RT-RAA-CRISPR/Cas12a可视化检测番茄褐色皱纹果病毒
Visual detection of tomato brown rugose fruit virus by RT-RAA-CRISPR/Cas12a method
赵振兴 1范奇璇 2王思元 1董铮 1胡中泽 3周涛 4张永江1
作者信息
- 1. 中国检验检疫科学研究院 北京 100176
- 2. 中国检验检疫科学研究院 北京 100176;中国农业大学植物保护学院
- 3. 江苏省农业科学院泰州农科所
- 4. 中国农业大学植物保护学院
- 折叠
摘要
番茄褐色皱纹果病毒(tomato brown rugose fruit virus,ToBRFV)严重威胁番茄等茄科园艺作物的生产安全.本研究根据其外壳蛋白(coat protein,CP)基因及其同属病毒的差异序列,设计了特异性重组酶介导等温核酸扩增技术(recombinase-aided amplifcation,RAA)引物,并基于CRISPR/Cas12a的设计原则,设计了靶向RT-RAA扩增产物的CRISPR RNA(crRNA).通过优化获得了检测信号最强的反应体系,其中报告基因FQ终浓度为600 nmol/L、Cas12a和crRNA终浓度分别为200 nmol/L和1 000 nmol/L,最终总反应时间仅为30 min.该方法可特异性检测ToBRFV,对携带ToBRFV的番茄样品RNA检测灵敏度为RT-PCR和RT-qPCR的10 000和100倍,检测限为3.46 fg/μL.阳性样品验证结果显示,本研究建立的RT-RAA-CRISPR/Cas12a检测技术可以在不同来源的辣椒、番茄侵染的植物叶片、果实及种子中检测到To-BRFV,表明该技术可用于番茄褐色皱纹果病毒的快速、灵敏的可视化检测.
Abstract
Tomato brown rugose fruit virus(ToBRFV)threatens production of Solanaceae crops like tomato.In this study we designed specific recombinase-aided amplification(RAA)primers for rapid isothermal amplification of ToBRFV based on its coat protein(CP)gene and the differential sequences of related viruses,and designed targeted CRISPR RNA(crRNA)targeting RT-RAA amplification products based on the design principle of CRISPR/Cas12a principles.The reaction took only 30 minutes to com-plete and resulting in the strongest visual detection signal,with a final concentration of reporter gene FQ,Cas12a,and crRNA of 600 nmol/L,200 nmol/L,and 1 000 nmol/L in the reaction system,respectively.This established RT-RAA-CRISPR/Cas12a assay was able to specific detect ToBRFV with a detection limit of 3.46 fg/μL,which was 10 000 and 100-fold higher than conventional RT-PCR and RT-qPCR methods.Val-idation test results for leaf,fruit,and seed samples from chili pepper and tomato plants of different ori-gins suggest that the RT-RAA-CRISPR/Cas12a detection method can be used for rapid and sensitive visu-al detection of ToBRFV.
关键词
番茄褐色皱纹果病毒/RT-RAA/CRISPR/Cas12a/可视化检测Key words
tomato brown rugose fruit virus/RT-RAA/CRISPR/Cas12a/visual detection引用本文复制引用
基金项目
国家重点研发计划(2021YFD14001002021YFD1400103)
出版年
2024
NETL
NSTL
万方数据