Mycobacterium tuberculosis
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA290456 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR2120751_1.fastq.gz | Fastqsanger.gz | |||
| SRR2120751_2.fastq.gz | Fastqsanger.gz | |||
| SRR2120772_1.fastq.gz | Fastqsanger.gz | |||
| SRR2120772_2.fastq.gz | Fastqsanger.gz |
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Project description:Tuberculosis (TB) remains a deadly disease. The genetic diversity of Mycobacterium tuberculosis was neglected in the past, but is increasingly recognized as a determinant of immune responses and clinical outcomes of TB. However, how this bacterial diversity orchestrates immune responses to direct differences in TB severity remains unknown. We studied 681 patients with pulmonary TB and found that phylogenetically related M. tuberculosis isolates from cases with mild disease induced robust cytokine responses in macrophages. In contrast, isolates associated with severe TB cases failed to do so. Using representative isolates, we show that M. tuberculosis inducing a low cytokine response in macrophages also diminished activation of cytosolic surveillance systems, including cGAS and the inflammasome, suggesting a novel mechanism of immune escape. Isolates exhibiting this evasion strategy carried mutations in various components of the ESX-I secretion system. We conclude that host interactions with different M. tuberculosis strains results in variable TB severity.
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Project description:Currently available model organisms such as Mycobacterium smegmatis and Mycobacterium bovis Bacillus Calmette-Guérin (BCG) have significantly contributed to our understanding of tuberculosis (TB) biology, these models have limitations such as differences in genome size, growth rates and virulence. Attenuated Mycobacterium tuberculosis strains may provide more representative, safer models to study M. tuberculosis biology. For example, the M. tuberculosis ΔleuDΔpanCD double auxotroph, has undergone rigorous in vitro and in vivo safety testing. Like other auxotrophic strains, this has subsequently been approved for use in biosafety level (BSL) 2 facilities. Auxotrophic strains have been assessed as models for drug-resistant M. tuberculosis and for studying latent TB. These offer the potential as safe and useful models, but it is important to understand how well these recapitulate salient features of non-attenuated M. tuberculosis. We therefore performed a comprehensive comparison of M. tuberculosis H37Rv and M. tuberculosis ΔleuDΔpanCD. These strains demonstrated similar in vitro and intra-macrophage replication rates, similar responses to anti-TB agents and whole genome sequence conservation. Shotgun proteomics analysis suggested that M. tuberculosis ΔleuDΔpanCD has an increased propensity to enter a dormant state during acid stress, which has been verified using a dual-fluorescent replication reporter assay. Importantly, infection of human peripheral blood mononuclear cells with the 2 strains elicited comparable cytokine production, demonstrating the suitability of M. tuberculosis ΔleuDΔpanCD for immunological assays. We provide comprehensive evidence to support the judicious use of M. tuberculosis ΔleuDΔpanCD as a safe and suitable model organism for M. tuberculosis research, without the need for a BSL3 facility.
2019-07-30 | PXD013677 | Pride
Project description:Mycobacterium tuberculosis infection of mice elicits a robust neutrophil influx that associates with poor outcome from tuberculosis (TB). However, the mechanism by which neutrophils contribute to TB disease pathogenesis is not understood. To gain insights into the pathological functions of neutrophils, the current study performs bulk mRNA sequencing from the neutrophils isolated from lung, spleen and bone marrow of resistant (C57BL/6) and susceptible (IL-1R1 KO) mice at 28 days post M.tuberculosis HN878 infection.
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Project description:Transcriptional profiling of mycobacterium tuberculosis clinical isolates in China comparing extensively drug-resistant tuberculosis with drug sensitive one.
