Single-particle tracking: effects of corrals

Trajectory Analysis in Single-Particle Tracking: From Mean Squared Displacement to Machine Learning Approaches

Single-particle tracking is a powerful technique to investigate the motion of molecules or particles. Here, we review the methods for analyzing the reconstructed trajectories, a fundamental step for deciphering the underlying mechanisms driving the motion. First, we review the traditional analysis based on the mean squared displacement (MSD), highlighting the sometimes-neglected factors potentially affecting the accuracy of the results. We then report methods that exploit the distribution of parameters other than displacements, e.g., angles, velocities, and times and probabilities of reaching a target, discussing how they are more sensitive in characterizing heterogeneities and transient behaviors masked in the MSD analysis. Hidden Markov Models are also used for this purpose, and these allow for the identification of different states, their populations and the switching kinetics. Finally, we discuss a rapidly expanding field-trajectory analysis based on machine learning. Various approaches, from random forest to deep learning, are used to classify trajectory motions, which can be identified by motion models or by model-free sets of trajectory features, either previously defined or automatically identified by the algorithms. We also review free software available for some of the analysis methods. We emphasize that approaches based on a combination of the different methods, including classical statistics and machine learning, may be the way to obtain the most informative and accurate results.

Impact of temporal resolution in single particle tracking analysis

Temporal resolution is a key parameter in the observation of dynamic processes, as in the case of single molecules motions visualized in real time in two-dimensions by wide field (fluorescence) microscopy, but a systematic investigation of its effects in all the single particle tracking analysis steps is still lacking. Here we present tools to quantify its impact on the estimation of diffusivity and of its distribution using one of the most popular tracking software for biological applications on simulated data and movies. We found important shifts and different widths for diffusivity distributions, depending on the interplay of temporal sampling conditions with various parameters, such as simulated diffusivity, density of spots, signal-to-noise ratio, lengths of trajectories, and kind of boundaries in the simulation. We examined conditions starting from the ones of experiments on the fluorescently labelled receptor p75NTR, a relatively fast-diffusing membrane receptor (diffusivity around 0.5-1 µm2/s), visualized by TIRF microscopy on the basal membrane of living cells. From the analysis of the simulations, we identified the best conditions in cases similar to these ones; considering also the experiments, we could confirm a range of values of temporal resolution suitable for obtaining reliable diffusivity results. The procedure we present can be exploited in different single particle/molecule tracking applications to find an optimal temporal resolution.

Syntaxin clusters and cholesterol affect the mobility of Syntaxin1a

Syntaxin1a (Syx1a) is essential for stimulated exocytosis in neuroendocrine cells. The vesicle docking process involves the formation of nanoscale Syx1a domains on the plasma membrane and the Syx1a clusters disintegrate during the fusion process. Syx1a nanodomains are static yet Syx1a molecules dynamically enter and leave the domains; the process by which these clusters maintain this balance is unclear. In this work, the dynamics of the Syx1a molecules is elucidated relative to the cluster position through a labeling strategy that allows both the bulk position of the Syx clusters to be visualized concurrent with the trajectories of single Syx1a molecules on the surface of PC12 cells. Single Syx1a molecules were tracked in time relative to cluster positions to decipher how Syx1a moves within a cluster and when clusters are not present. Syx1a is mobile on the plasma membrane, more mobile at the center of clusters, and less mobile near the edges of clusters; this depends on the presence of the N-terminal Habc domain and cholesterol, which are essential for proper exocytosis. Simulations of the dynamics observed at clusters support a model where clusters are maintained by a large cage (r = 100 nm) within which Syx1a remains highly mobile within the cluster (r = 50 nm). The depletion of cholesterol dramatically reduces the mobility of Syx1a within clusters and less so over the rest of the plasma membrane. This suggests that fluidity of Syx1a supramolecular clusters is needed for function.

High-throughput super-resolution single-particle trajectory analysis reconstructs organelle dynamics and membrane reorganization

Super-resolution imaging can generate thousands of single-particle trajectories. These data can potentially reconstruct subcellular organization and dynamics, as well as measure disease-linked changes. However, computational methods that can derive quantitative information from such massive datasets are currently lacking. We present data analysis and algorithms that are broadly applicable to reveal local binding and trafficking interactions and organization of dynamic subcellular sites. We applied this analysis to the endoplasmic reticulum and neuronal membrane. The method is based on spatiotemporal segmentation that explores data at multiple levels and detects the architecture and boundaries of high-density regions in areas measuring hundreds of nanometers. By connecting dense regions, we reconstructed the network topology of the endoplasmic reticulum (ER), as well as molecular flow redistribution and the local space explored by trajectories. The presented methods are available as an ImageJ plugin that can be applied to large datasets of overlapping trajectories offering a standard of single-particle trajectory (SPT) metrics.

Fluorescence intensity fluctuation analysis of receptor oligomerization in membrane domains

Fluorescence micrographs of the plasma membrane of cells expressing fluorescently labeled G protein-coupled receptors (GPCRs) often exhibit small clusters of pixels (or puncta) with intensities that are higher than those of the surrounding pixels. Although studies of GPCR interactions in uniform membrane areas abound, understanding the details of the GPCR interactions within such puncta as well as the nature of the membrane formations underlying the puncta is hampered by the lack of adequate experimental techniques. Here, we introduce an enhancement of a recently developed method termed fluorescence intensity fluctuation spectrometry, which permits analysis of protein-protein interactions within the puncta in live cell membranes. We applied the novel fluorescence intensity fluctuation data analysis protocol to previously published data from cells expressing human secretin receptors and determined that the oligomer size increases with receptor concentration and duration of treatment with cognate ligand, not only within uniform regions of the membrane (in agreement with previous publications) but also within the puncta. In addition, we found that the number density and fractional area of the puncta increased after treatment with ligand. This method could be applied for probing the evolution in the time of the chain of events that begins with ligand binding and continues with coated pits formation and receptor internalization for other GPCRs and, indeed, other membrane receptors in living cells.

