Abstract
Rare variant enrichment and quantification was achieved by allele-specific, competitive blocker, digital PCR for aiming to provide a noninvasive method for detecting rare DNA variants from circulating cells. The allele-specific blocking chemistry improves sensitivity and lowers assay cost over previously described digital PCR methods while the instrumentation allowed for rapid thermal cycling for faster turnaround time. Because the digital counting of the amplified variants occurs in the presence of many wild-type templates in each well, the method is called “quasi-digital PCR”. A spinning disk was used to separate samples into 1000 wells, followed by rapid-cycle, allele-specific amplification in the presence of a molecular beacon that serves as both a blocker and digital indicator. Monte Carlo simulations gave similar results to Poisson distribution statistics for mean number of template molecules and provided an upper and lower bound at a specified confidence level and accounted for input DNA concentration variation. A 111 bp genomic DNA fragment including the BRAF p.V600E mutation (c.T1799A) was amplified with quasi-digital PCR using cycle times of 23 s. Dilution series confirmed that wild-type amplification was suppressed and that the sensitivity for the mutant allele was <0.01 % (43 mutant alleles amongst 500,000 wild-type alleles). The Monte Carlo method presented here is publically available on the internet and can calculate target concentration given digital data or predict digital data given target concentration.
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Acknowledgments
The authors thank the University of Utah Research Foundation and the Utah Science Technology and Research initiative (USTAR) in conjunction with the American Recovery and Reinvestment Act (ARRA) for kindly supporting this work. We also thank Carl Wittwer’s lab group and Bruce Gale’s lab group for valuable advice pertaining to this research.
Conflicts of interest
Authors Scott Sundberg, Carl Wittwer and Bruce Gale hold patent rights pertaining to the spinning disk technology used in this work. The authors declare that they have no other conflicts of interest.
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Supplementary Fig 1
Screenshots of the uCountSM (Monte Carlo) web application (http://www.dna.utah.edu/ucount/uc.html), showing both A)analysis and B) prediction modes. In the analysis window (A), the total number of reactions, the number of observed positive reactions, and the desired confidence level for template concentrations are input. The outputs include the mean number of template copies present, the upper and lower bounds of the confidence interval, and the distribution of probable template concentrations. In the prediction window (B), the total number of reactions, the mean number of template copies present in the total PCR volume (volume of one digital PCR times the number of digital PCRs) and the desired confidence level are input. Outputs include the expected mean number of positive reactions, the upper and lower bounds of the confidence interval, and the distribution of positive reactions are output. (GIF 264 kb)
(GIF 264 kb)
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Sundberg, S.O., Wittwer, C.T., Zhou, L. et al. Quasi-digital PCR: Enrichment and quantification of rare DNA variants. Biomed Microdevices 16, 639–644 (2014). https://doi.org/10.1007/s10544-014-9866-0
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DOI: https://doi.org/10.1007/s10544-014-9866-0