GEO DataSets

(Submitter supplied) Previously unpublished expression data from E. coli K-12 MG1655 involved in the creation of a large RNAseq database.

Organism:

Escherichia coli str. K-12 substr. MG1655; Escherichia coli BW25113

Type:

Expression profiling by high throughput sequencing

4 related Platforms

12 Samples

Download data: CSV

(Submitter supplied) ChIPexo experiment was performed on E. coli K12 MG1655 with various supplements designed to activate transcriptional regulators

Organism:

Escherichia coli K-12

Type:

Genome binding/occupancy profiling by high throughput sequencing

Platform:

GPL24377

4 Samples

Download data: GFF

(Submitter supplied) RNA sequencing was performed on multiple E. coli strains grown on glucose minimal media

Organism:

Escherichia coli

Type:

Expression profiling by high throughput sequencing

Platform:

GPL16085

14 Samples

Download data: CSV

(Submitter supplied) RNA sequencing was performed on E. coli K12 MG1655 with various supplements designed to activate transcriptional regulators

Organism:

Escherichia coli

Type:

Expression profiling by high throughput sequencing

Platform:

GPL21433

30 Samples

Download data: CSV

(Submitter supplied) Wild-type E. coli are prototrophic for all amino acid and nucleotides. These are synthesized by a network of interconnected metabolic pathways from a handful precursors molecules, which are regulated at the level of gene expression. It was hypothesized in this study, that since metabolic pathways are interconnected, transcriptional regulation should be shared across multiple pathways. To uncover these regulatory interactions, cells growing at steady state were perturbed by the addition of an end-metabolite (aa or nt), and were allowed to recover. more...

Organism:

Escherichia coli str. K-12 substr. MG1655; Escherichia coli

Type:

Expression profiling by array

Platform:

GPL3503

22 Samples

Download data: GPR

(Submitter supplied) Cellular metabolism controls gene expression through allosteric interactions between metabolites and transcription factors. Methods to detect these regulatory interactions are mostly based on in vitro binding assays, but there are no methods to identify them at a genome-scale in vivo. Here we show that dynamic transcriptome and metabolome data identify metabolites that are potential effectors of transcription factors in E. more...

Organism:

Escherichia coli

Type:

Expression profiling by high throughput sequencing

Platform:

GPL26155

56 Samples

Download data: CSV

(Submitter supplied) In a given bacterial population, antibiotic treatment kills a large portion of the population, while a small, tolerant subpopulation survives. Tolerant cells disrupt the efficacy of antibiotic treatment and increase the likelihood that a population gains antibiotic resistance. Antibiotic tolerance is different from resistance because tolerant cells cannot grow and replicate in the presence of the antibiotic, but when the antibiotic is removed, they begin to propagate. more...

Organism:

Escherichia coli

Type:

Expression profiling by high throughput sequencing

Platform:

GPL14548

18 Samples

Download data: CSV

(Submitter supplied) This SuperSeries is composed of the SubSeries listed below.

Organism:

Escherichia coli str. K-12 substr. MG1655

Type:

Expression profiling by high throughput sequencing; Other

Platform:

GPL15010

50 Samples

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(Submitter supplied) Analysis of the contribution of the post-transcriptional regulator CsrA to translation during exponential growth in Escherichia coli

Organism:

Escherichia coli str. K-12 substr. MG1655

Type:

Expression profiling by high throughput sequencing; Other

Platform:

GPL15010

20 Samples

Download data: CSV

(Submitter supplied) Analysis of the contribution of the post-transcriptional regulator CsrA to RNA stability during exponential growth in Escherichia coli

Organism:

Escherichia coli str. K-12 substr. MG1655

Type:

Expression profiling by high throughput sequencing

Platform:

GPL15010

20 Samples

Download data: CSV

(Submitter supplied) Analysis of RNA binding partners of the post-transcriptional regulator CsrA to translation during exponential growth in Escherichia coli

Organism:

Escherichia coli str. K-12 substr. MG1655

Type:

Other

Platform:

GPL15010

10 Samples

Download data: CSV

(Submitter supplied) This dataset is a part of putidaPRECISE321, which was utilized to unveil the trnascriptional regulatory network of Pseudomonas putida KT244. Bacterial gene expression is orchestrated by numerous transcription factors (TFs). Elucidating how gene expression is regulated is fundamental to understanding bacterial physiology and engineering it for practical use. In this study, a machine-learning approach was applied to uncover the genome-scale transcriptional regulatory network (TRN) in Pseudomonas putida, an important organism for bioproduction. more...

