Tuberculosis (TB) remains one of the leading causes of mortality from infectious diseases worldwide. In 2023, there were 10.8 million TB infections, resulting in 1.25 million deaths. Among these, 400,000 patients with TB were infected with multidrug-resistant TB (MDR-TB) or rifampicin-resistant TB, yet only 44 % were correctly diagnosed and treated [1,2]. Moreover, TB presents symptoms that overlap with those of other bacterial or fungal infections, including non-tuberculous mycobacteria (NTM) infections, as well as non-infectious pulmonary conditions [[3], [4]]. This overlap makes the differential diagnosis of TB and other lung diseases particularly challenging [5]. Accurate and timely diagnosis of TB, drug-resistant TB (DR-TB), or other respiratory diseases is crucial for guiding appropriate treatment and improving patient outcomes.

Traditional methods, such as Acid-Fast Bacilli staining, microbiological culture, and phenotypic drug susceptibility testing (pDST), are limited by low sensitivity or long turnaround times. Molecular diagnostic methods, such as nucleic acid amplification tests like Xpert MTB/RIF, enable rapid and accurate detection of TB and rifampicin resistance [6]. However, their ability is restricted to detecting only the TB pathogen and rifampicin resistance. While metagenomic next-generation sequencing can identify a wide range of pathogens, it often lacks sufficient sequencing depth, making it less effective for diagnosing drug-resistant mutations [7].

Targeted next-generation sequencing (tNGS) has shown increasing sensitivity and specificity for TB and DR-TB detection. The target design for drug resistance regions can simultaneously cover multiple mutation sites associated with both first- and second-line drugs used in TB treatment [8,9]. It has been recommended by World Health Organization (WHO) for its culture-free nature and suitability for detecting resistance to new or repurposed drugs that are not covered by existing molecular diagnostic methods [10,11]. However, there remains a lack of a comprehensive tNGS method that can simultaneously diagnose TB and DR-TB while identifying other respiratory pathogens that may complicate the differential diagnosis of TB.

In this study, we propose an enhanced tNGS method to address the challenges in TB diagnosis. We evaluated not only the tNGS assay's performance for detecting TB and TB drug resistance mutations but also its ability to analyse multiple respiratory pathogens. Additionally, we prospectively enrolled clinically suspected patients with TB to demonstrate the tNGS assay's capability in diagnosing TB, DR-TB, and distinguishing other common respiratory pathogens in a clinical setting.