Visualization of individual Scr mRNAs during Drosophila embryogenesis yields evidence for transcriptional bursting

Medical and molecular biophysical techniques as substantial tools in the era of mRNA-based vaccine technology

The COVID-19 pandemic prompted the advancement of vaccine technology using mRNA delivery into the host cells. Consequently, mRNA-based vaccines have emerged as a practical approach against SARS-CoV-2 owing to their inherent properties, such as cost-effectiveness, rapid manufacturing, and preservation. These features are vital, especially in resource-constrained regions. Nevertheless, the design of mRNA-based vaccines is intricately intertwined with the refinement of biophysical technologies, thereby establishing their high potential. The preparation of mRNA-based vaccines involves a sequence of phases combining medical and molecular biophysical technologies. Furthermore, their efficiency depends on the capability to optimize their positive attributes, thus paving the way for their subsequent preclinical and clinical evaluations. Using biophysical techniques, the characterization of nucleic acids extends from their initial formulation to their cellular internalization abilities and encapsulation in biomolecule complexes, such as lipid nanoparticles (LNPs), for designing mRNA-based LNPs. Furthermore, nanoparticles are subjected to a series of careful screening steps to assess their physical and chemical characteristics before achieving an optimum formulation suitable for preclinical and clinical studies. This review provides a comprehensive understanding of the fundamental role of biophysical techniques in the complex development of mRNA-based vaccines and their role in the recent success during the COVID-19 pandemic.

Site-specific Covalent Labeling of DNA Substrates by an RNA Transglycosylase

Bacterial tRNA guanine transglycosylases (TGTs) catalyze the exchange of guanine for the 7-deazaguanine queuine precursor, prequeuosine1 (preQ1). While the native nucleic acid substrate for bacterial TGTs is the anticodon loop of queuine-cognate tRNAs, the minimum recognition sequence for the enzyme is a structured hairpin containing the target G nucleobase in a "UGU" loop motif. Previous work has established an RNA modification system, RNA-TAG, in which E. coli TGT exchanges the target G on an RNA of interest for chemically modified preQ1 substrates linked to a small molecule reporter such as biotin or a fluorophore. While extending the substrate scope of RNA transglycosylases to include DNA would enable numerous applications, it has been previously reported that TGT is incapable of modifying native DNA. Here we demonstrate that TGT can in fact recognize and label specific DNA substrates. Through iterative testing of rationally mutated DNA hairpin sequences, we determined the minimal sequence requirements for transglycosylation of unmodified DNA by E. coli TGT. Controlling steric constraint in the DNA hairpin dramatically affects labeling efficiency, and, when optimized, can lead to near quantitative site-specific modification. We demonstrate the utility of our newly developed DNA-TAG system by rapidly synthesizing probes for fluorescent Northern blotting of spliceosomal U6 RNA and RNA FISH visualization of the long noncoding RNA, MALAT1. The ease and convenience of the DNA-TAG system will provide researchers with a tool for accessing a wide variety of affordable modified DNA substrates.

Analysis of Gene Expression Patterns and RNA Localization by Fluorescence in Situ Hybridization in Whole Mount Drosophila Testes

Researchers have used RNA in situ hybridization to detect the presence of RNA in cells and tissues for approximately 50 years. The recent development of a method capable of visualizing a single RNA molecule by utilizing tiled fluorescently labeled oligonucleotide probes that together produce a diffraction-limited spot has greatly increased the resolution of this technique, allowing for the precise determination of subcellular RNA localization and relative abundance. Here, we present our method for single molecule RNA fluorescence in situ hybridization (smFISH) in whole mount Drosophila testes and discuss how we have utilized this method to better understand the expression pattern of the highly unusual Y-linked genes.

Activation domains can decouple the mean and noise of gene expression

Regulatory mechanisms set a gene's average level of expression, but a gene's expression constantly fluctuates around that average. These stochastic fluctuations, or expression noise, play a role in cell-fate transitions, bet hedging in microbes, and the development of chemotherapeutic resistance in cancer. An outstanding question is what regulatory mechanisms contribute to noise. Here, we demonstrate that, for a fixed mean level of expression, strong activation domains (ADs) at low abundance produce high expression noise, while weak ADs at high abundance generate lower expression noise. We conclude that differences in noise can be explained by the interplay between a TF's nuclear concentration and the strength of its AD's effect on mean expression, without invoking differences between classes of ADs. These results raise the possibility of engineering gene expression noise independently of mean levels in synthetic biology contexts and provide a potential mechanism for natural selection to tune the noisiness of gene expression.

The rate of thermodynamic cost against adiabatic and nonadiabatic fluctuations of a single gene circuit in Drosophila embryos

We study the stochastic dynamics of the externally regulating　gene circuit as an example of eve-skipped gene stripe in the development of Drosophila. Three gene regulation regimes are　considered: adiabatic phase when the switching rate of the gene from the OFF to the ON state is faster than the rate of mRNA degradation; nonadiabatic phase when the switching rate from the OFF to the ON state is slower than that of the mRNA degradation; the bursting phase when the gene switching is fast and transcription is very fast, while the ON state probability is very low. We found that the rate of　thermodynamic cost quantified by the entropy production rate can suppress the fluctuations of the gene circuit. Higher(lower) rate of thermodynamic cost leads to reduced (increased) fluctuations on the number of gene products in the adiabatic (nonadiabatic) regime. We also found that higher thermodynamic cost is often required to sustain the emergence of more gene states and therefore more heterogeneity coming from genetic mutations or epigenetics. We also study the stability of the gene state using the mean first passage time from one state to another. We found the monotonic decrease in time, i.e. on the stability of the state, in the transition from the nonadiabatic to the adiabatic regimes. Therefore, as the higher rate of thermodynamic cost suppresses the fluctuations, higher stability requires higher thermodynamics cost to maintain.

