Real-time observation of transcription initiation and elongation on an endogenous yeast gene

Exact and efficient hybrid Monte Carlo algorithm for accelerated Bayesian inference of gene expression models from snapshots of single-cell transcripts

Single cells exhibit a significant amount of variability in transcript levels, which arises from slow, stochastic transitions between gene expression states. Elucidating the nature of these states and understanding how transition rates are affected by different regulatory mechanisms require state-of-the-art methods to infer underlying models of gene expression from single cell data. A Bayesian approach to statistical inference is the most suitable method for model selection and uncertainty quantification of kinetic parameters using small data sets. However, this approach is impractical because current algorithms are too slow to handle typical models of gene expression. To solve this problem, we first show that time-dependent mRNA distributions of discrete-state models of gene expression are dynamic Poisson mixtures, whose mixing kernels are characterized by a piecewise deterministic Markov process. We combined this analytical result with a kinetic Monte Carlo algorithm to create a hybrid numerical method that accelerates the calculation of time-dependent mRNA distributions by 1000-fold compared to current methods. We then integrated the hybrid algorithm into an existing Monte Carlo sampler to estimate the Bayesian posterior distribution of many different, competing models in a reasonable amount of time. We demonstrate that kinetic parameters can be reasonably constrained for modestly sampled data sets if the model is known a priori. If there are many competing models, Bayesian evidence can rigorously quantify the likelihood of a model relative to other models from the data. We demonstrate that Bayesian evidence selects the true model and outperforms approximate metrics typically used for model selection.

Distribution of Initiation Times Reveals Mechanisms of Transcriptional Regulation in Single Cells

Transcription is the dominant point of control of gene expression. Biochemical studies have revealed key molecular components of transcription and their interactions, but the dynamics of transcription initiation in cells is still poorly understood. This state of affairs is being remedied with experiments that observe transcriptional dynamics in single cells using fluorescent reporters. Quantitative information about transcription initiation dynamics can also be extracted from experiments that use electron micrographs of RNA polymerases caught in the act of transcribing a gene (Miller spreads). Inspired by these data, we analyze a general stochastic model of transcription initiation and elongation and compute the distribution of transcription initiation times. We show that different mechanisms of initiation leave distinct signatures in the distribution of initiation times that can be compared to experiments. We analyze published data from micrographs of RNA polymerases transcribing ribosomal RNA genes in Escherichia coli and compare the observed distributions of interpolymerase distances with the predictions from previously hypothesized mechanisms for the regulation of these genes. Our analysis demonstrates the potential of measuring the distribution of time intervals between initiation events as a probe for dissecting mechanisms of transcription initiation in live cells.

Translation imaging of single mRNAs in established cell lines and primary cultured neurons

The central dogma of molecular biology reaches a crescendo at its final step: the translation of an mRNA into its corresponding protein product. This process is highly regulated both spatially and temporally, requiring techniques to interrogate the subcellular translational status of mRNAs in both living and fixed cells. Single-molecule imaging of nascent peptides (SINAPs) and related techniques allow us to study this fundamental process for single mRNAs in live cells. These techniques enable researchers to address previously intractable questions in the central dogma, such as the origin of stochastic translational control and the role of local translation in highly polarized cells. In this review, we present the methodology and the theoretical framework for conducting studies using SINAPs in both established cell lines and primary cultured neurons.

Single-Molecule Nanoscopy Elucidates RNA Polymerase II Transcription at Single Genes in Live Cells

Transforming the vast knowledge from genetics, biochemistry, and structural biology into detailed molecular descriptions of biological processes inside cells remains a major challenge-one in sore need of better imaging technologies. For example, transcription involves the complex interplay between RNA polymerase II (Pol II), regulatory factors (RFs), and chromatin, but visualizing these dynamic molecular transactions in their native intracellular milieu remains elusive. Here, we zoom into single tagged genes using nanoscopy techniques, including an active target-locking, ultra-sensitive system that enables single-molecule detection in addressable sub-diffraction volumes, within crowded intracellular environments. We image, track, and quantify Pol II with single-molecule resolution, unveiling its dynamics during the transcription cycle. Further probing multiple functionally linked events-RF-chromatin interactions, Pol II dynamics, and nascent transcription kinetics-reveals detailed operational parameters of gene-regulatory mechanisms hitherto-unseen in vivo. Our approach sets the stage for single-molecule studies of complex molecular processes in live cells.

Plasmids for Independently Tunable, Low-Noise Expression of Two Genes

Microbiologists often express foreign proteins in bacteria in order study them or to use bacteria as a microbial factory. Usually, this requires controlling the number of foreign proteins expressed in each cell, but for many common protein expression systems, it is difficult to “tune” protein expression without large cell-to-cell variation in expression levels (called “noise” in protein expression). This work describes two protein expression systems that can be combined in the same cell, with tunable expression levels and very low protein expression noise. One new system was used to detect single mRNA molecules by fluorescence microscopy, and the two systems were shown to be independent of each other. These protein expression systems may be useful in any experiment or biotechnology application that can be improved with low protein expression noise.

Some microbiology experiments and biotechnology applications can be improved if it is possible to tune the expression of two different genes at the same time with cell-to-cell variation at or below the level of genes constitutively expressed from the chromosome (the “extrinsic noise limit”). This was recently achieved for a single gene by exploiting negative autoregulation by the tetracycline repressor (TetR) and bicistronic gene expression to reduce gene expression noise. We report new plasmids that use the same principles to achieve simultaneous, low-noise expression for two genes in Escherichia coli. The TetR system was moved to a compatible plasmid backbone, and a system based on the lac repressor (LacI) was found to also exhibit gene expression noise below the extrinsic noise limit. We characterized gene expression mean and noise across the range of induction levels for these plasmids, applied the LacI system to tune expression for single-molecule mRNA detection under two different growth conditions, and showed that two plasmids can be cotransformed to independently tune expression of two different genes.

