DNA Methyltransferase HsdM Induce Drug Resistance on Mycobacterium tuberculosis via Multiple Effects.
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ABSTRACT:
SUBMITTER: Chu H
PROVIDER: S-EPMC8698436 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:The Mycobacterium tuberculosis (Mtb) genome encodes 20 different cytochrome P450 enzymes (CYPs), many of which serve essential biosynthetic roles. CYP51B1, the Mtb version of eukaryotic sterol demethylase, remains a potential therapeutic target. The binding of three drug fragments containing nitrogen heterocycles to CYP51B1 is studied here by continuous wave (CW) and pulsed electron paramagnetic resonance (EPR) techniques to determine how each drug fragment binds to the heme active-site. All three drug fragments form a mixture of complexes, some of which retain the axial water ligand from the resting state. Hyperfine sublevel correlation spectroscopy (HYSCORE) and electron-nuclear double resonance spectroscopy (ENDOR) observe protons of the axial water and on the drug fragments that reveal drug binding modes. Binding in CYP51B1 is complicated by the presence of multiple binding modes that coexist in the same solution. These results aid our understanding of CYP-inhibitor interactions and will help guide future inhibitor design.
| S-EPMC7092363 | biostudies-literature
Project description:Tuberculosis (TB) is the leading cause of death by an infectious disease, and global TB control efforts are increasingly threatened by drug resistance in Mycobacterium tuberculosis. Unlike most bacteria, where lateral gene transfer is an important mechanism of resistance acquisition, resistant M. tuberculosis arises solely by de novo chromosomal mutation. Using whole-genome sequencing data from two natural populations of M. tuberculosis, we characterized the population genetics of known drug resistance loci using measures of diversity, population differentiation, and convergent evolution. We found resistant subpopulations to be less diverse than susceptible subpopulations, consistent with ongoing transmission of resistant M. tuberculosis. A subset of resistance genes ("sloppy targets") were characterized by high diversity and multiple rare variants; we posit that a large genetic target for resistance and relaxation of purifying selection contribute to high diversity at these loci. For "tight targets" of selection, the path to resistance appeared narrower, evidenced by single favored mutations that arose numerous times in the phylogeny and segregated at markedly different frequencies in resistant and susceptible subpopulations. These results suggest that diverse genetic architectures underlie drug resistance in M. tuberculosis and that combined approaches are needed to identify causal mutations. Extrapolating from patterns observed for well-characterized genes, we identified novel candidate variants involved in resistance. The approach outlined here can be extended to identify resistance variants for new drugs, to investigate the genetic architecture of resistance, and when phenotypic data are available, to find candidate genetic loci underlying other positively selected traits in clonal bacteria. IMPORTANCEMycobacterium tuberculosis, the causative agent of tuberculosis (TB), is a significant burden on global health. Antibiotic treatment imposes strong selective pressure on M. tuberculosis populations. Identifying the mutations that cause drug resistance in M. tuberculosis is important for guiding TB treatment and halting the spread of drug resistance. Whole-genome sequencing (WGS) of M. tuberculosis isolates can be used to identify novel mutations mediating drug resistance and to predict resistance patterns faster than traditional methods of drug susceptibility testing. We have used WGS from natural populations of drug-resistant M. tuberculosis to characterize effects of selection for advantageous mutations on patterns of diversity at genes involved in drug resistance. The methods developed here can be used to identify novel advantageous mutations, including new resistance loci, in M. tuberculosis and other clonal pathogens.
| S-EPMC5790871 | biostudies-literature
Project description:The emergence of antibiotic resistance in Mycobacterium tuberculosis has raised the concern that pathogen strains that are virtually untreatable may become widespread. The acquisition of resistance to antibiotics results in a longer duration of infection in a host, but this resistance may come at a cost through a decreased transmission rate. This raises the question of whether the overall fitness of drug-resistant strains is higher than that of sensitive strains--essential information for predicting the spread of the disease. Here, we directly estimate the transmission cost of drug resistance, the rate at which resistance evolves, and the relative fitness of resistant strains. These estimates are made by using explicit models of the transmission and evolution of sensitive and resistant strains of M. tuberculosis, using approximate Bayesian computation, and molecular epidemiology data from Cuba, Estonia, and Venezuela. We find that the transmission cost of drug resistance relative to sensitivity can be as low as 10%, that resistance evolves at rates of approximately 0.0025-0.02 per case per year, and that the overall fitness of resistant strains is comparable with that of sensitive strains. Furthermore, the contribution of transmission to the spread of drug resistance is very high compared with acquired resistance due to treatment failure (up to 99%). Estimating such parameters directly from in vivo data will be critical to understanding and responding to antibiotic resistance. For instance, projections using our estimates suggest that the prevalence of tuberculosis may decline with successful treatment, but the proportion of cases associated with resistance is likely to increase.
