Analysis of transient behavior in complex trajectories: application to secretory vesicle dynamics

Vesicle docking and fusion pore modulation by the neuronal calcium sensor Synaptotagmin-1

Synaptotagmin-1 (Syt1) is a major calcium sensor for rapid neurotransmitter release in neurons and hormone release in many neuroendocrine cells. It possesses two tandem cytosolic C2 domains that bind calcium, negatively charged phospholipids, and the neuronal SNARE complex. Calcium binding to Syt1 triggers exocytosis, but how this occurs is not well understood. Syt1 has additional roles in docking dense core vesicles (DCV) and synaptic vesicles (SV) to the plasma membrane (PM) and in regulating fusion pore dynamics. Thus, Syt1 perturbations could affect release through vesicle docking, fusion triggering, fusion pore regulation, or a combination of these. Here, using a human neuroendocrine cell line, we show that neutralization of highly conserved polybasic patches in either C2 domain of Syt1 impairs both DCV docking and efficient release of serotonin from DCVs. Interestingly, the same mutations resulted in larger fusion pores and faster release of serotonin during individual fusion events. Thus, Syt1's roles in vesicle docking, fusion triggering, and fusion pore control may be functionally related.

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.

Cell Membrane Tension Gradients, Membrane Flows, and Cellular Processes

Cell membrane tension affects and is affected by many fundamental cellular processes, yet it is poorly understood. Recent experiments show that membrane tension can propagate at vastly different speeds in different cell types, reflecting physiological adaptations. Here we briefly review the current knowledge about membrane tension gradients, membrane flows, and their physiological context.

Identification of critical points in transient electroconvection dynamics using tensor bundles

We present and demonstrate a method to produce quantitative and qualitative descriptions of transient dynamics from empirical data, with the purpose of analyzing a novel transient discovered in liquid crystal electroconvection. By constructing a tensor bundle around an exemplar transient and creating a chart at every step aligned with the direction of propagation, we show that the Jacobian estimation problem can be reduced by a single dimension, relaxing data requirements and clarifying results. We apply this analysis to identify the onset of a boundary crisis in a predator-prey model. The resulting tensor bundle estimated from image data taken during a dynamical phase transition in a nematic liquid crystal details the behavior of the system along that trajectory, allowing topological analysis. Using this method, we quantify a saddle point in the phase space that drives the initial dynamics during a sudden increase in the driving voltage.

Slow kinesin-dependent microtubular transport facilitates ribbon synapse assembly in developing cochlear inner hair cells

Sensory synapses are characterized by electron-dense presynaptic specializations, so-called synaptic ribbons. In cochlear inner hair cells (IHCs), ribbons play an essential role as core active zone (AZ) organizers, where they tether synaptic vesicles, cluster calcium channels and facilitate the temporally-precise release of primed vesicles. While a multitude of studies aimed to elucidate the molecular composition and function of IHC ribbon synapses, the developmental formation of these signalling complexes remains largely elusive to date. To address this shortcoming, we performed long-term live-cell imaging of fluorescently-labelled ribbon precursors in young postnatal IHCs to track ribbon precursor motion. We show that ribbon precursors utilize the apico-basal microtubular (MT) cytoskeleton for targeted trafficking to the presynapse, in a process reminiscent of slow axonal transport in neurons. During translocation, precursor volume regulation is achieved by highly dynamic structural plasticity - characterized by regularly-occurring fusion and fission events. Pharmacological MT destabilization negatively impacted on precursor translocation and attenuated structural plasticity, whereas genetic disruption of the anterograde molecular motor Kif1a impaired ribbon volume accumulation during developmental maturation. Combined, our data thus indicate an essential role of the MT cytoskeleton and Kif1a in adequate ribbon synapse formation and structural maintenance.

Pre-fusion motion state determines the heterogeneity of membrane fusion dynamics for large dense-core vesicles

AIM

In neuroendocrine cells, large dense-core vesicles (LDCVs) undergo highly regulated pre-fusion processes before releasing hormones via membrane fusion. Significant heterogeneity has been found for LDCV population based on the dynamics of membrane fusion. However, how the pre-fusion status impacts the heterogeneity of LDCVs still remains unclear. Hence, we explored pre-fusion determinants of heterogeneous membrane fusion procedure of LDCV subpopulations.

METHODS

We assessed the pre-fusion motion of two LDCV subpopulations with distinct membrane fusion dynamics individually, using total internal reflection fluorescence microscopy. These two subpopulations were isolated by blocking Rho GTPase-dependent actin reorganization using Clostridium difficile toxin B (ToxB), which selectively targets the fast fusion vesicle pool.

RESULTS

We found that the fast fusion subpopulation was in an active motion mode prior to release, termed "active" LDCV pool, while vesicles from the slow fusion subpopulation were also moving but in a significantly more confined status, forming an "inert" pool. The depletion of the active pool by ToxB also eliminated fast fusion vesicles and was not rescued by pre-treatment with phorbol ester. A mild actin reorganization blocker, latrunculin A, that partially disrupted the active pool, only slightly attenuated the fast fusion subpopulation.

CONCLUSION

The pre-fusion motion state of LDCVs also exhibits heterogeneity and dictates the heterogeneous fusion pore dynamics. Rearrangement of F-actin network mediates vesicle pre-fusion motion and subsequently determines the membrane fusion kinetics.

TrajPy: empowering feature engineering for trajectory analysis across domains

Motivation

Trajectories, which are sequentially measured quantities that form a path, are an important presence in many different fields, from hadronic beams in physics to electrocardiograms in medicine. Trajectory analysis requires the quantification and classification of curves, either by using statistical descriptors or physics-based features. To date, no extensive and user-friendly package for trajectory analysis has been readily available, despite its importance and potential application across various domains.

Results

We have developed TrajPy, a free, open-source Python package that serves as a complementary tool for empowering trajectory analysis. This package features a user-friendly graphical user interface and offers a set of physical descriptors that aid in characterizing these complex structures. TrajPy has already been successfully applied to studies of mitochondrial motility in neuroblastoma cell lines and the analysis of in silico models for cell migration, in combination with image analysis.

Availability and implementation

The TrajPy package is developed in Python 3 and is released under the GNU GPL-3.0 license. It can easily be installed via PyPi, and the development source code is accessible at the repository: https://github.com/ocbe-uio/TrajPy/. The package release is also automatically archived with the DOI 10.5281/zenodo.3656044.

Interface extension is a continuum property suggesting a linkage between AP contractile and DV lengthening processes

In the early Drosophila embryo, the elongation of the anterior-posterior (AP) body axis is driven by cell intercalation in the germband epithelium. Neighboring cells intercalate through the contraction of AP interfaces (between AP neighbors) into higher-order vertices, which then resolve through the extension of new dorsal-ventral (DV) interfaces (between DV neighbors). Although interface contraction has been extensively studied, less is known about how new interfaces are established. Here we show that DV interface elongation behaviors initiate at the same time as AP contractions, and that DV interfaces which are newly created from resolution of higher-order vertices do not appear to possess a unique 'identity;' instead, all horizontal interfaces undergo lengthening, elongating through ratchetlike sliding behaviors analogous to those found in AP interfaces. Cortical F-actin networks are essential for high area oscillation amplitudes required for effective ratcheting. Our results suggest that, contrary to canonical models, the elongation of new DV interfaces is not produced by a mechanistically separate process. Instead, medial myosin populations drive oscillating radial forces in the cells to generate transient force asymmetries at all tricellular vertices, which-combined with planar polarized stabilization-produce directional ratcheted sliding to generate both AP interface contraction and DV interface elongation.

