Peer-reviewed veterinary case report
Virus-like particle (VLP)-based indirect ELISA (iELISA) for the detection of beak and feather disease virus (BFDV) antibodies.
- Journal:
- Applied microbiology and biotechnology
- Year:
- 2026
- Authors:
- Dhar, Pangkaj K et al.
- Affiliation:
- School of Agricultural · Australia
- Species:
- bird
Abstract
Beak and feather disease virus (BFDV) poses a significant threat to avian biodiversity and global aviculture. Reliable serodiagnostic tools are critical for assessing host immune status and guiding disease management. The haemagglutination inhibition (HI) assay, although historically regarded as the gold standard, is limited by technical complexity and its reliance on seropositive Galah erythrocytes, restricting broader application. This study describes the development and validation of a recombinant BFDV capsid protein-based indirect enzyme-linked immunosorbent assay (iELISA) for detecting anti-BFDV antibodies using dried blood spots from multiple psittacine species. The assay demonstrated high sensitivity and strong analytical performance, employing virus-like particles (VLPs) recombinantly expressed in Escherichia coli. Optimisation of the diagnostic cut-off by two-graph receiver operating characteristic (TG-ROC) analysis established an OD threshold of 1.73, achieving 96.5% sensitivity with a Youden's index of 0.74. Discriminative capacity was further supported by receiver operating characteristic (ROC) analysis, yielding an area under the curve (AUC) of 0.896. Agreement with the HI assay was very strong (Gwet's Agreement Coefficient 1= 0.843). This iELISA represents a scalable and universal serodiagnostic tool, supporting clinical diagnosis, enabling large-scale epidemiological investigations, and advancing conservation-focused BFDV surveillance. KEY POINTS: Efficient detection of anti-BFDV antibodies in psittacines using recombinant capsid protein as coating antigen. Use of TG-ROC curve to determine cut-off value supported by Gwet's Agreement Coefficient 1. Easily adaptable method with very high sensitivity in detecting anti-BFDV antibodies.
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Search related cases →Original publication: https://pubmed.ncbi.nlm.nih.gov/41577812/