Pseudomonas aeruginosa isolate:HU20
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA809509 | ENA |
REPOSITORIES: ENA
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Project description:Purpose: Pseudomonas aeruginosa is a major cause of morbidity and mortality in patients with cystic fibrosis (CF). We provide an insight to the DNA auxotrophy of P. aeruginosa PASS4 isolate. Better understanding of P. aeruginosa adaptations in the CF lung environment can have a great impact in the development of specialised treatment regimes aimed at the eradications of P. aeruginosa infections. Methods: P. aeruginosa strains PAO1 and PASS4 were grown in minimal medium with either L-Asparagine or DNA as a carbon source, in biological triplicates. RNA was extracted and sequenced on Illumina HiSeq 1000 platform. The sequence reads that passed quality filters were analyzed using EdgePro and DESeq packages, as well as the Rockhopper tool. Results: We mapped > 10 million paired sequence reads per sample to the genome of P. aeruginosa PAO1 and identified a total of 576 genes differentially expressed by PASS4 when grown in DNA (P value < 0.01, log2 fold-change 1< to < -1), with 322 genes upregulated and 254 genes downregulated. There were a total of 423 genes differentially expressed by PAO1 when grown in DNA (P value < 0.01, log2 fold-change 1< to <-1), with 359 genes upregulated and 64 genes downregulated . A total of 129 transcripts displayed similar expression patterns in both organisms, with 112 being upregulated and 17 down-regulated. Conclusions: Our study identified that P. aeruginosa PASS4 was a purine auxotroph. Purine auxotropy may represent a viable microbial strategy for adaptation to DNA rich environments such as the CF lung.
2019-06-16 | GSE100287 | GEO
Project description:Taxonomic outliers of Pseudomonas aeruginosa recently emerged as infectious for humans. Here we present the first analysis of a hyper-virulent isolate that cause hemorrhagic pneumonia. We demonstrated that, in two sequential clones CLJ1 and CLJ3 recovered from a patient with chronic obstructive pulmonary disease undergoing antibiotic therapy, insertion of a mobile genetic element into the P. aeruginosa chromosome affected major virulence-associated phenotypes and led to increased resistance to antibiotics used to treat the patient. Our work reveals insertion sequences as major players in enhancing the pathogenic potential of a P. aeruginosa taxonomic outlier by modulating both the virulence and resistance to antimicrobials. This also explains the ability of this bacterium to adapt to an infected host and cause a serious disease.
2019-03-18 | PXD011105 | Pride
Project description:Pseudomonas aeruginosa isolate:Pseudomonas aeruginosa HS17-127 Genome sequencing
| PRJNA661977 | ENA
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:Analysis of Pseudomonas aeruginosa PAO1 treated with 200 µM sphingomyelin. Results provide insight into the response to sphingomyelin in P. aeruginosa.
2017-02-12 | GSE83078 | GEO
Project description:We report RNA sequencing data for mRNA transcripts obtained from tobramycin exposed phoenix colonies, VBNCs, and various controls (untreated lawn, edge of the zone of clearance of tobramycin, treated outer background lawn). Extracted mRNA was sequenced using an Illumina HiSeq 4000, mapped to a Pseudomonas aeruginosa PAO1 reference genome, and processed to obtain counts for all gene transcripts for each sample. This is the first sequencing data generated for Pseudomonas aeruginosa phoenix colonies and VBNCs.
2022-03-27 | GSE199323 | GEO
Project description:Purpose : The goal of this study was to use RNA Seq to define the regulon of the transciption factor Anr by comparing global transcriptional profiles of Pseudomonas aeruginosa strain PAO1 and a clinical isolate with their isogenic ?anr mutants, grown in colony biofilms at 1% oxygen. Methods : mRNA profiles were generated for laboratory strain PAO1 and for a clinical isolate J215, as well as for ?anr derivatives of each strain, in duplicate, by deep sequencing. Strains were grown for 12 hours in colony biofilms at 1% O2, 5% CO2 prior to RNA harvest. Ribosomal and transfer RNAs were removed using the MICROBExpress kit (Life Technologies). mRNA reads were trimmed and mapped to the PAO1 NC_002516 reference genome from NCBI using the ClC Genomics Workbench platform and defaut parameters. mRNA profiles of 12 hour colony biofilms were generated for P. aeruginosa strains PAO1 WT, PAO1 ?anr, clinical isolate J215, and J215 ?anr, each in duplicate, by deep sequencing using Illumina HiSeq.
2015-06-29 | E-GEOD-68534 | biostudies-arrayexpress
Project description:We report the transcriptome of Pseudomonas aeruginosa PA14 under swarming conditions as compared to a swimming control
2019-12-23 | GSE121504 | GEO
Project description:Pseudomonas aeruginosa isolate:P59 Genome sequencing and assembly
| PRJNA343860 | ENA
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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MODEL1507180020.
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2015-07-30 | MODEL1507180020 | BioModels