Large-Scale, Wavelet-Based Analysis of Lysosomal Trajectories and Co-Movements of Lysosomes with Nanoparticle Cargos

Lysosomes—that is, acidic organelles known for degradation/recycling—move through the cytoplasm alternating between bursts of active transport and short, diffusive motions or even pauses. While their mobility is essential for lysosomes’ fusogenic and non-fusogenic interactions with target organelles, their movements have not been characterized in adequate detail. Here, large-scale statistical analysis of lysosomal movement trajectories reveals that lysosome trajectories in all examined cell types—both cancer and noncancerous ones—are superdiffusive and characterized by heavy-tailed distributions of run and flight lengths. Consideration of Akaike weights for various potential models (lognormal, power law, truncated power law, stretched exponential, and exponential) indicates that the experimental data are best described by the lognormal distribution, which, in turn, can be related to one of the space-search strategies particularly effective when “thorough” search needs to balance search for rare target(s) (organelles). In addition, automated, wavelet-based analysis allows for co-tracking the motions of lysosomes and the cargos they carry—particularly the nanoparticle aggregates known to cause selective lysosome disruption in cancerous cells. The methods we describe here could help study nanoparticle assemblies, viruses, and other objects transported inside various vesicle types, as well as coordinated movements of organelles/particles in the cytoplasm. Custom-written code that includes integrated workflow for our analyses is made available for academic use.

A PtdIns(3,4,5)P3 dispersal switch engages cell ratcheting at specific cell surfaces

Force generation in epithelial tissues is often pulsatile, with actomyosin networks generating contractile forces before cyclically disassembling. This pulsed nature of cytoskeletal forces implies that there must be ratcheting mechanisms that drive processive transformations in cell shape. Previous work has shown that force generation is coordinated with endocytic remodeling; however, how ratcheting becomes engaged at specific cell surfaces remains unclear. Here, we report that PtdIns(3,4,5)P₃ is a critical lipid-based cue for ratcheting engagement. The Sbf RabGEF binds to PIP₃, and disruption of PIP₃ reveals a dramatic switching behavior in which medial ratcheting is activated and epithelial cells begin globally constricting apical surfaces. PIP₃ enrichments are developmentally regulated, with mesodermal cells having high apical PIP₃ while germband cells have higher interfacial PIP₃. Finally, we show that JAK/STAT signaling constitutes a second pathway that combinatorially regulates Sbf/Rab35 recruitment. Our results elucidate a complex lipid-dependent regulatory machinery that directs ratcheting engagement in epithelial tissues.

Tracking single particles for hours via continuous DNA-mediated fluorophore exchange

Monitoring biomolecules in single-particle tracking experiments is typically achieved by employing fixed organic dyes or fluorescent fusion proteins linked to a target of interest. However, photobleaching typically limits observation times to merely a few seconds, restricting downstream statistical analysis and observation of rare biological events. Here, we overcome this inherent limitation via continuous fluorophore exchange using DNA-PAINT, where fluorescently-labeled oligonucleotides reversibly bind to a single-stranded DNA handle attached to the target molecule. Such versatile and facile labeling allows uninterrupted monitoring of single molecules for extended durations. We demonstrate the power of our approach by observing DNA origami on membranes for tens of minutes, providing perspectives for investigating cellular processes on physiologically relevant timescales.

The length of single-particle tracking experiments are limited due to photobleaching. Here the authors achieve long-term single-particle tracking with continuous fluorophore exchange in DNA-PAINT and use this to observe DNA origami on lipid bilayers for tens of minutes.

FisB relies on homo-oligomerization and lipid binding to catalyze membrane fission in bacteria

Little is known about mechanisms of membrane fission in bacteria despite their requirement for cytokinesis. The only known dedicated membrane fission machinery in bacteria, fission protein B (FisB), is expressed during sporulation in Bacillus subtilis and is required to release the developing spore into the mother cell cytoplasm. Here, we characterized the requirements for FisB-mediated membrane fission. FisB forms mobile clusters of approximately 12 molecules that give way to an immobile cluster at the engulfment pole containing approximately 40 proteins at the time of membrane fission. Analysis of FisB mutants revealed that binding to acidic lipids and homo-oligomerization are both critical for targeting FisB to the engulfment pole and membrane fission. Experiments using artificial membranes and filamentous cells suggest that FisB does not have an intrinsic ability to sense or induce membrane curvature but can bridge membranes. Finally, modeling suggests that homo-oligomerization and trans-interactions with membranes are sufficient to explain FisB accumulation at the membrane neck that connects the engulfment membrane to the rest of the mother cell membrane during late stages of engulfment. Together, our results show that FisB is a robust and unusual membrane fission protein that relies on homo-oligomerization, lipid binding, and the unique membrane topology generated during engulfment for localization and membrane scission, but surprisingly, not on lipid microdomains, negative-curvature lipids, or curvature sensing.

NK cells integrate signals over large areas when building immune synapses but require local stimuli for degranulation

Immune synapses are large-scale, transient molecular assemblies that serve as platforms for antigen presentation to B and T cells and for target recognition by cytotoxic T cells and natural killer (NK) cells. The formation of an immune synapse is a tightly regulated, stepwise process in which the cytoskeleton, cell surface receptors, and intracellular signaling proteins rearrange into supramolecular activation clusters (SMACs). We generated artificial immune synapses (AIS) consisting of synthetic and natural ligands for the NK cell-activating receptors LFA-1 and CD16 by microcontact printing the ligands into circular-shaped SMAC structures. Live-cell imaging and analysis of fixed human NK cells in this reductionist system showed that the spatial distribution of activating ligands influenced the formation, stability, and outcome of NK cell synapses. Whereas engagement of LFA-1 alone promoted synapse initiation, combined engagement of LFA-1 and CD16 was required for the formation of mature synapses and degranulation. Organizing LFA-1 and CD16 ligands into donut-shaped AIS resulted in fewer long-lasting, symmetrical synapses compared to dot-shaped AIS. NK cells spreading evenly over either AIS shape exhibited similar arrangements of the lytic machinery. However, degranulation only occurred in regions containing ligands that therefore induced local signaling, suggesting the existence of a late checkpoint for degranulation. Our results demonstrate that the spatial organization of ligands in the synapse can affect its outcome, which could be exploited by target cells as an escape mechanism.

