Deeplex® Myc-TB: A high-performance targeted sequencing solution for rapid mycobacterial identification and tuberculosis drug resistance diagnosis
Rapid diagnosis of mycobacterial infection and early detection of tuberculosis (TB) drug resistance are critical to guide prompt clinical decision-making and improving patient outcomes. A recent study published in the Journal of Clinical Microbiology highlights the excellent performances of the targeted next-generation sequencing (tNGS) solution Deeplex® Myc-TB, for identifying mycobacteria and for molecular detection of drug resistance directly from clinical specimens or cultured isolates.
Addressing the challenges of tuberculosis diagnosis
Traditional phenotypic methods for mycobacterial identification and drug susceptibility testing are slow, delaying the diagnosis and initiation of the appropriate treatment.
Deeplex® Myc-TB addresses this challenge by providing a comprehensive molecular solution that rapidly identifies Mycobacterium tuberculosis complex (MTBC) and nontuberculous mycobacteria (NTM) and detects the presence or absence of mutations associated with resistance to 15 anti-tuberculosis drugs.
Performances validated by a study from Advanced Diagnostic Laboratories, Denver, Colorado, USA
The study published in the Journal of Clinical Microbiology and conducted by a team from Advanced Diagnostic Laboratories, National Jewish Health (Denver, Colorado, USA) evaluated the performances of Deeplex® Myc-TB using both cultured isolates and respiratory specimens.
The molecular results obtained with Deeplex® Myc-TB were compared against reference phenotypic and genotypic methods. For MTBC drug resistance prediction, phenotypic resistance profiles were considered the primary gold standard reference. In cases of discrepancies, additional molecular confirmation methods were applied, including GeneXpert MTB/RIF real-time PCR testing for rifampicin resistance and whole-genome sequencing (WGS) for investigation of bedaquiline resistance-associated mutations.
Specificity for species identification was 100% for negative samples or non-target bacteria. Sensitivity for mycobacterial identification in isolates or sputum samples was 93% (38/41) and 98% (41/42) for MTBC, respectively. For NTM, sensitivity for identification was 90% (19/21) on isolates and 69% on sputum samples (with 13 tested samples only; 9/13).
The results demonstrated a high level of agreement with conventional reference methods for predicting antimicrobial resistance.
Overall concordance of predicted versus reference MTBC resistotypes reached:
- 8% for cultured isolates (489/505);
- 3% for respiratory specimens(472/485).
These findings confirm the reliability of Deeplex® Myc-TB for prompt MTBC genotypic resistance profiling, and the high overall specificity and sensitivity for mycobacterial identification, even if identification of rare NTM species in sputum might remain more challenging.
The study also confirmed the previously established analytical sensitivity of Deeplex® Myc-TB, with a limit of detection of 100 to 1,000 genome copies per test in both isolates and sputum, supporting its use directly on respiratory specimens and reducing reliance on culture whenever appropriate.
Advancing molecular tuberculosis diagnosis
As next-generation sequencing becomes increasingly integrated into clinical microbiology laboratories, Deeplex Myc-TB offers an integrated tNGS solution that enables clinicians to make faster, more informed clinical decisions.
The findings published in the Journal of Clinical Microbiology further validate the performances of this approach and reinforce its value for rapid mycobacterial diagnosis and tuberculosis drug resistance detection.
These results are fully aligned with the World Health Organization’s recommendation of Deeplex® Myc-TB for detection of drug resistance in patients with drug-susceptible TB or with multidrug resistant/rifampicin-resistant TB.
Sources:
Kuss-Duerkop S.K. et al. Performance of a targeted next generation sequencing assay for mycobacterial identification and drug resistance from sputum and isolates. Journal of Clinical Microbiology, 2026.
