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Seven novel probe systems for real-time PCR provide absolute single-base discrimination, higher signaling, and generic components.

ABSTRACT: We have developed novel probe systems for real-time PCR that provide higher specificity, greater sensitivity, and lower cost relative to dual-labeled probes. The seven DNA Detection Switch (DDS)-probe systems reported here employ two interacting polynucleotide components: a fluorescently labeled probe and a quencher antiprobe. High-fidelity detection is achieved with three DDS designs: two internal probes (internal DDS and Flip probes) and a primer probe (ZIPR probe), wherein each probe is combined with a carefully engineered, slightly mismatched, error-checking antiprobe. The antiprobe blocks off-target detection over a wide range of temperatures and facilitates multiplexing. Other designs (Universal probe, Half-Universal probe, and MacMan probe) use generic components that enable low-cost detection. Finally, single-molecule G-Force probes employ guanine-mediated fluorescent quenching by forming a hairpin between adjacent C-rich and G-rich sequences. Examples provided show how these probe technologies discriminate drug-resistant Mycobacterium tuberculosis mutants, Escherichia coli O157:H7, oncogenic EGFR deletion mutations, hepatitis B virus, influenza A/B strains, and single-nucleotide polymorphisms in the human VKORC1 gene.

SUBMITTER: Murray JL

PROVIDER: S-EPMC4210465 | biostudies-literature | 2014 Nov

REPOSITORIES: biostudies-literature

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Seven novel probe systems for real-time PCR provide absolute single-base discrimination, higher signaling, and generic components.

Murray James L JL Hu Peixu P Shafer David A DA

The Journal of molecular diagnostics : JMD 20141101 6

We have developed novel probe systems for real-time PCR that provide higher specificity, greater sensitivity, and lower cost relative to dual-labeled probes. The seven DNA Detection Switch (DDS)-probe systems reported here employ two interacting polynucleotide components: a fluorescently labeled probe and a quencher antiprobe. High-fidelity detection is achieved with three DDS designs: two internal probes (internal DDS and Flip probes) and a primer probe (ZIPR probe), wherein each probe is combi ...[more]

PMID: 25307756

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Project description:BackgroundDigital polymerase chain reaction (dPCR) is an increasingly popular technology for detecting and quantifying target nucleic acids. Its advertised strength is high precision absolute quantification without needing reference curves. The standard data analytic approach follows a seemingly straightforward theoretical framework but ignores sources of variation in the data generating process. These stem from both technical and biological factors, where we distinguish features that are 1) hard-wired in the equipment, 2) user-dependent and 3) provided by manufacturers but may be adapted by the user. The impact of the corresponding variance components on the accuracy and precision of target concentration estimators presented in the literature is studied through simulation.ResultsWe reveal how system-specific technical factors influence accuracy as well as precision of concentration estimates. We find that a well-chosen sample dilution level and modifiable settings such as the fluorescence cut-off for target copy detection have a substantial impact on reliability and can be adapted to the sample analysed in ways that matter. User-dependent technical variation, including pipette inaccuracy and specific sources of sample heterogeneity, leads to a steep increase in uncertainty of estimated concentrations. Users can discover this through replicate experiments and derived variance estimation. Finally, the detection performance can be improved by optimizing the fluorescence intensity cut point as suboptimal thresholds reduce the accuracy of concentration estimates considerably.ConclusionsLike any other technology, dPCR is subject to variation induced by natural perturbations, systematic settings as well as user-dependent protocols. Corresponding uncertainty may be controlled with an adapted experimental design. Our findings point to modifiable key sources of uncertainty that form an important starting point for the development of guidelines on dPCR design and data analysis with correct precision bounds. Besides clever choices of sample dilution levels, experiment-specific tuning of machine settings can greatly improve results. Well-chosen data-driven fluorescence intensity thresholds in particular result in major improvements in target presence detection. We call on manufacturers to provide sufficiently detailed output data that allows users to maximize the potential of the method in their setting and obtain high precision and accuracy for their experiments.

Project description:BACKGROUND: In real-time PCR data analysis, the cycle threshold (CT) method is currently the gold standard. This method is based on an assumption of equal PCR efficiency in all reactions, and precision may suffer if this condition is not met. Nonlinear regression analysis (NLR) or curve fitting has therefore been suggested as an alternative to the cycle threshold method for absolute quantitation. The advantages of NLR are that the individual sample efficiency is simulated by the model and that absolute quantitation is possible without a standard curve, releasing reaction wells for unknown samples. However, the calculation method has not been evaluated systematically and has not previously been applied to a TaqMan platform. AIM: To develop and evaluate an automated NLR algorithm capable of generating batch production regression analysis. RESULTS: Total RNA samples extracted from human gastric mucosa were reverse transcribed and analysed for TNFA, IL18 and ACTB by TaqMan real-time PCR. Fluorescence data were analysed by the regular CT method with a standard curve, and by NLR with a positive control for conversion of fluorescence intensity to copy number, and for this purpose an automated algorithm was written in SPSS syntax. Eleven separate regression models were tested, and the output data was subjected to Altman-Bland analysis. The Altman-Bland analysis showed that the best regression model yielded quantitative data with an intra-assay variation of 58% vs. 24% for the CT derived copy numbers, and with a mean inter-method deviation of x 0.8. CONCLUSION: NLR can be automated for batch production analysis, but the CT method is more precise for absolute quantitation in the present setting. The observed inter-method deviation is an indication that assessment of the fluorescence conversion factor used in the regression method can be improved. However, the versatility depends on the level of precision required, and in some settings the increased cost effectiveness of NLR may justify the lower precision.

Dataset Information

Seven novel probe systems for real-time PCR provide absolute single-base discrimination, higher signaling, and generic components.

Publications

Seven novel probe systems for real-time PCR provide absolute single-base discrimination, higher signaling, and generic components.

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