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Peer-reviewed veterinary case report

Characterization of a novel B-cell epitope in the structural protein of goose astrovirus 1 and its application in serological detection.

Journal:
Poultry science
Year:
2025
Authors:
Wang, Anping et al.
Affiliation:
Jiangsu Agri-Animal Husbandry Vocational College · China

Abstract

Goose astrovirus 1 (GAstV-1) is an emerging pathogen responsible for gosling gout and has caused substantial economic losses in the goose industry, particularly during frequent co-infections with goose astrovirus 2 (GAstV-2) that exacerbate pathogenicity. Despite advances in GAstV-2 research, the lack of GAstV-1-specific monoclonal antibodies (mAbs) and defined epitopes has hindered the development of targeted diagnostic tools and mechanistic studies. To address this gap, we generated the first GAstV-1-specific mAb (A5A1) by immunizing mice with prokaryotically expressed recombinant ORF2 protein. Western blotting (WB), immunofluorescence assay (IFA), and immunohistochemistry (IHC) confirmed A5A1's strict specificity for GAstV-1. Crucially, we identified a linear B-cell epitope (SNREVQITQL) within the conserved P1 domain of ORF2. Structural modeling revealed its surface-exposed &#x3b2;-sheet conformation, while sequence alignment demonstrated high conservation among GAstV-1 strains but marked divergence from GAstV-2 and other avian astrovirus (AAstV) strains, highlighting its diagnostic utility. Leveraging A5A1, we developed an indirect competitive ELISA (icELISA) for GAstV-1 antibody detection. The assay demonstrated high sensitivity (detection limit: 1:128 serum dilution), robust reproducibility (intra-/inter-assay CVs <10 %), and exceptional specificity (no cross-reactivity with GAstV-2 or other avian pathogens). Clinical validation using 80 field sera showed 87.5 % concordance with IFA, confirming its reliability. Collectively, this study delivers the first GAstV-1-specific mAb, a novel diagnostic epitope, and a robust serological tool, thereby advancing GAstV-1 pathogenesis research and enabling effective disease surveillance.

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Original publication: https://pubmed.ncbi.nlm.nih.gov/40818196/