The conservation and application of three hypothetical protein coding gene for direct detection of Mycobacterium tuberculosis in sputum specimens

Accurate and early diagnosis of tuberculosis (TB) is of major importance in the control of TB. One of the most important technical advances in diagnosis of tuberculosis is the development of nucleic acid amplification (NAA) tests. However, the choice of the target sequence remains controversial in NAA tests. Recently, interesting alternatives have been found in hypothetical protein coding sequences from mycobacterial genome. To obtain rational biomarker for TB diagnosis, the conservation of three hypothetical genes was firstly evaluated in 714 mycobacterial strains. The results showed that SCAR1 (Sequenced Characterized Amplified Region) based on Rv0264c coding gene showed the highest conservation (99.8%) and SCAR2 based on Rv1508c gene showed the secondary high conservation (99.7%) in M. tuberculosis (MTB) strains. SCAR3 based on Rv2135c gene (3.2%) and IS6110 (8%) showed relatively high deletion rate in MTB strains. Secondly, three SCAR markers were evaluated in 307 clinical sputum from patients in whom TB was suspected or patients with diseases other than TB. The amplification of IS6110 and 16SrRNA sequences together with both clinical and bacteriological identification was as a protocol to evaluate the efficacy of SCAR markers. The sensitivities and specificities, positive predictive value (PPV) and negative predictive value (NPV) of all NAA tests were higher than those of bacteriological detection. In four NAA tests, IS6110 and SCAR3 showed the highest PPV (100%) and low NPV (70% and 68.8%, respectively), and SCAR1 and SCAR2 showed the relatively high PPV and NPV (97% and 82.6%, 95.6% and 88.8%, respectively). Our result indicated that SCAR1 and SCAR2 with a high degree of sequence conservation represent efficient and promising alternatives as NAA test targets in identification of MTB. Moreover, the targets developed from this study may provide more alternative targets for the development of a multisite system to effectively detect MTB in samples.