- Mouhai He: College of Medical Technology and Nursing, Hunan Institute of Traffic Engineering Hengyang 421009, Hunan, China.
- Lingli Hu: Department of Ultrasound, Hengyang Central Hospital Hengyang 421001, Hunan, China.
OBJECTIVES: To evaluate the resistance of Mycobacterium tuberculosis to Rifampicin (RIF) and Isoniazid (INH) using enhanced qPCR methodologies.
METHODS: This study compared the detection of drug-resistant mutations in the rpoB and katG genes using AuNP-qPCR and No-AuNP-qPCR. Calibration curves were constructed to correlate the amount of template with the Ct values for resistant strains.
RESULTS: The AuNP-qPCR method demonstrated high efficacy in detecting RIF resistance with an area under the curve (AUC) of 0.951, sensitivity of 97.92%, specificity of 87.5%, and overall accuracy of 95.31%. Similarly, INH resistance detection by AuNP-qPCR showed an AUC of 0.981, sensitivity of 98.08%, specificity of 94.44%, and accuracy of 97.14%. Comparatively, No-AuNP-qPCR yielded lower performance metrics for RIF resistance (AUC: 0.867, sensitivity: 91.67%, specificity: 75%, accuracy: 87.5%) and INH resistance (AUC: 0.882, sensitivity: 88.46%, specificity: 83.33%, accuracy: 87.14%).
CONCLUSIONS: AuNP-qPCR exhibits over traditional qPCR methods, making it a promising tool for rapid and precise detection of drug resistance in Mycobacterium tuberculosis. This method's robust performance underscores its potential to improve diagnostic protocols and contribute to more effective management of tuberculosis treatment.