Cell identity specification in plants: lessons from flower development

Multicellular organisms display a fascinating complexity of cellular identities and patterns of diversification. The concept of 'cell type' aims to describe and categorize this complexity. In this review, we discuss the traditional concept of cell types and highlight the impact of single-cell technologies and spatial omics on the understanding of cellular differentiation in plants. We summarize and compare position-based and lineage-based mechanisms of cell identity specification using flower development as a model system. More than understanding ontogenetic origins of differentiated cells, an important question in plant science is to understand their position- and developmental stage-specific heterogeneity. Combinatorial action and crosstalk of external and internal signals is the key to cellular heterogeneity, often converging on transcription factors that orchestrate gene expression programs.

Dynamic regulation of anterior-posterior patterning genes in living Drosophila embryos

Expression of the gap and pair-rule genes plays an essential role in body segmentation during Drosophila embryogenesis.^1-5 However, it remains unclear how precise expression patterns of these key developmental genes arise from stochastic transcriptional activation at the single-cell level. Here, I employed genome-editing and live-imaging approaches to comprehensively visualize regulation of the gap and pair-rule genes at the endogenous loci. Quantitative image analysis revealed that the total duration of active transcription (transcription period) is a major determinant of spatial patterning of gene expression in early embryos. The length of the transcription period is determined by the continuity of bursting activities in individual nuclei, with the core expression domain producing more bursts than boundary regions. Each gene exhibits a distinct rate of nascent RNA production during transcriptional bursting, which contributes to gene-to-gene variability in the total output. I also provide evidence for "enhancer interference," wherein a distal weak enhancer interferes with transcriptional activation by a strong proximal enhancer to downregulate the length of the transcription period without changing the transcription rate. Analysis of the endogenous hunchback (hb) locus revealed that the removal of the distal shadow enhancer induces strong ectopic transcriptional activation, which suppresses refinement of the initial broad expression domain into narrower stripe patterns at the anterior part of embryos. This study provides key insights into the link between transcriptional bursting, enhancer-promoter interaction, and spatiotemporal patterning of gene expression during animal development.

Real-time single-cell characterization of the eukaryotic transcription cycle reveals correlations between RNA initiation, elongation, and cleavage

The eukaryotic transcription cycle consists of three main steps: initiation, elongation, and cleavage of the nascent RNA transcript. Although each of these steps can be regulated as well as coupled with each other, their in vivo dissection has remained challenging because available experimental readouts lack sufficient spatiotemporal resolution to separate the contributions from each of these steps. Here, we describe a novel application of Bayesian inference techniques to simultaneously infer the effective parameters of the transcription cycle in real time and at the single-cell level using a two-color MS2/PP7 reporter gene and the developing fruit fly embryo as a case study. Our method enables detailed investigations into cell-to-cell variability in transcription-cycle parameters as well as single-cell correlations between these parameters. These measurements, combined with theoretical modeling, suggest a substantial variability in the elongation rate of individual RNA polymerase molecules. We further illustrate the power of this technique by uncovering a novel mechanistic connection between RNA polymerase density and nascent RNA cleavage efficiency. Thus, our approach makes it possible to shed light on the regulatory mechanisms in play during each step of the transcription cycle in individual, living cells at high spatiotemporal resolution.

Tracing DNA paths and RNA profiles in cultured cells and tissues with ORCA

Chromatin conformation capture (3C) methods and fluorescent in situ hybridization (FISH) microscopy have been used to investigate the spatial organization of the genome. Although powerful, both techniques have limitations. Hi-C is challenging for low cell numbers and requires very deep sequencing to achieve its high resolution. In contrast, FISH can be done on small cell numbers and capture rare cell populations, but typically targets pairs of loci at a lower resolution. Here we detail a protocol for optical reconstruction of chromatin architecture (ORCA), a microscopy approach to trace the 3D DNA path within the nuclei of fixed tissues and cultured cells with a genomic resolution as fine as 2 kb and a throughput of ~10,000 cells per experiment. ORCA can identify structural features with comparable resolution to Hi-C while providing single-cell resolution and multimodal measurements characteristic of microscopy. We describe how to use this DNA labeling in parallel with multiplexed labeling of dozens of RNAs to relate chromatin structure and gene expression in the same cells. Oligopaint probe design, primary probe making, sample collection, cryosectioning and RNA/DNA primary probe hybridization can be completed in 1.5 weeks, while automated RNA/DNA barcode hybridization and RNA/DNA imaging typically takes 2-6 d for data collection and 2-7 d for the automated steps of image analysis.

Kinetic sculpting of the seven stripes of the Drosophila even-skipped gene

We used live imaging to visualize the transcriptional dynamics of the Drosophila melanogaster even-skipped gene at single-cell and high-temporal resolution as its seven stripe expression pattern forms, and developed tools to characterize and visualize how transcriptional bursting varies over time and space. We find that despite being created by the independent activity of five enhancers, even-skipped stripes are sculpted by the same kinetic phenomena: a coupled increase of burst frequency and amplitude. By tracking the position and activity of individual nuclei, we show that stripe movement is driven by the exchange of bursting nuclei from the posterior to anterior stripe flanks. Our work provides a conceptual, theoretical and computational framework for dissecting pattern formation in space and time, and reveals how the coordinated transcriptional activity of individual nuclei shapes complex developmental patterns.

Binary Expression Enhances Reliability of Messaging in Gene Networks

The promoter state of a gene and its expression levels are modulated by the amounts of transcription factors interacting with its regulatory regions. Hence, one may interpret a gene network as a communicating system in which the state of the promoter of a gene (the source) is communicated by the amounts of transcription factors that it expresses (the message) to modulate the state of the promoter and expression levels of another gene (the receptor). The reliability of the gene network dynamics can be quantified by Shannon's entropy of the message and the mutual information between the message and the promoter state. Here we consider a stochastic model for a binary gene and use its exact steady state solutions to calculate the entropy and mutual information. We show that a slow switching promoter with long and equally standing ON and OFF states maximizes the mutual information and reduces entropy. That is a binary gene expression regime generating a high variance message governed by a bimodal probability distribution with peaks of the same height. Our results indicate that Shannon's theory can be a powerful framework for understanding how bursty gene expression conciliates with the striking spatio-temporal precision exhibited in pattern formation of developing organisms.

