Probing membrane protein interactions with their lipid raft environment using single-molecule tracking and Bayesian inference analysis

Confinement energy landscape classification reveals membrane receptor nano-organization mechanisms

The cell membrane organization has an essential functional role through the control of membrane receptor confinement in micro- or nanodomains. Several mechanisms have been proposed to account for these properties, although some features have remained controversial, notably the nature, size, and stability of cholesterol- and sphingolipid-rich domains or lipid rafts. Here, we probed the effective energy landscape acting on single-nanoparticle-labeled membrane receptors confined in raft nanodomains- epidermal growth factor receptor (EGFR), Clostridium perfringens ε-toxin receptor (CPεTR), and Clostridium septicum α-toxin receptor (CSαTR)-and compared it with hop-diffusing transferrin receptors. By establishing a new analysis pipeline combining Bayesian inference, decision trees, and clustering approaches, we systematically classified single-protein trajectories according to the type of effective confining energy landscape. This revealed the existence of only two distinct organization modalities: confinement in a quadratic energy landscape for EGFR, CPεTR, and CSαTR (A), and free diffusion in confinement domains resulting from the steric hindrance due to F-actin barriers for transferrin receptor (B). The further characterization of effective confinement energy landscapes by Bayesian inference revealed the role of interactions with the domain environment in cholesterol- and sphingolipid-rich domains with (EGFR) or without (CPεTR and CSαTR) interactions with F-actin to regulate the confinement energy depth. These two distinct mechanisms result in the same organization type (A). We revealed that the apparent domain sizes for these receptor trajectories resulted from Brownian exploration of the energy landscape in a steady-state-like regime at a common effective temperature, independently of the underlying molecular mechanisms. These results highlight that confinement domains may be adequately described as interaction hotspots rather than rafts with abrupt domain boundaries. Altogether, these results support a new model for functional receptor confinement in membrane nanodomains and pave the way to the constitution of an atlas of membrane protein organization.

Errors in Energy Landscapes Measured with Particle Tracking

Tracking Brownian particles is often employed to map the energy landscape they explore. Such measurements have been exploited to study many biological processes and interactions in soft materials. Yet video tracking is irremediably contaminated by localization errors originating from two imaging artifacts: the "static" errors come from signal noise, and the "dynamic" errors arise from the motion blur due to finite frame-acquisition time. We show that these errors result in systematic and nontrivial biases in the measured energy landscapes. We derive a relationship between the true and the measured potential that elucidates, among other aberrations, the presence of false double-well minima in the apparent potentials reported in recent studies. We further assess several canonical trapping and pair-interaction potentials by using our analytically derived results and Brownian dynamics simulations. In particular, we show that the apparent spring stiffness of harmonic potentials (such as optical traps) is increased by dynamic errors but decreased by static errors. Our formula allows for the development of efficient corrections schemes, and we also present in this work a provisional method for reconstructing true potentials from the measured ones.

Controlling transmembrane protein concentration and orientation in supported lipid bilayers

The trans-membrane protein - proteorhodopsin (pR) has been incorporated into supported lipid bilayers (SLB). In-plane electric fields have been used to manipulate the orientation and concentration of these proteins, within the SLB, through electrophoresis leading to a 25-fold increase concentration of pR.

A Primer on the Bayesian Approach to High-Density Single-Molecule Trajectories Analysis

Tracking single molecules in living cells provides invaluable information on their environment and on the interactions that underlie their motion. New experimental techniques now permit the recording of large amounts of individual trajectories, enabling the implementation of advanced statistical tools for data analysis. In this primer, we present a Bayesian approach toward treating these data, and we discuss how it can be fruitfully employed to infer physical and biochemical parameters from single-molecule trajectories.

Integrative Analysis of Subcellular Quantitative Proteomics Studies Reveals Functional Cytoskeleton Membrane-Lipid Raft Interactions in Cancer

Lipid rafts are dynamic membrane microdomains that orchestrate molecular interactions and are implicated in cancer development. To understand the functions of lipid rafts in cancer, we performed an integrated analysis of quantitative lipid raft proteomics data sets modeling progression in breast cancer, melanoma, and renal cell carcinoma. This analysis revealed that cancer development is associated with increased membrane raft-cytoskeleton interactions, with ∼40% of elevated lipid raft proteins being cytoskeletal components. Previous studies suggest a potential functional role for the raft-cytoskeleton in the action of the putative tumor suppressors PTRF/Cavin-1 and Merlin. To extend the observation, we examined lipid raft proteome modulation by an unrelated tumor suppressor opioid binding protein cell-adhesion molecule (OPCML) in ovarian cancer SKOV3 cells. In agreement with the other model systems, quantitative proteomics revealed that 39% of OPCML-depleted lipid raft proteins are cytoskeletal components, with microfilaments and intermediate filaments specifically down-regulated. Furthermore, protein-protein interaction network and simulation analysis showed significantly higher interactions among cancer raft proteins compared with general human raft proteins. Collectively, these results suggest increased cytoskeleton-mediated stabilization of lipid raft domains with greater molecular interactions as a common, functional, and reversible feature of cancer cells.