IMPORTANCE Microbiologists often express foreign proteins in bacteria in order study them or to use bacteria as a microbial factory. Usually, this requires controlling the number of foreign proteins expressed in each cell, but for many common protein expression systems, it is difficult to “tune” protein expression without large cell-to-cell variation in expression levels (called “noise” in protein expression). This work describes two protein expression systems that can be combined in the same cell, with tunable expression levels and very low protein expression noise. One new system was used to detect single mRNA molecules by fluorescence microscopy, and the two systems were shown to be independent of each other. These protein expression systems may be useful in any experiment or biotechnology application that can be improved with low protein expression noise.

Molecular Engineering of the TGF-β Signaling Pathway

Transforming growth factor beta (TGF-β) is an important growth factor that plays essential roles in regulating tissue development and homeostasis. Dysfunction of TGF-β signaling is a hallmark of many human diseases. Therefore, targeting TGF-β signaling presents broad therapeutic potential. Since the discovery of the TGF-β ligand, a collection of engineered signaling proteins have been developed to probe and manipulate TGF-β signaling responses. In this review, we highlight recent progress in the engineering of TGF-β signaling for different applications and discuss how molecular engineering approaches can advance our understanding of this important pathway. In addition, we provide a future outlook on the opportunities and challenges in the engineering of the TGF-β signaling pathway from a quantitative perspective.

Live-cell imaging reveals the interplay between transcription factors, nucleosomes, and bursting

Transcription factors show rapid and reversible binding to chromatin in living cells, and transcription occurs in sporadic bursts, but how these phenomena are related is unknown. Using a combination of in vitro and in vivo single-molecule imaging approaches, we directly correlated binding of the Gal4 transcription factor with the transcriptional bursting kinetics of the Gal4 target genes GAL3 and GAL10 in living yeast cells. We find that Gal4 dwell time sets the transcriptional burst size. Gal4 dwell time depends on the affinity of the binding site and is reduced by orders of magnitude by nucleosomes. Using a novel imaging platform called orbital tracking, we simultaneously tracked transcription factor binding and transcription at one locus, revealing the timing and correlation between Gal4 binding and transcription. Collectively, our data support a model in which multiple RNA polymerases initiate transcription during one burst as long as the transcription factor is bound to DNA, and bursts terminate upon transcription factor dissociation.

Illuminating Genomic Dark Matter with RNA Imaging

In the postgenomic era, it is clear that the human genome encodes thousands of long noncoding RNAs (lncRNAs). Along the way, RNA imaging (e.g., RNA fluorescence in situ hybridization [RNA-FISH]) has been instrumental in identifying powerful roles for lncRNAs based on their subcellular localization patterns. Here, we explore how RNA imaging technologies have shed new light on how, when, and where lncRNAs may play functional roles. Specifically, we will synthesize the underlying principles of RNA imaging techniques by exploring several landmark lncRNA imaging studies that have illuminated key insights into lncRNA biology.

Ageing and sources of transcriptional heterogeneity

Cellular heterogeneity is an important contributor to biological function and is employed by cells, tissues and organisms to adapt, compensate, respond, defend and/or regulate specific processes. Research over the last decades has revealed that transcriptional noise is a major driver for cell-to-cell variability. In this review we will discuss sources of transcriptional variability, in particular bursting of gene expression and how it could contribute to cellular states and fate decisions. We will highlight recent developments in single cell sequencing technologies that make it possible to address cellular heterogeneity in unprecedented detail. Finally, we will review recent literature, in which these new technologies are harnessed to address pressing questions in the field of ageing research, such as transcriptional noise and cellular heterogeneity in the course of ageing.

The Drosophila Pioneer Factor Zelda Modulates the Nuclear Microenvironment of a Dorsal Target Enhancer to Potentiate Transcriptional Output

Connecting the developmental patterning of tissues to the mechanistic control of RNA polymerase II remains a long-term goal of developmental biology. Many key elements have been identified in the establishment of spatial-temporal control of transcription in the early Drosophila embryo, a model system for transcriptional regulation. The dorsal-ventral axis of the Drosophila embryo is determined by the graded distribution of Dorsal (Dl), a homolog of the nuclear factor κB (NF-κB) family of transcriptional activators found in humans [1, 2]. A second maternally deposited factor, Zelda (Zld), is uniformly distributed in the embryo and is thought to act as a pioneer factor, increasing enhancer accessibility for transcription factors, such as Dl [3-9]. Here, we utilized the MS2 live imaging system to evaluate the expression of the Dl target gene short gastrulation (sog) to better understand how a pioneer factor affects the kinetic parameters of transcription. Our experiments indicate that Zld modifies probability of activation, the timing of this activation, and the rate at which transcription occurs. Our results further show that this effective rate increase is due to an increased accumulation of Dl at the site of transcription, suggesting that transcription factor "hubs" induced by Zld [10] functionally regulate transcription.

Physical principles and functional consequences of nuclear compartmentalization in budding yeast

One striking feature of eukaryotic nuclei is the existence of discrete regions, in which specific factors concentrate while others are excluded, thus forming microenvironments with different molecular compositions and biological functions. These domains are often referred to as subcompartments even though they are not membrane enclosed. Despite their functional importance the physical nature of these structures remains largely unknown. Here, we describe how the Saccharomyces cerevisiae nucleus is compartmentalized and discuss possible physical models underlying the formation and maintenance of chromatin associated subcompartments. Focusing on three particular examples, the nucleolus, silencing foci, and repair foci, we discuss the biological implications of these different models as well as possible approaches to challenge them in living cells.