A technical review and guide to RNA fluorescence in situ hybridization

RNA-fluorescence in situ hybridization (FISH) is a powerful tool to visualize target messenger RNA transcripts in cultured cells, tissue sections or whole-mount preparations. As the technique has been developed over time, an ever-increasing number of divergent protocols have been published. There is now a broad selection of options available to facilitate proper tissue preparation, hybridization, and post-hybridization background removal to achieve optimal results. Here we review the technical aspects of RNA-FISH, examining the most common methods associated with different sample types including cytological preparations and whole-mounts. We discuss the application of commonly used reagents for tissue preparation, hybridization, and post-hybridization washing and provide explanations of the functional roles for each reagent. We also discuss the available probe types and necessary controls to accurately visualize gene expression. Finally, we review the most recent advances in FISH technology that facilitate both highly multiplexed experiments and signal amplification for individual targets. Taken together, this information will guide the methods development process for investigators that seek to perform FISH in organisms that lack documented or optimized protocols.

Spatially multiplexed RNA in situ hybridization to reveal tumor heterogeneity

Multiplexed RNA in situ hybridization for the analysis of gene expression patterns plays an important role in investigating development and disease. Here, we present a method for multiplexed RNA-ISH to detect spatial tumor heterogeneity in tissue sections. We made use of a microfluidic chip to deliver ISH-probes locally to regions of a few hundred micrometers over time periods of tens of minutes. This spatial multiplexing method can be combined with ISH-approaches based on signal amplification, with bright field detection and with the commonly used format of formalin-fixed paraffin-embedded tissue sections. By using this method, we analyzed the expression of HER2 with internal positive and negative controls (ActB, dapB) as well as predictive biomarker panels (ER, PgR, HER2) in a spatially multiplexed manner on single mammary carcinoma sections. We further demonstrated the applicability of the technique for subtype differentiation in breast cancer. Local analysis of HER2 revealed medium to high spatial heterogeneity of gene expression (Cohen effect size r = 0.4) in equivocally tested tumor tissues. Thereby, we exemplify the importance of using such a complementary approach for the analysis of spatial heterogeneity, in particular for equivocally tested tumor samples. As the method is compatible with a range of ISH approaches and tissue samples, it has the potential to find broad applicability in the context of molecular analysis of human diseases.

Multimodal transcriptional control of pattern formation in embryonic development

Predicting how interactions between transcription factors and regulatory DNA sequence dictate rates of transcription and, ultimately, drive developmental outcomes remains an open challenge in physical biology. Using stripe 2 of the even-skipped gene in Drosophila embryos as a case study, we dissect the regulatory forces underpinning a key step along the developmental decision-making cascade: the generation of cytoplasmic mRNA patterns via the control of transcription in individual cells. Using live imaging and computational approaches, we found that the transcriptional burst frequency is modulated across the stripe to control the mRNA production rate. However, we discovered that bursting alone cannot quantitatively recapitulate the formation of the stripe and that control of the window of time over which each nucleus transcribes even-skipped plays a critical role in stripe formation. Theoretical modeling revealed that these regulatory strategies (bursting and the time window) respond in different ways to input transcription factor concentrations, suggesting that the stripe is shaped by the interplay of 2 distinct underlying molecular processes.

Molecular basis and biological function of variability in spatial genome organization

The complex three-dimensional organization of genomes in the cell nucleus arises from a wide range of architectural features including DNA loops, chromatin domains, and higher-order compartments. Although these features are universally present in most cell types and tissues, recent single-cell biochemistry and imaging approaches have demonstrated stochasticity in transcription and high variability of chromatin architecture in individual cells. We review the occurrence, mechanistic basis, and functional implications of stochasticity in genome organization. We summarize recent observations on cell- and allele-specific variability of genome architecture, discuss the nature of extrinsic and intrinsic sources of variability in genome organization, and highlight potential implications of structural heterogeneity for genome function.

Lighting up the central dogma for predictive developmental biology

Although the last 30years have witnessed the mapping of the wiring diagrams of the gene regulatory networks that dictate cell fate and animal body plans, specific understanding building on such network diagrams that shows how DNA regulatory regions control gene expression lags far behind. These networks have yet to yield the predictive power necessary to, for example, calculate how the concentration dynamics of input transcription factors and DNA regulatory sequence prescribes output patterns of gene expression that, in turn, determine body plans themselves. Here, we argue that reaching a predictive understanding of developmental decision-making calls for an interplay between theory and experiment aimed at revealing how the regulation of the processes of the central dogma dictate network connections and how network topology guides cells toward their ultimate developmental fate. To make this possible, it is crucial to break free from the snapshot-based understanding of embryonic development facilitated by fixed-tissue approaches and embrace new technologies that capture the dynamics of developmental decision-making at the single cell level, in living embryos.

Transcriptional Bursting and Co-bursting Regulation by Steroid Hormone Release Pattern and Transcription Factor Mobility

Genes are transcribed in a discontinuous pattern referred to as RNA bursting, but the mechanisms regulating this process are unclear. Although many physiological signals, including glucocorticoid hormones, are pulsatile, the effects of transient stimulation on bursting are unknown. Here we characterize RNA synthesis from single-copy glucocorticoid receptor (GR)-regulated transcription sites (TSs) under pulsed (ultradian) and constant hormone stimulation. In contrast to constant stimulation, pulsed stimulation induces restricted bursting centered around the hormonal pulse. Moreover, we demonstrate that transcription factor (TF) nuclear mobility determines burst duration, whereas its bound fraction determines burst frequency. Using 3D tracking of TSs, we directly correlate TF binding and RNA synthesis at a specific promoter. Finally, we uncover a striking co-bursting pattern between TSs located at proximal and distal positions in the nucleus. Together, our data reveal a dynamic interplay between TF mobility and RNA bursting that is responsive to stimuli strength, type, modality, and duration.

