Quantifying the dynamic interactions between a clathrin-coated pit and cargo molecules

A paintbrush for delivery of nanoparticles and molecules to live cells with precise spatiotemporal control

Delivery of very small amounts of reagents to the near-field of cells with micrometer spatial precision and millisecond time resolution is currently out of reach. Here we present μkiss as a micropipette-based scheme for brushing a layer of small molecules and nanoparticles onto the live cell membrane from a subfemtoliter confined volume of a perfusion flow. We characterize our system through both experiments and modeling, and find excellent agreement. We demonstrate several applications that benefit from a controlled brush delivery, such as a direct means to quantify local and long-range membrane mobility and organization as well as dynamical probing of intercellular force signaling.

GLT-1a glutamate transporter nanocluster localization is associated with astrocytic actin and neuronal Kv2 clusters at sites of neuron-astrocyte contact

Introduction: Astrocytic GLT-1 glutamate transporters ensure the fidelity of glutamic neurotransmission by spatially and temporally limiting glutamate signals. The ability to limit neuronal hyperactivity relies on the localization and diffusion of GLT-1 on the astrocytic surface, however, little is known about the underlying mechanisms. We show that two isoforms of GLT-1, GLT-1a and GLT-1b, form nanoclusters on the surface of transfected astrocytes and HEK-293 cells. Methods: We used both fixed and live cell super-resolution imaging of fluorescent protein and epitope tagged proteins in co-cultures of rat astrocytes and neurons. Immunofluorescence techniques were also used. GLT1 diffusion was assessed via single particle tracking and fluorescence recovery after photobleach (FRAP). Results: We found GLT-1a, but not GLT-1b, nanoclusters concentrated adjacent to actin filaments which was maintained after addition of glutamate. GLT-1a nanocluster concentration near actin filaments was prevented by expression of a cytosolic GLT-1a C-terminus, suggesting the C-terminus is involved in the localization adjacent to cortical actin. Using super-resolution imaging, we show that astrocytic GLT-1a and actin co-localize in net-like structures around neuronal Kv2.1 clusters at points of neuron/astrocyte contact. Conclusion: Overall, these data describe a novel relationship between GLT-1a and cortical actin filaments, which localizes GLT-1a near neuronal structures responsive to ischemic insult.

Effects of crowding on the diffusivity of membrane adhered particles

The lateral diffusion of cell membrane inclusions, such as integral membrane proteins and bound receptors, drives critical biological processes, including the formation of complexes, cell-cell signaling, and membrane trafficking. These diffusive processes are complicated by how concentrated, or "crowded", the inclusions are, which can occupy between 30-50% of the area fraction of the membrane. In this work, we elucidate the effects of increasing concentration of model membrane inclusions in a free-standing artificial cell membrane on inclusion diffusivity and the apparent viscosity of the membrane. By multiple particle tracking of fluorescent microparticles covalently tethered to the bilayer, we show the transition from expected Brownian dynamics, which accurately measure the membrane viscosity, to subdiffusive behavior with decreased diffusion coefficient as the particle area fraction increases from 1% to around 30%, approaching physiological levels of crowding. At high crowding, the onset of non-Gaussian behavior is observed. Using hydrodynamic models relating the 2D diffusion coefficient to the viscosity of a membrane, we determine the apparent viscosity of the bilayer from the particle diffusivity and show an increase in the apparent membrane viscosity with increasing particle area fraction. However, the scaling of this increase is in contrast with the behavior of monolayer inclusion diffusion and bulk suspension rheology. These results demonstrate that physiological levels of model membrane crowding nontrivially alter the dynamics and apparent viscosity of the system, which has implications for understanding membrane protein interactions and particle-membrane transport processes.

Dynamin-like Protein 1 (DNML1) as a Molecular Target for Antibody-Based Immunotherapy to Treat Glaucoma

Slow and progressive loss of retinal ganglion cells (RGCs) is the main characteristic of glaucoma, the second leading cause of blindness worldwide. Previous studies have shown that impaired mitochondrial dynamics could facilitate retinal neurodegeneration. Mitochondrial dynamics are regulated directly (fission) or more indirectly (fusion) by dynamin-like protein 1 (DNML1). Therefore, DNM1L might be a promising target for an antibody-based approach to treat glaucoma. The consequences of targeting endogenous DNM1L by antibodies in a glaucoma animal model have not been investigated yet. Here, we show that the intravitreal application of an anti-DNM1L antibody showed protective effects regarding the survival of RGCs and their axons in the retinal nerve fiber layer (RNFL). Antibody treatment also improved retinal functionality, as observed by electroretinography (Ganzfeld ERG). Western blot analysis revealed altered DNM1L phosphorylation and altered expression of proteins related to apoptosis suggesting a decreased apoptosis rate. Mass spectrometry analysis revealed 28 up-regulated and 21 down-regulated proteins (p < 0.05) in both experimental groups. Protein pathway analysis showed that many proteins interacted directly with the target protein DNM1L and could be classified into three main protein clusters: Vesicle traffic-associated (NSF, SNCA, ARF1), mitochondrion-associated (HSP9A, SLC25A5/ANT2, GLUD1) and cytoskeleton-associated (MAP1A) signaling pathway. Our results demonstrate that DNM1L is a promising target for an antibody-based approach to glaucoma therapy.

