中国兽医科学2025，Vol.55Issue(3)：321-329,9.DOI:10.16656/j.issn.1673-4696.2025.0032
基于RAA-CRISPR/Cas12a建立牛病毒性腹泻病毒的可视化快速检测方法及其初步应用
Establishment and application of visualization detection technology for bovine viral diarrhea virus based on RAA-CRISPR/Cas12a
摘要
Abstract
To establish a visual detection method for bovine viral diarrhea virus(BVDV)based on the combination of recombinant enzyme mediated amplification(RAA)and CRISPR/Cas12a.By referring to the BVDV 5'UTR gene in the GenBank database,specific primers and probes for the RAA reaction were de-signed to further optimize the reaction conditions of RAA-CRISPR/Cas12a,and the detection method of RAA-CRISPR/Cas12a was evaluated by measuring sensitivity,specificity,and repeatability.BVDV was de-tected in 251 calf diarrhea samples by PCR and RAA-CRISPR/Cas12a,respectively.The results indicated that for the RAA-CRISPR/Cas12a detection method,the minimum detection limit of BVDV was 3 copies/μL and the detection time was 30 min.After multiple batches of positive samples with different copy num-bers were tested,the coefficients of variation intra-and inter-batches were both less than 5％and and the results of this method were negative in the detection of other common pathogens of cattle with good specificity.In clinical samples,the PCR positive rate of BVDV was 6.37％.When RAA-CRISPR/Cas12a was utilized simultaneously,the positive detection rate was 29.48％,and the positive detection rate reached 4.63 times.In this study,a rapid visual detection method for BVDV based on RAA-CRISPR/Cas12a was established,which is of great significance for the prevention and control of diarrhea in calves.关键词
牛病毒性腹泻病毒/重组酶介导等温核酸扩增技术/CRISPR/Cas12a/检测Key words
bovine viral diarrhea virus/recombinant enzyme mediated isothermal nucleic acid am-plification technique/CRISPR/Cas12a/detection分类
农业科技引用本文复制引用
热则古丽·艾科拜尔,张亚平,刘浩然,杨莉,马雪连,姚刚,史慧君,付强..基于RAA-CRISPR/Cas12a建立牛病毒性腹泻病毒的可视化快速检测方法及其初步应用[J].中国兽医科学,2025,55(3):321-329,9.基金项目
新疆维吾尔自治区杰出青年基金项目(2022D01E15) （2022D01E15）
新疆维吾尔自治区"天山英才"青年科技拔尖人才专项(2022TSYCCX0049) （2022TSYCCX0049）
新疆维吾尔自治区重大科技专项(2023A02007-2) （2023A02007-2）
