A novel quantum dot based nanoassay for high resolution copy number variation detection and DNA methylation quantification

Abstract

Abstract Background: Detection of DNA copy number variation (CNV) is not only fundamental to study molecular etiology of cancer but also provides a potential molecular diagnostics for cancer detection. Nonetheless, current techniques are not able to reliably differentiate less than a twofold change in copy number. The hypermethylation of the cytosines at CpG islands in the promoter regions of tumor suppressor genes has been proved to be a valuable epigenetic biomarker for early cancer diagnosis. However, current ways of quantifying DNA methylation heavily rely on PCR, which is believed to have only twofold resolution. This abstract presents a novel gene quantification platform named quantum dot (QD) Electrophoretic Mobility Shift Assay (QEMSA). This nanoassay demonstrates a remarkable resolution, capable of distinguishing a 1.1-fold (~9%) difference in target copy number. QEMSA could be very useful when a precise measurement of DNA copy number is required. Methods and Results: QEMSA employs a QD to physically transform the target copy number into different electrophoretic mobility levels. DNA molecules self assemble onto the QD surface through the streptavidin-biotin interaction to form a QD-DNA nanocomplex with certain DNA to QD ratios (N). The working principle of the QEMSA is analogous to a horse wagon, of which the QD serves as a nano wagon and harnesses the horsepower from the force exerted on the DNA molecules in the electric field. Intuitively, the more DNA molecules on one QD, the more horsepower and the faster the nanocomplex migrates. We have developed a mathematic model which predicts the electrophoretic migration distance Dm is proportional to ln(N). The electrophoretic migration distances of the nanocomplex are plotted against N in logarithmic scale (Thereafter refers to as the migration curve). The linear regression of the migration curves with R2=0.99 suggests the data agree well with our model. Using QEMSA, tiny differences in copy number can be magnified hence reliably detected by enlarging the separation distance between nanocomplexes with different N values. As a result, we have successfully quantified a 1.1-fold dilution series (~9% difference). A spike-in control experiment is performed by mixing the synthetic DNA fragments from the Rsf-1 gene and the reference sequence at various ratios. A single duplication on only one allele results in a total of 3 copies per cell therefore a target/reference ratio of 1.5. The fragments are tagged with biotin using biotinylated primer. The observed ratios are plotted against the expected ratios. A good linear correlation with R2=0.99 is obtained. Using same approach, the Rsf-1 gene is found being amplified by ~8.5 fold in the ovarian cancer cell line OVCAR3, which is in good agreement with the results analyzed by SNP array but with less detection noise. Two dilution series of the methylated DNA with dilution factors of 1.5 and 1.25 respectively are spiked with 100ng normal DNA to simulate different DNA methylation levels. Both the methylated DNA and the normal DNA undergo the bisulfite treatment. The methylated p16/CDK2A promoter region is tagged with biotin using methylation specific PCR. QEMSA successfully generates the standard migration curves for both dilution series. The same dilution series are analyzed in triplicates using qPCR, the results of which show larger fluctuation. Conclusion: In summary, we have demonstrated a promising high resolution gene copy number quantification platform using a quantum dot nanotechnology. The novel platform has been successfully applied to detect CNV and quantify DNA methylation level in human cancer.