Mycobacterium Tuberculosis Drug Research Articles

Suppressing Mycobacterium tuberculosis virulence and drug resistance by targeting Eis protein through computational drug discovery.

Tuberculosis (TB) remains a critical health threat, particularly with the emergence of multidrug-resistant strains. This demands attention from scientific communities and healthcare professionals worldwide to develop effective treatments. The enhanced intracellular survival (Eis) protein is an acetyltransferase enzyme of Mycobacterium tuberculosis that functions by adding acetyl groups to aminoglycoside antibiotics, which interferes with their ability to bind to the bacterial ribosome, thereby preventing them from inhibiting protein synthesis and killing the bacterium. Therefore, targeting this protein accelerates the chance of restoring the aminoglycoside drug activity, thereby reducing the emergence of drug-resistant TB. For this, we have screened 406,747 natural compounds from the Coconut database against Eis protein. Based on MM/GBSA rescoring binding energy, the top 5 most prominent natural compounds, viz. CNP0187003 (-96.14kcal/mol), CNP0176690 (-93.79kcal/mol), CNP0136537 (-92.31kcal/mol), CNP0398701 (-91.96kcal/mol), and CNP0043390 (-91.60kcal/mol) were selected. These compounds exhibited the presence of a substantial number of hydrogen bonds and other significant interactions confirming their strong binding affinity with the Eis protein during the docking process. Subsequently, the MD simulation of these compounds exhibited that the Eis-CNP0043390 complex was the most stable, followed by Eis-CNP0187003 and Eis-CNP0176690 complex, further verified by binding free energy calculation, principal component analysis (PCA), and Free energy landscape analysis. These compounds demonstrated the most favourable results in all parameters utilised for this investigation and may have the potential to inhibit the Eis protein. There these findings will leverage computational techniques to identify and develop a natural compound inhibitor as an alternative for drug-resistant TB.

Microbiota alterations in patients treated for susceptible or drug-resistant TB.

We investigated alterations of human microbiota under anti-TB therapies in relationship to the level of Mycobacterium tuberculosis drug response. Stool, sputum, and oral swab samples were analysed from participants with treatment-naïve TB and participants treated for drug-susceptible TB (DS-TB), drug-resistant TB without injectable drugs (DR-TB-inj-), or with injectable drugs (DR-TB-inj+) at 27-42 days of therapy. From September 2018 to December 2019, 5 participants with treatment-naïve TB, 6 participants with DS-TB, 10 participants with DR-TB-inj-, and 4 participants with DR-TB-inj+ were recruited. Reduced alpha diversities in stool samples indicated more profound dysbiosis in participants treated for DR-TB than in participants treated for DS-TB (-12% (non-significant) for DS-TB, -44% (P < 0.001) for DR-TB-inj-, and -60% (P < 0.05) for DR-TB-inj+ compared to treatment-naïve participants). While reduced abundances were observed in numerous taxa, genus Lactobacillus revealed the most substantial abundance increase in sputa of participants treated for DR-TB compared to treatment-naïve ones (P < 0.05 for DR-TB-inj- and DR-TB-inj+). Notably, a group of nosocomial pneumonia-associated taxa was increased in oral swabs of the DR-TB-inj+ compared to the treatment-naïve group (P < 0.05). Second-line anti-TB therapy in participants with DR-TB results in altered microbiota, including reduced alpha diversity and expansion of phylogenetically diverse taxa, including pathobionts.

Mycobacterium tuberculosis Drug Resistance and Evaluation of the Current Situation