An LRR Receptor-Teneurin System Directs Planar Polarity at Compartment Boundaries

Epithelial cells dynamically self-organize in response to extracellular spatial cues relayed by cell-surface receptors. During convergent extension in Drosophila, Toll-related receptors direct planar polarized cell rearrangements that elongate the head-to-tail axis. However, many cells establish polarity in the absence of Toll receptor activity, indicating the presence of additional spatial cues. Here we demonstrate that the leucine-rich-repeat receptor Tartan and the teneurin Ten-m provide critical polarity signals at epithelial compartment boundaries. The Tartan and Ten-m extracellular domains interact in vitro, and Tartan promotes Ten-m localization to compartment boundaries in vivo. We show that Tartan and Ten-m are necessary for the planar polarity and organization of compartment boundary cells. Moreover, ectopic stripes of Tartan and Ten-m are sufficient to induce myosin accumulation at stripe boundaries. These results demonstrate that the Tartan/Ten-m and Toll receptor systems together create a high-resolution network of spatial cues that guides cell behavior during convergent extension.

Is the cell really a machine?

It has become customary to conceptualize the living cell as an intricate piece of machinery, different to a man-made machine only in terms of its superior complexity. This familiar understanding grounds the conviction that a cell's organization can be explained reductionistically, as well as the idea that its molecular pathways can be construed as deterministic circuits. The machine conception of the cell owes a great deal of its success to the methods traditionally used in molecular biology. However, the recent introduction of novel experimental techniques capable of tracking individual molecules within cells in real time is leading to the rapid accumulation of data that are inconsistent with an engineering view of the cell. This paper examines four major domains of current research in which the challenges to the machine conception of the cell are particularly pronounced: cellular architecture, protein complexes, intracellular transport, and cellular behaviour. It argues that a new theoretical understanding of the cell is emerging from the study of these phenomena which emphasizes the dynamic, self-organizing nature of its constitution, the fluidity and plasticity of its components, and the stochasticity and non-linearity of its underlying processes.

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.

Vertebrate hox temporal collinearity: does it exist and what is it's function?

Hox temporal collinearity (TC) is a mysterious feature of embryogenesis. This article is opportune because of a recent challenge to TC’s existence This challenge is examined and the evidence that TC does exist is presented. Its function is discussed. Temporal collinearity is thought to be important because it lays the basis for Hox spatial collinearity and the vertebrate A-P axial pattern. The time-space translation mechanism whereby this occurs is examined.

Control of Hox transcription factor concentration and cell-to-cell variability by an auto-regulatory switch

The variability in transcription factor concentration among cells is an important developmental determinant, yet how variability is controlled remains poorly understood. Studies of variability have focused predominantly on monitoring mRNA production noise. Little information exists about transcription factor protein variability, as this requires the use of quantitative methods with single-molecule sensitivity. Using Fluorescence Correlation Spectroscopy (FCS), we have characterized the concentration and variability of 14 endogenously tagged TFs in live Drosophila imaginal discs. For the Hox TF Antennapedia, we investigated whether protein variability results from random stochastic events or is developmentally regulated. We found that Antennapedia transitioned from low concentration/high variability early, to high concentration/low variability later, in development. FCS and temporally resolved genetic studies uncovered that Antennapedia itself is necessary and sufficient to drive a developmental regulatory switch from auto-activation to auto-repression, thereby reducing variability. This switch is controlled by progressive changes in relative concentrations of preferentially activating and repressing Antennapedia isoforms, which bind chromatin with different affinities. Mathematical modeling demonstrated that the experimentally supported auto-regulatory circuit can explain the increase of Antennapedia concentration and suppression of variability over time.

Summary: Preferentially repressing and activating isoforms of the Hox transcription factor Antennapedia elicit a developmental regulatory switch from auto-activation to auto-repression that increases concentration and suppresses cell-to-cell variability over time.

Widespread inter-individual gene expression variability in Arabidopsis thaliana

A fundamental question in biology is how gene expression is regulated to give rise to a phenotype. However, transcriptional variability is rarely considered although it could influence the relationship between genotype and phenotype. It is known in unicellular organisms that gene expression is often noisy rather than uniform, and this has been proposed to be beneficial when environmental conditions are unpredictable. However, little is known about inter-individual transcriptional variability in multicellular organisms. Using transcriptomic approaches, we analysed gene expression variability between individual Arabidopsis thaliana plants growing in identical conditions over a 24-h time course. We identified hundreds of genes that exhibit high inter-individual variability and found that many are involved in environmental responses, with different classes of genes variable between the day and night. We also identified factors that might facilitate gene expression variability, such as gene length, the number of transcription factors regulating the genes and the chromatin environment. These results shed new light on the impact of transcriptional variability in gene expression regulation in plants.

Noise in bacterial gene expression

The expression level of a gene can fluctuate significantly between individuals within a population of genetically identical cells. The resultant phenotypic heterogeneity could be exploited by bacteria to adapt to changing environmental conditions. Noise is hence a genome-wide phenomenon that arises from the stochastic nature of the biochemical reactions that take place during gene expression and the relatively low abundance of the molecules involved. The production of mRNA and proteins therefore occurs in bursts, with alternating episodes of high and low activity during transcription and translation. Single-cell and single-molecule studies demonstrated that noise within gene expression is influenced by a combination of both intrinsic and extrinsic factors. However, our mechanistic understanding of this process at the molecular level is still rather limited. Further investigation is necessary that takes into account the detailed knowledge of gene regulation gained from biochemical studies.

