Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Acinetobacter baumannii

ABSTRACT: Multidrug-resistant Acinetobacter baumannii clinical isolates in Myanmar

PROVIDER: PRJDB8528 | ENA |

REPOSITORIES: ENA

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
	DRR188084_1.fastq.gz	Fastqsanger.gz
	DRR188084_2.fastq.gz	Fastqsanger.gz
	DRR188085_1.fastq.gz	Fastqsanger.gz
	DRR188085_2.fastq.gz	Fastqsanger.gz
	DRR188086_1.fastq.gz	Fastqsanger.gz

Items per page:

1 - 5 of 76

Similar Datasets

Transcription profiling of Acinetobacter baumannii multi-drug resistant strain and a susceptible reference strain - Abefflux

Project description:Transcriptomic comparison of a multidrug resistant Acinetobacter baumannii strain and a susceptible reference strain.

2009-11-20 | E-MEXP-2254 | biostudies-arrayexpress

Comparative phosphoproteomics reveals the role of AmpC β-lactamase phosphorylation in the clinical imipenem-resistant strain Acinetobacter baumannii SK17 (MaxQuant 1.3 and 1.4)

Project description:Nosocomial outbreaks of infections caused by multidrug-resistant Acinetobacter baumannii have emerged as a serious threat to human health. The phosphoproteomics of pathogenic bacteria have been investigated for their role in virulence regulation networks. In this study, we analyzed the phosphoproteomics of two clinical isolates of A. baumannii: imipenem-sensitive strain SK17-S and -resistant strain SK17-R.

2015-10-27 | PXD002033 | Pride

The transcriptomic response of Acinetobacter baumannii to colistin and doripenem alone and in combination in an in vitro pharmacokinetics/pharmacodynamics model

Project description:Objectives: Colistin remains a last-line treatment for multidrug-resistant Acinetobacter baumannii and combined use of colistin and carbapenems has shown synergistic effects against multidrug-resistant strains. In order to understand the bacterial responses to these antibiotics we analysed the transcriptome of A. baumannii following exposure to each.

2014-11-30 | GSE62794 | GEO

Combined analysis of genome-wide DNA methylome and transcriptome reveals the first epigenetic-based antibiotic-resistance mechanism in Acinetobacter baumannii

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

Transcriptional changes in response to OXA-23 overexpression in Acinetobacter baumannii ATCC 17978

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

Host cell response after infection with a virulent and a non virulent Acinetobacter baumannii IC2 OXA-23 strain

Project description:Acinetobacter baumannii is an emerging nosocomial pathogen that causes severe infections such as pneumonia or blood stream infections. As the incidence of multidrug-resistant A. baumannii infections in intensive care units increases, the pathogen is considered of greater clinical concern. Little is known about the molecular interaction of A. baumannii with its host yet. In order to study the host cell response upon A. baumannii infection, a complexome analysis was performed. For this, we identified a virulent ( A. baumannii 2778) and a non virulent (A. baumannii 1372) clinical isolate of genetic similarity > 95 % (both isolates from IC 2 harboring OXA 23). HUVECs were infected with each strain and enriched mitochondrial fraction was used for complexome profiling. Complexome analysis identified dramatic reduction of mitochondrial protein complexes in the strain of greater virulence.

2023-04-10 | PXD035235 | Pride

Deep learning-guided discovery of a narrow-spectrum antibiotic against Acinetobacter baumannii

Project description:Acinetobacter baumannii is a nosocomial Gram-negative pathogen that often displays multidrug-resistance due to its robust outer membrane and its ability to acquire and retain extracellular DNA. Moreover, it can survive for prolonged durations on surfaces and is resistant to desiccation. Discovering new antibiotics against A. baumannii has proven challenging through conventional screening approaches. Fortunately, machine learning methods allow for the rapid exploration of chemical space, increasing the probability of discovering new chemical matter with antibacterial activity against this burdensome pathogen. Here, we screened ~7,500 molecules for those that inhibited the growth of A. baumannii in vitro. We trained a deep neural network with this growth inhibition dataset and performed predictions on the Drug Repurposing Hub for structurally novel molecules with activity against A. baumannii. Through this approach, we discovered abaucin, an antibacterial compound with narrow-spectrum activity against A. baumannii, which could overcome intrinsic and acquired resistance mechanisms in clinical isolates. Further investigations revealed that abaucin perturbs lipoprotein trafficking through a mechanism involving LolE, a functionally conserved protein that contributes to shuttling lipoproteins from the inner membrane to the outer membrane. Moreover, abaucin was able to control an A. baumannii infection in a murine wound model. Together, this work highlights the utility of machine learning in discovering new antibiotics and describes a promising lead with narrow-spectrum activity against a challenging Gram-negative pathogen.