The coordination of spindle-positioning forces during the asymmetric division of the Caenorhabditis elegans zygote

In Caenorhabditis elegans zygote, astral microtubules generate forces essential to position the mitotic spindle, by pushing against and pulling from the cortex. Measuring microtubule dynamics there, we revealed the presence of two populations, corresponding to pulling and pushing events. It offers a unique opportunity to study, under physiological conditions, the variations of both spindle-positioning forces along space and time. We propose a threefold control of pulling force, by polarity, spindle position and mitotic progression. We showed that the sole anteroposterior asymmetry in dynein on-rate, encoding pulling force imbalance, is sufficient to cause posterior spindle displacement. The positional regulation, reflecting the number of microtubule contacts in the posterior-most region, reinforces this imbalance only in late anaphase. Furthermore, we exhibited the first direct proof that dynein processivity increases along mitosis. It reflects the temporal control of pulling forces, which strengthens at anaphase onset following mitotic progression and independently from chromatid separation. In contrast, the pushing force remains constant and symmetric and contributes to maintaining the spindle at the cell centre during metaphase.

Fundamentals of the logarithmic measure for revealing multimodal diffusion

We develop a theoretical foundation for a time-series analysis method suitable for revealing the spectrum of diffusion coefficients in mixed Brownian systems, for which no prior knowledge of particle distinction is required. This method is directly relevant for particle tracking in biological systems, in which diffusion processes are often nonuniform. We transform Brownian data onto the logarithmic domain, in which the coefficients for individual modes of diffusion appear as distinct spectral peaks in the probability density. We refer to the method as the logarithmic measure of diffusion, or simply as the logarithmic measure. We provide a general protocol for deriving analytical expressions for the probability densities on the logarithmic domain. The protocol is applicable for any number of spatial dimensions with any number of diffusive states. The analytical form can be fitted to data to reveal multiple diffusive modes. We validate the theoretical distributions and benchmark the accuracy and sensitivity of the method by extracting multimodal diffusion coefficients from two-dimensional Brownian simulations of polydisperse filament bundles. Bundling the filaments allows us to control the system nonuniformity and hence quantify the sensitivity of the method. By exploiting the anisotropy of the simulated filaments, we generalize the logarithmic measure to rotational diffusion. By fitting the analytical forms to simulation data, we confirm the method's theoretical foundation. An error analysis in the single-mode regime shows that the proposed method is comparable in accuracy to the standard mean-squared displacement approach for evaluating diffusion coefficients. For the case of multimodal diffusion, we compare the logarithmic measure against other, more sophisticated methods, showing that both model selectivity and extraction accuracy are comparable for small data sets. Therefore, we suggest that the logarithmic measure, as a method for multimodal diffusion coefficient extraction, is ideally suited for small data sets, a condition often confronted in the experimental context. Finally, we critically discuss the proposed benefits of the method and its information content.

An Estimation Algorithm for General Linear Single Particle Tracking Models with Time-Varying Parameters

Single Particle Tracking (SPT) is a powerful class of methods for studying the dynamics of biomolecules inside living cells. The techniques reveal the trajectories of individual particles, with a resolution well below the diffraction limit of light, and from them the parameters defining the motion model, such as diffusion coefficients and confinement lengths. Most existing algorithms assume these parameters are constant throughout an experiment. However, it has been demonstrated that they often vary with time as the tracked particles move through different regions in the cell or as conditions inside the cell change in response to stimuli. In this work, we propose an estimation algorithm to determine time-varying parameters of systems that discretely switch between different linear models of motion with Gaussian noise statistics, covering dynamics such as diffusion, directed motion, and Ornstein-Uhlenbeck dynamics. Our algorithm consists of three stages. In the first stage, we use a sliding window approach, combined with Expectation Maximization (EM) to determine maximum likelihood estimates of the parameters as a function of time. These results are only used to roughly estimate the number of model switches that occur in the data to guide the selection of algorithm parameters in the second stage. In the second stage, we use Change Detection (CD) techniques to identify where the models switch, taking advantage of the off-line nature of the analysis of SPT data to create non-causal algorithms with better precision than a purely causal approach. Finally, we apply EM to each set of data between the change points to determine final parameter estimates. We demonstrate our approach using experimental data generated in the lab under controlled conditions.

Silver nanoparticle uptake in the human lung assessed through in-vitro and in-silico methods

Silver nanoparticles (AgNP) are commonly used in medical, cosmetics, clothing, and industrial applications for their antibacterial and catalytic properties. As AgNP become more prevalent, the doses to which humans are exposed may increase and pose health risks, particularly through incidental inhalation. This exposure was evaluated through in-vitro methods simulating lung fluids and lung epithelium, and through computational fluid dynamics (CFD) methods of AgNP transport. A high-dose scenario simulated a short-term inhalation of 10 μg AgNP/m³, based on an exposure limit recommended by the National Institute of Occupational Safety and Health for the case of a health-care worker who handles AgNP-infused wound dressings, and regularly wears AgNP-imbedded clothing. Bioaccessibility tests were followed by a Parallel Artificial Membrane Permeability Assay (PAMPA) and supported by CFD models of the lung alveoli, membrane, pores, and blood capillaries. Results indicate that such exposure produces an average and maximum AgNP flux of approximately 4.7 × 10^-21 and 6.5 × 10^-19 mol m^-2·s^-1 through lung tissue, respectively, yielding a blood-silver accumulation of 0.46-64 mg per year, which may exceed the lowest adverse effect level of 25 mg for an adult male. Results from in-silico simulations were consistent with values estimated in vitro (within an order of magnitude), which suggest that CFD models may be used effectively to predict silver exposure from inhaled AgNP. Although the average short-term exposure concentrations are 3 orders of magnitude smaller than the reported threshold for mammalian cytotoxicity effects (observed at 5000 ppb), cumulative effects resulting from constant exposure to AgNP may pose risks to human health in the long-term, with predicted bioaccumulation reaching potential toxic effects after only five months of exposure, based on maximum flux.

Dynamic motions of molecular motors in the actin cytoskeleton

During intracellular transport, cellular cargos, such as organelles, vesicles, and proteins, are transported within cells. Intracellular transport plays an important role in diverse cellular functions. Molecular motors walking on the cytoskeleton facilitate active intracellular transport, which is more efficient than diffusion-based passive transport. Active transport driven by kinesin and dynein walking on microtubules has been studied well during recent decades. However, mechanisms of active transport occurring in disorganized actin networks via myosin motors remain elusive. To provide physiologically relevant insights, we probed motions of myosin motors in actin networks under various conditions using our well-established computational model that rigorously accounts for the mechanical and dynamical behaviors of the actin cytoskeleton. We demonstrated that myosin motions can be confined due to three different reasons in the absence of F-actin turnover. We verified mechanisms of motor stalling using in vitro reconstituted actomyosin networks. We also found that with F-actin turnover, motors consistently move for a long time without significant confinement. Our study sheds light on the importance of F-actin turnover for effective active transport in the actin cytoskeleton.

Viscoelastic voyages - Biophysical perspectives on cell intercalation during Drosophila gastrulation

Developmental processes are driven by a combination of cytoplasmic, cortical, and surface-associated forces. However, teasing apart the contributions of these forces and how a viscoelastic cell responds has long been a key question in developmental biology. Recent advances in applying biophysical approaches to these questions is leading to a fundamentally new understanding of morphogenesis. In this review, we discuss how computational analysis of experimental findings and in silico modeling of Drosophila gastrulation processes has led to a deeper comprehension of the physical principles at work in the early embryo. We also summarize many of the emerging methodologies that permit biophysical analysis as well as those that provide direct and indirect measurements of force directions and magnitudes. Finally, we examine the multiple frameworks that have been used to model tissue and cellular behaviors.

