Ontology highlight
ABSTRACT:
PROVIDER: PRJNA797098 | ENA |
REPOSITORIES: ENA
Similar Datasets
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:Transcriptional profiling of mycobacterium tuberculosis clinical isolates in China comparing extensively drug-resistant tuberculosis with drug sensitive one. The same condition experiment. The samples were from the different drug-resistant strains. Only one replicate.
2009-04-04 | E-GEOD-15540 | biostudies-arrayexpress
Project description:①Background:Tuberculosis is mainly a respiratory tract infection caused by mycobacterium tuberculosis and one of the leading causes of death worldwide. According to the Global Tuberculosis Report in 2021, About a quarter of the world's population is infected with Mycobacterium tuberculosis and China is the second highest burden of TB. Although TB diagnosis and prevention techniques have become more mature, the number of TB cases is still increasing, mainly due to: the prevalence of drug-resistant tuberculosis bacteria, tuberculosis and HIV co-infection, long incubation time of mycobacterium tuberculosis difficult to early diagnosis and so on. Therefore, it is of great significance to study the pathogenesis of mycobacterium tuberculosis infection.②Method: THP-1 cells were treated with 50ng/ml PMA for 24 hours, so that THP-1 cell can be induced into macrophages. After that THP-1 macrophages were infected with mycobacterium tuberculosis H37Rv(MOI=1), which were collected and applied to RNA-sequencing. The constructed sequencing library was sequenced using an Illumina Novaseq 6000 system.
2022-08-31 | GSE203261 | GEO
Project description:Whole genome sequencing of Mycobacterium tuberculosis drug-resistant spontaneous mutants
| PRJNA400301 | ENA
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:Jamshidi2007 - Genome-scale metabolic network
of Mycobacterium tuberculosis (iNJ661)
This model is described in the article:
Investigating the metabolic
capabilities of Mycobacterium tuberculosis H37Rv using the in
silico strain iNJ661 and proposing alternative drug
targets.
Jamshidi N, Palsson BØ.
BMC Syst Biol 2007; 1: 26
Abstract:
BACKGROUND: Mycobacterium tuberculosis continues to be a
major pathogen in the third world, killing almost 2 million
people a year by the most recent estimates. Even in
industrialized countries, the emergence of multi-drug resistant
(MDR) strains of tuberculosis hails the need to develop
additional medications for treatment. Many of the drugs used
for treatment of tuberculosis target metabolic enzymes.
Genome-scale models can be used for analysis, discovery, and as
hypothesis generating tools, which will hopefully assist the
rational drug development process. These models need to be able
to assimilate data from large datasets and analyze them.
RESULTS: We completed a bottom up reconstruction of the
metabolic network of Mycobacterium tuberculosis H37Rv. This
functional in silico bacterium, iNJ661, contains 661 genes and
939 reactions and can produce many of the complex compounds
characteristic to tuberculosis, such as mycolic acids and
mycocerosates. We grew this bacterium in silico on various
media, analyzed the model in the context of multiple
high-throughput data sets, and finally we analyzed the network
in an 'unbiased' manner by calculating the Hard Coupled
Reaction (HCR) sets, groups of reactions that are forced to
operate in unison due to mass conservation and connectivity
constraints. CONCLUSION: Although we observed growth rates
comparable to experimental observations (doubling times ranging
from about 12 to 24 hours) in different media, comparisons of
gene essentiality with experimental data were less encouraging
(generally about 55%). The reasons for the often conflicting
results were multi-fold, including gene expression variability
under different conditions and lack of complete biological
knowledge. Some of the inconsistencies between in vitro and in
silico or in vivo and in silico results highlight specific loci
that are worth further experimental investigations. Finally, by
considering the HCR sets in the context of known drug targets
for tuberculosis treatment we proposed new alternative, but
equivalent drug targets.
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2024-10-15 | BIOMD0000001095 | BioModels