Single molecule localization-based analysis of clathrin-coated pit and caveolar dynamics

Clathrin-coated pits and caveolae are nanoscale invaginations of the plasma membrane of cells, forming through the assembly of membrane coat and accessory proteins in a tightly regulated process. We have analyzed the development of these membrane coat structures with high spatial and temporal resolution and sensitivity using super-resolution single-molecule localization microscopy (SMLM) on live cells. To this end, we developed a sophisticated clustering and data analysis workflow that automatically extracts the relevant information from SMLM image sequences taken on live cells. We quantified lifetime distributions of clathrin-coated and caveolar structures, and analyzed their growth dynamics. Moreover, we observed hotspots in the plasma membrane where coat structures appear repeatedly. The stunningly similar temporal development of clathrin-coated and caveolar structures suggests that key accessory proteins, some of which are shared between the two types of membrane coat structures, orchestrate the temporal evolution of these complex architectures.

High spatial density is associated with non-conducting Kv channels from two families

Ion channels are well known for their ability to regulate the cell membrane potential. However, many ion channels also have functions that do not involve ion conductance. Kv2 channels are one family of ion channels whose non-conducting functions are central to mammalian cell physiology. Kv2.1 and Kv2.2 channels form stable contact sites between the endoplasmic reticulum and plasma membrane via an interaction with endoplasmic reticulum resident proteins. To perform this structural role, Kv2 channels are expressed at extremely high densities on the plasma membranes of many cell types, including central pyramidal neurons, α-motoneurons, and smooth muscle cells. Research from our lab and others has shown that the majority of these plasma membrane Kv2.1 channels do not conduct potassium in response to depolarization. The mechanism of this channel silencing is unknown but is thought to be dependent on channel density in the membrane. Furthermore, the prevalence of a non-conducting population of Kv2.2 channels has not been directly tested. In this work we make improved measurements of the numbers of conducting and non-conducting Kv2.1 channels expressed in HEK293 cells and expand the investigation of non-conducting channels to three additional Kv α-subunits: Kv2.2, Kv1.4, and Kv1.5. By comparing the numbers of gating and conducting channels in individual HEK293 cells, we found that on average, only 50% of both Kv2.1 and Kv2.2 channels conducted potassium and, as previously suggested, that fraction decreased with increased channel density in the plasma membrane. At the highest spatial densities tested, which are comparable with those found at Kv2 clusters in situ, only 20% of Kv2.1 and Kv2.2 channels conducted potassium. We also show for the first time that Kv1.4 and Kv1.5 exhibit density-dependent silencing, suggesting that this phenomenon has an underlying mechanism that is shared by Kv channels from multiple families.

Rate equations, spatial moments, and concentration profiles for mobile-immobile models with power-law and mixed waiting time distributions

We present a framework for systems in which diffusion-advection transport of a tracer substance in a mobile zone is interrupted by trapping in an immobile zone. Our model unifies different model approaches based on distributed-order diffusion equations, exciton diffusion rate models, and random-walk models for multirate mobile-immobile mass transport. We study various forms for the trapping time dynamics and their effects on the tracer mass in the mobile zone. Moreover, we find the associated breakthrough curves, the tracer density at a fixed point in space as a function of time, and the mobile and immobile concentration profiles and the respective moments of the transport. Specifically, we derive explicit forms for the anomalous transport dynamics and an asymptotic power-law decay of the mobile mass for a Mittag-Leffler trapping time distribution. In our analysis we point out that even for exponential trapping time densities, transient anomalous transport is observed. Our results have direct applications in geophysical contexts, but also in biological, soft matter, and solid state systems.

EVAP: A two-photon imaging tool to study conformational changes in endogenous Kv2 channels in live tissues

A primary goal of molecular physiology is to understand how conformational changes of proteins affect the function of cells, tissues, and organisms. Here, we describe an imaging method for measuring the conformational changes of the voltage sensors of endogenous ion channel proteins within live tissue, without genetic modification. We synthesized GxTX-594, a variant of the peptidyl tarantula toxin guangxitoxin-1E, conjugated to a fluorophore optimal for two-photon excitation imaging through light-scattering tissue. We term this tool EVAP (Endogenous Voltage-sensor Activity Probe). GxTX-594 targets the voltage sensors of Kv2 proteins, which form potassium channels and plasma membrane–endoplasmic reticulum junctions. GxTX-594 dynamically labels Kv2 proteins on cell surfaces in response to voltage stimulation. To interpret dynamic changes in fluorescence intensity, we developed a statistical thermodynamic model that relates the conformational changes of Kv2 voltage sensors to degree of labeling. We used two-photon excitation imaging of rat brain slices to image Kv2 proteins in neurons. We found puncta of GxTX-594 on hippocampal CA1 neurons that responded to voltage stimulation and retain a voltage response roughly similar to heterologously expressed Kv2.1 protein. Our findings show that EVAP imaging methods enable the identification of conformational changes of endogenous Kv2 voltage sensors in tissue.

