Single mRNA tracking in live cells

Single-Molecule RNA Imaging in Live Cells with an Avidity-Based Fluorescent Light-Up Aptamer biRhoBAST

Observing individual RNA molecules provides valuable insights into their regulation, interactions with other cellular components, organization, and functions. Although fluorescent light-up aptamers (FLAPs) have recently shown promise for RNA imaging, their wider applications have been mostly hindered by poor brightness and photostability. We recently developed an avidity-based FLAP known as biRhoBAST that allows for single-molecule RNA imaging in live or fixed cells and tracking individual mRNA molecules in living cells due to its excellent photostability and high brightness. Here, we present step-by-step detailed protocols starting from cloning biRhoBAST repeats into the target RNA sequence, to imaging dynamics of single mRNA molecules. Additionally, we address the validation of single-molecule imaging experiments through single-molecule fluorescence in situ hybridization (smFISH) and colocalization studies.

Synaptic logistics: Competing over shared resources

High turnover rates of synaptic proteins imply that synapses constantly need to replace their constituent building blocks. This requires sophisticated supply chains and potentially exposes synapses to shortages as they compete for limited resources. Interestingly, competition in neurons has been observed at different scales. Whether it is competition of receptors for binding sites inside a single synapse or synapses fighting for resources to grow. Here we review the implications of such competition for synaptic function and plasticity. We identify multiple mechanisms that synapses use to safeguard themselves against supply shortages and identify a fundamental neurologistic trade-off governing the sizes of reserve pools of essential synaptic building blocks.

BNP-Track: A framework for multi-particle superresolved tracking

When tracking fluorescently labeled molecules (termed "emitters") under widefield microscopes, point spread function overlap of neighboring molecules is inevitable in both dilute and especially crowded environments. In such cases, superresolution methods leveraging rare photophysical events to distinguish static targets nearby in space introduce temporal delays that compromise tracking. As we have shown in a companion manuscript, for dynamic targets, information on neighboring fluorescent molecules is encoded as spatial intensity correlations across pixels and temporal correlations in intensity patterns across time frames. We then demonstrated how we used all spatiotemporal correlations encoded in the data to achieve superresolved tracking. That is, we showed the results of full posterior inference over both the number of emitters and their associated tracks simultaneously and self-consistently through Bayesian nonparametrics. In this companion manuscript we focus on testing the robustness of our tracking tool, BNP-Track, across sets of parameter regimes and compare BNP-Track to competing tracking methods in the spirit of a prior Nature Methods tracking competition. We explore additional features of BNP-Track including how a stochastic treatment of background yields greater accuracy in emitter number determination and how BNP-Track corrects for point spread function blur (or "aliasing") introduced by intraframe motion in addition to propagating error originating from myriad sources (such as criss-crossing tracks, out-of-focus particles, pixelation, shot and camera artefact, stochastic background) in posterior inference over emitter numbers and their associated tracks. While head-to-head comparison with other tracking methods is not possible (as competitors cannot simultaneously learn molecule numbers and associated tracks), we can give competing methods some advantages in order to perform approximate head-to-head comparison. We show that even under such optimistic scenarios, BNP-Track is capable of tracking multiple diffraction-limited point emitters conventional tracking methods cannot resolve thereby extending the superresolution paradigm to dynamical targets.

Computational insights into mRNA and protein dynamics underlying synaptic plasticity rules

Recent advances in experimental techniques provide an unprecedented peek into the intricate molecular dynamics inside synapses and dendrites. The experimental insights into the molecular turnover revealed that such processes as diffusion, active transport, spine uptake, and local protein synthesis could dynamically modulate the copy numbers of plasticity-related molecules in synapses. Subsequently, theoretical models were designed to understand the interaction of these processes better and to explain how local synaptic plasticity cues can up or down-regulate the molecular copy numbers across synapses. In this review, we discuss the recent advances in experimental techniques and computational models to highlight how these complementary approaches can provide insight into molecular cross-talk across synapses, ultimately allowing us to develop biologically-inspired neural network models to understand brain function.

Poly(A)+ Sensing of Hybridization-Sensitive Fluorescent Oligonucleotide Probe Characterized by Fluorescence Correlation Methods

Ribonucleic acid (RNA) plays an important role in many cellular processes. Thus, visualizing and quantifying the molecular dynamics of RNA directly in living cells is essential to uncovering their role in RNA metabolism. Among the wide variety of fluorescent probes available for RNA visualization, exciton-controlled hybridization-sensitive fluorescent oligonucleotide (ECHO) probes are useful because of their low fluorescence background. In this study, we apply fluorescence correlation methods to ECHO probes targeting the poly(A) tail of mRNA. In this way, we demonstrate not only the visualization but also the quantification of the interaction between the probe and the target, as well as of the change in the fluorescence brightness and the diffusion coefficient caused by the binding. In particular, the uptake of ECHO probes to detect mRNA is demonstrated in HeLa cells. These results are expected to provide new insights that help us better understand the metabolism of intracellular mRNA.