| S-EPMC2732896 | biostudies-literature
Project description:BackgroundEmergence of drug resistant varieties of tuberculosis is posing a major threat to global tuberculosis eradication programmes. Although several approaches have been explored to counter resistance, there has been limited success due to a lack of understanding of how resistance emerges in bacteria upon drug treatment. A systems level analysis of the proteins involved is essential to gain insights into the routes required for emergence of drug resistance.ResultsWe derive a genome-scale protein-protein interaction network for Mycobacterium tuberculosis H37Rv from the STRING database, with proteins as nodes and interactions as edges. A set of proteins involved in both intrinsic and extrinsic drug resistance mechanisms are identified from literature. We then compute shortest paths from different drug targets to the set of resistance proteins in the protein-protein interactome, to derive a sub-network relevant to study emergence of drug resistance. The shortest paths are then scored and ranked based on a new scheme that considers (a) drug-induced gene upregulation data, from microarray experiments reported in literature, for the individual nodes and (b) edge-hubness, a network parameter which signifies centrality of a given edge in the network. High-scoring paths identified from this analysis indicate most plausible pathways for the emergence of drug resistance. Different targets appear to have different propensities for four drug resistance mechanisms. A new concept of 'co-targets' has been proposed to counter drug resistance, co-targets being defined as protein(s) that need to be simultaneously inhibited along with the intended target(s), to check emergence of resistance to a given drug.ConclusionThe study leads to the identification of possible pathways for drug resistance, providing novel insights into the problem of resistance. Knowledge of important proteins in such pathways enables identification of appropriate 'co-targets', best examples being RecA, Rv0823c, Rv0892 and DnaE1, for drugs targeting the mycolic acid pathway. Insights obtained about the propensity of a drug to trigger resistance will be useful both for more careful identification of drug targets as well as to identify target-co-target pairs, both implementable in early stages of drug discovery itself. This approach is also inherently generic, likely to significantly impact drug discovery.
| S-EPMC2649132 | biostudies-literature
Project description:Persistence, manifested as drug tolerance, represents a significant obstacle to global tuberculosis control. The bactericidal drugs isoniazid and rifampicin kill greater than 99% of exponentially growing Mycobacterium tuberculosis (Mtb) cells, but the remaining cells are persisters, cells with decreased metabolic rate, refractory to killing by these drugs, and able to generate drug-resistant mutants. We discovered that the combination of cysteine or other small thiols with either isoniazid or rifampicin prevents the formation of drug-tolerant and drug-resistant cells in Mtb cultures. This effect was concentration- and time-dependent, relying on increased oxygen consumption that triggered enhanced production of reactive oxygen species. In infected murine macrophages, the addition of N-acetylcysteine to isoniazid treatment potentiated the killing of Mtb Furthermore, we demonstrate that the addition of small thiols to Mtb drug treatment shifted the menaquinol/menaquinone balance toward a reduced state that stimulates Mtb respiration and converts persister cells to metabolically active cells. This prevention of both persister cell formation and drug resistance leads ultimately to mycobacterial cell death. Strategies to enhance respiration and initiate oxidative damage should improve tuberculosis chemotherapies.
| S-EPMC5410800 | biostudies-literature
Project description:Tuberculosis is a chronic infectious disease caused by Mycobacterium tuberculosis (Mtb). Due to the extensive use of anti-tuberculosis drugs and the development of mutations, the emergence and spread of multidrug-resistant tuberculosis is recognized as one of the most dangerous threats to global tuberculosis control. Some single mutations have been identified to be significantly linked with drug resistance. However, the prior research did not take gene-gene interactions into account, and the emergence of transmissible drug resistance is connected with multiple genetic mutations. In this study we use the bioinformatics software GBOOST (The Hong Kong University, Clear Water Bay, Kowloon, Hong Kong, China) to calculate the interactions of Single Nucleotide Polymorphism (SNP) pairs and identify gene pairs associated with drug resistance. A large part of the non-synonymous mutations in the drug target genes that were included in the screened gene pairs were confirmed by previous reports, which lent sound solid credits to the effectiveness of our method. Notably, most of the identified gene pairs containing drug targets also comprise Pro-Pro-Glu (PPE) family proteins, suggesting that PPE family proteins play important roles in the drug resistance of Mtb. Therefore, this study provides deeper insights into the mechanisms underlying anti-tuberculosis drug resistance, and the present method is useful for exploring the drug resistance mechanisms for other microorganisms.
| S-EPMC5037696 | biostudies-literature
Project description:Whole-genome sequencing allows rapid detection of drug-resistant Mycobacterium tuberculosis isolates. However, the availability of high-quality data linking quantitative phenotypic drug susceptibility testing (DST) and genomic data have thus far been limited. We determined drug resistance profiles of 176 genetically diverse clinical M. tuberculosis isolates from the Democratic Republic of the Congo, Ivory Coast, Peru, Thailand, and Switzerland by quantitative phenotypic DST for 11 antituberculous drugs using the BD Bactec MGIT 960 system and 7H10 agar dilution to generate a cross-validated phenotypic DST readout. We compared DST results with predicted drug resistance profiles inferred by whole-genome sequencing. Classification of strains by the two phenotypic DST methods into resistotype/wild-type populations was concordant in 73 to 99% of cases, depending on the drug. Our data suggest that the established critical concentration (5?mg/liter) for ethambutol resistance (MGIT 960 system) is too high and misclassifies strains as susceptible, unlike 7H10 agar dilution. Increased minimal inhibitory concentrations were explained by mutations identified by whole-genome sequencing. Using whole-genome sequences, we were able to predict quantitative drug resistance levels for the majority of drug resistance mutations. Predicting quantitative levels of drug resistance by whole-genome sequencing was partially limited due to incompletely understood drug resistance mechanisms. The overall sensitivity and specificity of whole-genome-based DST were 86.8% and 94.5%, respectively. Despite some limitations, whole-genome sequencing has the potential to infer resistance profiles without the need for time-consuming phenotypic methods.
