Quantifying the Central Dogma in the p53 Pathway in Live Single Cells

Hafner, Antonina; Reyes, José Santos; Stewart-Ornstein, Jacob; Tsabar, Michael; Jambhekar, Ashwini; Lahav, Galit

doi:10.1016/j.cels.2020.05.001

Cited by 31 publications

(25 citation statements)

References 45 publications

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“…3A, right). Such refractory cells have also been identified in live-imaging studies of the early development of the fruit fly (Garcia et al, 2013;Lammers et al, 2020;Berrocal et al, 2020) and in in vitro cultures of animal cells (Hafner et al, 2020).…”

Section: Uncovering Single-cell Transcriptional Responses To Heat Shockmentioning

confidence: 97%

“…Several Drosophila enhancers invoke both strategies simultaneously (Garcia et al, 2013;Bothma et al, 2014;Lammers et al, 2020;Berrocal et al, 2020). Single timepoint measurements in plants (Turco et al, 2019;Angel et al, 2011) and live-imaging studies in cell culture (Hafner et al, 2020) have also provided evidence for switch-like control.…”

Section: Tissue-wide Transcriptional Dynamics Arise From the Switch-lmentioning

confidence: 99%

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Quantitative imaging of RNA polymerase II activity in plants reveals the single-cell basis of tissue-wide transcriptional dynamics

Álamos

Reimer

Niyogi

et al. 2020

Preprint

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The responses of plants to their environment often hinge on the spatiotemporal dynamics of transcriptional regulation. While live-imaging tools have been used extensively to quantitatively capture rapid transcriptional dynamics in living animal cells, lack of implementation of these technologies in plants has limited concomitant quantitative studies. Here, we applied the PP7 and MS2 RNA-labeling technologies for the quantitative imaging of RNA polymerase II activity dynamics in single cells of living plants as they respond to experimental treatments. Using this technology, we count nascent RNA transcripts in real-time in Nicotiana benthamiana (tobacco) and Arabidopsis thaliana (Arabidopsis). Examination of heat shock reporters revealed that plant tissues respond to external signals by modulating the number of cells engaged in transcription rather than the transcription rate of active cells. This switch-like behavior, combined with cell-to-cell variability in transcription rate, results in mRNA production variability spanning three orders of magnitude. We determined that cellular heterogeneity stems mainly from the stochasticity intrinsic to individual alleles. Taken together, our results demonstrate that it is now possible to quantitatively study the dynamics of transcriptional programs in single cells of living plants.

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Section: Uncovering Single-cell Transcriptional Responses To Heat Shockmentioning

confidence: 97%

Section: Tissue-wide Transcriptional Dynamics Arise From the Switch-lmentioning

confidence: 99%

Quantitative imaging of RNA polymerase II activity in plants reveals the single-cell basis of tissue-wide transcriptional dynamics

Álamos

Reimer

Niyogi

et al. 2020

Preprint

View full text Add to dashboard Cite

show abstract

“…More recent work demonstrates that stochastic transcription of p53 target genes is controlled by transcription burst frequency, a parameter controlled by transcription initiation rates ( 160 ). Live cell imaging suggests that elevated p53 protein expression increases the likelihood a gene target will be transcribed (burst frequency), but does not influence the magnitude of the transcriptional response (burst size) ( 161 ). These data also suggest that affinity-based models of promoter activity are unlikely to fully describe p53 regulated transcription, with p53 CTD modifications controlling some of the observed kinetic differences between p53 target genes.…”

Section: Functional Consequences Of P53 Binding In Varied Genomic Conmentioning

confidence: 99%

Tumor suppressor p53: from engaging DNA to target gene regulation

Sammons

Nguyen

McDade

et al. 2020

Nucleic Acids Research

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The p53 transcription factor confers its potent tumor suppressor functions primarily through the regulation of a large network of target genes. The recent explosion of next generation sequencing protocols has enabled the study of the p53 gene regulatory network (GRN) and underlying mechanisms at an unprecedented depth and scale, helping us to understand precisely how p53 controls gene regulation. Here, we discuss our current understanding of where and how p53 binds to DNA and chromatin, its pioneer-like role, and how this affects gene regulation. We provide an overview of the p53 GRN and the direct and indirect mechanisms through which p53 affects gene regulation. In particular, we focus on delineating the ubiquitous and cell type-specific network of regulatory elements that p53 engages; reviewing our understanding of how, where, and when p53 binds to DNA and the mechanisms through which these events regulate transcription. Finally, we discuss the evolution of the p53 GRN and how recent work has revealed remarkable differences between vertebrates, which are of particular importance to cancer researchers using mouse models.

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“…Prompt and sharp transcriptional profiles are observed for other inducible transcriptional programs, ranging from stress response to nutrient detection and development ( Hafner et al., 2020 ; Senecal et al., 2014 ; Stevense et al., 2010 ). Furthermore, other inducible transcription factors such as p53 have similar search times ( Loffreda et al., 2017 ) to the one we calculated for NF-κB and produce population-level gene-independent nascent transcription dynamics and gene-specific mRNA profiles due to differential RNA degradation ( Hafner et al., 2017 ; Koh et al., 2019 ; Porter et al., 2016 ).…”

Section: Discussionmentioning

confidence: 99%

First Responders Shape a Prompt and Sharp NF-κB-Mediated Transcriptional Response to TNF-α

et al. 2020

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Summary Nuclear factor (NF)-κB controls the transcriptional response to inflammatory signals by translocating into the nucleus, but we lack a single-cell characterization of the resulting transcription dynamics. Here we show that upon tumor necrosis factor (TNF)-α transcription of NF-κB target genes is heterogeneous in individual cells but results in an average nascent transcription profile that is prompt (i.e., occurs almost immediately) and sharp (i.e., increases and decreases rapidly) compared with NF-κB nuclear localization. Using an NF-κB-controlled MS2 reporter we show that the single-cell nascent transcription is more heterogeneous than NF-κB translocation dynamics, with a fraction of synchronized “first responders” that shape the average transcriptional profile and are more prone to respond to multiple TNF-α stimulations. A mathematical model combining NF-κB-mediated gene activation and a gene refractory state is able to reproduce these features. Our work shows how the expression of target genes induced by transcriptional activators can be heterogeneous across single cells and yet time resolved on average.

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Quantifying the Central Dogma in the p53 Pathway in Live Single Cells

Cited by 31 publications

References 45 publications

Quantitative imaging of RNA polymerase II activity in plants reveals the single-cell basis of tissue-wide transcriptional dynamics

Quantitative imaging of RNA polymerase II activity in plants reveals the single-cell basis of tissue-wide transcriptional dynamics

Tumor suppressor p53: from engaging DNA to target gene regulation

First Responders Shape a Prompt and Sharp NF-κB-Mediated Transcriptional Response to TNF-α

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