Approach to Diagnosis of Nontuberculous Mycobacteria from Skin and Soft Tissue Infection in Resource-limited Settings using Convenient Culture Techniques

CONTEXT: Nontuberculous mycobacteria (NTM) are increasingly recognized as causes of skin and soft tissue infections (SSTIs), particularly in tuberculosis (TB)-endemic regions where diagnostic algorithms remain focused on Mycobacterium tuberculosis. Delayed diagnosis is common due to limited awareness and suboptimal detection methods. Therefore, rapid and sensitive diagnostic approaches suitable for resource-limited settings are needed. AIMS: To compare smear microscopy, Löwenstein-Jensen (LJ) culture, and automated liquid culture using the BacT/ALERT® Microbial Detection System (bioMérieux SA, Marcy-l'Étoile, France) microbial detection system for the detection of NTM in SSTIs. SETTINGS AND DESIGN: This prospective, descriptive laboratory-based study was conducted in the department of microbiology at a tertiary care teaching hospital in Eastern India over a period of 18 months. MATERIALS AND METHODS: A total of 161 specimens from patients with clinically suspected chronic SSTIs were analyzed using smear microscopy, direct LJ culture, and automated liquid culture (BacT/Alert system). Isolates were screened using Mycobacterium Protein Tuberculosis 64 (MPT 64) antigen testing to exclude M. tuberculosis complex. Species-level identification of NTM was performed using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry. The diagnostic yield of the three methods was compared. STATISTICAL ANALYSIS USED: Diagnostic yield across the three methods was compared using appropriate paired statistical tests. Effect sizes were expressed as absolute risk differences with 95% confidence intervals. A two-sided P < 0.05 was considered statistically significant. RESULTS: Automated liquid culture (BacT/Alert) demonstrated the highest detection rate, followed by LJ culture, while smear microscopy showed the lowest yield. Comparative analysis revealed a statistically significant difference in diagnostic performance among the three methods. Liquid culture detected additional cases not identified by LJ culture and showed an earlier time to positivity. Rapidly growing mycobacteria predominated, with Mycobacterium fortuitum being the most frequently isolated species. CONCLUSIONS: Automated liquid culture systems significantly improve the detection of NTM in SSTIs compared with conventional methods. Combining liquid and solid culture methods may provide a practical and cost-effective diagnostic strategy in TB-endemic, resource-limited settings.