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鱼类病毒性神经坏死症(VNN)多价疫苗的计算设计与评估,以对抗神经坏死病毒(Betanodavirus)感染。

Computational design and evaluation of a polyvalent vaccine for viral nervous necrosis (VNN) in fish to combat Betanodavirus infection.

机构信息

Department of Genetic Engineering and Biotechnology, Faculty of Biological Sciences, University of Chittagong, Chattogram, Bangladesh.

Faculty of Biotechnology and Genetic Engineering, Sylhet Agricultural University, Sylhet, 3100, Bangladesh.

出版信息

Sci Rep. 2024 Nov 6;14(1):27020. doi: 10.1038/s41598-024-72116-5.

Abstract

Viral nervous necrosis (VNN) poses a significant threat to the aquaculture industry, causing substantial losses and economic burdens. The disease, attributed to nervous necrosis viruses within the Betanodavirus genus, is particularly pervasive in the Mediterranean region, affecting various fish species across all production stages with mortality rates reaching 100%. Developing effective preventive measures against VNN is imperative. In this study, we employed rigorous immunoinformatics techniques to design a novel multi-epitope vaccine targeting VNN. Five RNA-directed RNA polymerases, crucial to the lifecycle of Betanodavirus, were selected as vaccine targets. The antigenicity and favorable physicochemical properties of these proteins were confirmed, and epitope mapping identified cytotoxic T lymphocyte, helper T lymphocyte, and linear B lymphocyte epitopes essential for eliciting a robust immune response. The selected epitopes, characterized by high antigenicity, non-allergenicity, and non-toxicity, were further enhanced by adding PADRE sequences and hBD adjuvants to increase immunogenicity. Two vaccine constructs were developed by linking epitopes using appropriate linkers, demonstrating high antigenicity, solubility, and stability. Molecular dynamics simulations revealed stable interactions between the vaccine constructs and Toll-like receptors (TLRs), essential for pathogen recognition and immune response activation in fish. Notably, vaccine construct V2 exhibited superior stability and binding affinity with TLR8, suggesting its potential as a promising candidate for VNN prevention. Overall, our study presents a comprehensive approach to VNN vaccine design utilizing immunoinformatics, offering safe, immunogenic, and effective solutions across multiple Betanodavirus species. Further experimental validation in model animals is recommended to fully assess the vaccine's efficacy. This research contributes to improved vaccine development against diverse fish pathogens by addressing emerging challenges and individualized immunization requirements in aquaculture.

摘要

病毒性神经坏死病(VNN)对水产养殖业构成重大威胁,造成巨大损失和经济负担。该疾病归因于属于 Betanodavirus 属的神经坏死病毒,在地中海地区尤为普遍,影响所有生产阶段的各种鱼类,死亡率高达 100%。开发针对 VNN 的有效预防措施至关重要。在这项研究中,我们采用严格的免疫信息学技术设计了一种针对 VNN 的新型多表位疫苗。选择了 5 种 RNA 指导的 RNA 聚合酶作为疫苗靶标,这些酶对 Betanodavirus 的生命周期至关重要。这些蛋白质的抗原性和有利的物理化学特性得到了确认,并且通过表位作图确定了引发强大免疫反应所必需的细胞毒性 T 淋巴细胞、辅助 T 淋巴细胞和线性 B 淋巴细胞表位。选择的表位具有高抗原性、非变应原性和非毒性,通过添加 PADRE 序列和 hBD 佐剂进一步增强其免疫原性,以增加免疫原性。通过使用适当的接头将表位连接起来,开发了两种疫苗构建体,证明了它们具有高抗原性、溶解性和稳定性。分子动力学模拟揭示了疫苗构建体与 Toll 样受体(TLR)之间的稳定相互作用,这对于鱼类中病原体识别和免疫反应激活至关重要。值得注意的是,疫苗构建体 V2 与 TLR8 表现出优异的稳定性和结合亲和力,表明其作为 VNN 预防的有前途的候选物的潜力。总体而言,我们的研究利用免疫信息学提出了一种全面的 VNN 疫苗设计方法,为多种 Betanodavirus 物种提供了安全、免疫原性和有效的解决方案。建议在模型动物中进行进一步的实验验证,以充分评估疫苗的功效。这项研究通过解决水产养殖中出现的挑战和个性化免疫要求,为针对不同鱼类病原体的疫苗开发做出了贡献。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/af77/11542017/c6003fea0792/41598_2024_72116_Fig1_HTML.jpg

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