Comparison of DNA extraction protocols to detect Mycobacterium bovis in bovine tissue by PCR
DOI:
https://doi.org/10.5433/1679-0359.2016v37n5Supl2p3709Palabras clave:
DNA extraction, Bovine tissue, Bovine tuberculosis, Mycobacterium bovis, PCR.Resumen
The current scenario of international beef trading has increased the pressure for better and faster diagnosis of bovine tuberculosis. Although traditional culture remains the gold standard method to confirm Mycobacterium bovis infection, it is exceedingly time consuming, and demands viable mycobacteria. Molecular methods overcome the flaws of the bacteriological methods with faster detection and identification. However, mycobacterial features like a complex cell wall and pathogen–host interaction make the molecular detection a challenge. Three protocols for DNA extraction (A, B and C) from bovine tissues were tested to verify the most suitable technique for routine diagnostic assessment of their specificity and sensitivity. Thirty culture-positive and thirty culture-negative granulomatous lesions were included in the trial. From each sample, three tissue suspensions at different dilutions (10-1, 10-2 and 10-3) were prepared and submitted to DNA extraction. PCR procedures targeting IS6110 were performed, employing two volumes of DNA: 5 µL of all three dilutions, and 2.5 µL of the 10-1 dilution. Protocol A was able to detect members of the M. tuberculosis complex in most samples. The sensitivity of the test decreased with increase in tissue-suspension dilution. Although Protocol A presented the highest sensitivity followed by C and B, it showed the lowest specificity, which can be due to a failure in primary isolation caused by the lack of viable organisms or incubation time. Regardless classical bacteriological methods are still recommended by OIE, after evaluating the sensitivity of DNA extraction protocols and PCR procedures, we conclude that the best strategy for M. bovis detection is to follow Protocol A on concentrated tissue suspensions.Descargas
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Derechos de autor 2016 Semina: Ciências Agrárias
Esta obra está bajo una licencia internacional Creative Commons Atribución-NoComercial 4.0.
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