Transcriptional Bursting Research Articles

Predictability and Control of Gene Bursting in Live Mammalian Cells

Transcriptional bursting is a hallmark for cellular variability across species. Whether predictability and output control exist within the stochastic bursting process is unknown. Here, we advance that collective behaviors from transient bio-molecular interactions help confer gene expression control in mammalian cells. We developed a live cell super-resolution approach to uncover the correlation between mRNA synthesis and the dynamics of RNA Polymerase II (Pol II) clusters at a gene locus. For endogenous β-actin genes in mouse embryonic fibroblasts, we observe that short (∼8 s) Pol II clusters correlate with basal mRNA output. With serum stimulation, a stereotyped increase in Pol II cluster lifetime correlates with the proportionate increase in mRNAs synthesized minutes later. An additional burst of mRNA synthesis can be induced, at will, with a drug that stalls then releases Pol II clustering. Our findings reveal that transient clustering of Pol II constitutes a pre-transcriptional regulatory event which dynamically controls gene expression output.

Characterizing Transcription and Splicing Kinetics by 3D Orbital Tracking

We describe our recent application of two photon laser scanning microscopy to characterize transcription and splicing rates in living cells with sub-diffraction limited spatial resolution and second to hour long temporal resolution by the application of 3D orbital tracking[1] and two color in vivo RNA labelling[2]. We find that measurements agree with previous studies utilizing widefield volumetric imaging but increase the temporal resolution 100 fold and the duration of each experiment by 10 fold characterizing protein-RNA binding, RNA synthesis and splicing and long timescale transcriptional bursting in a single measurement. This technique may have future applications for the study of both natural and synthetic gene regulation in eukaryotes.1. Levi V, Ruan Q, Gratton E. 3-D particle tracking in a two-photon microscope: application to the study of molecular dynamics in cells. Biophys J. 2005;88: 2919-2928. http://dx.doi.org/10.1529/biophysj.104.0442302. Coulon A, Ferguson ML, de Turris V, Palangat M, Chow CC, Larson DR. Kinetic competition during the transcription cycle results in stochastic RNA processing. Elife. 2014;3. http://dx.doi.org/10.7554/eLife.03939.

Universal Poisson Statistics of mRNAs with Complex Decay Pathways

Messenger RNA (mRNA) dynamics in single cells are often modeled as a memoryless birth-death process with a constant probability per unit time that an mRNA molecule is synthesized or degraded. This predicts a Poisson steady-state distribution of mRNA number, in close agreement with experiments. This is surprising, since mRNA decay is known to be a complex process. The paradox is resolved by realizing that the Poisson steady state generalizes to arbitrary mRNA lifetime distributions. A mapping between mRNA dynamics and queueing theory highlights an identifiability problem: a measured Poisson steady state is consistent with a large variety of microscopic models. Here, I provide a rigorous and intuitive explanation for the universality of the Poisson steady state. I show that the mRNA birth-death process and its complex decay variants all take the form of the familiar Poisson law of rare events, under a nonlinear rescaling of time. As a corollary, not only steady-states but also transients are Poisson distributed. Deviations from the Poisson form occur only under two conditions, promoter fluctuations leading to transcriptional bursts or nonindependent degradation of mRNA molecules. These results place severe limits on the power of single-cell experiments to probe microscopic mechanisms, and they highlight the need for single-molecule measurements.

A biophysical model of supercoiling dependent transcription predicts a structural aspect to gene regulation.

BackgroundTranscription in Escherichia coli generates positive supercoiling in the DNA, which is relieved by the enzymatic activity of gyrase. Recently published experimental evidence suggests that transcription initiation and elongation are inhibited by the buildup of positive supercoiling. It has therefore been proposed that intermittent binding of gyrase plays a role in transcriptional bursting. Considering that transcription is one of the most fundamental cellular processes, it is desirable to be able to account for the buildup and release of positive supercoiling in models of transcription.ResultsHere we present a detailed biophysical model of gene expression that incorporates the effects of supercoiling due to transcription. By directly linking the amount of positive supercoiling to the rate of transcription, the model predicts that highly transcribed genes’ mRNA distributions should substantially deviate from Poisson distributions, with enhanced density at low mRNA copy numbers. Additionally, the model predicts a high degree of correlation between expression levels of genes inside the same supercoiling domain.ConclusionsOur model, incorporating the supercoiling state of the gene, makes specific predictions that differ from previous models of gene expression. Genes in the same supercoiling domain influence the expression level of neighboring genes. Such structurally dependent regulation predicts correlations between genes in the same supercoiling domain. The topology of the chromosome therefore creates a higher level of gene regulation, which has broad implications for understanding the evolution and organization of bacterial genomes.Electronic supplementary materialThe online version of this article (doi:10.1186/s13628-016-0027-0) contains supplementary material, which is available to authorized users.