Aim: We aimed to determine the antituberculosis drug susceptibility status in Mycobacterium tuberculosis complex isolates, considering that current drug resistance rates will be an important indicator of the prevalence of primary drug resistance in the future. Material and Methods: All cases whose culture sample was taken with clinical suspicion of tuberculosis at Samsun Training and Research Hospital in the period between January 2018 and December 2023 and who had a positive result in at least one of the Acid-fast stain (AFS) and culture methods were included in the study. Results: The average age of the patients was 54.5±18.5 (range: 17-93) and 398 (74.1%) were male. In the study, 77.3% of the samples were sputum and 15.8% were bronchoalveolar lavage. 474 (88.3%) of the isolates were M. tuberculosis complex. 49% of the samples were positive with the AFS method, 96.5% with Mycobacteria Growth Indicator Tube (MGIT), and 84.5% with Löwenstein-Jensen (LJ) medium. The resistance rates in the isolates were 10.6%, 2.8%, 1.1% and 7.0% for isoniazid, rifampicin, ethambutol and streptomycin, respectively. All isolates resistant to rifampicin were also resistant to isoniazid. The rate of multidrug-resistant isolates was found to be 2.8%. The single drug resistance rate was found to be 14.0%. It was determined that the resistance rates before the pandemic were significantly higher than during the pandemic period. Conclusion: The resistance rates to isoniazid and streptomycin in M. tuberculosis complex isolates were around 10% and that the general resistance rates to primary anti-tuberculosis drugs decreased significantly during the pandemic period.

Identification of Mycobacterium tuberculosis Resistance to Common Antibiotics: An Overview of Current Methods and Techniques.

Multidrug-resistant tuberculosis (MDR-TB) is an essential cause of tuberculosis treatment failure and death of tuberculosis patients. The rapid and reliable profiling of Mycobacterium tuberculosis (MTB) drug resistance in the early stage is a critical research area for public health. Then, most traditional approaches for detecting MTB are time-consuming and costly, leading to the inappropriate therapeutic schedule resting on the ambiguous information of MTB drug resistance, increasing patient economic burden, morbidity, and mortality. Therefore, novel diagnosis methods are frequently required to meet the emerging challenges of MTB drug resistance distinguish. Considering the difficulty in treating MDR-TB, it is urgently required for the development of rapid and accurate methods in the identification of drug resistance profiles of MTB in clinical diagnosis. This review discussed recent advances in MTB drug resistance detection, focusing on developing emerging approaches and their applications in tangled clinical situations. In particular, a brief overview of antibiotic resistance to MTB was present, referred to as intrinsic bacterial resistance, consisting of cell wall barriers and efflux pumping action and acquired resistance caused by genetic mutations. Then, different drug susceptibility test (DST) methods were described, including phenotype DST,genotype DST and novel DST methods. The phenotype DST includes nitrate reductase assay, RocheTM solid ratio method, and liquid culture method and genotype DST includes fluorescent PCR, GeneXpert, PCR reverse dot hybridization, ddPCR, next-generation sequencing and gene chips. Then, novel DST methods were described, including metabolism testing, cell-free DNA probe, CRISPR assay, and spectral analysis technique. The limitations, challenges, and perspectives of different techniques for drug resistance are also discussed. These methods significantly improve the detection sensitivity and accuracy of multidrug-resistant tuberculosis (MRT) and can effectively curb the incidence of drug-resistant tuberculosis and accelerate the process of tuberculosis eradication.

Patterns and profiles of drug resistance-conferring mutations in Mycobacterium tuberculosis genotypes isolated from tuberculosis-suspected attendees of spiritual holy water sites in Northwest Ethiopia.

