Crowded Membranes Research Articles

Protein assembly in crowded membranes: Generating potential energy landscapes

Protein assembly in crowded membranes: Generating potential energy landscapes

Glycosylation and Crowded Membrane Effects on Influenza Neuraminidase Stability and Dynamics.

All protein simulations are conducted with varying degrees of simplification, oftentimes with unknown ramifications about how these simplifications affect the interpretability of the results. In this work, we investigated how protein glycosylation and lateral crowding effects modulate an array of properties characterizing the stability and dynamics of influenza neuraminidase. We constructed three systems: (1) glycosylated neuraminidase in a whole virion (i.e., crowded membrane) environment, (2) glycosylated neuraminidase in its own lipid bilayer, and (3) unglycosylated neuraminidase in its own lipid bilayer. We saw that glycans tend to stabilize the protein structure and reduce its conformational flexibility while restricting the solvent movement. Conversely, a crowded membrane environment encouraged exploration of the free energy landscape and a large-scale conformational change, while making the protein structure more compact. Understanding these effects informs what factors one must consider in attempting to recapture the desired level of physical accuracy.

Effects of Shape on Interaction Dynamics of Tetrahedral Nanoplastics and the Cell Membrane.

Cellular uptake of nanoplastics is instrumental in their environmental accumulation and transfer to humans through the food chain. Despite extensive studies using spherical plastic nanoparticles, the influence of the morphological characteristics of environmentally released nanoplastics is understudied. Using dissipative particle dynamics simulations, we modeled the interactions between a cell membrane and hydrophobic nanotetrahedra, which feature high shape anisotropy and large surface curvature seen for environmental nanoplastics. We observe robust uptake of nanotetrahedra with sharp vertices and edges by the lipid membrane. Two local energy minimum configurations of nanotetrahedra embedded in the membrane bilayer were identified for particles of large sizes. Further analysis of particle dynamics within the membrane shows that the two interaction states exhibit distinct translational and rotational dynamics in the directions normal and parallel to the plane of the membrane. The membrane confinement significantly arrests the out-of-plane motion, resulting in caged translation and subdiffusive rotation. While the in-plane diffusion remains Brownian, we find that the translational and rotational modes decouple from each other as the particle size increases. The rotational diffusion decreases by a greater extent compared to the translational diffusion, deviating from the continuum theory predictions. These results provide fundamental insights into the shape effect on the nanoparticle dynamics in crowded lipid membranes.

Disordered regions of respiratory supercomplexes offer new pathways for substrate channeling in crowded membranes.

Are protein supercomplexes biological redundancies or do they have a functional role? This question has been perplexing biophysicists and bioenergeticists for decades, especially on the significances in crowded environments. Now, cryo-EM has brought forth remarkable insights into the structures of supercomplexes, but functional relevance of their intrinsically disordered regions remains a mystery. First, using a combination of maximum entropy (MaxEnT)-guided molecular simulations with low-resolution cryo-EM data, we have resolved the disordered Qcr6 subunit of respiratory complex III (CIII). Second, porting this whole-CIII model into the crowded yeast CIII2CIV2 supercomplex, long-timescale Brownian Dynamics computations were performed. We found that the negative charge on the disordered region surprisingly cooperates with that of the anionic lipids in the mitochondrial membrane to attract a pool of complementary protein substrates in its vicinity. Third, we discovered how the transient fold of Qcr6 expedites directional diffusion of the substrates from CIII to CIV that simultaneously leverage the supercomplex architecture as well as the electrostatic environment of the membrane. A re-classification of the EM images based on our computational model have brought to light new density features that indeed describe the 2-dimensional dynamic of the substrate in crowded supercomplexes. Finally, using multisequence alignment via Alphafold2, mutations are designed to control the diffusivity of substrates by tuning the disorder of the protein surface, for future biochemical validation.

Single-molecule Diffusion and Assembly on Polymer-crowded Lipid Membranes.

