Ontology highlight
ABSTRACT:
PROVIDER: PRJNA996734 | ENA |
REPOSITORIES: ENA
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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: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: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.
This model is hosted on
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MODEL1507180020.
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2015-07-30 | MODEL1507180020 | 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.
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Project description:Genomic DNA from Pseudomonas aeruginosa strains PAO1 and PA14
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2024-02-07 | GSE249862 | GEO