Nuclear Retention of mRNA in Mammalian Tissues.

SummarymRNA is thought to predominantly reside in the cytoplasm, where it is translated and eventually degraded. Although nuclear retention of mRNA has a regulatory potential, it is considered extremely rare in mammals. Here, to explore the extent of mRNA retention in metabolic tissues, we combine deep sequencing of nuclear and cytoplasmic RNA fractions with single-molecule transcript imaging in mouse beta cells, liver, and gut. We identify a wide range of protein-coding genes for which the levels of spliced polyadenylated mRNA are higher in the nucleus than in the cytoplasm. These include genes such as the transcription factor ChREBP, Nlrp6, Glucokinase, and Glucagon receptor. We demonstrate that nuclear retention of mRNA can efficiently buffer cytoplasmic transcript levels from noise that emanates from transcriptional bursts. Our study challenges the view that transcripts predominantly reside in the cytoplasm and reveals a role of the nucleus in dampening gene expression noise.

Cell-to-Cell Transcript Variability: Seeing Signal in the Noise

How stochastic is gene expression in mammalian cells? Not very, according to Battich etal., who report that single-cell variability in cytoplasmic mRNAs is remarkably predictable given measurements of a cell's phenotypic state and microenvironment. The noise from transcriptional bursts is buffered by a hallmark of eukaryotes-the nucleus.

Temperature-induced variation in gene expression burst size in metazoan cells.

BackgroundGene expression is an inherently stochastic process, owing to its dynamic molecular nature. Protein amount distributions, which can be acquired by cytometry using a reporter gene, can inform about the mechanisms of the underlying microscopic molecular system.ResultsBy using different clones of chicken erythroid progenitor cells harboring different integration sites of a CMV-driven mCherry protein, we investigated the dynamical behavior of such distributions. We show that, on short term, clone distributions can be quickly regenerated from small population samples with a high accuracy. On longer term, on the contrary, we show variations manifested by correlated fluctuation in the Mean Fluorescence Intensity. In search for a possible cause of this correlation, we demonstrate that in response to small temperature variations cells are able to adjust their gene expression rate: a modest (2 °C) increase in external temperature induces a significant down regulation of mean expression values, with a reverse effect observed when the temperature is decreased. Using a two-state model of gene expression we further demonstrate that temperature acts by modifying the size of transcription bursts, while the burst frequency of the investigated promoter is less systematically affected.ConclusionsFor the first time, we report that transcription burst size is a key parameter for gene expression that metazoan cells from homeotherm animals can modify in response to an external thermal stimulus.Electronic supplementary materialThe online version of this article (doi:10.1186/s12867-015-0048-2) contains supplementary material, which is available to authorized users.

Endoplasmic Reticulum Stress Signaling in Plant Immunity—At the Crossroad of Life and Death

Rapid and complex immune responses are induced in plants upon pathogen recognition. One form of plant defense response is a programmed burst in transcription and translation of pathogenesis-related proteins, of which many rely on ER processing. Interestingly, several ER stress marker genes are up-regulated during early stages of immune responses, suggesting that enhanced ER capacity is needed for immunity. Eukaryotic cells respond to ER stress through conserved signaling networks initiated by specific ER stress sensors tethered to the ER membrane. Depending on the nature of ER stress the cell prioritizes either survival or initiates programmed cell death (PCD). At present two plant ER stress sensors, bZIP28 and IRE1, have been described. Both sensor proteins are involved in ER stress-induced signaling, but only IRE1 has been additionally linked to immunity. A second branch of immune responses relies on PCD. In mammals, ER stress sensors are involved in activation of PCD, but it is unclear if plant ER stress sensors play a role in PCD. Nevertheless, some ER resident proteins have been linked to pathogen-induced cell death in plants. In this review, we will discuss the current understanding of plant ER stress signaling and its cross-talk with immune signaling.

