Molecular detection of African horse sickness virus from selected areas in Ethiopia.
African horse sickness virus, particularly serotype 9, significantly affects equines in Ethiopia, necessitating strategic control measures.
Where it sits
this study against the rest of the teriparatide (pth 1-34) corpusSummary and findings
A cross-sectional study in Ethiopia detected African horse sickness virus in equines using RT-PCR. Out of 32 samples, 21.88% were positive for the virus, specifically serotype 9. The study highlights the virus's impact on equine mortality and the need for strategic disease control.
Abstract
Equines are vital to global economies and support millions of livelihoods. However, their productivity and welfare are severely hindered by infectious diseases such as African Horse Sickness, which causes major socio-economic losses in Ethiopia. A cross-sectional study was conducted from November 2022 to May 2023 to isolate and detect African horse sickness virus in equines across epidemic areas of Ethiopia. In total, 30 blood samples and 2 tissue representative specimens were aseptically collected from clinically sick and recently dead animals and transported under cold chain to the National Veterinary Institute, Bishoftu. A total of 32 samples were analyzed using conventional Reverse Transcriptase Polymerase Chain Reaction (RT-PCR), targeting the Viral Protein 7 (VP7) gene to amplify segment 7 fragments of all serotypes with serogroup-specific primers. Of these, 7 samples (21.88%) produced 102bp fragments on 2% agarose gel electrophoresis. For serotyping, the 7 PCR-positive samples were further tested by targeting the gene encoding Viral Protein 2 (VP2) with serotype-specific primers, and serotype 9 was identified from tissue samples with a 228bp band. Only tissue samples were cultured on Vero cells, which exhibited cytopathic effects characterized by cell aggregation, rounding, and detachment. In conclusion, African horse sickness caused by serotype 9 severely impacts equines and leads to high mortality in horses. Strategic disease control through vaccination is essential, and further studies are needed to assess outbreak potential and conduct genotypic characterization of the virus in both equines and insect vectors.
Background
African horse sickness is a significant infectious disease affecting equines, leading to severe socio-economic losses, particularly in regions like Ethiopia. The disease is caused by a virus that impacts equine health and productivity. This study aims to detect and characterize the virus in epidemic areas to inform control strategies.
Methods
The study employed a cross-sectional design from November 2022 to May 2023, collecting 30 blood samples and 2 tissue specimens from clinically sick and recently dead equines. Samples were analyzed using RT-PCR targeting the VP7 gene to detect the virus, and serotyping was conducted using VP2 gene primers. Tissue samples were also cultured on Vero cells to observe cytopathic effects.
Results
Out of 32 samples, 7 (21.88%) tested positive for African horse sickness virus, producing 102bp fragments on gel electrophoresis. Serotyping identified serotype 9 in tissue samples, which showed a 228bp band. Vero cell cultures exhibited cytopathic effects, indicating viral presence.
Interpretation
The detection of serotype 9 in Ethiopian equines highlights a specific viral strain impacting the region. While the study confirms the presence of the virus, the small sample size and geographic focus limit broader applicability. The findings suggest a need for targeted vaccination strategies and further research into virus transmission dynamics.
Key findings
- 21.88% of samples tested positive for African horse sickness virus.
- 102bp fragments were observed in 7 samples on agarose gel electrophoresis.
- Serotype 9 was identified from tissue samples with a 228bp band.
- Cytopathic effects were observed in Vero cells cultured with tissue samples.
Limitations
- small sample size (n=32)
- single geographic region focus
- animal study, no human data
- cross-sectional design limits causality