Maximum likelihood estimates of diffusion coefficients from single-particle tracking experiments

Single-molecule localization microscopy allows practitioners to locate and track labeled molecules in biological systems. When extracting diffusion coefficients from the resulting trajectories, it is common practice to perform a linear fit on mean-squared-displacement curves. However, this strategy is suboptimal and prone to errors. Recently, it was shown that the increments between the observed positions provide a good estimate for the diffusion coefficient, and their statistics are well-suited for likelihood-based analysis methods. Here, we revisit the problem of extracting diffusion coefficients from single-particle tracking experiments subject to static noise and dynamic motion blur using the principle of maximum likelihood. Taking advantage of an efficient real-space formulation, we extend the model to mixtures of subpopulations differing in their diffusion coefficients, which we estimate with the help of the expectation-maximization algorithm. This formulation naturally leads to a probabilistic assignment of trajectories to subpopulations. We employ the theory to analyze experimental tracking data that cannot be explained with a single diffusion coefficient. We test how well a dataset conforms to the assumptions of a diffusion model and determine the optimal number of subpopulations with the help of a quality factor of known analytical distribution. To facilitate use by practitioners, we provide a fast open-source implementation of the theory for the efficient analysis of multiple trajectories in arbitrary dimensions simultaneously.

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.

Diffusion of DNA-Binding Species in the Nucleus: A Transient Anomalous Subdiffusion Model

Single-particle tracking experiments have measured escape times of DNA-binding species diffusing in living cells: CRISPR-Cas9, TetR, and LacI. The observed distribution is a truncated power law. Working backward from the experimental results, the observed distribution appears inconsistent with a Gaussian distribution of binding energies. Working forward, the observed distribution leads to transient anomalous subdiffusion, in which diffusion is anomalous at short times and normal at long times, here only mildly anomalous. Monte Carlo simulations are used to characterize the time-dependent diffusion coefficient D(t) in terms of the anomalous exponent α, the crossover time tcross, and the limits D(0) and D(∞) and to relate these quantities to the escape time distribution. The simplest interpretations identify the escape time as the actual binding time to DNA or the period of one-dimensional diffusion on DNA in the standard model combining one-dimensional and three-dimensional search, but a more complicated interpretation may be required. The model has several implications for cell biophysics. 1) The initial anomalous regime represents the search of the DNA-binding species for its target DNA sequence. 2) Non-target DNA sites have a significant effect on search kinetics. False positives in bioinformatic searches of the genome are potentially rate-determining in vivo. For simple binding, the search would be speeded if false-positive sequences were eliminated from the genome. 3) Both binding and obstruction affect diffusion. Obstruction ought to be measured directly, using as the primary probe the DNA-binding species with the binding site inactivated and eGFP as a calibration standard among laboratories and cell types. 4) Overexpression of the DNA-binding species reduces anomalous subdiffusion because the deepest binding sites are occupied and unavailable. 5) The model provides a coarse-grained phenomenological description of diffusion of a DNA-binding species, useful in larger-scale modeling of kinetics, FCS, and FRAP.

Single-Virus Tracking: From Imaging Methodologies to Virological Applications

Uncovering the mechanisms of virus infection and assembly is crucial for preventing the spread of viruses and treating viral disease. The technique of single-virus tracking (SVT), also known as single-virus tracing, allows one to follow individual viruses at different parts of their life cycle and thereby provides dynamic insights into fundamental processes of viruses occurring in live cells. SVT is typically based on fluorescence imaging and reveals insights into previously unreported infection mechanisms. In this review article, we provide the readers a broad overview of the SVT technique. We first summarize recent advances in SVT, from the choice of fluorescent labels and labeling strategies to imaging implementation and analytical methodologies. We then describe representative applications in detail to elucidate how SVT serves as a valuable tool in virological research. Finally, we present our perspectives regarding the future possibilities and challenges of SVT.

Practical Considerations in Particle and Object Tracking and Analysis

The rapid advancement of live-cell imaging technologies has enabled biologists to generate high-dimensional data to follow biological movement at the microscopic level. Yet, the "perceived" ease of use of modern microscopes has led to challenges whereby sub-optimal data are commonly generated that cannot support quantitative tracking and analysis as a result of various ill-advised decisions made during image acquisition. Even optimally acquired images often require further optimization through digital processing before they can be analyzed. In writing this article, we presume our target audience to be biologists with a foundational understanding of digital image acquisition and processing, who are seeking to understand the essential steps for particle/object tracking experiments. It is with this targeted readership in mind that we review the basic principles of image-processing techniques as well as analysis strategies commonly used for tracking experiments. We conclude this technical survey with a discussion of how movement behavior can be mathematically modeled and described. © 2019 by John Wiley & Sons, Inc.

Fluorescence correlation spectroscopy: The technique and its applications in soft matter

Fluorescence correlation spectroscopy (FCS) is a well-established single-molecule method used for the quantitative spatiotemporal analysis of dynamic processes in a wide range of samples. It possesses single-molecule sensitivity but provides ensemble averaged molecular parameters such as mobility, concentration, chemical reaction kinetics, photophysical properties and interaction properties. These parameters have been utilized to characterize a variety of soft matter systems. This review provides an overview of the basic principles of various FCS modalities, their instrumentation, data analysis, and the applications of FCS to soft matter systems.

Assessing metastatic potential of breast cancer cells based on EGFR dynamics

Derailed transmembrane receptor trafficking could be a hallmark of tumorigenesis and increased tumor invasiveness, but receptor dynamics have not been used to differentiate metastatic cancer cells from less invasive ones. Using single-particle tracking techniques, we  developed a phenotyping asssay named Transmembrane Receptor Dynamics (TReD), studied the dynamics of epidermal growth factor receptor (EGFR) in seven breast epithelial cell lines and developed a phenotyping assay named Transmembrane Receptor Dynamics (TReD). Here we show a clear evidence that increased EGFR diffusivity and enlarged EGFR confinement size in the plasma membrane (PM) are correlated with the enhanced metastatic potential in these cell lines. By comparing the TReD results with the gene expression profiles, we found a clear negative correlation between the EGFR diffusivities and the breast cancer luminal differentiation scores (r = -0.75). Upon the induction of epithelial-mesenchymal transition (EMT), EGFR diffusivity significantly increased for the non-tumorigenic MCF10A (99%) and the non-invasive MCF7 (56%) cells, but not for the highly metastatic MDA-MB-231 cell. We believe that the reorganization of actin filaments during EMT modified the PM structures, causing the receptor dynamics to change. TReD can thus serve as a new biophysical marker to probe the metastatic potential of cancer cells and even to monitor the transition of metastasis.

