摘要
为建立一种鸭星状病毒2型(DAstV-2)核酸的快速可视化检测方法,本试验基于重组酶聚合酶扩增结合横向侧流层析试纸条(RPA-LFD)技术,以DAstV-2的ORF2基因为检测靶标,设计和筛选适用于DAstV-2核酸检测的RPA引物和匹配探针,并优化反应条件;进一步验证该方法的灵敏性、特异性和准确性。结果显示,筛选获得1对引物和匹配探针适用于DAstV-2核酸的RPA-LFD检测,探针的最佳工作浓度为5μmol/L;建立的RPA-LFD检测方法对DAstV-2核酸的最低检测限为3×10^(1)copies/μL;可特异性检测DAstV-2核酸,对鸭肝炎病毒(DHV)、鹅星状病毒(GAstV)、鸭圆环病毒(DuCV)和鸭瘟病毒(DPV)的检测结果均为阴性;对疑似DAstV-2感染病鸭肝脏组织病毒核酸样本的检测结果显示,建立的RPA-LFD与实时荧光定量PCR检测结果的符合率为100%,且该检测方法更加便捷。本试验结果表明,利用RPA-LFD检测DAstV-2核酸灵敏度高、特异性强、准确性高,操作简单、检测快速,可在38℃恒温条件下15 min内实现DAstV-2核酸的快速可视化检测。
In order to establish a rapid visual detection method for duck astrovirus type 2(DAstV-2)nucleic acid,this study utilized recombinant polymerase amplification combined with lateral flow dipstick(RPA-LFD)technology.The ORF 2 gene of DAstV-2 was selected as the detection target,and RPA primers and matching probes suitable for DAstV-2 nucleic acid detection were designed and screened,along with the optimization of reaction conditions.The sensitivity,specificity,and accuracy of the method were further validated.The results indicated that one pair of primers and matching probes were successfully selected for the RPA-LFD detection of DAstV-2 nucleic acid,with an optimal working concentration of the probe at 5μmol/L.The established RPA-LFD detection method had a minimum detection limit for DAstV-2 nucleic acid of 3×101 copies/μL and could specifically detect DAstV-2 nucleic acid,with negative results for duck hepatitis virus(DHV),goose astrovirus(GAstV),duck circovirus(DuCV),and duck plague virus(DPV).Detection results from suspected DAstV-2 infected duck liver tissue virus nucleic acid samples showed a 100%concordance rate with results from real-time fluorescence quantitative PCR,and the RPA-LFD method proved to be more convenient.The findings indicate that RPA-LFD for detecting DAstV-2 nucleic acid is highly sensitive,specific,and accurate,with simple operation and rapid detection,achieving rapid visual detection of DAstV-2 nucleic acid within 15 minutes at a constant temperature of 38℃.
作者
何书海
晋丹丹
薛玉坤
曲哲会
鲁绍芳
董建国
胡建新
HE Shuhai;JIN Dandan;XUE Yukun;QU Zhehui;LU Shaofang;DONG Jianguo;HU Jianxin(College of Animal Science and Technology,Xinyang University of Agriculture and Forestry,Xinyang 464000,China;Henan Provincial Waterfowl Resources Development and Utilization and Disease Control Engineering Technology Research Center,Xinyang 464000,China;Xinyang Animal Husbandry and Veterinary Technical Service Center,Xinyang 464000,China)
出处
《中国兽医杂志》
CAS
北大核心
2024年第12期46-51,共6页
Chinese Journal of Veterinary Medicine
基金
2023年度河南省重点研发与推广专项(科技攻关)资助项目(232102111043)
信阳农林学院家禽重大疫病防控科技创新团队资助项目(2022CXTD06)。
