Filters
Technology
Platform
GSE51594
Homo sapiens
6 Downloadable Samples
Affymetrix Human Genome U133A Array (hgu133a)
Description
We compared gene expression profiles of a human CD4+ T-cell line 24 h after infection with a cell line of the same origin permanently releasing SIVmac251/32H. A new knowledge-based-network approach (Inter-Chain-Finder) was used to identify subnetworks leading to resistance to SIV-induced cell death. Notably, the method can identify not only differentially-expressed key hub genes but also non-differentially expressed, critical, hidden regulators.
Publication Title
Identification of molecular sub-networks associated with cell survival in a chronically SIVmac-infected human CD4+ T cell line.
Sample Metadata Fields
Disease, Disease stage
View Samples- Saccharomyces cerevisiae
- 13 Downloadable Samples
- Affymetrix Yeast Genome 2.0 Array (yeast2)
Description
Resistance of Saccharomyces cerevisiae to high furfural concentration is based on NADPH-dependent reduction by at least two oxireductases.
Publication Title
Resistance of Saccharomyces cerevisiae to high concentrations of furfural is based on NADPH-dependent reduction by at least two oxireductases.
Sample Metadata Fields
No sample metadata fields
View Samples- Pseudomonas aeruginosa
- 6 Downloadable Samples
- Affymetrix Pseudomonas aeruginosa Array (paeg1a)
Description
Biofilms are surface-adhered bacterial communities encased in an extracellular matrix composed of polysaccharides, proteins, and extracelluar (e)DNA, with eDNA being required for the formation and integrity of biofilms. Here we demonstrate that the spatial and temporal release of eDNA is regulated by BfmR, a regulator essential for Pseudomonas aeruginosa biofilm development. The expression of bfmR coincided with localized cell death and DNA release, with high eDNA concentrations localized to the outer part of microcolonies in the form of a ring and as a cap on small clusters. Additionally, eDNA release and cell lysis increased significantly following bfmR inactivation. Genome-wide transcriptional profiling indicated that bfmR was required for repression of genes associated with bacteriophage assembly and bacteriophage-mediated lysis. In order to determine which of these genes were directly regulated by BfmR, we utilized chromatin immunoprecipitation (ChIP) analysis to identify the promoter of PA0691, termed here phdA, encoding a previously undescribed homologue of the prevent-host-death (Phd) family of proteins. Lack of phdA expression coincided with impaired biofilm development, increased cell death and bacteriophage release, a phenotype comparable to bfmR. Expression of phdA in bfmR biofilms restored eDNA release, cell lysis, release of bacteriophages, and biofilm formation to wild type levels. Moreover, overexpression of phdA rendered P. aeruginosa resistant to lysis mediated by superinfective bacteriophage Pf4 which was only detected in biofilms. The expression of bfmR was stimulated by conditions resulting in membrane perturbation and cell lysis. Thus, we propose that BfmR regulates biofilm development by controlling bacteriophage-mediated lysis and thus, cell death and eDNA release, via PhdA.
Publication Title
The novel Pseudomonas aeruginosa two-component regulator BfmR controls bacteriophage-mediated lysis and DNA release during biofilm development through PhdA.
