Confined diffusion without fences of a g-protein-coupled receptor as revealed by single particle tracking

Where Biology Meets Physics--A Converging View on Membrane Microdomain Dynamics

For several decades, the phenomenon of membrane component segregation into microdomains has been a well-known and highly debated subject, and varying concepts including the raft hypothesis, the fence-and-picket model, hydrophobic-mismatch, and specific protein-protein interactions have been offered as explanations. Here, we review the level of insight into the molecular architecture of membrane domains one is capable of obtaining through biological experimentation. Using SNARE proteins as a paradigm, comprehensive data suggest that several dozens of molecules crowd together into almost circular spots smaller than 100 nm. Such clusters are highly dynamical as they constantly capture and lose molecules. The organization has a strong influence on the functional availability of proteins and likely provides a molecular scaffold for more complex protein networks. Despite this high level of insight, fundamental open questions remain, applying not only to SNARE protein domains but more generally to all types of membrane domains. In this context, we explain the view of physical models and how they are beneficial in advancing our concept of micropatterning. While biological models generally remain qualitative and descriptive, physics aims towards making them quantitative and providing reproducible numbers, in order to discriminate between different mechanisms which have been proposed to account for experimental observations. Despite the fundamental differences in biological and physical approaches as far as cell membrane microdomains are concerned, we are able to show that convergence on common points of views is in reach.

Extracting Diffusive States of Rho GTPase in Live Cells: Towards In Vivo Biochemistry

Resolving distinct biochemical interaction states when analyzing the trajectories of diffusing proteins in live cells on an individual basis remains challenging because of the limited statistics provided by the relatively short trajectories available experimentally. Here, we introduce a novel, machine-learning based classification methodology, which we call perturbation expectation-maximization (pEM), that simultaneously analyzes a population of protein trajectories to uncover the system of diffusive behaviors which collectively result from distinct biochemical interactions. We validate the performance of pEM in silico and demonstrate that pEM is capable of uncovering the proper number of underlying diffusive states with an accurate characterization of their diffusion properties. We then apply pEM to experimental protein trajectories of Rho GTPases, an integral regulator of cytoskeletal dynamics and cellular homeostasis, in vivo via single particle tracking photo-activated localization microcopy. Remarkably, pEM uncovers 6 distinct diffusive states conserved across various Rho GTPase family members. The variability across family members in the propensities for each diffusive state reveals non-redundant roles in the activation states of RhoA and RhoC. In a resting cell, our results support a model where RhoA is constantly cycling between activation states, with an imbalance of rates favoring an inactive state. RhoC, on the other hand, remains predominantly inactive.

Single particle tracking is a powerful tool that captures the diffusive dynamics of proteins as they undergo various interactions in living cells. Uncovering different biochemical interactions by analyzing the diffusive behaviors of individual protein trajectories, however, is challenging due to the limited statistics provided by short trajectories and experimental noise sources which are intimately coupled into each protein’s localization. Here, we introduce a novel, unsupervised, machine-learning based classification methodology, which we call perturbation expectation-maximization (pEM), that simultaneously analyzes a population of protein trajectories to uncover the system of diffusive behaviors which collectively result from distinct biochemical interactions. We validate the performance of pEM in silico and in vivo on the biological system of Rho GTPase, a signal transduction protein responsible for regulating cytoskeletal dynamics. We envision that the presented methodology will be applicable to a wide range of single protein tracking data where different biochemical interactions result in distinct diffusive behaviors. More generally, this study brings us an important step closer to the possibility of monitoring the endogenous biochemistry of diffusing proteins within live cells with single molecule resolution.

Oxygen depletion speeds and simplifies diffusion in HeLa cells

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

Probing the pharmacology of G protein-coupled receptors with fluorescent ligands

G protein-coupled receptors control a wide range of physiological processes and are the target for many clinically used drugs. Understanding the way in which receptors bind agonists and antagonists, their organisation in the membrane and their regulation after agonist binding are important properties which are key to developing new drugs. One way to achieve this knowledge is through the use of fluorescent ligands, which have been used to study the expression and function of receptors in endogenously expressing systems. Fluorescent ligands with appropriate imaging properties can be used in conjunction with confocal microscopy to investigate the regulation of receptors after activation. Alternatively, through the use of single molecule microscopy, they can probe the spatial organisation of receptors within the membrane. This review focuses on the techniques in which fluorescent ligands have been used and the novel aspects of G protein-coupled receptor pharmacology which have been uncovered. This article is part of the Special Issue entitled 'Fluorescent Tools in Neuropharmacology'.

Single-quantum-dot tracking reveals altered membrane dynamics of an attention-deficit/hyperactivity-disorder-derived dopamine transporter coding variant

The presynaptic, cocaine- and amphetamine-sensitive dopamine (DA) transporter (DAT, SLC6A3) controls the intensity and duration of synaptic dopamine signals by rapid clearance of DA back into presynaptic nerve terminals. Abnormalities in DAT-mediated DA clearance have been linked to a variety of neuropsychiatric disorders, including addiction, autism, and attention deficit/hyperactivity disorder (ADHD). Membrane trafficking of DAT appears to be an important, albeit incompletely understood, post-translational regulatory mechanism; its dysregulation has been recently proposed as a potential risk determinant of these disorders. In this study, we demonstrate a link between an ADHD-associated DAT mutation (Arg615Cys, R615C) and variation on DAT transporter cell surface dynamics, a combination only previously studied with ensemble biochemical and optical approaches that featured limited spatiotemporal resolution. Here, we utilize high-affinity, DAT-specific antagonist-conjugated quantum dot (QD) probes to establish the dynamic mobility of wild-type and mutant DATs at the plasma membrane of living cells. Single DAT-QD complex trajectory analysis revealed that the DAT 615C variant exhibited increased membrane mobility relative to DAT 615R, with diffusion rates comparable to those observed after lipid raft disruption. This phenomenon was accompanied by a loss of transporter mobilization triggered by amphetamine, a common component of ADHD medications. Together, our data provides the first dynamic imaging of single DAT proteins, providing new insights into the relationship between surface dynamics and trafficking of both wild-type and disease-associated transporters. Our approach should be generalizable to future studies that explore the possibilities of perturbed surface DAT dynamics that may arise as a consequence of genetic alterations, regulatory changes, and drug use that contribute to the etiology or treatment of neuropsychiatric disorders.

