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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:We identified binding sites genome-wide for carbon metabolism transcriptional response regulators in Pseudomonas stutzeri RCH2, Pseudomonas putida KT2240, Pseudomonas fluorescens FW300-N2E2 and FW300-N2C3 by DNA-affinity-purified (DAP) sequencing.
2020-10-01 | GSE157075 | GEO
Project description:Sohn2010 - Genome-scale metabolic network of
Pseudomonas putida (PpuMBEL1071)
This model is described in the article:
In silico genome-scale
metabolic analysis of Pseudomonas putida KT2440 for
polyhydroxyalkanoate synthesis, degradation of aromatics and
anaerobic survival.
Sohn SB, Kim TY, Park JM, Lee
SY.
Biotechnol J 2010 Jul; 5(7):
739-750
Abstract:
Genome-scale metabolic models have been appearing with
increasing frequency and have been employed in a wide range of
biotechnological applications as well as in biological studies.
With the metabolic model as a platform, engineering strategies
have become more systematic and focused, unlike the random
shotgun approach used in the past. Here we present the
genome-scale metabolic model of the versatile Gram-negative
bacterium Pseudomonas putida, which has gained widespread
interest for various biotechnological applications. With the
construction of the genome-scale metabolic model of P. putida
KT2440, PpuMBEL1071, we investigated various characteristics of
P. putida, such as its capacity for synthesizing
polyhydroxyalkanoates (PHA) and degrading aromatics. Although
P. putida has been characterized as a strict aerobic bacterium,
the physiological characteristics required to achieve anaerobic
survival were investigated. Through analysis of PpuMBEL1071,
extended survival of P. putida under anaerobic stress was
achieved by introducing the ackA gene from Pseudomonas
aeruginosa and Escherichia coli.
This model is hosted on
BioModels Database
and identified by:
MODEL1507180043.
To cite BioModels Database, please use:
BioModels Database:
An enhanced, curated and annotated resource for published
quantitative kinetic models.
To the extent possible under law, all copyright and related or
neighbouring rights to this encoded model have been dedicated to
the public domain worldwide. Please refer to
CC0
Public Domain Dedication for more information.
2015-07-30 | MODEL1507180043 | 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
BioModels Database
and identified by:
MODEL1507180020.
To cite BioModels Database, please use:
BioModels Database:
An enhanced, curated and annotated resource for published
quantitative kinetic models.
To the extent possible under law, all copyright and related or
neighbouring rights to this encoded model have been dedicated to
the public domain worldwide. Please refer to
CC0
Public Domain Dedication for more information.
2015-07-30 | MODEL1507180020 | BioModels