Bioinformatics Predicted Linear Epitopes of the Major Coat Protein of the Beet Yellows Virus for Detection of the Virus in the Cell Extract of the Infected Plant

利用生物信息学方法预测甜菜黄化病毒主要外壳蛋白的线性表位,用于检测受感染植物细胞提取物中的病毒。

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Abstract

Beet yellows virus, which belongs to the genus Closterovirus, family Closteroviridae and has a significant negative economic impact, has proven to be challenging to detect and diagnose. To obtain antibodies against BYV, we propose an easier bioinformatics approach than the isolation and purification of the wild virus as an antigen. We used the SWISS-MODEL Workspace (Biozentrum Basel) protein 3D prediction program to discover epitopes of major coat protein p22 lying on the surface of the BYV capsid. Sequences coding these epitopes were cloned into plasmid pQE-40 (Qiagen) in frame with mouse dihydrofolate reductase gene. Fused epitopes were expressed in Escherichia coli and isolated by the Ni-NTA affinity chromatography. Murine antibodies were raised against each epitope and in a combination of both and characterized by dot-ELISA and indirect ELISA. We successively used these antibodies for diagnosis of virus disease in systemically infected Tetragonia tetragonioides. We believe the approach described above can be used for diagnostics of difficult-to-obtain and hazardous-to-health viral infections.

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