How Important Is Protein Diffusion in Prokaryotes?

That diffusion is important for the proper functioning of cells is without question. The extent to which the diffusion coefficient is important is explored here for prokaryotic cells. We discuss the principles of diffusion focusing on diffusion-limited reactions, summarize the known values for diffusion coefficients in prokaryotes and in in vitro model systems, and explain a number of cases where diffusion coefficients are either limiting for reaction rates or necessary for the existence of phenomena. We suggest a number of areas that need further study including expanding the range of organism growth temperatures, direct measurements of diffusion limitation, expanding the range of cell sizes, diffusion limitation for membrane proteins, and taking into account cellular context when assessing the possibility of diffusion limitation.

Synergistic Integration of Laboratory and Numerical Approaches in Studies of the Biomechanics of Diseased Red Blood Cells

In red blood cell (RBC) disorders, such as sickle cell disease, hereditary spherocytosis, and diabetes, alterations to the size and shape of RBCs due to either mutations of RBC proteins or changes to the extracellular environment, lead to compromised cell deformability, impaired cell stability, and increased propensity to aggregate. Numerous laboratory approaches have been implemented to elucidate the pathogenesis of RBC disorders. Concurrently, computational RBC models have been developed to simulate the dynamics of RBCs under physiological and pathological conditions. In this work, we review recent laboratory and computational studies of disordered RBCs. Distinguished from previous reviews, we emphasize how experimental techniques and computational modeling can be synergically integrated to improve the understanding of the pathophysiology of hematological disorders.

Actin filaments partition primary cilia membranes into distinct fluid corrals

Lee et al. examine the dynamics of membrane proteins within the ciliary membrane using quantum dots and 2P Super FRAP. They show that ciliary membrane proteins diffuse rapidly within highly fluid local membrane domains delimited by actin filaments.

Physical properties of primary cilia membranes in living cells were examined using two independent, high-spatiotemporal-resolution approaches: fast tracking of single quantum dot–labeled G protein–coupled receptors and a novel two-photon super-resolution fluorescence recovery after photobleaching of protein ensemble. Both approaches demonstrated the cilium membrane to be partitioned into corralled domains spanning 274 ± 20 nm, within which the receptors are transiently confined for 0.71 ± 0.09 s. The mean membrane diffusion coefficient within the corrals, D_m1 = 2.9 ± 0.41 µm²/s, showed that the ciliary membranes were among the most fluid encountered. At longer times, the apparent membrane diffusion coefficient, D_m2 = 0.23 ± 0.05 µm²/s, showed that corral boundaries impeded receptor diffusion 13-fold. Mathematical simulations predict the probability of G protein–coupled receptors crossing corral boundaries to be 1 in 472. Remarkably, latrunculin A, cytochalasin D, and jasplakinolide treatments altered the corral permeability. Ciliary membranes are thus partitioned into highly fluid membrane nanodomains that are delimited by filamentous actin.

SPT and Imaging FCS Provide Complementary Information on the Dynamics of Plasma Membrane Molecules

The dynamics of biomolecules in the plasma membrane is of fundamental importance to understanding cellular processes. Cellular signaling often starts with extracellular ligand binding to a membrane receptor, which then transduces an intracellular signal. Ligand binding and receptor-complex activation often involve a complex rearrangement of proteins in the membrane, which results in changes in diffusion properties. Two widely used methods to characterize biomolecular diffusion are single-particle tracking (SPT) and imaging total internal reflection fluorescence correlation spectroscopy (ITIR-FCS). Here, we compare the results of recovered diffusion coefficients and mean-square displacements of the two methods by simulations of free, domain-confined, or meshwork diffusion. We introduce, to our knowledge, a new method for the determination of confinement radii from ITIR-FCS data. We further establish and demonstrate simultaneous SPT/ITIR-FCS for direct comparison within living cells. Finally, we compare the results obtained by SPT and ITIR-FCS for the receptor tyrosine kinase MET. Our results show that SPT and ITIR-FCS yield complementary information on diffusion properties of biomolecules in cell membranes.

Numerical calculation on a two-step subdiffusion behavior of lateral protein movement in plasma membranes

A two-step subdiffusion behavior of lateral movement of transmembrane proteins in plasma membranes has been observed by using single-molecule experiments. A nested double-compartment model where large compartments are divided into several smaller ones has been proposed in order to explain this observation. These compartments are considered to be delimited by membrane-skeleton "fences" and membrane-protein "pickets" bound to the fences. We perform numerical simulations of a master equation using a simple two-dimensional lattice model to investigate the heterogeneous diffusion dynamics behavior of transmembrane proteins within plasma membranes. We show that the experimentally observed two-step subdiffusion process can be described using fence and picket models combined with decreased local diffusivity of transmembrane proteins in the vicinity of the pickets. This allows us to explain the two-step subdiffusion behavior without explicitly introducing nested double compartments.

Computational Biomechanics of Human Red Blood Cells in Hematological Disorders

We review recent advances in multiscale modeling of the biomechanical characteristics of red blood cells (RBCs) in hematological diseases, and their relevance to the structure and dynamics of defective RBCs. We highlight examples of successful simulations of blood disorders including malaria and other hereditary disorders, such as sickle-cell anemia, spherocytosis, and elliptocytosis.

Mechanics of Biomimetic Liposomes Encapsulating an Actin Shell

Cell-shape changes are insured by a thin, dynamic, cortical layer of cytoskeleton underneath the plasma membrane. How this thin cortical structure impacts the mechanical properties of the whole cell is not fully understood. Here, we study the mechanics of liposomes or giant unilamellar vesicles, when a biomimetic actin cortex is grown at the inner layer of the lipid membrane via actin-nucleation-promoting factors. Using a hydrodynamic tube-pulling technique, we show that tube dynamics is clearly affected by the presence of an actin shell anchored to the lipid bilayer. The same force pulls much shorter tubes in the presence of the actin shell compared to bare membranes. However, in both cases, we observe that the dynamics of tube extrusion has two distinct features characteristic of viscoelastic materials: rapid elastic elongation, followed by a slower elongation phase at a constant rate. We interpret the initial elastic regime by an increase of membrane tension due to the loss of lipids into the tube. Tube length is considerably shorter for cortex liposomes at comparable pulling forces, resulting in a higher spring constant. The presence of the actin shell seems to restrict lipid mobility, as is observed in the corral effect in cells. The viscous regime for bare liposomes corresponds to a leakout of the internal liquid at constant membrane tension. The presence of the actin shell leads to a larger friction coefficient. As the tube is pulled from a patchy surface, membrane tension increases locally, leading to a Marangoni flow of lipids. As a conclusion, the presence of an actin shell is revealed by its action that alters membrane mechanics.