Buffering and Amplifying Transcriptional Noise During Cell Fate Specification

The molecular processes that drive gene transcription are inherently noisy. This noise often manifests in the form of transcriptional bursts, producing fluctuations in gene activity over time. During cell fate specification, this noise is often buffered to ensure reproducible developmental outcomes. However, sometimes noise is utilized as a “bet-hedging” mechanism to diversify functional roles across a population of cells. Studies of bacteria, yeast, and cultured cells have provided insights into the nature and roles of noise in transcription, yet we are only beginning to understand the mechanisms by which noise influences the development of multicellular organisms. Here we discuss the sources of transcriptional noise and the mechanisms that either buffer noise to drive reproducible fate choices or amplify noise to randomly specify fates.

Lessons and perspectives for applications of stochastic models in biological and cancer research

The effects of randomness, an unavoidable feature of intracellular environments, are observed at higher hierarchical levels of living matter organization, such as cells, tissues, and organisms. Additionally, the many compounds interacting as a well-orchestrated network of reactions increase the difficulties of assessing these systems using only experiments. This limitation indicates that elucidation of the dynamics of biological systems is a complex task that will benefit from the establishment of principles to help describe, categorize, and predict the behavior of these systems. The theoretical machinery already available, or ones to be discovered to help solve biological problems, might play an important role in these processes. Here, we demonstrate the application of theoretical tools by discussing some biological problems that we have approached mathematically: fluctuations in gene expression and cell proliferation in the context of loss of contact inhibition. We discuss the methods that have been employed to provide the reader with a biologically motivated phenomenological perspective of the use of theoretical methods. Finally, we end this review with a discussion of new research perspectives motivated by our results.

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).

The Secret Life of RNA: Lessons from Emerging Methodologies

The last past decade has witnessed a revolution in our appreciation of transcriptome complexity and regulation. This remarkable expansion in our knowledge largely originates from the advent of high-throughput methodologies, and the consecutive discovery that up to 90% of eukaryotic genomes are transcribed, thus generating an unanticipated large range of noncoding RNAs (Hangauer et al., 15(4):112, 2014). Besides leading to the identification of new noncoding RNA species, transcriptome-wide studies have uncovered novel layers of posttranscriptional regulatory mechanisms controlling RNA processing, maturation or translation, and each contributing to the precise and dynamic regulation of gene expression. Remarkably, the development of systems-level studies has been accompanied by tremendous progress in the visualization of individual RNA molecules in single cells, such that it is now possible to image RNA species with a single-molecule resolution from birth to translation or decay. Monitoring quantitatively, with unprecedented spatiotemporal resolution, the fate of individual molecules has been key to understanding the molecular mechanisms underlying the different steps of RNA regulation. This has also revealed biologically relevant, intracellular and intercellular heterogeneities in RNA distribution or regulation. More recently, the convergence of imaging and high-throughput technologies has led to the emergence of spatially resolved transcriptomic techniques that provide a means to perform large-scale analyses while preserving spatial information. By generating transcriptome-wide data on single-cell RNA content, or even subcellular RNA distribution, these methodologies are opening avenues to a wide range of network-level studies at the cell and organ-level, and promise to strongly improve disease diagnostic and treatment.In this introductory chapter, we highlight how recently developed technologies aiming at detecting and visualizing RNA molecules have contributed to the emergence of entirely new research fields, and to dramatic progress in our understanding of gene expression regulation.

Stochastic gene expression in Arabidopsis thaliana

Although plant development is highly reproducible, some stochasticity exists. This developmental stochasticity may be caused by noisy gene expression. Here we analyze the fluctuation of protein expression in Arabidopsis thaliana. Using the photoconvertible KikGR marker, we show that the protein expressions of individual cells fluctuate over time. A dual reporter system was used to study extrinsic and intrinsic noise of marker gene expression. We report that extrinsic noise is higher than intrinsic noise and that extrinsic noise in stomata is clearly lower in comparison to several other tissues/cell types. Finally, we show that cells are coupled with respect to stochastic protein expression in young leaves, hypocotyls and roots but not in mature leaves. Our data indicate that stochasticity of gene expression can vary between tissues/cell types and that it can be coupled in a non-cell-autonomous manner.

Noisy gene expression can cause stochasticity in the expression of plant traits. Here, Araújo et al. use a dual reporter system of protein expression in Arabidopsis to show that expression noise is lowest in stomata relative to other tissues and that leaf cells are coupled with respect to noise.

Transcriptional precision and accuracy in development: from measurements to models and mechanisms

During development, genes are transcribed at specific times, locations and levels. In recent years, the emergence of quantitative tools has significantly advanced our ability to measure transcription with high spatiotemporal resolution in vivo. Here, we highlight recent studies that have used these tools to characterize transcription during development, and discuss the mechanisms that contribute to the precision and accuracy of the timing, location and level of transcription. We attempt to disentangle the discrepancies in how physicists and biologists use the term ‘precision' to facilitate interactions using a common language. We also highlight selected examples in which the coupling of mathematical modeling with experimental approaches has provided important mechanistic insights, and call for a more expansive use of mathematical modeling to exploit the wealth of quantitative data and advance our understanding of animal transcription.

Summary: This Review highlights how high-resolution quantitative tools and theoretical models have formed our current view of the mechanisms determining precision and accuracy in the timing, location and level of transcription in the Drosophila embryo.

Intrinsic Noise Profoundly Alters the Dynamics and Steady State of Morphogen-Controlled Bistable Genetic Switches

During tissue development, patterns of gene expression determine the spatial arrangement of cell types. In many cases, gradients of secreted signalling molecules—morphogens—guide this process by controlling downstream transcriptional networks. A mechanism commonly used in these networks to convert the continuous information provided by the gradient into discrete transitions between adjacent cell types is the genetic toggle switch, composed of cross-repressing transcriptional determinants. Previous analyses have emphasised the steady state output of these mechanisms. Here, we explore the dynamics of the toggle switch and use exact numerical simulations of the kinetic reactions, the corresponding Chemical Langevin Equation, and Minimum Action Path theory to establish a framework for studying the effect of gene expression noise on patterning time and boundary position. This provides insight into the time scale, gene expression trajectories and directionality of stochastic switching events between cell states. Taking gene expression noise into account predicts that the final boundary position of a morphogen-induced toggle switch, although robust to changes in the details of the noise, is distinct from that of the deterministic system. Moreover, the dramatic increase in patterning time close to the boundary predicted from the deterministic case is substantially reduced. The resulting stochastic switching introduces differences in patterning time along the morphogen gradient that result in a patterning wave propagating away from the morphogen source with a velocity determined by the intrinsic noise. The wave sharpens and slows as it advances and may never reach steady state in a biologically relevant time. This could explain experimentally observed dynamics of pattern formation. Together the analysis reveals the importance of dynamical transients for understanding morphogen-driven transcriptional networks and indicates that gene expression noise can qualitatively alter developmental patterning.