Cell ratcheting through the Sbf RabGEF directs force balancing and stepped apical constriction

Miao et al. show that a membrane trafficking pathway centered on Sbf and Rab35 is essential for the irreversibility of pulsed contractile events during apical constriction. Sbf/Rab35 disruption leads to a convoluted cell surface, suggesting that membrane remodeling is essential for the construction of effective actomyosin networks.

During Drosophila melanogaster gastrulation, the invagination of the prospective mesoderm is driven by the pulsed constriction of apical surfaces. Here, we address the mechanisms by which the irreversibility of pulsed events is achieved while also permitting uniform epithelial behaviors to emerge. We use MSD-based analyses to identify contractile steps and find that when a trafficking pathway initiated by Sbf is disrupted, contractile steps become reversible. Sbf localizes to tubular, apical surfaces and associates with Rab35, where it promotes Rab GTP exchange. Interestingly, when Sbf/Rab35 function is compromised, the apical plasma membrane becomes deeply convoluted, and nonuniform cell behaviors begin to emerge. Consistent with this, Sbf/Rab35 appears to prefigure and organize the apical surface for efficient Myosin function. Finally, we show that Sbf/Rab35/CME directs the plasma membrane to Rab11 endosomes through a dynamic interaction with Rab5 endosomes. These results suggest that periodic ratcheting events shift excess membrane from cell apices into endosomal pathways to permit reshaping of actomyosin networks and the apical surface.

Distribution of active forces in the cell cortex

In this work, we study in detail the distribution of stochastic forces generated by the molecular motors activity, in the actin cortex of pre-muscular cells. By combining active and passive rheology experiments, performed on the same micro-bead bound to the actin network through membrane adhesive receptors, we measure the auto-correlation function C_ff(τ) of the average force pulling on the bead. As for any out-of-equilibrium system, the force distribution differs from the thermodynamical equilibrium one, especially at long time scale τ⪆ 1 s where the bead motion becomes partially directed. Thus the fluctuation-dissipation theorem does not apply and one can measure the distance from equilibrium through its violation. We investigate the influence of different parameters on the force distribution, focusing particularly on the role of ligand density: a detailed study shows how the amplitude of active forces increases when the bead is more tightly attached to the cortex. We introduce and study a model, which takes into account the number of bonds between the bead and the cytoskeleton, as well as the viscoelastic properties of the medium. This model faithfully accounts for the experimental observations. Also, it is shown that the amplitude of active forces increases with temperature. Finally, our data confirm that ATP depletion in the cell, or partial inhibition of the actomyosin activity, leads to a decrease of the amplitude of the force distribution. Altogether, we propose a consistent and quantitative description for the motion of a micrometric probe interacting with the actin network, and for the amplitude of the stochastic forces generated by molecular motors in the cortex surrounding this probe.

A composition-dependent molecular clutch between T cell signaling condensates and actin

During T cell activation, biomolecular condensates form at the immunological synapse (IS) through multivalency-driven phase separation of LAT, Grb2, Sos1, SLP-76, Nck, and WASP. These condensates move radially at the IS, traversing successive radially-oriented and concentric actin networks. To understand this movement, we biochemically reconstituted LAT condensates with actomyosin filaments. We found that basic regions of Nck and N-WASP/WASP promote association and co-movement of LAT condensates with actin, indicating conversion of weak individual affinities to high collective affinity upon phase separation. Condensates lacking these components were propelled differently, without strong actin adhesion. In cells, LAT condensates lost Nck as radial actin transitioned to the concentric network, and engineered condensates constitutively binding actin moved aberrantly. Our data show that Nck and WASP form a clutch between LAT condensates and actin in vitro and suggest that compositional changes may enable condensate movement by distinct actin networks in different regions of the IS.

Multistep Track Segmentation and Motion Classification for Transient Mobility Analysis

Molecular interactions are often transient and might change within the window of observation, leading to changes in molecule movement. Therefore, accurate motion analysis often requires transient motion classification. Here we present an accurate and computationally efficient transient mobility analysis framework, termed "divide-and-conquer moment scaling spectrum" (DC-MSS). DC-MSS works in a multistep fashion: 1) it utilizes a local movement descriptor throughout a track to divide it into initial segments of putatively different motion classes; 2) it classifies these segments via moment scaling spectrum (MSS) analysis of molecule displacements; and 3) it uses the MSS analysis results to refine the track segmentation. This strategy uncouples the initial identification of motion switches from motion classification, allowing DC-MSS to circumvent the sensitivity-accuracy tradeoff of classic rolling window approaches for transient motion analysis, while at the same time harnessing the classification power of MSS analysis. Testing of DC-MSS demonstrates that it detects switches among free diffusion, confined diffusion, directed diffusion, and immobility with great sensitivity. To illustrate the utility of DC-MSS, we have applied it to single-particle tracks of the transmembrane protein CD44 on the surface of macrophages, revealing actin cortex-dependent transient mobility changes.

The polarity-induced force imbalance in Caenorhabditis elegans embryos is caused by asymmetric binding rates of dynein to the cortex

During asymmetric cell division, the molecular motor dynein generates cortical pulling forces that position the spindle to reflect polarity and adequately distribute cell fate determinants. In Caenorhabditis elegans embryos, despite a measured anteroposterior force imbalance, antibody staining failed to reveal dynein enrichment at the posterior cortex, suggesting a transient localization there. Dynein accumulates at the microtubule plus ends, in an EBP-2EB-dependent manner. This accumulation, although not transporting dynein, contributes modestly to cortical forces. Most dyneins may instead diffuse to the cortex. Tracking of cortical dynein revealed two motions: one directed and the other diffusive-like, corresponding to force-generating events. Surprisingly, while dynein is not polarized at the plus ends or in the cytoplasm, diffusive-like tracks were more frequently found at the embryo posterior tip, where the forces are higher. This asymmetry depends on GPR-1/2LGN and LIN-5NuMA, which are enriched there. In csnk-1(RNAi) embryos, the inverse distribution of these proteins coincides with an increased frequency of diffusive-like tracks anteriorly. Importantly, dynein cortical residence time is always symmetric. We propose that the dynein-binding rate at the posterior cortex is increased, causing the polarity-reflecting force imbalance. This mechanism of control supplements the regulation of mitotic progression through the nonpolarized dynein detachment rate.