Single-molecule diffusion and conformational dynamics by spatial integration of temporal fluctuations

Single-molecule localization and tracking has been used to translate spatiotemporal information of individual molecules to map their diffusion behaviours. However, accurate analysis of diffusion behaviours and including other parameters, such as the conformation and size of molecules, remain as limitations to the method. Here, we report a method that addresses the limitations of existing single-molecular localization methods. The method is based on temporal tracking of the cumulative area occupied by molecules. These temporal fluctuations are tied to molecular size, rates of diffusion and conformational changes. By analysing fluorescent nanospheres and double-stranded DNA molecules of different lengths and topological forms, we demonstrate that our cumulative-area method surpasses the conventional single-molecule localization method in terms of the accuracy of determined diffusion coefficients. Furthermore, the cumulative-area method provides conformational relaxation times of structurally flexible chains along with diffusion coefficients, which together are relevant to work in a wide spectrum of scientific fields.

Single-molecule localization and tracking technique is widely used to visualize molecular dynamics in life science, yet it fails to detect molecular conformation. Serag et al. address this limitation via spatial quantization of temporal fluctuations in the cumulative area occupied by molecules.

Heterologous regulation of Mu-opioid (MOP) receptor mobility in the membrane of SH-SY5Y cells

The dynamic organization of G protein-coupled receptors in the plasma membrane is suspected of playing a role in their function. The regulation of the diffusion mode of the mu-opioid (MOP) receptor was previously shown to be agonist-specific. Here we investigate the regulation of MOP receptor diffusion by heterologous activation of other G protein-coupled receptors and characterize the dynamic properties of the MOP receptor within the heterodimer MOP/neuropeptide FF (NPFF2) receptor. The data show that the dynamics and signaling of the MOP receptor in SH-SY5Y cells are modified by the activation of α2-adrenergic and NPFF2 receptors, but not by the activation of receptors not described to interact with the opioid receptor. By combining, for the first time, fluorescence recovery after photobleaching at variable radius experiments with bimolecular fluorescence complementation, we show that the MOP/NPFF2 heterodimer adopts a specific diffusion behavior that corresponds to a mix of the dynamic properties of both MOP and NPFF2 receptors. Altogether, the data suggest that heterologous regulation is accompanied by a specific organization of receptors in the membrane.

Dynamic imaging of genomic loci in living human cells by an optimized CRISPR/Cas system

The spatiotemporal organization and dynamics of chromatin play critical roles in regulating genome function. However, visualizing specific, endogenous genomic loci remains challenging in living cells. Here, we demonstrate such an imaging technique by repurposing the bacterial CRISPR/Cas system. Using an EGFP-tagged endonuclease-deficient Cas9 protein and a structurally optimized small guide (sg) RNA, we show robust imaging of repetitive elements in telomeres and coding genes in living cells. Furthermore, an array of sgRNAs tiling along the target locus enables the visualization of nonrepetitive genomic sequences. Using this method, we have studied telomere dynamics during elongation or disruption, the subnuclear localization of the MUC4 loci, the cohesion of replicated MUC4 loci on sister chromatids, and their dynamic behaviors during mitosis. This CRISPR imaging tool has potential to significantly improve the capacity to study the conformation and dynamics of native chromosomes in living human cells.

Influences of excluded volume of molecules on signaling processes on the biomembrane

We investigate the influences of the excluded volume of molecules on biochemical reaction processes on 2-dimensional surfaces using a model of signal transduction processes on biomembranes. We perform simulations of the 2-dimensional cell-based model, which describes the reactions and diffusion of the receptors, signaling proteins, target proteins, and crowders on the cell membrane. The signaling proteins are activated by receptors, and these activated signaling proteins activate target proteins that bind autonomously from the cytoplasm to the membrane, and unbind from the membrane if activated. If the target proteins bind frequently, the volume fraction of molecules on the membrane becomes so large that the excluded volume of the molecules for the reaction and diffusion dynamics cannot be negligible. We find that such excluded volume effects of the molecules induce non-trivial variations of the signal flow, defined as the activation frequency of target proteins, as follows. With an increase in the binding rate of target proteins, the signal flow varies by monotonically increasing; increasing then decreasing in a bell-shaped curve; or increasing, decreasing, then increasing in an S-shaped curve. We further demonstrate that the excluded volume of molecules influences the hierarchical molecular distributions throughout the reaction processes. In particular, when the system exhibits a large signal flow, the signaling proteins tend to surround the receptors to form receptor-signaling protein clusters, and the target proteins tend to become distributed around such clusters. To explain these phenomena, we analyze the stochastic model of the local motions of molecules around the receptor.

