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Transcriptional control of the TNF gene.

ABSTRACT: The cytokine TNF is a critical mediator of immune and inflammatory responses. The TNF gene is an immediate early gene, rapidly transcribed in a variety of cell types following exposure to a broad range of pathogens and signals of inflammation and stress. Regulation of TNF gene expression at the transcriptional level is cell type- and stimulus-specific, involving the recruitment of distinct sets of transcription factors to a compact and modular promoter region. In this review, we describe our current understanding of the mechanisms through which TNF transcription is specifically activated by a variety of extracellular stimuli in multiple cell types, including T cells, B cells, macrophages, mast cells, dendritic cells, and fibroblasts. We discuss the role of nuclear factor of activated T cells and other transcription factors and coactivators in enhanceosome formation, as well as the contradictory evidence for a role for nuclear factor kappaB as a classical activator of the TNF gene. We describe the impact of evolutionarily conserved cis-regulatory DNA motifs in the TNF locus upon TNF gene transcription, in contrast to the neutral effect of single nucleotide polymorphisms. We also assess the regulatory role of chromatin organization, epigenetic modifications, and long-range chromosomal interactions at the TNF locus.

SUBMITTER: Falvo JV

PROVIDER: S-EPMC4785889 | biostudies-literature | 2010

REPOSITORIES: biostudies-literature

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Transcriptional control of the TNF gene.

Falvo James V JV Tsytsykova Alla V AV Goldfeld Anne E AE

Current directions in autoimmunity 20100218

The cytokine TNF is a critical mediator of immune and inflammatory responses. The TNF gene is an immediate early gene, rapidly transcribed in a variety of cell types following exposure to a broad range of pathogens and signals of inflammation and stress. Regulation of TNF gene expression at the transcriptional level is cell type- and stimulus-specific, involving the recruitment of distinct sets of transcription factors to a compact and modular promoter region. In this review, we describe our cur ...[more]

PMID: 20173386

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Project description:BackgroundThe cytokine tumor necrosis factor (TNF) initiates tissue inflammation, a process mediated by the NF-kappaB transcription factor. In response to TNF, latent cytoplasmic NF-kappaB is activated, enters the nucleus, and induces expression of inflammatory and anti-apoptotic gene expression programs. Recently it has been shown that NF-kappaB displays two distinct activation modes, monophasic and oscillatory, depending on stimulus duration. Characterization of temporal expression patterns for the NF-kappaB network and determination of those genes under monophasic- or oscillatory control has not been experimentally addressed.ResultsTo identify the kinetics of NF-kappaB-dependent gene expression and determine whether these two types of NF-kappaB translocation modes control distinct gene programs, a detailed kinetic analysis of a validated microarray data set was performed on 74 unique NF-kappaB-dependent genes in response to TNF. Hierarchical clustering identified distinct expression profiles termed the "Early", "Middle", "Late" response groups, peaking 1, 3, and 6 h after stimulation, respectively. These expression patterns were validated by Quantitative Real Time PCR (Q-RT-PCR) and NF-kappaB binding was demonstrated by chromatin immunoprecipitation (ChIP) assays. Each response group was mapped to its molecular function; this analysis indicated that the Early group encodes cytokines or negative regulators of the IKK-NF-kappaB pathway, and the Late group encodes cell surface receptors, adhesion molecules and signal adapters. That similar coordinated sequential cascades of gene expression were also seen in response to stimulation by the cytokine IL-1, and expression patterns observed in MRC-5 fibroblasts indicated that the epithelial NF-kappaB program is relatively stimulus- and cell type-independent. Bioinformatic analysis of the Early and Late gene promoters indicates that although both groups contain similar patterns of NF-kappaB-binding sites, only the Early gene promoters contain NF-kappaB-binding sites located in phylogenetically conserved domains. Stimulation protocols designed to produce either monophasic or oscillatory NF-kappaB activation modes showed that the oscillatory mode is required only for expression of the Late genes.ConclusionThis analysis provides important insights into the TNF-regulated genetic response program in epithelial cells, where NF-kappaB controls sequential expression patterns of functionally distinct genes that depend on its oscillatory activation mode.

Project description:The segmentation gene network of Drosophila consists of maternal and zygotic factors that generate, by transcriptional (cross-) regulation, expression patterns of increasing complexity along the anterior-posterior axis of the embryo. Using known binding site information for maternal and zygotic gap transcription factors, the computer algorithm Ahab recovers known segmentation control elements (modules) with excellent success and predicts many novel modules within the network and genome-wide. We show that novel module predictions are highly enriched in the network and typically clustered proximal to the promoter, not only upstream, but also in intronic space and downstream. When placed upstream of a reporter gene, they consistently drive patterned blastoderm expression, in most cases faithfully producing one or more pattern elements of the endogenous gene. Moreover, we demonstrate for the entire set of known and newly validated modules that Ahab's prediction of binding sites correlates well with the expression patterns produced by the modules, revealing basic rules governing their composition. Specifically, we show that maternal factors consistently act as activators and that gap factors act as repressors, except for the bimodal factor Hunchback. Our data suggest a simple context-dependent rule for its switch from repressive to activating function. Overall, the composition of modules appears well fitted to the spatiotemporal distribution of their positive and negative input factors. Finally, by comparing Ahab predictions with different categories of transcription factor input, we confirm the global regulatory structure of the segmentation gene network, but find odd skipped behaving like a primary pair-rule gene. The study expands our knowledge of the segmentation gene network by increasing the number of experimentally tested modules by 50%. For the first time, the entire set of validated modules is analyzed for binding site composition under a uniform set of criteria, permitting the definition of basic composition rules. The study demonstrates that computational methods are a powerful complement to experimental approaches in the analysis of transcription networks.

Project description:BACKGROUND: Cellular signaling involves a sequence of events from ligand binding to membrane receptors through transcription factors activation and the induction of mRNA expression. The transcriptional-regulatory system plays a pivotal role in the control of gene expression. A novel computational approach to the study of gene regulation circuits is presented here. METHODOLOGY: Based on the concept of finite state machine, which provides a discrete view of gene regulation, a novel sequential logic model (SLM) is developed to decipher control mechanisms of dynamic transcriptional regulation of gene expressions. The SLM technique is also used to systematically analyze the dynamic function of transcriptional inputs, the dependency and cooperativity, such as synergy effect, among the binding sites with respect to when, how much and how fast the gene of interest is expressed. PRINCIPAL FINDINGS: SLM is verified by a set of well studied expression data on endo16 of Strongylocentrotus purpuratus (sea urchin) during the embryonic midgut development. A dynamic regulatory mechanism for endo16 expression controlled by three binding sites, UI, R and Otx is identified and demonstrated to be consistent with experimental findings. Furthermore, we show that during transition from specification to differentiation in wild type endo16 expression profile, SLM reveals three binary activities are not sufficient to explain the transcriptional regulation of endo16 expression and additional activities of binding sites are required. Further analyses suggest detailed mechanism of R switch activity where indirect dependency occurs in between UI activity and R switch during specification to differentiation stage. CONCLUSIONS/SIGNIFICANCE: The sequential logic formalism allows for a simplification of regulation network dynamics going from a continuous to a discrete representation of gene activation in time. In effect our SLM is non-parametric and model-independent, yet providing rich biological insight. The demonstration of the efficacy of this approach in endo16 is a promising step for further application of the proposed method.

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Transcriptional control of the TNF gene.

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Transcriptional control of the TNF gene.

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