SNARE-Mediated Fusion of Single Chromaffin Granules with Pore-Spanning Membranes

Pore-spanning membranes (PSMs) composed of supported membrane parts as well as freestanding membrane parts are shown to be very versatile to investigate SNARE-mediated fusion on the single-particle level. They provide a planar geometry readily accessible by confocal fluorescence microscopy, which enabled us for the first time, to our knowledge, to investigate the fusion of individual natural secretory granules (i.e., chromaffin granules (CGs)) on the single-particle level by two-color fluorescence microscopy in a time-resolved manner. The t-SNARE acceptor complex ΔN49 was reconstituted into PSMs containing 2 mol % 1,2-dipalmitoyl-sn-glycero-3-phosphatidylinositol-4,5-bisphosphate and Atto488-1,2-dipalmitoyl-sn-glycero-3-phosphoethanolamine, and CGs were fluorescently labeled with 2-((1E,3E)-5-((Z)-3,3-dimethyl-1-octadecylindolin-2-ylidene)penta-1,3-dien-1-yl)-3,3-dimethyl-1-octadecyl-3H-indol-1-ium perchlorate. We compared the dynamics of docked and hemifused CGs as well as their fusion efficacy and kinetics with the results obtained for synthetic synaptobrevin 2-doped vesicles fusing with PSMs of the same composition. Whereas the synthetic vesicles were fully immobile on supported PSMs, docked as well as hemifused CGs were mobile on both PSM parts, which suggests that this system resembles more closely the natural situation. The fusion process of CGs proceeded through three-dimensional post-lipid-mixing structures, which were readily resolved on the gold-covered pore rims of the PSMs and which are discussed in the context of intermediate states observed in live cells.

Characterize Collective Lysosome Heterogeneous Dynamics in Live Cell with a Space- and Time-Resolved Method

While studies of collective cell migration and bacteria swarming have tremendously promoted our fundamental knowledge of the complex systematic phenomena, the quantitative characterization of the collective organelles movement at subcellular level is yet to be fully explored. Here we tagged the lysosomes in live cells with fluorescent probe and imaged their spatial motion with wide field microscopy. To quantitatively characterize the collective lysosomal behavior with high spatiotemporal heterogeneity dynamics, we developed the particle collective analysis (PECAN) method based on the single particle tracking techniques. Thousands of trajectories were detected and analyzed in each single cell. The reliability was validated by comparing with traditional PIV method, simulated and experimental data sets. We show that the lysosomes in live cells move collectively with spatial heterogeneous and temporal long-term correlated dynamics. Furthermore, the continuous wavelet analysis suggested the existence of collective lysosomal oscillation in mouse neural cells. Generally, our method provides a practical workflow for characterizing the collective lysosomal motions which can benefit related areas such as organelles mediated drug delivery and cell activity profiling.

Imaging, Tracking and Computational Analyses of Virus Entry and Egress with the Cytoskeleton

Viruses have a dual nature: particles are “passive substances” lacking chemical energy transformation, whereas infected cells are “active substances” turning-over energy. How passive viral substances convert to active substances, comprising viral replication and assembly compartments has been of intense interest to virologists, cell and molecular biologists and immunologists. Infection starts with virus entry into a susceptible cell and delivers the viral genome to the replication site. This is a multi-step process, and involves the cytoskeleton and associated motor proteins. Likewise, the egress of progeny virus particles from the replication site to the extracellular space is enhanced by the cytoskeleton and associated motor proteins. This overcomes the limitation of thermal diffusion, and transports virions and virion components, often in association with cellular organelles. This review explores how the analysis of viral trajectories informs about mechanisms of infection. We discuss the methodology enabling researchers to visualize single virions in cells by fluorescence imaging and tracking. Virus visualization and tracking are increasingly enhanced by computational analyses of virus trajectories as well as in silico modeling. Combined approaches reveal previously unrecognized features of virus-infected cells. Using select examples of complementary methodology, we highlight the role of actin filaments and microtubules, and their associated motors in virus infections. In-depth studies of single virion dynamics at high temporal and spatial resolutions thereby provide deep insight into virus infection processes, and are a basis for uncovering underlying mechanisms of how cells function.

Spatial Cytoskeleton Organization Supports Targeted Intracellular Transport

The efficiency of intracellular cargo transport from specific sources to target locations is strongly dependent upon molecular motor-assisted motion along the cytoskeleton. Radial transport along microtubules and lateral transport along the filaments of the actin cortex underneath the cell membrane are characteristic for cells with a centrosome. The interplay between the specific cytoskeleton organization and the motor performance results in a spatially inhomogeneous intermittent search strategy. To analyze the efficiency of such intracellular search strategies, we formulate a random velocity model with intermittent arrest states. We evaluate efficiency in terms of mean first passage times for three different, frequently encountered intracellular transport tasks: 1) the narrow escape problem, which emerges during cargo transport to a synapse or other specific region of the cell membrane; 2) the reaction problem, which considers the binding time of two particles within the cell; and 3) the reaction-escape problem, which arises when cargo must be released at a synapse only after pairing with another particle. Our results indicate that cells are able to realize efficient search strategies for various intracellular transport tasks economically through a spatial cytoskeleton organization that involves only a narrow actin cortex rather than a cell body filled with randomly oriented actin filaments.

Detection of Velocity and Diffusion Coefficient Change Points in Single-Particle Trajectories

The position-time trajectory of a biological subject moving in a complex environment contains rich information about how it interacts with the local setting. Whether the subject be an animal or an intracellular endosomal vesicle, the two primary modes of biological locomotion are directional movement and random walk, respectively characterized by velocity and diffusion coefficient. This contribution introduces a method to quantitatively divide a single-particle trajectory into segments that exhibit changes in the diffusion coefficient, velocity, or both. With the determination of these two physical parameters given by the maximum likelihood estimators, the relative precisions are given as explicit functions of the number of data points and total trajectory time. The method is based on rigorous statistical tests and does not require any presumed kinetics scheme. Results of extensive characterizations, extensions to 2D and 3D trajectories, and applications to common scenarios are also discussed.

Activity-Dependence of Synaptic Vesicle Dynamics

The proper function of synapses relies on efficient recycling of synaptic vesicles. The small size of synaptic boutons has hampered efforts to define the dynamical states of vesicles during recycling. Moreover, whether vesicle motion during recycling is regulated by neural activity remains largely unknown. We combined nanoscale-resolution tracking of individual synaptic vesicles in cultured hippocampal neurons from rats of both sexes with advanced motion analyses to demonstrate that the majority of recently endocytosed vesicles undergo sequences of transient dynamical states including epochs of directed, diffusional, and stalled motion. We observed that vesicle motion is modulated in an activity-dependent manner, with dynamical changes apparent in ∼20% of observed boutons. Within this subpopulation of boutons, 35% of observed vesicles exhibited acceleration and 65% exhibited deceleration, accompanied by corresponding changes in directed motion. Individual vesicles observed in the remaining ∼80% of boutons did not exhibit apparent dynamical changes in response to stimulation. More quantitative transient motion analyses revealed that the overall reduction of vesicle mobility, and specifically of the directed motion component, is the predominant activity-evoked change across the entire bouton population. Activity-dependent modulation of vesicle mobility may represent an important mechanism controlling vesicle availability and neurotransmitter release.SIGNIFICANCE STATEMENT Mechanisms governing synaptic vesicle dynamics during recycling remain poorly understood. Using nanoscale resolution tracking of individual synaptic vesicles in hippocampal synapses and advanced motion analysis tools we demonstrate that synaptic vesicles undergo complex sets of dynamical states that include epochs of directed, diffusive, and stalled motion. Most importantly, our analyses revealed that vesicle motion is modulated in an activity-dependent manner apparent as the reduction in overall vesicle mobility in response to stimulation. These results define the vesicle dynamical states during recycling and reveal their activity-dependent modulation. Our study thus provides fundamental new insights into the principles governing synaptic function.

