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Dynamic rewiring of transcription factor networks during smooth muscle cell phenotypic modulation (ChIP-Rx data sets)

ABSTRACT: Dynamic rewiring of transcription factor networks during smooth muscle cell phenotypic modulation (ChIP-Rx data sets)

PROVIDER: PRJNA437963 | ENA |

REPOSITORIES: ENA

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			Action	DRS
	SRR6826260.fastq.gz	Fastqsanger.gz
	SRR6826270.fastq.gz	Fastqsanger.gz
	SRR6826261.fastq.gz	Fastqsanger.gz
	SRR6826271.fastq.gz	Fastqsanger.gz
	SRR6826262.fastq.gz	Fastqsanger.gz

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Dynamic rewiring of transcription factor networks during smooth muscle cell phenotypic modulation (ChIP-Rx data sets)

Project description:Phenotypic modulation of smooth muscle cells (SMC) is a hallmark of vascular disease and a classic cell state transformation mediated by convergent signal-integration in the nucleus. Here, using PDGF-mediated SMC activation, we describe for the first time the dynamic active chromatin response and global transcriptional remodeling of cell state. We find that PDGF stimulation drives global transcriptional amplification and anabolism concurrent with increased proliferation and motility. Kinetic gene expression and Brd4 chromatin co-activator occupancy analysis reveals transcription factor (TF) directed enhancer re-wiring shaped by an immediate-early (Jun/Fos) response followed by increased nuclear hormone receptor transcriptional signaling that is Rev-erbdependent. Interdicting signaling between enhancers and transcription via Brd4 inhibition halts canonical cellular features of PDGF stimulation, and in vivo Brd4 inhibition potently abrogates vascular injury responses. These data provide a global map of TF-directed chromatin remodeling during SMC phenotypic modulation and elucidate key therapeutic mechanisms of transcriptional inhibition in vascular disease.

2019-01-01 | GSE111710 | GEO

Dynamic rewiring of transcription factor networks during smooth muscle cell phenotypic modulation (RNA-Seq data sets)

Project description:Dynamic rewiring of transcription factor networks during smooth muscle cell phenotypic modulation (RNA-Seq data sets)

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Dynamic rewiring of transcription factor networks during smooth muscle cell phenotypic modulation (ChIP-Seq data sets)

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Dynamic rewiring of transcription factor networks during smooth muscle cell phenotypic modulation (ATAC-Seq data sets)

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Dynamic rewiring of transcription factor networks during smooth muscle cell phenotypic modulation

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Dynamic rewiring of transcription factor networks during smooth muscle cell phenotypic modulation (RNA-Seq data sets)

2019-01-01 | GSE111714 | GEO

Dynamic rewiring of transcription factor networks during smooth muscle cell phenotypic modulation (ATAC-Seq data sets)

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Dynamic rewiring of transcription factor networks during smooth muscle cell phenotypic modulation (ChIP-Seq data sets)

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Dynamic rewiring of transcription factor networks during smooth muscle cell phenotypic modulation

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

2019-01-01 | GSE111715 | GEO

Interaction between Lactiplantibacillus plantarum RX-8 and Wickerhamomyces anomalus Y-5 under co-culture by proteomics analysis

Project description:In present study, it was found that the co-culture of Wickerhamomyces anomalus Y-5 and L. plantarum RX-8 could enhance bacteriocin production. To analyze the interaction between W. anomalus Y-5 and L. plantarum RX-8, a quantitative proteomic approach was used to analyze and compare the proteome in L. plantarum RX-8 and W. anomalus Y-5 under mono-culture and co-culture. In total, 339 differently expressed proteins (DEPs) were screened in comparison of L. plantarum RX-8 under mono-culture and co-culture, 645 proteins of W. anomalus Y-5 changed in mono-culture and co-culture. The Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis indicated that DEPs participated in various metabolic pathways such as PTS system, glycolysis, galactose metabolism, glutamate, aspartate, arginine and cysteine metabolism etc. These pathways were related to inducing mechanism on improving bacteriocin production by co-culture. Quantitative proteomic analysis-based strategies can therefore provide further evidence for new regulated targets to improve the production of bacteriocins.

2022-12-04 | PXD038315 | Pride

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