Ontology highlight
ABSTRACT:
PROVIDER: PRJNA807601 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR18050743_1.fastq.gz | Fastqsanger.gz | |||
| SRR18050743_2.fastq.gz | Fastqsanger.gz | |||
| SRR18050744_1.fastq.gz | Fastqsanger.gz | |||
| SRR18050744_2.fastq.gz | Fastqsanger.gz | |||
| SRR18050745_1.fastq.gz | Fastqsanger.gz |
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Project description:P. aeruginosa bacteremia in cancer and bone marrow transplant patients transpires when P. aeruginosa colonizes the GI tract and translocates when the host undergoes immunosuppression. We used microarrays to analyze gene expression when P. aeruginosa transitions from being in the drinking water to when it colonizes the murine GI tract. to analyze gene expression changes in P. aeruginosa as it transitions from living in the drinking water to when it colonizes the murine GI tract. P. aeruginosa was recovered from the drinking water administered to adult C3H/HeN mice and also from murine cecums, and RNA was extracted and hybridized on Affymetrix microarrays.
2010-07-29 | E-GEOD-22665 | biostudies-arrayexpress
Project description:P. aeruginosa bacteremia in cancer and bone marrow transplant patients transpires when P. aeruginosa colonizes the GI tract and translocates when the host undergoes immunosuppression. We used microarrays to analyze gene expression when P. aeruginosa transitions from being in the drinking water to when it colonizes the murine GI tract. to analyze gene expression changes in P. aeruginosa as it transitions from living in the drinking water to when it colonizes the murine GI tract.
2010-07-03 | GSE22665 | GEO
Project description:We characterized the bacterial diversity of chlorinated drinking water from three surface water treatment plants supplying the city of Paris, France. For this purpose, we used serial analysis of V6 ribosomal sequence tag (SARST-V6) to produce concatemers of PCR-amplified ribosomal sequence tags (RSTs) from the V6 hypervariable region of the 16S rRNA gene for sequence analysis. Using SARST-V6, we obtained bacterial profiles for each drinking water sample, demonstrating a strikingly high degree of biodiversity dominated by a large collection of low-abundance phylotypes. In all water samples, between 57.2-77.4% of the sequences obtained indicated bacteria belonging to the Proteobacteria phylum. Full-length 16S rDNA sequences were also generated for each sample, and comparison of the RSTs with these sequences confirmed the accurate assignment for several abundant bacterial phyla identified by SARST-V6 analysis, including members of unclassified bacteria, which account for 6.3-36.5% of all V6 sequences. These results suggest that these bacteria may correspond to a common group adapted to drinking water systems. The V6 primers used were subsequently evaluated with a computer algorithm to assess their hybridization efficiency. Potential errors associated with primer-template mismatches and their impacts on taxonomic group detection were investigated. The biodiversity present in all three drinking water samples suggests that the bacterial load of the drinking water leaving treatment plants may play an important role in determining the downstream community dynamics of water distribution networks.
2009-01-08 | GSE14318 | GEO
Project description:We characterized the bacterial diversity of chlorinated drinking water from three surface water treatment plants supplying the city of Paris, France. For this purpose, we used serial analysis of V6 ribosomal sequence tag (SARST-V6) to produce concatemers of PCR-amplified ribosomal sequence tags (RSTs) from the V6 hypervariable region of the 16S rRNA gene for sequence analysis. Using SARST-V6, we obtained bacterial profiles for each drinking water sample, demonstrating a strikingly high degree of biodiversity dominated by a large collection of low-abundance phylotypes. In all water samples, between 57.2-77.4% of the sequences obtained indicated bacteria belonging to the Proteobacteria phylum. Full-length 16S rDNA sequences were also generated for each sample, and comparison of the RSTs with these sequences confirmed the accurate assignment for several abundant bacterial phyla identified by SARST-V6 analysis, including members of unclassified bacteria, which account for 6.3-36.5% of all V6 sequences. These results suggest that these bacteria may correspond to a common group adapted to drinking water systems. The V6 primers used were subsequently evaluated with a computer algorithm to assess their hybridization efficiency. Potential errors associated with primer-template mismatches and their impacts on taxonomic group detection were investigated. The biodiversity present in all three drinking water samples suggests that the bacterial load of the drinking water leaving treatment plants may play an important role in determining the downstream community dynamics of water distribution networks. 3 different drinking water samples (Orly, Ivry, Joinville drinking water sample)
2009-01-07 | E-GEOD-14318 | biostudies-arrayexpress
Project description:Mice were exposed to 2.5% DSS (MW 36,000–50,000, MP Biomedicals) prepared in autoclaved drinking water for five days, after which they were provided DSS-free drinking water for 13 days. On day 12, 16.7% of mice (20 of 120) whose body weight returned to the same level as on day 1 (the change of body weight was less than 0.5 g) and exhibited an DAI of 0 or 1.00, were used as “well-recovered” mice. To identify which fecal miRNAs were affected during DSS-induced colitis and the recovery phase, we performed small RNA sequencing in feces obtained from well-recovered mice on days 0, 5, and 12 of the treatment regimen.
2021-01-28 | GSE165648 | GEO
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.
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Project description:Pseudomonas aeruginosa is a common bacterium in the terminal plumbing system of buildings and it is from this niche that a substantial fraction of infections are acquired. To better understand P. aeruginosa biology in this environment, we examined the transcriptomes in tap water and pond water.
2017-10-24 | GSE104819 | GEO
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
Project description:We investigated the specific interactions of the most dominant bacterial CF-pathogen, Pseudomonas aeruginosa, and the anaerobic bacterium Veilllonella parvula, that has been recovered at comparable cell numbers in the respiratory tract of CF patients. We used our recently established in-vivo murine tumor model to investigate mutual influences of the two pathogens during a biofilm-associated infection process. We found that although P. aeruginosa and V. parvula colonized distinct niches within the tumor, in mice that were co-infected with both bacterial species significant higher cell numbers of P. aeruginosa were recovered from the tumor tissue. Concordantly, in vivo transcriptional profiling implied that the presence of V. parvula supports P. aeruginosa growth at the infected host site, and the higher P. aeruginosa load correlated with clinical deterioration.
2014-11-06 | GSE58388 | GEO