Planar polarized Rab35 functions as an oscillatory ratchet during cell intercalation in the Drosophila epithelium

The coordination between membrane trafficking and actomyosin networks is essential to the regulation of cell and tissue shape. Here, we examine Rab protein distributions during Drosophila epithelial tissue remodeling and show that Rab35 is dynamically planar polarized. Rab35 compartments are enriched at contractile interfaces of intercalating cells and provide the first evidence of interfacial monopolarity. When Rab35 function is disrupted, apical area oscillations still occur and contractile steps are observed. However, contractions are followed by reversals and interfaces fail to shorten, demonstrating that Rab35 functions as a ratchet ensuring unidirectional movement. Although actomyosin forces have been thought to drive interface contraction, initiation of Rab35 compartments does not require Myosin II function. However, Rab35 compartments do not terminate and continue to grow into large elongated structures following actomyosin disruption. Finally, Rab35 represents a common contractile cell-shaping mechanism, as mesoderm invagination fails in Rab35 compromised embryos and Rab35 localizes to constricting surfaces.

Various stages of tissue morphogenesis involve the contraction of epithelial surfaces. Here, the authors identify the Rab GTPase Rab35 as an essential component of this contractile process, which functions as a membrane ratchet to ensure unidirectional movement of intercalating cells.

Impact of a mechanical shear stress on intracellular trafficking

Intracellular trafficking mainly takes place along the microtubules, and its efficiency depends on the local architecture and organization of the cytoskeletal network. In this work, the cytoplasm of stem cells is subjected to mechanical vortexing at a frequency of up to 1 Hz, by using magnetic chains of endosomes embedded in the cell body, in order to locally perturb the network structure. The consequences are evaluated on the directionality and processivity of the spontaneous motion of endosomes. When the same chains are used both to shear the cell medium and to probe the intracellular traffic, a substantial decrease in transport efficiency is detected after applying the mechanical shear. Interestingly, when using different objects to apply the shear and to probe the spontaneous motion, no alteration of the transport efficiency can be detected. We conclude that shaking the vesicles mainly causes their unbinding from the cytoskeletal tracks, but has little influence on the integrity of the network itself. This is corroborated by active microrheology measurements, performed with chains actuated by a magnetic field, and showing that the mechanical compliance of the cytoplasm is similar before and after slow vortexing.

Hybrid colored noise process with space-dependent switching rates

A fundamental issue in the theory of continuous stochastic process is the interpretation of multiplicative white noise, which is often referred to as the Itô-Stratonovich dilemma. From a physical perspective, this reflects the need to introduce additional constraints in order to specify the nature of the noise, whereas from a mathematical perspective it reflects an ambiguity in the formulation of stochastic differential equations (SDEs). Recently, we have identified a mechanism for obtaining an Itô SDE based on a form of temporal disorder. Motivated by switching processes in molecular biology, we considered a Brownian particle that randomly switches between two distinct conformational states with different diffusivities. In each state, the particle undergoes normal diffusion (additive noise) so there is no ambiguity in the interpretation of the noise. However, if the switching rates depend on position, then in the fast switching limit one obtains Brownian motion with a space-dependent diffusivity of the Itô form. In this paper, we extend our theory to include colored additive noise. We show that the nature of the effective multiplicative noise process obtained by taking both the white-noise limit (κ→0) and fast switching limit (ε→0) depends on the order the two limits are taken. If the white-noise limit is taken first, then we obtain Itô, and if the fast switching limit is taken first, then we obtain Stratonovich. Moreover, the form of the effective diffusion coefficient differs in the two cases. The latter result holds even in the case of space-independent transition rates, where one obtains additive noise processes with different diffusion coefficients. Finally, we show that yet another form of multiplicative noise is obtained in the simultaneous limit ε,κ→0 with ε/κ^{2} fixed.

Segmentation of 3D Trajectories Acquired by TSUNAMI Microscope: An Application to EGFR Trafficking

Whereas important discoveries made by single-particle tracking have changed our view of the plasma membrane organization and motor protein dynamics in the past three decades, experimental studies of intracellular processes using single-particle tracking are rather scarce because of the lack of three-dimensional (3D) tracking capacity. In this study we use a newly developed 3D single-particle tracking method termed TSUNAMI (Tracking of Single particles Using Nonlinear And Multiplexed Illumination) to investigate epidermal growth factor receptor (EGFR) trafficking dynamics in live cells at 16/43 nm (xy/z) spatial resolution, with track duration ranging from 2 to 10 min and vertical tracking depth up to tens of microns. To analyze the long 3D trajectories generated by the TSUNAMI microscope, we developed a trajectory analysis algorithm, which reaches 81% segment classification accuracy in control experiments (termed simulated movement experiments). When analyzing 95 EGF-stimulated EGFR trajectories acquired in live skin cancer cells, we find that these trajectories can be separated into three groups-immobilization (24.2%), membrane diffusion only (51.6%), and transport from membrane to cytoplasm (24.2%). When EGFRs are membrane-bound, they show an interchange of Brownian diffusion and confined diffusion. When EGFRs are internalized, transitions from confined diffusion to directed diffusion and from directed diffusion back to confined diffusion are clearly seen. This observation agrees well with the model of clathrin-mediated endocytosis.

Accuracy of the detection of binding events using 3D single particle tracking

BACKGROUND

Nanoparticles can be used as markers to track the position of biomolecules, such as single proteins, inside living cells. The activity of a protein can sometimes be inferred from changes in the mobility of the attached particle. Mean Square Displacement analysis is the most common method to obtain mobility information from trajectories of tracked particles, such as the diffusion coefficient D. However, the precision of D sets a limit to discriminate changes in mobility caused by biological events from changes that reflect the stochasticity inherent to diffusion. This issue is of particular importance in an experiment aiming to quantify dynamic processes.

RESULTS

Here, we present simulations and 3D tracking experiments with Gold Nanorods freely diffusing in glycerol solution to establish the best analysis parameters to extract the diffusion coefficient. We applied this knowledge to the detection of a temporary change in diffusion, as it can occur due to the transient binding of a particle to an immobile structure within the cell, and tested its dependence on the magnitude of the change in diffusion and duration of this event.

CONCLUSIONS

The simulations show that the spatial accuracy of particle tracking generally does not limit the detection of short binding events. Careful analysis of the magnitude of the change in diffusion and the number of frames per binding event is required for accurate quantification of such events.

