背景:SenecavirusA(SVA)是小核糖核酸科中Senecavirus属病毒的唯一成员,是猪水疱病的病原体之一。SVA在美国有报道,加拿大,中国,泰国,和哥伦比亚。
方法:在本研究中,通过RT-PCR在从安徽省不同规模的猪场收集的病态材料中检测到SVA阳性感染。
结果:在这项研究中,通过在BHK21细胞上进行病毒分离,成功获得了SVA的强毒株,并命名为SVA-CH-AHAU-1。同时,一个简单的,本研究建立了快速、准确的检测SVA感染的纳米PCR方法,使用重组质粒pClone-SVA-3D作为模板。
结论:SVA-CH-AHAU-1的完整基因组为7286bp,包括5'非编码区(UTR),6546个核苷酸的开放阅读框(ORF),编码2182个氨基酸(aa),和具有Poly(A)特征的3'UTR,系统发育分析表明,该分离株与美国分离株US-15-41901SD的核苷酸同源性最高(97.9%)。在这项研究中,发现毒株SVA-CH-AHAU-1在ORF区域与分离株SVA-CH-SDGT-2017和SVA/Canada/ON/FMA-2015-0024T2/2015重组.完整的基因组已提交给Genebank,登录号为OM654411。此外,我们的结果表明,建立的纳米PCR检测方法可以作为一种经济的,SVA方法的现场诊断的可靠和灵敏的方法,特别是在资源有限的地区。
BACKGROUND: Senecavirus A (SVA) is the only member of the genus Senecavirus in the family Picornaviridae, and is one of the pathogens of porcine blistering disease. SVA has been reported in the United States, Canada, China, Thailand, and Colombia.
METHODS: In this study, positive SVA infection was detected by RT-PCR in sick materials collected from pig farms of different sizes in Anhui Province.
RESULTS: In this study, a virulent strain of SVA was successfully obtained by viral isolation on BHK21 cells and named SVA-CH-AHAU-1. Meanwhile, a simple, rapid and accurate nano-PCR method for the detection of SVA infection was established in this study, using the recombinant plasmid pClone-SVA-3D as a template.
CONCLUSIONS: The complete genome of SVA-CH-AHAU-1 is 7286 bp, including a 5\' non-coding region (UTR), an open reading frame (ORF) of 6546 nucleotides, encoding 2182 amino acids (aa), and a 3\' UTR with Poly(A) features, and phylogenetic analysis showed that this isolate had the highest nucleotide homology (97.9 %) with the US isolate US-15-41901SD. In this study, the virulent strain SVA-CH-AHAU-1 was found to recombine in the ORF region with isolates SVA-CH-SDGT-2017 and SVA/Canada/ON/FMA-2015-0024 T2/2015. The complete genome has been submitted to GeneBank with the accession number OM654411. In addition, our results suggest that the established nano-PCR assay can be used as an economical, reliable and sensitive method for the field diagnosis of SVA method, especially in resource-limited areas.