Analysis and Interpretation of Superresolution Single-Particle Trajectories

A large number (tens of thousands) of single molecular trajectories on a cell membrane can now be collected by superresolution methods. The data contains information about the diffusive motion of molecule, proteins, or receptors and here we review methods for its recovery by statistical analysis of the data. The information includes the forces, organization of the membrane, the diffusion tensor, the long-time behavior of the trajectories, and more. To recover the long-time behavior and statistics of long trajectories, a stochastic model of their nonequilibrium motion is required. Modeling and data analysis serve extracting novel biophysical features at an unprecedented spatiotemporal resolution. The review presents data analysis, modeling, and stochastic simulations applied in particular on surface receptors evolving in neuronal cells.

Residence times of receptors in dendritic spines analyzed by stochastic simulations in empirical domains

Analysis of high-density superresolution imaging of receptors reveals the organization of dendrites at nanoscale resolution. We present here an apparently novel method that uses local statistics extracted from short-range trajectories for the simulations of long-range trajectories in empirical live cell images. Based on these empirical simulations, we compute the residence time of a receptor in dendritic spines that accounts for receptors' local interactions and geometrical membrane organization. We report here that depending on the type of the spine, the residence time varies from 1 to 5 min. Moreover, we show that there exists transient organized structures, previously described as potential wells that can regulate the trafficking of receptors to dendritic spine: the simulation results suggest that receptor trafficking is regulated by transient structures.

Modeling of band-3 protein diffusion in the normal and defective red blood cell membrane

We employ a two-component red blood cell (RBC) membrane model to simulate lateral diffusion of band-3 proteins in the normal RBC and in the RBC with defective membrane proteins. The defects reduce the connectivity between the lipid bilayer and the membrane skeleton (vertical connectivity), or the connectivity of the membrane skeleton itself (horizontal connectivity), and are associated with the blood disorders of hereditary spherocytosis (HS) and hereditary elliptocytosis (HE) respectively. Initially, we demonstrate that the cytoskeleton limits band-3 lateral mobility by measuring the band-3 macroscopic diffusion coefficients in the normal RBC membrane and in a lipid bilayer without the cytoskeleton. Then, we study band-3 diffusion in the defective RBC membrane and quantify the relation between band-3 diffusion coefficients and percentage of protein defects in HE RBCs. In addition, we illustrate that at low spectrin network connectivity (horizontal connectivity) band-3 subdiffusion can be approximated as anomalous diffusion, while at high horizontal connectivity band-3 diffusion is characterized as confined diffusion. Our simulations show that the band-3 anomalous diffusion exponent depends on the percentage of protein defects in the membrane cytoskeleton. We also confirm that the introduction of attraction between the lipid bilayer and the spectrin network reduces band-3 diffusion, but we show that this reduction is lower than predicted by the percolation theory. Furthermore, we predict that the attractive force between the spectrin filament and the lipid bilayer is at least 20 times smaller than the binding forces at band-3 and glycophorin C, the two major membrane binding sites. Finally, we explore diffusion of band-3 particles in the RBC membrane with defects related to vertical connectivity. We demonstrate that in this case band-3 diffusion can be approximated as confined diffusion for all attraction levels between the spectrin network and the lipid bilayer. By comparing the diffusion coefficients measured in horizontal vs. vertical defects, we conclude that band-3 mobility is primarily controlled by the horizontal connectivity.

Lipid Exchange Envelope Penetration (LEEP) of Nanoparticles for Plant Engineering: A Universal Localization Mechanism

Nanoparticles offer clear advantages for both passive and active penetration into biologically important membranes. However, the uptake and localization mechanism of nanoparticles within living plants, plant cells, and organelles has yet to be elucidated.1 Here, we examine the subcellular uptake and kinetic trapping of a wide range of nanoparticles for the first time, using the plant chloroplast as a model system, but validated in vivo in living plants. Confocal visible and near-infrared fluorescent microscopy and single particle tracking of gold-cysteine-AF405 (GNP-Cys-AF405), streptavidin-quantum dot (SA-QD), dextran and poly(acrylic acid) nanoceria, and various polymer-wrapped single-walled carbon nanotubes (SWCNTs), including lipid-PEG-SWCNT, chitosan-SWCNT and 30-base (dAdT) sequence of ssDNA (AT)15 wrapped SWCNTs (hereafter referred to as ss(AT)15-SWCNT), are used to demonstrate that particle size and the magnitude, but not the sign, of the zeta potential are key in determining whether a particle is spontaneously and kinetically trapped within the organelle, despite the negative zeta potential of the envelope. We develop a mathematical model of this lipid exchange envelope and penetration (LEEP) mechanism, which agrees well with observations of this size and zeta potential dependence. The theory predicts a critical particle size below which the mechanism fails at all zeta potentials, explaining why nanoparticles are critical for this process. LEEP constitutes a powerful particulate transport and localization mechanism for nanoparticles within the plant system.

