Abstract
Tuberculosis (TB) remains a significant global health challenge, demanding rapid and comprehensive diagnostics for effective treatment. Secondary infections further complicate TB infection, worsening outcomes. Conventional diagnostics are hindered by prolonged turnaround times, high costs, and inability to detect co-infections. This study utilizes full-length 16S rDNA and internal transcribed spacer (ITS) amplicon sequencing based on Oxford Nanopore Technologies (ONT) to analyze clinical metagenomics of sputum microbiota from patients suspected with TB Infection. Our findings highlight the potential of ONT for profiling microbial communities associated with TB infection. The MTB group exhibited a significant abundance of Mycobacterium tuberculosis (M. tuberculosis) and Stenotrophomonas maltophilia. In contrast, Prevotella melaninogenica, Veillonella parvula, Corynebacterium striatum and Pseudomonas aeruginosa were more abundant in the negative samples. Fungal analysis revealed Candida orthopsilosis was enriched in MTB samples, while Aureobasidium leucospermi and Wallemia muriae predominated in negative samples. Correlation network analysis revealed M. tuberculosis exhibits positive and negative correlations with other microbial species, suggesting cooperative and competitive interactions that may influence microbial community dynamics and disease progression in TB patients. This study demonstrates the promise of ONT-based clinical metagenomics for rapid, comprehensive detection of bacterial and fungal co-infections, addressing limitations of conventional diagnostics and improving outcomes.