Regulation of μ-opioid receptors: desensitization, phosphorylation, internalization, and tolerance

Morphine and related µ-opioid receptor (MOR) agonists remain among the most effective drugs known for acute relief of severe pain. A major problem in treating painful conditions is that tolerance limits the long-term utility of opioid agonists. Considerable effort has been expended on developing an understanding of the molecular and cellular processes that underlie acute MOR signaling, short-term receptor regulation, and the progression of events that lead to tolerance for different MOR agonists. Although great progress has been made in the past decade, many points of contention and controversy cloud the realization of this progress. This review attempts to clarify some confusion by clearly defining terms, such as desensitization and tolerance, and addressing optimal pharmacological analyses for discerning relative importance of these cellular mechanisms. Cellular and molecular mechanisms regulating MOR function by phosphorylation relative to receptor desensitization and endocytosis are comprehensively reviewed, with an emphasis on agonist-biased regulation and areas where knowledge is lacking or controversial. The implications of these mechanisms for understanding the substantial contribution of MOR signaling to opioid tolerance are then considered in detail. While some functional MOR regulatory mechanisms contributing to tolerance are clearly understood, there are large gaps in understanding the molecular processes responsible for loss of MOR function after chronic exposure to opioids. Further elucidation of the cellular mechanisms that are regulated by opioids will be necessary for the successful development of MOR-based approaches to new pain therapeutics that limit the development of tolerance.

Inferring diffusion in single live cells at the single-molecule level

The movement of molecules inside living cells is a fundamental feature of biological processes. The ability to both observe and analyse the details of molecular diffusion in vivo at the single-molecule and single-cell level can add significant insight into understanding molecular architectures of diffusing molecules and the nanoscale environment in which the molecules diffuse. The tool of choice for monitoring dynamic molecular localization in live cells is fluorescence microscopy, especially so combining total internal reflection fluorescence with the use of fluorescent protein (FP) reporters in offering exceptional imaging contrast for dynamic processes in the cell membrane under relatively physiological conditions compared with competing single-molecule techniques. There exist several different complex modes of diffusion, and discriminating these from each other is challenging at the molecular level owing to underlying stochastic behaviour. Analysis is traditionally performed using mean square displacements of tracked particles; however, this generally requires more data points than is typical for single FP tracks owing to photophysical instability. Presented here is a novel approach allowing robust Bayesian ranking of diffusion processes to discriminate multiple complex modes probabilistically. It is a computational approach that biologists can use to understand single-molecule features in live cells.

The dynamics of somatic exocytosis in monoaminergic neurons

Some monoaminergic neurons can release neurotransmitters by exocytosis from their cell bodies. The amount of monoamine released by somatic exocytosis can be comparable to that released by synaptic exocytosis, though neither the underlying mechanisms nor the functional significance of somatic exocytosis are well understood. A detailed examination of these characteristics may provide new routes for therapeutic intervention in mood disorders, substance addiction, and neurodegenerative diseases. The relatively large size of the cell body provides a unique opportunity to understand the mechanism of this mode of neuronal exocytosis in microscopic detail. Here we used three photon and total internal reflection fluorescence microscopy to focus on the dynamics of the pre-exocytotic events and explore the nature of somatic vesicle storage, transport, and docking at the membrane of serotonergic neurons from raphe nuclei of the rat brain. We find that the vesicles (or unresolved vesicular clusters) are quiescent (mean square displacement, MSD ∼0.04 μm(2)/s) before depolarization, and they move minimally (<1 μm) from their locations over a time-scale of minutes. However, within minutes of depolarization, the vesicles become more dynamic (MSD ∼0.3 μm(2)/s), and display larger range (several μm) motions, though without any clear directionality. Docking and subsequent exocytosis at the membrane happen at a timescale (∼25 ms) that is slower than most synaptic exocytosis processes, but faster than almost all somatic exocytosis processes observed in endocrine cells. We conclude that, (A) depolarization causes de-tethering of the neurotransmitter vesicles from their storage locations, and this constitutes a critical event in somatic exocytosis; (B) their subsequent transport kinetics can be described by a process of constrained diffusion, and (C) the pre-exocytosis kinetics at the membrane is faster than most other somatic exocytosis processes reported so far.

Visualization of lipid raft membrane compartmentalization in living RN46A neuronal cells using single quantum dot tracking

Lipid rafts are cholesterol-enriched subdomains in the plasma membrane that have been reported to act as a platform to facilitate neuronal signaling; however, they are suspected to have a very short lifetime, up to only a few seconds, which calls into question their roles in biological signaling. To better understand their diffusion dynamics and membrane compartmentalization, we labeled lipid raft constituent ganglioside GM1 with single quantum dots through the connection of cholera toxin B subunit, a protein that binds specifically to GM1. Diffusion measurements revealed that single quantum dot-labeled GM1 ganglioside complexes undergo slow, confined lateral diffusion with a diffusion coefficient of ∼7.87 × 10(-2) μm(2)/s and a confinement domain about 200 nm in size. Further analysis of their trajectories showed lateral confinement persisting on the order of tens of seconds, comparable to the time scales of the majority of cellular signaling and biological reactions. Hence, our results provide further evidence in support of the putative function of lipid rafts as signaling platforms.

Membrane cholesterol strongly influences confined diffusion of prestin

Prestin is the membrane motor protein that drives outer hair cell (OHC) electromotility, a process that is essential for mammalian hearing. Prestin function is sensitive to membrane cholesterol levels, and numerous studies have suggested that prestin localizes in cholesterol-rich membrane microdomains. Previously, fluorescence recovery after photobleaching experiments were performed in HEK cells expressing prestin-GFP after cholesterol manipulations, and revealed evidence of transient confinement. To further characterize this apparent confined diffusion of prestin, we conjugated prestin to a photostable fluorophore (tetramethylrhodamine) and performed single-molecule fluorescence microscopy. Using single-particle tracking, we determined the microscopic diffusion coefficient from the full time course of the mean-squared deviation. Our results indicate that prestin undergoes diffusion in confinement regions, and that depletion of membrane cholesterol increases confinement size and decreases confinement strength. By interpreting the data in terms of a mathematical model of hop-diffusion, we quantified these cholesterol-induced changes in membrane organization. A complementary analysis of the distribution of squared displacements confirmed that cholesterol depletion reduces prestin confinement. These findings support the hypothesis that prestin function is intimately linked to membrane organization, and further promote a regulatory role for cholesterol in OHC and auditory function.