Cellular membranes are highly crowded environments for biomolecular reactions and signaling. Yet, most in vitro experiments probing protein interaction with lipids employ naked bilayer membranes. Such systems lack the complexities of crowding by membrane-embedded proteins and glycans and exclude the associated volume effects encountered on cellular membrane surfaces. Also, the negatively charged glass surface onto which the lipid bilayers are formed prevents the free diffusion of transmembrane biomolecules. Here, we present a well-characterized polymer-lipid membrane as a mimic for crowded lipid membranes. This protocol utilizes polyethylene glycol (PEG)-conjugated lipids as a generalized approach for incorporating crowders into the supported lipid bilayer(SLB). First, a cleaning procedure of the microscopic slides and coverslips for performing single-molecule experiments is presented. Next, methods for characterizing the PEG-SLBs and performing single-molecule experiments of the binding, diffusion, and assembly of biomolecules using single-molecule tracking and photobleaching are discussed. Finally, this protocol demonstrates how to monitor the nanopore assembly of bacterial pore-forming toxin Cytolysin A (ClyA) on crowded lipid membranes with single-molecule photobleaching analysis. MATLAB codes with example datasets are also included to perform some of the common analyses such as particle tracking, extracting diffusive behavior, and subunit counting.

Annexin A4 trimers are recruited by high membrane curvatures in giant plasma membrane vesicles.

The plasma membrane (PM) of eukaryotic cells consists of a crowded environment comprised of a high diversity of proteins in a complex lipid matrix. The lateral organization of membrane proteins in the PM is closely correlated with biological functions such as endocytosis, membrane budding and other processes which involve protein mediated shaping of the membrane into highly curved structures. Annexin A4 (ANXA4) is a prominent player in a number of biological functions including PM repair. Its binding to membranes is activated by Ca2+ influx and it is therefore rapidly recruited to the cell surface near rupture sites where Ca2+ influx takes place. However, the free edges near rupture sites can easily bend into complex curvatures and hence may accelerate recruitment of curvature sensing proteins to facilitate rapid membrane repair. To analyze the curvature sensing behavior of curvature inducing proteins in crowded membranes, we quantifify the affinity of ANXA4 monomers and trimers for high membrane curvatures by extracting membrane nanotubes from giant PM vesicles (GPMVs). ANXA4 is found to be a sensor of negative membrane curvatures. Multiscale simulations, in which we extract molecular information from atomistic scale simulations as input to our macroscopic scale simulations, furthermore predicted that ANXA4 trimers generate membrane curvature upon binding and have an affinity for highly curved membrane regions only within a well defined membrane curvature window. Our results indicate that curvature sensing and mobility of ANXA4 depend on the trimer structure of ANXA4 which could provide new biophysical insight into the role of ANXA4 in membrane repair and other biological processes.

Subnanometer-resolution structure determination in situ by hybrid subtomogram averaging - single particle cryo-EM

Cryo-electron tomography combined with subtomogram averaging (StA) has yielded high-resolution structures of macromolecules in their native context. However, high-resolution StA is not commonplace due to beam-induced sample drift, images with poor signal-to-noise ratios (SNR), challenges in CTF correction, and limited particle number. Here we address these issues by collecting tilt series with a higher electron dose at the zero-degree tilt. Particles of interest are then located within reconstructed tomograms, processed by conventional StA, and then re-extracted from the high-dose images in 2D. Single particle analysis tools are then applied to refine the 2D particle alignment and generate a reconstruction. Use of our hybrid StA (hStA) workflow improved the resolution for tobacco mosaic virus from 7.2 to 4.4 Å and for the ion channel RyR1 in crowded native membranes from 12.9 to 9.1 Å. These resolution gains make hStA a promising approach for other StA projects aimed at achieving subnanometer resolution.

Rotational Diffusion of Membrane Proteins in Crowded Membranes.

Membrane proteins travel along cellular membranes and reorient themselves to form functional oligomers and protein-lipid complexes. Following the Saffman-Delbrück model, protein radius sets the rate of this diffusive motion. However, it is unclear how this model, derived for ideal and dilute membranes, performs under crowded conditions of cellular membranes. Here, we study the rotational motion of membrane proteins using molecular dynamics simulations of coarse-grained membranes and 2-dimensional Lennard-Jones fluids with varying levels of crowding. We find that the Saffman-Delbrück model captures the size-dependency of rotational diffusion under dilute conditions where protein-protein interactions are negligible, whereas stronger scaling laws arise under crowding. Together with our recent work on lateral diffusion, our results reshape the description of protein dynamics in native membrane environments: The translational and rotational motions of proteins with small transmembrane domains are rapid, whereas larger proteins or protein complexes display substantially slower dynamics.