Exploring in vivo cholesterol-mediated interactions between activated EGF receptors in plasma membrane with single-molecule optical tracking

Background

The first step in many cellular signaling processes occurs at various types of receptors in the plasma membrane. Membrane cholesterol can alter these signaling pathways of living cells. However, the process in which the interaction of activated receptors is modulated by cholesterol remains unclear.

Methods

In this study, we measured single-molecule optical trajectories of epidermal growth factor receptors moving in the plasma membranes of two cancerous cell lines and one normal endothelial cell line. A stochastic model was developed and applied to identify critical information from single-molecule trajectories.

Results

We discovered that unliganded epidermal growth factor receptors may reside nearby cholesterol-riched regions of the plasma membrane and can move into these lipid domains when subjected to ligand binding. The amount of membrane cholesterol considerably affects the stability of correlated motion of activated epidermal growth factor receptors.

Conclusions

Our results provide single-molecule evidence of membrane cholesterol in regulating signaling receptors. Because the three cell lines used for this study are quite diverse, our results may be useful to shed light on the mechanism of cholesterol-mediated interaction between activated receptors in live cells.

Membrane Protein Mobility and Orientation Preserved in Supported Bilayers Created Directly from Cell Plasma Membrane Blebs

Membrane protein interactions with lipids are crucial for their native biological behavior, yet traditional characterization methods are often carried out on purified protein in the absence of lipids. We present a simple method to transfer membrane proteins expressed in mammalian cells to an assay-friendly, cushioned, supported lipid bilayer platform using cell blebs as an intermediate. Cell blebs, expressing either GPI-linked yellow fluorescent proteins or neon-green fused transmembrane P2X2 receptors, were induced to rupture on glass surfaces using PEGylated lipid vesicles, which resulted in planar supported membranes with over 50% mobility for multipass transmembrane proteins and over 90% for GPI-linked proteins. Fluorescent proteins were tracked, and their diffusion in supported bilayers characterized, using single molecule tracking and moment scaling spectrum (MSS) analysis. Diffusion was characterized for individual proteins as either free or confined, revealing details of the local lipid membrane heterogeneity surrounding the protein. A particularly useful result of our bilayer formation process is the protein orientation in the supported planar bilayer. For both the GPI-linked and transmembrane proteins used here, an enzymatic assay revealed that protein orientation in the planar bilayer results in the extracellular domains facing toward the bulk, and that the dominant mode of bleb rupture is via the "parachute" mechanism. Mobility, orientation, and preservation of the native lipid environment of the proteins using cell blebs offers advantages over proteoliposome reconstitution or disrupted cell membrane preparations, which necessarily result in significant scrambling of protein orientation and typically immobilized membrane proteins in SLBs. The bleb-based bilayer platform presented here is an important step toward integrating membrane proteomic studies on chip, especially for future studies aimed at understanding fundamental effects of lipid interactions on protein activity and the roles of membrane proteins in disease pathways.

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.

Single-virus force spectroscopy unravels molecular details of virus infection

Virus infection is a multistep process that has significant effects on the structure and function of both the virus and the host cell. The first steps of virus replication include cell binding, entry and release of the viral genome. Single-virus force spectroscopy (SVFS) has become a promising tool to understand the molecular details of those steps. SVFS data complemented by biochemical and biophysical, including theoretical modeling approaches provide valuable insights into molecular events that accompany virus infection. Properties of virus-cell interaction as well as structural alterations of the virus essential for infection can be investigated on a quantitative level. Here we review applications of SVFS to virus binding, structure and mechanics. We demonstrate that SVFS offers unexpected new insights not accessible by other methods.

Mapping the energy and diffusion landscapes of membrane proteins at the cell surface using high-density single-molecule imaging and Bayesian inference: application to the multiscale dynamics of glycine receptors in the neuronal membrane

Protein mobility is conventionally analyzed in terms of an effective diffusion. Yet, this description often fails to properly distinguish and evaluate the physical parameters (such as the membrane friction) and the biochemical interactions governing the motion. Here, we present a method combining high-density single-molecule imaging and statistical inference to separately map the diffusion and energy landscapes of membrane proteins across the cell surface at ~100 nm resolution (with acquisition of a few minutes). Upon applying these analytical tools to glycine neurotransmitter receptors at inhibitory synapses, we find that gephyrin scaffolds act as shallow energy traps (~3 kBT) for glycine neurotransmitter receptors, with a depth modulated by the biochemical properties of the receptor-gephyrin interaction loop. In turn, the inferred maps can be used to simulate the dynamics of proteins in the membrane, from the level of individual receptors to that of the population, and thereby, to model the stochastic fluctuations of physiological parameters (such as the number of receptors at synapses). Overall, our approach provides a powerful and comprehensive framework with which to analyze biochemical interactions in living cells and to decipher the multiscale dynamics of biomolecules in complex cellular environments.