β-arrestin-dependent PI(4,5)P2 synthesis boosts GPCR endocytosis

β-arrestins regulate many cellular functions including intracellular signaling and desensitization of G protein-coupled receptors (GPCRs). Previous studies show that β-arrestin signaling and receptor endocytosis are modulated by the plasma membrane phosphoinositide lipid phosphatidylinositol-(4, 5)-bisphosphate (PI(4,5)P2). We found that β-arrestin also helped promote synthesis of PI(4,5)P2 and up-regulated GPCR endocytosis. We studied these questions with the Gq-coupled protease-activated receptor 2 (PAR2), which activates phospholipase C, desensitizes quickly, and undergoes extensive endocytosis. Phosphoinositides were monitored and controlled in live cells using lipid-specific fluorescent probes and genetic tools. Applying PAR2 agonist initiated depletion of PI(4,5)P2, which then recovered during rapid receptor desensitization, giving way to endocytosis. This endocytosis could be reduced by various manipulations that depleted phosphoinositides again right after phosphoinositide recovery: PI(4)P, a precusor of PI(4,5)P2, could be depleted at either the Golgi or the plasma membrane (PM) using a recruitable lipid 4-phosphatase enzyme and PI(4,5)P2 could be depleted at the PM using a recruitable 5-phosphatase. Endocytosis required the phosphoinositides. Knock-down of β-arrestin revealed that endogenous β-arrestin normally doubles the rate of PIP5-kinase (PIP5K) after PAR2 desensitization, boosting PI(4,5)P2-dependent formation of clathrin-coated pits (CCPs) at the PM. Desensitized PAR2 receptors were swiftly immobilized when they encountered CCPs, showing a dwell time of ∼90 s, 100 times longer than for unactivated receptors. PAR2/β-arrestin complexes eventually accumulated around the edges or across the surface of CCPs promoting transient binding of PIP5K-Iγ. Taken together, β-arrestins can coordinate potentiation of PIP5K activity at CCPs to induce local PI(4,5)P2 generation that promotes recruitment of PI(4,5)P2-dependent endocytic machinery.

Kinetics of nanoparticle uptake into and distribution in human cells

Whether one wishes to optimise drug delivery using nano-sized carriers or avoid hazard posed by engineered nanomaterials, the kinetics of nanoparticle uptake into human cells and their subsequent intracellular distribution is key. Unique properties of the nanoscale implies that such nanoparticles are taken up and trafficked in a different fashion compared to molecular species. In this review, we discuss in detail how to describe the kinetics of nanoparticle uptake and intracellular distribution, using previous studies for illustration. We also cover the extracellular kinetics, particle degradation, endosomal escape and cell division, ending with an outlook on the future of kinetic studies.

A kinetic view of clathrin assembly and endocytic cargo sorting

Specificity and sensitivity in biochemical reactions can be achieved through regulation of equilibrium binding affinity or through proofreading mechanisms that allow for the dissociation of unwanted intermediates. In this essay, we aim to provide our perspectives on how the concept of kinetic proofreading might apply in the context of cargo sorting in clathrin-mediated endocytosis.

Quantitative visualization of endocytic trafficking through photoactivation of fluorescent proteins

Endocytic trafficking controls the density of molecules at the plasma membrane and by doing so, the cell surface profile, which in turn determines how cells interact with their environment. A full apprehension of any cellular process necessitates understanding how proteins associated with the plasma membrane are endocytosed, how they are sorted after internalization, and if and how they are recycled to the plasma membrane. To date, it is still difficult to experimentally gain access to this information, even more to do it in a quantitative way. Here we present a toolset based on photoactivation of fluorescent proteins that enabled us to generate quantitative information on endocytosis, incorporation into sorting and recycling endosomes, delivery from endosomes to the plasma membrane, and on the type of vesicles performing intracellular transport. We illustrate these approaches by revealing striking differences in the endocytic trafficking of T-cell receptor and CD4, which bind to the same molecule at the surface of antigen-presenting cells during T-cell activation.

Rapidly Transducing and Spatially Localized Magnetofection Using Peptide-Mediated Non-Viral Gene Delivery Based on Iron Oxide Nanoparticles

Non-viral delivery systems are generally of low efficiency, which limits their use in gene therapy and editing applications. We previously developed a technology termed glycosaminoglycan (GAG)-binding enhanced transduction (GET) to efficiently deliver a variety of cargos intracellularly; our system employs GAG-binding peptides, which promote cell targeting, and cell penetrating peptides (CPPs), which enhance endocytotic cell internalization. Herein, we describe a further modification by combining gene delivery and magnetic targeting with the GET technology. We associated GET peptides, plasmid (p)DNA, and iron oxide superparamagnetic nanoparticles (MNPs), allowing rapid and targeted GET-mediated uptake by application of static magnetic fields in NIH3T3 cells. This produced effective transfection levels (significantly higher than the control) with seconds to minutes of exposure and localized gene delivery two orders of magnitude higher in targeted over non-targeted cell monolayers using magnetic fields (in 15 min exposure delivering GFP reporter pDNA). More importantly, high cell membrane targeting by GET-DNA and MNP co-complexes and magnetic fields allowed further enhancement to endocytotic uptake, meaning that the nucleic acid cargo was rapidly internalized beyond that of GET complexes alone (GET-DNA). Magnetofection by MNPs combined with GET-mediated delivery allows magnetic field-guided local transfection in vitro and could facilitate focused gene delivery for future regenerative and disease-targeted therapies in vivo.