Reconstitution of Respiratory Enzymes in PDMS-g-PEO Polymer and Polymer/Lipid Hybrid Vesicles

Mechanical characteristics (e.g. rigidity, tightness) of cellular compartments are alterable by partial or complete replacement of natural building blocks with synthetic alternatives, but often at the expense of other properties (e.g. fluidity, thickness). Since the scope of bottom-up synthetic biology aims to reconstitute essential life processes such as selective transport and energy transduction, we seek to retain properties of the interfaces, necessary for interaction with membrane proteins. PDMS-g-PEO polymer appears to accommodate these demands. Thus, we co-reconstituted the chemically-driven proton pump bo3 oxidase and F1Fo-ATPase in PDMS-g-PEO polymer and hybrid nanocompartments (LUVs) in order to build a synthetic energy conversion module. Successful scale-up to the micron-scale plays a crucial role in the real-time visualization and characterization of this module. Via an optimized fusion/electroformation approach we integrated bo3 oxidase in giant vesicles (GUVs) and determined its influence on mechanical properties. The reconstituted enzymes had preserved activity and exhibited unidirectional orientation, which led to the acidification of the synthetic compartments. The most remarkable finding is that the characteristics of hybrid membranes are not always intermediate between pure lipid- and pure polymer ones. Blending led to increased permeability, but after inserting the proton pump the compartments were surprisingly re-sealed. The measurements of active proton pumping and passive proton permeability were done in a microfluidic setup, which enabled monitoring of individual GUVs as well as better control of the experimental conditions. Moreover, we observed an interesting phenomenon beneficial for crowded membranes: While insertion of bo3 oxidase in soy PC decreased the fluidity, it exercised the opposite effect on the polymer by loosening its structure. The F1Fo-GUVs were prepared by the aforementioned procedure and the enzymatic activity was analyzed via outward proton pumping. Finally, respiratory-driven energy-converting GUVs were constructed. Sponsored by BMBF and MPG.

Non-universality of the dynamic exponent in two-dimensional random media

The diffusion of solutes in two-dimensional random media is important in diverse physical situations including the dynamics of proteins in crowded cell membranes and the adsorption on nano-structured substrates. It has generally been thought that the diffusion constant, D, should display universal behavior near the percolation threshold, i.e., D ~ (ϕ − ϕc)μ, where ϕ is the area fraction of the matrix, ϕc is the value of ϕ at the percolation threshold, and μ is the dynamic exponent. The universality of μ is important because it implies that very different processes, such as protein diffusion in membranes and the electrical conductivity in two-dimensional networks, obey similar underlying physical principles. In this work we demonstrate, using computer simulations on a model system, that the exponent μ is not universal, but depends on the microscopic nature of the dynamics. We consider a hard disc that moves via random walk in a matrix of fixed hard discs and show that μ depends on the maximum possible displacement Δ of the mobile hard disc, ranging from 1.31 at Δ ≤ 0.1 to 2.06 for relatively large values of Δ. We also show that this behavior arises from a power-law singularity in the distribution of transition rates due to a failure of the local equilibrium approximation. The non-universal value of μ obeys the prediction of the renormalization group theory. Our simulations do not, however, exclude the possibility that the non-universal values of μ might be a crossover between two different limiting values at very large and small values of Δ. The results allow one to rationalize experiments on diffusion in two-dimensional systems.

Investigating the Nanodomain Organization of Rhodopsin in Native Membranes by Atomic Force Microscopy.

