Dataset Information

Micro-droplet Digital Polymerase Chain Reaction and Real-Time Quantitative Polymerase Chain Reaction Technologies Provide Highly Sensitive and Accurate Detection of Zika Virus.

ABSTRACT: The establishment of highly sensitive diagnostic methods is critical in the early diagnosis and control of Zika virus (ZIKV) and in preventing serious neurological complications of ZIKV infection. In this study, we established micro-droplet digital polymerase chain reaction (ddPCR) and real-time quantitative PCR (RT-qPCR) protocols for the detection of ZIKV based on the amplification of the NS5 gene. For the ZIKV standard plasmid, the RT-qPCR results showed that the cycle threshold (Ct) value was linear from 101 to 108 copy/?L, with a standard curve R2 of 0.999 and amplification efficiency of 92.203%; however, a concentration as low as 1 copy/?L could not be detected. In comparison with RT-qPCR, the ddPCR method resulted in a linear range of 101-104 copy/?L and was able to detect concentrations as low as 1 copy/?L. Thus, for detecting ZIKV from clinical samples, RT-qPCR is a better choice for high-concentration samples (above 101 copy/?L), while ddPCR has excellent accuracy and sensitivity for low-concentration samples. These results indicate that the ddPCR method should be of considerable use in the early diagnosis, laboratory study, and monitoring of ZIKV.

SUBMITTER: Hui Y

PROVIDER: S-EPMC6178550 | biostudies-literature | 2018 Jun

REPOSITORIES: biostudies-literature

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Micro-droplet Digital Polymerase Chain Reaction and Real-Time Quantitative Polymerase Chain Reaction Technologies Provide Highly Sensitive and Accurate Detection of Zika Virus.

Hui Yuan Y Wu Zhiming Z Qin Zhiran Z Zhu Li L Liang Junhe J Li Xujuan X Fu Hanmin H Feng Shiyu S Yu Jianhai J He Xiaoen X Lu Weizhi W Xiao Weiwei W Wu Qinghua Q Zhang Bao B Zhao Wei W

Virologica Sinica 20180614 3

The establishment of highly sensitive diagnostic methods is critical in the early diagnosis and control of Zika virus (ZIKV) and in preventing serious neurological complications of ZIKV infection. In this study, we established micro-droplet digital polymerase chain reaction (ddPCR) and real-time quantitative PCR (RT-qPCR) protocols for the detection of ZIKV based on the amplification of the NS5 gene. For the ZIKV standard plasmid, the RT-qPCR results showed that the cycle threshold (Ct) value wa ...[more]

PMID: 29931514

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Project description:Digital PCR in droplets (ddPCR) is an emerging method for more and more applications in DNA (and RNA) analysis. Special requirements when establishing ddPCR for analysis of genetically modified organisms (GMO) in a laboratory include the choice between validated official qPCR methods and the optimization of these assays for a ddPCR format. Differentiation between droplets with positive reaction and negative droplets, that is setting of an appropriate threshold, can be crucial for a correct measurement. This holds true in particular when independent transgene and plant-specific reference gene copy numbers have to be combined to determine the content of GM material in a sample. Droplets which show fluorescent units ranging between those of explicit positive and negative droplets are called 'rain'. Signals of such droplets can hinder analysis and the correct setting of a threshold. In this manuscript, a computer-based algorithm has been carefully designed to evaluate assay performance and facilitate objective criteria for assay optimization. Optimized assays in return minimize the impact of rain on ddPCR analysis. We developed an Excel based 'experience matrix' that reflects the assay parameters of GMO ddPCR tests performed in our laboratory. Parameters considered include singleplex/duplex ddPCR, assay volume, thermal cycler, probe manufacturer, oligonucleotide concentration, annealing/elongation temperature, and a droplet separation evaluation. We additionally propose an objective droplet separation value which is based on both absolute fluorescence signal distance of positive and negative droplet populations and the variation within these droplet populations. The proposed performance classification in the experience matrix can be used for a rating of different assays for the same GMO target, thus enabling employment of the best suited assay parameters. Main optimization parameters include annealing/extension temperature and oligonucleotide concentrations. The droplet separation value allows for easy and reproducible assay performance evaluation. The combination of separation value with the experience matrix simplifies the choice of adequate assay parameters for a given GMO event.

Dataset Information

Micro-droplet Digital Polymerase Chain Reaction and Real-Time Quantitative Polymerase Chain Reaction Technologies Provide Highly Sensitive and Accurate Detection of Zika Virus.

Publications

Micro-droplet Digital Polymerase Chain Reaction and Real-Time Quantitative Polymerase Chain Reaction Technologies Provide Highly Sensitive and Accurate Detection of Zika Virus.

Similar Datasets

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