Sample Metadata Fields
No sample metadata fields
View Samples- Pseudomonas aeruginosa
- 6 Downloadable Samples
- Affymetrix Pseudomonas aeruginosa Array (paeg1a)
Description
A hallmark of the biofilm architecture is the presence of microcolonies. However, little is known about the underlying mechanisms governing microcolony formation. In the human pathogen Pseudomonas aeruginosa, microcolony formation is dependent on the two-component regulator MifR, with mifR mutant biofilms exhibiting an overall thin structure lacking microcolonies, and overexpression of mifR resulting in hyper-microcolony formation. Here, we made use of the distinct MifR-dependent phenotypes to elucidate mechanisms associated with microcolony formation. Using global transcriptomic and proteomic approaches, we demonstrate that cells located within microcolonies experience stressful, oxygen limited, and energy starving conditions, as indicated by the activation of stress response mechanisms and anaerobic and fermentative processes, in particular pyruvate fermentation. Inactivation of genes involved in pyruvate utilization including uspK, acnA and ldhA abrogated microcolony formation in a manner similar to mifR inactivation. Moreover, depletion of pyruvate from the growth medium impaired biofilm and microcolony formation, while addition of pyruvate significantly increased microcolony formation. Addition of pyruvate partly restored microcolony formation in mifR biofilms. Moreover, addition of pyruvate to or expression of mifR in lactate dehydrogenase (ldhA) mutant biofilms did not restore microcolony formation. Consistent with the finding of denitrification genes not demonstrating distinct expression patterns in biofilms forming or lacking microcolonies, addition of nitrate did not alter microcolony formation. Our findings indicate the fermentative utilization of pyruvate to be a microcolony-specific adaptation to the oxygen limitation and energy starvation of the P. aeruginosa biofilm environment.
Publication Title
Microcolony formation by the opportunistic pathogen Pseudomonas aeruginosa requires pyruvate and pyruvate fermentation.
Sample Metadata Fields
No sample metadata fields
View Samples- Saccharomyces cerevisiae
- 23 Downloadable Samples
- Affymetrix Yeast Genome 2.0 Array (yeast2)
Description
This SuperSeries is composed of the SubSeries listed below.
Publication Title
Unraveling condition-dependent networks of transcription factors that control metabolic pathway activity in yeast.
Sample Metadata Fields
No sample metadata fields
View Samples- Saccharomyces cerevisiae
- 6 Downloadable Samples
- Affymetrix Yeast Genome 2.0 Array (yeast2)
Description
Expression data from wild-type FY4 and GCR2 deletion strain. Impact of the transcription factor Gcr2p on mRNA expression was investigated in the corresponding deletion strain in exponentially growing glucose minimal medium batch cultures.
Publication Title
Unraveling condition-dependent networks of transcription factors that control metabolic pathway activity in yeast.
Sample Metadata Fields
No sample metadata fields
View Samples- Saccharomyces cerevisiae
- 6 Downloadable Samples
- Affymetrix Yeast Genome 2.0 Array (yeast2)
Description
The impact on mRNA expression of the transcription factors Bas1, Pho2, Gcn4 and Gcr2p was investigated in the corresponding deletion strains during exponential growth in glucose minimal media batch cultures.
Publication Title
Unraveling condition-dependent networks of transcription factors that control metabolic pathway activity in yeast.
Sample Metadata Fields
No sample metadata fields
View Samples- Saccharomyces cerevisiae
- 6 Downloadable Samples
- Affymetrix Yeast Genome 2.0 Array (yeast2)
Description
The impact on mRNA expression of the transcription factors Bas1, Pho2, Gcn4 and Gcr2p was investigated in the corresponding deletion strains during exponential growth in glucose minimal media batch cultures.
Publication Title
Unraveling condition-dependent networks of transcription factors that control metabolic pathway activity in yeast.
Sample Metadata Fields
No sample metadata fields
View Samples- Saccharomyces cerevisiae
- 5 Downloadable Samples
- Affymetrix Yeast Genome 2.0 Array (yeast2)
Description
The impact on mRNA expression of the transcription factors Bas1, Pho2, Gcn4 and Gcr2p was investigated in the corresponding deletion strains during exponential growth in glucose minimal media batch cultures.
Publication Title
Unraveling condition-dependent networks of transcription factors that control metabolic pathway activity in yeast.
Sample Metadata Fields
No sample metadata fields
View Samples- Mus musculus
- 38 Downloadable Samples
- Illumina MouseWG-6 v2.0 expression beadchip
Description
This SuperSeries is composed of the SubSeries listed below.
Publication Title
Protein sets define disease states and predict in vivo effects of drug treatment.
Sample Metadata Fields
Sex, Age, Specimen part
View Samples