This study examined the patterns and frequency of genetic changes responsible for resistance to first-line (rifampicin and isoniazid), fluoroquinolones, and second-line injectable drugs in drug-resistant Mycobacterium tuberculosis (MTB) isolated from culture-positive pulmonary tuberculosis (PTB) symptomatic attendees of spiritual holy water sites (HWSs) in the Amhara region. From June 2019 to March 2020, a cross-sectional study was carried out. A total of 122 culture-positive MTB isolates from PTB-suspected attendees of HWSs in the Amhara region were evaluated for their drug resistance profiles, and characterized gene mutations conferring resistance to rifampicin (RIF), isoniazid (INH), fluoroquinolones (FLQs), and second-line injectable drugs (SLIDs) using GenoType®MTBDRplus VER2.0 and GenoType®MTBDRsl VER2.0. Drug-resistant MTB isolates were Spoligotyped following the manufacturer's protocol. Genetic changes (mutations) responsible for resistance to RIF, INH, and FLQs were identified in 15/122 (12.3%), 20/122 (16.4%), and 5/20 (25%) of MTB isolates, respectively. In RIF-resistant, rpoB/Ser531Lue (n = 12, 80%) was most frequent followed by His526Tyr (6.7%). Amongst INH-resistant isolates, katG/Ser315Thr1 (n = 19, 95%) was the most frequent. Of 15 MDR-TB, the majority (n = 12, 80%) isolates had mutations at both rpoB/Ser531Leu and katG/Ser315Thr1. All 20 INH and/or RIF-resistant isolates were tested with the MTBDRsl VER 2.0, yielding 5 FLQs-resistant isolates with gene mutations at rpoB/Ser531Lue, katG/Ser315Thr1, and gyrA/Asp94Ala genes. Of 20 Spoligotyped drug-resistant MTB isolates, the majority (n = 11, 55%) and 6 (30%) were SIT149/T3-ETH and SIT21/CAS1-Kili sublineages, respectively; and they were any INH-resistant (mono-hetero/multi-). Of 15 RIF-resistant (RR/MDR-TB) isolates, 7 were SIT149/T3-ETH, while 6 were SIT21/CAS1-Kili sublineages. FLQ resistance was detected in four SIT21/CAS1-Kili lineages. In the current study, the most common gene mutations responsible for resistance to INH, RIF, and FLQs were identified. SIT149/T3-ETH and SIT21/CAS1-Kili constitute the majority of drug-resistant TB (DR-TB) isolates. To further understand the complete spectrum of genetic changes/mutations and related genotypes, a sequencing technology is warranted.

Mechanisms of Mycobacterium tuberculosis Drug Resistance

Mechanisms of Mycobacterium tuberculosis Drug Resistance

Inferring Mycobacterium Tuberculosis Drug Resistance and Transmission using Whole-genome Sequencing in a High TB-burden Setting in China

ObjectiveChina is among the 30 countries with a high burden of tuberculosis (TB) worldwide, and TB remains a public health concern. Kashgar Prefecture in the southern Xinjiang Autonomous Region is considered as one of the highest TB burden regions in China. However, molecular epidemiological studies of Kashgar are lacking. MethodsA population-based retrospective study was conducted using whole-genome sequencing (WGS) to determine the characteristics of drug resistance and the transmission patterns. ResultsA total of 1,668 isolates collected in 2020 were classified into lineages 2 (46.0%), 3 (27.5%), and 4 (26.5%). The drug resistance rates revealed by WGS showed that the top three drugs in terms of the resistance rate were isoniazid (7.4%, 124/1,668), streptomycin (6.0%, 100/1,668), and rifampicin (3.3%, 55/1,668). The rate of rifampicin resistance was 1.8% (23/1,290) in the new cases and 9.4% (32/340) in the previously treated cases. Known resistance mutations were detected more frequently in lineage 2 strains than in lineage 3 or 4 strains, respectively: 18.6% vs. 8.7 or 9%, P < 0.001. The estimated proportion of recent transmissions was 25.9% (432/1,668). Multivariate logistic analyses indicated that sex, age, occupation, lineage, and drug resistance were the risk factors for recent transmission. Despite the low rate of drug resistance, drug-resistant strains had a higher risk of recent transmission than the susceptible strains (adjusted odds ratio, 1.414; 95% CI, 1.023–1.954; P = 0.036). Among all patients with drug-resistant tuberculosis (DR-TB), 78.4% (171/218) were attributed to the transmission of DR-TB strains. ConclusionOur results suggest that drug-resistant strains are more transmissible than susceptible strains and that transmission is the major driving force of the current DR-TB epidemic in Kashgar.

