Mycobacterium tuberculosis H37Rv
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA182521 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR638895_1.fastq.gz | Fastqsanger.gz | |||
| SRR638895_2.fastq.gz | Fastqsanger.gz | |||
| SRR799107_1.fastq.gz | Fastqsanger.gz | |||
| SRR799107_2.fastq.gz | Fastqsanger.gz | |||
| SRR799108_1.fastq.gz | Fastqsanger.gz |
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Project description:BACKGROUND: Mycobacterium tuberculosis (M.tb) is the causative agent of tuberculosis, killing ~1.7 million people annually. The remarkable capacity of this pathogen to escape the host immune system for decades and then to cause active tuberculosis disease, makes M.tb a successful pathogen. Currently available anti-mycobacterial therapy has poor compliance due to requirement of prolonged treatment resulting in accelerated emergence of drug resistant strains. Hence, there is an urgent need to identify new chemical entities with novel mechanism of action and potent activity against the drug resistant strains. RESULTS: This study describes novel computational models developed for predicting inhibitors against both replicative and non-replicative phase of drug-tolerant M.tb under carbon starvation stage. These models were trained on highly diverse dataset of 2135 compounds using four classes of binary fingerprint namely PubChem, MACCS, EState, SubStructure. We achieved the best performance Matthews correlation coefficient (MCC) of 0.45 using the model based on MACCS fingerprints for replicative phase inhibitor dataset. In case of non-replicative phase, Hybrid model based on PubChem, MACCS, EState, SubStructure fingerprints performed better with maximum MCC value of 0.28. In this study, we have shown that molecular weight, polar surface area and rotatable bond count of inhibitors (replicating and non-replicating phase) are significantly different from non-inhibitors. The fragment analysis suggests that substructures like hetero_N_nonbasic, heterocyclic, carboxylic_ester, and hetero_N_basic_no_H are predominant in replicating phase inhibitors while hetero_O, ketone, secondary_mixed_amine are preferred in the non-replicative phase inhibitors. It was observed that nitro, alkyne, and enamine are important for the molecules inhibiting bacilli residing in both the phases. In this study, we introduced a new algorithm based on Matthews correlation coefficient called MCCA for feature selection and found that this algorithm is better or comparable to frequency based approach. CONCLUSION: In this study, we have developed computational models to predict phase specific inhibitors against drug resistant strains of M.tb grown under carbon starvation. Based on simple molecular properties, we have derived some rules, which would be useful in robust identification of tuberculosis inhibitors. Based on these observations, we have developed a webserver for predicting inhibitors against drug tolerant M.tb H37Rv available at http://crdd.osdd.net/oscadd/mdri/.
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Project description:1. The biosynthesis of nucleic acid purine in Mycobacterium tuberculosis H(37)R(v) has been studied by using (14)C-labelled precursors. 2. The results indicate that C-2 and C-8 of the purine ring are derived most efficiently from serine and glycine and not from formate. 3. [(14)C]Methionine is not incorporated into the ureide carbon atoms of the purine ring.
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Project description:Haloalkane dehalogenases convert haloalkanes to their corresponding alcohols by a hydrolytic mechanism. To date, various haloalkane dehalogenases have been isolated from bacteria colonizing environments that are contaminated with halogenated compounds. A search of current databases with the sequences of these known haloalkane dehalogenases revealed the presence of three different genes encoding putative haloalkane dehalogenases in the genome of the human parasite Mycobacterium tuberculosis H37Rv. The ability of M. tuberculosis and several other mycobacterial strains to dehalogenate haloaliphatic compounds was therefore studied. Intact cells of M. tuberculosis H37Rv were found to dehalogenate 1-chlorobutane, 1-chlorodecane, 1-bromobutane, and 1,2-dibromoethane. Nine isolates of mycobacteria from clinical material and four strains from a collection of microorganisms were found to be capable of dehalogenating 1,2-dibromoethane. Crude extracts prepared from two of these strains, Mycobacterium avium MU1 and Mycobacterium smegmatis CCM 4622, showed broad substrate specificity toward a number of halogenated substrates. Dehalogenase activity in the absence of oxygen and the identification of primary alcohols as the products of the reaction suggest a hydrolytic dehalogenation mechanism. The presence of dehalogenases in bacterial isolates from clinical material, including the species colonizing both animal tissues and free environment, indicates a possible role of parasitic microorganisms in the distribution of degradation genes in the environment.