Regulated Dynamic Trafficking of Neurexins Inside and Outside of Synaptic Terminals

Synapses depend on trafficking of key membrane proteins by lateral diffusion from surface populations and by exocytosis from intracellular pools. The cell adhesion molecule neurexin (Nrxn) plays essential roles in synapses, but the dynamics and regulation of its trafficking are unknown. Here, we performed single-particle tracking and live imaging of transfected, epitope-tagged Nrxn variants in cultured rat and mouse wild-type or knock-out neurons. We observed that structurally larger αNrxn molecules are more mobile in the plasma membrane than smaller βNrxns because αNrxns displayed higher diffusion coefficients in extrasynaptic regions and excitatory or inhibitory terminals. We found that well characterized interactions with extracellular binding partners regulate the surface mobility of Nrxns. Binding to neurexophilin-1 (Nxph1) reduced the surface diffusion of αNrxns when both molecules were coexpressed. Conversely, impeding other interactions by insertion of splice sequence #4 or removal of extracellular Ca(2+) augmented the mobility of αNrxns and βNrxns. We also determined that fast axonal transport delivers Nrxns to the neuronal surface because Nrxns comigrate as cargo on synaptic vesicle protein transport vesicles (STVs). Unlike surface mobility, intracellular transport of βNrxn(+) STVs was faster than that of αNrxns, but both depended on the microtubule motor protein KIF1A and neuronal activity regulated the velocity. Large spontaneous fusion of Nrxn(+) STVs occurred simultaneously with synaptophysin on axonal membranes mostly outside of active presynaptic terminals. Surface Nrxns enriched at synaptic terminals where αNrxns and Nxph1/αNrxns recruited GABAAR subunits. Therefore, our results identify regulated dynamic trafficking as an important property of Nrxns that corroborates their function at synapses.

SIGNIFICANCE STATEMENT

Synapses mediate most functions in our brains and depend on the precise and timely delivery of key molecules throughout life. Neurexins (Nrxns) are essential synaptic cell adhesion molecules that are involved in synaptic transmission and differentiation of synaptic contacts. In addition, Nrxns have been linked to neuropsychiatric diseases such as autism. Because little is known about the dynamic aspects of trafficking of neurexins to synapses, we investigated this important question using single-molecule tracking and time-lapse imaging. We identify distinct differences between major Nrxn variants both in surface mobility and during intracellular transport. Because their dynamic behavior is highly regulated, for example, by different binding activities, these processes have immediate consequences for the function of Nrxns at synapses.

Effects of protein crowding on membrane systems

Cellular membranes are typically decorated with a plethora of embedded and adsorbed macromolecules, e.g. proteins, that participate in numerous vital processes. With typical surface densities of 30,000 proteins per μm(2) cellular membranes are indeed crowded places that leave only few nanometers of private space for individual proteins. Here, we review recent advances in our understanding of protein crowding in membrane systems. We first give a brief overview on state-of-the-art approaches in experiment and simulation that are frequently used to study crowded membranes. After that, we review how crowding can affect diffusive transport of proteins and lipids in membrane systems. Next, we discuss lipid and protein sorting in crowded membrane systems, including effects like protein cluster formation, phase segregation, and lipid droplet formation. Subsequently, we highlight recent progress in uncovering crowding-induced conformational changes of membranes, e.g. membrane budding and vesicle formation. Finally, we give a short outlook on potential future developments in the field of crowded membrane systems. This article is part of a Special Issue entitled: Biosimulations edited by Ilpo Vattulainen and Tomasz Róg.

A review of progress in single particle tracking: from methods to biophysical insights

Optical microscopy has for centuries been a key tool to study living cells with minimum invasiveness. The advent of single molecule techniques over the past two decades has revolutionized the field of cell biology by providing a more quantitative picture of the complex and highly dynamic organization of living systems. Amongst these techniques, single particle tracking (SPT) has emerged as a powerful approach to study a variety of dynamic processes in life sciences. SPT provides access to single molecule behavior in the natural context of living cells, thereby allowing a complete statistical characterization of the system under study. In this review we describe the foundations of SPT together with novel optical implementations that nowadays allow the investigation of single molecule dynamic events with increasingly high spatiotemporal resolution using molecular densities closer to physiological expression levels. We outline some of the algorithms for the faithful reconstruction of SPT trajectories as well as data analysis, and highlight biological examples where the technique has provided novel insights into the role of diffusion regulating cellular function. The last part of the review concentrates on different theoretical models that describe anomalous transport behavior and ergodicity breaking observed from SPT studies in living cells.

Method for simultaneous localization and parameter estimation in particle tracking experiments

We present a numerical method for the simultaneous localization and parameter estimation of a fluorescent particle undergoing a discrete-time continuous-state Markov process. In particular, implementation of the method proposed in this work yields an approximation to the posterior density of the particle positions over time in addition to maximum likelihood estimates of fixed, unknown parameters. The method employs sequential Monte Carlo methods and can take into account complex, potentially nonlinear noise models, including shot noise and camera-specific readout noise, as well as a wide variety of motion models and observation models, including those representing recent engineered point spread functions. We demonstrate the technique by applying it to four scenarios, including a particle undergoing free, confined, and tethered diffusions.

Erythrocyte membrane model with explicit description of the lipid bilayer and the spectrin network

The membrane of the red blood cell (RBC) consists of spectrin tetramers connected at actin junctional complexes, forming a two-dimensional (2D) sixfold triangular network anchored to the lipid bilayer. Better understanding of the erythrocyte mechanics in hereditary blood disorders such as spherocytosis, elliptocytosis, and especially, sickle cell disease requires the development of a detailed membrane model. In this study, we introduce a mesoscale implicit-solvent coarse-grained molecular dynamics (CGMD) model of the erythrocyte membrane that explicitly describes the phospholipid bilayer and the cytoskeleton, by extending a previously developed two-component RBC membrane model. We show that the proposed model represents RBC membrane with the appropriate bending stiffness and shear modulus. The timescale and self-consistency of the model are established by comparing our results with experimentally measured viscosity and thermal fluctuations of the RBC membrane. Furthermore, we measure the pressure exerted by the cytoskeleton on the lipid bilayer. We find that defects at the anchoring points of the cytoskeleton to the lipid bilayer (as in spherocytes) cause a reduction in the pressure compared with an intact membrane, whereas defects in the dimer-dimer association of a spectrin filament (as in elliptocytes) cause an even larger decrease in the pressure. We conjecture that this finding may explain why the experimentally measured diffusion coefficients of band-3 proteins are higher in elliptocytes than in spherocytes, and higher than in normal RBCs. Finally, we study the effects that possible attractive forces between the spectrin filaments and the lipid bilayer have on the pressure applied on the lipid bilayer by the filaments. We discover that the attractive forces cause an increase in the pressure as they diminish the effect of membrane protein defects. As this finding contradicts with experimental results, we conclude that the attractive forces are moderate and do not impose a complete attachment of the filaments to the lipid bilayer.