Molecular Docking Study on Phytochemicals of Alpinia galanga and Their Derivatives as Inhibitors of β-Ketoacyl Reductase (MabA) of Mycobacterium Tuberculosis: An In-silico Study

Introduction: Tuberculosis (TB), an infectious disease caused by the bacterium Mycobacterium Tuberculosis (MTB), continues to be a global health problem. Alpinia galanga (Linn.) of the Zingiberaceae family has antitubercular properties, and their mode of action in in-vitro as well as in-vivo conditions is well established. This knowledge of the active phytochemicals of Alpinia galanga has been utilised to identify new potent drugs for MTB. Aim: To perform molecular docking studies of various phytochemicals of Alpinia galanga and their derivatives with β-ketoacyl reductase (MabA) of MTB. Materials and Methods: The present study is an in-silico study conducted in the Bioinformatics facility of the Central Research Laboratory of Tagore Medical College and Hospital, Chennai, Tamil Nadu, India from November 2022 to April 2023. The receptor protein was downloaded from the Research Collaboratory for Structural Bioinformatics (RCSB) database. The phytochemicals in. sdf format were downloaded from the PubChem database. The derivatives were prepared by Chemsketch software. Docking was performed using AutoDock Vina with PyRx as the GUI (Graphical User Interface). Postdocking analysis was performed in LigPlot+. Results: Phytochemicals from Alpinia galanga were obtained from the PubChem database and docked with MabA of MTB. The derivatives were further subjected to docking analyses. From the docking study, two molecules, namely, (1E,6Z)-2,4-diamino6-fluoro-1,7-bis(4-hydroxyphenyl)-1-sulfanylhepta-1,6-diene3,5-dione and (2E,6Z,10E)-2,6,9,9-tetrakis(hydroxymethyl) cycloundeca-2,6,10-trien-1-one-ethane (1/1), were found to have good binding energy values. Conclusion: The present study helped us find drug-like molecules that can inhibit the MabA of MTB. Two compounds derived from the phytochemicals of A. galanga were found to have an effective binding capacity to the drug target in-silico. Hence, the outcome of present study has provided a therapeutic strategy for TB, especially for strains of MTB that are drug-resistant.

Mycobacterium tuberculosis drugs resistance mechanisms

Mycobacterium tuberculosis drugs resistance mechanisms

Rapid Diagnosis of Drug-Resistant Tuberculosis-Opportunities and Challenges.

Global tuberculosis (TB) eradication is undermined by increasing prevalence of emerging resistance to available drugs, fuelling ongoing demand for more complex diagnostic and treatment strategies. Early detection of TB drug resistance coupled with therapeutic decision making guided by rapid characterisation of pre-treatment and treatment emergent resistance remains the most effective strategy for averting Drug-Resistant TB (DR-TB) transmission, reducing DR-TB associated mortality, and improving patient outcomes. Solid- and liquid-based mycobacterial culture methods remain the gold standard for Mycobacterium tuberculosis (MTB) detection and drug susceptibility testing (DST). Unfortunately, delays to result return, and associated technical challenges from requirements for specialised resource and capacity, have limited DST use and availability in many high TB burden resource-limited countries. There is increasing availability of a variety of rapid nucleic acid-based diagnostic assays with adequate sensitivity and specificity to detect gene mutations associated with resistance to one or more drugs. While a few of these assays produce comprehensive calls for resistance to several first- and second-line drugs, there is still no endorsed genotypic drug susceptibility test assay for bedaquiline, pretomanid, and delamanid. The global implementation of regimens comprising these novel drugs in the absence of rapid phenotypic drug resistance profiling has generated a new set of diagnostic challenges and heralded a return to culture-based phenotypic DST. In this review, we describe the available tools for rapid diagnosis of drug-resistant tuberculosis and discuss the associated opportunities and challenges.

A precision overview of genomic resistance screening in Ecuadorian isolates of Mycobacterium tuberculosis using web-based bioinformatics tools.