Quantitative relationships between SMAD dynamics and target gene activation kinetics in single live cells

The transduction of extracellular signals through signaling pathways that culminate in a transcriptional response is central to many biological processes. However, quantitative relationships between activities of signaling pathway components and transcriptional output of target genes remain poorly explored. Here we developed a dual bioluminescence imaging strategy allowing simultaneous monitoring of nuclear translocation of the SMAD4 and SMAD2 transcriptional activators upon TGF-β stimulation, and the transcriptional response of the endogenous connective tissue growth factor (ctgf) gene. Using cell lines allowing to vary exogenous SMAD4/2 expression levels, we performed quantitative measurements of the temporal profiles of SMAD4/2 translocation and ctgf transcription kinetics in hundreds of individual cells at high temporal resolution. We found that while nuclear translocation efficiency had little impact on initial ctgf transcriptional activation, high total cellular SMAD4 but not SMAD2 levels increased the probability of cells to exhibit a sustained ctgf transcriptional response. The approach we present here allows time-resolved single cell quantification of transcription factor dynamics and transcriptional responses and thereby sheds light on the quantitative relationship between SMADs and target gene responses.

Advances in CRISPR-Cas systems for RNA targeting, tracking and editing

Clustered regularly interspaced short palindromic repeat (CRISPR)/CRISPR-associated protein (Cas) systems, especially type II (Cas9) systems, have been widely used in gene/genome targeting. Modifications of Cas9 enable these systems to become platforms for precise DNA manipulations. However, the utilization of CRISPR-Cas systems in RNA targeting remains preliminary. The discovery of type VI CRISPR-Cas systems (Cas13) shed light on RNA-guided RNA targeting. Cas13d, the smallest Cas13 protein, with a length of only ~930 amino acids, is a promising platform for RNA targeting compatible with viral delivery systems. Much effort has also been made to develop Cas9, Cas13a and Cas13b applications for RNA-guided RNA targeting. The discovery of new RNA-targeting CRISPR-Cas systems as well as the development of RNA-targeting platforms with Cas9 and Cas13 will promote RNA-targeting technology substantially. Here, we review new advances in RNA-targeting CRISPR-Cas systems as well as advances in applications of these systems in RNA targeting, tracking and editing. We also compare these Cas protein-based technologies with traditional technologies for RNA targeting, tracking and editing. Finally, we discuss remaining questions and prospects for the future.

Writing a wrong: Coupled RNA polymerase II transcription and RNA quality control

Processing and maturation of precursor RNA species is coupled to RNA polymerase II transcription. Co-transcriptional RNA processing helps to ensure efficient and proper capping, splicing, and 3' end processing of different RNA species to help ensure quality control of the transcriptome. Many improperly processed transcripts are not exported from the nucleus, are restricted to the site of transcription, and are in some cases degraded, which helps to limit any possibility of aberrant RNA causing harm to cellular health. These critical quality control pathways are regulated by the highly dynamic protein-protein interaction network at the site of transcription. Recent work has further revealed the extent to which the processes of transcription and RNA processing and quality control are integrated, and how critically their coupling relies upon the dynamic protein interactions that take place co-transcriptionally. This review focuses specifically on the intricate balance between 3' end processing and RNA decay during transcription termination. This article is categorized under: RNA Turnover and Surveillance > Turnover/Surveillance Mechanisms RNA Processing > 3' End Processing RNA Processing > Splicing Mechanisms RNA Processing > Capping and 5' End Modifications.

Thirty years of neuroendocrinology: Technological advances pave the way for molecular discovery

Since the 1950s, the systems level interactions between the hypothalamus, pituitary and end organs such as the adrenal, thyroid and gonads have been well known; however, it is only over the last three decades that advances in molecular biology and information technology have provided a tremendous expansion of knowledge at the molecular level. Neuroendocrinology has benefitted from developments in molecular genetics, epigenetics and epigenomics, and most recently optogenetics and pharmacogenetics. This has enabled a new understanding of gene regulation, transcription, translation and post-translational regulation, which should help direct the development of drugs to treat neuroendocrine-related diseases.

Dynamics of transcriptional enhancers and chromosome topology in gene regulation

Transcriptional enhancers are regulatory DNAs that instruct when and where genes should be transcribed in response to a variety of intrinsic and external signals. They contain a cluster of binding sites for sequence-specific transcription factors and co-activators to determine the spatiotemporal specificity of gene activities during development. Enhancers are often positioned in distal locations from their target promoters. In some cases, they work over a million base pairs or more. In the traditional view, enhancers have been thought to stably interact with promoters in a targeted manner. However, quantitative imaging studies provide a far more dynamic picture of enhancer action. Moreover, recent Hi-C methods suggest that regulatory interactions are dynamically regulated by the higher-order chromosome topology. In this review, we summarize the emerging findings in the field and propose that assembly of "transcription hubs" in the context of 3D genome structure plays an important role in transcriptional regulation.

An Optogenetic Platform for Real-Time, Single-Cell Interrogation of Stochastic Transcriptional Regulation

Transcription is a highly regulated and inherently stochastic process. The complexity of signal transduction and gene regulation makes it challenging to analyze how the dynamic activity of transcriptional regulators affects stochastic transcription. By combining a fast-acting, photo-regulatable transcription factor with nascent RNA quantification in live cells and an experimental setup for precise spatiotemporal delivery of light inputs, we constructed a platform for the real-time, single-cell interrogation of transcription in Saccharomyces cerevisiae. We show that transcriptional activation and deactivation are fast and memoryless. By analyzing the temporal activity of individual cells, we found that transcription occurs in bursts, whose duration and timing are modulated by transcription factor activity. Using our platform, we regulated transcription via light-driven feedback loops at the single-cell level. Feedback markedly reduced cell-to-cell variability and led to qualitative differences in cellular transcriptional dynamics. Our platform establishes a flexible method for studying transcriptional dynamics in single cells.