Membrane proteins play an integral role in cellular communication. They are often organized within the crowded cell membrane into nanoscale domains (i.e., nanodomains), which facilitates their function in cell signaling processes. The visualization of membrane proteins and nanodomains within biological membranes under physiological conditions presents a challenge and is not possible using conventional microscopy methods. Atomic force microscopy (AFM) provides an opportunity to study the organization of membrane proteins within biological membranes with sub-nanometer resolution. An example of a membrane protein organized into nanodomains is rhodopsin. Rhodopsin is expressed in photoreceptor cells of the retina and upon photoactivation initiates a series of biochemical reactions called phototransduction, which represents the first steps of vision. AFM has provided an opportunity to directly visualize the packing of rhodopsin in native retinal membranes and the quantitative analysis of AFM images is beginning to reveal insights about the nanodomain organization of rhodopsin in the membrane. In this report, we outline procedures for imaging rhodopsin nanodomains by AFM and the quantitative analysis of those AFM images.

Excessive aggregation of membrane proteins in the Martini model.

The coarse-grained Martini model is employed extensively to study membrane protein oligomerization. While this approach is exceptionally promising given its computational efficiency, it is alarming that a significant fraction of these studies demonstrate unrealistic protein clusters, whose formation is essentially an irreversible process. This suggests that the protein–protein interactions are exaggerated in the Martini model. If this held true, then it would limit the applicability of Martini to study multi-protein complexes, as the rapidly clustering proteins would not be able to properly sample the correct dimerization conformations. In this work we first demonstrate the excessive protein aggregation by comparing the dimerization free energies of helical transmembrane peptides obtained with the Martini model to those determined from FRET experiments. Second, we show that the predictions provided by the Martini model for the structures of transmembrane domain dimers are in poor agreement with the corresponding structures resolved using NMR. Next, we demonstrate that the first issue can be overcome by slightly scaling down the Martini protein–protein interactions in a manner, which does not interfere with the other Martini interaction parameters. By preventing excessive, irreversible, and non-selective aggregation of membrane proteins, this approach renders the consideration of lateral dynamics and protein–lipid interactions in crowded membranes by the Martini model more realistic. However, this adjusted model does not lead to an improvement in the predicted dimer structures. This implicates that the poor agreement between the Martini model and NMR structures cannot be cured by simply uniformly reducing the interactions between all protein beads. Instead, a careful amino-acid specific adjustment of the protein–protein interactions is likely required.

Stress Propagation through Biological Lipid Bilayers in Silico.

Membrane tension plays various critical roles in the cell. We here asked how fast and how far localized pulses of mechanical stress dynamically propagate through biological lipid bilayers. In both coarse-grained and all-atom molecular dynamics simulations of a dipalmitoylphosphatidylcholine lipid bilayer, we observed nanometer-wide stress pulses, propagating very efficiently longitudinally at a velocity of approximately 1.4 ± 0.5 nm/ps (km/s), in close agreement with the expected speed of sound from experiments. Remarkably, the predicted characteristic attenuation time of the pulses was in the order of tens of picoseconds, implying longitudinal stress propagation over length scales up to several tens of nanometers before damping. Furthermore, the computed dispersion relation leading to such damping was consistent with proposed continuum viscoelastic models of propagation. We suggest this mode of stress propagation as a potential ultrafast mechanism of signaling that may quickly couple mechanosensitive elements in crowded biological membranes.

Stochastic lattice model of synaptic membrane protein domains.

Neurotransmitter receptor molecules, concentrated in synaptic membrane domains along with scaffolds and other kinds of proteins, are crucial for signal transmission across chemical synapses. In common with other membrane protein domains, synaptic domains are characterized by low protein copy numbers and protein crowding, with rapid stochastic turnover of individual molecules. We study here in detail a stochastic lattice model of the receptor-scaffold reaction-diffusion dynamics at synaptic domains that was found previously to capture, at the mean-field level, the self-assembly, stability, and characteristic size of synaptic domains observed in experiments. We show that our stochastic lattice model yields quantitative agreement with mean-field models of nonlinear diffusion in crowded membranes. Through a combination of analytic and numerical solutions of the master equation governing the reaction dynamics at synaptic domains, together with kinetic Monte Carlo simulations, we find substantial discrepancies between mean-field and stochastic models for the reaction dynamics at synaptic domains. Based on the reaction and diffusion properties of synaptic receptors and scaffolds suggested by previous experiments and mean-field calculations, we show that the stochastic reaction-diffusion dynamics of synaptic receptors and scaffolds provide a simple physical mechanism for collective fluctuations in synaptic domains, the molecular turnover observed at synaptic domains, key features of the observed single-molecule trajectories, and spatial heterogeneity in the effective rates at which receptors and scaffolds are recycled at the cell membrane. Our work sheds light on the physical mechanisms and principles linking the collective properties of membrane protein domains to the stochastic dynamics that rule their molecular components.