Tuberculosis (TB) is among the deadliest diseases worldwide, and its impact is mainly due to the continuous emergence of resistant isolates during treatment due to the laborious process of resistance diagnosis, nonadherence to treatment and circulation of previously resistant isolates of Mycobacterium tuberculosis. In this study, we evaluated the performance and functionalities of web-based tools, including Mykrobe, TB-profiler, PhyResSE, KvarQ, and SAM-TB, for detecting resistance in 88 Ecuadorian isolates of Mycobacterium tuberculosis drug susceptibility tested previously. Statistical analysis was used to determine the correlation between genomic and phenotypic analysis. Our results showed that with the exception of KvarQ, all tools had the highest correlation with the conventional drug susceptibility test (DST) for global resistance detection (98% agreement and 0.941 Cohen's kappa), while SAM-TB, PhyResSE, TB-profiler and Mykrobe had better correlations with DST for first-line drug analysis individually. We also identified that in our study, only 50% of mutations characterized by the web-based tools in the rpoB, katG, embB, pncA, gyrA and rrs regions were canonical and included in the World Health Organization (WHO) catalogue. Our findings suggest that SAM-TB, PhyResSE, TB-profiler and Mykrobe were efficient in determining canonical resistance-related mutations, but more analysis is needed to improve second-line detection. Improving surveillance programs using whole-genome sequencing tools for first-line drugs, MDR-TB and XDR-TB is essential to understand the molecular epidemiology of TB in Ecuador. Tuberculosis, an infectious disease caused by Mycobacterium tuberculosis, most commonly affects the lungs and is often spread through the air when infected people cough, sneeze, or spit. However, despite the existence of effective drug treatment, patient adherence, long duration of treatment, and late diagnosis have reduced the effectiveness of therapy and increased drug resistance. The increase in resistant cases, added to the impact of the COVID-19 pandemic, has highlighted the importance of implementing efficient and timely diagnostic methodologies worldwide. The significance of our research is in evaluating and identifying a more efficient and user-friendly web-based tool to characterize resistance in Mycobacterium tuberculosis by whole-genome sequencing, which will allow more routine application to improve TB strain surveillance programs locally.

Comprehensive assessment of invalid and indeterminate results in Truenat MTB-RIF testing across sites under the national TB elimination program of India.

Truenat MTB-RIF assay (Truenat), a nucleic acid amplification test (NAAT), is a real-time polymerase chain reaction (RT-PCR) chip-based assay that can detect Mycobacterium tuberculosis (Mtb) and rifampicin (RIF) drug resistance using portable, battery-operated devices. The National TB Elimination Program (NTEP) in India introduced this novel tool at the district and subdistrict level in 2020. This study aimed to assess the level and causes of inconclusive results (invalid results, errors, and indeterminate results) in MTB and RIF testing at NTEP sites and the root causes of these in the programmatic setting. Truenat testing data from 1,690 functional Truenat sites under the NTEP from April to June 2021 were analyzed to assess the rates of errors, invalid MTB results, and indeterminate RIF results. Following this analysis, 12 Truenat sites were selected based on site performance in Truenat testing, diversity of climatic conditions, and geographical terrain. These sites were visited to assess the root causes of their high and low rates of inconclusive results using a structured checklist. A total of 327,649 Truenat tests performed for MTB and RIF testing were analyzed. The rate of invalid MTB results was 5.2% [95% confidence interval (CI): 5.11-5.26; n = 16,998] and the rate of errors was 2.5% (95% CI: 2.46-2.57; n = 8,240) in Truenat MTB chip testing. For Mtb-positive samples tested using the Truenat RIF chip for detection of RIF resistance (n = 40,926), the rate of indeterminate results was 15.3% (95% CI: 14.97-15.67; n = 6,267) and the rate of errors was 1.6% (95% CI: 1.53-1.78; n = 675). There was a 40.1% retesting gap for Mtb testing and a 78.2% gap for inconclusive RR results. Among the inconclusive results retested, 27.9% (95% CI: 27.23-28.66; n = 4,222) were Mtb-positive, and 9.2% (95% CI: 7.84-10.76; n = 139) were detected as RR. The main causes affecting Truenat testing performance include suboptimal adherence to standard operating procedures (SOPs), inadequate training, improper storage of testing kits, inadequate sputum quality, lack of quality control, and delays in the rectification of machine issues. Root cause analysis identified that strengthening of training, external quality control, and supervision could improve the rate of inconclusive results. Ensuring hands-on training of technicians for Truenat testing and retesting of samples with inconclusive results are major recommendations while planning for Truenat scale-up. The recommendations from the study were consolidated into technical guidance documents and videos and disseminated to laboratory staff working at the tiered network of TB laboratories under the NTEP in order to improve Truenat MTB-RIF testing performance.

