中华绒螯蟹白斑症病毒病的诊断
Diagnosis of White Spot Syndrome Virus Disease in Eriocheir sinensis
雷燕 1肖洋 1王娟 1张文文 1戚瑞荣 1张会军 1王学鹏2
作者信息
- 1. 广州利洋水产科技股份有限公司,广东广州510515;广州金水动物保健品有限公司,广东广州510515
- 2. 山东农业大学动物科技学院,山东泰安271018
- 折叠
摘要
[目的]对江苏省吴中地区养殖池塘患病的中华绒螯蟹进行诊断.[方法]结合临床流行病学调查和分子生物学鉴定,对江苏省吴中地区发病的中华绒螯蟹进行实验室检测与鉴定.参考GenBank中白斑症病毒(WSSV)的基因序列设计1对特异性引物,以从中华绒螯蟹的鳃、肝胰腺、肌肉等组织提取的DNA为模板,进行PCR扩增.[结果]经过解剖观察,发现病蟹内脏器官无明显变化.从病蟹的肝胰腺和肌肉中未分离到致病菌.通过PCR扩增,均能扩增出预期大小的特异性产物,测序比对显示扩增条带的基因序列与WSSV的基因序列同源性高达99.6％.病理切片显示鳃和肝胰腺可见大量细胞核肿大细胞,与WSSV引起对虾组织的病变相一致.[结论]经初步诊断,确定引起中华绒螯蟹发病死亡的病原为WSSV.
Abstract
[Objective] To diagnose the diseased Eriocheir sinensis in culture pond of Wuzhong Region of Jiangsu Province.[Method] The laboratory detection and identification were made on diseased E.sinensis by using clinical epidemiological investigation and molecular biological identification.One pair of specific primers were designed according to WSSV sequence in GenBank.DNA was extracted from the gill,hepatopancreas,muscle and other organs of E.sinensis and taken as templates to make PCR amplification.[Result] It was found that there was no obvious change of visceral organs in diseased E.sinensis by anatomical observation.No pathogenic bacterium was isolated from liver and muscle of diseased E.sinensis.Specific products with predicted size were obtained from diseased E.sinensis by PCR.The sequencing comparison results showed that the homology of nucleotide sequences between the amplified brands and WSSV was 99.6％.By observing the pathological sections,it was found that there were a large number of cells with enlargement nucleus in the gill and liver of diseased E.sinensis,which was accordant with the lesions of shrimp infected by WSSV.[Conclusion] The pathogen of diseased E.sinensis was confirmed as WSSV by tentative diagnosis.
关键词
中华绒螯蟹/白斑症病毒/诊断/组织病理变化Key words
Eriocheir sinensis/White spot syndrome virus (WSSV)/Diagnosis/Histopathological changes引用本文复制引用
基金项目
浙江省科技计划项目(2012F20029)
中央财政支持地方高校发展专项学科项目()
温州市重点科技创新团队项目(C2012004-02)
浙江省重大科技专项(2012C12017-3)
温州市科技计划项目(2011N0006)
出版年
2017
国家科技期刊平台
NSTL
维普
万方数据