Recent advancement of light-based single-molecule approaches for studying biomolecules

Recent advances in single-molecule techniques have led to new discoveries in analytical chemistry, biophysics, and medicine. Understanding the structure and behavior of single biomolecules provides a wealth of information compared to studying large ensembles. However, developing single-molecule techniques is challenging and requires advances in optics, engineering, biology, and chemistry. In this paper, we will review the state of the art in single-molecule applications with a focus over the last few years of development. The advancements covered will mainly include light-based in vitro methods, and we will discuss the fundamentals of each with a focus on the platforms themselves. We will also summarize their limitations and current and future applications to the wider biological and chemical fields. This article is categorized under: Laboratory Methods and Technologies > Imaging Laboratory Methods and Technologies > Macromolecular Interactions, Methods Analytical and Computational Methods > Analytical Methods.

Progress and Challenges for Live-cell Imaging of Genomic Loci Using CRISPR-based Platforms

Chromatin conformation, localization, and dynamics are crucial regulators of cellular behaviors. Although fluorescence in situ hybridization-based techniques have been widely utilized for investigating chromatin architectures in healthy and diseased states, the requirement for cell fixation precludes the comprehensive dynamic analysis necessary to fully understand chromatin activities. This has spurred the development and application of a variety of imaging methodologies for visualizing single chromosomal loci in the native cellular context. In this review, we describe currently-available approaches for imaging single genomic loci in cells, with special focus on clustered regularly interspaced short palindromic repeats (CRISPR)-based imaging approaches. In addition, we discuss some of the challenges that limit the application of CRISPR-based genomic imaging approaches, and potential solutions to address these challenges. We anticipate that, with continued refinement of CRISPR-based imaging techniques, significant understanding can be gained to help decipher chromatin activities and their relevance to cellular physiology and pathogenesis.

Enhancer Histone Acetylation Modulates Transcriptional Bursting Dynamics of Neuronal Activity-Inducible Genes

Neuronal activity-inducible gene transcription correlates with rapid and transient increases in histone acetylation at promoters and enhancers of activity-regulated genes. Exactly how histone acetylation modulates transcription of these genes has remained unknown. We used single-cell in situ transcriptional analysis to show that Fos and Npas4 are transcribed in stochastic bursts in mouse neurons and that membrane depolarization increases mRNA expression by increasing burst frequency. We then expressed dCas9-p300 or dCas9-HDAC8 fusion proteins to mimic or block activity-induced histone acetylation locally at enhancers. Adding histone acetylation increased Fos transcription by prolonging burst duration and resulted in higher Fos protein levels and an elevation of resting membrane potential. Inhibiting histone acetylation reduced Fos transcription by reducing burst frequency and impaired experience-dependent Fos protein induction in the hippocampus in vivo. Thus, activity-inducible histone acetylation tunes the transcriptional dynamics of experience-regulated genes to affect selective changes in neuronal gene expression and cellular function.

Analysis of Cell Lineage Trees by Exact Bayesian Inference Identifies Negative Autoregulation of Nanog in Mouse Embryonic Stem Cells

Many cellular effectors of pluripotency are dynamically regulated. In principle, regulatory mechanisms can be inferred from single-cell observations of effector activity across time. However, rigorous inference techniques suitable for noisy, incomplete, and heterogeneous data are lacking. Here, we introduce stochastic inference on lineage trees (STILT), an algorithm capable of identifying stochastic models that accurately describe the quantitative behavior of cell fate markers observed using time-lapse microscopy data collected from proliferating cell populations. STILT performs exact Bayesian parameter inference and stochastic model selection using a particle-filter-based algorithm. We use STILT to investigate the autoregulation of Nanog, a heterogeneously expressed core pluripotency factor, in mouse embryonic stem cells. STILT rejects the possibility of positive Nanog autoregulation with high confidence; instead, model predictions indicate weak negative feedback. We use STILT for rational experimental design and validate model predictions using novel experimental data. STILT is available for download as an open source framework from http://www.imsb.ethz.ch/research/claassen/Software/stilt---stochastic-inference-on-lineage-trees.html.

Lighting Up Gene Activation in Living Drosophila Embryos

With its rapid development, ease of collection, and the presence of a unique layer of nuclei located close to the surface, the Drosophila syncytial embryo is ideally suited to study the establishment of gene expression patterns during development. Recent improvements in RNA labeling technologies and confocal microscopy allow for visualizing gene activation and quantifying transcriptional dynamics in living Drosophila embryos. Here we review the available tools for mRNA fluorescent labeling and detection in live embryos and precisely describe the overall procedure, from design to mounting and confocal imaging.

Single-molecule imaging of transcription at damaged chromatin

How DNA double-strand breaks (DSBs) affect ongoing transcription remains elusive due to the lack of single-molecule resolution tools directly measuring transcription dynamics upon DNA damage. Here, we established new reporter systems that allow the visualization of individual nascent RNAs with high temporal and spatial resolution upon the controlled induction of a single DSB at two distinct chromatin locations: a promoter-proximal (PROP) region downstream the transcription start site and a region within an internal exon (EX2). Induction of a DSB resulted in a rapid suppression of preexisting transcription initiation regardless of the genomic location. However, while transcription was irreversibly suppressed upon a PROP DSB, damage at the EX2 region drove the formation of promoter-like nucleosome-depleted regions and transcription recovery. Two-color labeling of transcripts at sequences flanking the EX2 lesion revealed bidirectional break-induced transcription initiation. Transcriptome analysis further showed pervasive bidirectional transcription at endogenous intragenic DSBs. Our data provide a novel framework for interpreting the reciprocal interactions between transcription and DNA damage at distinct chromatin regions.

