Detection of Mycobacterium tuberculosis Antigens in Urinary Extracellular Vesicles using Real-Time Immuno-PCR: A Non-Invasive Diagnostic Approach for Pulmonary Tuberculosis

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Abstract

Non-sputum–based diagnostics using readily available clinical samples represent an urgent need in the effort to improve tuberculosis (TB) detection and control. This study evaluated urine as a non-invasive alternative by isolating urinary extracellular vesicles (uEVs), which naturally concentrate Mycobacterium tuberculosis (Mtb) antigens such as MPT-64 and lipoarabinomannan (LAM). A total of 162 participants were enrolled, including pulmonary TB (PTB) patients (n = 54), latent TB infection (LTBI) subjects (n = 33), other respiratory disease (ORD) controls (n = 58), and healthy controls. (n = 17). uEVs were characterized using nanoparticle tracking analysis, transmission electron microscopy, and western blotting, and subsequently analyzed by real-time immuno-PCR (RT-I-PCR) for simultaneous detection of MPT-64 and LAM. The assay demonstrated ultralow detection of purified MPT-64 + LAM (9.7 fg/mL), markedly outperforming indirect ELISA (3.7 ng/mL). Clinically, RT-I-PCR demonstrated 94.44% sensitivity in bacteriologically confirmed PTB, detecting all smear- and/or culture-positive cases and 92.31% of smear- and culture-negative but GeneXpert-positive cases, with an overall specificity of 90.74% among the control groups. In comparison, indirect ELISA identified only 31.48% of bacteriologically confirmed PTB cases while maintaining a high specificity of 96.15%. Receiver operating characteristic (ROC) curve analysis of RT-I-PCR assay indicated high diagnostic accuracy, with area under the curve (AUC) values ranging from 0.9741–0.9847. These findings highlight the potential of uEVs-based RT-I-PCR as a highly sensitive, non-invasive approach for PTB diagnosis, while emphasizing the need for further evaluation in larger and more diverse clinical cohorts to develop a scalable, non-invasive diagnostic platform suitable for TB-endemic settings.

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