Nuclear physics: quantitative single-cell approaches to nuclear organization and gene expression

The minimal intrinsic stochasticity of constitutively expressed eukaryotic genes is sub-Poissonian

Gene expression inherently gives rise to stochastic variation ("noise") in the production of gene products. Minimizing noise is crucial for ensuring reliable cellular functions. However, noise cannot be suppressed below a certain intrinsic limit. For constitutively expressed genes, this limit is typically assumed to be Poissonian noise, wherein the variance in mRNA numbers is equal to their mean. Here, we demonstrate that several cell division genes in fission yeast exhibit mRNA variances significantly below this limit. The reduced variance can be explained by a gene expression model incorporating multiple transcription and mRNA degradation steps. Notably, in this sub-Poissonian regime, distinct from Poissonian or super-Poissonian regimes, cytoplasmic noise is effectively suppressed through a higher mRNA export rate. Our findings redefine the lower limit of eukaryotic gene expression noise and uncover molecular requirements for achieving ultralow noise, which is expected to be important for vital cellular functions.

The minimal intrinsic stochasticity of constitutively expressed eukaryotic genes is sub-Poissonian

Stochastic variation in gene products ("noise") is an inescapable by-product of gene expression. Noise must be minimized to allow for the reliable execution of cellular functions. However, noise cannot be suppressed beyond an intrinsic lower limit. For constitutively expressed genes, this limit is believed to be Poissonian, meaning that the variance in mRNA numbers cannot be lower than their mean. Here, we show that several cell division genes in fission yeast have mRNA variances significantly below this limit, which cannot be explained by the classical gene expression model for low-noise genes. Our analysis reveals that multiple steps in both transcription and mRNA degradation are essential to explain this sub-Poissonian variance. The sub-Poissonian regime differs qualitatively from previously characterized noise regimes, a hallmark being that cytoplasmic noise is reduced when the mRNA export rate increases. Our study re-defines the lower limit of eukaryotic gene expression noise and identifies molecular requirements for ultra-low noise which are expected to support essential cell functions.

Enhancers, gene regulation, and genome organization

How transcriptional enhancers function to activate distant genes has been the subject of lively investigation for decades. "Enhancers, gene regulation, and genome organization" was the subject of a virtual meeting held November 16-17, 2020, under sponsorship of the National Cancer Institute (NCI), the National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS), and the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) at the National Institutes of Health (NIH). The goal of the meeting was to advance an understanding of how transcriptional enhancers function within the framework of the folded genome as we understand it, emphasizing how levels of organization may influence each other and may contribute to the spatiotemporal specification of transcription. Here we focus on broad questions about enhancer function that remain unsettled and that we anticipate will be central to work in this field going forward. Perforce, we cover contributions of only some speakers and apologize to other contributors in vital areas that we could not include because of space constraints.

Agonist binding directs dynamic competition among nuclear receptors for heterodimerization with retinoid X receptor

Retinoid X receptor (RXR) plays a pivotal role as a transcriptional regulator and serves as an obligatory heterodimerization partner for at least 20 other nuclear receptors (NRs). Given a potentially limiting/sequestered pool of RXR and simultaneous expression of several RXR partners, we hypothesized that NRs compete for binding to RXR and that this competition is directed by specific agonist treatment. Here, we tested this hypothesis on three NRs: peroxisome proliferator-activated receptor gamma (PPARγ), vitamin D receptor (VDR), and retinoic acid receptor alpha (RARα). The evaluation of competition relied on a nuclear translocation assay applied in a three-color imaging model system by detecting changes in heterodimerization between RXRα and one of its partners (NR1) in the presence of another competing partner (NR2). Our results indicated dynamic competition between the NRs governed by two mechanisms. First, in the absence of agonist treatment, there is a hierarchy of affinities between RXRα and its partners in the following order: RARα > PPARγ > VDR. Second, upon agonist treatment, RXRα favors the liganded partner. We conclude that recruiting RXRα by the liganded NR not only facilitates a stimulus-specific cellular response but also might impede other NR pathways involving RXRα.

