Abstract

This study aims to develop a novel diagnostic approach using the recombinase aided amplification-lateral flow dipstick(RAA-LFD) assay for the distinction of Mycobacterium tuberculosis (MTB) and Mycobacterium avium complex (MAC), enabling rapid and convenient as well as accurate identification of them in clinical samples. Our study established a duplex RAA-LFD assay capable of discriminating between MTB and MAC. Based on the principles of RAA primer and probe design, specific primers and probes were developed targeting the MTB IS6110 and the MAC DT1 separately. Optimization of reaction time points and temperatures was conducted, followed by an evaluation of specificity, sensitivity, and reproducibility. The established detection method was then applied to clinical samples and compared with smear microscopy, liquid culture, LAMP, and Xpert/MTB RIF in terms of diagnostic performance. The complete workflow allows for the effective amplification of the MTB IS6110 and MAC DT1 target sequences at constant 37°C within 20min, and the amplification products can be visually observed on the LFD test strip. This method exhibits high specificity, showing no cross-reactivity with nucleic acids from M. kansassi, M. abscessus, M. gordonae, M. chelonae, M. fortuitum, M. scrofulaceum, M. malmoense, M. chimaera, M. szulgai and common respiratory pathogens. It also demonstrates high sensitivity, with a detection limit as low as 102 CFU/mL. Additionally, the method's Coefficient of Variation (CV) is less than 5%, ensuring excellent repeatability and reliability. Furthermore, clinical performance evaluations, using Xpert/MTB RIF as the gold standard, demonstrated that the duplex RAA-LFD assay achieves a sensitivity of 92.86% and a specificity of 93.75%. It is also noteworthy that the assay exhibits considerable diagnostic efficacy in smear-negative patients. Our study introduces a rapid, specific, and sensitive duplex RAA-LFD assay for the discriminatory diagnosis of MTB and MAC. This method represents a significant advancement in the field of infectious disease diagnostics, offering a valuable tool for rapid detection and management of MTB and MAC infections. The implementation of this approach in point-of-care settings could greatly enhance TB control and prevention efforts, especially in resource-limited environments.

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