Development and Validation of a New Robust Detection Method for Low-Content DNA Using ΔΔCq-Based Real-Time PCR with Optimized Standard Plasmids as a Control Sample.

Real-time polymerase chain reaction (PCR) is the gold standard for DNA detection in many fields, including food analysis. However, robust detection using a real-time PCR for low-content DNA samples remains challenging. In this study, we developed a robust real-time PCR method for low-content DNA using genetically modified (GM) maize at concentrations near the limit of detection (LOD) as a model. We evaluated the LOD of real-time PCR targeting two common GM maize sequences (P35S and TNOS) using GM maize event MON863 containing a copy of P35S and TNOS. The interlaboratory study revealed that the LOD differed among laboratories partly because DNA input amounts were variable depending on measurements of DNA concentrations. To minimize this variability for low-content DNA samples, we developed ΔΔCq-based real-time PCR. In this study, ΔCq and ΔΔCq are as follows: ΔCq = Cq (P35S or TNOS) - Cq (SSIIb; maize endogenous gene), ΔΔCq = ΔCq (analytical sample) - ΔCq (control sample at concentrations near the LOD). The presence of GM maize was determined based on ΔΔCq values. In addition, we used optimized standard plasmids containing SSIIb, P35S, and TNOS with ΔCq equal to the MON863 genomic DNA (gDNA) at concentrations near the LOD as a control sample. A validation study indicated that at least 0.2% MON863 gDNA could be robustly detected. Using several GM maize certified reference materials, we have demonstrated that this method was practical for detecting low-content GM crops and thus for validating GM food labeling. With appropriate standards, this method would be applicable in many fields, not just food.