Anomalous protein kinetics on low-fouling surfaces

In this work, protein-surface interactions were probed in terms of adsorption and desorption of a model protein, bovine serum albumin, on a low-fouling surface with single-molecule localization microscopy. Single-molecule experiments enable precise determination of both adsorption and desorption rates. Strikingly the experimental data show anomalous desorption kinetics, evident as a surface dwell time that exhibits a power-law distribution, i.e. a heavy-tailed rather than the expected exponential distribution. As a direct consequence of this heavy-tailed distribution, the average desorption rate depends upon the time scale of the experiment and the protein surface concentration does not reach equilibrium. Further analysis reveals that the observed anomalous desorption emerges due to the reversible formation of a small fraction of soluble protein multimers (small oligomers), such that each one desorbs from the surface with a different rate. The overall kinetics can be described by a series of elementary reactions, yielding simple scaling relations that predict experimental observations. This work reveals a mechanistic origin for anomalous desorption kinetics that can be employed to interpret observations where low-protein fouling surfaces eventually foul when in long-term contact with protein solutions. The work also provides new insights that can be used to define design principles for non-fouling surfaces and to predict their performance.

The diffusion of doxorubicin drug molecules in silica nanoslits is non-Gaussian, intermittent and anticorrelated

The motion of the confined doxorubicin drug molecule exhibits an interesting combination of anomalous diffusion features.

An in vitro assay and artificial intelligence approach to determine rate constants of nanomaterial-cell interactions

In vitro assays and simulation technologies are powerful methodologies that can inform scientists of nanomaterial (NM) distribution and fate in humans or pre-clinical species. For small molecules, less animal data is often needed because there are a multitude of in vitro screening tools and simulation-based approaches to quantify uptake and deliver data that makes extrapolation to in vivo studies feasible. Small molecule simulations work because these materials often diffuse quickly and partition after reaching equilibrium shortly after dosing, but this cannot be applied to NMs. NMs interact with cells through energy dependent pathways, often taking hours or days to become fully internalized within the cellular environment. In vitro screening tools must capture these phenomena so that cell simulations built on mechanism-based models can deliver relationships between exposure dose and mechanistic biology, that is biology representative of fundamental processes involved in NM transport by cells (e.g. membrane adsorption and subsequent internalization). Here, we developed, validated, and applied the FORECAST method, a combination of a calibrated fluorescence assay (CF) with an artificial intelligence-based cell simulation to quantify rates descriptive of the time-dependent mechanistic biological interactions between NMs and individual cells. This work is expected to provide a means of extrapolation to pre-clinical or human biodistribution with cellular level resolution for NMs starting only from in vitro data.

Molecular thermodynamics of receptor competition for endocytic uptake

Endocytic uptake of receptors from the cell surface plays an important role in diverse processes from cell signaling to nutrient internalization. Understanding the mechanisms by which endocytic structures select receptors for internalization is of fundamental importance to our understanding of cellular physiology. Binding of receptors to the endocytic protein machinery is known to facilitate receptor loading into endocytic structures. However, many receptor species use the same small set of biochemical motifs to interact with the endocytic machinery, suggesting that receptors may compete for a limited number of binding sites within endocytic structures. Previous studies have shown that such competition can substantially modify receptor uptake. However, a predictive biophysical understanding of this phenomenon is currently lacking. Toward addressing this gap, here we employ quantitative imaging and statistical thermodynamics to measure and predict the competition between two distinct receptor species that are internalized simultaneously from the cell surface. Our studies demonstrate that when receptors compete for the same interactions with the endocytic machinery, their uptake is fundamentally coupled. Importantly, we find that these trends can be quantitatively predicted by a simple thermodynamic analysis. These results suggest that multiple receptor species reach an equilibrium partitioning between endocytic structures and the surrounding plasma membrane as the receptors compete for occupancy within dynamic endocytic structures. More broadly, this work provides a quantitative framework for predicting the impact of competition on receptor uptake, an effect which has the potential to physically couple signaling pathways that impact diverse aspects of cellular physiology.

Membrane Diffusion Occurs by Continuous-Time Random Walk Sustained by Vesicular Trafficking

Diffusion in cellular membranes is regulated by processes that occur over a range of spatial and temporal scales. These processes include membrane fluidity, interprotein and interlipid interactions, interactions with membrane microdomains, interactions with the underlying cytoskeleton, and cellular processes that result in net membrane movement. The complex, non-Brownian diffusion that results from these processes has been difficult to characterize, and moreover, the impact of factors such as membrane recycling on membrane diffusion remains largely unexplored. We have used a careful statistical analysis of single-particle tracking data of the single-pass plasma membrane protein CD93 to show that the diffusion of this protein is well described by a continuous-time random walk in parallel with an aging process mediated by membrane corrals. The overall result is an evolution in the diffusion of CD93: proteins initially diffuse freely on the cell surface but over time become increasingly trapped within diffusion-limiting membrane corrals. Stable populations of freely diffusing and corralled CD93 are maintained by an endocytic/exocytic process in which corralled CD93 is selectively endocytosed, whereas freely diffusing CD93 is replenished by exocytosis of newly synthesized and recycled CD93. This trafficking not only maintained CD93 diffusivity but also maintained the heterogeneous distribution of CD93 in the plasma membrane. These results provide insight into the nature of the biological and biophysical processes that can lead to significantly non-Brownian diffusion of membrane proteins and demonstrate that ongoing membrane recycling is critical to maintaining steady-state diffusion and distribution of proteins in the plasma membrane.