Insulin receptors and downstream substrates associate with membrane microdomains after treatment with insulin or chromium(III) picolinate

We have examined the association of insulin receptors (IR) and downstream signaling molecules with membrane microdomains in rat basophilic leukemia (RBL-2H3) cells following treatment with insulin or tris(2-pyridinecarbxylato)chromium(III) (Cr(pic)(3)). Single-particle tracking demonstrated that individual IR on these cells exhibited reduced lateral diffusion and increased confinement within 100 nm-scale membrane compartments after treatment with either 200 nM insulin or 10 μM Cr(pic)(3). These treatments also increased the association of native IR, phosphorylated insulin receptor substrate 1 and phosphorylated AKT with detergent-resistant membrane microdomains of characteristically high buoyancy. Confocal fluorescence microscopic imaging of Di-4-ANEPPDHQ labeled RBL-2H3 cells also showed that plasma membrane lipid order decreased following treatment with Cr(pic)(3) but was not altered by insulin treatment. Fluorescence correlation spectroscopy demonstrated that Cr(pic)(3) did not affect IR cell-surface density or compete with insulin for available binding sites. Finally, Fourier transform infrared spectroscopy indicated that Cr(pic)(3) likely associates with the lipid interface in reverse-micelle model membranes. Taken together, these results suggest that activation of IR signaling in a cellular model system by both insulin and Cr(pic)(3) involves retention of IR in specialized nanometer-scale membrane microdomains but that the insulin-like effects of Cr(pic)(3) are due to changes in membrane lipid order rather than to direct interactions with IR.

Non-Gaussianity in single-particle tracking: use of kurtosis to learn the characteristics of a cage-type potential

Nonlinear interaction of membrane proteins with cytoskeleton and membrane leads to non-Gaussian structure of their displacement probability distribution. We propose a statistical analysis technique for learning the characteristics of the nonlinear potential from the time dependence of the cumulants of the displacement distribution. The efficiency of the approach is demonstrated on the analysis of the kurtosis of the displacement distribution of the particle traveling on a membrane in a cage-type potential. Results of numerical simulations are supported by analytical predictions. We show that the approach allows robust identification of some characteristics of the potential for the much lower temporal resolution compared with the mean-square displacement analysis and we demonstrate robustness to experimental errors in determining the particle positions.

Single Particle Tracking reveals two distinct environments for CD4 receptors at the surface of living T lymphocytes

We investigated the lateral diffusion of the HIV receptor CD4 at the surface of T lymphocytes at 20°C and 37°C by Single Particle Tracking using Quantum Dots. We found that the receptors presented two major distinct behaviors that were not equally affected by temperature changes. About half of the receptors showed a random diffusion with a diffusion coefficient increasing upon raising the temperature. The other half of the receptors was permanently or transiently confined with unchanged dynamics on raising the temperature. These observations suggest that two distinct subpopulations of CD4 receptors with different environments are present at the surface of living T lymphocytes.

ErbB1 dimerization is promoted by domain co-confinement and stabilized by ligand binding

The extent to which ligand occupancy and dimerization contribute to erbB1 signaling is controversial. To examine this, we utilized two-color Quantum Dot tracking for visualization of erbB1 homodimerization and quantification of the dimer off rate (k_off) on living cells. Kinetic parameters were extracted using a 3-state Hidden Markov Model to identify transition rates between free, co-confined, and dimerized states. We report that dimers composed of 2 ligand-bound receptors are long-lived and their k_off is independent of kinase activity. By comparison, unliganded dimers have >4-fold faster k_off. Transient co-confinement of receptors promotes repeated encounters and enhances dimer formation. Mobility decreases >6-fold when ligand-bound receptors dimerize. Blockade of erbB1 kinase activity or disruption of actin networks results in faster diffusion of receptor dimers. These results implicate both signal propagation and the cortical cytoskeleton in reduced mobility of signaling-competent erbB1 dimers.

Restricted lateral diffusion of luteinizing hormone receptors in membrane microdomains

Single particle tracking was used to evaluate lateral motions of individual FLAG-tagged human luteinizing hormone (LH) receptors expressed on CHO cells and native LH receptors on both KGN human granulosa-derived tumor cells and M17 human neuroblastoma cells before and after exposure to human chorionic gonadotropin (hCG). Compared with LH receptors on untreated cells, LH receptors on cells treated with 100 nm hCG exhibit restricted lateral diffusion and are confined in small, nanometer-scale, membrane compartments. Similar to LH receptors labeled with Au-hCG, LH receptors labeled with gold-deglycosylated hCG, an hCG antagonist, also exhibit restricted lateral diffusion and are confined in nanoscale membrane compartments on KGN cells treated with 100 nm hCG. LH receptor point mutants lacking potential palmitoylation sites remain in large compartments despite treatment with 100 nm hCG as do LH receptors on cells treated with cytochalasin D. Finally, both polarization homotransfer fluorescence resonance energy transfer imaging and photon counting histogram analysis indicate that treatment with hCG induces aggregation of YFP-coupled LH receptors stably expressed on CHO cells. Taken together, our results demonstrate that binding of hCG induces aggregation of LH receptors within nanoscale, cell surface membrane compartments, that hCG binding also affects the lateral motions of antagonist binding LH receptors, and that receptor surface densities must be considered in evaluating the extent of hormone-dependent receptor aggregation.