Transcriptional read-through is not sufficient to induce an epigenetic switch in the silencing activity of Polycomb response elements

In Drosophila, Polycomb (PcG) and Trithorax (TrxG) group proteins are assembled on Polycomb response elements (PREs) to maintain tissue and stage-specific patterns of gene expression. Critical to coordinating gene expression with the process of differentiation, the activity of PREs can be switched "on" and "off." When on, the PRE imposes a silenced state on the genes in the same domain that is stably inherited through multiple rounds of cell division. When the PRE is switched off, the domain is in a state permissive for gene expression that can be stably inherited. Previous studies have suggested that a burst of transcription through a PRE sequence displaces PcG proteins and provides a universal mechanism for inducing a heritable switch in PRE activity from on to off; however, the evidence favoring this model is indirect. Here, we have directly tested the transcriptional read-through mechanism. Contrary to previous suggestions, we show that transcription through the PRE is not sufficient for inducing an epigenetic switch in PRE activity. In fact, even high levels of continuous transcription through a PRE fails to dislodge the PcG proteins, nor does it remove repressive histone marks. Our results indicate that other mechanisms involving adjacent DNA regulatory elements must be implicated in heritable switch of PRE activity.

The Low Noise Limit in Gene Expression.

Protein noise measurements are increasingly used to elucidate biophysical parameters. Unfortunately noise analyses are often at odds with directly measured parameters. Here we show that these inconsistencies arise from two problematic analytical choices: (i) the assumption that protein translation rate is invariant for different proteins of different abundances, which has inadvertently led to (ii) the assumption that a large constitutive extrinsic noise sets the low noise limit in gene expression. While growing evidence suggests that transcriptional bursting may set the low noise limit, variability in translational bursting has been largely ignored. We show that genome-wide systematic variation in translational efficiency can–and in the case of E. coli does–control the low noise limit in gene expression. Therefore constitutive extrinsic noise is small and only plays a role in the absence of a systematic variation in translational efficiency. These results show the existence of two distinct expression noise patterns: (1) a global noise floor uniformly imposed on all genes by expression bursting; and (2) high noise distributed to only a select group of genes.

Transcriptional Bursting in Gene Expression: Analytical Results for General Stochastic Models.

Gene expression in individual cells is highly variable and sporadic, often resulting in the synthesis of mRNAs and proteins in bursts. Such bursting has important consequences for cell-fate decisions in diverse processes ranging from HIV-1 viral infections to stem-cell differentiation. It is generally assumed that bursts are geometrically distributed and that they arrive according to a Poisson process. On the other hand, recent single-cell experiments provide evidence for complex burst arrival processes, highlighting the need for analysis of more general stochastic models. To address this issue, we invoke a mapping between general stochastic models of gene expression and systems studied in queueing theory to derive exact analytical expressions for the moments associated with mRNA/protein steady-state distributions. These results are then used to derive noise signatures, i.e. explicit conditions based entirely on experimentally measurable quantities, that determine if the burst distributions deviate from the geometric distribution or if burst arrival deviates from a Poisson process. For non-Poisson arrivals, we develop approaches for accurate estimation of burst parameters. The proposed approaches can lead to new insights into transcriptional bursting based on measurements of steady-state mRNA/protein distributions.

Single Cell Analysis Reveals Concomitant Transcription of Pluripotent and Lineage Markers During the Early Steps of Differentiation of Embryonic Stem Cells

The differentiation of embryonic stem cells is associated with extensive changes in gene expression. It is not yet clear whether these changes are the result of binary switch-like mechanisms or that of continuous and progressive variation. Here, I have used immunostaining and single molecule RNA fluorescence in situ hybridization (FISH) to assess changes in the expression of the well-known pluripotency-associated gene Pou5f1 (also known as Oct4) and early differentiation markers Sox1 and T-brachyury in single cells during the early steps of differentiation of mouse embryonic stem cells. I found extensive overlap between the expression of Pou5f1/Sox1 or Pou5f1/T-brachyury shortly after the initiation of differentiation towards either the neuronal or the mesendodermal lineage, but no evidence of correlation between their respective expression levels. Quantitative analysis of transcriptional output at the sites of nascent transcription revealed that Pou5f1 and Sox1 were transcribed in pulses and that embryonic stem cell differentiation was accompanied by changes in pulsing frequencies. The progressive induction of Sox1 was further associated with an increase in the average size of individual transcriptional bursts. Surprisingly, single cells that actively and simultaneously transcribe both the pluripotency- and the lineage-associated genes could easily be found in the differentiating population. The results presented here show for the first time that lineage priming can occur in cells that are actively transcribing a pluripotent marker. Furthermore, they suggest that this process is associated with changes in transcriptional dynamics.

Transient bursts of Zscan4 expression are accompanied by the rapid derepression of heterochromatin in mouse embryonic stem cells.