The bistable switch, a common regulatory sub-network, is found in many biological processes. It consists of cross-repressing components that generate a switch-like transition between two possible states. In developing tissues, bistable switches, created by cross-repressing transcriptional determinants, are often controlled by gradients of secreted signalling molecules—morphogens. These provide a mechanism to convert a morphogen gradient into stripes of gene expression that determine the arrangement of distinct cell types. Here we use mathematical models to analyse the temporal response of such a system. We find that the behaviour is highly dependent on the intrinsic fluctuations that result from the stochastic nature of gene expression. This noise has a marked effect on both patterning time and the location of the stripe boundary. One of the techniques we use, Minimum Action Path theory, identifies key features of the switch without computationally expensive calculations. The results reveal a noise driven switching wave that propels the stripe boundary away from the morphogen source to eventually settle, at steady state, further from the morphogen source than in the deterministic description. Together the analysis highlights the importance dynamics in patterning and demonstrates a set of mathematical tools for studying this problem.

Redeployment of a conserved gene regulatory network during Aedes aegypti development

Changes in gene regulatory networks (GRNs) underlie the evolution of morphological novelty and developmental system drift. The fruitfly Drosophila melanogaster and the dengue and Zika vector mosquito Aedes aegypti have substantially similar nervous system morphology. Nevertheless, they show significant divergence in a set of genes co-expressed in the midline of the Drosophila central nervous system, including the master regulator single minded and downstream genes including short gastrulation, Star, and NetrinA. In contrast to Drosophila, we find that midline expression of these genes is either absent or severely diminished in A. aegypti. Instead, they are co-expressed in the lateral nervous system. This suggests that in A. aegypti this "midline GRN" has been redeployed to a new location while lost from its previous site of activity. In order to characterize the relevant GRNs, we employed the SCRMshaw method we previously developed to identify transcriptional cis-regulatory modules in both species. Analysis of these regulatory sequences in transgenic Drosophila suggests that the altered gene expression observed in A. aegypti is the result of trans-dependent redeployment of the GRN, potentially stemming from cis-mediated changes in the expression of sim and other as-yet unidentified regulators. Our results illustrate a novel "repeal, replace, and redeploy" mode of evolution in which a conserved GRN acquires a different function at a new site while its original function is co-opted by a different GRN. This represents a striking example of developmental system drift in which the dramatic shift in gene expression does not result in gross morphological changes, but in more subtle differences in development and function of the late embryonic nervous system.

Current techniques for visualizing RNA in cells

Labeling RNA is of utmost interest, particularly in living cells, and thus RNA imaging is an emerging field. There are numerous methods relying on different concepts ranging from hybridization-based probes, over RNA-binding proteins to chemo-enzymatic modification of RNA. These methods have different benefits and limitations. This review aims to outline the current state-of-the-art techniques and point out their benefits and limitations.

Transcription Dynamics in Living Cells

The transcription cycle can be roughly divided into three stages: initiation, elongation, and termination. Understanding the molecular events that regulate all these stages requires a dynamic view of the underlying processes. The development of techniques to visualize and quantify transcription in single living cells has been essential in revealing the transcription kinetics. They have revealed that (a) transcription is heterogeneous between cells and (b) transcription can be discontinuous within a cell. In this review, we discuss the progress in our quantitative understanding of transcription dynamics in living cells, focusing on all parts of the transcription cycle. We present the techniques allowing for single-cell transcription measurements, review evidence from different organisms, and discuss how these experiments have broadened our mechanistic understanding of transcription regulation.

Shadow Enhancers Mediate Dynamic Shifts of Gap Gene Expression in the Drosophila Embryo

Drosophila patterning genes often contain pairs of primary and shadow enhancers that possess overlapping activities [1-5]. It has been suggested that this regulatory "redundancy" helps ensure reliable activation of gene expression under stressful conditions such as increases in temperature [4, 5]. There is also evidence that shadow enhancers help produce sharp on/off boundaries of gene expression in response to small changes in the levels of regulatory factors, such as the maternal Bicoid gradient [6, 7]. Here, we use live-imaging methods to visualize the temporal dynamics of the gap genes Kruppel and knirps, which are essential for the patterning of the thorax and abdomen, respectively [8, 9]. Previous analyses of fixed embryos suggested anterior shifts of the Kruppel and knirps expression patterns [10]. Here, we use computational visualization methods to reveal the precise temporal dynamics of these shifts and further suggest that shadow enhancers are crucial for this process. We discuss potential mechanisms for enhancer dominance, whereby one enhancer represses the other to foster temporal dynamics.

Stochastic model for gene transcription on Drosophila melanogaster embryos

We examine immunostaining experimental data for the formation of stripe 2 of even-skipped (eve) transcripts on D. melanogaster embryos. An estimate of the factor converting immunofluorescence intensity units into molecular numbers is given. The analysis of the eve dynamics at the region of stripe 2 suggests that the promoter site of the gene has two distinct regimes: an earlier phase when it is predominantly activated until a critical time when it becomes mainly repressed. That suggests proposing a stochastic binary model for gene transcription on D. melanogaster embryos. Our model has two random variables: the transcripts number and the state of the source of mRNAs given as active or repressed. We are able to reproduce available experimental data for the average number of transcripts. An analysis of the random fluctuations on the number of eves and their consequences on the spatial precision of stripe 2 is presented. We show that the position of the anterior or posterior borders fluctuate around their average position by ∼1% of the embryo length, which is similar to what is found experimentally. The fitting of data by such a simple model suggests that it can be useful to understand the functions of randomness during developmental processes.

