Ontology highlight
ABSTRACT:
PROVIDER: PRJNA938288 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Comparative Genomic and Transcriptomic Characterization of Colistin-Resistant Acinetobacter baumannii
2019-01-23 | GSE109951 | GEO
Project description:Acinetobacter baumannii causes high mortality in ventilator-associated pneumonia patients and antibiotic treatment is compromised in multi-drug resistant strains resistant to beta-lactams, carbapenems, cephalosporins, polymyxins and tetracyclines. Among COVID-19 patients receiving ventilator support, multi-drug resistant A. baumannii secondary infection is associated with a two-fold increase in mortality. Here we investigated the use of the 8-hydroxyquinoline ionophore PBT2 to break resistance of A. baumannii to tetracycline class antibiotics.
2021-12-17 | GSE175535 | GEO
Project description:Using Nanopore sequencing, our study has revealed a close correlation between genomic methylation levels and antibiotic resistance rates in Acinetobacter Baumannii. Specifically, the combined genome-wide DNA methylome and transcriptome analysis revealed the first epigenetic-based antibiotic-resistance mechanism in A. baumannii. Our findings suggest that the precise location of methylation sites along the chromosome could provide new diagnostic markers and drug targets to improve the management of multidrug-resistant A. baumannii infections.
2023-09-01 | E-MTAB-13272 | biostudies-arrayexpress
Project description:Kim2009 - Genome-scale metabolic network of
Acinetobacter baumannii (AbyMBEL891)
This model is described in the article:
Genome-scale metabolic
network analysis and drug targeting of multi-drug resistant
pathogen Acinetobacter baumannii AYE.
Kim HU, Kim TY, Lee SY.
Mol Biosyst 2010 Feb; 6(2):
339-348
Abstract:
Acinetobacter baumannii has emerged as a new clinical threat
to human health, particularly to ill patients in the hospital
environment. Current lack of effective clinical solutions to
treat this pathogen urges us to carry out systems-level studies
that could contribute to the development of an effective
therapy. Here we report the development of a strategy for
identifying drug targets by combined genome-scale metabolic
network and essentiality analyses. First, a genome-scale
metabolic network of A. baumannii AYE, a drug-resistant strain,
was reconstructed based on its genome annotation data, and
biochemical knowledge from literatures and databases. In order
to evaluate the performance of the in silico model,
constraints-based flux analysis was carried out with
appropriate constraints. Simulations were performed from both
reaction (gene)- and metabolite-centric perspectives, each of
which identifies essential genes/reactions and metabolites
critical to the cell growth. The gene/reaction essentiality
enables validation of the model and its comparative study with
other known organisms' models. The metabolite essentiality
approach was undertaken to predict essential metabolites that
are critical to the cell growth. The EMFilter, a framework that
filters initially predicted essential metabolites to find the
most effective ones as drug targets, was also developed.
EMFilter considers metabolite types, number of total and
consuming reaction linkage with essential metabolites, and
presence of essential metabolites and their relevant enzymes in
human metabolism. Final drug target candidates obtained by this
system framework are presented along with implications of this
approach.
This model is hosted on
BioModels Database
and identified by:
MODEL1507180029.
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2015-07-30 | MODEL1507180029 | BioModels
Project description:Purpose: The goal of this study was to elucidate the collateral effects associated with OXA-23 overexpression on the Acinetobacter baumannii global transcriptome. Results: Besides the 99.73-fold increase in blaOXA-23 transcript upon IPTG induction, no other transcripts showed more than a 2-fold change compared to the wildtype control. This suggests that OXA-23 over expression to levels similarly observed in multi drug resistant A. baumannii clinical isolates does not effect the transcriptome.
2021-11-15 | GSE185203 | GEO
Project description:Acinetobacter baumannii is a Gram-negative opportunistic pathogen that causes multiple infections, including pneumonia, bacteremia, and wound infections. Due to multiple intrinsic and acquired drug-resistance mechanisms, A. baumannii isolates are commonly multi-drug resistant and infections are notoriously difficult to treat. Therefore, it is important to identify mechanisms used by A. baumannii to survive stresses encountered during infection as a means of identifying new drug targets. In this study, we determined the transcriptional response of A. baumannii to hydrogen peroxide stress using RNASequencing. Upon exposure to hydrogen peroxide, A. baumannii differentially transcribes several hundred genes. In this study, we also determined the transcriptional profile of A. baumannii strains with the transcriptional regulators mumR or oxyR genetically inactivated and identified transcriptional differences between these strains and wild-type A. baumannii in response to hydrogen peroxide stress. In doing this, the function of A. baumannii OxyR in hydrogen peroxide stress resistance and regulation of genes required for hydrogen peroxide detoxification was defined. Moreover, the contribution of the uncharacterized regulator MumR to hydrogen peroxide stress resistance was also explored. This work reveals the transcriptome of an important human pathogen in the presence of hydrogen peroxide stress.
2018-11-13 | GSE114130 | GEO
Project description:Transcriptomic comparison of a multidrug resistant Acinetobacter baumannii strain and a susceptible reference strain.
2009-11-20 | E-MEXP-2254 | biostudies-arrayexpress
Project description:The bacterial pathogen, Acinetobacter baumannii, is a leading cause of drug-resistant infections. Here, we investigated the potential of developing nanobodies that specifically recognize A. baumannii over other Gram-negative bacteria. Through generation and panning of a synthetic nanobody library, we identified several potential lead candidates. We demonstrate how incorporation of next generation sequencing analysis can aid in selection of lead candidates for further characterization. Using monoclonal phage display, we validated the binding of several lead nanobodies to A. baumannii. Subsequent purification and biochemical characterization revealed one particularly robust nanobody that broadly and specifically bound A. baumannii compared to other common drug resistant pathogens. These findings support the potentially for nanobodies to selectively target A. baumannii and the identification of lead candidates for possible future diagnostic and therapeutic development.
2023-06-21 | GSE202972 | GEO
Project description:We analyzed the extracellular proteome of colistin-resistant Korean Acinetobacter baumannii (KAB) strains to identify proteome profiles that can be used to characterize extensively drug-resistant KAB strains.
2020-05-27 | PXD015959 | Pride
Project description:Two Acinetobacter baumannii strains with low susceptibility to fosmidomycin and two reference with high susceptibility to fosmidomycin were DNA-sequenced to investigate the genomic determinants of fosmidomycin resistance.
2022-12-21 | E-MTAB-12357 | biostudies-arrayexpress