Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Validated transcriptional regulatory roles for five two-component systems in E. coli (RNA-seq dataset)

ABSTRACT: Escherichia coli use two-component systems (TCSs) to respond to environmental signals. TCSs affect gene expression and are parts of E. coli’s global transcriptional regulatory network (TRN). Here, we identified the regulons of five TCSs in E. coli MG1655: BaeSR and CpxAR, which were stimulated by ethanol stress, and KdpDE, PhoRB, and ZraSR, which were stimulated by potassium, phosphate, and zinc, respectively. We analyzed RNA-seq data using independent component analysis (ICA). ChIP-exo data was used to validate condition-specific target gene binding sites. Based on this data we (1) identify the target genes for each TCS; (2) show how the target genes are transcribed in response to stimulus; and (3) reveal novel relationships between TCSs, which indicate non-cognate inducers for various response regulators, such as BaeR to iron starvation, CpxR to phosphate limitation, and PhoB and ZraR to cell envelope stress. Our understanding of the TRN in E. coli is thus notably expanded.

ORGANISM(S): Escherichia coli str. K-12 substr. MG1655

PROVIDER: GSE143855 | GEO | 2020/10/21

REPOSITORIES: GEO

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

Validated transcriptional regulatory roles for five two-component systems in E. coli (ChIP-exo dataset)

Project description:Escherichia coli use two-component systems (TCSs) to respond to environmental signals. TCSs affect gene expression and are parts of E. coli’s global transcriptional regulatory network (TRN). Here, we identified the regulons of five TCSs in E. coli MG1655: BaeSR and CpxAR, which were stimulated by ethanol stress, and KdpDE, PhoRB, and ZraSR, which were stimulated by potassium, phosphate, and zinc, respectively. We analyzed RNA-seq data using independent component analysis (ICA). ChIP-exo data was used to validate condition-specific target gene binding sites. Based on this data we (1) identify the target genes for each TCS; (2) show how the target genes are transcribed in response to stimulus; and (3) reveal novel relationships between TCSs, which indicate non-cognate inducers for various response regulators, such as BaeR to iron starvation, CpxR to phosphate limitation, and PhoB and ZraR to cell envelope stress. Our understanding of the TRN in E. coli is thus notably expanded.

2020-10-21 | GSE143851 | GEO

Assessing the effects of four two-component system response regulator knockouts in E. coli

Project description:Escherichia coli use two-component systems (TCSs) to respond to environmental signals. TCSs affect gene expression and are parts of E. coli’s global transcriptional regulatory network (TRN). Here, we profiled the effects of knockout of 4 TCS regulators: atoC, btsR, cusR, and rcsB. These knockouts were grown in the presence of their typical effector molecules to enable comparison to the intact response of the WT system (K-12 MG1655).

2023-02-12 | GSE225096 | GEO

ChIP-exo analysis reveals novel uncharacterized transcription factors involved in the diverse regulatory functions of Escherichia coli

Project description:Bacteria regulate gene expression to adapt to changing environments through transcriptional regulatory networks (TRNs). Although extensively studied, TRNs are not fully characterized since the identity of all the transcriptional regulators that comprise a TRN are not known. Here, we experimentally evaluate 40 uncharacterized proteins in the model organism Escherichia coli K-12 MG1655, which were previously predicted to be transcription factors (TFs). First, we used myc-tagging and a multiplexed ChIP-exo assay to characterize genome-wide binding sites for these candidate TFs. We then compared those binding sites with those of RNA polymerase and sigma factors to increase the confidence in the measured DNA-binding events. Finally, we used these data to infer potential functional annotations for 13 candidate TFs. Our results revealed that these candidate TFs have a varied number of regulatory genes and are involved in E. coli’s primary cellular processes. Taken together, thes results: (1) expand the number of confirmed TFs from 249 to 276, close to the estimated total of 280 TFs in E. coli K-12 MG1655; (2) provide a roadmap for the functional characterization of the newly discovered TFs; and (3) enable the elucidation of the first comprehensive TRN in this model organism.

2021-08-17 | GSE159777 | GEO

Expression Profiling of Avian Pathogenic E. coli WT and mutant

Project description:RNA-Seq was performed on Avian pathogenic E. coli (APEC) WT and mutant to investigate the pathogenicity of ArcA (Aerobic Respiratory Control), a global regulator important for E. coli’s adaptation from anaerobic to aerobic conditions and control of that bacterium’s enzymatic defenses against ROS.