New methods to image transcription in living fly embryos: the insights so far, and the prospects

The regulation of transcription is a fundamental process underlying the determination of cell identity and its maintenance during development. In the last decades, most of the transcription factors, which have to be expressed at the right place and at the right time for the proper development of the fly embryo, have been identified. However, mostly because of the lack of methods to visualize transcription as the embryo develops, their coordinated spatiotemporal dynamics remains largely unexplored. Efforts have been made to decipher the transcription process with single molecule resolution at the single cell level. Recently, the fluorescent labeling of nascent RNA in developing fly embryos allowed the direct visualization of ongoing transcription at single loci within each nucleus. Together with powerful imaging and quantitative data analysis, these new methods provide unprecedented insights into the temporal dynamics of the transcription process and its intrinsic noise. Focusing on the Drosophila embryo, we discuss how the detection of single RNA molecules enhanced our comprehension of the transcription process and we outline the potential next steps made possible by these new imaging tools. In combination with genetics and theoretical analysis, these new imaging methods will aid the search for the mechanisms responsible for the robustness of development. For further resources related to this article, please visit the WIREs website.

Detection and signal amplification in zebrafish RNA FISH

In situ hybridization (ISH) has become an invaluable tool for the detection of RNA in cells, tissues and organisms. Due to improvements in target and signal amplification and in probe design remarkable progress has been made concerning sensitivity, specificity and resolution of chromogenic and fluorescent ISH (FISH). These advancements allow for exquisite cellular and sub-cellular resolution and for detecting multiple RNA species at a time by multiplexing. In zebrafish (F)ISH non-enzymatic and enzymatic amplification systems have been employed to obtain enhanced signal intensities and signal-to-noise ratios. These amplification strategies include branched DNA-based RNAscope and in situ hybridization chain reaction (HCR) techniques, as well as alkaline phosphatase (AP)- and horseradish peroxidase (PO)-based immunoassays. For practical application, we provide proven multiplex FISH protocols for AP- and PO-based visualization of mRNAs at high resolution. The protocols take advantage of optimized tyramide signal amplification (TSA) conditions of the PO assay and long-lasting high signal-to-noise ratio of the AP reaction, thereby enabling detection of less abundant transcripts.

Quantitative gene expression analysis in Caenorhabditis elegans using single molecule RNA FISH

Advances in fluorescent probe design and synthesis have allowed the uniform in situ labeling of individual RNA molecules. In a technique referred to as single molecule RNA FISH (smRNA FISH), the labeled RNA molecules can be imaged as diffraction-limited spots and counted using image analysis algorithms. Single RNA counting has provided valuable insights into the process of gene regulation. This microscopy-based method has often revealed a high cell-to-cell variability in expression levels, which has in turn led to a growing interest in investigating the biological significance of gene expression noise. Here we describe the application of the smRNA FISH technique to samples of Caenorhabditis elegans, a well-characterized model organism.

Mid-embryo patterning and precision in Drosophila segmentation: Krüppel dual regulation of hunchback

In early development, genes are expressed in spatial patterns which later define cellular identities and tissue locations. The mechanisms of such pattern formation have been studied extensively in early Drosophila (fruit fly) embryos. The gap gene hunchback (hb) is one of the earliest genes to be expressed in anterior-posterior (AP) body segmentation. As a transcriptional regulator for a number of downstream genes, the spatial precision of hb expression can have significant effects in the development of the body plan. To investigate the factors contributing to hb precision, we used fine spatial and temporal resolution data to develop a quantitative model for the regulation of hb expression in the mid-embryo. In particular, modelling hb pattern refinement in mid nuclear cleavage cycle 14 (NC14) reveals some of the regulatory contributions of simultaneously-expressed gap genes. Matching the model to recent data from wild-type (WT) embryos and mutants of the gap gene Krüppel (Kr) indicates that a mid-embryo Hb concentration peak important in thoracic development (at parasegment 4, PS4) is regulated in a dual manner by Kr, with low Kr concentration activating hb and high Kr concentration repressing hb. The processes of gene expression (transcription, translation, transport) are intrinsically random. We used stochastic simulations to characterize the noise generated in hb expression. We find that Kr regulation can limit the positional variability of the Hb mid-embryo border. This has been recently corroborated in experimental comparisons of WT and Kr- mutant embryos. Further, Kr regulation can decrease uncertainty in mid-embryo hb expression (i.e. contribute to a smooth Hb boundary) and decrease between-copy transcriptional variability within nuclei. Since many tissue boundaries are first established by interactions between neighbouring gene expression domains, these properties of Hb-Kr dynamics to diminish the effects of intrinsic expression noise may represent a general mechanism contributing to robustness in early development.

Abundance and distribution of RNA polymerase II in Arabidopsis interphase nuclei

RNA polymerase II (RNAPII) is responsible for the transcription of most eukaryotic protein-coding genes. Analysing the topological distribution and quantification of RNAPII can contribute to understanding its function in interphase nuclei. Previously it was shown that RNAPII molecules in plant nuclei form reticulate structures within euchromatin of differentiated Arabidopsis thaliana nuclei rather than being organized in distinct 'transcription factories' as observed in mammalian nuclei. Immunosignal intensity measurements based on specific antibody labelling in maximum intensity projections of image stacks acquired by structured illumination microscopy (SIM) suggested a relative proportional increase of RNAPII in endopolyploid plant nuclei. Here, photoactivated localization microscopy (PALM) was applied to determine the absolute number and distribution of active and inactive RNAPII molecules in differentiated A. thaliana nuclei. The proportional increase of RNAPII during endopolyploidization is confirmed, but it is also shown that PALM measurements are more reliable than those based on SIM in terms of quantification. The single molecule localization results show that, although RNAPII molecules are globally dispersed within plant euchromatin, they also aggregate within smaller distances as described for mammalian transcription factories.