Expectation maximization based framework for joint localization and parameter estimation in single particle tracking from segmented images

Single Particle Tracking (SPT) is a well known class of tools for studying the dynamics of biological macromolecules moving inside living cells. In this paper, we focus on the problem of localization and parameter estimation given a sequence of segmented images. In the standard paradigm, the location of the emitter inside each frame of a sequence of camera images is estimated using, for example, Gaussian fitting (GF), and these locations are linked to provide an estimate of the trajectory. Trajectories are then analyzed by using Mean Square Displacement (MSD) or Maximum Likelihood Estimation (MLE) techniques to determine motion parameters such as diffusion coefficients. However, the problems of localization and parameter estimation are clearly coupled. Motivated by this, we have created an Expectation Maximization (EM) based framework for simultaneous localization and parameter estimation. We demonstrate this framework through two representative methods, namely, Sequential Monte Carlo combined with Expectation Maximization (SMC-EM) and Unscented Kalman Filter combined with Expectation Maximization (U-EM). Using diffusion in two-dimensions as a prototypical example, we conduct quantitative investigations on localization and parameter estimation performance across a wide range of signal to background ratios and diffusion coefficients and compare our methods to the standard techniques based on GF-MSD/MLE. To demonstrate the flexibility of the EM based framework, we do comparisons using two different camera models, an ideal camera with Poisson distributed shot noise but no readout noise, and a camera with both shot noise and the pixel-dependent readout noise that is common to scientific complementary metal-oxide semiconductor (sCMOS) camera. Our results indicate our EM based methods outperform the standard techniques, especially at low signal levels. While U-EM and SMC-EM have similar accuracy, U-EM is significantly more computationally efficient, though the use of the Unscented Kalman Filter limits U-EM to lower diffusion rates.

LNCcation: lncRNA localization and function

Subcellular localization of RNAs has gained attention in recent years as a prevalent phenomenon that influences numerous cellular processes. This is also evident for the large and relatively novel class of long noncoding RNAs (lncRNAs). Because lncRNAs are defined as RNA transcripts >200 nucleotides that do not encode protein, they are themselves the functional units, making their subcellular localization critical to their function. The discovery of tens of thousands of lncRNAs and the cumulative evidence involving them in almost every cellular activity render assessment of their subcellular localization essential to fully understanding their biology. In this review, we summarize current knowledge of lncRNA subcellular localization, factors controlling their localization, emerging themes, including the role of lncRNA isoforms and the involvement of lncRNAs in phase separation bodies, and the implications of lncRNA localization on their function and on cellular behavior. We also discuss gaps in the current knowledge as well as opportunities that these provide for novel avenues of investigation.

Two- and Three-Dimensional Tracking of MFA2 mRNA Molecules in Mating Yeast

Intracellular mRNA transport contributes to the spatio-temporal regulation of mRNA function and localized translation. In the budding yeast, Saccharomyces cerevisiae, asymmetric mRNA transport localizes ~30 specific mRNAs including those encoding polarity and secretion factors, to the bud tip. The underlying process involves RNA-binding proteins (RBPs), molecular motors, processing bodies (PBs), and the actin cytoskeleton. Recently, pheromone a-factor expression in mating yeast was discovered to depend on proper localization of its mRNA, MFA2 mRNAs in conjunction with PBs cluster at the shmoo tip to form "mating bodies", from which a-factor is locally expressed. The mechanism ensuring the correct targeting of mRNA to the shmoo tip is poorly understood. Here we analyzed the kinetics and trajectories of MFA2 mRNA transport in living, alpha-factor treated yeast. Two- (2D) and three-dimensional (3D) analyses allowed us to reconstruct the granule tracks and estimate granule velocities. Tracking analysis of single MFA2 mRNA granules, labeled using a fluorescent aptamer system, demonstrated three types movement: vibrational, oscillatory and translocational. The mRNA granule transport was complex; a granule could change its movement behavior and composition during its journey to the shmoo. Processing body assembly and the actin-based motor, Myo4p, were involved in movement of MFA2 mRNA to the shmoo, but neither was required, indicating that multiple mechanisms for translocation were at play. Our visualization studies present a dynamic view of the localization mechanism in shmoo-bearing cells.

A time-varying approach to single particle tracking with a nonlinear observation model

Single Particle Tracking (SPT) is a powerful class of tools for analyzing the dynamics of individual biological macromolecules moving inside living cells. The acquired data is typically in the form of a sequence of camera images that are then post-processed to reveal details about the motion. In this work, we develop a local time-varying estimation algorithm for estimating motion model parameters from the data considering nonlinear observations. Our approach uses several well-known existing tools, namely the Expectation Maximization (EM) algorithm combined with an Unscented Kalman filter (UKF) and an Unscented Rauch-Tung-Striebel smoother (URTSS), and applies them to the time-varying case through a sliding window methodology. Due to the shot noise characteristics of the photon generation process, this model uses a Poisson distribution to capture the measurement noise inherent in imaging. In order to apply our time-varying approach to the UKF, we first need to transform the measurements into a model with additive Gaussian noise. This is carried out using a variance stabilizing transform. Results from simulations show that our approach is successful in tracing time-varying diffusion constants at a range of physically relevant signal levels. We also discuss the initialization for the EM algorithm based on the available data.

Following the messenger: Recent innovations in live cell single molecule fluorescence imaging

Messenger RNAs (mRNAs) convey genetic information from the DNA genome to proteins and thus lie at the heart of gene expression and regulation of all cellular activities. Live cell single molecule tracking tools enable the investigation of mRNA trafficking, translation and degradation within the complex environment of the cell and in real time. Over the last 5 years, nearly all tools within the mRNA tracking toolbox have been improved to achieve high-quality multi-color tracking in live cells. For example, the bacteriophage-derived MS2-MCP system has been improved to facilitate cloning and achieve better signal-to-noise ratio, while the newer PP7-PCP system now allows for orthogonal tracking of a second mRNA or mRNA region. The coming of age of epitope-tagging technologies, such as the SunTag, MoonTag and Frankenbody, enables monitoring the translation of single mRNA molecules. Furthermore, the portfolio of fluorogenic RNA aptamers has been expanded to improve cellular stability and achieve a higher fluorescence "turn-on" signal upon fluorogen binding. Finally, microinjection-based tools have been shown to be able to track multiple RNAs with only small fluorescent appendages and to track mRNAs together with their interacting partners. We systematically review and compare the advantages, disadvantages and demonstrated applications in discovering new RNA biology of this refined, expanding toolbox. Finally, we discuss developments expected in the near future based on the limitations of the current methods. This article is categorized under: RNA Export and Localization > RNA Localization RNA Structure and Dynamics > RNA Structure, Dynamics, and Chemistry RNA Interactions with Proteins and Other Molecules > RNA-Protein Complexes.

