Online Service with Automated Interpretation of Sequencing Data and Prediction of Pyrazinamide Resistance in Mycobacterium tuberculosis.

Abstract

Pyrazinamide plays an important role in the treatment of tuberculosis. However, the microbiological test for pyrazinamide resistance is more complex and less reliable than testing of susceptibility to other anti-tuberculosis drugs due to the need to grow the pathogen at pH 5.5. Identification of mutations that cause resistance to anti-tuberculosis drugs can replace microbiological methods. Mutations in the pncA gene are responsible for the main mechanism of the resistance to pyrazinamide and are found in more than 90% of resistant strains. However, the genetic method for determining drug susceptibility is very complex, because mutations leading to pyrazinamide resistance are diverse and scattered throughout the gene. We have developed a software package for automatic data interpretation and prediction of the resistance to pyrazinamide based on Sanger sequencing results. The effectiveness of detection of pyrazinamide resistance in 16 clinical samples was compared using the BACTEC MGIT 960 automated system and pncA gene Sanger sequencing with automated analysis of the results. A significant advantage of the developed method over a single microbiological study was shown, due to greater reliability of the results irrespective of the purity of isolates.