Ontology highlight
ABSTRACT:
PROVIDER: PRJNA1244350 | ENA |
REPOSITORIES: ENA
Similar Datasets
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:Tolerance is a major defense strategy against infection. During the host response to pathogens, tolerance restricts inflammatory damage to tissues, maintaining the long-term integrity of organs. The mechanisms that establish tolerance are poorly understood. We analyzed pulmonary isolates of Pseudomonas aeruginosa that evolved to coexist with tolerant hosts and found that these opportunistic pathogens facilitate tolerance by stimulating ketogenesis. Ketone body production in the airway limits the accumulation of detrimental factors that injure the lung, such as inflammatory cytokines and effector phagocytes. Although ketones are typically synthesized in the liver, in situ metabolo-transcriptomic studies revealed that P. aeruginosa drives their generation in the lung by co-opting the metabolism of alveolar macrophages, which are pulmonary cells of hepatic origin. This phenomenon was restricted to clinical isolates and not observed with laboratory strains of P. aeruginosa , confirming the unique metabolo-tolerogenic properties of ESKAPE pathogens adapted to the human lung.
2023-10-12 | GSE203352 | GEO
Project description:Transcriptome analysis was applied to characterize the physiological activities of Psuedomonas aeruginosa cells grown for three days in drip flow biofilm reactors when compared to the activities of P. aeruginosa grown planktonically to exponential phase in the same media. Here, rather than examining the effect of an individual gene on biofilm antibiotic tolerance, we used a transcriptomics approach to identify regulons and groups of related genes that are induced during biofilm growth of Pseudomonas aeruginosa. We then tested for statistically significant overlap between the biofilm-induced genes and independently compiled gene lists corresponding to stress responses and other putative antibiotic protective mechanisms. This data was evaluated and used to select strains that carry transposon mutations in genes that might play a role in antibiotic tolerance of biofilms. The strains were evaluated for defects in biofilm tolerance.
2015-05-11 | GSE65869 | GEO
Project description:Pseudomonas aeruginosa harbors sophisticated transcription factor (TF) networks to coordinately regulate cellular metabolic states for rapidly adapting to changing environments. The superior capacity in fine-tuning the metabolic states enables its success in tolerance to antibiotics and evading host immune defenses. However, the linkage among transcriptional regulation, metabolic states, and antibiotic tolerance in P. aeruginosa remains largely unclear. By screening the P. aeruginosa TF mutant library constructed by CRISPR/Cas12k-guided transposase, we identify that rccR (PA5438) is a major genetic determinant in aminoglycoside antibiotic tolerance, the deletion of which substantially enhances bacterial tolerance. We further reveal the inhibitory roles of RccR in pyruvate metabolism (aceE/F) and glyoxylate shunt pathway (aceA and glcB), and overexpression of aceA or glcB enhances bacterial tolerance. Moreover, we identify that 2-keto-3-deoxy-6-phosphogluconate (KDPG) is a signal molecule that directly binds to RccR. Structural analysis of the RccR/KDPG complex reveals the detailed interactions. Substitution of the key residues R152, K270, or R277 with alanine abolishes KDPG sensing by RccR and impairs bacterial growth with glycerol or glucose as the sole carbon source. Collectively, our study unveils the connection between aminoglycoside antibiotic tolerance and RccR-mediated central carbon metabolism regulation in P. aeruginosa, and elucidates the KDPG sensing mechanism by RccR.
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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.
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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:Pseudomonas aeruginosa PA14 metabolic model
2022-05-09 | MODEL2205060001 | BioModels
Project description:Genomic DNA from Pseudomonas aeruginosa strains PAO1 and PA14
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Project description:Transcriptome analysis was applied to characterize the physiological activities of Psuedomonas aeruginosa cells grown for three days in drip flow biofilm reactors when compared to the activities of P. aeruginosa grown planktonically to exponential phase in the same media. Here, rather than examining the effect of an individual gene on biofilm antibiotic tolerance, we used a transcriptomics approach to identify regulons and groups of related genes that are induced during biofilm growth of Pseudomonas aeruginosa. We then tested for statistically significant overlap between the biofilm-induced genes and independently compiled gene lists corresponding to stress responses and other putative antibiotic protective mechanisms. This data was evaluated and used to select strains that carry transposon mutations in genes that might play a role in antibiotic tolerance of biofilms. The strains were evaluated for defects in biofilm tolerance. One planktonic condition with four biological replicates; One drip flow biofilm condition grown for 72 hours with three biological replicates; One drip flow biofilm condition grown for 84 hours with three biological replicates.
2015-05-11 | E-GEOD-65869 | biostudies-arrayexpress
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