Fluorophore-Promoted RNA Folding and Photostability Enables Imaging of Single Broccoli-Tagged mRNAs in Live Mammalian Cells

Spinach and Broccoli are fluorogenic RNA aptamers that bind DFHBI, a mimic of the chromophore in green fluorescent protein, and activate its fluorescence. Spinach/Broccoli-DFHBI complexes exhibit high fluorescence in vitro, but they exhibit lower fluorescence in mammalian cells. Here, computational screening was used to identify BI, a DFHBI derivative that binds Broccoli with higher affinity and leads to markedly higher fluorescence in cells compared to previous ligands. BI prevents thermal unfolding of Broccoli at 37 °C, leading to more folded Broccoli and thus more fluorescent Broccoli-BI complexes in cells. Broccoli-BI complexes are more photostable owing to impaired photoisomerization and rapid unbinding of photoisomerized cis-BI. These properties enable single mRNA containing 24 Broccoli aptamers to be imaged in live mammalian cells treated with BI. Small molecule ligands can thus promote RNA folding in cells, and thus allow single mRNA imaging with fluorogenic aptamers.

Recent progress in single-molecule studies of mRNA localization in vivo

From biogenesis to degradation, mRNA goes through diverse types of regulation and interaction with other biomolecules. Uneven distribution of mRNA transcripts and the diverse isoforms and modifications of mRNA make us wonder how cells manage the complexity and keep the functional integrity for the normal development of cells and organisms. Single-molecule microscopy tools have expanded the scope of RNA research with unprecedented spatiotemporal resolution. In this review, we highlight the recent progress in the methods for labeling mRNA targets and analyzing the quantitative information from fluorescence images of single mRNA molecules. In particular, the MS2 system and its various applications are the main focus of this article. We also review how recent studies have addressed biological questions related to the significance of mRNA localization in vivo. Efforts to visualize the dynamics of single mRNA molecules in live cells will push forward our knowledge on the nature of heterogeneity in RNA sequence, structure, and distribution as well as their molecular function and coordinated interaction with RNA binding proteins.

Visualization of Single mRNAs in Live Neurons

Transcription and post-transcriptional regulations are critical in gene expression. To study the spatiotemporal regulation of RNA inside a cell, techniques for high-resolution imaging of RNA have been developed. In this chapter, we describe RNA fluorescent labeling methods using MS2 and PP7 systems to detect single RNA molecules in live neurons. We use hippocampal neurons cultured from knock-in mouse models in which β-actin or Arc mRNAs are tagged with MS2 or PP7 stem-loops. Adeno-associated virus (AAV) or lentiviral vectors are used to express MS2 or PP7 capsid proteins fused with GFP in those neurons. Then, GFP-labeled RNAs in live neurons can be detected by epifluorescence microscopy, and their moving pathways can be analyzed using single-particle tracking software. For these processes, we introduce protocols for neuron culture, transfection, imaging, and particle tracking methods.

CRISPR Tools for Systematic Studies of RNA Regulation

RNA molecules perform diverse functions in mammalian cells, including transferring genetic information from DNA to protein and playing diverse regulatory roles through interactions with other cellular components. Here, we discuss how clustered regularly interspaced short palindromic repeat (CRISPR)-based technologies for directed perturbations of DNA and RNA are revealing new insights into RNA regulation. First, we review the fundamentals of CRISPR-Cas enzymes and functional genomics tools that leverage these systems. Second, we explore how these new perturbation technologies are transforming the study of regulation of and by RNA, focusing on the functions of DNA regulatory elements and long noncoding RNAs (lncRNAs). Third, we highlight an emerging class of RNA-targeting CRISPR-Cas enzymes that have the potential to catalyze studies of RNA biology by providing tools to directly perturb or measure RNA modifications and functions. Together, these tools enable systematic studies of RNA function and regulation in mammalian cells.

MS2 Labeling of Endogenous Beta-Actin mRNA Does Not Result in Stabilization of Degradation Intermediates

The binding of MS2 bacteriophage coat protein (MCP) to MS2 binding site (MBS) RNA stem-loop sequences has been widely used to label mRNA for live-cell imaging at single-molecule resolution. However, concerns have been raised recently from studies with budding yeast showing aberrant mRNA metabolism following the MS2-GFP labeling. To investigate the degradation pattern of MS2-GFP-labeled mRNA in mammalian cells and tissues, we used Northern blot analysis of β-actin mRNA extracted from the Actb-MBS knock-in and MBS×MCP hybrid mouse models. In the immortalized mouse embryonic cell lines and various organ tissues derived from the mouse models, we found no noticeable accumulation of decay products of β-actin mRNA compared with the wild-type mice. Our results suggest that accumulation of MBS RNA decay fragments does not always happen depending on the mRNA species and the model organisms used.

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.

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.

Neuronal messenger ribonucleoprotein transport follows an aging Lévy walk

Localization of messenger ribonucleoproteins (mRNPs) plays an essential role in the regulation of gene expression for long-term memory formation and neuronal development. Knowledge concerning the nature of neuronal mRNP transport is thus crucial for understanding how mRNPs are delivered to their target synapses. Here, we report experimental and theoretical evidence that the active transport dynamics of neuronal mRNPs, which is distinct from the previously reported motor-driven transport, follows an aging Lévy walk. Such nonergodic, transient superdiffusion occurs because of two competing dynamic phases: the motor-involved ballistic run and static localization of mRNPs. Our proposed Lévy walk model reproduces the experimentally extracted key dynamic characteristics of mRNPs with quantitative accuracy. Moreover, the aging status of mRNP particles in an experiment is inferred from the model. This study provides a predictive theoretical model for neuronal mRNP transport and offers insight into the active target search mechanism of mRNP particles in vivo.

HybTrack: A hybrid single particle tracking software using manual and automatic detection of dim signals

Single particle tracking is a compelling technique for investigating the dynamics of nanoparticles and biological molecules in a broad range of research fields. In particular, recent advances in fluorescence microscopy have made single molecule tracking a prevalent method for studying biomolecules with a high spatial and temporal precision. Particle tracking algorithms have matured over the past three decades into more easily accessible platforms. However, there is an inherent difficulty in tracing particles that have a low signal-to-noise ratio and/or heterogeneous subpopulations. Here, we present a new MATLAB based tracking program which combines the benefits of manual and automatic tracking methods. The program prompts the user to manually locate a particle when an ambiguous situation occurs during automatic tracking. We demonstrate the utility of this program by tracking the movement of β-actin mRNA in the dendrites of cultured hippocampal neurons. We show that the diffusion coefficient of β-actin mRNA decreases upon neuronal stimulation by bicuculline treatment. This tracking method enables an efficient dissection of the dynamic regulation of biological molecules in highly complex intracellular environments.

Single-molecule imaging and tracking of molecular dynamics in living cells

Unlike the ensemble-averaging measurements, the single-molecule imaging and tracking (SMIT) in living cells provides the real-time quantitative information about the locations, kinetics, dynamics and interactions of individual molecules in their native environments with high spatiotemporal resolution and minimal perturbation. The past decade has witnessed a transforming development in the methods of SMIT with living cells, including fluorescent probes, labeling strategies, fluorescence microscopy, and detection and tracking algorithms. In this review, we will discuss these aspects with a particular focus on their recent advancements. We will then describe representative single-molecule studies to illustrate how the single-molecule approaches can be applied to monitor biomolecular interaction/reaction dynamics, and extract the molecular mechanistic information for different cellular systems.

Unraveling the Thousand Word Picture: An Introduction to Super-Resolution Data Analysis

Super-resolution microscopy provides direct insight into fundamental biological processes occurring at length scales smaller than light's diffraction limit. The analysis of data at such scales has brought statistical and machine learning methods into the mainstream. Here we provide a survey of data analysis methods starting from an overview of basic statistical techniques underlying the analysis of super-resolution and, more broadly, imaging data. We subsequently break down the analysis of super-resolution data into four problems: the localization problem, the counting problem, the linking problem, and what we've termed the interpretation problem.

Recent advances in high-performance fluorescent and bioluminescent RNA imaging probes

RNA plays an important role in life processes. Imaging of messenger RNAs (mRNAs) and micro-RNAs (miRNAs) not only allows us to learn the formation and transcription of mRNAs and the biogenesis of miRNAs involved in various life processes, but also helps in detecting cancer. High-performance RNA imaging probes greatly expand our view of life processes and enhance the cancer detection accuracy. In this review, we summarize the state-of-the-art high-performance RNA imaging probes, including exogenous probes that can image RNA sequences with special modification and endogeneous probes that can directly image endogenous RNAs without special treatment. For each probe, we review its structure and imaging principle in detail. Finally, we summarize the application of mRNA and miRNA imaging probes in studying life processes as well as in detecting cancer. By correlating the structures and principles of various probes with their practical uses, we compare different RNA imaging probes and offer guidance for better utilization of the current imaging probes and the future design of higher-performance RNA imaging probes.

Single Particle Tracking: From Theory to Biophysical Applications

After three decades of developments, single particle tracking (SPT) has become a powerful tool to interrogate dynamics in a range of materials including live cells and novel catalytic supports because of its ability to reveal dynamics in the structure-function relationships underlying the heterogeneous nature of such systems. In this review, we summarize the algorithms behind, and practical applications of, SPT. We first cover the theoretical background including particle identification, localization, and trajectory reconstruction. General instrumentation and recent developments to achieve two- and three-dimensional subdiffraction localization and SPT are discussed. We then highlight some applications of SPT to study various biological and synthetic materials systems. Finally, we provide our perspective regarding several directions for future advancements in the theory and application of SPT.

Single-Cell and Single-Molecule Analysis of Gene Expression Regulation

Recent advancements in single-cell and single-molecule imaging technologies have resolved biological processes in time and space that are fundamental to understanding the regulation of gene expression. Observations of single-molecule events in their cellular context have revealed highly dynamic aspects of transcriptional and post-transcriptional control in eukaryotic cells. This approach can relate transcription with mRNA abundance and lifetimes. Another key aspect of single-cell analysis is the cell-to-cell variability among populations of cells. Definition of heterogeneity has revealed stochastic processes, determined characteristics of under-represented cell types or transitional states, and integrated cellular behaviors in the context of multicellular organisms. In this review, we discuss novel aspects of gene expression of eukaryotic cells and multicellular organisms revealed by the latest advances in single-cell and single-molecule imaging technology.

Live Cell Imaging of Endogenous mRNA Using RNA-Based Fluorescence "Turn-On" Probe

Messenger RNA (mRNA) plays a critical role in cellular growth and development. However, there have been limited methods available to visualize endogenous mRNA in living cells with ease. We have designed RNA-based fluorescence "turn-on" probes that target mRNA by fusing an unstable form of Spinach with target-complementary sequences. These probes have been demonstrated to be selective, stable, and capable of targeting various mRNAs for live E. coli imaging.

Imaging Single-mRNA Localization and Translation in Live Neurons

Local protein synthesis mediates precise spatio-temporal regulation of gene expression for neuronal functions such as long-term plasticity, axon guidance and regeneration. To reveal the underlying mechanisms of local translation, it is crucial to understand mRNA transport, localization and translation in live neurons. Among various techniques for mRNA analysis, fluorescence microscopy has been widely used as the most direct method to study localization of mRNA. Live-cell imaging of single RNA molecules is particularly advantageous to dissect the highly heterogeneous and dynamic nature of messenger ribonucleoprotein (mRNP) complexes in neurons. Here, we review recent advances in the study of mRNA localization and translation in live neurons using novel techniques for single-RNA imaging.

mRNA quantification using single-molecule FISH in Drosophila embryos

Spatial information is critical to the interrogation of developmental and tissue-level regulation of gene expression. However, this information is usually lost when global mRNA levels from tissues are measured using reverse transcriptase PCR, microarray analysis or high-throughput sequencing. By contrast, single-molecule fluorescence in situ hybridization (smFISH) preserves the spatial information of the cellular mRNA content with subcellular resolution within tissues. Here we describe an smFISH protocol that allows for the quantification of single mRNAs in Drosophila embryos, using commercially available smFISH probes (e.g., short fluorescently labeled DNA oligonucleotides) in combination with wide-field epifluorescence, confocal or instant structured illumination microscopy (iSIM, a super-resolution imaging approach) and a spot-detection algorithm. Fixed Drosophila embryos are hybridized in solution with a mixture of smFISH probes, mounted onto coverslips and imaged in 3D. Individual fluorescently labeled mRNAs are then localized within tissues and counted using spot-detection software to generate quantitative, spatially resolved gene expression data sets. With minimum guidance, a graduate student can successfully implement this protocol. The smFISH procedure described here can be completed in 4-5 d.

Motion blur filtering: A statistical approach for extracting confinement forces and diffusivity from a single blurred trajectory

Single particle tracking (SPT) can aid in understanding a variety of complex spatiotemporal processes. However, quantifying diffusivity and confinement forces from individual live cell trajectories is complicated by inter- and intratrajectory kinetic heterogeneity, thermal fluctuations, and (experimentally resolvable) statistical temporal dependence inherent to the underlying molecule's time correlated confined dynamics experienced in the cell. The problem is further complicated by experimental artifacts such as localization uncertainty and motion blur. The latter is caused by the tagged molecule emitting photons at different spatial positions during the exposure time of a single frame. The aforementioned experimental artifacts induce spurious time correlations in measured SPT time series that obscure the information of interest (e.g., confinement forces and diffusivity). We develop a maximum likelihood estimation (MLE) technique that decouples the above noise sources and systematically treats temporal correlation via time series methods. This ultimately permits a reliable algorithm for extracting diffusivity and effective forces in confined or unconfined environments. We illustrate how our approach avoids complications inherent to mean square displacement or autocorrelation techniques. Our algorithm modifies the established Kalman filter (which does not handle motion blur artifacts) to provide a likelihood based time series estimation procedure. The result extends A. J. Berglund's motion blur model [Phys. Rev. E 82, 011917 (2010)PLEEE81539-375510.1103/PhysRevE.82.011917] to handle confined dynamics. The approach can also systematically utilize (possibly time dependent) localization uncertainty estimates afforded by image analysis if available. This technique, which explicitly treats confinement and motion blur within a time domain MLE framework, uses an exact likelihood (time domain methods facilitate analyzing nonstationary signals). Our estimator is demonstrated to be consistent over a wide range of exposure times (5 to 100 ms), diffusion coefficients (1×10^{-3} to 1μm^{2}/s), and confinement widths (100 nm to 2μm). We demonstrate that neglecting motion blur or confinement can substantially bias estimation of kinetic parameters of interest to researchers. The technique also permits one to check statistical model assumptions against measured individual trajectories without "ground truth." The ability to reliably and consistently extract motion parameters in trajectories exhibiting confined and/or non-stationary dynamics, without exposure time artifacts corrupting estimates, is expected to aid in directly comparing trajectories obtained from different experiments or imaging modalities. A Python implementation is provided (open-source code will be maintained on GitHub; see also the Supplemental Material with this paper).

TRICK: A Single-Molecule Method for Imaging the First Round of Translation in Living Cells and Animals

The life of an mRNA is dynamic within a cell. The development of quantitative fluorescent microscopy techniques to image single molecules of RNA has allowed many aspects of the mRNA lifecycle to be directly observed in living cells. Recent advances in live-cell multicolor RNA imaging, however, have now made it possible to investigate RNA metabolism in greater detail. In this chapter, we present an overview of the design and implementation of the translating RNA imaging by coat protein knockoff RNA biosensor, which allows untranslated mRNAs to be distinguished from ones that have undergone a round of translation. The methods required for establishing this system in mammalian cell lines and Drosophila melanogaster oocytes are described here, but the principles may be applied to any experimental system.

In Vivo RNA Visualization in Plants Using MS2 Tagging

Intracellular trafficking and asymmetric localization of RNA molecules within cells are a prevalent process across phyla involved in developmental control and signaling and thus in the determination of cell fate. In addition to intracellular localization, plants support the trafficking of RNA molecules also between cells through plasmodesmata (PD), which has important roles in the cell-to-cell and systemic communication during plant growth and development. Viruses have developed strategies to exploit the underlying plant RNA transport mechanisms for the cell-to-cell and systemic dissemination of infection. In vivo RNA visualization methods have revolutionized the study of RNA dynamics in living cells. However, their application in plants is still in its infancy. To gain insights into the RNA transport mechanisms in plants, we study the localization and transport of Tobacco mosaic virus RNA using MS2 tagging. This technique involves the tagging of the RNA of interest with repeats of an RNA stem-loop (SL) that is derived from the origin of assembly of the bacteriophage MS2 and recruits the MS2 coat protein (MCP). Thus, expression of MCP fused to a fluorescent marker allows the specific visualization of the SL-carrying RNA. Here we describe a detailed protocol for Agrobacterium tumefaciens-mediated transient expression and in vivo visualization of MS2-tagged mRNAs in Nicotiana benthamiana leaves.

Advanced fluorescence microscopy methods for the real-time study of transcription and chromatin dynamics

In this contribution we provide an overview of the recent advances allowed by the use of fluorescence microscopy methods in the study of transcriptional processes and their interplay with the chromatin architecture in living cells. Although the use of fluorophores to label nucleic acids dates back at least to about half a century ago,¹ two recent breakthroughs have effectively opened the way to use fluorescence routinely for specific and quantitative probing of chromatin organization and transcriptional activity in living cells: namely, the possibility of labeling first the chromatin loci and then the mRNA synthesized from a gene using fluorescent proteins. In this contribution we focus on methods that can probe rapid dynamic processes by analyzing fast fluorescence fluctuations.

Inferring Latent States and Refining Force Estimates via Hierarchical Dirichlet Process Modeling in Single Particle Tracking Experiments

Understanding the basis for intracellular motion is critical as the field moves toward a deeper understanding of the relation between Brownian forces, molecular crowding, and anisotropic (or isotropic) energetic forcing. Effective forces and other parameters used to summarize molecular motion change over time in live cells due to latent state changes, e.g., changes induced by dynamic micro-environments, photobleaching, and other heterogeneity inherent in biological processes. This study discusses limitations in currently popular analysis methods (e.g., mean square displacement-based analyses) and how new techniques can be used to systematically analyze Single Particle Tracking (SPT) data experiencing abrupt state changes in time or space. The approach is to track GFP tagged chromatids in metaphase in live yeast cells and quantitatively probe the effective forces resulting from dynamic interactions that reflect the sum of a number of physical phenomena. State changes can be induced by various sources including: microtubule dynamics exerting force through the centromere, thermal polymer fluctuations, and DNA-based molecular machines including polymerases and protein exchange complexes such as chaperones and chromatin remodeling complexes. Simulations aiming to show the relevance of the approach to more general SPT data analyses are also studied. Refined force estimates are obtained by adopting and modifying a nonparametric Bayesian modeling technique, the Hierarchical Dirichlet Process Switching Linear Dynamical System (HDP-SLDS), for SPT applications. The HDP-SLDS method shows promise in systematically identifying dynamical regime changes induced by unobserved state changes when the number of underlying states is unknown in advance (a common problem in SPT applications). We expand on the relevance of the HDP-SLDS approach, review the relevant background of Hierarchical Dirichlet Processes, show how to map discrete time HDP-SLDS models to classic SPT models, and discuss limitations of the approach. In addition, we demonstrate new computational techniques for tuning hyperparameters and for checking the statistical consistency of model assumptions directly against individual experimental trajectories; the techniques circumvent the need for "ground-truth" and/or subjective information.

Single-molecule insights into mRNA dynamics in neurons

Targeting of mRNAs to neuronal dendrites and axons plays an integral role in intracellular signaling, development, and synaptic plasticity. Single-molecule imaging of mRNAs in neurons and brain tissue has led to enhanced understanding of mRNA dynamics. Here we discuss aspects of mRNA regulation as revealed by single-molecule detection, which has led to quantitative analyses of mRNA diversity, localization, transport, and translation. These exciting new discoveries propel our understanding of the life of an mRNA in a neuron and how its activity is regulated at the single-molecule level.

In vivo RNA labeling using MS2

The trafficking and asymmetric distribution of cytoplasmic RNA is a fundamental process during development and signaling across phyla. Plants support the intercellular trafficking of RNA molecules such as gene transcripts, small RNAs, and viral RNA genomes by targeting these RNA molecules to plasmodesmata (PD). Intercellular transport of RNA molecules through PD has fundamental implications in the cell-to-cell and systemic signaling during plant development and in the systemic spread of viral disease. Recent advances in time-lapse microscopy allow researchers to approach dynamic biological processes at the molecular level in living cells and tissues. These advances include the ability to label RNA molecules in vivo and thus to monitor their distribution and trafficking. In a broadly used RNA labeling approach, the MS2 method, the RNA of interest is tagged with a specific stem-loop (SL) RNA sequence derived from the origin of assembly region of the bacteriophage MS2 genome that binds to the bacteriophage coat protein (CP) and which, if fused to a fluorescent protein, allows the visualization of the tagged RNA by fluorescence microscopy. Here we describe a protocol for the in vivo visualization of transiently expressed SL-tagged RNA and discuss key aspects to study RNA localization and trafficking to and through plasmodesmata in Nicotiana benthamiana plants.

In the right place at the right time: visualizing and understanding mRNA localization

The spatial regulation of protein translation is an efficient way to create functional and structural asymmetries in cells. Recent research has furthered our understanding of how individual cells spatially organize protein synthesis, by applying innovative technology to characterize the relationship between mRNAs and their regulatory proteins, single-mRNA trafficking dynamics, physiological effects of abrogating mRNA localization in vivo and for endogenous mRNA labelling. The implementation of new imaging technologies has yielded valuable information on mRNA localization, for example, by observing single molecules in tissues. The emerging movements and localization patterns of mRNAs in morphologically distinct unicellular organisms and in neurons have illuminated shared and specialized mechanisms of mRNA localization, and this information is complemented by transgenic and biochemical techniques that reveal the biological consequences of mRNA mislocalization.

Data-driven techniques for detecting dynamical state changes in noisily measured 3D single-molecule trajectories

Optical microscopes and nanoscale probes (AFM, optical tweezers, etc.) afford researchers tools capable of quantitatively exploring how molecules interact with one another in live cells. The analysis of in vivo single-molecule experimental data faces numerous challenges due to the complex, crowded, and time changing environments associated with live cells. Fluctuations and spatially varying systematic forces experienced by molecules change over time; these changes are obscured by "measurement noise" introduced by the experimental probe monitoring the system. In this article, we demonstrate how the Hierarchical Dirichlet Process Switching Linear Dynamical System (HDP-SLDS) of Fox et al. [IEEE Transactions on Signal Processing 59] can be used to detect both subtle and abrupt state changes in time series containing "thermal" and "measurement" noise. The approach accounts for temporal dependencies induced by random and "systematic overdamped" forces. The technique does not require one to subjectively select the number of "hidden states" underlying a trajectory in an a priori fashion. The number of hidden states is simultaneously inferred along with change points and parameters characterizing molecular motion in a data-driven fashion. We use large scale simulations to study and compare the new approach to state-of-the-art Hidden Markov Modeling techniques. Simulations mimicking single particle tracking (SPT) experiments are the focus of this study.

A single molecule approach to mRNA transport by a class V myosin

mRNA localization ensures correct spatial and temporal control of protein synthesis in the cell. We show that an in vitro single molecule approach, using purified recombinant full-length proteins and synthesized mRNA, provides insight into the mechanism by which localizing mRNAs are carried to their destination. A messenger ribonucleoprotein (mRNP) complex was reconstituted from a budding yeast class V myosin motor complex (Myo4p-She3p), an mRNA-binding adaptor protein (She2p), and a localizing mRNA (ASH1). The motion of the mRNP was tracked with high spatial (∼10 nm) and temporal (70 ms) resolution. Using this "bottom-up" methodology, we show that mRNA triggers the assembly of a high affinity double-headed motor-mRNA complex that moves continuously for long distances on actin filaments at physiologic ionic strength. Without mRNA, the myosin is monomeric and unable to move continuously on actin. This finding reveals an elegant strategy to ensure that only cargo-bound motors are activated for transport. Increasing the number of localization elements ("zip codes") in the mRNA enhanced both the frequency of motile events and their run length, features which likely enhance cellular localization. Future in vitro reconstitution of mRNPs with kinesin and dynein motors should similarly yield mechanistic insight into mRNA transport by microtubule-based motors.

Isolation of mRNAs associated with yeast mitochondria to study mechanisms of localized translation

Most of mitochondrial proteins are encoded in the nucleus and need to be imported into the organelle. Import may occur while the protein is synthesized near the mitochondria. Support for this possibility is derived from recent studies, in which many mRNAs encoding mitochondrial proteins were shown to be localized to the mitochondria vicinity. Together with earlier demonstrations of ribosomes' association with the outer membrane, these results suggest a localized translation process. Such localized translation may improve import efficiency, provide unique regulation sites and minimize cases of ectopic expression. Diverse methods have been used to characterize the factors and elements that mediate localized translation. Standard among these is subcellular fractionation by differential centrifugation. This protocol has the advantage of isolation of mRNAs, ribosomes and proteins in a single procedure. These can then be characterized by various molecular and biochemical methods. Furthermore, transcriptomics and proteomics methods can be applied to the resulting material, thereby allow genome-wide insights. The utilization of yeast as a model organism for such studies has the advantages of speed, costs and simplicity. Furthermore, the advanced genetic tools and available deletion strains facilitate verification of candidate factors.

Dissecting non-coding RNA mechanisms in cellulo by Single-molecule High-Resolution Localization and Counting

Non-coding RNAs (ncRNAs) recently were discovered to outnumber their protein-coding counterparts, yet their diverse functions are still poorly understood. Here we report on a method for the intracellular Single-molecule High-Resolution Localization and Counting (iSHiRLoC) of microRNAs (miRNAs), a conserved, ubiquitous class of regulatory ncRNAs that controls the expression of over 60% of all mammalian protein coding genes post-transcriptionally, by a mechanism shrouded by seemingly contradictory observations. We present protocols to execute single particle tracking (SPT) and single-molecule counting of functional microinjected, fluorophore-labeled miRNAs and thereby extract diffusion coefficients and molecular stoichiometries of micro-ribonucleoprotein (miRNP) complexes from living and fixed cells, respectively. This probing of miRNAs at the single molecule level sheds new light on the intracellular assembly/disassembly of miRNPs, thus beginning to unravel the dynamic nature of this important gene regulatory pathway and facilitating the development of a parsimonious model for their obscured mechanism of action.

Correcting for bias of molecular confinement parameters induced by small-time-series sample sizes in single-molecule trajectories containing measurement noise

Several single-molecule studies aim to reliably extract parameters characterizing molecular confinement or transient kinetic trapping from experimental observations. Pioneering works from single-particle tracking (SPT) in membrane diffusion studies [Kusumi et al., Biophys. J. 65, 2021 (1993)] appealed to mean square displacement (MSD) tools for extracting diffusivity and other parameters quantifying the degree of confinement. More recently, the practical utility of systematically treating multiple noise sources (including noise induced by random photon counts) through likelihood techniques has been more broadly realized in the SPT community. However, bias induced by finite-time-series sample sizes (unavoidable in practice) has not received great attention. Mitigating parameter bias induced by finite sampling is important to any scientific endeavor aiming for high accuracy, but correcting for bias is also often an important step in the construction of optimal parameter estimates. In this article, it is demonstrated how a popular model of confinement can be corrected for finite-sample bias in situations where the underlying data exhibit Brownian diffusion and observations are measured with non-negligible experimental noise (e.g., noise induced by finite photon counts). The work of Tang and Chen [J. Econometrics 149, 65 (2009)] is extended to correct for bias in the estimated "corral radius" (a parameter commonly used to quantify confinement in SPT studies) in the presence of measurement noise. It is shown that the approach presented is capable of reliably extracting the corral radius using only hundreds of discretely sampled observations in situations where other methods (including MSD and Bayesian techniques) would encounter serious difficulties. The ability to accurately statistically characterize transient confinement suggests additional techniques for quantifying confined and/or hop diffusion in complex environments.

Application of live-cell RNA imaging techniques to the study of retroviral RNA trafficking

Retroviruses produce full-length RNA that serves both as a genomic RNA (gRNA), which is encapsidated into virus particles, and as an mRNA, which directs the synthesis of viral structural proteins. However, we are only beginning to understand the cellular and viral factors that influence trafficking of retroviral RNA and the selection of the RNA for encapsidation or translation. Live cell imaging studies of retroviral RNA trafficking have provided important insight into many aspects of the retrovirus life cycle including transcription dynamics, nuclear export of viral RNA, translational regulation, membrane targeting, and condensation of the gRNA during virion assembly. Here, we review cutting-edge techniques to visualize single RNA molecules in live cells and discuss the application of these systems to studying retroviral RNA trafficking.

Axonal mRNA localization and local protein synthesis in nervous system assembly, maintenance and repair

mRNAs can be targeted to specific neuronal subcellular domains, which enables rapid changes in the local proteome through local translation. This mRNA-based mechanism links extrinsic signals to spatially restricted cellular responses and can mediate stimulus-driven adaptive responses such as dendritic plasticity. Local mRNA translation also occurs in growing axons where it can mediate directional responses to guidance signals. Recent profiling studies have revealed that both growing and mature axons possess surprisingly complex and dynamic transcriptomes, thereby suggesting that axonal mRNA localization is highly regulated and has a role in a broad range of processes, a view that is increasingly being supported by new experimental evidence. Here, we review current knowledge on the roles and regulatory mechanisms of axonal mRNA translation and discuss emerging links to axon guidance, survival, regeneration and neurological disorders.

Single-mRNA counting using fluorescent in situ hybridization in budding yeast

Fluorescent in situ hybridization (FISH) allows the quantification of single mRNAs in budding yeast using fluorescently labeled single-stranded DNA probes, a wide-field epifluorescence microscope and a spot-detection algorithm. Fixed yeast cells are attached to coverslips and hybridized with a mixture of FISH probes, each conjugated to several fluorescent dyes. Images of cells are acquired in 3D and maximally projected for single-molecule analysis. Diffraction-limited labeled mRNAs are observed as bright fluorescent spots and can be quantified using a spot-detection algorithm. FISH preserves the spatial distribution of cellular RNA distribution within the cell and the stochastic fluctuations in individual cells that can lead to phenotypic differences within a clonal population. This information, however, is lost if the RNA content is measured on a population of cells by using reverse transcriptase PCR, microarrays or high-throughput sequencing. The FISH procedure and image acquisition described here can be completed in 3 d.

Recent advances in single-cell studies of gene regulation

A mechanistic understanding of gene regulatory network dynamics requires quantitative single-cell data of multiple network components in response to well-defined perturbations. Recent advances in the development of fluorescent biomarkers for proteins, detection of RNA and interactions, microfluidic technology, and high-resolution imaging have set the stage for a host of new studies that elucidate the important roles of stochasticity and cell-cell variability in response to external perturbations. In this review, we briefly describe methods for high-resolution visualization and the control of gene expression, along with application of these novel methods to recent studies involving gene networks.

Molecular-beacon-based tricomponent probe for SNP analysis in folded nucleic acids

Hybridization probes are often inefficient in the analysis of single-stranded DNA or RNA that are folded in stable secondary structures. A molecular beacon (MB) probe is a short DNA hairpin with a fluorophore and a quencher attached to opposite sides of the oligonucleotide. The probe is widely used in real-time analysis of specific DNA and RNA sequences. This study demonstrates how a conventional MB probe can be used for the analysis of nucleic acids that form very stable (T(m) > 80 °C) hairpin structures. Here we demonstrate that the MB probe is not efficient in direct analysis of secondary structure-folded analytes, whereas a MB-based tricomponent probe is suitable for these purposes. The tricomponent probe takes advantage of two oligonucleotide adaptor strands f and m. Each adaptor strand contains a fragment complementary to the analyte and a fragment complementary to a MB probe. In the presence of a specific analyte, the two adaptor strands hybridize to the analyte and the MB probe, thus forming a quadripartite complex. DNA strand f binds to the analyte with high affinity and unwinds its secondary structure. Strand m forms a stable complex only with the fully complementary analyte. The MB probe fluorescently reports the formation of the quadripartite associate. It was demonstrated that the DNA analytes folded in hairpin structures with stems containing 5, 6, 7, 8, 9, 11, or 13 base pairs can be detected in real time with the limit of detection (LOD) lying in the nanomolar range. The stability of the stem region in the DNA analyte did not affect the LOD. Analytes containing single base substitutions in the stem or in the loop positions were discriminated from the fully complementary DNA at room temperature. The tricomponent probe promises to simplify nucleic acid analysis at ambient temperatures in such applications as in vivo RNA monitoring, detection of pathogens, and single nucleotide polymorphism (SNP) genotyping by DNA microarrays.