Dataset Information

Fold-Change Detection of NF-?B at Target Genes with Different Transcript Outputs.

ABSTRACT: The transcription factor nuclear factor (NF)-?B promotes inflammatory and stress-responsive gene transcription across a range of cell types in response to the cytokine tumor necrosis factor (TNF). Although NF-?B signaling exhibits significant variability across single cells, some target genes supporting high levels of TNF-inducible transcription exhibit fold-change detection of NF-?B, which may buffer against stochastic variation in signaling molecules. It is unknown whether fold-change detection is maintained at NF-?B target genes with low levels of TNF-inducible transcription, for which stochastic promoter events may be more pronounced. Here, we used a microfluidic cell-trapping device to measure how TNF-induced activation of NF-?B controls transcription in single Jurkat T cells at the promoters of integrated HIV and the endogenous cytokine gene IL6, which produce only a few transcripts per cell. We tracked TNF-stimulated NF-?B RelA nuclear translocation by live-cell imaging and then quantified transcript number by RNA FISH in the same cell. We found that TNF-induced transcript abundance at 2 h for low- and high-abundance target genes correlates with similar strength with the fold change in nuclear NF-?B. A computational model of TNF-NF-?B signaling, which implements fold-change detection from competition for binding to ?B motifs, could reproduce fold-change detection across the experimentally measured range of transcript outputs. However, multiple model parameters affecting transcription had to be simultaneously varied across promoters to maintain fold-change detection while also matching other trends in the single-cell data for low-abundance transcripts. Our results suggest that cells use multiple biological mechanisms to tune transcriptional output while maintaining robustness of NF-?B fold-change detection.

SUBMITTER: Wong VC

PROVIDER: S-EPMC6382958 | biostudies-literature | 2019 Feb

REPOSITORIES: biostudies-literature

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Publications

Fold-Change Detection of NF-κB at Target Genes with Different Transcript Outputs.

Wong Victor C VC Mathew Shibin S Ramji Ramesh R Gaudet Suzanne S Miller-Jensen Kathryn K

Biophysical journal 20190112 4

The transcription factor nuclear factor (NF)-κB promotes inflammatory and stress-responsive gene transcription across a range of cell types in response to the cytokine tumor necrosis factor (TNF). Although NF-κB signaling exhibits significant variability across single cells, some target genes supporting high levels of TNF-inducible transcription exhibit fold-change detection of NF-κB, which may buffer against stochastic variation in signaling molecules. It is unknown whether fold-change detectio ...[more]

PMID: 30704857

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Project description:Visual processing transforms the complexities of the visual world into useful information. Ciona, an invertebrate chordate and close relative of the vertebrates, has one of the simplest nervous systems known, yet has a range of visuomotor behaviors. This simplicity has facilitated studies linking behavior and neural circuitry. Ciona larvae have two distinct visuomotor behaviors - a looming shadow response and negative phototaxis. These are mediated by separate neural circuits that initiate from different clusters of photoreceptors, with both projecting to a CNS structure called the posterior brain vesicle (pBV). We report here that inputs from both circuits are processed to generate fold change detection (FCD) outputs. In FCD, the behavioral response scales with the relative fold change in input, but is invariant to the overall magnitude of the stimulus. Moreover, the two visuomotor behaviors have fundamentally different stimulus/response relationships - indicative of differing circuit strategies, with the looming shadow response showing a power relationship to fold change, while the navigation behavior responds linearly. Pharmacological modulation of the FCD response points to the FCD circuits lying outside of the visual organ (the ocellus), with the pBV being the most likely location. Consistent with these observations, the connectivity and properties of pBV interneurons conform to known FCD circuit motifs, but with different circuit architectures for the two circuits. The negative phototaxis circuit forms a putative incoherent feedforward loop that involves interconnecting cholinergic and GABAergic interneurons. The looming shadow circuit uses the same cholinergic and GABAergic interneurons, but with different synaptic inputs to create a putative non-linear integral feedback loop. These differing circuit architectures are consistent with the behavioral outputs of the two circuits. Finally, while some reports have highlighted parallels between the pBV and the vertebrate midbrain, suggesting a common origin for the two, others reports have disputed this, suggesting that invertebrate chordates lack a midbrain homolog. The convergence of visual inputs at the pBV, and its putative role in visual processing reported here and in previous publications, lends further support to the proposed common origin of the pBV and the vertebrate midbrain.

Project description:BackgroundGene expression experiments are common in molecular biology, for example in order to identify genes which play a certain role in a specified biological framework. For that purpose expression levels of several thousand genes are measured simultaneously using DNA microarrays. Comparing two distinct groups of tissue samples to detect those genes which are differentially expressed one statistical test per gene is performed, and resulting p-values are adjusted to control the false discovery rate. In addition, the expression change of each gene is quantified by some effect measure, typically the log fold change. In certain cases, however, a gene with a significant p-value can have a rather small fold change while in other cases a non-significant gene can have a rather large fold change. The biological relevance of the change of gene expression can be more intuitively judged by a fold change then merely by a p-value. Therefore, confidence intervals for the log fold change which accompany the adjusted p-values are desirable.ResultsIn a new approach, we employ an existing algorithm for adjusting confidence intervals in the case of high-dimensional data and apply it to a widely used linear model for microarray data. Furthermore, we adopt a concept of different relevance categories for effects in clinical trials to assess biological relevance of genes in microarray experiments. In a brief simulation study the properties of the adjusting algorithm are maintained when being combined with the linear model for microarray data. In two cancer data sets the adjusted confidence intervals can indicate significance of large fold changes and distinguish them from other large but non-significant fold changes. Adjusting of confidence intervals also corrects the assessment of biological relevance.ConclusionsOur new combination approach and the categorization of fold changes facilitates the selection of genes in microarray experiments and helps to interpret their biological relevance.

Dataset Information

Fold-Change Detection of NF-?B at Target Genes with Different Transcript Outputs.

Publications

Fold-Change Detection of NF-κB at Target Genes with Different Transcript Outputs.

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