Clusters of proteins in biomembranes: insights into the roles of interaction potential shapes and of protein diversity

It has recently been proposed that proteins embedded in lipidic biomembranes can spontaneously self-organize into stable small clusters, or membrane nanodomains, due to the competition between short-range attractive and longer-range repulsive forces between proteins, specific to these systems. In this paper, we carry on our investigation, by Monte Carlo simulations, of different aspects of cluster phases of proteins in biomembranes. First, we compare different long-range potentials (including notably three-body terms) to demonstrate that the existence of cluster phases should be quite generic. Furthermore, a real membrane contains hundreds of different protein species that are far from being randomly distributed in these nanodomains. We take this protein diversity into account by modulating protein-protein interaction potentials both at short and longer range. We confirm theoretical predictions in terms of biological cluster specialization by deciphering how clusters recruit only a few protein species. In this respect, we highlight that cluster phases can turn out to be an advantage at the biological level, for example by enhancing the cell response to external stimuli.

Neuroprotective potential of CB1 receptor agonists in an in vitro model of Huntington's disease

BACKGROUND AND PURPOSE

The therapeutic potential of cannabinoids in Huntington's disease (HD) has been investigated by several groups with complex and sometimes contrasting results. We sought to examine key points of intersection between cannabinoid receptor 1 (CB(1)) signalling, survival and the formation of mutant huntingtin aggregates in HD.

EXPERIMENTAL APPROACH

Using a simplified pheochromocytoma (PC12) cell model of HD expressing exon 1 of wild-type or mutant huntingtin, we assayed cell death and aggregate formation using high-throughput cytotoxicity and image-based assays respectively.

KEY RESULTS

CB(1) activation by HU210 conferred a small but significant level of protection against mutant huntingtin-induced cell death. Pertussis toxin uncoupled HU210 from the inhibition of cAMP, preventing rescue of cell death. Phosphorylation of extracellular signal-regulated kinase (ERK) was also critical to CB(1)-mediated rescue. Conversely, treatments that elevated cAMP exacerbated mutant huntingtin-induced cell death. Despite opposing effects on HD cell survival, both HU210 and compounds that elevated cAMP increased the formation of mutant huntingtin aggregates. The increase in aggregation by HU210 was insensitive to Pertussis toxin and UO126, suggesting a G-protein alpha subtype s (G(s))-linked mechanism.

CONCLUSIONS AND IMPLICATIONS

We suggest that the CB(1) receptor, through G-protein alpha subtype i/o (G(i/o))-linked, ERK-dependent signal transduction, is a therapeutic target in HD. However the protective potential of CB(1) may be limited by promiscuous coupling to G(s), the stimulation of cAMP formation and increased aggregate formation. This may underpin the poor therapeutic efficacy of cannabinoids in more complex model systems and suggest that therapies that are selective for the G(i/o), ERK pathway may be of most benefit in HD.

Quantifying biomolecule diffusivity using an optimal Bayesian method

We propose a Bayesian method to extract the diffusivity of biomolecules evolving freely or inside membrane microdomains. This approach assumes a model of motion for the particle considered, namely free Brownian motion or confined diffusion. In each framework, a systematic Bayesian scheme is provided for estimating the diffusivity. We show that this method reaches the best performances theoretically achievable. Its efficiency overcomes that of widely used methods based on the analysis of the mean-square displacement. The approach presented here also gives direct access to the uncertainty on the estimation of the diffusivity and predicts the number of steps of the trajectory necessary to achieve any desired precision. Its robustness with respect to noise on the position of the biomolecule is also investigated.

Formation and dissociation of M1 muscarinic receptor dimers seen by total internal reflection fluorescence imaging of single molecules

G-protein-coupled receptors (GPCRs) are the largest family of transmembrane signaling proteins in the human genome. Events in the GPCR signaling cascade have been well characterized, but the receptor composition and its membrane distribution are still generally unknown. Although there is evidence that some members of the GPCR superfamily exist as constitutive dimers or higher oligomers, interpretation of the results has been disputed, and recent studies indicate that monomeric GPCRs may also be functional. Because there is controversy within the field, to address the issue we have used total internal reflection fluorescence microscopy (TIRFM) in living cells to visualize thousands of individual molecules of a model GPCR, the M(1) muscarinic acetylcholine receptor. By tracking the position of individual receptors over time, their mobility, clustering, and dimerization kinetics could be directly determined with a resolution of approximately 30 ms and approximately 20 nm. In isolated CHO cells, receptors are randomly distributed over the plasma membrane. At any given time, approximately 30% of the receptor molecules exist as dimers, and we found no evidence for higher oligomers. Two-color TIRFM established the dynamic nature of dimer formation with M(1) receptors undergoing interconversion between monomers and dimers on the timescale of seconds.

A hidden Markov model for single particle tracks quantifies dynamic interactions between LFA-1 and the actin cytoskeleton

The extraction of hidden information from complex trajectories is a continuing problem in single-particle and single-molecule experiments. Particle trajectories are the result of multiple phenomena, and new methods for revealing changes in molecular processes are needed. We have developed a practical technique that is capable of identifying multiple states of diffusion within experimental trajectories. We model single particle tracks for a membrane-associated protein interacting with a homogeneously distributed binding partner and show that, with certain simplifying assumptions, particle trajectories can be regarded as the outcome of a two-state hidden Markov model. Using simulated trajectories, we demonstrate that this model can be used to identify the key biophysical parameters for such a system, namely the diffusion coefficients of the underlying states, and the rates of transition between them. We use a stochastic optimization scheme to compute maximum likelihood estimates of these parameters. We have applied this analysis to single-particle trajectories of the integrin receptor lymphocyte function-associated antigen-1 (LFA-1) on live T cells. Our analysis reveals that the diffusion of LFA-1 is indeed approximately two-state, and is characterized by large changes in cytoskeletal interactions upon cellular activation.