2017-03-01 | E-MTAB-3396 | biostudies-arrayexpress

Intrinsic cardiac adrenergic (ICA) cells contribute to LPS-induced myocardial dysfunction

Project description:The role of ICA cells in septic cardiomyopathy is unknown. Here we show that norepinephrine (NE) secretion from ICA cells is increased through activation of Toll-like receptor 4 (TLR4) to aggravate myocardial TNF-α production and dysfunction by lipopolysaccharide (LPS). In ICA cells, LPS activated TLR4-MyD88/TRIF-AP-1 signaling that promoted NE biosynthesis through expression of tyrosine hydroxylase, but did not trigger TNF-α production due to impairment of p65 translocation. Our findings suggest that ICA cells may be a potential therapeutic target for septic cardiomyopathy.

2022-02-02 | GSE189964 | GEO

Escherichia coli strain:KdpDE

Project description:Escherichia coli strain:KdpDE Raw sequence reads

| PRJNA485009 | ENA

Effect of different Two-component systems system deletion in S. aureus NCTC8325

Project description:To analyze function of three Two-component systems SAOUHSC_00184-185, SAOUHSC_01313-1314, and SAOUHSC_01980-1981, we have employed whole genome microarray expression profiling to identify genes transcription changed in respective mutant strains. Target TCSs were replaced by ermB gene. Cells were grown to OD600=2.0, and the RNA level of wild type NCTC8325 and three TCSs mutant were compared.

2013-09-30 | E-GEOD-51197 | biostudies-arrayexpress

ChIP-seq and RNA-seq for TCSs in Pseudomonas syringae

Project description:Bacteria relies on two-component systems (TCSs) to respond to a wide range of stimuli or environmental cues for their survival and virulence. However, the functions and synergistic actions of TCSs in genomic level remains unclear. Here, in model phytopathogen Pseudomonas syringae, by integrating multiomics data, we developed a network-based PSTCSome (Pseudomonas syringae two-component systems regulome) to identify functions and crosstalk among global TCSs under either virulence suppressing (King’s B medium, KB) or activating conditions (minimal medium, MM). Transcriptome profiling identifies 2,099 differentially expressed genes (DEGs) in KB and 1,250 DEGs in MM, while ChIP-seq identifies 1,628 target genes across the whole genome. The multiomics results are applied to perform not only gene ontology (GO) analysis to detect the biological processes that TCSs involved in, but also subnetworks and co-expression analysis of 8 virulence-related pathways to decipher the TCSs regulated pathogenic behaviors. The following phenotypic experiments newly confirmed 8 TCSs that regulates type III secretion system (T3SS) (PSPPH_0253, PSPPH_2606, PSPPH_4416, and PSPPH_4451) and surface attachment (PSPPH_0253, PSPPH_3041, PSPPH_3473, PSPPH_3736, PSPPH_4001). We then compute 259 functional genes in KB and 161 in MM for those cluster TCSs. Analysis of cluster TCSs regulons led to the identification of either novel functions or 2 master regulatory TCSs (RhpS/RhpR and PSPPH_4827/4828) toward virulence. Our results show that TCSs in P. syringae dynamically adjust their regulatory networks by sensing the external environment, and then switch bacteria between pathogenic and non-pathogenic states in a sophisticated way. Furthermore, we present an online platform of PSTCSome to facilitate updating, network visualization and user-customized analyses.

2022-10-04 | GSE148104 | GEO

Vibrio cholerae N16961 overexpression of CpxR

Project description:Transcriptionnal profiling comparing a V. Choleare ∆cpxR mutant harboring either (pBAD33-cpxR) or empty (pBAD33) grown for 1h under inducing conditions.

2014-05-03 | GSE54081 | GEO

A Genome Scale Transcriptional Regulatory Model of the Human Placenta

Project description:Gene regulation is essential to placental function and fetal development. We built a genome-scale transcriptional regulatory network (TRN) of the human placenta using digital genomic footprinting and transcriptomic data. We integrated 475 transcriptomes and 12 DNase hypersensitivity datasets from placental samples to globally and quantitatively map transcription factor (TF)-target gene interactions. We performed siRNA knockdowns of 4 TFs and achieved concordance between the predicted gene targets in our TRN.

2024-07-03 | GSE245395 | GEO

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data