Organism:

Pseudomonas putida KT2440

Type:

Expression profiling by high throughput sequencing

Platform:

GPL28478

81 Samples

Download data: CSV

(Submitter supplied) Bacterial gene expression is orchestrated by numerous transcription factors (TFs). Elucidating how gene expression is regulated is fundamental to understanding bacterial physiology and engineering it for practical use. In this study, a machine-learning approach was applied to uncover the genome-scale transcriptional regulatory network (TRN) in Pseudomonas putida, an important organism for bioproduction. more...

Organism:

Pseudomonas putida KT2440

Type:

Expression profiling by high throughput sequencing

Platforms:

GPL28478 GPL28971

22 Samples

Download data: CSV

(Submitter supplied) Cellular tolerance toward ethanol is a complex phenotype involved many genes, and hard to be improved by manipulating individual genes. We previously established exogenous global regulator IrrE mutants that confer Escherichia coli with significantly enhanced tolerance to stresses, including ethanol. In order to elucidate the mechanism for enhancement of ethanol tolerance in the mutants and to identify new genes and pathways that can be possible targets for engineering of ethanol tolerance, we carried out comparative transcriptomic and proteomic analyses with the representative strains E1 and E0 (harboring the ethanol-tolerant mutant E1 of IrrE and the wild type IrrE, respectively). more...

Organism:

Escherichia coli

Type:

Expression profiling by array

Platform:

GPL3154

6 Samples

Download data: CEL

(Submitter supplied) This SuperSeries is composed of the SubSeries listed below.

Organism:

Escherichia coli str. K-12 substr. MG1655; Escherichia coli

Type:

Genome binding/occupancy profiling by high throughput sequencing; Expression profiling by high throughput sequencing

Platforms:

GPL17439 GPL16085

16 Samples

Download data: GFF

(Submitter supplied) The response to acid stress is a fundamental process in bacteria. Three transcription factors, GadE, GadW, and GadX (GadEWX) are known to play a critical role in the transcriptional regulation of glutamate-dependent acid resistance (GDAR) system in Escherichia coli K-12 MG1655. However, the regulatory role of GadEWX in coordinating interacting cellular functions is still unknown. Here, we comprehensively reconstruct genome-wide GadEWX transcriptional regulatory network in E. more...

Organism:

Escherichia coli

Type:

Expression profiling by high throughput sequencing

Platform:

GPL16085

8 Samples

Download data: CSV

(Submitter supplied) The response to acid stress is a fundamental process in bacteria. Three transcription factors, GadE, GadW, and GadX (GadEWX) are known to play a critical role in the transcriptional regulation of glutamate-dependent acid resistance (GDAR) system in Escherichia coli K-12 MG1655. However, the regulatory role of GadEWX in coordinating interacting cellular functions is still unknown. Here, we comprehensively reconstruct genome-wide GadEWX transcriptional regulatory network in E. more...

Organism:

Escherichia coli str. K-12 substr. MG1655

Type:

Genome binding/occupancy profiling by high throughput sequencing

Platform:

GPL17439

8 Samples

Download data: GFF

(Submitter supplied) Machine learning approaches offer the potential to systematically identify transcriptional regulatory interactions from a compendium of microarray expression profiles. However, experimental validation of the performance of these methods at the genome scale has remained elusive. Here we assess the global performance of four existing classes of inference algorithms using 445 Escherichia coli Affymetrix arrays and 3,216 known E. more...

Organism:

Escherichia coli; Escherichia coli K-12

Type:

Expression profiling by array

Platform:

GPL199

266 Samples

Download data: CEL

(Submitter supplied) Triclosan is a biocidal active agent commonly found in domestic cleaning products, hand sanitizers, cosmetics and personal care products. It is used to control microbial contamination and has a broad-spectrum of activity against many Gram-positive and Gram-negative bacteria. The development of triclosan tolerance with potential cross resistance to clinically relevant antibiotics in zoonotic pathogens is of concern given the widespread use of this active agent in clinical, food processing and domestic environments. more...

Organism:

Escherichia coli; Escherichia coli O157

Type:

Expression profiling by array

Platform:

GPL3154

12 Samples

Download data: CEL

(Submitter supplied) The experiment is a time course for the aerobic to anaerobic switch response in E. coli. The data was used to validate the utility of a set of predicted transcription factor gene interactions for modeling the dynamic regulatory response networks of this response. The transcription factor gene interaction predictions were generated by a semi-supervised classification method that takes advantage of a separate compendium of gene expression and a data set of curated interactions. more...

Organism:

Escherichia coli

Type:

Expression profiling by array

Platforms:

GPL5435 GPL5436

11 Samples

Download data: XLS