Ontology highlight
ABSTRACT:
PROVIDER: PRJNA975476 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Pseudomonas aeruginosa is a virulent opportunistic pathogen responsible for high morbity in COPD, burns , implanted medical devices and cystic fibrosis. Pseudomonas aeruginosa is a problematic colonizer of the human lung. P. aeruginosa produces a phospholipase C (PlcH) that degrades choline-containing lipids such as phosphatidylcholine and sphingomylein that are found in lung surfactant and in host membranes. In this study, we analyzed gene expression in mutants defective in PlcH production (delta-plcH and delta-gbdR) and the wild type when growing in medium with lung surfactant. Pseudomonas aeruginosa was cultured in liquid cultures with aeration in a defined medium with Survanta, a lung surfactant replacement. Cultures were harvested during mid-exponential phase, and RNA was isolated for microarray analysis. The P. aeruginosa strain PAO1 wild type gene expression was compared to expression profiles from delta-gbdR and delta-plcHR deletion mutants, two mutants defective in PlcH production.
2013-01-01 | E-GEOD-41926 | biostudies-arrayexpress
Project description:ErfA is a transcription factor of Pseudomonas aeruginosa. We here define the genome-wide binding sites of ErfA by DAP-seq in Pseudomonas aeruginosa PAO1 and IHMA87, Pseudomonas chlororaphis PA23, Pseudomonas protegens CHA0 and Pseudomonas putida KT2440.
2019-12-20 | GSE137648 | GEO
Project description:The Pseudomonas aeruginosa quorum-sensing (QS) systems contribute to bacterial homeostasis and pathogenicity. Although many regulators have been characterized to control the production of virulence factors and QS signaling molecules, its detailed regulatory mechanisms still remain elusive. Here, we performed chromatin immunoprecipitation followed by high-throughput DNA sequencing (ChIP-seq) on 10 key QS regulators. The direct regulation of these genes by corresponding regulator has been confirmed by Electrophoretic mobility shift assays (EMSAs) and quantitative real-time polymerase chain reactions (qRT-PCR). Binding motifs are found by using MEME suite and verified by footprint assays in vitro. Collectively, this work provides new cues to better understand the detailed regulatory networks of QS systems. ChIP-seq of 10 QS regulators in Pseudomonas aeruginosa
2015-08-04 | E-GEOD-65356 | biostudies-arrayexpress
Project description:Pseudomonas aeruginosa is a virulent opportunistic pathogen responsible for high morbity in COPD, burns , implanted medical devices and cystic fibrosis. Pseudomonas aeruginosa is a problematic colonizer of the human lung. P. aeruginosa produces a phospholipase C (PlcH) that degrades choline-containing lipids such as phosphatidylcholine and sphingomylein that are found in lung surfactant and in host membranes. In this study, we analyzed gene expression in mutants defective in PlcH production (delta-plcH and delta-gbdR) and the wild type when growing in medium with lung surfactant.
2013-01-01 | GSE41926 | GEO
Project description:The Pseudomonas aeruginosa quorum-sensing (QS) systems contribute to bacterial homeostasis and pathogenicity. Although the AraC family transcription factor VqsM has been characterized to control the production of virulence factors and QS signaling molecules, its detailed regulatory mechanisms still remain elusive. Here, we report that VqsM directly binds to the lasI promoter region, and thus regulates its expression. To identify additional targets of VqsM in P. aeruginosa PAO1, we performed chromatin immunoprecipitation followed by high-throughput DNA sequencing (ChIP-seq) which detected 48 enriched loci harboring VqsM-binding peaks in P. aeruginosa genome. The direct regulation of these genes by VqsM has been confirmed by Electrophoretic mobility shift assays (EMSAs) and quantitative real-time polymerase chain reactions (qRT-PCR). A VqsM-binding motif is found by using MEME suite and verified by footprint assays in vitro. In addition, VqsM directly binds to the promoter regions of antibiotic resistance regulator NfxB and the master type III system regulator ExsA. Notably, the vqsM mutant displayed more resistance to two types of antibiotics and promoted bacterial survival in a mouse model, compared to the wild type PAO1 strain. Collectively, this work provides new cues to better understand the detailed regulatory networks of QS systems, T3SS, and antibiotic resistance. Pseudomonas aeruginosa MAPO1 containing empty pAK1900 or pAK1900-VqsM-VSV
