A novel peptide nuclide acid (PNA) electrochemical biosensor based on reduced graphene oxide (NH2-rGO)/2,2,6,6-tetramethylpiperidin-1-yl)oxyl nanocrystalline cellulose (TEMPO-NCC) for the detection of Mycobacterium tuberculosis (M. Tuberculosis) is described. In this study, the nanohybrid films NH2-rGO/TEMPO-NCC were immobilized onto screen-printed carbon electrode (SPE) via a simple drop-coating method. The electrochemical characterization of the designed electrode was investigated using cyclic voltammetry (CV) and impedance spectroscopy (EIS). Meanwhile, the sensitivity and selectivity of the designed biosensor against M. tuberculosis were measured by the differential pulse voltammetry (DPV). The response of the PNA probe-modified (NH2-rGO)/TEMPO-NCC demonstrated that the fabricated biosensor was able to distinguish between complementary, noncomplementary, and one-base mismatch DNA sequences using methylene blue (MB) as the electrochemical indicator. The developed electrochemical biosensor exhibited a linear calibration curve in the concentration range of 1×10−8 M to 1×10−13 M with the limit of detection of 3.14×10−14 M. The developed electrochemical biosensor has also been tested with a polymerase chain reaction (PCR) product of M. tuberculosis DNA which has shown successful results in distinguishing between negative and positive samples of M. tuberculosis.

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A quantitative real-time PCR (qPCR) followed by high resolution melting (HRM) analysis was developed for the differentiation of Mycobacterium species. Rapid differentiation of Mycobacterium species is necessary for the effective diagnosis and management of tuberculosis. In this study, the 16S rRNA gene was tested as the target since this has been identified as a suitable target for the identification of mycobacteria species. During the temperature gradient and primer optimization process, the melting peak (Tm) analysis was determined at a concentration of 50 ng DNA template and 0.3, 0.4 and 0.5 mM primer. The qPCR assay for the detection of other mycobacterial species was done at the Tm and primer concentration of 62 6C and 0.4 mM, respectively. The HRM analysis generated cluster patterns that were specific and sensitive to distinguished small sequence differences of the Mycobacterium species. This study suggests that the 16S rRNA-based real-time PCR followed by HRM analysis produced unique cluster patterns for species of Mycobacterium and could differentiate the closely related mycobacteria species.

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