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Protein-protein interaction of Rv0148 with Htdy and its predicted role towards drug resistance in Mycobacterium tuberculosis.

ABSTRACT: BACKGROUND:Mycobacterium tuberculosis resides inside host macrophages during infection and adapts to resilient stresses generated by the host immune system. As a response, M. tuberculosis codes for short-chain dehydrogenases/reductases (SDRs). These SDRs are nicotinamide adenine dinucleotide-reliant oxidoreductases involved in cell homeostasis. The precise function of oxidoreductases in bacteria especially M. tuberculosis were not fully explored. This study aimed to know the detail functional role of one of the oxidoreductase Rv0148 in M. tuberculosis. RESULTS:In silico analysis revealed that Rv0148 interacts with Htdy (Rv3389) and the protein interactions were confirmed using far western blot. Gene knockout mutant of Rv0148 in M. tuberculosis was constructed by specialized transduction. Macrophage cell line infection with this knockout mutant showed increased expression of pro-inflammatory cytokines. This knockout mutant is sensitive to oxidative, nitrogen, redox and electron transport inhibitor stress agents. Drug susceptibility testing of the deletion mutant showed resistance to first-line drugs such as streptomycin and ethambutol and second-line aminoglycosides such as amikacin and kanamycin. Based on interactorme analysis for Rv0148 using STRING database, we identified 220 most probable interacting partners for Htdy protein. In the Rv0148 knockout mutants, high expression of htdy was observed and we hypothesize that this would have perturbed the interactome thus resulting in drug resistance. Finally, we propose that Rv0148 and Htdy are functionally interconnected and involved in drug resistance and cell homeostasis of M. tuberculosis. CONCLUSIONS:Our study suggests that Rv0148 plays a significant role in various functional aspects such as intermediatory metabolism, stress, homeostasis and also in drug resistance.

SUBMITTER: Bhargavi G

PROVIDER: S-EPMC7161113 | biostudies-literature | 2020 Apr

REPOSITORIES: biostudies-literature

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Protein-protein interaction of Rv0148 with Htdy and its predicted role towards drug resistance in Mycobacterium tuberculosis.

Bhargavi Gunapati G Hassan Sameer S Balaji Subramanyam S Tripathy Srikanth Prasad SP Palaniyandi Kannan K

BMC microbiology 20200415 1

<h4>Background</h4>Mycobacterium tuberculosis resides inside host macrophages during infection and adapts to resilient stresses generated by the host immune system. As a response, M. tuberculosis codes for short-chain dehydrogenases/reductases (SDRs). These SDRs are nicotinamide adenine dinucleotide-reliant oxidoreductases involved in cell homeostasis. The precise function of oxidoreductases in bacteria especially M. tuberculosis were not fully explored. This study aimed to know the detail funct ...[more]

PMID: 32295519

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Project description:Combating the spread of drug resistant tuberculosis is a global health priority. Whole genome association studies are being applied to identify genetic determinants of resistance to anti-tuberculosis drugs. Protein structure and interaction modelling are used to understand the functional effects of putative mutations and provide insight into the molecular mechanisms leading to resistance.To investigate the potential utility of these approaches, we analysed the genomes of 144 Mycobacterium tuberculosis clinical isolates from The Special Programme for Research and Training in Tropical Diseases (TDR) collection sourced from 20 countries in four continents. A genome-wide approach was applied to 127 isolates to identify polymorphisms associated with minimum inhibitory concentrations for first-line anti-tuberculosis drugs. In addition, the effect of identified candidate mutations on protein stability and interactions was assessed quantitatively with well-established computational methods.The analysis revealed that mutations in the genes rpoB (rifampicin), katG (isoniazid), inhA-promoter (isoniazid), rpsL (streptomycin) and embB (ethambutol) were responsible for the majority of resistance observed. A subset of the mutations identified in rpoB and katG were predicted to affect protein stability. Further, a strong direct correlation was observed between the minimum inhibitory concentration values and the distance of the mutated residues in the three-dimensional structures of rpoB and katG to their respective drugs binding sites.Using the TDR resource, we demonstrate the usefulness of whole genome association and convergent evolution approaches to detect known and potentially novel mutations associated with drug resistance. Further, protein structural modelling could provide a means of predicting the impact of polymorphisms on drug efficacy in the absence of phenotypic data. These approaches could ultimately lead to novel resistance mutations to improve the design of tuberculosis control measures, such as diagnostics, and inform patient management.

Project description:BackgroundIn spite of the implementations of several strategies, tuberculosis (TB) is overwhelmingly a serious global public health problem causing millions of infections and deaths every year. This is mainly due to the emergence of drug-resistance varieties of TB. The current treatment strategies for the drug-resistance TB are of longer duration, more expensive and have side effects. This highlights the importance of identification and prioritization of targets for new drugs. This study has been carried out to prioritize potential drug targets of Mycobacterium tuberculosis H37Rv based on their flow to resistance genes.MethodsThe weighted proteome interaction network of the pathogen was constructed using a dataset from STRING database. Only a subset of the dataset with interactions that have a combined score value ≥770 was considered. Maximum flow approach has been used to prioritize potential drug targets. The potential drug targets were obtained through comparative genome and network centrality analysis. The curated set of resistance genes was retrieved from literatures. Detail literature review and additional assessment of the method were also carried out for validation.ResultsA list of 537 proteins which are essential to the pathogen and non-homologous with human was obtained from the comparative genome analysis. Through network centrality measures, 131 of them were found within the close neighborhood of the centre of gravity of the proteome network. These proteins were further prioritized based on their maximum flow value to resistance genes and they are proposed as reliable drug targets of the pathogen. Proteins which interact with the host were also identified in order to understand the infection mechanism.ConclusionPotential drug targets of Mycobacterium tuberculosis H37Rv were successfully prioritized based on their flow to resistance genes of existing drugs which is believed to increase the druggability of the targets since inhibition of a protein that has a maximum flow to resistance genes is more likely to disrupt the communication to these genes. Purposely selected literature review of the top 14 proteins showed that many of them in this list were proposed as drug targets of the pathogen.

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.

Dataset Information

Protein-protein interaction of Rv0148 with Htdy and its predicted role towards drug resistance in Mycobacterium tuberculosis.

Publications

Protein-protein interaction of Rv0148 with Htdy and its predicted role towards drug resistance in Mycobacterium tuberculosis.

Similar Datasets

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