Time series analysis of particle tracking data for molecular motion on the cell membrane

Biophysicists use single particle tracking (SPT) methods to probe the dynamic behavior of individual proteins and lipids in cell membranes. The mean squared displacement (MSD) has proven to be a powerful tool for analyzing the data and drawing conclusions about membrane organization, including features like lipid rafts, protein islands, and confinement zones defined by cytoskeletal barriers. Here, we implement time series analysis as a new analytic tool to analyze further the motion of membrane proteins. The experimental data track the motion of 40 nm gold particles bound to Class I major histocompatibility complex (MHCI) molecules on the membranes of mouse hepatoma cells. Our first novel result is that the tracks are significantly autocorrelated. Because of this, we developed linear autoregressive models to elucidate the autocorrelations. Estimates of the signal to noise ratio for the models show that the autocorrelated part of the motion is significant. Next, we fit the probability distributions of jump sizes with four different models. The first model is a general Weibull distribution that shows that the motion is characterized by an excess of short jumps as compared to a normal random walk. We also fit the data with a chi distribution which provides a natural estimate of the dimension d of the space in which a random walk is occurring. For the biological data, the estimates satisfy 1 < d < 2, implying that particle motion is not confined to a line, but also does not occur freely in the plane. The dimension gives a quantitative estimate of the amount of nanometer scale obstruction met by a diffusing molecule. We introduce a new distribution and use the generalized extreme value distribution to show that the biological data also have an excess of long jumps as compared to normal diffusion. These fits provide novel estimates of the microscopic diffusion constant. Previous MSD analyses of SPT data have provided evidence for nanometer-scale confinement zones that restrict lateral diffusion, supporting the notion that plasma membrane organization is highly structured. Our demonstration that membrane protein motion is autocorrelated and is characterized by an excess of both short and long jumps reinforces the concept that the membrane environment is heterogeneous and dynamic. Autocorrelation analysis and modeling of the jump distributions are powerful new techniques for the analysis of SPT data and the development of more refined models of membrane organization. The time series analysis also provides several methods of estimating the diffusion constant in addition to the constant provided by the mean squared displacement. The mean squared displacement for most of the biological data shows a power law behavior rather the linear behavior of Brownian motion. In this case, we introduce the notion of an instantaneous diffusion constant. All of the diffusion constants show a strong consistency for most of the biological data.

Membrane functional organisation and dynamic of mu-opioid receptors

The activation and signalling activity of the membrane mu-opioid receptor (MOP-R) involve interactions among the receptor, G-proteins, effectors and many other membrane or cytosolic proteins. Decades of investigation have led to identification of the main biochemical processes, but the mechanisms governing the successive protein-protein interactions have yet to be established. We will need to unravel the dynamic membrane organisation of this complex and multifaceted molecular machinery if we are to understand these mechanisms. Here, we review and discuss advances in our understanding of the signalling mechanism of MOP-R resulting from biochemical or biophysical studies of the organisation of this receptor in the plasma membrane.

Molecular simulation of protein dynamics in nanopores. II. Diffusion

A novel combination of discontinuous molecular dynamics and the Langevin equation, together with an intermediate-resolution model of proteins, is used to carry out long (several microsecond) simulations in order to study transport of proteins in nanopores. We simulated single-domain proteins with the alpha-helical native structure. Both attractive and repulsive interaction potentials between the proteins and the pores' walls are considered. The diffusivity D of the proteins is computed not only under the bulk conditions but also as a function of their "length" (the number of the amino-acid groups), temperature T, pore size, and interaction potentials with the walls. Compared with the experimental data, the computed diffusivities under the bulk conditions are of the correct order of magnitude. The diffusivities both in the bulk and in the pores follow a power law in the length [script-l] of the proteins and are larger in pores with repulsive walls. D(+)/D(-), the ratio of the diffusivities in pores with attractive and repulsive walls, exhibits two local maxima in its dependence on the pore size h, which are attributed to the pore sizes and protein configurations that induce long-lasting simultaneous interactions with both walls of the pores. Far from the folding temperature T(f), D increases about linearly with T, but due to the thermal fluctuations and their effect on the proteins' structure near T(f), the dependence of D on T in this region is nonlinear. We propose a novel and general "phase diagram," consisting of four regions, that describes qualitatively the effect of h, T, and interaction potentials with the walls on the diffusivity D of a protein.

Quantitative microscopy: protein dynamics and membrane organisation

The mobility of membrane proteins is a critical determinant of their interaction capabilities and protein functions. The heterogeneity of cell membranes imparts different types of motion onto proteins; immobility, random Brownian motion, anomalous sub-diffusion, 'hop' or confined diffusion, or directed flow. Quantifying the motion of proteins therefore enables insights into the lateral organisation of cell membranes, particularly membrane microdomains with high viscosity such as lipid rafts. In this review, we examine the hypotheses and findings of three main techniques for analysing protein dynamics: fluorescence recovery after photobleaching, single particle tracking and fluorescence correlation spectroscopy. These techniques, and the physical models employed in data analysis, have become increasingly sophisticated and provide unprecedented details of the biophysical properties of protein dynamics and membrane domains in cell membranes. Yet despite these advances, there remain significant unknowns in the relationships between cholesterol-dependent lipid microdomains, protein-protein interactions, and the effect of the underlying cytoskeleton. New multi-dimensional microscopy approaches may afford greater temporal and spatial resolution resulting in more accurate quantification of protein and membrane dynamics in live cells.