Classification and Segmentation of Nanoparticle Diffusion Trajectories in Cellular Micro Environments

Darkfield and confocal laser scanning microscopy both allow for a simultaneous observation of live cells and single nanoparticles. Accordingly, a characterization of nanoparticle uptake and intracellular mobility appears possible within living cells. Single particle tracking allows to measure the size of a diffusing particle close to a cell. However, within the more complex system of a cell’s cytoplasm normal, confined or anomalous diffusion together with directed motion may occur. In this work we present a method to automatically classify and segment single trajectories into their respective motion types. Single trajectories were found to contain more than one motion type. We have trained a random forest with 9 different features. The average error over all motion types for synthetic trajectories was 7.2%. The software was successfully applied to trajectories of positive controls for normal- and constrained diffusion. Trajectories captured by nanoparticle tracking analysis served as positive control for normal diffusion. Nanoparticles inserted into a diblock copolymer membrane was used to generate constrained diffusion. Finally we segmented trajectories of diffusing (nano-)particles in V79 cells captured with both darkfield- and confocal laser scanning microscopy. The software called “TraJClassifier” is freely available as ImageJ/Fiji plugin via https://git.io/v6uz2.

Dual-Color Herpesvirus Capsids Discriminate Inoculum from Progeny and Reveal Axonal Transport Dynamics

Alphaherpesviruses such as herpes simplex virus and pseudorabies virus (PRV) are neuroinvasive double-stranded DNA (dsDNA) viruses that establish lifelong latency in peripheral nervous system (PNS) neurons of their native hosts. Following reactivation, infection can spread back to the initial mucosal site of infection or, in rare cases, to the central nervous system, with usually serious outcomes. During entry and egress, viral capsids depend on microtubule-based molecular motors for efficient and fast transport. In axons of PNS neurons, cytoplasmic dynein provides force for retrograde movements toward the soma, and kinesins move cargo in the opposite, anterograde direction. The dynamic properties of virus particles in cells can be imaged by fluorescent protein fusions to the small capsid protein VP26, which are incorporated into capsids. However, single-color fluorescent protein tags fail to distinguish the virus inoculum from progeny. Therefore, we established a dual-color system by growing a recombinant PRV expressing a red fluorescent VP26 fusion (PRV180) on a stable cell line expressing a green VP26 fusion (PK15-mNG-VP26). The resulting dual-color virus preparation (PRV180G) contains capsids tagged with both red and green fluorescent proteins, and 97% of particles contain detectable levels of mNeonGreen (mNG)-tagged VP26. After replication in neuronal cells, all PRV180G progeny exclusively contain monomeric red fluorescent protein (mRFP)-VP26-tagged capsids. We used PRV180G for an analysis of axonal capsid transport dynamics in PNS neurons. Fast dual-color total internal reflection fluorescence (TIRF) microscopy, single-particle tracking, and motility analyses reveal robust, bidirectional capsid motility mediated by cytoplasmic dynein and kinesin during entry, whereas egressing progeny particles are transported exclusively by kinesins. IMPORTANCE Alphaherpesviruses are neuroinvasive viruses that infect the peripheral nervous system (PNS) of infected hosts as an integral part of their life cycle. Establishment of a quiescent or latent infection in PNS neurons is a hallmark of most alphaherpesviruses. Spread of infection to the central nervous system is surprisingly rare in natural hosts but can be fatal. Pseudorabies virus (PRV) is a broad-host-range swine alphaherpesvirus that enters neuronal cells and utilizes intracellular transport processes to establish infection and to spread between cells. By using a virus preparation with fluorescent viral capsids that change color depending on the stage of the infectious cycle, we find that during entry, axons of PNS neurons support robust, bidirectional capsid motility, similar to cellular cargo, toward the cell body. In contrast, progeny particles appear to be transported unidirectionally by kinesin motors toward distal egress sites.

Retrograde NGF axonal transport--motor coordination in the unidirectional motility regime

We present a detailed motion analysis of retrograde nerve growth factor (NGF) endosomes in axons to show that mechanical tugs-of-war and intracellular motor regulation are complimentary features of the near-unidirectional endosome directionality. We used quantum dots to fluorescently label NGF and acquired trajectories of retrograde quantum-dot-NGF-endosomes with <20-nm accuracy at 32 Hz in microfluidic neuron cultures. Using a combination of transient motion analysis and Bayesian parsing, we partitioned the trajectories into sustained periods of retrograde (dynein-driven) motion, constrained pauses, and brief anterograde (kinesin-driven) reversals. The data shows many aspects of mechanical tugs-of-war and multiple-motor mechanics in NGF-endosome transport. However, we found that stochastic mechanical models based on in vitro parameters cannot simulate the experimental data, unless the microtubule-binding affinity of kinesins on the endosome is tuned down by 10 times. Specifically, the simulations suggest that the NGF-endosomes are driven on average by 5-6 active dyneins and 1-2 downregulated kinesins. This is also supported by the dynamics of endosomes detaching under load in axons, showcasing the cooperativity of multiple dyneins and the subdued activity of kinesins. We discuss the possible motor coordination mechanism consistent with motor regulation and tugs-of-war for future investigations.

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.

Detection of Diffusion Heterogeneity in Single Particle Tracking Trajectories Using a Hidden Markov Model with Measurement Noise Propagation

We develop a Bayesian analysis framework to detect heterogeneity in the diffusive behaviour of single particle trajectories on cells, implementing model selection to classify trajectories as either consistent with Brownian motion or with a two-state (diffusion coefficient) switching model. The incorporation of localisation accuracy is essential, as otherwise false detection of switching within a trajectory was observed and diffusion coefficient estimates were inflated. Since our analysis is on a single trajectory basis, we are able to examine heterogeneity between trajectories in a quantitative manner. Applying our method to the lymphocyte function-associated antigen 1 (LFA-1) receptor tagged with latex beads (4 s trajectories at 1000 frames s⁻¹), both intra- and inter-trajectory heterogeneity were detected; 12–26% of trajectories display clear switching between diffusive states dependent on condition, whilst the inter-trajectory variability is highly structured with the diffusion coefficients being related by D₁ = 0.68D₀ − 1.5 × 10⁴ nm² s⁻¹, suggestive that on these time scales we are detecting switching due to a single process. Further, the inter-trajectory variability of the diffusion coefficient estimates (1.6 × 10² − 2.6 × 10⁵ nm² s⁻¹) is very much larger than the measurement uncertainty within trajectories, suggesting that LFA-1 aggregation and cytoskeletal interactions are significantly affecting mobility, whilst the timescales of these processes are distinctly different giving rise to inter- and intra-trajectory variability. There is also an ‘immobile’ state (defined as D < 3.0 × 10³ nm² s⁻¹) that is rarely involved in switching, immobility occurring with the highest frequency (47%) under T cell activation (phorbol-12-myristate-13-acetate (PMA) treatment) with enhanced cytoskeletal attachment (calpain inhibition). Such ‘immobile’ states frequently display slow linear drift, potentially reflecting binding to a dynamic actin cortex. Our methods allow significantly more information to be extracted from individual trajectories (ultimately limited by time resolution and time-series length), and allow statistical comparisons between trajectories thereby quantifying inter-trajectory heterogeneity. Such methods will be highly informative for the construction and fitting of molecule mobility models within membranes incorporating aggregation, binding to the cytoskeleton, or traversing membrane microdomains.