Single YVO4:Eu nanoparticle emission spectra using direct Eu3+ ion excitation with a sum-frequency 465-nm solid-state laser

We report emission spectrum measurements on single YxEu(1-x)VO4 nanoparticles. The inhomogeneous widths of the emission peaks are identical for single nanoparticles and for ensembles of nanoparticles, while being broader than those of the bulk material. This indicates that individual nanoparticles are identical in terms of the distribution of different local Eu3+ sites due to crystalline defects and confirms their usability as identical, single-particle oxidant biosensors. Moreover, we report a 465 nm solid-state laser based on sum-frequency mixing that provides a compact, efficient solution for direct Eu3+ excitation of these nanoparticles. Both these two aspects should broaden the scope of Eu-doped nanoparticle applications.

Receptor displacement in the cell membrane by hydrodynamic force amplification through nanoparticles

We introduce an intrinsically multiplexed and easy to implement method to apply an external force to a biomolecule and thus probe its interaction with a second biomolecule or, more generally, its environment (for example, the cell membrane). We take advantage of the hydrodynamic interaction with a controlled fluid flow within a microfluidic channel to apply a force. By labeling the biomolecule with a nanoparticle that acts as a kite and increases the hydrodynamic interaction with the fluid, the drag induced by convection becomes important. We use this approach to track the motion of single membrane receptors, the Clostridium perfringens ε-toxin (CPεT) receptors that are confined in lipid raft platforms, and probe their interaction with the environment. Under external force, we observe displacements over distances up to 10 times the confining domain diameter due to elastic deformation of a barrier and return to the initial position after the flow is stopped. Receptors can also jump over such barriers. Analysis of the receptor motion characteristics before, during, and after a force is applied via the flow indicates that the receptors are displaced together with their confining raft platform. Experiments before and after incubation with latrunculin B reveal that the barriers are part of the actin cytoskeleton and have an average spring constant of 2.5 ± 0.6 pN/μm before vs. 0.6 ± 0.2 pN/μm after partial actin depolymerization. Our data, in combination with our previous work demonstrating that the ε-toxin receptor confinement is not influenced by the cytoskeleton, imply that it is the raft platform and its constituents rather than the receptor itself that encounters and deforms the barriers formed by the actin cytoskeleton.

Bayesian decision tree for the classification of the mode of motion in single-molecule trajectories

Membrane proteins move in heterogeneous environments with spatially (sometimes temporally) varying friction and with biochemical interactions with various partners. It is important to reliably distinguish different modes of motion to improve our knowledge of the membrane architecture and to understand the nature of interactions between membrane proteins and their environments. Here, we present an analysis technique for single molecule tracking (SMT) trajectories that can determine the preferred model of motion that best matches observed trajectories. The method is based on Bayesian inference to calculate the posteriori probability of an observed trajectory according to a certain model. Information theory criteria, such as the Bayesian information criterion (BIC), the Akaike information criterion (AIC), and modified AIC (AICc), are used to select the preferred model. The considered group of models includes free Brownian motion, and confined motion in 2nd or 4th order potentials. We determine the best information criteria for classifying trajectories. We tested its limits through simulations matching large sets of experimental conditions and we built a decision tree. This decision tree first uses the BIC to distinguish between free Brownian motion and confined motion. In a second step, it classifies the confining potential further using the AIC. We apply the method to experimental Clostridium Perfingens [Formula: see text]-toxin (CP[Formula: see text]T) receptor trajectories to show that these receptors are confined by a spring-like potential. An adaptation of this technique was applied on a sliding window in the temporal dimension along the trajectory. We applied this adaptation to experimental CP[Formula: see text]T trajectories that lose confinement due to disaggregation of confining domains. This new technique adds another dimension to the discussion of SMT data. The mode of motion of a receptor might hold more biologically relevant information than the diffusion coefficient or domain size and may be a better tool to classify and compare different SMT experiments.

Calibrating optical tweezers with Bayesian inference

We present a new method for calibrating an optical-tweezer setup that does not depend on input parameters and is less affected by systematic errors like drift of the setup. It is based on an inference approach that uses Bayesian probability to infer the diffusion coefficient and the potential felt by a bead trapped in an optical or magnetic trap. It exploits a much larger amount of the information stored in the recorded bead trajectory than standard calibration approaches. We demonstrate that this method outperforms the equipartition method and the power-spectrum method in input information required (bead radius and trajectory length) and in output accuracy.