Oxygen depletion speeds and simplifies diffusion in HeLa cells

Many cell types undergo a hypoxic response in the presence of low oxygen, which can lead to transcriptional, metabolic, and structural changes within the cell. Many biophysical studies to probe the localization and dynamics of single fluorescently labeled molecules in live cells either require or benefit from low-oxygen conditions. In this study, we examine how low-oxygen conditions alter the mobility of a series of plasma membrane proteins with a range of anchoring motifs in HeLa cells at 37°C. Under high-oxygen conditions, diffusion of all proteins is heterogeneous and confined. When oxygen is reduced with an enzymatic oxygen-scavenging system for ≥ 15 min, diffusion rates increase by > 2-fold, motion becomes unconfined on the timescales and distance scales investigated, and distributions of diffusion coefficients are remarkably consistent with those expected from Brownian motion. More subtle changes in protein mobility are observed in several other laboratory cell lines examined under both high- and low-oxygen conditions. Morphological changes and actin remodeling are observed in HeLa cells placed in a low-oxygen environment for 30 min, but changes are less apparent in the other cell types investigated. This suggests that changes in actin structure are responsible for increased diffusion in hypoxic HeLa cells, although superresolution localization measurements in chemically fixed cells indicate that membrane proteins do not colocalize with F-actin under either experimental condition. These studies emphasize the importance of controls in single-molecule imaging measurements, and indicate that acute response to low oxygen in HeLa cells leads to dramatic changes in plasma membrane structure. It is possible that these changes are either a cause or consequence of phenotypic changes in solid tumor cells associated with increased drug resistance and malignancy.

A quantitative imaging-based screen reveals the exocyst as a network hub connecting endocytosis and exocytosis

The mechanisms governing the spatial organization of endocytosis and exocytosis are ill defined. A quantitative imaging screen and high-density single-vesicle tracking are used to identify mutants that are defective in endocytic and exocytic vesicle organization. The screen identifies a role for the exocyst complex in connecting the two pathways.

The coupling of endocytosis and exocytosis underlies fundamental biological processes ranging from fertilization to neuronal activity and cellular polarity. However, the mechanisms governing the spatial organization of endocytosis and exocytosis require clarification. Using a quantitative imaging-based screen in budding yeast, we identified 89 mutants displaying defects in the localization of either one or both pathways. High-resolution single-vesicle tracking revealed that the endocytic and exocytic mutants she4∆ and bud6∆ alter post-Golgi vesicle dynamics in opposite ways. The endocytic and exocytic pathways display strong interdependence during polarity establishment while being more independent during polarity maintenance. Systems analysis identified the exocyst complex as a key network hub, rich in genetic interactions with endocytic and exocytic components. Exocyst mutants displayed altered endocytic and post-Golgi vesicle dynamics and interspersed endocytic and exocytic domains compared with control cells. These data are consistent with an important role for the exocyst in coordinating endocytosis and exocytosis.

Detecting protein association at the T cell plasma membrane

At the moment, many models on T cell signaling rely on results obtained via rather indirect methodologies, which makes direct comparison and conclusions to the in vivo situation difficult. Recently, a variety of new imaging methods were developed, which have the potential to directly shed light onto the mysteries of protein association at the T cell membrane. While the new modalities are extremely promising, for a broad readership it may be difficult to judge the results, since technological shortcomings are not always obvious. In this review article, we put key questions on the mechanism of protein interactions in the T cell plasma membrane into relation with techniques that allow to address such questions. We discuss applicability of the techniques, their strengths and weaknesses. This article is part of a Special Issue entitled: Nanoscale membrane organisation and signalling.

Transient cholesterol effects on nicotinic acetylcholine receptor cell-surface mobility

To what extent do cholesterol-rich lipid platforms modulate the supramolecular organization of the nicotinic acetylcholine receptor (AChR)? To address this question, the dynamics of AChR particles at high density and its cholesterol dependence at the surface of mammalian cells were studied by combining total internal reflection fluorescence microscopy and single-particle tracking. AChR particles tagged with a monovalent ligand, fluorescent α-bungarotoxin (αBTX), exhibited two mobile pools: i) a highly mobile one undergoing simple Brownian motion (16%) and ii) one with restricted motion (∼50%), the rest being relatively immobile (∼44%). Depletion of membrane cholesterol by methyl-α-cyclodextrin increased the fraction of the first pool to 22% and 33% after 15 and 40 min, respectively; the pool undergoing restricted motion diminished from 50% to 44% and 37%, respectively. Monoclonal antibody binding results in AChR crosslinking-internalization after 2 h; here, antibody binding immobilized within minutes ∼20% of the totally mobile AChR. This proportion dramatically increased upon cholesterol depletion, especially during the initial 10 min (83.3%). Thus, antibody crosslinking and cholesterol depletion exhibited a mutually synergistic effect, increasing the average lifetime of cell-surface AChRs∼10 s to ∼20 s. The instantaneous (microscopic) diffusion coefficient D2-4 of the AChR obtained from the MSD analysis diminished from ∼0.001 µm2 s(-1) to ∼0.0001-0.00033 µm2 s(-1) upon cholesterol depletion, ∼30% of all particles falling into the stationary mode. Thus, muscle-type AChR exhibits heterogeneous motional regimes at the cell surface, modulated by the combination of intrinsic (its supramolecular organization) and extrinsic (membrane cholesterol content) factors.

High-density single-particle tracking: quantifying molecule organization and dynamics at the nanoscale

The organization and dynamics of proteins are fundamental parameters for cellular function. Their study, at the single-molecule level, provides precise information on molecular interactions. Over the last 30 years, the single-particle tracking imaging technique has proven its capability to efficiently quantify such parameters in many biological systems, with nanometric accuracy and millisecond temporal resolutions. Nevertheless, the low concentration of labeling required for single-molecule imaging usually prevents the extraction of large statistics. The advent of high-density single-molecule-based super-resolution techniques has revolutionized the field, allowing monitoring of thousands of biomolecules in the minute timescale and providing unprecedented insight into the molecular organization and dynamics of cellular compounds. In this issue, I will review the main principles of single-particle tracking, a highly interdisciplinary technique at the interface between microscopy, image analysis and labeling strategies. I will point out the advantages brought by high-density single-particle tracking which will be illustrated with a few recent biological results.

Impact of morphology on diffusive dynamics on curved surfaces

Diffusive processes on nonplanar substrates are deeply relevant for cellular function and transport and increasingly used to probe and characterize the behavior of proteins in membranes. We present analytical and numerical analyses of in-plane diffusion of discrete particles on curved geometries reflecting various generic motifs in biology and explore, in particular, the effect that the shape of the substrate has on the characteristic time scales of diffusive processes. To this end, we consider both collective measures (the relaxation of concentration profiles towards equilibrium) and single-particle measures (escape rates and first passage times of individual diffusing molecules): the first relevant for the correct interpretation of FRAP experiments in curved environments; the second, for single-particle tracking probes. Each of these measures is sensitively affected by the morphology of the substrate, and we find that the exit rate out of a domain is not uniquely set by the size of its boundary, illustrating the general principle we reveal: By varying the shape of a substrate, Nature can control the diffusive time scales in a microenvironment without changing the bare substrate properties.

The fast polarization modulation based dual-focus fluorescence correlation spectroscopy

We introduce two new alternative experimental realizations of dual focus fluorescence correlation spectroscopy (2fFCS), a method which allows for obtaining absolute diffusion coefficient of fast moving fluorescing molecules at nanomolar concentrations, based on fast polarization modulation of the excitation beam by a resonant electro-optical modulator. The first approach rotates every second linearly polarized laser pulse by 90 degrees to obtain independent intensity readout for both foci, similar to original design. The second approach combines polarization modulation of cw laser and fluorescence lifetime correlation spectroscopy (FLCS) like analysis to obtain clean correlation curves for both overlapping foci. We tested our new approaches with different lasers and samples, revealed a need for intensity cross-talk corrections by comparing the methods with each other and discussed experimental artifacts stemming from improper polarization alignment and detector afterpulsing. The advantages of our solutions are that the polarization rotation approach requires just one pulsed laser for each wavelength, that the polarization modulation approach even mitigates the need of pulsed lasers by using standard cw lasers and that it allows the DIC prism to be placed at an arbitrary angle. As a consequence the presented experimental solutions for 2fFCS can be more easily implemented into commercial laser scanning microscopes.

Anomalous diffusion models and their properties: non-stationarity, non-ergodicity, and ageing at the centenary of single particle tracking

This Perspective summarises the properties of a variety of anomalous diffusion processes and provides the necessary tools to analyse and interpret recorded anomalous diffusion data.

TRF1 and TRF2 use different mechanisms to find telomeric DNA but share a novel mechanism to search for protein partners at telomeres

Human telomeres are maintained by the shelterin protein complex in which TRF1 and TRF2 bind directly to duplex telomeric DNA. How these proteins find telomeric sequences among a genome of billions of base pairs and how they find protein partners to form the shelterin complex remains uncertain. Using single-molecule fluorescence imaging of quantum dot-labeled TRF1 and TRF2, we study how these proteins locate TTAGGG repeats on DNA tightropes. By virtue of its basic domain TRF2 performs an extensive 1D search on nontelomeric DNA, whereas TRF1’s 1D search is limited. Unlike the stable and static associations observed for other proteins at specific binding sites, TRF proteins possess reduced binding stability marked by transient binding (∼9–17 s) and slow 1D diffusion on specific telomeric regions. These slow diffusion constants yield activation energy barriers to sliding ∼2.8–3.6 κ_BT greater than those for nontelomeric DNA. We propose that the TRF proteins use 1D sliding to find protein partners and assemble the shelterin complex, which in turn stabilizes the interaction with specific telomeric DNA. This ‘tag-team proofreading’ represents a more general mechanism to ensure a specific set of proteins interact with each other on long repetitive specific DNA sequences without requiring external energy sources.

Control of flux by narrow passages and hidden targets in cellular biology

Critical biological processes, such as synaptic plasticity and transmission, activation of genes by transcription factors, or double-strained DNA break repair, are controlled by diffusion in structures that have both large and small spatial scales. These may be small binding sites inside or on the surface of the cell, or narrow passages between subcellular compartments. The great disparity in spatial scales is the key to controlling cell function by structure. We report here recent progress on resolving analytical and numerical difficulties in extracting properties from experimental data, from biophysical models, and from Brownian dynamics simulations of diffusion in multi-scale structures. This progress is achieved by developing an analytical approximation methodology for solving the model equations. The reported results are applied to analysis and simulations of subcellular processes and to the quantification of their biological functions.

Neurexin-1β binding to neuroligin-1 triggers the preferential recruitment of PSD-95 versus gephyrin through tyrosine phosphorylation of neuroligin-1

Adhesion between neurexin-1β (Nrx1β) and neuroligin-1 (Nlg1) induces early recruitment of the postsynaptic density protein 95 (PSD-95) scaffold; however, the associated signaling mechanisms are unknown. To dissociate the effects of ligand binding and receptor multimerization, we compared conditions in which Nlg1 in neurons was bound to Nrx1β or nonactivating HA antibodies. Time-lapse imaging, fluorescence recovery after photobleaching, and single-particle tracking demonstrated that in addition to aggregating Nlg1, Nrx1β binding stimulates the interaction between Nlg1 and PSD-95. Phosphotyrosine immunoblots and pull-down of gephyrin by Nlg1 peptides in vitro showed that Nlg1 can be phosphorylated at a unique tyrosine (Y782), preventing gephyrin binding. Expression of Nlg1 point mutants in neurons indicated that Y782 phosphorylation controls the preferential binding of Nlg1 to PSD-95 versus gephyrin, and accordingly the formation of inhibitory and excitatory synapses. We propose that ligand-induced changes in the Nlg1 phosphotyrosine level control the balance between excitatory and inhibitory scaffold assembly during synapse formation and stabilization.

[Cellular and molecular motions: order and disorder]

Video-microscopy allows monitoring the dynamics of biological components, specifically labeled, usually by fluorescent tags such as GFP or quantum dots, either at the cellular or at the molecular scale. Reconstructing trajectories over time with dedicated algorithms allows to characterize on both scale different categories of movement, such as random, linear or confined, and to report events such as transient confinements among recorded species and with their environment. Single cell or molecule measurements hence provide detailed access not only to mean values of relevant descriptors, such as speed or interaction duration, but also to the exhaustive distribution of recorded values.

