Label-free biosensor detects gene-pimb in urine samples, suggesting a novel approach for improved tuberculosis diagnostics.
Tuberculosis (TB) is a significant public health issue, and the existing diagnostic tests have shortcomings that cause delays in initiating treatment. In this study, we designed a Gene-pimB-based biosensor for the determination of TB and tested it using an electrochemical technique. The Gene-pimB has been reported to be upregulated in mannose-capped lipoarabinomannan (manLAM) in Multidrug-resistant tuberculosis (MDR-TB). Due to its link with drug resistance, Gene-pimB holds promise as a biomarker for identifying MDR-TB strains. In this work, the biosensor is fabricated using Graphite-Zinc Oxide nanofibers (GPH-ZnO-NFs), which are generated using electrospinning and deposited on glassy carbon electrodes (GCE). The GPH-ZnO functionalized electrode were further functionalized with MSA/EDC/NHS protocol to provide efficient immobilization which enable the effective binding of pimB-sequences to the nanofibers on the electrodes. In addition, the Gene-pimB hybridization on biosensors immobilized with Gene-pimB probe sequences was quantified using Cyclic Voltammetry (CV), Differential Pulse Voltammetry (DPV), and Electrochemical Impedance Spectrometry (EIS) techniques. The experimental tests revealed that the Limit of Detection (LoD) for CV is 0.1482pM/mL, for DPV it is 0.196 pM/mL, and for EIS it is 0.302 pM/mL. Our findings suggest that Gene-pimB may prove to be a useful technique in the creation of novel tests for TB prognosis. The efficacy of the developed biosensor was confirmed by a hybridization sensing assay including targeted short oligonucleotide sequences (probe) and Gene-pimB (Target) isolated from the urine sample. To assess its potential for clinical detection, urine samples were artificially spiked with the gene to simulate conditions encountered in clinical diagnostics. This approach allows for evaluating the feasibility of detecting Gene-pimB in a non-invasive manner, which could aid in the early identification of drug-resistant TB cases and improve diagnostic strategies for effective disease management.
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Rotake et al. (2025) studied this question.
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