Development of a reverse transcription quantitative polymerase chain reaction-based assay for broad coverage detection of African and Asian Zika virus lineages.
Yang YangGary WongBaoguo YeShihua LiShanqin LiHaixia ZhengQiang WangMifang LiangGeorge F GaoLei LiuYingxia LiuYu-Hai BiPublished in: Virologica Sinica (2017)
The Zika virus (ZIKV) is an arbovirus that has spread rapidly worldwide within recent times. There is accumulating evidence that associates ZIKV infections with Guillain-Barré Syndrome (GBS) and microcephaly in humans. The ZIKV is genetically diverse and can be separated into Asian and African lineages. A rapid, sensitive, and specific assay is needed for the detection of ZIKV across various pandemic regions. So far, the available primers and probes do not cover the genetic diversity and geographic distribution of all ZIKV strains. To this end, we have developed a one-step quantitative reverse transcription polymerase chain reaction (qRT-PCR) assay based on conserved sequences in the ZIKV envelope (E) gene. The detection limit of the assay was determined to be five RNA transcript copies and 2.94 × 10-3 50% tissue culture infectious doses (TCID50) of live ZIKV per reaction. The assay was highly specific and able to detect five different ZIKV strains covering the Asian and African lineages without nonspecific amplification, when tested against other flaviviruses. The assay was also successful in testing for ZIKV in clinical samples. Our assay represents an improvement over the current methods available for the detection ZIKV and would be valuable as a diagnostic tool in various pandemic regions.
Keyphrases
- zika virus
- dengue virus
- high throughput
- aedes aegypti
- loop mediated isothermal amplification
- real time pcr
- genetic diversity
- label free
- sars cov
- coronavirus disease
- escherichia coli
- transcription factor
- high resolution
- healthcare
- small molecule
- dna methylation
- autism spectrum disorder
- rna seq
- sensitive detection
- genome wide
- fluorescent probe
- fluorescence imaging
- genome wide identification