Mouse embryonic stem cells (mESCs) have a remarkable capacity to maintain normal genome stability and karyotype in culture. We previously showed that infrequent bursts of Zscan4 expression (Z4 events) are important for the maintenance of telomere length and genome stability in mESCs. However, the molecular details of Z4 events remain unclear. Here we show that Z4 events involve unexpected transcriptional derepression in heterochromatin regions that usually remain silent. During a Z4 event, we see rapid derepression and rerepression of heterochromatin leading to a burst of transcription that coincides with transient histone hyperacetylation and DNA demethylation, clustering of pericentromeric heterochromatin around the nucleolus, and accumulation of activating and repressive chromatin remodelling complexes. This heterochromatin-based transcriptional activity suggests that mESCs may maintain their extraordinary genome stability at least in part by transiently resetting their heterochromatin.

The role of master regulators in gene regulatory networks

Gene regulatory networks present a wide variety of dynamical responses to intrinsic and extrinsic perturbations. Arguably, one of the most important of such coordinated responses is the one of amplification cascades, in which activation of a few key-responsive transcription factors (termed master regulators, MRs) lead to a large series of transcriptional activation events. This is so since master regulators are transcription factors controlling the expression of other transcription factor molecules and so on. MRs hold a central position related to transcriptional dynamics and control of gene regulatory networks and are often involved in complex feedback and feedforward loops inducing non-trivial dynamics. Recent studies have pointed out to the myocyte enhancing factor 2C (MEF2C, also known as MADS box transcription enhancer factor 2, polypeptide C) as being one of such master regulators involved in the pathogenesis of primary breast cancer. In this work, we perform an integrative genomic analysis of the transcriptional regulation activity of MEF2C and its target genes to evaluate to what extent are these molecules inducing collective responses leading to gene expression deregulation and carcinogenesis. We also analyzed a number of induced dynamic responses, in particular those associated with transcriptional bursts, and nonlinear cascading to evaluate the influence they may have in malignant phenotypes and cancer.Received: 20 Novembre 2014, Accepted: 24 June 2015; Edited by: C. A. Condat, G. J. Sibona; DOI: http://dx.doi.org/10.4279/PIP.070011Cite as: E Hernández-Lemus, K Baca-López, R Lemus, R García-Herrera, Papers in Physics 7, 070011 (2015)This paper, by E Hernández-Lemus, K Baca-López, R Lemus, R García-Herrera, is licensed under the Creative Commons Attribution License 3.0.

The utility of simple mathematical models in understanding gene regulatory dynamics.

In this review, we survey work that has been carried out in the attempts of biomathematicians to understand the dynamic behaviour of simple bacterial operons starting with the initial work of the 1960’s. We concentrate on the simplest of situations, discussing both repressible and inducible systems and then turning to concrete examples related to the biology of the lactose and tryptophan operons. We conclude with a brief discussion of the role of both extrinsic noise and so-called intrinsic noise in the form of translational and/or transcriptional bursting.

Structure of silent transcription intervals and noise characteristics of mammalian genes.

Mammalian transcription occurs stochastically in short bursts interspersed by silent intervals showing a refractory period. However, the underlying processes and consequences on fluctuations in gene products are poorly understood. Here, we use single allele time-lapse recordings in mouse cells to identify minimal models of promoter cycles, which inform on the number and durations of rate-limiting steps responsible for refractory periods. The structure of promoter cycles is gene specific and independent of genomic location. Typically, five rate-limiting steps underlie the silent periods of endogenous promoters, while minimal synthetic promoters exhibit only one. Strikingly, endogenous or synthetic promoters with TATA boxes show simplified two-state promoter cycles. Since transcriptional bursting constrains intrinsic noise depending on the number of promoter steps, this explains why TATA box genes display increased intrinsic noise genome-wide in mammals, as revealed by single-cell RNA-seq. These findings have implications for basic transcription biology and shed light on interpreting single-cell RNA-counting experiments.

From Structural Variation of Gene Molecules to Chromatin Dynamics and Transcriptional Bursting

Transcriptional activation of eukaryotic genes is accompanied, in general, by a change in the sensitivity of promoter chromatin to endonucleases. The structural basis of this alteration has remained elusive for decades; but the change has been viewed as a transformation of one structure into another, from “closed” to “open” chromatin. In contradistinction to this static and deterministic view of the problem, a dynamical and probabilistic theory of promoter chromatin has emerged as its solution. This theory, which we review here, explains observed variation in promoter chromatin structure at the level of single gene molecules and provides a molecular basis for random bursting in transcription—the conjecture that promoters stochastically transition between transcriptionally conducive and inconducive states. The mechanism of transcriptional regulation may be understood only in probabilistic terms.