2014-08-04 | E-GEOD-57284 | biostudies-arrayexpress
Project description:An antivirulence approach targets bacterial virulence rather than cell viability in the antibiotic approach that can readily lead to drug resistance. Opportunistic human pathogen Pseudomonas aeruginosa produces a variety of virulence factors, and biofilm cells of this bacterium are much more resistant to antibiotics than planktonic cells. To identify novel inorganic antivirulence compounds, the dual screenings of thirty-six metal ions were performed to identify that zinc ions and ZnO nanoparticle inhibited the pyocyanin production and biofilm formation in P. aeruginosa without affecting the growth of planktonic cells. Moreover, zinc ion and ZnO nanoparticle markedly reduced the production of 2-heptyl-3-hydroxy-4(1H)-quinolone and siderophore pyochelin, while increased the production of another sideropore pyoverdine and swarming motility. Further, zinc ion and ZnO nanoparticle clearly suppressed hemolytic activity in P. aeruginosa. Transcriptome analyses showed that ZnO nanoparticle induced zinc cation efflux pump czc operon, porin genes (oprD and opdT), and Pseudomonas type III repressor A ptrA, while repressed pyocyanin-related phz operon, which partially explains the phenotypic changes. Overall, ZnO nanoparticle is a potential candidate for use in an antivirulence approach against persistent P. aeruginosa infection.
2015-05-25 | GSE46947 | GEO
Project description:To further determine the origin of the increased virulence of Pseudomonas aeruginosa PA14 compared to Pseudomonas aeruginosa PAO1, we report a transcriptomic approach through RNA sequencing. Next-generation sequencing (NGS) has revolutioned sistems-based analsis of transcriptomic pathways. The goals of this study are to compare the transcriptomic profile of all 5263 orthologous genes of these nearly two strains of Pseudomonas aeruginosa.
2019-09-23 | GSE125646 | GEO
Project description:Pseudomonas aeruginosa PA14 metabolic model
2022-05-09 | MODEL2205060001 | BioModels
Project description:Analysis of a SigX knockout mutant of Pseudomonas aeruginosa H103 strain in minimal medium with glucose as carbon source (M9G). SigX, one of the 19 extra-cytoplasmic function sigma factors of P. aeruginosa, was only known to be involved in transcription of the gene encoding the major outer membrane protein OprF in Pseudomonas aeruginosa. Deletion of the ECF sigma factor sigX gene provide insights into the SigX role in several virulence and biofilm- related phenotypes in Pseudomonas aeruginosa.
2014-01-01 | GSE51076 | GEO
Project description:Oberhardt2008 - Genome-scale metabolic
network of Pseudomonas aeruginosa (iMO1056)
This model is described in the article:
Genome-scale metabolic
network analysis of the opportunistic pathogen Pseudomonas
aeruginosa PAO1.
Oberhardt MA, Puchałka J, Fryer
KE, Martins dos Santos VA, Papin JA.
J. Bacteriol. 2008 Apr; 190(8):
2790-2803
Abstract:
Pseudomonas aeruginosa is a major life-threatening
opportunistic pathogen that commonly infects immunocompromised
patients. This bacterium owes its success as a pathogen largely
to its metabolic versatility and flexibility. A thorough
understanding of P. aeruginosa's metabolism is thus pivotal for
the design of effective intervention strategies. Here we aim to
provide, through systems analysis, a basis for the
characterization of the genome-scale properties of this
pathogen's versatile metabolic network. To this end, we
reconstructed a genome-scale metabolic network of Pseudomonas
aeruginosa PAO1. This reconstruction accounts for 1,056 genes
(19% of the genome), 1,030 proteins, and 883 reactions. Flux
balance analysis was used to identify key features of P.
aeruginosa metabolism, such as growth yield, under defined
conditions and with defined knowledge gaps within the network.
BIOLOG substrate oxidation data were used in model expansion,
and a genome-scale transposon knockout set was compared against
in silico knockout predictions to validate the model.
Ultimately, this genome-scale model provides a basic modeling
framework with which to explore the metabolism of P. aeruginosa
in the context of its environmental and genetic constraints,
thereby contributing to a more thorough understanding of the
genotype-phenotype relationships in this resourceful and
dangerous pathogen.
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2015-07-30 | MODEL1507180020 | BioModels