10-Plex Digital Polymerase Chain Reaction with Four-Color Melting Curve Analysis for Simultaneous KRAS and BRAF Genotyping.

Digital PCR (dPCR) is a promising method for performing liquid biopsies that quantifies nucleic acids more sensitively than real-time PCR. However, dPCR shows large fluctuations in the fluorescence intensity of droplets or wells due to insufficient PCR amplification in the small partitions, limiting the multiplexing capability of using the fluorescence intensity. In this study, we propose a measurement method that combines dPCR with melting curve analysis for highly multiplexed genotyping. A sample was digitized into a silicon chip with up to 2 × 104 wells in which asymmetric PCR was performed to obtain more single-stranded amplicons that were complementary to molecular beacon probes. Fluorescence images were captured while controlling the temperature of the chip, and the melting curve was measured for each well. Then, genotyping was performed by using the fluorescence intensity, the dye color of the probe, and the melting temperature (Tm). Because the Tm of the PCR products is not highly dependent on the amplification efficiency of PCR, genotyping accuracy is improved by using Tm values, enabling highly multiplexed genotyping. The concept was confirmed by simultaneously identifying wild-type KRAS, BRAF, and eight mutants of these genes (G12D, G12R, G12V, G13D, G12A, G12C, G12S, and V600E) through four-color melting curve analysis. To the best of our knowledge, this is the first demonstration of the genotyping of 10 DNA groups including single mutations of cancer-related genes by combining dPCR with four-color melting curve analysis.

KRAS genotyping by digital PCR combined with melting curve analysis.

Digital PCR (dPCR) has been developed as a method that can quantify nucleic acids more sensitively than real-time PCR. However, dPCR exhibits large fluctuations in the fluorescence intensity of the compartment, resulting in low accuracy. The main cause is most likely due to insufficient PCR. In this study, we proposed a new method that combines dPCR with melting curve analysis and applied that method to KRAS genotyping. Since the melting temperature (Tm) of the PCR product hardly depends on the amplification efficiency, genotyping accuracy is improved by using the Tm value. The results showed that the peaks of the distribution of the Tm values of DNA in the wells were 68.7, 66.3, and 62.6 °C for wild-type KRAS, the G12R mutant, and the G12D mutant, respectively, and the standard deviation of the Tm values was 0.2 °C for each genotype. This result indicates that the proposed method is capable of discriminating between the wild-type sequence and the two mutants. To the best of our knowledge, this is the first demonstration of the genotyping of single mutations by combining melting curve analysis and dPCR. The application of this approach could be useful for the quantification and genotyping of cancer-related genes in low-abundance samples.

System-on-fluidics immunoassay device integrating wireless radio-frequency-identification sensor chips.

A simple and sensitive point-of-care-test (POCT) device for chemiluminescence (CL) immunoassay was devised and tested. The device consists of a plastic flow-channel reactor and two wireless-communication sensor chips, namely, a photo-sensor chip and a temperature-sensor chip. In the flow-channel reactor, a target antigen is captured by an antibody immobilized on the inner wall of the flow-channel and detected with enzyme labeled antibody by using CL substrate. The CL signal corresponding to the amount of antigen is measured by a newly developed radio-frequency-identification (RFID) sensor, which enables batteryless operation and wireless data communication with an external reader. As for the POCT device, its usage environment, especially temperature, varies for each measurement. Hence, temperature compensation is a key issue in regard to eliminating dark-signal fluctuation, which is a major factor in deterioration of the precision of the POCT device. A two-stage temperature-compensation scheme was adopted. As for the first stage, the signals of two photodiodes, one with an open window and one with a sealed window, integrated on the photo-sensor chip are differentiated to delete the dark signal. As for the second stage, the differentiated signal fluctuation caused by a temperature variation is compensated by using the other sensor chip (equipped with a temperature sensor). The dark-level fluctuation caused by temperature was reduced from 0.24 to 0.02 pA/°C. The POCT device was evaluated as a CL immunoassay of thyroid-stimulating hormone (TSH). The flow rate of the CL reagent in the flow channel was optimized. As a result, the detection limit of the POCT device was 0.08 ng/ml (i.e., 0.4 µIU/ml).

An integrative in silico approach for discovering candidates for drug-targetable protein-protein interactions in interactome data.

BACKGROUND: Protein-protein interactions (PPIs) are challenging but attractive targets for small chemical drugs. Whole PPIs, called the 'interactome', have been emerged in several organisms, including human, based on the recent development of high-throughput screening (HTS) technologies. Individual PPIs have been targeted by small drug-like chemicals (SDCs), however, interactome data have not been fully utilized for exploring drug targets due to the lack of comprehensive methodology for utilizing these data. Here we propose an integrative in silico approach for discovering candidates for drug-targetable PPIs in interactome data. RESULTS: Our novel in silico screening system comprises three independent assessment procedures: i) detection of protein domains responsible for PPIs, ii) finding SDC-binding pockets on protein surfaces, and iii) evaluating similarities in the assignment of Gene Ontology (GO) terms between specific partner proteins. We discovered six candidates for drug-targetable PPIs by applying our in silico approach to original human PPI data composed of 770 binary interactions produced by our HTS yeast two-hybrid (HTS-Y2H) assays. Among them, we further examined two candidates, RXRA/NRIP1 and CDK2/CDKN1A, with respect to their biological roles, PPI network around each candidate, and tertiary structures of the interacting domains. CONCLUSION: An integrative in silico approach for discovering candidates for drug-targetable PPIs was applied to original human PPIs data. The system excludes false positive interactions and selects reliable PPIs as drug targets. Its effectiveness was demonstrated by the discovery of the six promising candidate target PPIs. Inhibition or stabilization of the two interactions may have potential therapeutic effects against human diseases.

Complete sequencing and characterization of 21,243 full-length human cDNAs.

As a base for human transcriptome and functional genomics, we created the "full-length long Japan" (FLJ) collection of sequenced human cDNAs. We determined the entire sequence of 21,243 selected clones and found that 14,490 cDNAs (10,897 clusters) were unique to the FLJ collection. About half of them (5,416) seemed to be protein-coding. Of those, 1,999 clusters had not been predicted by computational methods. The distribution of GC content of nonpredicted cDNAs had a peak at approximately 58% compared with a peak at approximately 42%for predicted cDNAs. Thus, there seems to be a slight bias against GC-rich transcripts in current gene prediction procedures. The rest of the cDNAs unique to the FLJ collection (5,481) contained no obvious open reading frames (ORFs) and thus are candidate noncoding RNAs. About one-fourth of them (1,378) showed a clear pattern of splicing. The distribution of GC content of noncoding cDNAs was narrow and had a peak at approximately 42%, relatively low compared with that of protein-coding cDNAs.