Single Molecule Imaging Deciphers the Relation between Mobility and Signaling of a Prototypical G Protein-coupled Receptor in Living Cells

Lateral diffusion enables efficient interactions between membrane proteins, leading to signal transmission across the plasma membrane. An open question is how the spatiotemporal distribution of cell surface receptors influences the transmembrane signaling network. Here we addressed this issue by studying the mobility of a prototypical G protein-coupled receptor, the neurokinin-1 receptor, during its different phases of cellular signaling. Attaching a single quantum dot to individual neurokinin-1 receptors enabled us to follow with high spatial and temporal resolution over long time regimes the fate of individual receptors at the plasma membrane. Single receptor trajectories revealed a very heterogeneous mobility distribution pattern with diffusion constants ranging from 0.0005 to 0.1 μm(2)/s comprising receptors freely diffusing and others confined in 100-600-nm-sized membrane domains as well as immobile receptors. A two-dimensional representation of mobility and confinement resolved two major, broadly distributed receptor populations, one showing high mobility and low lateral restriction and the other showing low mobility and high restriction. We found that about 40% of the receptors in the basal state are already confined in membrane domains and are associated with clathrin. After stimulation with an agonist, an additional 30% of receptors became further confined. Using inhibitors of clathrin-mediated endocytosis, we found that the fraction of confined receptors at the basal state depends on the quantity of membrane-associated clathrin and is correlated to a significant decrease of the canonical pathway activity of the receptors. This shows that the high plasticity of receptor mobility is of central importance for receptor homeostasis and fine regulation of receptor activity.

Identifying transport behavior of single-molecule trajectories

Models of biological diffusion-reaction systems require accurate classification of the underlying diffusive dynamics (e.g., Fickian, subdiffusive, or superdiffusive). We use a renormalization group operator to identify the anomalous (non-Fickian) diffusion behavior from a short trajectory of a single molecule. The method provides quantitative information about the underlying stochastic process, including its anomalous scaling exponent. The classification algorithm is first validated on simulated trajectories of known scaling. Then it is applied to experimental trajectories of microspheres diffusing in cytoplasm, revealing heterogeneous diffusive dynamics. The simplicity and robustness of this classification algorithm makes it an effective tool for analysis of rare stochastic events that occur in complex biological systems.

Signal focusing through active transport

The accuracy of molecular signaling in biological cells and novel diagnostic devices is ultimately limited by the counting noise floor imposed by the thermal diffusion. Motivated by the fact that messenger RNA and vesicle-engulfed signaling molecules transiently bind to molecular motors and are actively transported in biological cells, we show here that the random active delivery of signaling particles to within a typical diffusion distance to the receptor generically reduces the correlation time of the counting noise. Considering a variety of signaling particle sizes from mRNA to vesicles and cell sizes from prokaryotic to eukaryotic cells, we show that the conditions for active focusing-faster and more precise signaling-are indeed compatible with observations in living cells. Our results improve the understanding of molecular cellular signaling and novel diagnostic devices.

Memoryless self-reinforcing directionality in endosomal active transport within living cells

In contrast to Brownian transport, the active motility of microbes, cells, animals and even humans often follows another random process known as truncated Lévy walk. These stochastic motions are characterized by clustered small steps and intermittent longer jumps that often extend towards the size of the entire system. As there are repeated suggestions, although disagreement, that Lévy walks have functional advantages over Brownian motion in random searching and transport kinetics, their intentional engineering into active materials could be useful. Here, we show experimentally in the classic active matter system of intracellular trafficking that Brownian-like steps self-organize into truncated Lévy walks through an apparent time-independent positive feedback such that directional persistence increases with the distance travelled persistently. A molecular model that allows the maximum output of the active propelling forces to fluctuate slowly fits the experiments quantitatively. Our findings offer design principles for programming efficient transport in active materials.

Ligand-induced dynamics of neurotrophin receptors investigated by single-molecule imaging approaches

Neurotrophins are secreted proteins that regulate neuronal development and survival, as well as maintenance and plasticity of the adult nervous system. The biological activity of neurotrophins stems from their binding to two membrane receptor types, the tropomyosin receptor kinase and the p75 neurotrophin receptors (NRs). The intracellular signalling cascades thereby activated have been extensively investigated. Nevertheless, a comprehensive description of the ligand-induced nanoscale details of NRs dynamics and interactions spanning from the initial lateral movements triggered at the plasma membrane to the internalization and transport processes is still missing. Recent advances in high spatio-temporal resolution imaging techniques have yielded new insight on the dynamics of NRs upon ligand binding. Here we discuss requirements, potential and practical implementation of these novel approaches for the study of neurotrophin trafficking and signalling, in the framework of current knowledge available also for other ligand-receptor systems. We shall especially highlight the correlation between the receptor dynamics activated by different neurotrophins and the respective signalling outcome, as recently revealed by single-molecule tracking of NRs in living neuronal cells.

A method for multiprotein assembly in cells reveals independent action of kinesins in complex

A new system for generating cellular protein assemblies of defined spacing and composition reveals that kinesin motors located near each other function independently rather than cooperatively and are influenced primarily by the characteristics of the microtubule track on which they are moving.

Teams of processive molecular motors are critical for intracellular transport and organization, yet coordination between motors remains poorly understood. Here, we develop a system using protein components to generate assemblies of defined spacing and composition inside cells. This system is applicable to studying macromolecular complexes in the context of cell signaling, motility, and intracellular trafficking. We use the system to study the emergent behavior of kinesin motors in teams. We find that two kinesin motors in complex act independently (do not help or hinder each other) and can alternate their activities. For complexes containing a slow kinesin-1 and fast kinesin-3 motor, the slow motor dominates motility in vitro but the fast motor can dominate on certain subpopulations of microtubules in cells. Both motors showed dynamic interactions with the complex, suggesting that motor–cargo linkages are sensitive to forces applied by the motors. We conclude that kinesin motors in complex act independently in a manner regulated by the microtubule track.

Micro-heterogeneity metrics for diffusion in soft matter

Passive particle tracking of diffusive paths in soft matter, coupled with analysis of the path data, is firmly established as a fundamental methodology for characterization of both diffusive transport properties (the focus here) and linear viscoelasticity. For either focus, particle time series are typically analyzed by ensemble averaging over paths, a perfectly natural protocol for homogeneous materials or for applications where mean properties are sufficient. Many biological materials, however, are heterogeneous over length scales above the probe diameter, and the implications of heterogeneity for biologically relevant transport properties (e.g. diffusive passage times through a complex fluid layer) motivate this paper. Our goals are three-fold: first, to detect heterogeneity as reflected by the ensemble path data; second, to further decompose the ensemble of particle paths into statistically distinct clusters; and third, to fit the path data in each cluster to a model for the underlying stochastic process. After reviewing current best practices for detection and assessment of heterogeneity in diffusive processes, we introduce our strategy toward the first two goals with methods from the statistics and machine learning literature that have not found application thus far to passive particle tracking data. We apply an analysis based solely on the path data that detects heterogeneity and yields a decomposition of particle paths into statistically distinct clusters. After these two goals are achieved, one can then pursue model-fitting. We illustrate these heterogeneity metrics on diverse datasets: for numerically generated and experimental particle paths, with tunable and unknown heterogeneity, on numerical models for simple diffusion and anomalous sub-diffusion, and experimentally on sucrose, hyaluronic acid, agarose, and human lung culture mucus solutions.