Pseudomonas aeruginosa
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA1154445 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR30500523_1.fastq.gz | Fastqsanger.gz | |||
| SRR30500523_2.fastq.gz | Fastqsanger.gz | |||
| SRR30500524_1.fastq.gz | Fastqsanger.gz | |||
| SRR30500524_2.fastq.gz | Fastqsanger.gz | |||
| SRR30500525_1.fastq.gz | Fastqsanger.gz |
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Project description:Gene expression profiles of two Pseudomonas aeruginosa taxonomic outlier clinical isolates, CLJ1 and CLJ3 [CLJ3] Pseudomonas aeruginosa taxonomic outliers emerged recently as infectious for humans, provoking hemorrhagic pneumonia. Those bacteria lack classical type III secretion system, and utilize the pore-forming toxin for infection. Two clones CLJ1 and CLJ3 belonging to these taxonomic outliers have been isolated from the same patient at two different times during hospitalization. P. aeruginosa CLJ3 displays antibiotic resistance phenotype, while CLJ1 is more cytotoxic on epithelial and endothelial cells.
2018-11-30 | GSE123107 | GEO
Project description:Gene expression profiles of two Pseudomonas aeruginosa taxonomic outlier clinical isolates, CLJ1 and CLJ3 [CLJ1] Pseudomonas aeruginosa taxonomic outliers emerged recently as infectious for humans, provoking hemorrhagic pneumonia. Those bacteria lack classical type III secretion system, and utilize the pore-forming toxin for infection. Two clones CLJ1 and CLJ3 belonging to these taxonomic outliers have been isolated from the same patient at two different times during hospitalization. P. aeruginosa CLJ3 displays antibiotic resistance phenotype, while CLJ1 is more cytotoxic on epithelial and endothelial cells.
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Project description:Pseudomonas aeruginosa undergoes genetic change during chronic infection of the airways of cystic fibrosis (CF) patients. One common change is mutation of lasR. LasR is a transcriptional regulator that responds to one of the quorum sensing signals in P. aeruginosa, and regulates acute virulence factor expression as well as central metabolic functions. P. aeruginosa mutants in which lasR was inactivated emerged in the airways of CF patients early during chronic infection, and during growth in the laboratory on Luria-Bertani agar. Both environments are rich in amino acids. Inactivation of lasR in these isolates conferred a growth advantage with amino acids, a phenotype that could account for selection of lasR mutants both in vivo and in vitro. P. aeruginosa lasR mutants were identified by their distinctive colony morphology, including autolysis that correlated with an imbalance in 4-hydroxy-2-alkylquinolines (HAQs), and an iridescent metallic sheen likely caused by the accumulation of one such HAQ. The alterations in transcriptional profile due to inactivation of lasR were conserved in isolates from multiple young CF patients. P. aeruginosa lasR mutations may represent surrogate markers to delineate stages in the natural history of CF airway disease, each with different prognostic and therapeutic implications, analogous to the markers used to direct cancer treatment. Similar to cancer cell mutations that promote unrestricted growth, lasR mutations may promote unrestricted growth of P. aeruginosa in the CF airway by enabling more efficient utilization of available amino acids. Analyse the effects of mutation of the lasR gene in Pseudomonas aeruginosa isolates from cystic fibrosis patients by comparing the transcriptional profile of an isolate from a young patient with that of an isogenic engineered lasR mutant.
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Project description:Pseudomonas aeruginosa (P. aeruginosa) lung infection is a significant cause of mortality in patients with cystic fibrosis (CF). Most CF patients acquire unique P. aeruginosa strains from the environment; however clonal strains have been identified in CF communities in several countries. Two clonal strains infect 10% to 40% of patients in three CF clinics in mainland eastern Australia. The expression profiles of four planktonically-grown isolates of one Australian clonal strain (AES-2), and four non–clonal CF P. aeruginosa isolates were compared to each other and to the reference strain PAO1 using the Affymetrix P. aeruginosa PAO1 genome array, to gain insight into properties mediating the enhanced infectivity of AES-1. The isolates were subsequently grown as 3-day old biofilms and similarly extracted for RNA and compared as above. Data analysis was carried out using BIOCONDUCTOR software. Keywords: Comparative strain hybridization
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Project description:Pseudomonas aeruginosa undergoes genetic change during chronic infection of the airways of cystic fibrosis (CF) patients. One common change is mutation of lasR. LasR is a transcriptional regulator that responds to one of the quorum sensing signals in P. aeruginosa, and regulates acute virulence factor expression as well as central metabolic functions. P. aeruginosa mutants in which lasR was inactivated emerged in the airways of CF patients early during chronic infection, and during growth in the laboratory on Luria-Bertani agar. Both environments are rich in amino acids. Inactivation of lasR in these isolates conferred a growth advantage with amino acids, a phenotype that could account for selection of lasR mutants both in vivo and in vitro. P. aeruginosa lasR mutants were identified by their distinctive colony morphology, including autolysis that correlated with an imbalance in 4-hydroxy-2-alkylquinolines (HAQs), and an iridescent metallic sheen likely caused by the accumulation of one such HAQ. The alterations in transcriptional profile due to inactivation of lasR were conserved in isolates from multiple young CF patients. P. aeruginosa lasR mutations may represent surrogate markers to delineate stages in the natural history of CF airway disease, each with different prognostic and therapeutic implications, analogous to the markers used to direct cancer treatment. Similar to cancer cell mutations that promote unrestricted growth, lasR mutations may promote unrestricted growth of P. aeruginosa in the CF airway by enabling more efficient utilization of available amino acids. Keywords: disease state analysis
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