Dynamic partitioning of a glycosyl-phosphatidylinositol-anchored protein in glycosphingolipid-rich microdomains imaged by single-quantum dot tracking

Recent experimental developments have led to a revision of the classical fluid mosaic model proposed by Singer and Nicholson more than 35 years ago. In particular, it is now well established that lipids and proteins diffuse heterogeneously in cell plasma membranes. Their complex motion patterns reflect the dynamic structure and composition of the membrane itself, as well as the presence of the underlying cytoskeleton scaffold and that of the extracellular matrix. How the structural organization of plasma membranes influences the diffusion of individual proteins remains a challenging, yet central, question for cell signaling and its regulation. Here we have developed a raft-associated glycosyl-phosphatidyl-inositol-anchored avidin test probe (Av-GPI), whose diffusion patterns indirectly report on the structure and dynamics of putative raft microdomains in the membrane of HeLa cells. Labeling with quantum dots (qdots) allowed high-resolution and long-term tracking of individual Av-GPI and the classification of their various diffusive behaviors. Using dual-color total internal reflection fluorescence (TIRF) microscopy, we studied the correlation between the diffusion of individual Av-GPI and the location of glycosphingolipid GM1-rich microdomains and caveolae. We show that Av-GPI exhibit a fast and a slow diffusion regime in different membrane regions, and that slowing down of their diffusion is correlated with entry in GM1-rich microdomains located in close proximity to, but distinct, from caveolae. We further show that Av-GPI dynamically partition in and out of these microdomains in a cholesterol-dependent manner. Our results provide direct evidence that cholesterol-/sphingolipid-rich microdomains can compartmentalize the diffusion of GPI-anchored proteins in living cells and that the dynamic partitioning raft model appropriately describes the diffusive behavior of some raft-associated proteins across the plasma membrane.

Diffusion in a fluid membrane with a flexible cortical cytoskeleton

We calculate the influence of a flexible network of long-chain proteins, which is anchored to a fluid membrane, on protein diffusion in this membrane. This is a model for the cortical cytoskeleton and the lipid bilayer of the red blood cell, which we apply to predict the influence of the cytoskeleton on the diffusion coefficient of a mobile band 3 protein. Using the pressure field that the cytoskeleton exerts on the membrane, from the steric repulsion between the diffusing protein and the cytoskeletal filaments, we define a potential landscape for the diffusion within the bilayer. We study the changes to the diffusion coefficient on removal of one type of anchor proteins, e.g., in several hemolytic anemias, as well as for isotropic and anisotropic stretching of the cytoskeleton. We predict an overall increase of the diffusion for a smaller number of anchor proteins and increased diffusion for anisotropic stretching in the direction of the stretch, because of the decrease in the spatial frequency as well as in the height of the potential barriers.

Single molecule tracking of quantum dot-labeled mRNAs in a cell nucleus

Single particle tracking (SPT) is a powerful technique for studying mRNA dynamics in cells. Although SPT of mRNA has been performed by labeling mRNA with fluorescent dyes or proteins, observation of mRNA for long durations with high temporal resolution has been difficult due to weak fluorescence and rapid photobleaching. Using quantum dots (QDs), we succeeded in observing the movement of individual mRNAs for more than 60 s, with a temporal resolution of 30 ms. Intronless and truncated ftz mRNA, synthesized in vitro and labeled with QDs, was microinjected into the nuclei of Cos7 cells. Almost all mRNAs were in motion, and statistical analyses revealed anomalous diffusion between barriers, with a microscopic diffusion coefficient of 0.12 microm2/s and a macroscopic diffusion coefficient of 0.025 microm2/s. Diffusion of mRNA was observed in interchromatin regions but not in histone2B-GFP-labeled chromatin regions. These results provide direct evidence of channeled mRNA diffusion in interchromatin regions.

Inferring maps of forces inside cell membrane microdomains

Mapping of the forces on biomolecules in cell membranes has spurred the development of effective labels, e.g., organic fluorophores and nanoparticles, to track trajectories of single biomolecules. Standard methods use particular statistics, namely the mean square displacement, to analyze the underlying dynamics. Here, we introduce general inference methods to fully exploit information in the experimental trajectories, providing sharp estimates of the forces and the diffusion coefficients in membrane microdomains. Rapid and reliable convergence of the inference scheme is demonstrated on trajectories generated numerically. The method is then applied to infer forces and potentials acting on the receptor of the toxin labeled by lanthanide-ion nanoparticles. Our scheme is applicable to any labeled biomolecule and results show its general relevance for membrane compartmentation.

Collision coupling, crosstalk, and compartmentalization in G-protein coupled receptor systems: can a single model explain disparate results?

The collision coupling model describes interactions between receptors and G-proteins as first requiring the molecules to find each other by diffusion. A variety of experimental data on G-protein activation have been interpreted as suggesting (or not) the compartmentalization of receptors and/or G-proteins in addition to a collision coupling mechanism. In this work, we use a mathematical model of G-protein activation via collision coupling but without compartmentalization to demonstrate that these disparate observations do not imply the existence of such compartments. In experiments with GTP analogs (commonly GTPgammaS), the extent of G-protein activation is predicted to be a function of both receptor number and the rate of GTP analog hydrolysis. The sensitivity of G-protein activation to receptor number is shown to be dependent upon the assay used, with the sensitivity of phosphate production assays (GTPase) >GTPgammaS-binding assays >cAMP inhibition assays. Finally, the amount of competition or crosstalk between receptor species activating the same type of G-proteins is predicted to depend on receptor and G-protein number, but in some (common) experimental regimes this dependence is expected to be minimal. Taken together, these observations suggest that the collision coupling model, without compartments of receptors and/or G-proteins, is sufficient to explain a variety of observations in literature data.

What do diffusion measurements tell us about membrane compartmentalisation? Emergence of the role of interprotein interactions

The techniques of diffusion analysis based on optical microscopy approaches have revealed a great diversity of the dynamic organisation of cell membranes. For a long period, two frameworks have dominated the way of representing the membrane structure: the membrane skeleton fences and the lipid raft models. Progresses in the methods of data analysis have shed light on the features and consequently the possible origin of membrane domains: Inter-protein interactions play a role in confinement. Innovative developments pushing forward the spatiotemporal resolution limits are currently emerging, which are likely to provide in the future a detailed understanding of the intimate functional dynamic organisation of the cell membrane.