Strength in numbers: quantitative single-molecule RNA detection assays

Gene expression is a fundamental process that underlies development, homeostasis, and behavior of organisms. The fact that it relies on nucleic acid intermediates, which can specifically interact with complementary probes, provides an excellent opportunity for studying the multiple steps—transcription, RNA processing, transport, translation, degradation, and so forth—through which gene function manifests. Over the past three decades, the toolbox of nucleic acid science has expanded tremendously, making high‐precision in situ detection of DNA and RNA possible. This has revealed that many—probably the vast majority of—transcripts are distributed within the cytoplasm or the nucleus in a nonrandom fashion. With the development of microscopy techniques we have learned not only about the qualitative localization of these molecules but also about their absolute numbers with great precision. Single‐molecule techniques for nucleic acid detection have been transforming our views of biology with elementary power: cells are not average members of their population but are highly distinct individuals with greatly and suddenly changing gene expression, and this behavior of theirs can be measured, modeled, and thus predicted and, finally, comprehended. WIREs Dev Biol 2015, 4:135–150. doi: 10.1002/wdev.170

For further resources related to this article, please visit the WIREs website.

Conflict of interest: The authors have declared no conflicts of interest for this article.

A positional Toll receptor code directs convergent extension in Drosophila

Elongation of the head-to-tail body axis by convergent extension is a conserved developmental process throughout metazoans. In Drosophila, patterns of transcription factor expression provide spatial cues that induce systematically oriented cell movements and promote tissue elongation. However, the mechanisms by which patterned transcriptional inputs control cell polarity and behaviour have long been elusive. We demonstrate that three Toll family receptors, Toll-2, Toll-6 and Toll-8, are expressed in overlapping transverse stripes along the anterior-posterior axis and act in combination to direct planar polarity and polarized cell rearrangements during convergent extension. Simultaneous disruption of all three receptors strongly reduces actomyosin-driven junctional remodelling and axis elongation, and an ectopic stripe of Toll receptor expression is sufficient to induce planar polarized actomyosin contractility. These results demonstrate that tissue-level patterns of Toll receptor expression provide spatial signals that link positional information from the anterior-posterior patterning system to the essential cell behaviours that drive convergent extension.

Protein expression analyses at the single cell level

The central dogma of molecular biology explains how genetic information is converted into its end product, proteins, which are responsible for the phenotypic state of the cell. Along with the protein type, the phenotypic state depends on the protein copy number. Therefore, quantification of the protein expression in a single cell is critical for quantitative characterization of the phenotypic states. Protein expression is typically a dynamic and stochastic phenomenon that cannot be well described by standard experimental methods. As an alternative, fluorescence imaging is being explored for the study of protein expression, because of its high sensitivity and high throughput. Here we review key recent progresses in fluorescence imaging-based methods and discuss their application to proteome analysis at the single cell level.

Analytic approaches to stochastic gene expression in multicellular systems

Deterministic thermodynamic models of the complex systems, which control gene expression in metazoa, are helping researchers identify fundamental themes in the regulation of transcription. However, quantitative single cell studies are increasingly identifying regulatory mechanisms that control variability in expression. Such behaviors cannot be captured by deterministic models and are poorly suited to contemporary stochastic approaches that rely on continuum approximations, such as Langevin methods. Fortunately, theoretical advances in the modeling of transcription have assembled some general results that can be readily applied to systems being explored only through a deterministic approach. Here, I review some of the recent experimental evidence for the importance of genetically regulating stochastic effects during embryonic development and discuss key results from Markov theory that can be used to model this regulation. I then discuss several pairs of regulatory mechanisms recently investigated through a Markov approach. In each case, a deterministic treatment predicts no difference between the mechanisms, but the statistical treatment reveals the potential for substantially different distributions of transcriptional activity. In this light, features of gene regulation that seemed needlessly complex evolutionary baggage may be appreciated for their key contributions to reliability and precision of gene expression.

The embryo as a laboratory: quantifying transcription in Drosophila

Transcriptional regulation of gene expression is fundamental to most cellular processes, including determination of cellular fates. Quantitative studies of transcription in cultured cells have led to significant advances in identifying mechanisms underlying transcriptional control. Recent progress allowed implementation of these same quantitative methods in multicellular organisms to ask how transcriptional regulation unfolds both in vivo and at the single molecule level in the context of embryonic development. Here we review some of these advances in early Drosophila development, which bring the embryo on par with its single celled counterparts. In particular, we discuss progress in methods to measure mRNA and protein distributions in fixed and living embryos, and we highlight some initial applications that lead to fundamental new insights about molecular transcription processes. We end with an outlook on how to further exploit the unique advantages that come with investigating transcriptional control in the multicellular context of development.

Dynamic regulation of eve stripe 2 expression reveals transcriptional bursts in living Drosophila embryos

We present the use of recently developed live imaging methods to examine the dynamic regulation of even-skipped (eve) stripe 2 expression in the precellular Drosophila embryo. Nascent transcripts were visualized via MS2 RNA stem loops. The eve stripe 2 transgene exhibits a highly dynamic pattern of de novo transcription, beginning with a broad domain of expression during nuclear cycle 12 (nc12), and progressive refinement during nc13 and nc14. The mature stripe 2 pattern is surprisingly transient, constituting just ∼15 min of the ∼90-min period of expression. Nonetheless, this dynamic transcription profile faithfully predicts the limits of the mature stripe visualized by conventional in situ detection methods. Analysis of individual transcription foci reveals intermittent bursts of de novo transcription, with duration cycles of 4-10 min. We discuss a multistate model of transcription regulation and speculate on its role in the dynamic repression of the eve stripe 2 expression pattern during development.