High-throughput detection of west Nile virus RNA
High-throughput detection of west Nile virus RNA
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DOI：
10.1128/jcm.39.4.1264-1271.2001
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发表时间：
2001-04-01
影响因子：
9.4
通讯作者：
Kramer, LD
中科院分区：
文献类型：
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作者：
Shi, PY;Kauffman, EB;Kramer, LD
西尼罗河病毒(West Nile Virus，WNV)最近在美国东北部和世界其他地区的暴发，使得制定有效的西尼罗河病毒监测方案变得至关重要。在本报告中，我们描述了一种结合了西尼罗河病毒RNA的自动提取、扩增和检测的高通量程序。该程序在大约4.5小时内分析了96个样本，机器人系统，ABI Prism 6700自动核酸工作站，提取RNA，并以96孔格式建立实时逆转录(RT)-PCR反应。该机器人提取RNA的回收率与商业RNA提取试剂盒相当，实时荧光RT-PCR方法用于检测和定量检测西尼罗河病毒RNA。利用体外转录的RNA，我们估计实时RT-FCR的检测下限约为10个拷贝的RNA。对标准的RT-PCR方法进行了优化，使其灵敏度与实时RT-PCR方法相似。标准检测方法可以可靠地用于检测少量样本或确认先前的检测结果，在套式RT-PCR中使用内部引物，我们将灵敏度提高了大约10倍，与标准RT-PCR相比。这项研究的结果首次表明，使用自动化系统进行大规模病毒RNA监测，极大地提高了诊断样本吞吐量的速度和效率。
The recent outbreaks of West Nile virus (WNV) in the northeastern United States and other regions of the world have made it essential to develop an efficient protocol for surveillance of WNV. In the present report, we describe a high-throughput procedure that combines automated RNA extraction, amplification, and detection of WNV RNA. The procedure analyzed 96 samples in approximately 4.5 h, A robotic system, the ABI Prism 6700 Automated Nucleic Acid workstation, extracted RNA and set up reactions for real-time reverse transcription (RT)-PCR in a 96-well format. The robot extracted RNA with a recovery as efficient as that of a commercial RNA extraction kit, A real-time RT-PCR assay was used to detect and quantitate WNV RNA. Using in vitro transcribed RNA, we estimated the detection limit of the real-time RT-FCR to be approximately 10 copies of RNA. A standard RT-PCR assay was optimized to a sensitivity similar to that of the real-time RT-PCR. The standard assay can be reliably used to test a small number of samples or to confirm previous test results, Using internal primers in a nested RT-PCR, we increased the sensitivity by approximately 10-fold compared to that of the standard RT-PCR. The results of the study demonstrated for the first time that the use of an automated system for the purpose of large-scale viral RNA surveillance dramatically increased the speed and efficiency of sample throughput for diagnosis.