Dataset Information

Do Copper enhance antibiotic resistance (AR) in resistant bacteria and/or induce AR in sensitive bacteria? [RNA-seq]

ABSTRACT: The aim of this experiment was to determine if the development of resistance to antibiotics can be driven by the concentration and speciation of Cu. Experimental setup was designed to investigate two hypotheses for which two strains of Gram- bacteria have been selected: - Do TE enhance AR in resistant bacteria? Resistant strain: Bioluminescent Pseudomonas aeruginosa PAO1 (Xen41, Tetracycline resistant) - Do TE induce AR in sensitive bacteria? Sensitive strain: Pseudomonas aeruginosa PAO1 (Wild Type)

ORGANISM(S): Pseudomonas aeruginosa

PROVIDER: GSE160187 | GEO | 2020/10/28

REPOSITORIES: GEO

ACCESS DATA

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

Project description:Although Pseudomonas aeruginosa is an opportunistic pathogen that does not often naturally infect alternate hosts such as plants, the plant-P. aeruginosa model has become a widely recognized system for identifying new virulence determinants and studying pathogenesis of this organism. Here we examine how both host factors and P. aeruginosa PAO1 gene expression are affected in planta after infiltration into incompatible and compatible cultivars of tobacco (Nicotiana tabacum L.) Nicotiana tabacum has a resistance gene (N) against tobacco mosaic virus; and although resistance to PAO1 infection correlated to the presence of a dominant N-gene, our data suggests that it is not a factor in resistance against Pseudomonas. We did observe that the resistant tobacco cultivar had higher basal levels of salicylic acid, and a stronger salicylic acid response upon infiltration of PAO1. Salicylic acid acts as a signal to activate defense responses in plants, limiting the spread of the pathogen and preventng access to nutrients. It has also been shown to have direct virulence modulating effects on P. aeruginosa. We also examined host effects on the pathogen by analyzing global gene expression profiles of bacteria removed from the intracellular fluid of the two plant hosts. We discovered that the availability of micronutrients, particularly sulfate and Pi, are important factors in in planta pathogenesis, and that the amounts of these nutrients made available to the bacteria may in turn have an effect on virulence gene expression. Indeed, there are several reports suggesting that P. aeruginosa virulence is influenced in mammalian hosts by the availability of iron and by levels of O2. Experiment Overall Design: Pseudomonas aeruginosa cells were removed from leaf tissue 24 hours post-infiltration and RNA was directly extracted from these cells. Comparisons are between cells removed from a susceptible cultivar of Nicotiana tabacum (cv. Samsun) and a resistant cultivar (cv. Xanthi). Three biological replicates per cultivar were analyzed.

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.

Dataset Information

Do Copper enhance antibiotic resistance (AR) in resistant bacteria and/or induce AR in sensitive bacteria? [RNA-seq]

Dataset's files

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets