Title |
Micro-droplet Digital Polymerase Chain Reaction and Real-Time Quantitative Polymerase Chain Reaction Technologies Provide Highly Sensitive and Accurate Detection of Zika Virus
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Published in |
Virologica Sinica, June 2018
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DOI | 10.1007/s12250-018-0037-y |
Pubmed ID | |
Authors |
Yuan Hui, Zhiming Wu, Zhiran Qin, Li Zhu, Junhe Liang, Xujuan Li, Hanmin Fu, Shiyu Feng, Jianhai Yu, Xiaoen He, Weizhi Lu, Weiwei Xiao, Qinghua Wu, Bao Zhang, Wei Zhao |
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/μL, with a standard curve R2 of 0.999 and amplification efficiency of 92.203%; however, a concentration as low as 1 copy/μL could not be detected. In comparison with RT-qPCR, the ddPCR method resulted in a linear range of 101-104 copy/μL and was able to detect concentrations as low as 1 copy/μL. Thus, for detecting ZIKV from clinical samples, RT-qPCR is a better choice for high-concentration samples (above 101 copy/μL), 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. |
X Demographics
Geographical breakdown
Country | Count | As % |
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Algeria | 1 | 33% |
Switzerland | 1 | 33% |
Unknown | 1 | 33% |
Demographic breakdown
Type | Count | As % |
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Members of the public | 3 | 100% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
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Unknown | 28 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
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Student > Master | 6 | 21% |
Student > Doctoral Student | 4 | 14% |
Researcher | 3 | 11% |
Student > Bachelor | 2 | 7% |
Student > Ph. D. Student | 2 | 7% |
Other | 2 | 7% |
Unknown | 9 | 32% |
Readers by discipline | Count | As % |
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Biochemistry, Genetics and Molecular Biology | 5 | 18% |
Medicine and Dentistry | 3 | 11% |
Environmental Science | 2 | 7% |
Engineering | 2 | 7% |
Agricultural and Biological Sciences | 1 | 4% |
Other | 3 | 11% |
Unknown | 12 | 43% |