Temporal dependence of shifts in mu opioid receptor mobility at the cell surface after agonist binding observed by single-particle tracking

Agonist binding to the mu opioid receptor (MOR) results in conformational changes that allow recruitment of G-proteins, activation of downstream effectors and eventual desensitization and internalization, all of which could affect receptor mobility. The present study employed single particle tracking (SPT) of quantum dot labeled FLAG-tagged MORs to examine shifts in MOR mobility after agonist binding. FLAG-MORs on the plasma membrane were in both mobile and immobile states under basal conditions. Activation of FLAG-MORs with DAMGO caused an acute increase in the fraction of mobile MORs, and free portions of mobile tracks were partially dependent on interactions with G-proteins. In contrast, 10-minute exposure to DAMGO or morphine increased the fraction of immobile FLAG-MORs. While the decrease in mobility with prolonged DAMGO exposure corresponded to an increase in colocalization with clathrin, the increase in colocalization was present in both mobile and immobile FLAG-MORs. Thus, no single mobility state of the receptor accounted for colocalization with clathrin. These findings demonstrate that SPT can be used to track agonist-dependent changes in MOR mobility over time, but that the mobility states observed likely arise from a diverse set of interactions and will be most informative when examined in concert with particular downstream effectors.

Entropic Control of Receptor Recycling Using Engineered Ligands

Receptor internalization by endocytosis regulates diverse cellular processes, from the rate of nutrient uptake to the timescale of essential signaling events. The established view is that internalization is tightly controlled by specific protein-binding interactions. However, recent work suggests that physical aspects of receptors influence the process in ways that cannot be explained by biochemistry alone. Specifically, work from several groups suggests that increasing the steric bulk of receptors may inhibit their uptake by multiple types of trafficking vesicles. How do biochemical and biophysical factors work together to control internalization? Here, we show that receptor uptake is well described by a thermodynamic trade-off between receptor-vesicle binding energy and the entropic cost of confining receptors within endocytic vesicles. Specifically, using large ligands to acutely increase the size of engineered variants of the transferrin receptor, we demonstrate that an increase in the steric bulk of a receptor dramatically decreases its probability of uptake by clathrin-coated structures. Further, in agreement with a simple thermodynamic analysis, all data collapse onto a single trend relating fractional occupancy of the endocytic structure to fractional occupancy of the surrounding plasma membrane, independent of receptor size. This fundamental scaling law provides a simple tool for predicting the impact of receptor expression level, steric bulk, and the size of endocytic structures on receptor uptake. More broadly, this work suggests that bulky ligands could be used to drive the accumulation of specific receptors at the plasma membrane surface, providing a biophysical tool for targeted modulation of signaling and metabolism from outside the cell.

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.

Recent advances in optical microscopic methods for single-particle tracking in biological samples

With the rapid development of optical microscopic techniques, explorations on the chemical and biological properties of target objects in biological samples at single-molecule/particle level have received great attention recently. In the past decades, various powerful techniques have been developed for single-particle tracking (SPT) in biological samples. In this review, we summarize the commonly used optical microscopic methods for SPT, such as total internal reflection fluorescence microscopy (TIRFM), super-resolution fluorescence microscopy (SRM), dark-field optical microscopy (DFM), total internal reflection scattering microscopy (TIRSM), and differential interference contrast microscopy (DICM). We then discuss the image processing and data analysis methods, including particle localization, trajectory reconstruction, and diffusion behavior analysis. The application of SPT on the cell membrane, within the cell, and the cellular invading process of viruses are introduced. Finally, the challenges and prospects of optical microscopic technologies for SPT are delineated.

Identifying diffusive motions in single-particle trajectories on the plasma membrane via fractional time-series models

In this paper we show that an autoregressive fractionally integrated moving average time-series model can identify two types of motion of membrane proteins on the surface of mammalian cells. Specifically we analyze the motion of the voltage-gated sodium channel Nav1.6 and beta-2 adrenergic receptors. We find that the autoregressive (AR) part models well the confined dynamics whereas the fractionally integrated moving average (FIMA) model describes the nonconfined periods of the trajectories. Since the Ornstein-Uhlenbeck process is a continuous counterpart of the AR model, we are also able to calculate its physical parameters and show their biological relevance. The fitted FIMA and AR parameters show marked differences in the dynamics of the two studied molecules.

Neuronal messenger ribonucleoprotein transport follows an aging Lévy walk

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

Elucidating distinct ion channel populations on the surface of hippocampal neurons via single-particle tracking recurrence analysis

Protein and lipid nanodomains are prevalent on the surface of mammalian cells. In particular, it has been recently recognized that ion channels assemble into surface nanoclusters in the soma of cultured neurons. However, the interactions of these molecules with surface nanodomains display a considerable degree of heterogeneity. Here, we investigate this heterogeneity and develop statistical tools based on the recurrence of individual trajectories to identify subpopulations within ion channels in the neuronal surface. We specifically study the dynamics of the K^{+} channel Kv1.4 and the Na^{+} channel Nav1.6 on the surface of cultured hippocampal neurons at the single-molecule level. We find that both these molecules are expressed in two different forms with distinct kinetics with regards to surface interactions, emphasizing the complex proteomic landscape of the neuronal surface. Further, the tools presented in this work provide new methods for the analysis of membrane nanodomains, transient confinement, and identification of populations within single-particle trajectories.