Global and targeted approaches to single-cell transcriptome characterization

Analysing transcriptomes of cell populations is a standard molecular biology approach to understand how cells function. Recent methodological development has allowed performing similar experiments on single cells. This has opened up the possibility to examine samples with limited cell number, such as cells of the early embryo, and to obtain an understanding of heterogeneity within populations such as blood cell types or neurons. There are two major approaches for single-cell transcriptome analysis: quantitative reverse transcription PCR (RT-qPCR) on a limited number of genes of interest, or more global approaches targeting entire transcriptomes using RNA sequencing. RT-qPCR is sensitive, fast and arguably more straightforward, while whole-transcriptome approaches offer an unbiased perspective on a cell's expression status.

RNA Polymerase II cluster dynamics predict mRNA output in living cells

Protein clustering is a hallmark of genome regulation in mammalian cells. However, the dynamic molecular processes involved make it difficult to correlate clustering with functional consequences in vivo. 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-lived (~8 s) Pol II clusters correlate with basal mRNA output. During serum stimulation, a stereotyped increase in Pol II cluster lifetime correlates with a proportionate increase in the number of mRNAs synthesized. Our findings suggest that transient clustering of Pol II may constitute a pre-transcriptional regulatory event that predictably modulates nascent mRNA output.

DOI:http://dx.doi.org/10.7554/eLife.13617.001

Imaging Transcription: Past, Present, and Future

Transcription, the first step of gene expression, is exquisitely regulated in higher eukaryotes to ensure correct development and homeostasis. Traditional biochemical, genetic, and genomic approaches have proved successful at identifying factors, regulatory sequences, and potential pathways that modulate transcription. However, they typically only provide snapshots or population averages of the highly dynamic, stochastic biochemical processes involved in transcriptional regulation. Single-molecule live-cell imaging has, therefore, emerged as a complementary approach capable of circumventing these limitations. By observing sequences of molecular events in real time as they occur in their native context, imaging has the power to derive cause-and-effect relationships and quantitative kinetics to build predictive models of transcription. Ongoing progress in fluorescence imaging technology has brought new microscopes and labeling technologies that now make it possible to visualize and quantify the transcription process with single-molecule resolution in living cells and animals. Here we provide an overview of the evolution and current state of transcription imaging technologies. We discuss some of the important concepts they uncovered and present possible future developments that might solve long-standing questions in transcriptional regulation.

Single-site transcription rates through fitting of ensemble-averaged data from fluorescence recovery after photobleaching: a fat-tailed distribution

The stochastic process of gene expression is commonly controlled at the level of RNA transcription. The synthesis of messenger RNA (mRNA) is a multistep process, performed by RNA polymerase II and controlled by many transcription factors. Although mRNA transcription is intensively studied, real-time in vivo dynamic rates of a single transcribing polymerase are still not available. A popular method for examining transcription kinetics is the fluorescence recovery after photobleaching (FRAP) approach followed by kinetic modeling. Such analysis has yielded a surprisingly broad range of transcription rates. As transcription depends on many variables such as the chromatin state, binding and unbinding of transcription factors, and cell phase, transcription rates are stochastic variables. Thus, the distribution of rates is expected to follow Poissonian statistics, which does not coincide with the wide range of transcription rate results. Here we present an approach for analyzing FRAP data for single-gene transcription. We find that the transcription dynamics of a single gene can be described with a constant rate for all transcribing polymerases, while cell population transcription rates follow a fat-tailed distribution. This distribution suggests a larger probability for extreme rates than would be implied by normal distribution. Our analysis supports experimental results of transcription from two different promoters, and it explains the puzzling observation of extreme average rate values of transcription.

Eukaryotic transcriptional dynamics: from single molecules to cell populations

Transcriptional regulation is achieved through combinatorial interactions between regulatory elements in the human genome and a vast range of factors that modulate the recruitment and activity of RNA polymerase. Experimental approaches for studying transcription in vivo now extend from single-molecule techniques to genome-wide measurements. Parallel to these developments is the need for testable quantitative and predictive models for understanding gene regulation. These conceptual models must also provide insight into the dynamics of transcription and the variability that is observed at the single-cell level. In this Review, we discuss recent results on transcriptional regulation and also the models those results engender. We show how a non-equilibrium description informs our view of transcription by explicitly considering time- and energy-dependence at the molecular level.

Fluorescence fluctuation spectroscopy approaches to the study of receptors in live cells

Communication between cells and their environment, including other cells, is often mediated by cell surface receptors. Fluorescence methodologies are among the most important techniques used to study receptors and their interactions, and in the past decade, fluorescence fluctuation spectroscopy (FFS) approaches have been increasingly utilized. In this overview, we illustrate how diverse FFS approaches have been used to elucidate important aspects of receptor systems, including interactions of receptors with their ligands and receptor oligomerization and clustering. We also describe the most popular methods used to introduce fluorescent moieties into the biological systems. Finally, specific attention will be given to cell maintenance and transfection strategies especially as related to microscopy studies.

