Escherichia coli
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA338159 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:ChIP-exo/nexus experiments present modifications on the commonly used ChIP-seq protocol for high resolution mapping of transcription factor binding sites. Although many aspects of the ChIP-exo data analysis are similar to those of ChIP-seq, these high throughput experiments pose a number of unique quality control and analysis challenges. We develop a statistical quality control pipeline and accompanying R package, ChIPexoQual, to enable exploration and analysis of ChIP-exo and related experiments. ChIPexoQual evaluates a number of key issues including strand imbalance, library complexity, and signal enrichment of data. Assessment of these features are facilitated through diagnostic plots and summary statistics calculated over regions of the genome with varying levels of coverage. We evaluated our QC pipeline with both large collections of public ChIP-exo/nexus data and multiple, new ChIP-exo datasets from E. coli. ChIPexoQual analysis of these datasets resulted in guidelines for using these QC metrics across a wide range of sequencing depths and provided further insights for modelling ChIP-exo data. Finally, although ChIP-exo experiments have been compared to ChIP-seq experiments with single-end (SE) sequencing, we provide, for the first time, comparisons with paired-end (PE) ChIP-seq experiments. We illustrate that, at fixed sequencing depths, ChIP-exo provides higher sensitivity, specificity, and spatial resolution than PE ChIP-seq and both significantly outperform their SE ChIP-seq counterpart.
2017-03-01 | GSE84830 | GEO
Project description:Chip-exo and Chip-nexus for FOXA1, HNF4A, KLF5, MYC, and TCF7L2 in colorectal cancer cell lines LoVo, GP5D, COLO320DM
| EGAD00001004099 | EGA
Project description:Understanding how eukaryotic enhancers are bound and regulated by specific combinations of transcription factors is still a major challenge. To better map transcription factor binding genome-wide at nucleotide resolution in vivo, we have developed a robust ChIP-exo protocol called ChIP-nexus (chromatin immunoprecipitation experiments with nucleotide resolution through exonuclease, unique barcode and single ligation), which utilizes an efficient DNA self-circularization step during library preparation. Application of ChIP-nexus to four proteins—human TBP, Drosophila NFkB, Twist and Max—showed that it outperformed existing ChIP protocols in resolution and specificity, pinpointed relevant binding sites within enhancers containing multiple binding motifs, and allowed for the analysis of in vivo binding specificities. Notably, we show that Max frequently interacted with DNA sequences next to its motif, and that this binding pattern correlated with local DNA-sequence features such as DNA shape. ChIP-nexus will be broadly applicable to the study of in vivo transcription factor binding specificity and its relationship to cis-regulatory changes in humans and model organisms.
2014-12-02 | GSE55306 | GEO
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 | GSE60668 | GEO
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
Project description:Quality control of single amplified genome information by using no template control sequence
| PRJDB4896 | ENA
Project description:RNA Seq and ChIP-exo experiments related to this project
2018-09-25 | GSE87657 | GEO
Project description:RNA Seq and ChIP-exo experiments related to this project
2019-07-30 | GSE135056 | GEO
Project description:The ferric uptake regulator (Fur) plays a critical role in the transcriptional regulation of iron metabolism in many bacteria. However, the full regulatory potential of Fur beyond iron metabolism remains undefined. Here, we comprehensively reconstructed the Fur transcriptional regulatory network in Escherichia coli K-12 MG1655 in response to iron availability using genome-wide measurements (ChIP-exo and RNA-seq). Polyomic data analysis revealed that a total of 81 genes in 42 transcription units (TUs) are directly regulated by three different modes of Fur regulation, including apo- and holo-Fur activation as well as holo-Fur repression. We showed that Fur connects iron transport and utilization enzymes with negative-feedback loop pairs for iron homeostasis. In addition, direct involvement of Fur in the regulation of DNA synthesis, energy metabolism, and biofilm development was found. These results indicate that Fur exhibits a comprehensive regulatory role affecting many fundamental cellular processes linked to iron metabolism in order to coordinate E. coli responses to the availability of iron. [ChIP-exo]: A total of twelve samples were analyzed. WT and Fur-8-myc tagged cells were cultured in the presense and absence of iron with biological duplicates. To analyze static RNAP binding, rifampicin was also added to the media with biological duplicates. DPD = iron chelator.
2014-09-09 | E-GEOD-54899 | biostudies-arrayexpress
Project description:Degradation of intracellular proteins in Gram-negative bacteria regulates various cellular processes and serves as a quality control mechanism by eliminating damaged proteins. To understand what causes the proteolytic machinery of the cell to degrade some proteins while sparing others, we employed a quantitative pulsed-SILAC (Stable Isotope Labeling with Amino acids in Cell culture) method followed by mass spectrometry analysis to determine the half-lives for the proteome of exponentially growing Escherichia coli, under standard conditions. We developed a likelihood-based statistical test to findactively degraded proteins, and identified dozens of novel proteins that are fast-degrading. Finally, we used structural, physicochemical and protein-protein interaction network descriptorsto train a machine-learning classifier to discriminate fast-degrading proteins from the rest of the proteome. Our combined computational-experimental approach provides means for proteomic-based discovery of fast degrading proteins in bacteria and the elucidation of the factors determining protein half-livesand have implications for protein engineering. Moreover, as rapidly degraded proteins may play an important role in pathogenesis, our findings could identify new potential antibacterial drug targets
2021-01-13 | PXD022112 | Pride