Ergodicity breaking on the neuronal surface emerges from random switching between diffusive states

Stochastic motion on the surface of living cells is critical to promote molecular encounters that are necessary for multiple cellular processes. Often the complexity of the cell membranes leads to anomalous diffusion, which under certain conditions it is accompanied by non-ergodic dynamics. Here, we unravel two manifestations of ergodicity breaking in the dynamics of membrane proteins in the somatic surface of hippocampal neurons. Three different tagged molecules are studied on the surface of the soma: the voltage-gated potassium and sodium channels Kv1.4 and Nav1.6 and the glycoprotein CD4. In these three molecules ergodicity breaking is unveiled by the confidence interval of the mean square displacement and by the dynamical functional estimator. Ergodicity breaking is found to take place due to transient confinement effects since the molecules alternate between free diffusion and confined motion.

Single-Molecule Imaging of Nav1.6 on the Surface of Hippocampal Neurons Reveals Somatic Nanoclusters

Voltage-gated sodium (Nav) channels are responsible for the depolarizing phase of the action potential in most nerve cells, and Nav channel localization to the axon initial segment is vital to action potential initiation. Nav channels in the soma play a role in the transfer of axonal output information to the rest of the neuron and in synaptic plasticity, although little is known about Nav channel localization and dynamics within this neuronal compartment. This study uses single-particle tracking and photoactivation localization microscopy to analyze cell-surface Nav1.6 within the soma of cultured hippocampal neurons. Mean-square displacement analysis of individual trajectories indicated that half of the somatic Nav1.6 channels localized to stable nanoclusters ∼230 nm in diameter. Strikingly, these domains were stabilized at specific sites on the cell membrane for >30 min, notably via an ankyrin-independent mechanism, indicating that the means by which Nav1.6 nanoclusters are maintained in the soma is biologically different from axonal localization. Nonclustered Nav1.6 channels showed anomalous diffusion, as determined by mean-square-displacement analysis. High-density single-particle tracking of Nav channels labeled with photoactivatable fluorophores in combination with Bayesian inference analysis was employed to characterize the surface nanoclusters. A subpopulation of mobile Nav1.6 was observed to be transiently trapped in the nanoclusters. Somatic Nav1.6 nanoclusters represent a new, to our knowledge, type of Nav channel localization, and are hypothesized to be sites of localized channel regulation.

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

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

Nonergodic subdiffusion from transient interactions with heterogeneous partners

Spatiotemporal disorder has been recently associated to the occurrence of anomalous nonergodic diffusion of molecular components in biological systems, but the underlying microscopic mechanism is still unclear. We introduce a model in which a particle performs continuous Brownian motion with changes of diffusion coefficients induced by transient molecular interactions with diffusive binding partners. In spite of the exponential distribution of waiting times, the model shows subdiffusion and nonergodicity similar to the heavy-tailed continuous time random walk. The dependence of these properties on the density of binding partners is analyzed and discussed. Our work provides an experimentally testable microscopic model to investigate the nature of nonergodicity in disordered media.

Plasma Membrane is Compartmentalized by a Self-Similar Cortical Actin Meshwork

A broad range of membrane proteins display anomalous diffusion on the cell surface. Different methods provide evidence for obstructed subdiffusion and diffusion on a fractal space, but the underlying structure inducing anomalous diffusion has never been visualized because of experimental challenges. We addressed this problem by imaging the cortical actin at high resolution while simultaneously tracking individual membrane proteins in live mammalian cells. Our data confirm that actin introduces barriers leading to compartmentalization of the plasma membrane and that membrane proteins are transiently confined within actin fences. Furthermore, superresolution imaging shows that the cortical actin is organized into a self-similar meshwork. These results present a hierarchical nanoscale picture of the plasma membrane.

Aging underdamped scaled Brownian motion: Ensemble- and time-averaged particle displacements, nonergodicity, and the failure of the overdamping approximation

We investigate both analytically and by computer simulations the ensemble- and time-averaged, nonergodic, and aging properties of massive particles diffusing in a medium with a time dependent diffusivity. We call this stochastic diffusion process the (aging) underdamped scaled Brownian motion (UDSBM). We demonstrate how the mean squared displacement (MSD) and the time-averaged MSD of UDSBM are affected by the inertial term in the Langevin equation, both at short, intermediate, and even long diffusion times. In particular, we quantify the ballistic regime for the MSD and the time-averaged MSD as well as the spread of individual time-averaged MSD trajectories. One of the main effects we observe is that, both for the MSD and the time-averaged MSD, for superdiffusive UDSBM the ballistic regime is much shorter than for ordinary Brownian motion. In contrast, for subdiffusive UDSBM, the ballistic region extends to much longer diffusion times. Therefore, particular care needs to be taken under what conditions the overdamped limit indeed provides a correct description, even in the long time limit. We also analyze to what extent ergodicity in the Boltzmann-Khinchin sense in this nonstationary system is broken, both for subdiffusive and superdiffusive UDSBM. Finally, the limiting case of ultraslow UDSBM is considered, with a mixed logarithmic and power-law dependence of the ensemble- and time-averaged MSDs of the particles. In the limit of strong aging, remarkably, the ordinary UDSBM and the ultraslow UDSBM behave similarly in the short time ballistic limit. The approaches developed here open ways for considering other stochastic processes under physically important conditions when a finite particle mass and aging in the system cannot be neglected.

Identifying ergodicity breaking for fractional anomalous diffusion: Criteria for minimal trajectory length

In this paper, we study ergodic properties of α-stable autoregressive fractionally integrated moving average (ARFIMA) processes which form a large class of anomalous diffusions. A crucial practical question is how long trajectories one needs to observe in an experiment in order to claim that the analyzed data are ergodic or not. This will be solved by checking the asymptotic convergence to 0 of the empirical estimator F(n) for the dynamical functional D(n) defined as a Fourier transform of the n-lag increments of the ARFIMA process. Moreover, we introduce more flexible concept of the ε-ergodicity.