State-of-the-art strategies to prioritize Mycobacterium tuberculosis drug targets for drug discovery using a subtractive genomics approach

Tuberculosis remains one of the causes of death from a single infectious bacterium. The inappropriate use of antibiotics and patients’ non-compliance among other factors drive the emergence of drug-resistant tuberculosis. Multidrug-resistant and extensively drug-resistant strains of tuberculosis pose significant challenges to current treatment regimens, as their reduced efficacy against these strains limits successful patient outcomes. Furthermore, the limited effectiveness and associated toxicity of second-line drugs further compound the issue. Moreover, the scarcity of novel pharmacological targets and the subsequent decline in the number of anti-TB compounds in the drug development pipeline has further hindered the emergence of new therapies. As a result, researchers need to develop innovative approaches to identify potential new anti-TB drugs. The evolution of technology and the breakthrough in omics data allow the use of computational biology approaches, for example, metabolomic analysis to uncover pharmacological targets for structured-based drug design. The role of metabolism in pathogen development, growth, survival, and infection has been established. Therefore, this review focuses on the M. tb metabolic network as a hub for novel target identification and highlights a step-by-step subtractive genomics approach for target prioritization.

Overcoming Mycobacterium tuberculosis Drug Resistance: Novel Medications and Repositioning Strategies.

Mycobacterium tuberculosis, the bacterium responsible for tuberculosis, is a global health concern, affecting millions worldwide. This bacterium has earned a reputation as a formidable adversary due to its multidrug-resistant nature, allowing it to withstand many antibiotics. The development of this drug resistance in Mycobacterium tuberculosis is attributed to innate and acquired mechanisms. In the past, rifampin was considered a potent medication for treating tuberculosis infections. However, the rapid development of resistance to this drug by the bacterium underscores the pressing need for new therapeutic agents. Fortunately, several other medications previously overlooked for tuberculosis treatment are already available in the market. Moreover, several innovative drugs are under clinical investigation, offering hope for more effective treatments. To enhance the effectiveness of these drugs, it is recommended that researchers concentrate on identifying unique target sites within the bacterium during the drug development process. This strategy could potentially circumvent the issues presented by Mycobacterium drug resistance. This review primarily focuses on the characteristics of novel drug resistance mechanisms in Mycobacterium tuberculosis. It also discusses potential medications being repositioned or sourced from novel origins. The ultimate objective of this review is to discover efficacious treatments for tuberculosis that can successfully tackle the hurdles posed by Mycobacterium drug resistance.

Drug resistance prediction for Mycobacterium tuberculosis with reference graphs.

Tuberculosis is a global pandemic disease with a rising burden of antimicrobial resistance. As a result, the World Health Organization (WHO) has a goal of enabling universal access to drug susceptibility testing (DST). Given the slowness of and infrastructure requirements for phenotypic DST, whole-genome sequencing, followed by genotype-based prediction of DST, now provides a route to achieving this. Since a central component of genotypic DST is to detect the presence of any known resistance-causing mutations, a natural approach is to use a reference graph that allows encoding of known variation. We have developed DrPRG (Drug resistance Prediction with Reference Graphs) using the bacterial reference graph method Pandora. First, we outline the construction of a Mycobacterium tuberculosis drug resistance reference graph. The graph is built from a global dataset of isolates with varying drug susceptibility profiles, thus capturing common and rare resistance- and susceptible-associated haplotypes. We benchmark DrPRG against the existing graph-based tool Mykrobe and the haplotype-based approach of TBProfiler using 44 709 and 138 publicly available Illumina and Nanopore samples with associated phenotypes. We find that DrPRG has significantly improved sensitivity and specificity for some drugs compared to these tools, with no significant decreases. It uses significantly less computational memory than both tools, and provides significantly faster runtimes, except when runtime is compared to Mykrobe with Nanopore data. We discover and discuss novel insights into resistance-conferring variation for M. tuberculosis - including deletion of genes katG and pncA - and suggest mutations that may warrant reclassification as associated with resistance.