Live-Cell Imaging of mRNP-NPC Interactions in Budding Yeast

Single-molecule resolution imaging has become an important tool in the study of cell biology. Aptamer-based approaches (e.g., MS2 and PP7) allow for detection of single RNA molecules in living cells and have been used to study various aspects of mRNA metabolism, including mRNP nuclear export. Here we outline an imaging protocol for the study of interactions between mRNPs and nuclear pore complexes (NPCs) in the yeast S. cerevisiae, including mRNP export. We describe in detail the steps that allow for high-resolution live-cell mRNP imaging and measurement of mRNP interactions with NPCs using simultaneous two-color imaging. Our protocol discusses yeast strain construction, choice of marker proteins to label the nuclear pore complex, as well as imaging conditions that allow high signal-to-noise data acquisition. Moreover, we describe various aspects of postacquisition image analysis for single molecule tracking and image registration allowing for the characterization of mRNP-NPC interactions.

Intrinsic Dynamics of a Human Gene Reveal the Basis of Expression Heterogeneity

Transcriptional regulation in metazoans occurs through long-range genomic contacts between enhancers and promoters, and most genes are transcribed in episodic "bursts" of RNA synthesis. To understand the relationship between these two phenomena and the dynamic regulation of genes in response to upstream signals, we describe the use of live-cell RNA imaging coupled with Hi-C measurements and dissect the endogenous regulation of the estrogen-responsive TFF1 gene. Although TFF1 is highly induced, we observe short active periods and variable inactive periods ranging from minutes to days. The heterogeneity in inactive times gives rise to the widely observed "noise" in human gene expression and explains the distribution of protein levels in human tissue. We derive a mathematical model of regulation that relates transcription, chromosome structure, and the cell's ability to sense changes in estrogen and predicts that hypervariability is largely dynamic and does not reflect a stable biological state.

Imaging the Life and Death of mRNAs in Single Cells

RNA plays a central role in gene expression from its transcription in the nucleus through translation and degradation in the cytoplasm. Technological advances in fluorescent microscopy and labeling methodologies have made it possible to detect single molecules of RNA in both fixed and living cells. Here, we focus on the recent developments in RNA imaging that have allowed quantitatively measuring the lives of individual transcripts from birth to death and all the events in between in single cells and tissues. Direct observation of RNAs within their native cellular environment has revealed a complex layer of spatial and temporal regulation that has profoundly impacted our understanding of RNA biology.

Single-Molecule Tracking Approaches to Protein Synthesis Kinetics in Living Cells

Decades of traditional biochemistry, structural approaches, and, more recently, single-molecule-based in vitro techniques have provided us with an astonishingly detailed understanding of the molecular mechanism of ribosome-catalyzed protein synthesis. However, in order to understand these details in the context of cell physiology and population biology, new techniques to probe the dynamics of molecular processes inside the cell are needed. Recent years' development in super-resolved fluorescence microscopy has revolutionized imaging of intracellular processes, and we now have the possibility to directly peek into the microcosm of biomolecules in their native environment. In this Perspective, we discuss how these methods are currently being applied and further developed to study the kinetics of protein synthesis directly inside living cells.

Quantifying Single mRNA Translation Kinetics in Living Cells

One of the last hurdles to quantifying the full central dogma of molecular biology in living cells with single-molecule resolution has been the imaging of single messenger RNA (mRNA) translation. Here we describe how recent advances in protein tagging and imaging technologies are being used to precisely visualize and quantify the synthesis of nascent polypeptide chains from single mRNA in living cells. We focus on recent applications of repeat-epitope tags and describe how they enable quantification of single mRNA ribosomal densities, translation initiation and elongation rates, and translation site mobility and higher-order structure. Together with complementary live-cell assays to monitor translation using fast-maturing fluorophores and mRNA-binding protein knockoff, single-molecule studies are beginning to uncover striking and unexpected heterogeneity in gene expression at the level of translation.

Single-Molecule Kinetics in Living Cells

In the past decades, advances in microscopy have made it possible to study the dynamics of individual biomolecules in vitro and resolve intramolecular kinetics that would otherwise be hidden in ensemble averages. More recently, single-molecule methods have been used to image, localize, and track individually labeled macromolecules in the cytoplasm of living cells, allowing investigations of intermolecular kinetics under physiologically relevant conditions. In this review, we illuminate the particular advantages of single-molecule techniques when studying kinetics in living cells and discuss solutions to specific challenges associated with these methods.

Nascent RNA kinetics: Transient and steady state behavior of models of transcription

Regulation of transcription is a vital process in cells, but mechanistic details of this regulation still remain elusive. The dominant approach to unravel the dynamics of transcriptional regulation is to first develop mathematical models of transcription and then experimentally test the predictions these models make for the distribution of mRNA and protein molecules at the individual cell level. However, these measurements are affected by a multitude of downstream processes which make it difficult to interpret the measurements. Recent experimental advancements allow for counting the nascent mRNA number of a gene as a function of time at the single-cell level. These measurements closely reflect the dynamics of transcription. In this paper, we consider a general mechanism of transcription with stochastic initiation and deterministic elongation and probe its impact on the temporal behavior of nascent RNA levels. Using techniques from queueing theory, we derive exact analytical expressions for the mean and variance of the nascent RNA distribution as functions of time. We apply these analytical results to obtain the mean and variance of nascent RNA distribution for specific models of transcription. These models of initiation exhibit qualitatively distinct transient behaviors for both the mean and variance which further allows us to discriminate between them. Stochastic simulations confirm these results. Overall the analytical results presented here provide the necessary tools to connect mechanisms of transcription initiation to single-cell measurements of nascent RNA.

