Optimization of Mycobacterial Infection Management: From Prevalence Studies to Molecular Diagnostics and Characteristic Analysis for Tuberculosis and Non-Tuberculous Mycobacteria

Mycobacterial infections, encompassing Mycobacterium tuberculosis (MTB) and Non-Tuberculous Mycobacteria (NTM), remain an enduring challenge in clinical microbiology and public health. Despite global advances in tuberculosis (TB) control, the persistence of drug-resistant strains and the rising prevalence of NTM pulmonary disease complicate diagnosis, treatment, and surveillance. This study presents a comprehensive investigation that spans prevalence studies, diagnostic optimization, and molecular approaches for resistance profiling. In Chapter Ⅰ, we conducted a prospective study in North Sardinia, Italy, from 2020 to 2023, analyzing 1,836 clinical specimens. We observed a declining incidence of tuberculosis (3.26/100,000 population per year), contrasting with a steady prevalence of NTM infections (1.54/100,000 population per year), particularly among older adults. Conventional methods (microscopy, culture) and molecular techniques (real-time PCR, DNA probe assay, Mass Spectrometry) for mycobacteria identification were evaluated, revealing superior sensitivity of liquid culture and PCR-based methods. Notably, 71.9% of MTB isolates exhibited resistance to at least one first-line drug, with isoniazid resistance being most prevalent (28.09%). Molecular detection of resistance genes showed limited sensitivity in smear-negative samples, highlighting the need for improved diagnostics in paucibacillary cases. In Chapter Ⅱ, we assessed a novel RNase Hybridization-Assisted Amplification (RHAM)-based point-of-care test (POCT) for MTB detection. The assay demonstrated high sensitivity and specificity across diverse sample types (sputum, BAL, biopsy, etc.), with an average turnaround time of 18 minutes. Its performance, affordability, and portability align with the WHO ASSURED criteria, making it a promising tool for resource-limited settings. In Chapter Ⅲ, we presented a meta-analysis of 49 studies evaluating molecular technologies for NTM identification and antibiotic resistance profiling. MALDI-TOF MS and PCR-based methods showed high sensitivity (0.92 and 0.98, respectively), while sequencing achieved near-perfect accuracy (0.99). Subspecies differentiation within the Mycobacterium abscessus complex and Mycobacterium avium complex was critical due to varying resistance patterns, particularly to macrolides and quinolones. Global resistance data underscored the urgency for species-directed therapy. In Chapter Ⅳ, we explored the application of sequencing technologies (16S rRNA, Next Generation Sequencing, Whole Genome Sequencing) for NTM species identification and antibiotic resistance analysis. Sequencing outperformed conventional methods in resolution, enabling subspecies-level discrimination and detection of resistance mutations. A robust bioinformatics pipeline was established to enhance data accuracy, emphasizing the role of quality control and genomic analysis in clinical diagnostics. In conclusion, this work underscores the importance of integrating advanced molecular diagnostics into routine practice to address the evolving challenges of mycobacterial infections. Our findings support the adoption of rapid, accurate, and accessible technologies to improve patient outcomes and guide public health strategies.