Whole-Genome Sequencing to Predict Mycobacterium tuberculosis Drug Resistance: A Retrospective Observational Study in Eastern China.

Pulmonary tuberculosis (TB) is an infectious disease caused by Mycobacterium tuberculosis (MTB). Whole-genome sequencing (WGS) holds great promise as an advanced technology for accurately predicting anti-TB drug resistance. The development of a reliable method for detecting drug resistance is crucial in order to standardize anti-TB treatments, enhance patient prognosis, and effectively reduce the risk of transmission. In this study, our primary objective was to explore and determine the potential of WGS for assessing drug resistance based on genetic variants recommended by the World Health Organization (WHO). A total of 1105 MTB strains were selected from samples collected from 2014-2018 in Zhejiang Province, China. Phenotypic drug sensitivity tests (DST) of the anti-TB drugs were conducted for isoniazid (INH), rifampicin (RFP), streptomycin, ethambutol, fluoroquinolones (levofloxacin and moxifloxacin), amikacin, kanamycin, and capreomycin, and the drug-resistance rates were calculated. The clean WGS data of the 1105 strains were acquired and analyzed. The predictive performance of WGS was evaluated by the comparison between genotypic and phenotypic DST results. For all anti-TB drugs, WGS achieved good specificity values (>90%). The sensitivity values for INH and RFP were 91.78% and 82.26%, respectively; however, they were ≤60% for other drugs. The positive predictive values for anti-TB drugs were >80%, except for ethambutol and moxifloxacin, and the negative predictive values were >90% for all drugs. In light of the findings from our study, we draw the conclusion that WGS is a valuable tool for identifying genome-wide variants. Leveraging the genetic variants recommended by the WHO, WGS proves to be effective in detecting resistance to RFP and INH, enabling the identification of multi-drug resistant TB patients. However, it is evident that the genetic variants recommended for predicting resistance to other anti-TB drugs require further optimization and improvement.

Investigating the Roles of Active Site Residues in Mycobacterium tuberculosis Indole-3-glycerol Phosphate Synthase, a Potential Target for Antitubercular Agents.

Mycobacterium tuberculosis drug resistance is emerging and new drug targets are needed. Tryptophan biosynthesis is necessary for M. tuberculosis replication and virulence. Indole-3-glycerol phosphate synthase (IGPS) catalyzes a step in M. tuberculosis tryptophan biosynthesis and has been suggested as a potential anti-infective target, but our understanding of this enzyme is limited. To aid in inhibitor design and gain a greater mechanistic picture of this enzyme, there is a need to understand the roles of active site amino acids in ligand binding and catalysis. In this work, we explored the roles of conserved active site amino acids Glu57, Lys59, Lys119, Glu168, and Glu219. Mutation of each to Ala results in loss of all detectable activity. The Glu57Gln, Lys59Arg, Lys119Arg, Glu168Gln, and Glu219Asp mutations result in large activity losses, while Glu219Gln has enhanced activity. Analysis of the enzymatic data yields the following main conclusions: (A) Lys119 is the likely catalytic acid in the CdRP ring closure step. (B) Glu168 stabilizes a charged reaction intermediate and may also be the catalytic base. (C) Glu57, Glu219, and Lys119 form a closely arranged triad in which Glu57 and Glu219 modulate the pKa of Lys119, and thus overall activity. This increased understanding of inter- and intramolecular interactions and demonstration of the highly coordinated nature of the M. tuberculosis IGPS active site provide new mechanistic information and guidance for future work with this potential new drug target.

Design, Synthesis, and Evaluation of Novel Δ2-Thiazolino 2-Pyridone Derivatives That Potentiate Isoniazid Activity in an Isoniazid-Resistant Mycobacterium tuberculosis Mutant.

