Molecular identification of Mycoplasma synoviae from seroprevalent commercial breeder farms at Chittagong district, Bangladesh
نویسندگان
چکیده
AIM Worldwide, Mycoplasma synoviae (MS) is an important pathogen of poultry, especially for chicken and turkey. It causes respiratory tract infection and infectious sinusitis. The study was conducted to determine the seroprevalence of MS infection with associated risk factors and identification of MS organism in unvaccinated flocks of commercial breeder farms of the Chittagong district, Bangladesh. MATERIALS AND METHODS A total of 365 serum samples were collected and tested for MS using serum plate agglutination (SPA) test for determination of MS seroprevalence. On the other hand, tracheal swabs were collected from each seropositive flocks for polymerase chain reaction (PCR) to determine the presence of MS organism. RESULTS Among the farms, the highest prevalence was found to be 69% and the lowest prevalence was 28% with the average 60%. The seroprevalence of MS infection in breeder farms was highest 70% with the flock size >10,000 birds, whereas it was lowest 57% in the flocks ranging from 4000 to 7000. According to age group, the prevalence was found highest 70% in >60 weeks age group of birds and lowest 42% in 10-19 weeks group. The seroprevalence of MS in winter season was found as highest as 64%, whereas it was found lowest 60% in the summer season. There was a statistically significant difference (p<0.01) among the seroprevalence of MS in different breeder farms, flock size, and age groups, but there was no significant (p>0.05) difference in the winter, summer, and rainy season. To confirm the presence of MS in the samples, PCR test was applied using specific primers to amplify a 214 bp region of the 16S rRNA gene of the organism. In PCR, all seropositive flocks showed a positive result for MS. CONCLUSION As the plate agglutination test result showed 100% similar with PCR result, it can be suggested that agglutination test is better than molecular and culture techniques for MS detection and it is also cheaper and less time-consuming method.
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