Visualization of actin filaments and monomers in somatic cell nuclei

Fluorescent nuclear actin reporters are used to determine the distribution of nuclear actin in live somatic cells and evaluate its potential functions. They reveal distinct monomeric and filamentous actin populations in nuclei of live somatic cells and implicate nuclear actin in mRNA processing and organization of the nucleoplasm.

In addition to its long-studied presence in the cytoplasm, actin is also found in the nuclei of eukaryotic cells. The function and form (monomer, filament, or noncanonical oligomer) of nuclear actin are hotly debated, and its localization and dynamics are largely unknown. To determine the distribution of nuclear actin in live somatic cells and evaluate its potential functions, we constructed and validated fluorescent nuclear actin probes. Monomeric actin probes concentrate in nuclear speckles, suggesting an interaction of monomers with RNA-processing factors. Filamentous actin probes recognize discrete structures with submicron lengths that are excluded from chromatin-rich regions. In time-lapse movies, these actin filament structures exhibit one of two types of mobility: 1) diffusive, with an average diffusion coefficient of 0.06–0.08 μm²/s, or (2) subdiffusive, with a mobility coefficient of 0.015 μm²/s. Individual filament trajectories exhibit features of particles moving within a viscoelastic mesh. The small size of nuclear actin filaments is inconsistent with a role in micron-scale intranuclear transport, and their localization suggests that they do not participate directly in chromatin-based processes. Our results instead suggest that actin filaments form part of a large, viscoelastic structure in the nucleoplasm and may act as scaffolds that help organize nuclear contents.

Ensemble and single particle fluorimetric techniques in concerted action to study the diffusion and aggregation of the glycine receptor α3 isoforms in the cell plasma membrane

The spatio-temporal membrane behavior of glycine receptors (GlyRs) is known to be of influence on receptor homeostasis and functionality. In this work, an elaborate fluorimetric strategy was applied to study the GlyR α3K and L isoforms. Previously established differential clustering, desensitization and synaptic localization of these isoforms imply that membrane behavior is crucial in determining GlyR α3 physiology. Therefore diffusion and aggregation of homomeric α3 isoform-containing GlyRs were studied in HEK 293 cells. A unique combination of multiple diffraction-limited ensemble average methods and subdiffraction single particle techniques was used in order to achieve an integrated view of receptor properties. Static measurements of aggregation were performed with image correlation spectroscopy (ICS) and, single particle based, direct stochastic optical reconstruction microscopy (dSTORM). Receptor diffusion was measured by means of raster image correlation spectroscopy (RICS), temporal image correlation spectroscopy (TICS), fluorescence recovery after photobleaching (FRAP) and single particle tracking (SPT). The results show a significant difference in diffusion coefficient and cluster size between the isoforms. This reveals a positive correlation between desensitization and diffusion and disproves the notion that receptor aggregation is a universal mechanism for accelerated desensitization. The difference in diffusion coefficient between the clustering GlyR α3L and the non-clustering GlyR α3K cannot be explained by normal diffusion. SPT measurements indicate that the α3L receptors undergo transient trapping and directed motion, while the GlyR α3K displays mild hindered diffusion. These findings are suggestive of differential molecular interaction of the isoforms after incorporation in the membrane.

Mapping molecular diffusion in the plasma membrane by Multiple-Target Tracing (MTT)

Our goal is to obtain a comprehensive description of molecular processes occurring at cellular membranes in different biological functions. We aim at characterizing the complex organization and dynamics of the plasma membrane at single-molecule level, by developing analytic tools dedicated to Single-Particle Tracking (SPT) at high density: Multiple-Target Tracing (MTT). Single-molecule videomicroscopy, offering millisecond and nanometric resolution, allows a detailed representation of membrane organization by accurately mapping descriptors such as cell receptors localization, mobility, confinement or interactions. We revisited SPT, both experimentally and algorithmically. Experimental aspects included optimizing setup and cell labeling, with a particular emphasis on reaching the highest possible labeling density, in order to provide a dynamic snapshot of molecular dynamics as it occurs within the membrane. Algorithmic issues concerned each step used for rebuilding trajectories: peaks detection, estimation and reconnection, addressed by specific tools from image analysis. Implementing deflation after detection allows rescuing peaks initially hidden by neighboring, stronger peaks. Of note, improving detection directly impacts reconnection, by reducing gaps within trajectories. Performances have been evaluated using Monte-Carlo simulations for various labeling density and noise values, which typically represent the two major limitations for parallel measurements at high spatiotemporal resolution. The nanometric accuracy obtained for single molecules, using either successive on/off photoswitching or non-linear optics, can deliver exhaustive observations. This is the basis of nanoscopy methods such as STORM, PALM, RESOLFT or STED, which may often require imaging fixed samples. The central task is the detection and estimation of diffraction-limited peaks emanating from single-molecules. Hence, providing adequate assumptions such as handling a constant positional accuracy instead of Brownian motion, MTT is straightforwardly suited for nanoscopic analyses. Furthermore, MTT can fundamentally be used at any scale: not only for molecules, but also for cells or animals, for instance. Hence, MTT is a powerful tracking algorithm that finds applications at molecular and cellular scales.

Activated STAT1 transcription factors conduct distinct saltatory movements in the cell nucleus

The activation of STAT transcription factors is a critical determinant of their subcellular distribution and their ability to regulate gene expression. Yet, it is not known how activation affects the behavior of individual STAT molecules in the cytoplasm and nucleus. To investigate this issue, we injected fluorescently labeled STAT1 in living HeLa cells and traced them by single-molecule microscopy. We determined that STAT1 moved stochastically in the cytoplasm and nucleus with very short residence times (<0.03 s) before activation. Upon activation, STAT1 mobility in the cytoplasm decreased ∼2.5-fold, indicating reduced movement of STAT1/importinα/β complexes to the nucleus. In the nucleus, activated STAT1 displayed a distinct saltatory mobility, with residence times of up to 5 s and intermittent diffusive motion. In this manner, activated STAT1 factors can occupy their putative chromatin target sites within ∼2 s. These results provide a better understanding of the timescales on which cellular signaling and regulated gene transcription operate at the single-molecule level.