Mycobacterium tuberculosis (Mtb) drug resistance poses an alarming threat to global tuberculosis control. We previously reported that C10, a ring-fused thiazolo-2-pyridone, inhibits Mtb respiration, blocks biofilm formation, and restores the activity of the antibiotic isoniazid (INH) in INH-resistant Mtb isolates. This discovery revealed a new strategy to address INH resistance. Expanding upon this strategy, we identified C10 analogues with improved potency and drug-like properties. By exploring three heterocycle spacers (oxadiazole, 1,2,3-triazole, and isoxazole) on the ring-fused thiazolo-2-pyridone scaffold, we identified two novel isoxazoles, 17h and 17j. 17h and 17j inhibited Mtb respiration and biofilm formation more potently with a broader therapeutic window, were better potentiators of INH-mediated inhibition of an INH-resistant Mtb mutant, and more effectively inhibited intracellular Mtb replication than C10. The (-)17j enantiomer showed further enhanced activity compared to its enantiomer and the 17j racemic mixture. Our potent second-generation C10 analogues offer promise for therapeutic development against drug-resistant Mtb.

Profile and Frequency of Mutations Conferring Drug-Resistant Tuberculosis in the Central, Southeastern and Eastern Ethiopia.

Advances in molecular tools that assess genes harboring drug resistance mutations have greatly improved the detection and treatment of drug-resistant tuberculosis (DR-TB). This study was conducted to determine the frequency and type of mutations that are responsible for resistance to rifampicin (RIF), isoniazid (INH), fluoroquinolones (FLQs) and second-line injectable drugs (SLIDs) in Mycobacterium tuberculosis (MTB) isolates obtained from culture-positive pulmonary tuberculosis (TB) patients in the central, southeastern and eastern Ethiopia. In total, 224 stored culture-positive MTB isolates from pulmonary TB patients referred to Adama and Harar regional TB laboratories between August 2018 and January 2019 were assessed for mutations conferring RIF, INH, FLQs and SLIDs resistance using GenoType®MTBDRplus (MTBDRplus) and GenoType®MTBDRsl (MTBDRsl). RIF, INH, FLQs and SLIDs resistance-conferring mutations were identified in 88/224 (39.3%), 85/224 (38.0%), 7/77 (9.1%), and 3/77% (3.9%) of MTB isolates, respectively. Mutation codons rpoB S531L (59.1%) for RIF, katG S315T (96.5%) for INH, gyrA A90V (42.1%) for FLQs and WT1 rrs (100%) for SLIDs were observed in the majority of the isolates tested. Over a 10th of rpoB mutations detected in the current study were unknown. In this study, the most common mutations conferring drug resistance to RIF, INH, FLQs were identified. However, a significant proportion of RIF-resistant isolates manifested unknown rpoB mutations. Similarly, although few in number, all SLID-resistant isolates had unknown rrs mutations. To further elucidate the entire spectrum of mutations, tool such as whole-genome sequencing is imperative. Furthermore, the expansion of molecular drug susceptibility testing services is critical for tailoring patient treatment and preventing disease transmission.

Afro-TB dataset as a large scale genomic data of Mycobacterium tuberuclosis in Africa

Mycobacterium tuberculosis (MTB) is a pathogenic bacterium accountable for 10.6 million new infections with tuberculosis (TB) in 2021. The fact that the genetic sequences of M. tuberculosis vary widely provides a basis for understanding how this bacterium causes disease, how the immune system responds to it, how it has evolved over time, and how it is distributed geographically. However, despite extensive research efforts, the evolution and transmission of MTB in Africa remain poorly understood. In this study, we used 17,641 strains from 26 countries to create the first curated African Mycobacterium tuberculosis (MTB) classification and resistance dataset, containing 13,753 strains. We identified 157 mutations in 12 genes associated with resistance and additional new mutations potentially associated with resistance. The resistance profile was used to classify strains. We also performed a phylogenetic classification of each isolate and prepared the data in a format that can be used for phylogenetic and comparative analysis of tuberculosis worldwide. These genomic data will extend current information for comparative genomic studies to understand the mechanisms and evolution of MTB drug resistance.