College of Veterinary Medicine, Gansu Agricultural University, Lanzhou, PR China; China Agricultural Veterinary Biological Science and Technology Co. Ltd., Lanzhou, PR China.
College of Veterinary Medicine, Gansu Agricultural University, Lanzhou, PR China; China Agricultural Veterinary Biological Science and Technology Co. Ltd., Lanzhou, PR China; Lanzhou Veterinary Research Institute, Chinese Academy of Agricultural Sciences, Lanzhou, PR China.
Anal Biochem. 2022 Jun 1;646:114627. doi: 10.1016/j.ab.2022.114627. Epub 2022 Mar 1.
(SVA), an emerging picornavirus, has been associated with vesicular disease and neonatal mortality in swine, posing a great threat to the global swine industry. Accurate diagnosis of SVA is crucial for the effective prevention and control disease. In the present study, a simple, rapid and accurate diagnostic assay was developed combining recombinase polymerase amplification and a lateral flow dipstrip (RPA-LF) to detect SVA infection. Using recombinant plasmid pMD19-T-VP1 DNA as a template, the RPA-LF optimal reaction conditions were incubated at 35 °C for 25 min, and the result was visualized directly on the dipstrip. The specificity assay showed no cross-reactivity with other tested viruses, and the sensitivity assay revealed the minimum detection limit was 15 copies/μl. Moreover, the RPA-LF method was successfully applied with viral cDNA as template to test clinical samples, with no significant difference being observed between RPA-LF and qRT-PCR. Hence, the established RPA-LF assay could be used as a potential optional rapid, reliable, sensitive and low-cost method for field diagnosis of SVA, especially in resource-limited regions.
塞尼卡病毒 A(SVA)是一种新兴的小 RNA 病毒,与猪的水疱病和新生仔猪死亡有关,对全球养猪业构成了巨大威胁。准确诊断 SVA 对于有效预防和控制疾病至关重要。在本研究中,开发了一种简单、快速和准确的诊断检测方法,结合重组酶聚合扩增和侧向流动试纸条(RPA-LF)来检测 SVA 感染。使用重组质粒 pMD19-T-VP1 DNA 作为模板,RPA-LF 的最佳反应条件是在 35°C 孵育 25 分钟,结果可直接在试纸条上观察到。特异性试验显示与其他测试的病毒无交叉反应,敏感性试验显示最低检测限为 15 拷贝/μl。此外,该 RPA-LF 方法成功地应用于病毒 cDNA 作为模板检测临床样本,与 qRT-PCR 相比无显著差异。因此,建立的 RPA-LF 检测方法可作为一种潜在的快速、可靠、敏感和低成本的现场诊断 SVA 的方法,特别是在资源有限的地区。