Membrane Crowding and Complexity: Interplay between Protein-Lipid Interactions, Clustering and Diffusion

It is well-understood that cell membranes are crowded and complex environments, containing up to 50 % protein by mass [1] and comprised of myriad types of lipid species [2]. Less well understood is the molecular detail of the effects of complexity and crowding on membrane organisation and dynamics. Advances in coarse-grained force fields and computational power mean that large-scale coarse-grained (CG) molecular dynamics (MD) simulations are increasingly being used to gain such understanding [3].To investigate the role of protein crowding and lipid complexity on the organisation and dynamics of mammalian cell membranes, and particularly the effect of protein-lipid interactions on protein and lipid diffusion in crowded membranes, we have performed large CG MD simulations containing over 100 inward rectifier potassium (Kir) channels, which have specific lipid interactions with PIP2, other anionic lipid interactions and cholesterol.Lipid complexity has a marked effect on the clustering behaviour of channels, underlying which are the diffusive properties of different lipid mixtures. Subdiffusion of lipids tightly interacting with Kir channels is also observed, and this subdiffusion is further modulated by protein crowding. By simulating Kir channels in a complex lipid mixture, we can also examine the interplay between PIP2, other anionic lipids and cholesterol interactions. In simulating systems of >100 nm in dimension whilst retaining membrane complexity at a molecular level, we start to move further towards the use of simulation as a computational microscope, and can assess the possibilities using this approach.1. Dupuy and Engelman. Proc Natl Acad Sci USA, 2008 105 (8): 2848–522. Coskun and Simons. Structure, 2011 19(11): 1543–48.3. Chavent, Duncan and Sansom. Curr Op Struct Biol, 2016. 40: 8–16

Stochastic single-molecule dynamics of synaptic membrane protein domains

Motivated by single-molecule experiments on synaptic membrane protein domains, we use a stochastic lattice model to study protein reaction and diffusion processes in crowded membranes. We find that the stochastic reaction-diffusion dynamics of synaptic proteins provide a simple physical mechanism for collective fluctuations in synaptic domains, the molecular turnover observed at synaptic domains, key features of the single-molecule trajectories observed for synaptic proteins, and spatially inhomogeneous protein lifetimes at the cell membrane. Our results suggest that central aspects of the single-molecule and collective dynamics observed for membrane protein domains can be understood in terms of stochastic reaction-diffusion processes at the cell membrane.

Stochastic Single-Molecule Dynamics of Synaptic Receptor Domains

Neurotransmitter receptor molecules, concentrated in postsynaptic membrane domains along with scaffold and other kinds of molecules, are crucial for signal transmission across chemical synapses. Using superresolution light microscopy it has been found that individual receptor molecules have very quick turnover rates of the order of seconds, while synaptic receptor domains are globally stable over months or even longer periods of time. Through an interplay between experiments on a minimal model system and theoretical modeling it has been demonstrated that the diffusion and reaction properties of receptors and scaffolds at the membrane are necessary and sufficient for the formation of stable receptor-scaffold domains of the characteristic size observed in nerve cells. However, existing theoretical models of synaptic receptor domains are limited to the mean-field level, and thus cannot account for the stochastic trajectories of individual synaptic molecules observed in experiments on nerve cells. Here we formulate and study a stochastic lattice gas model of synaptic receptor domains which allows us to overcome this challenge. Using kinetic Monte Carlo simulations we show that our stochastic lattice gas model reproduces the experimentally observed patterns of receptor-scaffold domains of a stable characteristic size, while also allowing for a coupling of reaction and diffusion noise to the nonlinear reaction and diffusion dynamics of receptors and scaffolds in the highly crowded membrane environments provided by synaptic domains. Our stochastic lattice gas model allows us to make detailed comparisons with experimental data on the stochastic properties of synaptic domains, and provides a bridge connecting the rapid and highly stochastic dynamics that rule the molecular realm of cell membranes to the global stability of synaptic receptor domains essential for the biological function of synapses.