2023-02-01 | GSE214305 | GEO

ppGpp signal plays critical role in pathogenesis of Acinetobacter baumannii 17978

Project description:Acinetobacter baumannii is a major cause of nosocomial infections which can survive in different hospital environments and its multidrug-resistant capacity is major concern now-a-days. ppGpp dependent stringent response mediates reprogramming of gene expression with diverse function in many bacteria. A baumannii A1S_0579 gene is responsible for ppGpp production. Transcriptome analysis of early stationary phase cultures represents several differentially expressed genes in ppGpp deficient strain (∆A1S_0579). We found that the expression of csu operon, which is important in pili biosynthesis for early biofilm formation, was significantly reduced in the ppGpp-deficient strain. Our findings showed that ppGpp signaling plays critical role in biofilm formation, surface motility, adherence and virulence of A baumannii. This study is the first demonstration of the association between ppGpp and pathogenicity of A. baumannii.

2021-05-01 | GSE173627 | GEO

Transcriptomic analysis of paired patient isolates of Acinetobacter baumannii following failed colistin treatment

Project description:Colistin is a crucial last-line drug used for the treatment of life-threatening infections caused by multi-drug resistant strains of the Gram-negative bacteria, Acinetobacter baumannii. However, colistin resistant A. baumannii isolates can be isolated following failed colistin therapy. Resistance is most often mediated by the addition of phosphoethanolamine (pEtN) to lipid A by PmrC, following missense mutations in the pmrCAB operon encoding PmrC and the two-component signal transduction system PmrA/PmrB. We recovered an isogenic pair of A. baumannii isolates from a single patient before (6009-1) and after (6009-2) failed colistin treatment that displayed low/intermediate and high levels of colistin resistance, respectively. To understand how increased colistin-resistance arose, we genome sequenced each isolate which revealed that 6009-2 had an extra copy of the insertion sequence element ISAba125 within a gene encoding an H-NS-family transcriptional regulator. Consequently, transcriptomic analysis of the clinical isolates identified was performed and more than 150 genes as differentially expressed in the colistin-resistant, hns mutant, 6009-2. Importantly, the expression of eptA, encoding a second lipid A-specific pEtN transferase, but not pmrC, was significantly increased in the hns mutant. This is the first time an H-NS-family transcriptional regulator has been associated with a pEtN transferase and colistin resistance.

2018-02-19 | GSE107964 | GEO

A Subtractive Proteomics Approach for the Identification of Immunodominant Acinetobacter baumannii Vaccine Candidate Proteins

Project description:Background: Acinetobacter baumannii is one of the most dangerous multidrug-resistant pathogens worldwide. Currently, 50-70% of clinical isolates of A. baumannii are extensively drug-resistant (XDR) and available antibiotic options against A. baumannii infections are limited. There are still needs to discover specific de facto bacterial antigenic proteins that could be effective vaccine candidates in human infection. With the growth of research in recent years, several candidate molecules have been identified for vaccine development. So far, there is no public health authorities approved vaccine against A. baumannii. Methods: The purpose of this study was to identify immunodominant vaccine candidate proteins that can be immunoprecipitated specifically with patients’ IgGs. Relaying on hypothesis that IgGs of infected person have capacity to capture immunodominant bacterial proteins. Herein, outer membrane and secreted proteins of sensitive and drug resistant A. baumannii were captured by using IgGs obtained from patient and healthy control sera and were identified by LC-MS/MS analysis. Results: By using subtractive proteomic approach, we determined 34 unique proteins which were captured only in drug-resistant A. baumannii strain via patient sera. After extensive evaluation of predicted epitope regions, solubility, membrane transverse characteristics, and structural properties, we selected several notable vaccine candidates. Conclusion: We identified vaccine candidate proteins that triggered de facto response of human immune system against the antibiotic-resistant A. baumannii. Precipitation of bacterial proteins via patient immunoglobulins was a novel approach to identify the proteins which have potential to trigger to response in patient immune system.

2022-11-02 | PXD037507 | Pride

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data