Increased spatiotemporal resolution reveals highly dynamic dense tubular matrices in the peripheral ER

The endoplasmic reticulum (ER) is an expansive, membrane-enclosed organelle that plays crucial roles in numerous cellular functions. We used emerging superresolution imaging technologies to clarify the morphology and dynamics of the peripheral ER, which contacts and modulates most other intracellular organelles. Peripheral components of the ER have classically been described as comprising both tubules and flat sheets. We show that this system consists almost exclusively of tubules at varying densities, including structures that we term ER matrices. Conventional optical imaging technologies had led to misidentification of these structures as sheets because of the dense clustering of tubular junctions and a previously uncharacterized rapid form of ER motion. The existence of ER matrices explains previous confounding evidence that had indicated the occurrence of ER "sheet" proliferation after overexpression of tubular junction-forming proteins.

Strange kinetics of bulk-mediated diffusion on lipid bilayers

Diffusion at solid-liquid interfaces is crucial in many technological and biophysical processes. Although its behavior seems to be deceivingly simple, recent studies showing passive superdiffusive transport suggest that diffusion on surfaces may hide rich complexities. In particular, bulk-mediated diffusion occurs when molecules are transiently released from the surface to perform three-dimensional excursions into the liquid bulk. This phenomenon bears the dichotomy where a molecule always return to the surface but the mean jump length is infinite. Such behavior is associated with a breakdown of the central limit theorem and weak ergodicity breaking. Here, we use single-particle tracking to study the statistics of bulk-mediated diffusion on a supported lipid bilayer. We find that the time-averaged mean square displacement (MSD) of individual trajectories, the archetypal measure in diffusion processes, does not converge to the ensemble MSD but it remains a random variable, even in the long observation-time limit. The distribution of time averages is shown to agree with a Lévy flight model. Our results also unravel intriguing anomalies in the statistics of displacements. The time-averaged MSD is shown to depend on experimental time and investigations of fractional moments show a scaling 〈|r(t)|(q)〉∼t(qν(q)) with non-linear exponents, i.e. ν(q) ≠ const. This type of behavior is termed strong anomalous diffusion and is rare among experimental observations.

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

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

Imaging approaches for analysis of cholesterol distribution and dynamics in the plasma membrane

Cholesterol is an important lipid component of the plasma membrane (PM) of mammalian cells, where it is involved in control of many physiological processes, such as endocytosis, cell migration, cell signalling and surface ruffling. In an attempt to explain these functions of cholesterol, several models have been put forward about cholesterol's lateral and transbilayer organization in the PM. In this article, we review imaging techniques developed over the last two decades for assessing the distribution and dynamics of cholesterol in the PM of mammalian cells. Particular focus is on fluorescence techniques to study the lateral and inter-leaflet distribution of suitable cholesterol analogues in the PM of living cells. We describe also several methods for determining lateral cholesterol dynamics in the PM including fluorescence recovery after photobleaching (FRAP), fluorescence correlation spectroscopy (FCS), single particle tracking (SPT) and spot variation FCS coupled to stimulated emission depletion (STED) microscopy. For proper interpretation of such measurements, we provide some background in probe photophysics and diffusion phenomena occurring in cell membranes. In particular, we show the equivalence of the reaction-diffusion approach, as used in FRAP and FCS, and continuous time random walk (CTRW) models, as often invoked in SPT studies. We also discuss mass spectrometry (MS) based imaging of cholesterol in the PM of fixed cells and compare this method with fluorescence imaging of sterols. We conclude that evidence from many experimental techniques converges towards a model of a homogeneous distribution of cholesterol with largely free and unhindered diffusion in both leaflets of the PM.

Membrane bending by protein crowding is affected by protein lateral confinement

Crowding of asymmetrically-distributed membrane proteins has been recently recognized as an important factor in remodeling of biological membranes, for example during transport vesicle formation. In this paper, we theoretically analyze the effect of protein crowding on membrane bending and examine its dependence on protein size, shape, transmembrane asymmetry and lateral confinement. We consider three scenarios of protein lateral organization, which are highly relevant for cellular membranes in general: freely diffusing membrane proteins without lateral confinement, the presence of a diffusion barrier and interactions with a vesicular coat. We show that protein crowding affects vesicle formation even if the proteins are distributed symmetrically across the membrane and that this effect depends significantly on lateral confinement. The largest crowding effect is predicted for the proteins that are confined to the forming vesicle by a diffusion barrier. We calculate the bending properties of a crowded membrane and find that its spontaneous curvature depends primarily on the degree of transmembrane asymmetry, and its effective bending modulus on the type of lateral confinement. Using the example of COPII vesicle formation from the endoplasmic reticulum, we analyze the energetic cost of vesicle formation. The results provide a novel insight into the effects of lateral and transmembrane organization of membrane proteins, and can guide data interpretation and future experimental approaches.