Actin restricts FcepsilonRI diffusion and facilitates antigen-induced receptor immobilization

The actin cytoskeleton has been implicated in restricting diffusion of plasma membrane components. Here, simultaneous observations of quantum dot-labelled FcepsilonRI motion and GFP-tagged actin dynamics provide direct evidence that actin filament bundles define micron-sized domains that confine mobile receptors. Dynamic reorganization of actin structures occurs over seconds, making the location and dimensions of actin-defined domains time-dependent. Multiple FcepsilonRI often maintain extended close proximity without detectable correlated motion, suggesting that they are co-confined within membrane domains. FcepsilonRI signalling is activated by crosslinking with multivalent antigen. We show that receptors become immobilized within seconds of crosslinking. Disruption of the actin cytoskeleton results in delayed immobilization kinetics and increased diffusion of crosslinked clusters. These results implicate actin in membrane partitioning that not only restricts diffusion of membrane proteins, but also dynamically influences their long-range mobility, sequestration and response to ligand binding.

Theory of fluorescence correlation spectroscopy at variable observation area for two-dimensional diffusion on a meshgrid

It has recently been proposed, with the help of numerical investigations, that fluorescence correlation spectroscopy at variable observation area can reveal the existence of a meshgrid of semi-permeable barriers hindering the two-dimensional diffusion of tagged particles, such as plasmic membrane constituents. We present a complete theory confirming and accounting for these findings. It enables a reliable, quantitative exploitation of experimental data from which the sub-wavelength mesh size can be extracted. Time-scales at which fluorescence correlation spectroscopy must be performed experimentally are discussed in detail.

High-Resolution Models of Motion of Macromolecules in Cell Membranes

The path of a macromolecule on a cell membrane is modeled by a sum of independent identically distributed random variables. Random variables with simple discrete distribution functions capture some important aspects of the jump or hop diffusion reported from single particle tracking experiments that measure the motion of single molecules on a cell membrane. The detail provided by the distribution function for the random variables is critical for accurate simulations of the motion and interactions of macromolecules on the cell membrane. Additionally, the probability distribution for the random variables is easily estimated from single-particle tracking data. The diffusion constant is given by the second moment of the probability distribution, which agrees with the diffusion constant estimated from the mean-square displacement, and thus represents far less information than the distribution function.

Dynamics of single potassium channel proteins in the plasma membrane of migrating cells

Cell migration is an important physiological process among others controlled by ion channel activity. Calcium-activated potassium channels (K(Ca)3.1) are required for optimal cell migration. Previously, we identified single human (h)K(Ca)3.1 channel proteins in the plasma membrane by means of quantum dot (QD) labeling. In the present study, we tracked single-channel proteins during migration to classify their dynamics in the plasma membrane of MDCK-F cells. Single hK(Ca)3.1 channels were visualized with QD- or Alexa488-conjugated antibodies and tracked at the basal cell membrane using time-lapse total internal reflection fluorescence (TIRF) microscopy. Analysis of the trajectories allowed the classification of channel dynamics. Channel tracks were compared with those of free QD-conjugated antibodies. The size of the label has a pronounced effect on hK(Ca)3.1 channel diffusion. QD-labeled channels have a (sub)diffusion coefficient D(QDbound) = 0.067 microm(2)/s(alpha), whereas that of Alexa488-labeled channels is D(Alexa) = 0.139 microm(2)/s. Free QD-conjugated antibodies move much faster: D(QDfree) = 2.163 microm(2)/s(alpha). Plotting the mean squared distances (msd) covered by hK(Ca)3.1 channels as a function of time points to the mode of diffusion. Alexa488-labeled channels diffuse normally, whereas the QD-label renders hK(Ca)3.1 channel diffusion anomalous. Free QD-labeled antibodies also diffuse anomalously. Hence, QDs slow down diffusion of hK(Ca)3.1 channels and change the mode of diffusion. These results, referring to the role of label size and properties of the extracellular environment, suggest that the pericellular glycocalyx has an important impact on labels used for single molecule tracking. Thus tracking fluorescent particles within the glycocalyx opens up a possibility to characterize the pericellular nanoenvironment.

Cluster phases of membrane proteins

A physical scenario accounting for the existence of size-limited submicrometric domains in cell membranes is proposed. It is based on the numerical investigation of the counterpart, in lipidic membranes where proteins are diffusing, of the recently discovered cluster phases in colloidal suspensions. I demonstrate that the interactions between proteins, namely, short-range attraction and longer-range repulsion, make possible the existence of stable small clusters. The consequences are explored in terms of membrane organization and diffusion properties. The connection with lipid rafts is discussed, and the apparent protein diffusion coefficient as a function of their concentration is analyzed.

Statistical analysis of sets of random walks: how to resolve their generating mechanism

The analysis of experimental random walks aims at identifying the process(es) that generate(s) them. It is in general a difficult task, because statistical dispersion within an experimental set of random walks is a complex combination of the stochastic nature of the generating process, and the possibility to have more than one simple process. In this paper, we study by numerical simulations how the statistical distribution of various geometric descriptors such as the second, third and fourth order moments of two-dimensional random walks depends on the stochastic process that generates that set. From these observations, we derive a method to classify complex sets of random walks, and resolve the generating process(es) by the systematic comparison of experimental moment distributions with those numerically obtained for candidate processes. In particular, various processes such as Brownian diffusion combined with convection, noise, confinement, anisotropy, or intermittency, can be resolved by using high order moment distributions. In addition, finite-size effects are observed that are useful for treating short random walks. As an illustration, we describe how the present method can be used to study the motile behavior of epithelial microvilli. The present work should be of interest in biology for all possible types of single particle tracking experiments.