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Project description:The ability to adapt to different conditions is key for Mycobacterium tuberculosis, the causative agent of tuberculosis (TB), to successfully infect human hosts. Adaptations allow the organism to evade the host immune responses during acute infections and persist for an extended period of time during the latent infectious stage. In latently infected individuals, estimated to include one-third of the human population, the organism exists in a variety of metabolic states, which impedes the development of a simple strategy for controlling or eradicating this disease. Direct knowledge of the metabolic states of M. tuberculosis in patients would aid in the management of the disease as well as in forming the basis for developing new drugs and designing more efficacious drug cocktails. Here, we propose an in silico approach to create state-specific models based on readily available gene expression data. The coupling of differential gene expression data with a metabolic network model allowed us to characterize the metabolic adaptations of M. tuberculosis H37Rv to hypoxia. Given the microarray data for the alterations in gene expression, our model predicted reduced oxygen uptake, ATP production changes, and a global change from an oxidative to a reductive tricarboxylic acid (TCA) program. Alterations in the biomass composition indicated an increase in the cell wall metabolites required for cell-wall growth, as well as heightened accumulation of triacylglycerol in preparation for a low-nutrient, low metabolic activity life style. In contrast, the gene expression program in the deletion mutant of dosR, which encodes the immediate hypoxic response regulator, failed to adapt to low-oxygen stress. Our predictions were compatible with recent experimental observations of M. tuberculosis activity under hypoxic and anaerobic conditions. Importantly, alterations in the flow and accumulation of a particular metabolite were not necessarily directly linked to differential gene expression of the enzymes catalyzing the related metabolic reactions.
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Project description:H37Rv is the most widely used Mycobacterium tuberculosis strain, and its genome is globally used as the M. tuberculosis reference sequence. Here, we present Bact-Builder, a pipeline that uses consensus building to generate complete and accurate bacterial genome sequences and apply it to three independently cultured and sequenced H37Rv aliquots of a single laboratory stock. Two of the 4,417,942 base-pair long H37Rv assemblies are 100% identical, with the third differing by a single nucleotide. Compared to the existing H37Rv reference, the new sequence contains ~6.4 kb additional base pairs, encoding ten new regions that include insertions in PE/PPE genes and new paralogs of esxN and esxJ, which are differentially expressed compared to the reference genes. New sequencing and de novo assemblies with Bact-Builder confirm that all 10 regions, plus small additional polymorphisms, are also present in the commonly used H37Rv strains NR123, TMC102, and H37Rv1998. Thus, Bact-Builder shows promise as an improved method to perform accurate and reproducible de novo assemblies of bacterial genomes, and our work provides important updates to the primary M. tuberculosis reference genome.
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Project description:Toxin-antitoxin (TA) systems, which consist of an intracellular toxin and its antidote (antitoxin), are encoded by ubiquitous genetic modules in prokaryotes. Commonly, the activity of a toxin is inhibited by its antitoxin under normal growth conditions. However, antitoxins are degraded in response to environmental stress, and toxins liberated from antitoxins consequently induce cell death or growth arrest. In free-living prokaryotes, TA systems are often present in large numbers and are considered to be associated with the adaptation of pathogenic bacteria or extremophiles to various unfavorable environments by shifting cells to a slow growth rate. Genomic analysis of the human pathogen Mycobacterium tuberculosis H37Rv (Mtb) revealed the presence of a large number of TA systems. Accordingly, we investigated five uncharacterized TA systems (Rv2019-Rv2018, Rv3697c-Rv3697A, Rv3180c-Rv3181c, Rv0299-Rv0298, and Rv3749c-Rv3750c) of Mtb. Among these, the expression of the Rv2019 toxin inhibited the growth of Escherichia coli, and M. smegmatis and this growth defect was recovered by the expression of the Rv2018 antitoxin. Interestingly, Rv3180c was toxic only in M. smegmatis, whose toxicity was neutralized by Rv3181c antitoxin. In vivo and in vitro assays revealed the ribosomal RNA (rRNA) cleavage activity of the Rv2019 toxin. Moreover, mRNAs appeared to be substrates of Rv2019. Therefore, we concluded that the ribonuclease activity of the Rv2019 toxin triggers the growth defect in E. coli and that the Rv2018 antitoxin inhibits the ribonuclease activity of the Rv2019 toxin.
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