Pulsatile inputs achieve tunable attenuation of gene expression variability and graded multi-gene regulation

Many natural transcription factors are regulated in a pulsatile fashion, but it remains unknown whether synthetic gene expression systems can benefit from such dynamic regulation. Here we find, using a fast-acting, optogenetic transcription factor in Saccharomyces cerevisiae, that dynamic pulsatile signals reduce cell-to-cell variability in gene expression. We then show that by encoding such signals into a single input, expression mean and variability can be independently tuned. Further, we construct a light-responsive promoter library and demonstrate how pulsatile signaling also enables graded multi-gene regulation at fixed expression ratios, despite differences in promoter dose-response characteristics. Pulsatile regulation can thus lead to beneficial functional behaviors in synthetic biological systems, which previously required laborious optimization of genetic parts or the construction of synthetic gene networks.

Dynamic interplay between enhancer-promoter topology and gene activity

A long-standing question in gene regulation is how remote enhancers communicate with their target promoters, and specifically how chromatin topology dynamically relates to gene activation. Here, we combine genome editing and multi-color live imaging to simultaneously visualize physical enhancer-promoter interaction and transcription at the single-cell level in Drosophila embryos. By examining transcriptional activation of a reporter by the endogenous even-skipped enhancers, which are located 150 kb away, we identify three distinct topological conformation states and measure their transition kinetics. We show that sustained proximity of the enhancer to its target is required for activation. Transcription in turn affects the three-dimensional topology as it enhances the temporal stability of the proximal conformation and is associated with further spatial compaction. Furthermore, the facilitated long-range activation results in transcriptional competition at the locus, causing corresponding developmental defects. Our approach offers quantitative insight into the spatial and temporal determinants of long-range gene regulation and their implications for cellular fates.

Distribution shapes govern the discovery of predictive models for gene regulation

Systems biology seeks to combine experiments with computation to predict biological behaviors. However, despite tremendous data and knowledge, biological models make less-accurate predictions compared with other fields. By analyzing single-cell, single-molecule measurements of mRNA during yeast stress response, we explore why and how the shapes of experimental distributions control prediction accuracy. We show how asymmetric data distributions with long tails cause standard modeling approaches to yield excellent fits but make meaningless predictions. We show how these biases arise from the violation of fundamental assumptions in standard modeling approaches. We demonstrate how advanced computational tools solve this dilemma and achieve predictive understanding of spatiotemporal mechanisms of transcription control including RNA polymerase initiation and elongation and mRNA accumulation, transport, and decay.

Despite substantial experimental and computational efforts, mechanistic modeling remains more predictive in engineering than in systems biology. The reason for this discrepancy is not fully understood. One might argue that the randomness and complexity of biological systems are the main barriers to predictive understanding, but these issues are not unique to biology. Instead, we hypothesize that the specific shapes of rare single-molecule event distributions produce substantial yet overlooked challenges for biological models. We demonstrate why modern statistical tools to disentangle complexity and stochasticity, which assume normally distributed fluctuations or enormous datasets, do not apply to the discrete, positive, and nonsymmetric distributions that characterize mRNA fluctuations in single cells. As an example, we integrate single-molecule measurements and advanced computational analyses to explore mitogen-activated protein kinase induction of multiple stress response genes. Through systematic analyses of different metrics to compare the same model to the same data, we elucidate why standard modeling approaches yield nonpredictive models for single-cell gene regulation. We further explain how advanced tools recover precise, reproducible, and predictive understanding of transcription regulation mechanisms, including gene activation, polymerase initiation, elongation, mRNA accumulation, spatial transport, and decay.

Kaposi's Sarcoma-Associated Herpesvirus mRNA Accumulation in Nuclear Foci Is Influenced by Viral DNA Replication and Viral Noncoding Polyadenylated Nuclear RNA

Kaposi's sarcoma-associated herpesvirus (KSHV), like other herpesviruses, replicates within the nuclei of its human cell host and hijacks host machinery for expression of its genes. The activities that culminate in viral DNA synthesis and assembly of viral proteins into capsids physically concentrate in nuclear areas termed viral replication compartments. We sought to better understand the spatiotemporal regulation of viral RNAs during the KSHV lytic phase by examining and quantifying the subcellular localization of select viral transcripts. We found that viral mRNAs, as expected, localized to the cytoplasm throughout the lytic phase. However, dependent on active viral DNA replication, viral transcripts also accumulated in the nucleus, often in foci in and around replication compartments, independent of the host shutoff effect. Our data point to involvement of the viral long noncoding polyadenylated nuclear (PAN) RNA in the localization of an early, intronless viral mRNA encoding ORF59-58 to nuclear foci that are associated with replication compartments.IMPORTANCE Late in the lytic phase, mRNAs from Kaposi's sarcoma-associated herpesvirus accumulate in the host cell nucleus near viral replication compartments, centers of viral DNA synthesis and virion production. This work contributes spatiotemporal data on herpesviral mRNAs within the lytic host cell and suggests a mechanism for viral RNA accumulation. Our findings indicate that the mechanism is independent of the host shutoff effect and splicing but dependent on active viral DNA synthesis and in part on the viral noncoding RNA, PAN RNA. PAN RNA is essential for the viral life cycle, and its contribution to the nuclear accumulation of viral messages may facilitate propagation of the virus.

