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Objectives: Isoniazid-monoresistant tuberculosis (HR-TB) is the most prevalent form of drug-resistant TB worldwide and in France and is associated with poorer treatment outcomes compared with drug-susceptible TB (DS-TB). The objective of this study was to determine the characteristics of HR-TB patients in France and to compare outcomes and safety of treatment for HR-TB and DS-TB. Methods: We performed a case-control multicenter study to identify risk factors associated with HR-TB and compare treatment outcomes and safety between HR-TB patients and DS-TB patients. Results: Characteristics of 99 HR-TB patients diagnosed and treated in the university hospitals of Paris, Lille, Caen and Strasbourg were compared with 99 DS-TB patients. Female sex (OR = 2.2; 1.0–4.7), birth in the West-Pacific World Health Organization region (OR = 4.6; 1.1–18.7) and resistance to streptomycin (OR = 77.5; 10.1–594.4) were found to be independently associated with HR-TB. Rates of treatment success did not differ significantly between HR-TB and DS-TB. Conclusions: Factors associated with HR-TB are not significant enough to efficiently screen TB patients at risk of HR-TB. The systematic implementation of rapid molecular testing on clinical samples remains the only effective way to make the early diagnosis of HR-TB and adapt treatment.

The GeneLEAD VIII (Diagenode, Belgium) is a new, fully automated, sample-to-result precision instrument for the extraction of DNA and PCR detection of Mycobacterium tuberculosis complex (MTBC) directly from clinical samples. The Deeplex Myc-TB® assay (Genoscreen, France) is a diagnostic kit based on the deep sequencing of a 24-plexed amplicon mix allowing simultaneously the detection of resistance to 13 antituberculous (antiTB) drugs and the determination of spoligotype. We evaluated the performance of a strategy combining the both mentioned tools to detect directly from clinical samples, in 8 days, MTBC and its resistance to 13 antiTB drugs, and identify potential transmission of strains from patient-to-patient. Using this approach, we screened 112 clinical samples (65 smear-negative) and 94 MTBC cultured strains. The sensitivity and the specificity of the GeneLEAD/Deeplex Myc-TB approach for MTBC detection were 79.3% and 100%, respectively. One hundred forty successful Deeplex Myc-TB results were obtained for 46 clinical samples and 94 strains, a total of 85.4% of which had a Deeplex Myc-TB susceptibility and resistance prediction consistent with phenotypic drug susceptibility testing (DST). Importantly, the Deeplex Myc-TB assay was able to detect 100% of the multidrug-resistant (MDR) MTBC tested. The lowest concordance rates were for pyrazinamide, ethambutol, streptomycin, and ethionamide (84.5%, 81.5%, 73%, and 55%, respectively) for which the determination of susceptibility or resistance is generally difficult with current tools. One of the main difficulties of Deeplex Myc-TB is to interpret the non-synonymous uncharacterized variants that can represent up to 30% of the detected single nucleotide variants. We observed a good level of concordance between Deeplex Myc-TB-spoligotyping and MIRU-VNTR despite a lower discriminatory power for spoligotyping. The median time to obtain complete results from clinical samples was 8 days (IQR 7–13) provided a high-throughput NGS sequencing platform was available. Our results highlight that the GeneLEAD/Deeplex Myc-TB approach could be a breakthrough in rapid diagnosis of MDR TB in routine practice.

The Clinical and Laboratory Standards Institute recommends the use of Mueller Hinton (MH) medium to perform drug susceptibility testing (DST) of Mycobacterium avium complex (MAC) using the microdilution method. For MAC, there has been no study on the impact of media on the determination of minimum inhibitory concentrations (MICs) of antibiotics other than clarithromycin. This study aimed at determining the impact of two media used for DST of MAC and at augmenting the number of pertinent MICs for MAC species encountered in clinical practice. MICs of antibiotics used for the treatment of MAC infections were determined for 158 clinical MAC isolates (80 M. avium, 40 M. intracellulare, 35 M. chimaera, two M. yongonense and one M. timonense) in MH and 7H9 broths using the SLOMYCO SensititreTM system (TREK Diagnostic Systems, East Grinstead, United Kingdom). The modal MICs determined in both media were the same for linezolid, moxifloxacin, rifabutin and amikacin but not for clarithromycin, rifampin and ethambutol. The kappa test for MICs converted to susceptibility categories showed an excellent agreement for clarithromycin, a moderate agreement for linezolid and a weak agreement for moxifloxacin and amikacin. For amikacin, 7H9 allowed a better distinction (fewer intermediate strains) of wild-type populations than MH. Existing breakpoints for linezolid and moxifloxacin are spread through the distribution of MICs for wild-type populations. The only breakpoints that can be used rationally are those for amikacin and clarithromycin. For amikacin, 7H9 performs better than MH, whereas both media perform equally for clarithromycin. Given that testing in 7H9, as opposed to MH, allows easier MIC measurements and yields greater reproducibility, we propose the use of 7H9 medium for DST of MAC.

Ethionamide (ETH) is a second-line antituberculosis drug. ETH resistance (ETH-R) is mainly related to the mutations of the monooxygenase-activating ETH (EthA), the ETH target (InhA), and the inhA promoter. Nonetheless, diagnosing ETH-R is still challenging. We assessed the strategy used for detecting ETH-R at the French National Reference Center for Mycobacteria in 497 MDR-TB isolates received from 2008 to 2016. The genotypic ETH’s resistance detection was performed by sequencing ethA, ethR, the ethA-ethR intergenic region, and the inhA promoter in the 497 multidrug-resistant isolates, whereas the phenotypic ETH susceptibility testing (PST) was performed using the reference proportion method. Mutations were found in up to 76% of the 387 resistant isolates and in up to 28% of the 110 susceptible isolates. Our results do not support the role of ethR mutations in ETH resistance. Altogether, the positive predictive value of our genotypic strategy to diagnose ETH-R was improved when only considering the variants included in the WHO catalogue and in other databases, such as TB-Profiler. Therefore, our work will help to update the list of mutations that could be graded as being associated with resistance to improve ETH-R diagnosis.