Prediction of drug resistance by Sanger sequencing of Mycobacterium tuberculosis complex strains isolated from multidrug resistant tuberculosis suspect patients in Ethiopia

Exploring diagnostic methods for drug-resistant tuberculosis: A comprehensive overview

Despite available global efforts and funding, Tuberculosis (TB) continues to affect a considerable number of patients worldwide. Policy makers and stakeholders set clear goals to reduce TB incidence and mortality, but the emergence of multidrug-resistant TB (MDR-TB) and extensively drug-resistant TB (XDR-TB) complicate the reach of these goals. Drug-resistance TB needs to be diagnosed rapidly and accurately to effectively treat patients, prevent the transmission of MDR-TB, minimise mortality, reduce treatment costs and avoid unnecessary hospitalisations. In this narrative review, we provide a comprehensive overview of laboratory methods for detecting drug resistance in MTB, focusing on phenotypic, molecular and other drug susceptibility testing (DST) techniques. We found a large variety of methods used, with the BACTEC MGIT 960 being the most common phenotypic DST and the Xpert MTB/RIF being the most common molecular DST. We emphasise the importance of integrating phenotypic and molecular DST to address issues like resistance to new drugs, heteroresistance, mixed infections and low-level resistance mutations. Notably, most of the analysed studies adhered to the outdated definition of XDR-TB and did not consider the pre-XDR definition, thus posing challenges in aligning diagnostic methods with the current landscape of TB resistance.

Mycobacterium tuberculosis Lineage Distribution Using Whole-Genome Sequencing and Bedaquiline, Clofazimine, and Linezolid Phenotypic Profiles among Rifampicin-Resistant Isolates from West Java, Indonesia

Tuberculosis (TB) is caused by Mycobacterium tuberculosis infection. Indonesia is ranked second in the world for TB cases. New anti-TB drugs from groups A and B, such as bedaquiline, clofazimine, and linezolid, have been shown to be effective in curing drug resistance in TB patients, and Indonesia is already using these drugs to treat patients. However, studies comparing the TB strain types with anti-TB resistance profiles are still relevant to understanding the prevalent strains in the country and their phenotypic characteristics. This study aimed to determine the association between the TB lineage distribution using whole-genome sequencing and bedaquiline, clofazimine, and linezolid phenotypic profile resistance among M. tuberculosisrifampicin-resistant isolates from West Java. M. tuberculosis isolates stock of the Department of Microbiology, Faculty of Medicine, Universitas Indonesia, was tested against bedaquiline, clofazimine, and linezolid using a mycobacteria growth indicator tube liquid culture. All isolates were tested for M. tuberculosis and rifampicin resistance using Xpert MTB/RIF. The DNA genome of M. tuberculosis was freshly extracted from a Löwenstein-Jensen medium culture and then sequenced. The isolates showed phenotypically resistance to bedaquiline, clofazimine, and linezolid at 5%, 0%, and 0%, respectively. We identified gene mutations on phenotypically bedaquiline-resistant strains (2/3), and other mutations also found in phenotypically drug-sensitive strains. Mykrobe analysis showed that most (88.33%) of the isolates could be classified as rifampicin-resistant TB. Using Mykrobe and TB-Profiler to determine the lineage distribution, the isolates were found to belong to lineage 4 (Euro-American; 48.33%), lineage 2 (East Asian/Beijing; 46.67%), and lineage 1 (Indo-Oceanic; 5%). This work underlines the requirement to increase the representation of genotype-phenotype TB data while also highlighting the importance and efficacy of WGS in predicting medication resistance and inferring disease transmission.

Direct detection of drug-resistant Mycobacterium tuberculosis using targeted next generation sequencing

Mycobacterium tuberculosis complex (MTBC) infections are treated with combinations of antibiotics; however, these regimens are not as efficacious against multidrug and extensively drug resistant MTBC. Phenotypic (growth-based) drug susceptibility testing on slow growing bacteria like MTBC requires many weeks to months to complete, whereas sequencing-based approaches can predict drug resistance (DR) with reduced turnaround time. We sought to develop a multiplexed, targeted next generation sequencing (tNGS) assay that can predict DR and can be performed directly on clinical respiratory specimens. A multiplex PCR was designed to amplify a group of thirteen full-length genes and promoter regions with mutations known to be involved in resistance to first- and second-line MTBC drugs. Long-read amplicon libraries were sequenced with Oxford Nanopore Technologies platforms and high-confidence resistance mutations were identified in real-time using an in-house developed bioinformatics pipeline. Sensitivity, specificity, reproducibility, and accuracy of the tNGS assay was assessed as part of a clinical validation study. In total, tNGS was performed on 72 primary specimens and 55 MTBC-positive cultures and results were compared to clinical whole genome sequencing (WGS) performed on paired patient cultures. Complete or partial susceptibility profiles were generated from 82% of smear positive primary specimens and the resistance mutations identified by tNGS were 100% concordant with WGS. In addition to performing tNGS on primary clinical samples, this assay can be used to sequence MTBC cultures mixed with other mycobacterial species that would not yield WGS results. The assay can be effectively implemented in a clinical/diagnostic laboratory with a two to three day turnaround time and, even if batched weekly, tNGS results are available on average 15 days earlier than culture-derived WGS results. This study demonstrates that tNGS can reliably predict MTBC drug resistance directly from clinical specimens or cultures and provide critical information in a timely manner for the appropriate treatment of patients with DR tuberculosis.

In Silico Design and Investigation of Novel Thiazetidine Derivatives as Potent Inhibitors of PrpR in Mycobacterium tuberculosis

Tuberculosis is one of the most life-threatening acute infectious diseases diagnosed in humans. In the present investigation, a series of 16 new disubstituted 1,3-thiazetidines derivatives is designed, and investigated via various in silico methods for their potential as anti-tubercular agent by evaluating their ability to block the active site of PrpR transcription factor protein of Mycobacterium tuberculosis. The efficacy of the molecules was initially assessed with the help of AutoDock Vina algorithm. Further Glide module is used to redock the previously docked complexes. The binding energies and other physiochemical properties of the designed molecules were evaluated using the Prime-MM/GBSA and the QikProp module, respectively. The results of docking revealed the nature, site of interaction and the binding affinity between the proposed candidates and the active site of PrpR. Further the inhibitory effect of the scaffolds was predicted and evaluated employing a machine learning-based algorithm and was used accordingly. Further, the molecular dynamics simulation studies ascertained the binding characteristics of the unique 13, when analysed across a time frame of 100 ns with GROMACS software. The results show that the proposed 1,3-thiazetidine derivatives such as 10, 11, 13 and 14 could be potent and selective anti-tubercular agents as compared to the standard drug Pyrazinamide. Finally, this study concludes that designed thiazetidines can be employed as anti-tubercular agents. Undeniably, the results may guide the experimental biologists to develop safe and non-toxic drugs against tuberculosis by demanding further in vivo and in vitro analyses.