208. Single-Cell Gene Expression Profiles of Genetically Modified T Cells for Adoptive Immunotherapy

System-level characterization of cell states requires detailed portrayal of cellular components such as gene transcripts or proteins. Here, we exploit a robust single-cell platform technology to characterize T cells expanded ex vivo intended for human application. Coupled with advanced custom analytics, we identify “drivers” (relatively few, but vital) genes which orchestrate T-cell activation and clonal expansion programming, versus “passengers” (relatively many, less critical) or resultant/downstream transcripts.Detailed analyses reveal that there is considerable variability between individual activated T cells, implying that cell state may undergo multiple stepwise transitions in a stochastic manner. Compared to interrogation of bulk T-cell populations (e.g., analyzed using RNA-Seq, microarrays, and Northern blotting), where heterogeneity in expression signals is attenuated by temporal and cell-cycle averaging, the genetic heterogeneity between cells in isogenic populations may be a reflection of fundamental phenomena such as transcriptional bursting. Our model describes cell state oscillation in tandem with transcriptional repressive (closed chromatin) and permissive conformations (open chromatin), versus simpler probabilistic models of transcription. T-cell variability can significantly impact upon individual cell behavior within seemly isogenic populations, and may be essential in molding survival and cytotoxicity within certain contexts, such as the rapidly changing and stressful tumor microenvironments. We find that lactate dehydrogenase A (LDHA) is a leading indicator for the metabolic adaptation during T-cell activation and together with other energetics related genes such pyruvate kinase isoform 2 (PKM2), can be harnessed to adjust our culture conditions during ex vivo expansion. These cellular fingerprints suggest useful ways for tuning the balance between oxidative and non-oxidative glucose metabolism to enhance the killing and thus therapeutic potential of our T cells. Our framework to harness catalogs of gene expression data into clinically-applicable insights can be adapted for meaningful characterization of other therapeutically-relevant source populations such as hematopoietic stem cells and reprogrammed NK cells. This is being reduced to practice by understanding the heterogeneity within and between genetically modified T-cell products generated for clinical use.

Single-cell RNA sequencing reveals regulatory patterns of self-antigen expression by medullary thymic epithelial cells (BA8P.162)

Abstract The crucial capability of T cells for discrimination between self and non-self peptides is based on rigorous negative selection of developing thymocytes by medullary thymic epithelial cells (mTECs). The mTECs purge autoreactive T cells by apparently stochastic expression of cell-type specific genes referred to as tissue-restricted antigens (TRAs). The expression of many TRAs is promoted by the autoimmune regulator (AIRE) protein, while others are induced by yet unknown factors. Despite its tremendous immunological significance, the regulation of TRA expression in mTECs is incompletely understood. Recently developed single-cell RNA-sequencing enables systematic dissection of such genome-wide patterns for the first time. Here we present analysis of 152 murine mTEC transcriptomes, revealing a regulatory hierarchy within the highly diverse population of TRA genes. We find that TRAs dependent on AIRE exhibit distinct transcriptional dynamics, with high degree of genomic clustering and characteristic transcriptional burst profiles. We show that expression of other, AIRE-independent TRAs, is likely to be secured by regulatory pathways promoting differentiation of the mTEC cells from the TEC progenitors. The TRA repertoire is further shaped by the maturation of the mTECs to MHCIIhigh state. We further show that certain subsets of TRAs are neglected by the mTEC population, and that mTEC-driven negative selection of thymocytes may have intrinsic leakiness.

CAST: An automated segmentation and tracking tool for the analysis of transcriptional kinetics from single-cell time-lapse recordings

Fluorescence and bioluminescence time-lapse imaging allows to investigate a vast range of cellular processes at single-cell or even subcellular resolution. In particular, time-lapse imaging can provide uniquely detailed information on the fine kinetics of transcription, as well as on biological oscillations such as the circadian and cell cycles. However, we face a paucity of automated methods to quantify time-lapse imaging data with single-cell precision, notably throughout multiple cell cycles. We developed CAST (Cell Automated Segmentation and Tracking platform) to automatically and robustly detect the position and size of cells or nuclei, quantify the corresponding light signals, while taking into account both cell divisions (lineage tracking) and migration events. We present here how CAST analyzes bioluminescence data from a short-lived transcriptional luciferase reporter. However, our flexible and modular implementation makes it easily adaptable to a wide variety of time-lapse recordings. We exemplify how CAST efficiently quantifies single-cell gene expression over multiple cell cycles using mouse NIH3T3 culture cells with a luminescence expression driven by the Bmal1 promoter, a central gene of the circadian oscillator. We further illustrate how such data can be used to quantify transcriptional bursting in conditions of lengthened circadian period, revealing thereby remarkably similar bursting signature compared to the endogenous circadian condition despite marked period lengthening. In summary, we establish CAST as novel tool for the efficient segmentation, signal quantification, and tracking of time-lapse images from mammalian cell culture.