Role of Kip2 during early mitosis - impact on spindle pole body separation and chromosome capture

Mitotic spindle dynamics are regulated during the cell cycle by microtubule motor proteins. In Saccharomyces cerevisiae, one such protein is Kip2p, a plus-end motor that regulates the polymerization and stability of cytoplasmic microtubules (cMTs). Kip2p levels are regulated during the cell cycle, and its overexpression leads to the formation of hyper-elongated cMTs. To investigate the significance of varying Kip2p levels during the cell cycle and the hyper-elongated cMTs, we overexpressed KIP2 in the G1 phase and examined the effects on the separation of spindle pole bodies (SPBs) and chromosome segregation. Our results show that failure to regulate the cMT lengths during G1-S phase prevents the separation of SPBs. This, in turn, affects chromosome capture and leads to the activation of spindle assembly checkpoint (SAC) and causes mitotic arrest. These defects could be rescued by either the inactivation of checkpoint components or by co-overexpression of CIN8, which encodes a motor protein that elongates inter-polar microtubules (ipMTs). Hence, we propose that the maintenance of Kip2p level and cMT lengths during early cell division is important to ensure coordination between SPB separation and chromosome capture by kinetochore microtubules (kMTs).

Imaging mRNA In Vivo, from Birth to Death

RNA is the fundamental information transfer system in the cell. The ability to follow single messenger RNAs (mRNAs) from transcription to degradation with fluorescent probes gives quantitative information about how the information is transferred from DNA to proteins. This review focuses on the latest technological developments in the field of single-mRNA detection and their usage to study gene expression in both fixed and live cells. By describing the application of these imaging tools, we follow the journey of mRNA from transcription to decay in single cells, with single-molecule resolution. We review current theoretical models for describing transcription and translation that were generated by single-molecule and single-cell studies. These methods provide a basis to study how single-molecule interactions generate phenotypes, fundamentally changing our understating of gene expression regulation.

Cell-Cycle Modulation of Transcription Termination Factor Sen1

Many non-coding transcripts (ncRNA) generated by RNA polymerase II in S. cerevisiae are terminated by the Nrd1-Nab3-Sen1 complex. However, Sen1 helicase levels are surprisingly low compared with Nrd1 and Nab3, raising questions regarding how ncRNA can be terminated in an efficient and timely manner. We show that Sen1 levels increase during the S and G2 phases of the cell cycle, leading to increased termination activity of NNS. Overexpression of Sen1 or failure to modulate its abundance by ubiquitin-proteasome-mediated degradation greatly decreases cell fitness. Sen1 toxicity is suppressed by mutations in other termination factors, and NET-seq analysis shows that its overexpression leads to a decrease in ncRNA production and altered mRNA termination. We conclude that Sen1 levels are carefully regulated to prevent aberrant termination. We suggest that ncRNA levels and coding gene transcription termination are modulated by Sen1 to fulfill critical cell cycle-specific functions.

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Transcription termination factor Sen1 levels fluctuate throughout the cell cycle

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APC targets Sen1 for degradation during G1

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Reduced Sen1 levels lower efficiency of Sen1-mediated termination

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Sen1 overexpression reduces cell viability because of excessive termination

What shapes eukaryotic transcriptional bursting?

Isogenic cells in a common environment present a large degree of heterogeneity in gene expression. Part of this variability is attributed to transcriptional bursting: the stochastic activation and inactivation of promoters that leads to the discontinuous production of mRNA. The diversity in bursting patterns displayed by different genes suggests the existence of a connection between bursting and gene regulation. Experimental strategies such as single-molecule RNA FISH, MS2-GFP or short-lived protein reporters allow the quantification of transcriptional bursting and the comparison of bursting kinetics between conditions, allowing therefore the identification of molecular mechanisms modulating transcriptional bursting. In this review we recapitulate the impact on transcriptional bursting of different molecular aspects of transcription such as the chromatin environment, nucleosome occupancy, histone modifications, the number and affinity of regulatory elements, DNA looping and transcription factor availability. More specifically, we examine their role in tuning the burst size or the burst frequency. While some molecular mechanisms involved in transcription such as histone marks can affect every aspect of bursting, others predominantly influence the burst size (e.g. the number and affinity of cis-regulatory elements) or frequency (e.g. transcription factor availability).

Ras hyperactivation versus overexpression: Lessons from Ras dynamics in Candida albicans

Ras signaling in response to environmental cues is critical for cellular morphogenesis in eukaryotes. This signaling is tightly regulated and its activation involves multiple players. Sometimes Ras signaling may be hyperactivated. In C. albicans, a human pathogenic fungus, we demonstrate that dynamics of hyperactivated Ras1 (Ras1G13V or Ras1 in Hsp90 deficient strains) can be reliably differentiated from that of normal Ras1 at (near) single molecule level using fluorescence correlation spectroscopy (FCS). Ras1 hyperactivation results in significantly slower dynamics due to actin polymerization. Activating actin polymerization by jasplakinolide can produce hyperactivated Ras1 dynamics. In a sterol-deficient hyperfilamentous GPI mutant of C. albicans too, Ras1 hyperactivation results from Hsp90 downregulation and causes actin polymerization. Hyperactivated Ras1 co-localizes with G-actin at the plasma membrane rather than with F-actin. Depolymerizing actin with cytochalasin D results in faster Ras1 dynamics in these and other strains that show Ras1 hyperactivation. Further, ergosterol does not influence Ras1 dynamics.

