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Xu Z, Liu M, He Q, Li W, Pan J, El-Sheikh ESA, Liu W, Hammock BD, Li D. Nanobody based immunoassay for detection of aquatic virus: Giant salamander iridovirus. Anal Chim Acta 2025; 1350:343877. [PMID: 40155175 PMCID: PMC12118806 DOI: 10.1016/j.aca.2025.343877] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2024] [Revised: 02/18/2025] [Accepted: 02/26/2025] [Indexed: 04/01/2025]
Abstract
Aquatic viruses cause devastating diseases in aquaculture, severely limiting production and resulting in significant economic losses. The giant salamander iridovirus (GSIV), a member of the genus Ranavirus, is the only virus reported to infect giant salamanders, posing a severe threat to the farming industry. Currently, there are no effective strategies available for its control. In this context, a reliable diagnostic tool for the rapid detection of GSIV is crucial to mitigate its impact. This study developed a nanobody-based immunoassay for the rapid and reliable detection of GSIV. GSIV was cultured and used to immunize an alpaca, A phage library with an original diversity of 1.89 × 108 PFU was established, and six nanobodies were identified after three rounds of panning. Among them, HC-2 exhibited superior performance and was used to develop a highly sensitive ELISA method employing streptavidin-PolyHRP (SA-PolyHRP) as a signal amplification strategy. The assay achieved a detection limit of 3.3 × 105 PFU/mL and demonstrated high specificity without cross-reactivity. Practical application was validated in infected giant salamander samples, underscoring its diagnostic potential. This work provides a robust tool for GSIV diagnosis and showcases the potential of nanobodies in advancing aquaculture diagnostics.
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Affiliation(s)
- Zhihao Xu
- College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou, 310058, People's Republic of China; Zhejiang Key Laboratory of Intelligent Sensing and Robotics for Agriculture, Hangzhou, 310058, People's Republic of China
| | - Man Liu
- Yangtze River Fisheries Research Institute, Chinese Academy of Fishery Sciences, Wuhan, 430223, People's Republic of China
| | - Qiyi He
- College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou, 310058, People's Republic of China; Zhejiang Key Laboratory of Intelligent Sensing and Robotics for Agriculture, Hangzhou, 310058, People's Republic of China
| | - Wenkai Li
- College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou, 310058, People's Republic of China; Zhejiang Key Laboratory of Intelligent Sensing and Robotics for Agriculture, Hangzhou, 310058, People's Republic of China
| | - Junkang Pan
- College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou, 310058, People's Republic of China; Zhejiang Key Laboratory of Intelligent Sensing and Robotics for Agriculture, Hangzhou, 310058, People's Republic of China
| | | | - Wenzhi Liu
- Yangtze River Fisheries Research Institute, Chinese Academy of Fishery Sciences, Wuhan, 430223, People's Republic of China
| | - Bruce D Hammock
- Department of Entomology and Nematology and UCD Comprehensive Cancer Center, University of California Davis, Davis, CA, 95616, United States
| | - Dongyang Li
- College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou, 310058, People's Republic of China; Zhejiang Key Laboratory of Intelligent Sensing and Robotics for Agriculture, Hangzhou, 310058, People's Republic of China.
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