polymerase Chain Reaction for Salmonella spp. Quantification.

ABSTRACT: Salmonellosis is a foodborne disease caused by Salmonella spp. Although cell culture is the gold standard for its identification, validated molecular methods are becoming an alternative, because of their rapidity, selectivity, and specificity. A simplex and duplex droplet digital polymerase chain reaction (ddPCR)-based method for the identification and quantification of Salmonella using ttr, invA, hilA, spaQ, and siiA gene sequences was validated. The method has high specificity, working interval between 8 and 8,000 cp/?L in ddPCR reaction, a limit of detection of 0.5 copies/?L, and precision ranging between 5 and 10% measured as a repeatability standard deviation. The relative standard measurement uncertainty was between 2 and 12%. This tool will improve food safety in national consumption products and will increase the competitiveness in agricultural product trade.

SUBMITTER: Villamil C

PROVIDER: S-EPMC7358645 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Publications

Validation of Droplet Digital Polymerase Chain Reaction for Salmonella spp. Quantification.

Villamil Carolina C Calderon Martha Nancy MN Arias Maria Mercedes MM Leguizamon John Emerson JE

Frontiers in microbiology 20200707

Salmonellosis is a foodborne disease caused by Salmonella spp. Although cell culture is the gold standard for its identification, validated molecular methods are becoming an alternative, because of their rapidity, selectivity, and specificity. A simplex and duplex droplet digital polymerase chain reaction (ddPCR)-based method for the identification and quantification of Salmonella using ttr, invA, hilA, spaQ, and siiA gene sequences was validated. The method ha ...[more]

PMID: 32733415

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Project description:Digital PCR in droplets (ddPCR) is an emerging method for more and more applications in DNA (and RNA) analysis. Special requirements when establishing ddPCR for analysis of genetically modified organisms (GMO) in a laboratory include the choice between validated official qPCR methods and the optimization of these assays for a ddPCR format. Differentiation between droplets with positive reaction and negative droplets, that is setting of an appropriate threshold, can be crucial for a correct measurement. This holds true in particular when independent transgene and plant-specific reference gene copy numbers have to be combined to determine the content of GM material in a sample. Droplets which show fluorescent units ranging between those of explicit positive and negative droplets are called 'rain'. Signals of such droplets can hinder analysis and the correct setting of a threshold. In this manuscript, a computer-based algorithm has been carefully designed to evaluate assay performance and facilitate objective criteria for assay optimization. Optimized assays in return minimize the impact of rain on ddPCR analysis. We developed an Excel based 'experience matrix' that reflects the assay parameters of GMO ddPCR tests performed in our laboratory. Parameters considered include singleplex/duplex ddPCR, assay volume, thermal cycler, probe manufacturer, oligonucleotide concentration, annealing/elongation temperature, and a droplet separation evaluation. We additionally propose an objective droplet separation value which is based on both absolute fluorescence signal distance of positive and negative droplet populations and the variation within these droplet populations. The proposed performance classification in the experience matrix can be used for a rating of different assays for the same GMO target, thus enabling employment of the best suited assay parameters. Main optimization parameters include annealing/extension temperature and oligonucleotide concentrations. The droplet separation value allows for easy and reproducible assay performance evaluation. The combination of separation value with the experience matrix simplifies the choice of adequate assay parameters for a given GMO event.

Dataset Information

Validation of Droplet Digital Polymerase Chain Reaction for Salmonella spp. Quantification.

Publications

Validation of Droplet Digital Polymerase Chain Reaction for <i>Salmonella</i> spp. Quantification.

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