Project description:The sarcosine oxidase locus is controlled by GbdR and SouR independently induced by glycine betaine and sarcosine, respectively. The goal of this study was to identify the members of the SouR regulon. Therefore, the comparison strains were a gbdR mutant and a gbdRsouR double mutant. The conditions for inclusion in the souR regulon were: (i) called present in the array, (ii) changed more than 2.5-fold in signal in a statistically significant manner, (iii) altered in the presence of sarcosine and dependent on souR.
Project description:The Pseudomonas aeruginosa MvfR-dependent QS regulatory pathway controls the expression of key virulence genes; and is activated via the extracellular signals 4-hydroxy-2-heptylquinoline (HHQ) and 3,4-dihydroxy-2-heptylquinoline (PQS). Our findings reveal a multi-layered homeostatic regulation of PQS and HHQ and the MvfR regulon component PqsE which is a key mediator in orchestrating this homeostatic regulation.
Project description:The ParS/ParR two component regulatory system plays important roles for multidrug resistance in Pseudomonas aeruginosa. In this study we report RNA-seq analyses of the transcriptomes of P. aeruginosa PAO1 wild type and par mutants growing in a minimal medium containing 2% casamino acids. This has allowed the quantification of PAO1 transcriptome, and further defines the regulon that is dependent on the ParS/ParR system for expression. Our RNA-seq analysis produced the first estimates of absolute transcript abundance for the 5570 coding genes in P. aeruginosa PAO1. Comparative transcriptomics of P. aeruginosa PAO1 and par mutants identified a total of 464 genes regulated by ParS and ParR. Results also showed that mutations in the parS/parR system abolished the expression of the mexEF-oprN operon by down-regulating the regulatory gene mexS. In addition to affecting drug resistance genes, transcripts of quorum sensing genes (rhlIR and pqsABCDE-phnAB), were significantly up-regulated in both parS and parR mutants. Consistent with these results, a significant portion of the ParS/ParR regulated genes belonged to the MexEF-OprN and quorum sensing regulons. Deletion of par genes also lead to overproduction of phenazines and increased swarming motility, consistent with the up-regulation of quorum sensing genes. Our results established a link among ParS/ParR, MexEF-OprN and quorum sensing in Pseudomonas aeruginosa. Based on these results, we propose a model to illustrate the relationship among these regulatory systems in P. aeruginosa. A total of 9 samples were analyzed in AB medium + 2% casamino acids, Pseudomonas aeruginosa PAO1 wild type strain (3 replicates); Pseudomonas aeruginosa parS mutant (3 replicates); Pseudomonas aeruginosa parR mutant (3 replicates).
Project description:Analysis of Pseudomonas aeruginosa PAO1 treated with 200 µM sphingomyelin. Results provide insight into the response to sphingomyelin in P. aeruginosa.
Project description:Characterization of the sRNA content of OMVs harvested from Pseudomonas aeruginosa strain PA14 LB cultue with and without tobramycin (1ug/mL)
Project description:The ParS/ParR two component regulatory system plays important roles for multidrug resistance in Pseudomonas aeruginosa. In this study we report RNA-seq analyses of the transcriptomes of P. aeruginosa PAO1 wild type and par mutants growing in a minimal medium containing 2% casamino acids. This has allowed the quantification of PAO1 transcriptome, and further defines the regulon that is dependent on the ParS/ParR system for expression. Our RNA-seq analysis produced the first estimates of absolute transcript abundance for the 5570 coding genes in P. aeruginosa PAO1. Comparative transcriptomics of P. aeruginosa PAO1 and par mutants identified a total of 464 genes regulated by ParS and ParR. Results also showed that mutations in the parS/parR system abolished the expression of the mexEF-oprN operon by down-regulating the regulatory gene mexS. In addition to affecting drug resistance genes, transcripts of quorum sensing genes (rhlIR and pqsABCDE-phnAB), were significantly up-regulated in both parS and parR mutants. Consistent with these results, a significant portion of the ParS/ParR regulated genes belonged to the MexEF-OprN and quorum sensing regulons. Deletion of par genes also lead to overproduction of phenazines and increased swarming motility, consistent with the up-regulation of quorum sensing genes. Our results established a link among ParS/ParR, MexEF-OprN and quorum sensing in Pseudomonas aeruginosa. Based on these results, we propose a model to illustrate the relationship among these regulatory systems in P. aeruginosa.
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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