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. 2008 Jun;74(12):3831-8.
doi: 10.1128/AEM.02743-07. Epub 2008 Apr 18.

Development and experimental validation of a predictive threshold cycle equation for quantification of virulence and marker genes by high-throughput nanoliter-volume PCR on the OpenArray platform

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Development and experimental validation of a predictive threshold cycle equation for quantification of virulence and marker genes by high-throughput nanoliter-volume PCR on the OpenArray platform

Robert D Stedtfeld et al. Appl Environ Microbiol. 2008 Jun.

Abstract

Development of quantitative PCR (QPCR) assays typically requires extensive screening within and across a given species to ensure specific detection and lucid identification among various pathogenic and nonpathogenic strains and to generate standard curves. To minimize screening requirements, multiple virulence and marker genes (VMGs) were targeted simultaneously to enhance reliability, and a predictive threshold cycle (C(T)) equation was developed to calculate the number of starting copies based on an experimental C(T). The empirical equation was developed with Sybr green detection in nanoliter-volume QPCR chambers (OpenArray) and tested with 220 previously unvalidated primer pairs targeting 200 VMGs from 30 pathogens. A high correlation (R(2) = 0.816) was observed between the predicted and experimental C(T)s based on the organism's genome size, guanine and cytosine (GC) content, amplicon length, and stability of the primer's 3' end. The performance of the predictive C(T) equation was tested using 36 validation samples consisting of pathogenic organisms spiked into genomic DNA extracted from three environmental waters. In addition, the primer success rate was dependent on the GC content of the target organisms and primer sequences. Targeting multiple assays per organism and using the predictive C(T) equation are expected to reduce the extent of the validation necessary when developing QPCR arrays for a large number of pathogens or other targets.

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Figures

FIG. 1.
FIG. 1.
Impact of gDNA from various environmental water samples and primer stability on specificity and sensitivity. The left panel shows the percentages of targeted and nontargeted primer assays displaying amplification at various dilutions of organisms spiked in gDNA from environmental samples. Error bars represent the standard deviations between replicates performed on three plates. The right panel shows the sum of the GC bases on the terminal 3′ end (various-size circles) versus the percentages of primer sets displaying false-positive amplification when targets are spiked into background gDNA and not spiked into background gDNA. bkg, background.
FIG. 2.
FIG. 2.
Experimental versus predicted CT using predictive CT equation. The results obtained are with the primer designed to establish the predictive CT equation. The equation is derived using amplicon length, starting genomic copies, number of base pairs in the target organism's genome, GC content of the target organism's genome, and theoretical Tm of the last 7 bases of the primer's 3′ end. Errors bars represent the standard deviations of experimental CT between replicates on three plates.
FIG. 3.
FIG. 3.
Success rate (%) of all assays targeting an organism. Success rate is defined as the sum of all true-positive and -negative assays divided by the sum of all assays targeting a single organism. The success rate was taken as an average of all 36 validation sample mixtures prepared to validate the predictive CT equation.
FIG. 4.
FIG. 4.
Distribution of predicted starting copy numbers using predictive CT equation and standard curves for validation samples and primers designed to validate the predictive CT equation. Note that the x axes of the three panels have different scales. The templates of all the organisms were spiked at either 10, 100, or 1,000 genomic copies per reaction well (indicated by the dotted lines). Error bars represent the standard deviations between three replicates performed on the same OpenArray plates.
FIG. 5.
FIG. 5.
Factors potentially influencing quantitative inaccuracies as observed with primers and samples designed to establish the predictive CT equation. In the left panel, a box plot shows the distribution of PCR efficiency for target organisms spiked into gDNA from complex environmental waters and a control (no background). The right panel shows the cumulative frequency distributions of the standard deviations of CT determined between three separate OpenArray plates with various transcript concentrations.

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