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NF-?B-Chromatin Interactions Drive Diverse Phenotypes by Modulating Transcriptional Noise.

ABSTRACT: Noisy gene expression generates diverse phenotypes, but little is known about mechanisms that modulate noise. Combining experiments and modeling, we studied how tumor necrosis factor (TNF) initiates noisy expression of latent HIV via the transcription factor nuclear factor ?B (NF-?B) and how the HIV genomic integration site modulates noise to generate divergent (low-versus-high) phenotypes of viral activation. We show that TNF-induced transcriptional noise varies more than mean transcript number and that amplification of this noise explains low-versus-high viral activation. For a given integration site, live-cell imaging shows that NF-?B activation correlates with viral activation, but across integration sites, NF-?B activation cannot account for differences in transcriptional noise and phenotypes. Instead, differences in transcriptional noise are associated with differences in chromatin state and RNA polymerase II regulation. We conclude that, whereas NF-?B regulates transcript abundance in each cell, the chromatin environment modulates noise in the population to support diverse HIV activation in response to TNF.

SUBMITTER: Wong VC

PROVIDER: S-EPMC5812697 | biostudies-literature | 2018 Jan

REPOSITORIES: biostudies-literature

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NF-κB-Chromatin Interactions Drive Diverse Phenotypes by Modulating Transcriptional Noise.

Wong Victor C VC Bass Victor L VL Bullock M Elise ME Chavali Arvind K AK Lee Robin E C REC Mothes Walther W Gaudet Suzanne S Miller-Jensen Kathryn K

Cell reports 20180101 3

Noisy gene expression generates diverse phenotypes, but little is known about mechanisms that modulate noise. Combining experiments and modeling, we studied how tumor necrosis factor (TNF) initiates noisy expression of latent HIV via the transcription factor nuclear factor κB (NF-κB) and how the HIV genomic integration site modulates noise to generate divergent (low-versus-high) phenotypes of viral activation. We show that TNF-induced transcriptional noise varies more than mean transcript number ...[more]

PMID: 29346759

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Project description:Gene regulation often appears deterministic in the average cell population, but transcription is a probabilistic process at the single-cell level. Although many mechanisms are invoked to account for this behavior, it is difficult to determine how cell-to-cell variation in the interactions of transcription factors with target chromatin impact transcriptional output. Here, we use cells that contain a 200-copy tandem array of promoter or reporter gene units to simultaneously visualize transient interaction, equilibrium or steady-state binding of fluorescent-protein-labeled glucocorticoid receptor with its DNA response elements, the recruitment of diverse coregulators, and transcriptional output at the single-cell level. These regulatory proteins associate with target chromatin via a probabilistic mechanism that produces cell-to-cell variability in binding. The multiple steps of this process are partially independent and differ between individual regulators. The association level of each regulator influences the transcriptional output in individual cells, but this does not account for all transcriptional heterogeneity. Additionally, specific combinatorial interactions of the glucocorticoid receptor and coregulators with response elements regulate transcription at the single-cell level. Like many endogenous genes, the average array transcriptional activity evolves over time. This apparently deterministic average temporal promoter progression involves changes in the probability that specific combinatorial glucocorticoid receptor and coregulator interactions will occur on the response elements in single cells. These data support the emerging ;return-to-template' transcription model, which mechanistically unifies the observed extremely transient interactions between the transcription factor and response elements, cell-to-cell variability in steady-state association of factors with chromatin, and the resulting heterogeneous gene expression between individual cells.

Dataset Information

NF-?B-Chromatin Interactions Drive Diverse Phenotypes by Modulating Transcriptional Noise.

Publications

NF-κB-Chromatin Interactions Drive Diverse Phenotypes by Modulating Transcriptional Noise.

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