2009-04-04 | GSE15540 | GEO
Project description:Tuberculosis (TB) is still a major global health challenge, killing over 1.5 million people each year, and hence, there is a need to identify and develop novel treatments for Mycobacterium tuberculosis (M. tuberculosis). The prevalence of infections caused by nontuberculous mycobacteria (NTM) is also increasing and has overtaken TB cases in the United States and much of the developed world. Mycobacterium abscessus (M. abscessus) is one of the most frequently encountered NTM and is difficult to treat. We describe the use of drug-disease association using a semantic knowledge graph approach combined with machine learning models that has enabled the identification of several molecules for testing anti-mycobacterial activity. We established that niclosamide (M. tuberculosis IC90 2.95 μM; M. abscessus IC90 59.1 μM) and tribromsalan (M. tuberculosis IC90 76.92 μM; M. abscessus IC90 147.4 μM) inhibit M. tuberculosis and M. abscessus in vitro. To investigate the mode of action, we determined the transcriptional response of M. tuberculosis and M. abscessus to both compounds in axenic log phase, demonstrating a broad effect on gene expression that differed from known M. tuberculosis inhibitors. Both compounds elicited transcriptional responses indicative of respiratory pathway stress and the dysregulation of fatty acid metabolism. Further testing against drug-resistant isolates and other NTM is warranted to clarify the usefulness of these repurposed drugs for mycobacteria.
2024-03-01 | E-MTAB-13761 | biostudies-arrayexpress
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Project description:Rifampicin plays an important role during tuberculosis treatment, which historically contributed for shortening therapy; however, rifampicin resistance has been the intersection for the definition of multi (MDR-TB) and extensively (XDR-TB) resistant outcomes. A key aspect which has contributed for investigations of drug action/resistance is the understanding of the dynamic genome expression, as that analyzed by Proteomics. Proteins from the reference strain, Mycobacterium tuberculosis H37Rv were extracted after 12, 24 and 48 hours over rifampicin challenge at the minimal inhibitory concentration (0.03 μg•mL-1) and identified by LC-MS.
2021-05-04 | PXD014177 | Pride
Project description:Beste2007 - Genome-scale metabolic network of
Mycobacterium tuberculosis (GSMN_TB)
This model is described in the article:
GSMN-TB: a web-based
genome-scale network model of Mycobacterium tuberculosis
metabolism.
Beste DJ, Hooper T, Stewart G, Bonde
B, Avignone-Rossa C, Bushell ME, Wheeler P, Klamt S, Kierzek AM,
McFadden J.
Genome Biol. 2007; 8(5): R89
Abstract:
BACKGROUND: An impediment to the rational development of
novel drugs against tuberculosis (TB) is a general paucity of
knowledge concerning the metabolism of Mycobacterium
tuberculosis, particularly during infection. Constraint-based
modeling provides a novel approach to investigating microbial
metabolism but has not yet been applied to genome-scale
modeling of M. tuberculosis. RESULTS: GSMN-TB, a genome-scale
metabolic model of M. tuberculosis, was constructed, consisting
of 849 unique reactions and 739 metabolites, and involving 726
genes. The model was calibrated by growing Mycobacterium bovis
bacille Calmette Guérin in continuous culture and
steady-state growth parameters were measured. Flux balance
analysis was used to calculate substrate consumption rates,
which were shown to correspond closely to experimentally
determined values. Predictions of gene essentiality were also
made by flux balance analysis simulation and were compared with
global mutagenesis data for M. tuberculosis grown in vitro. A
prediction accuracy of 78% was achieved. Known drug targets
were predicted to be essential by the model. The model
demonstrated a potential role for the enzyme isocitrate lyase
during the slow growth of mycobacteria, and this hypothesis was
experimentally verified. An interactive web-based version of
the model is available. CONCLUSION: The GSMN-TB model
successfully simulated many of the growth properties of M.
tuberculosis. The model provides a means to examine the
metabolic flexibility of bacteria and predict the phenotype of
mutants, and it highlights previously unexplored features of M.
tuberculosis metabolism.
This model is hosted on
BioModels Database
and identified by:
MODEL1507180021.
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2015-07-30 | MODEL1507180021 | BioModels
Project description:Synchronised cultures of Mycobacterium tuberculosis (M. tb H37Ra DnaAcos115) were used to determine the cell cycle dependent gene expression.
2015-12-31 | GSE53640 | GEO