Measuring transcription dynamics in living cells using fluctuation analysis

Single-cell studies of gene regulation suggest that transcription dynamics play a fundamental role in determining expression heterogeneity within a population. In addition, the three-dimensional organization of the nucleus seems to both reflect and influence expression patterns in the cell. Therefore, to gain a holistic understanding of transcriptional regulation, it is necessary to develop methods for studying transcription of single genes in living cells with high spatial and temporal resolution. In this chapter, we describe a recently developed approach for visualizing and quantifying pre-mRNA synthesis at a single active gene in the nucleus. The approach is based on the high-affinity interaction between MS2/PP7 bacteriophage coat proteins and RNA hairpins which are transcribed by the gene of interest. The MS2/PP7 coat protein is fused to a fluorescent protein and binds the nascent mRNA, allowing for detection of single transcription events in the fluorescence microscope. By time-lapse fluorescence imaging and quantitative image analysis, one can generate a time trace of fluorescence intensity at the site of transcription. By temporal autocorrelation analysis, one can determine enzymatic activities of RNAP such as initiation rate and elongation rate. In this protocol, we summarize the experimental concept, design, and execution for real-time observation of transcription in living cells.

Transcription goes digital

Transcription is a complex process that integrates the state of the cell and its environment to generate adequate responses for cell fitness and survival. Recent microscopy experiments have been able to monitor transcription from single genes in individual cells. These observations have revealed two striking features: transcriptional activity can vary markedly from one cell to another, and is subject to large changes over time, sometimes within minutes. How the chromatin structure, transcription machinery assembly and signalling networks generate such patterns is still unclear. In this review, we present the techniques used to investigate transcription from single genes, introduce quantitative modelling tools, and discuss transcription mechanisms and their implications for gene expression regulation.

Complexity of RNA polymerase II elongation dynamics

Transcription of protein-coding genes by RNA polymerase II can be regulated at multiple points during the process of RNA synthesis, including initiation, elongation, and termination. In vivo data suggests that elongating polymerases exhibit heterogeneity throughout the gene body, suggestive of changes in elongation rate and/or pausing. Here, we review evidence from a variety of different experimental approaches for understanding regulation of transcription elongation. We compare steady-state measurements of nascent RNA density and polymerase occupancy to time-resolved measurements and point out areas of disagreement. Finally, we discuss future avenues of investigation for understanding this critically important step in gene regulation. This article is part of a Special Issue entitled: Chromatin in time and space.

What do expression dynamics tell us about the mechanism of transcription?

Single-cell microscopy studies have the potential to provide an unprecedented view of gene expression with exquisite spatial and temporal sensitivity. However, there is a challenge to connect the holistic cellular view with a reductionist biochemical view. In particular, experimental efforts to characterize the in vivo regulation of transcription have focused primarily on measurements of the dynamics of transcription factors and chromatin modifying factors. Such measurements have elucidated the transient nature of many nuclear interactions. In the past few years, experimental approaches have emerged that allow for interrogation of the output of transcription at the single-molecule, single-cell level. Here, I summarize the experimental results and models that aim to provide an integrated view of transcriptional regulation.

Spatial Organization and Dynamics of Transcription Elongation and Pre-mRNA Processing in Live Cells

During the last 30 years, systematic biochemical and functional studies have significantly expanded our knowledge of the transcriptional molecular components and the pre-mRNA processing machinery of the cell. However, our current understanding of how these functions take place spatiotemporally within the highly compartmentalized eukaryotic nucleus remains limited. Moreover, it is increasingly clear that “the whole is more than the sum of its parts” and that an understanding of the dynamic coregulation of genes is essential for fully characterizing complex biological phenomena and underlying diseases. Recent technological advances in light microscopy in addition to novel cell and molecular biology approaches have led to the development of new tools, which are being used to address these questions and may contribute to achieving an integrated and global understanding of how the genome works at a cellular level. Here, we review major hallmarks and novel insights in RNA polymerase II activity and pre-mRNA processing in the context of nuclear organization, as well as new concepts and challenges arising from our ability to gather extensive dynamic information at the single-cell resolution.