Evaluation of the Standard M10 MTB/NTM Molecular Test for the Rapid Identification of Tuberculous and Nontuberculous Mycobacteria in Liquid Cultures
Since 2013, the World Health Organization has recommended the use of rapid molecular tests as the initial diagnostic step for <i>Mycobacterium tuberculosis</i> (MTB) infection to enhance the control of tuberculosis. In recent years, the prevalence of infections by non-tuberculous mycobac...
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| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-05-01
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| Series: | Pathogens |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2076-0817/14/6/517 |
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| Summary: | Since 2013, the World Health Organization has recommended the use of rapid molecular tests as the initial diagnostic step for <i>Mycobacterium tuberculosis</i> (MTB) infection to enhance the control of tuberculosis. In recent years, the prevalence of infections by non-tuberculous mycobacteria (NTM) in humans has also risen, particularly in countries with low tuberculosis incidence, such as Italy. Therefore, the rapid differentiation between NTM and <i>Mycobacterium tuberculosis</i> complex is crucial for timely therapeutic decisions. This study evaluates a new rapid molecular assay, Standard M10 MTB/NTM, designed to detect MTB, NTM, or co-detection in Mycobacteria Growth Indicator Tube cultures from different biological matrices. The assay was validated using 100 positive and 50 negative liquid mycobacteria cultures, already confirmed by specific real-time PCR and Sanger sequencing. Following optimization of assay conditions for culture sample processing and assessment of potential interference, Standard M10 demonstrated excellent sample stability, high specificity, and good sensitivity, identifying all 50 MTB and 49 NTM samples. Some limitations included the non-detection of <i>M. celatum</i> in one case and false positive results (MTB co-infection) in two NTB cases. Nevertheless, overall, the adoption of this test could be considered for laboratory management to enable rapid and effective sample targeting for subsequent diagnostic evaluation and treatment decision-making. |
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| ISSN: | 2076-0817 |