Disputed rpoB Mutations in Mycobacterium tuberculosis and Tuberculosis Treatment Outcomes

Unraveling resistance mechanisms in combination therapy: A comprehensive review of recent advances and future directions

Antimicrobial resistance is a global health threat. Misuse and overuse of antimicrobials are the main drivers in developing drug-resistant bacteria. The emergence of the rapid global spread of multi-resistant bacteria requires urgent multisectoral action to generate novel treatment alternatives. Combination therapy offers the potential to exploit synergistic effects for enhanced antibacterial efficacy of drugs. Understanding the complex dynamics and kinetics of drug interactions in combination therapy is crucial. Therefore, this review outlines the current advances in antibiotic resistance's evolutionary and genetic dynamics in combination therapies-exposed bacteria. Moreover, we also discussed four pivotal future research areas to comprehend better the development of antibiotic resistance in bacteria treated with combination strategies.

Rapid detection of multidrug resistance in tuberculosis using nanopore-based targeted next-generation sequencing: a multicenter, double-blind study

Background

Resistance to anti-tuberculous drugs is a major challenge in the treatment of tuberculosis (TB). We aimed to evaluate the clinical availability of nanopore-based targeted next-generation sequencing (NanoTNGS) for the diagnosis of drug-resistant tuberculosis (DR-TB).

Methods

This study enrolled 253 patients with suspected DR-TB from six hospitals. The diagnostic efficacy of NanoTNGS for detecting Mycobacterium tuberculosis and its susceptibility or resistance to first- and second-line anti-tuberculosis drugs was assessed by comparing conventional phenotypic drug susceptibility testing (pDST) and Xpert MTB/RIF assays. NanoTNGS can be performed within 12 hours from DNA extraction to the result delivery.

Results

NanoTNGS showed a remarkable concordance rate of 99.44% (179/180) with the culture assay for identifying the Mycobacterium tuberculosis complex. The sensitivity of NanoTNGS for detecting drug resistance was 93.53% for rifampicin, 89.72% for isoniazid, 85.45% for ethambutol, 74.00% for streptomycin, and 88.89% for fluoroquinolones. Specificities ranged from 83.33% to 100% for all drugs tested. Sensitivity for rifampicin-resistant tuberculosis using NanoTNGS increased by 9.73% compared to Xpert MTB/RIF. The most common mutations were S531L (codon in E. coli) in the rpoB gene, S315T in the katG gene, and M306V in the embB gene, conferring resistance to rifampicin, isoniazid, and ethambutol, respectively. In addition, mutations in the pncA gene, potentially contributing to pyrazinamide resistance, were detected in 32 patients. Other prevalent variants, including D94G in the gyrA gene and K43R in the rpsL gene, conferred resistance to fluoroquinolones and streptomycin, respectively. Furthermore, the rv0678 R94Q mutation was detected in one sample, indicating potential resistance to bedaquiline.

Conclusion

NanoTNGS rapidly and accurately identifies resistance or susceptibility to anti-TB drugs, outperforming traditional methods. Clinical implementation of the technique can recognize DR-TB in time and provide guidance for choosing appropriate antituberculosis agents.

Whole-genome sequencing-based analyses of drug-resistant Mycobacterium tuberculosis from Taiwan

Drug-resistant tuberculosis (DR-TB) posed challenges to global TB control. Whole-genome sequencing (WGS) is recommended for predicting drug resistance to guide DR-TB treatment and management. Nevertheless, data are lacking in Taiwan. Phenotypic drug susceptibility testing (DST) of 12 anti-TB drugs was performed for 200 Mycobacterium tuberculosis isolates. WGS was performed using the Illumina platform. Drug resistance profiles and lineages were predicted in silico using the Total Genotyping Solution for TB (TGS-TB). Using the phenotypic DST results as a reference, WGS-based prediction demonstrated high concordance rates of isoniazid (95.0%), rifampicin (RIF) (98.0%), pyrazinamide (98.5%) and fluoroquinolones (FQs) (99.5%) and 96.0% to 99.5% for second-line injectable drugs (SLIDs); whereas, lower concordance rates of ethambutol (87.5%), streptomycin (88.0%) and ethionamide (84.0%). Furthermore, minimum inhibitory concentrations confirmed that RIF rpoB S450L, FQs gyrA D94G and SLIDs rrs a1401g conferred high resistance levels. Besides, we identified lineage-associated mutations in lineage 1 (rpoB H445Y and fabG1 c-15t) and predominant lineage 2 (rpoB S450L and rpsL K43R). The WGS-based prediction of drug resistance is highly concordant with phenotypic DST results and can provide comprehensive genetic information to guide DR-TB precision therapies in Taiwan.

Reevaluating Rifampicin Breakpoint Concentrations for Mycobacterium tuberculosis Isolates with Disputed rpoB Mutations and Discordant Susceptibility Phenotypes

In this study, rifampicin resistance breakpoints based on MICs of disrupted rpoB mutants of Mycobacterium tuberculosis (MTB) were explored using the Mycobacteria Growth Indicator Tube (MGIT) system and microplate alamarBlue assay (MABA). Sixty-one MTB isolates with disputed low-level rifampicin resistance-associated rpoB mutations and 40 RIF-susceptible wild-type isolates were included. Among the 61 resistant isolates, 25 (41.0%) had MICs ≥2.0 mg/L via MABA, while 16 (26.2%) were identified as RIF resistant via MGIT. Epidemiological cut-off (ECOFF) values obtained using MABA and MGIT were 0.25 and 0.125 mg/L, respectively. Based on 0.125 mg/L as a tentative critical concentration (CC), MABA RIF resistance-detection sensitivity was 93.4%, prompting the reduction of the MGIT CC to 0.125 mg/L, given that only a single isolate (1.6%) with the borderline mutation would be misclassified as susceptible to RIF based on this CC. Based on DNA sequencing of RRDR as the gold standard, the diagnostic accuracy of MGIT (99.0%) was significantly higher than that of MABA (91.1%). MICs of Leu⁵¹¹Pro mutant isolates were negatively correlated with time to liquid culture positivity (TTP) in our analysis (R = 0.957, P < 0.01). In conclusion, our results demonstrated missed detection of a high proportion of rifampicin-resistant isolates based on the WHO-endorsed CC. Such missed detections would be avoided by reducing the optimal MGIT RIF CC to 0.125 mg/L. In addition, MGIT based on reduced CC outperformed MABA in detecting borderline RIF resistance, with MABA MIC results obtained for isolates with the same mutation correlating with MTB growth rate.

IMPORTANCE Tuberculosis (TB) is still one of the world's leading infectious disease killers. The early and accurate diagnosis of RIF resistance is necessary to deliver timely and appropriate treatment for TB patients and improve their clinical outcome. Actually, a proportion of MTB isolates with disputed rpoB mutations present a diagnostic dilemma between Xpert and phenotypical drug susceptibility testing (pDST). Recently, WHO reported a pragmatic approach by lowering critical concentration (CC) to boost sensitivity of resistance detection of pDST. Therefore, a detailed analysis of the association between RIF susceptibility and disrupted mutations within rpoB gene would lay a foundation to assess the diagnostic accuracy of pDST with lowering RIF CC. In this study, we aim to determine the MICs of MTB isolates with disrupted mutations by MGIT and microplate alamarBlue assay (MABA). We also aimed to determine the optimal breakpoints for MTB isolates with these mutations.