Browse
Submit Data
Databases
API
Help

Dataset Information

30 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Unraveling the functions of uncharacterized transcription factors in Escherichia coli using ChIP-exo.

ABSTRACT: Bacteria regulate gene expression to adapt to changing environments through transcriptional regulatory networks (TRNs). Although extensively studied, no TRN is fully characterized since the identity and activity of all the transcriptional regulators comprising a TRN are not known. Here, we experimentally evaluate 40 uncharacterized proteins in Escherichia coli K-12 MG1655, which were computationally predicted to be transcription factors (TFs). First, we used a multiplexed chromatin immunoprecipitation method combined with lambda exonuclease digestion (multiplexed ChIP-exo) assay to characterize binding sites for these candidate TFs; 34 of them were found to be DNA-binding proteins. We then compared the relative location between binding sites and RNA polymerase (RNAP). We found 48% (283/588) overlap between the TFs and RNAP. Finally, we used these data to infer potential functions for 10 of the 34 TFs with validated DNA binding sites and consensus binding motifs. Taken together, this study: (i) significantly expands the number of confirmed TFs to 276, close to the estimated total of about 280 TFs; (ii) provides putative functions for the newly discovered TFs and (iii) confirms the functions of four representative TFs through mutant phenotypes.

SUBMITTER: Gao Y

PROVIDER: S-EPMC8464067 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Similar Datasets

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

Systematic discovery of uncharacterized transcription factors in Escherichia coli K-12 MG1655 (ChIP-exo data set)

Project description:Transcriptional regulation enables cells to respond to environmental changes. Yet, among the estimated 304 candidate transcription factors (TFs) in Escherichia coli K-12 MG1655, only 185 have been experimentally characterized. Here we developed an integrated workflow that contains the prediction of TFs using machine learning and comprehensive experimental validation using a suite of genome-wide experiments. Applying this workflow we: 1) computationally identified 16 candidate genes encoding uncharacterized TFs; 2) confirmed that ten of these 16 are TF candidates that showed 255 DNA binding sites; 3) found high-confidence TF-binding sequence motifs for six of the ten TFs; 4) reconstructed the regulons of the ten TFs by determining gene expression change upon deletion of each TF; and 5) further determined the regulatory roles of three TFs (YdcI, YeiE and YiaJ) to be regulating acetate metabolism, iron homeostasis under iron limited condition, and utilization of L-ascorbate, respectively. Together, these results demonstrate how the integrated workflow can be used to discover, characterize, and elucidate regulatory functions of uncharacterized TFs. This workflow can be applied to less studied bacteria for systematic discovery and characterization of their transcriptional regulatory networks.

2018-08-08 | GSE111093 | GEO

Systematic discovery of uncharacterized transcription factors in Escherichia coli K-12 MG1655.

Project description:Transcriptional regulation enables cells to respond to environmental changes. Of the estimated 304 candidate transcription factors (TFs) in Escherichia coli K-12 MG1655, 185 have been experimentally identified, but ChIP methods have been used to fully characterize only a few dozen. Identifying these remaining TFs is key to improving our knowledge of the E. coli transcriptional regulatory network (TRN). Here, we developed an integrated workflow for the computational prediction and comprehensive experimental validation of TFs using a suite of genome-wide experiments. We applied this workflow to (i) identify 16 candidate TFs from over a hundred uncharacterized genes; (ii) capture a total of 255 DNA binding peaks for ten candidate TFs resulting in six high-confidence binding motifs; (iii) reconstruct the regulons of these ten TFs by determining gene expression changes upon deletion of each TF and (iv) identify the regulatory roles of three TFs (YiaJ, YdcI, and YeiE) as regulators of l-ascorbate utilization, proton transfer and acetate metabolism, and iron homeostasis under iron-limited conditions, respectively. Together, these results demonstrate how this workflow can be used to discover, characterize, and elucidate regulatory functions of uncharacterized TFs in parallel.

| S-EPMC6237786 | biostudies-literature

Systematic discovery of uncharacterized transcription factors in Escherichia coli K-12 MG1655

Project description:This SuperSeries is composed of the SubSeries listed below.

2018-08-08 | GSE111095 | GEO

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

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

| PRJNA670504 | ENA

Systematic identification and characterization of uncharacterized transcription factors in Escherichia coli K-12 MG1655

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 we do not know the identity of all the transcriptional regulators that comprise a TRN. Here, we experimentally evaluate 40 uncharacterized proteins in the model organisms 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 the 40 candidate TFs. Then, we 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 annotation for 13 candidate TFs. As a result, we characterized 570 new binding sites for 34 of 40 candidate TFs. Taken together, the study; 1) expands the number of confirmed TFs from 249 to 278, that is close to the estimated total of about 280 TFs in E. coli K-12 MG1655, 2) it provides a roadmap for functional characterization of the 34 discovered TFs, and 3) it enables the elucidation of the first comprehensive TRN.

2021-08-26 | GSE159658 | GEO

ChEAP: ChIP-exo analysis pipeline and the investigation of Escherichia coli RpoN protein-DNA interactions.

Project description:Genome-scale studies of the bacterial regulatory network have been leveraged by declining sequencing cost and advances in ChIP (chromatin immunoprecipitation) methods. Of which, ChIP-exo has proven competent with its near-single base-pair resolution. While several algorithms and programs have been developed for different analytical steps in ChIP-exo data processing, there is a lack of effort in incorporating them into a convenient bioinformatics pipeline that is intuitive and publicly available. In this paper, we developed ChIP-exo Analysis Pipeline (ChEAP) that executes the one-step process, starting from trimming and aligning raw sequencing reads to visualization of ChIP-exo results. The pipeline was implemented on the interactive web-based Python development environment - Jupyter Notebook, which is compatible with the Google Colab cloud platform to facilitate the sharing of codes and collaboration among researchers. Additionally, users could exploit the free GPU and CPU resources allocated by Colab to carry out computing tasks regardless of the performance of their local machines. The utility of ChEAP was demonstrated with the ChIP-exo datasets of RpoN sigma factor in E. coli K-12 MG1655. To analyze two raw data files, ChEAP runtime was 2 min and 25 s. Subsequent analyses identified 113 RpoN binding sites showing a conserved RpoN binding pattern in the motif search. ChEAP application in ChIP-exo data analysis is extensive and flexible for the parallel processing of data from various organisms.

| S-EPMC9735260 | biostudies-literature

Systematic discovery of uncharacterized transcription factors in Escherichia coli K-12 MG1655 (RNA-seq data set)

2018-08-08 | GSE111094 | GEO

In vivo probing of promoter overlapping between σ-factors in Escherichia coli (ChIP-exo)

Project description:An alternative sigma factor (σ32) recognizes the unique set of promoters upon heat shock. Here, we determined 54 σ32 promoters at nucleotide resolution using ChIP-exo, enabling us to compare those with housekeeping σ70 promoters. The results elucidated the overarching principles of promoter overlapping between the two σ-factors, which are sequence-specific non-, half-, and full-shared modes with a perfect sequence conservativeness of −35 element as a key determinant of full-shared mode.

2020-08-12 | GSE60667 | GEO

Systematic discovery of uncharacterized transcription factors in Escherichia coli K-12 MG1655 (ChIP-exo data set)

Project description:Systematic discovery of uncharacterized transcription factors in Escherichia coli K-12 MG1655 (ChIP-exo data set)

| PRJNA435925 | ENA