Pseudomonas aeruginosa
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA238880 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR1173920.fastq.gz | Fastqsanger.gz | |||
| SRR1173930.fastq.gz | Fastqsanger.gz | |||
| SRR1173940.fastq.gz | Fastqsanger.gz | |||
| SRR1173950.fastq.gz | Fastqsanger.gz | |||
| SRR1173960.fastq.gz | Fastqsanger.gz |
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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:We analyzed the transcriptional profile of P.aeruginosa PA14 grown under 14 different environmental conditions. These included conditions of growth within biofilms, at various temperatures, osmolarities and phosphate concentrations, under anaerobic conditions, attached to a surface and conditions encountered within the eukaryotic host. We found that >30% of the PA14 genome was differentially regulated at least under one of the 14 environmental conditions (referred to as the adaptive transcriptome). Most of the genes were also differentially regulated upon sigma factor hyper expression and/or inactivation (GEO accession number GSE54999) and many of those belonged to primary alternative sigma factor regulons. The samples of P. aeruginosa PA14 wild type strain were cultivated under 14 different experimental conditions and were analyzed by RNA-seq. For each condition, at least two biological replicates were generated Please note that PA14 is our standard lab strain used for all generated data in this records. There is no mutation introduced for any of those experiments, and thus, the descriptions only highlight the growth conditions.
2015-06-16 | E-GEOD-55197 | biostudies-arrayexpress
Project description:Systems biology approaches address the challenge of translating sequence information into function. In this study, we described the Pseudomonas aeruginosa PA14 proteomic landscape and quantified environment-driven changes in protein levels by the use of LC-MS techniques. Previously recorded mRNA data allowed a comparison of RNA to protein ratios for each individual gene and, thus, to explore the relationship between an mRNA being differentially expressed between environmental conditions and the mRNA-protein correlation for that gene. We developed a Random Forest-based predictor for protein levels and found that the mRNA to protein correlation was higher for genes/proteins that undergo dynamic changes. One example of a discrepancy between protein and predicted protein levels was observed for a phage-related gene cluster, which was translated into low protein levels under standard growth conditions. However, under SOS-inducing conditions more protein was produced and the prediction of protein levels based on mRNA abundancy became more accurate. In conclusion, our systems biology approach sheds light on complex mRNA to protein level relationships and uncovered condition-dependent post-transcriptional regulatory events.
2020-06-25 | GSE116308 | GEO
Project description:Transcriptiomes of non-replicating, replicating and pre-divisonal P. aeruginosa PA14 FACS subpopulations during replication-coupled growth in LB medium.
2022-11-07 | GSE217100 | GEO
Project description:We studied adaptation of the metabolically versatile bacterium Pseudomonas aeruginosa to standard laboratory conditions by propagating mismatch repair-deficient P. aeruginosa in exponential phase for 24 days in rich medium. In the selective environment of this large-bottleneck mutation accumulation experiment, the bacteria developed shorter lag phases, higher growth rates and higher maximum cell densities. Transcriptional profiling and phenotyping for growth in different media revealed that higher fitness under laboratory conditions evolved via different pathways. Although common adaptive mutations or mutations that define trade-offs were not identified, there was a convergent evolution of transcriptional profiles associated with a shift from biofilm-associated to planktonic lifestyles. Our results indicate that under constant planktonic conditions P. aeruginosa uses several genetic pathways in order to fine-tune adaptation towards faster growth. The selected mutations in the different genetic pathways show a great variety of biofilm, virulence and motility phenotypic trade-offs, thus implying that on the population level, the adaptation of P. aeruginosa to constant conditions does not compromise its versatility. Methods: mRNA profiles were generated for Pseudomonas aeruginosa samples derived from LB-cultures grown to an OD600 =0.4-0.6. The removal of ribosomal RNA was performed using the Ribo-Zero Bacteria Kit (Illumina) and cDNA libraries were generated with the ScriptSeq v2 Kit (Illumina). The samples were sequenced in single end mode on an Illumina HiSeq 2500 device and mRNA reads were trimmed and mapped to the NC_008463.1 (PA14) reference genome from NCBI using Stampy pipeline with default settings.
2020-11-26 | GSE146906 | GEO
Project description:Recent studies have shown that the concentrations of proteins expressed from orthologous genes are often conserved across organisms, and to a greater extent than the abundances of the corresponding mRNAs. However, such studies have not distinguished between evolutionary (e.g., sequence divergence) and environmental (e.g., growth condition) effects on the regulation of steady-state protein and mRNA abundances. Here we systematically investigated the transcriptome and proteome of two closely related Pseudomonas aeruginosa strains, PAO1 and PA14, under identical experimental conditions, thus controlling for environmental effects. For 703 genes observed by both shotgun proteomics and microarray experiments, we find that the protein-to-mRNA ratios are highly correlated between orthologous genes in the two strains, to an extent comparable to protein and mRNA abundances. In spite of this high molecular similarity between PAO1 and PA14, we found that several metabolic, virulence, and antibiotic resistance genes are differentially expressed between the two strains, mostly at the protein but not at the mRNA level. Our data demonstrate that post-transcriptional regulation is important for understanding the discordance between mRNA and protein abundance.
2014-05-08 | PXD000684 | Pride
Project description:LFQ proteome datasets of Pseudomonas aeruginosa type strain PA14 cultured at different enviromental conditions: Exponential-, transition- and stationary(12 h and 24 h)growth phases. Biofilm (24 h and 48 h), low osmolarity conditions (control = exponential phase), iron starvation and respective control, Sub-MIC ciproflox treatment and respective control.
2018-11-20 | PXD010200 | Pride
Project description:Genomic DNA from Pseudomonas aeruginosa strains PAO1 and PA14
2015-11-15 | GSE67038 | GEO
Project description:Determination of the RNA interacting with vfr mRNA at two different time-points during growth on the three strains PAO1, PA14 and IHMA87, representing the three major P. aeruginosa phylogenetic lineages, using rGRIL-seq.
2022-02-07 | GSE171893 | GEO
Project description:Before and after anaerobic Fe(II) shocked WT and ∆bqsR of late stationary phase P. aeruginosa PA14 strains Associated publication: Kreamer NN, Costa F, Newman DK. 2015. The ferrous iron-responsive BqsRS two-component system activates genes that promote cationic stress tolerance. mBio 6(1):e02549-14. doi:10.1128/mBio.02549-14.
2015-02-01 | GSE65393 | GEO