Non-Brownian diffusion in lipid membranes: Experiments and simulations

The dynamics of constituents and the surface response of cellular membranes-also in connection to the binding of various particles and macromolecules to the membrane-are still a matter of controversy in the membrane biophysics community, particularly with respect to crowded membranes of living biological cells. We here put into perspective recent single particle tracking experiments in the plasma membranes of living cells and supercomputing studies of lipid bilayer model membranes with and without protein crowding. Special emphasis is put on the observation of anomalous, non-Brownian diffusion of both lipid molecules and proteins embedded in the lipid bilayer. While single component, pure lipid bilayers in simulations exhibit only transient anomalous diffusion of lipid molecules on nanosecond time scales, the persistence of anomalous diffusion becomes significantly longer ranged on the addition of disorder-through the addition of cholesterol or proteins-and on passing of the membrane lipids to the gel phase. Concurrently, experiments demonstrate the anomalous diffusion of membrane embedded proteins up to macroscopic time scales in the minute time range. Particular emphasis will be put on the physical character of the anomalous diffusion, in particular, the occurrence of ageing observed in the experiments-the effective diffusivity of the measured particles is a decreasing function of time. Moreover, we present results for the time dependent local scaling exponent of the mean squared displacement of the monitored particles. Recent results finding deviations from the commonly assumed Gaussian diffusion patterns in protein crowded membranes are reported. The properties of the displacement autocorrelation function of the lipid molecules are discussed in the light of their appropriate physical anomalous diffusion models, both for non-crowded and crowded membranes. In the last part of this review we address the upcoming field of membrane distortion by elongated membrane-binding particles. We discuss how membrane compartmentalisation and the particle-membrane binding energy may impact the dynamics and response of lipid membranes. This article is part of a Special Issue entitled: Biosimulations edited by Ilpo Vattulainen and Tomasz Róg.

Superdiffusive motion of membrane-targeting C2 domains

Membrane-targeting domains play crucial roles in the recruitment of signalling molecules to the plasma membrane. For most peripheral proteins, the protein-to-membrane interaction is transient. After proteins dissociate from the membrane they have been observed to rebind following brief excursions in the bulk solution. Such membrane hops can have broad implications for the efficiency of reactions on membranes. We study the diffusion of membrane-targeting C2 domains using single-molecule tracking in supported lipid bilayers. The ensemble-averaged mean square displacement (MSD) exhibits superdiffusive behaviour. However, traditional time-averaged MSD analysis of individual trajectories remains linear and does not reveal superdiffusion. Our observations are explained in terms of bulk excursions that introduce jumps with a heavy-tail distribution. These hopping events allow proteins to explore large areas in a short time. The experimental results are shown to be consistent with analytical models of bulk-mediated diffusion and numerical simulations.

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.

Single Particle Tracking Reveals that EGFR Signaling Activity Is Amplified in Clathrin-Coated Pits

Signaling from the epidermal growth factor receptor (EGFR) via phosphorylation on its C-terminal tyrosine residues requires self-association, which depends on the diffusional properties of the receptor and its density in the plasma membrane. Dimerization is a key event for EGFR activation, but the role of higher order clustering is unknown. We employed single particle tracking to relate the mobility and aggregation of EGFR to its signaling activity. EGFR mobility alternates between short-lived free, confined and immobile states. In the immobile state, EGFR tends to aggregate in clathrin-coated pits, which is further enhanced in a phosphorylation-dependent manner and does not require ligand binding. EGFR phosphorylation is further amplified by cross-phosphorylation in clathrin-coated pits. Because phosphorylated receptors can escape from the pits, local gradients of signaling active EGFR are formed. These results show that amplification of EGFR phosphorylation by receptor clustering in clathrin-coated pits supports signal activation at the plasma membrane.

Dynamics and Interactions of Individual Proteins in the Membrane of Single, Living Cells

Total internal reflection fluorescence (TIRF) microscopy is a powerful technique for interrogating protein dynamics in the membranes of living single cells. Receptor-ligand interactions are of particular interest for improving our understanding of cell signaling networks in a variety of applications. Here, we describe methods for fluorescently labeling individual receptors and their ligands, conducting single-molecule TIRF microscopy of receptors and ligands in single, living cells, and importantly, performing image analysis on the resulting time sequence of images to extract quantitative dynamics. While we use Toll-like receptor 4 and its ligand lipopolysaccharide as a specific example, the methods are general and readily extendable to other receptor-ligand systems of importance in cellular biology.

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

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

Single Molecule 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.

Intrinsically disordered proteins drive membrane curvature

Assembly of highly curved membrane structures is essential to cellular physiology. The prevailing view has been that proteins with curvature-promoting structural motifs, such as wedge-like amphipathic helices and crescent-shaped BAR domains, are required for bending membranes. Here we report that intrinsically disordered domains of the endocytic adaptor proteins, Epsin1 and AP180 are highly potent drivers of membrane curvature. This result is unexpected since intrinsically disordered domains lack a well-defined three-dimensional structure. However, in vitro measurements of membrane curvature and protein diffusivity demonstrate that the large hydrodynamic radii of these domains generate steric pressure that drives membrane bending. When disordered adaptor domains are expressed as transmembrane cargo in mammalian cells, they are excluded from clathrin-coated pits. We propose that a balance of steric pressure on the two surfaces of the membrane drives this exclusion. These results provide quantitative evidence for the influence of steric pressure on the content and assembly of curved cellular membrane structures.

Proteins that bend membranes often contain curvature-promoting structural motifs such as wedges or crescent-shaped domains. Busch et al. report that intrinsically disordered domains can also drive membrane curvature and provide evidence that steric pressure driven by protein crowding mediates this effect.