A simple and rapid approach to prepare Sindbis and West Nile viral RNA controls for differentiation between positive samples and laboratory contamination.

Micah Dimaculangan, Siewert C Wiid,Phillip A Bester,Tumelo R Sekee,Felicity J Burt

Journal of virological methods(2020)

引用 0|浏览11
暂无评分
摘要
Reverse transcription-polymerase chain reaction (RT-PCR) is frequently used for surveillance and diagnosis of arboviruses and emerging viruses. A disadvantage of RT-PCR assays, especially nested assays, is the potential for false-positive results caused by laboratory contamination from either positive controls or positive samples. Positive reactors usually require sequence determination for confirmation which delay timeous reporting of a result. Thus, the aim of the study was to use a simple technique to prepare a positive control allowing true positives to be differentiated from laboratory contamination based on size differentiation for conventional PCR, or melt temperatures for real time assays. A flavivirus positive control and an alphavirus positive control were prepared for two RT-PCR assays that we are currently using for arbovirus surveillance in South Africa. Primers targeting a region of the partial genes of interest cloned in pGEM®T-easy were modified at the 5' ends with non-viral nucleotides. The resulting amplicons were circularised, resulting in pGEM®T-easy constructs with 51 and 65 non-viral bases inserted into the partial flaviviral and alphaviral genes respectively and used as template for transcribing RNA. Sequence analysis was used to confirm the manipulation of the partial genes. Using virus specific primer pairs, viral RNA could be readily differentiated from the modified positive controls either by size differentiation, or melt temperature in a SYBR®Green real time RT-PCR. This study demonstrates how simple recombinant technology can be used to produce a positive control that has application in the laboratory for surveillance studies or as a diagnostic tool using synthetic genes to abrogate the requirement for handling infectious virus.
更多
查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要