| S-EPMC6496161 | biostudies-literature
Project description:Identification of new drug targets is vital for the advancement of drug discovery against Mycobacterium tuberculosis, especially given the increase of resistance worldwide to first- and second-line drugs. Because traditional target-based screening has largely proven unsuccessful for antibiotic discovery, we have developed a scalable platform for target identification in M. tuberculosis that is based on whole-cell screening, coupled with whole-genome sequencing of resistant mutants and recombineering to confirm. The method yields targets paired with whole-cell active compounds, which can serve as novel scaffolds for drug development, molecular tools for validation, and/or as ligands for co-crystallization. It may also reveal other information about mechanisms of action, such as activation or efflux. Using this method, we identified resistance-linked genes for eight compounds with anti-tubercular activity. Four of the genes have previously been shown to be essential: AspS, aspartyl-tRNA synthetase, Pks13, a polyketide synthase involved in mycolic acid biosynthesis, MmpL3, a membrane transporter, and EccB3, a component of the ESX-3 type VII secretion system. AspS and Pks13 represent novel targets in protein translation and cell-wall biosynthesis. Both MmpL3 and EccB3 are involved in membrane transport. Pks13, AspS, and EccB3 represent novel candidates not targeted by existing TB drugs, and the availability of whole-cell active inhibitors greatly increases their potential for drug discovery.
| S-EPMC3781026 | biostudies-literature
Project description:BackgroundChina is a country with high burden of tuberculosis (TB), especially drug-resistant TB (DR-TB), which is still a serious health problem in Yunnan Province. Mycobacterium tuberculosis (MTB) is the pathogenic microorganism of TB. The epidemiological characteristics of MTB strains in local areas need to be described.MethodsA total of 430 clinical MTB isolates were collected from Yunnan Province and genotyped through the method of 24-locus mycobacterial interspersed repetitive unit-variable number tandem DNA repeats (MIRU-VNTR).ResultsThe genotypes of the 24 loci showed abundantly genetic diversity, and allelic diversity index (h) of these loci varied from 0.012 to 0.817. Among the 430 strains, 30 clusters and 370 unique genotypes were identified. Beijing family was the predominant lineage (70.47%) in Yunnan MTB strains, and the other lineages contained T family (5.81%), MANU2 (0.70%), LAM (3.26%), CAS (0.23%), New-1 (8.37%), and some unknown clades (11.16%). A total of 74 TB strains were identified as drug resistance through drug susceptibility testing (DST), including 38 multidrug-resistant TB (MDR-TB) and 36 single-drug-resistant TB (SDR-TB). The frequency of MDR-TB strains was significantly higher in Beijing family (10.89%) than that in non-Beijing family (3.94%, P = 0.032).ConclusionsAlthough MTB strains showed high genetic diversity in Yunnan, China, the Beijing family was still the dominant strain. A high frequency of MDR-TB strains was recorded in the Beijing family.
| S-EPMC6595362 | biostudies-literature
Project description:RationaleMultiple infections with different strains of Mycobacterium tuberculosis may occur in settings where the infection pressure is high. The relevance of mixed infections for the patient, clinician, and control program remains unclear.ObjectivesThis study aimed to describe reinfection and mixed infection as underlying mechanisms of changing drug-susceptibility patterns in serial sputum cultures.MethodsSerial M. tuberculosis sputum cultures from patients diagnosed with multi-drug-resistant (MDR) tuberculosis were evaluated by phenotypic drug-susceptibility testing and mutation detection methods. Genotypic analysis was done by IS6110 DNA fingerprinting and a novel strain-specific polymerase chain reaction amplification method.Measurements and main resultsDNA fingerprinting analysis of serial sputum cultures from 48 patients with MDR tuberculosis attributed 10 cases to reinfection and 1 case to mixed infection. In contrast, strain-specific polymerase chain reaction amplification analysis in 9 of the 11 cases demonstrated mixed infection in 5 cases, reinfection in 3 cases, and laboratory contamination in 1 case. Analysis of clinical data suggests that first-line therapy can select for a resistant subpopulation, whereas poor adherence or second-line therapy resulted in the reemergence of the drug-susceptible subpopulations.ConclusionsWe have shown that, in some patients with MDR tuberculosis, mixed infection may be responsible for observations attributed to reinfection by DNA fingerprinting. We conclude that treatment and adherence determines which strain is dominant. We hypothesize that treatment with second-line drugs may lead to reemergence of the drug-susceptible strain in patients with mixed infection.
| S-EPMC2718533 | biostudies-literature