The impact of physiological crowding on the diffusivity of membrane bound proteins.

Diffusion of transmembrane and peripheral membrane-bound proteins within the crowded cellular membrane environment is essential to diverse biological processes including cellular signaling, endocytosis, and motility. Nonetheless we presently lack a detailed understanding of the influence of physiological levels of crowding on membrane protein diffusion. Utilizing quantitative in vitro measurements, here we demonstrate that the diffusivities of membrane bound proteins follow a single linearly decreasing trend with increasing membrane coverage by proteins. This trend holds for homogenous protein populations across a range of protein sizes and for heterogeneous mixtures of proteins of different sizes, such that protein diffusivity is controlled by the total coverage of the surrounding membrane. These results demonstrate that steric exclusion within the crowded membrane environment can fundamentally limit the diffusive rate of proteins, regardless of their size. In cells this "speed limit" could be modulated by changes in local membrane coverage, providing a mechanism for tuning the rate of molecular interaction and assembly.

Molecular mechanism of cardiolipin-mediated assembly of respiratory chain supercomplexes.

Mitochondria produce most of the ATP consumed by cells through the respiratory chain in their inner membrane. This process involves protein complexes assembled into larger structures, the respiratory supercomplexes (SCs). Cardiolipin (CL), the mitochondrial signature phospholipid, is crucial for the structural and functional integrity of these SCs, but it is as yet unclear by what mechanism it operates. Our data disclose the mechanism for bulk CL in gluing SCs, steering their formation, and suggest how it may stabilize specific interfaces. We describe self-assembly molecular dynamics simulations of 9 cytochrome bc1 (CIII) dimers and 27 cytochrome c oxidase (CIV) monomers from bovine heart mitochondria embedded in a CL-containing model lipid bilayer, aimed at mimicking the crowdedness and complexity of mitochondrial membranes. The simulations reveal a large diversity of interfaces, including those of existing experimental CIII/CIV SC models and an alternative interface with CIV rotated by 180°. SC interfaces enclose 4 to 12 CLs, a ∼10 fold enrichment from the bulk. Half of these CLs glue complexes together using CL binding sites at the surface of both complexes. Free energy calculations demonstrate a larger CL binding strength, compared to other mitochondrial lipids, that is exclusive to these binding sites and results from non-additive electrostatic and van der Waals forces. This study provides a key example of the ability of lipids to selectively mediate protein-protein interactions by altering all ranges of forces, lubricate protein interfaces and act as traffic control agents steering proteins together.

Anomalous, non-Gaussian tracer diffusion in crowded two-dimensional environments

A topic of intense current investigation pursues the question of how the highly crowded environment of biological cells affects the dynamic properties of passively diffusing particles. Motivated by recent experiments we report results of extensive simulations of the motion of a finite sized tracer particle in a heterogeneously crowded environment made up of quenched distributions of monodisperse crowders of varying sizes in finite circular two-dimensional domains. For given spatial distributions of monodisperse crowders we demonstrate how anomalous diffusion with strongly non-Gaussian features arises in this model system. We investigate both biologically relevant situations of particles released either at the surface of an inner domain or at the outer boundary, exhibiting distinctly different features of the observed anomalous diffusion for heterogeneous distributions of crowders. Specifically we reveal an asymmetric spreading of tracers even at moderate crowding. In addition to the mean squared displacement (MSD) and local diffusion exponent we investigate the magnitude and the amplitude scatter of the time averaged MSD of individual tracer trajectories, the non-Gaussianity parameter, and the van Hove correlation function. We also quantify how the average tracer diffusivity varies with the position in the domain with a heterogeneous radial distribution of crowders and examine the behaviour of the survival probability and the dynamics of the tracer survival probability. Inter alia, the systems we investigate are related to the passive transport of lipid molecules and proteins in two-dimensional crowded membranes or the motion in colloidal solutions or emulsions in effectively two-dimensional geometries, as well as inside supercrowded, surface adhered cells.