| Detection of the presence of a target organism using nucleic acids is a commonly used method in a multitude of circumstances, namely, metagenome characterization for monitoring community ecology and estimating biodiversity, species identification, medical diagnostics, and forensics. Nucleic acid detection by amplification using PCR, for example, is an invaluable technique when the organisms cannot be cultivated in artificial media in a laboratory. This method, however, faces some commonly encountered challenges such as false-detection, cross-reactivity, and low sensitivity exacerbated by the presence of excess unrelated nucleic acid in the background. Excess background may interfere with the detection, per se. In PCR, the primers may misprime with the background nucleic acid resulting in false-positive detection. Specific primers can completely fail to prime an otherwise detectable amount of target because of the presence of excess background DNA.;A new approach for ultrasensitive PCR detection, by enrichment of rare target from abundant background is also described and successfully demonstrated. This approach describes cot-fractionation by combining the classic technique of cot-analysis with the newly described crab duplex-specific nuclease. The rare target was shown to be detected after enrichment, and not to be detected without it. The methodology described may be applied toward improving detection of rare targets in pathogen detection.;This study demonstrated a PCR primer design and primer-implementation method, for detection of a target present in vast excess of background nucleic acid, using dengue virus cDNA/RNA and human genome DNA/RNA. The primer sequences were designed to be 'human-blind' by ensuring their absence from the human genome and sequence distance of at least two mismatches. Additionally, a multiple-primer-reagent strategy is described and demonstrated for one-step detection of any of the four subtypes of dengue virus, without resorting to performing separate tests. These primers showed high analytical reactivity for dengue virus and were predicted to detect 99% of the strains analyzed computationally. The method described may be applied especially toward detection of RNA viruses in clinical samples, among others. |