Imaging transcriptional dynamics

Recent advances in imaging techniques have enabled visualizations of nascent transcripts or individual protein molecules at high spatiotemporal resolution, revealing the complex nature of transcriptional regulation. Here, we highlight recent studies that have provided comprehensive insights to transcriptional dynamics using such quantitative imaging techniques. Specifically, they demonstrated that transcriptional activity is stochastic, and such transcriptional bursting is modulated by multiple components like chromatin environments, concentration of transcription factors, and enhancer-promoter interactions. Moreover, recent studies suggested that regulation of transcriptional activity is more complex than previously thought, by showing that transcription factors and RNA polymerases also move within the cell with distinct kinetics and sometimes form dynamic clusters to mediate transcriptional initiation.

Assessing sufficiency and necessity of enhancer activities for gene expression and the mechanisms of transcription activation

Enhancers are important genomic regulatory elements directing cell type-specific transcription. They assume a key role during development and disease, and their identification and functional characterization have long been the focus of scientific interest. The advent of next-generation sequencing and clustered regularly interspaced short palindromic repeat (CRISPR)/Cas9-based genome editing has revolutionized the means by which we study enhancer biology. In this review, we cover recent developments in the prediction of enhancers based on chromatin characteristics and their identification by functional reporter assays and endogenous DNA perturbations. We discuss that the two latter approaches provide different and complementary insights, especially in assessing enhancer sufficiency and necessity for transcription activation. Furthermore, we discuss recent insights into mechanistic aspects of enhancer function, including findings about cofactor requirements and the role of post-translational histone modifications such as monomethylation of histone H3 Lys4 (H3K4me1). Finally, we survey how these approaches advance our understanding of transcription regulation with respect to promoter specificity and transcriptional bursting and provide an outlook covering open questions and promising developments.

Live Imaging of mRNA Synthesis in Drosophila

mRNA synthesis is one of the earliest readouts of the activity of a transcribed gene, which is of particular interest in the context of metazoan cell fate specification. These processes are intrinsically dynamic and stochastic, which makes in vivo single-cell measurements inevitable. Here, we present the application of a technology that has been widely used in single celled organisms to measure transcriptional activity in developing embryos of the fruit fly Drosophila melanogaster. The method allows for quantification of instantaneous polymerase occupancy of active gene loci and thereby enables the development and testing of models of gene regulation in development.

Regulatory Architecture of the LβT2 Gonadotrope Cell Underlying the Response to Gonadotropin-Releasing Hormone

The LβT2 mouse pituitary cell line has many characteristics of a mature gonadotrope and is a widely used model system for studying the developmental processes and the response to gonadotropin-releasing hormone (GnRH). The global epigenetic landscape, which contributes to cell-specific gene regulatory mechanisms, and the single-cell transcriptome response variation of LβT2 cells have not been previously investigated. Here, we integrate the transcriptome and genome-wide chromatin accessibility state of LβT2 cells during GnRH stimulation. In addition, we examine cell-to-cell variability in the transcriptional response to GnRH using Gel bead-in-Emulsion Drop-seq technology. Analysis of a bulk RNA-seq data set obtained 45 min after exposure to either GnRH or vehicle identified 112 transcripts that were regulated >4-fold by GnRH (FDR < 0.05). The top regulated transcripts constitute, as determined by Bayesian massive public data integration analysis, a human pituitary-relevant coordinated gene program. Chromatin accessibility [assay for transposase-accessible chromatin with high-throughput sequencing (ATAC-seq)] data sets generated from GnRH-treated LβT2 cells identified more than 58,000 open chromatin regions, some containing notches consistent with bound transcription factor footprints. The study of the most prominent open regions showed that 75% were in transcriptionally active promoters or introns, supporting their involvement in active transcription. Lhb, Cga, and Egr1 showed significantly open chromatin over their promoters. While Fshb was closed over its promoter, several discrete significantly open regions were found at -40 to -90 kb, which may represent novel upstream enhancers. Chromatin accessibility determined by ATAC-seq was associated with high levels of gene expression determined by RNA-seq. We obtained high-quality single-cell Gel bead-in-Emulsion Drop-seq transcriptome data, with an average of >4,000 expressed genes/cell, from 1,992 vehicle- and 1,889 GnRH-treated cells. While the individual cell expression patterns showed high cell-to-cell variation, representing both biological and measurement variation, the average expression patterns correlated well with bulk RNA-seq data. Computational assignment of each cell to its precise cell cycle phase showed that the response to GnRH was unaffected by cell cycle. To our knowledge, this study represents the first genome-wide epigenetic and single-cell transcriptomic characterization of this important gonadotrope model. The data have been deposited publicly and should provide a resource for hypothesis generation and further study.

Measuring mRNA Decay in Budding Yeast Using Single Molecule FISH

Cellular mRNA levels are determined by the rates of mRNA synthesis and mRNA decay. Typically, mRNA degradation kinetics are measured on a population of cells that are either chemically treated or genetically engineered to inhibit transcription. However, these manipulations can affect the mRNA decay process itself by inhibiting regulatory mechanisms that govern mRNA degradation, especially if they occur on short time-scales. Recently, single molecule fluorescent in situ hybridization (smFISH) approaches have been implemented to quantify mRNA decay rates in single, unperturbed cells. Here, we provide a step-by-step protocol that allows quantification of mRNA decay in single Saccharomyces cerevisiae using smFISH. Our approach relies on fluorescent labeling of single cytoplasmic mRNAs and nascent mRNAs found at active sites of transcription, coupled with mathematical modeling to derive mRNA half-lives. Commercially available, single-stranded smFISH DNA oligonucleotides (smFISH probes) are used to fluorescently label mRNAs followed by the quantification of cellular and nascent mRNAs using freely available spot detection algorithms. Our method enables quantification of mRNA decay of any mRNA in single, unperturbed yeast cells and can be implemented to quantify mRNA turnover in a variety of cell types as well as tissues.