Mechanisms of protein nanoscale clustering

Direct Imaging of Protein Clusters in Metal-Organic Frameworks

Protein@metal-organic frameworks (P@MOFs) prepared by coprecipitation of protein, metal ions, and organic ligands represent an effective method for protein stabilization with a wide spectrum of applications. However, the formation mechanism of P@MOFs via the coprecipitation process and the reason why proteins can retain their biological activity in the frameworks with highly concentrated metal ions remain unsettled. Here, by a combined methodology of single molecule localization microscopy and clustering analysis, we discovered that in this process enzyme molecules form clusters with metal ions and organic ligands, contributing to both the nucleation and subsequent crystal growth. We proposed that the clusters played an important role in the retention of overall enzymatic activity by sacrificing protein molecules on the cluster surface. This work offers fresh perspectives on protein behaviors in the formation of P@MOFs, inspiring future endeavors in the design and development of artificial bionanocomposites with high biological activities.

The ubiquitous nanocluster: A molecular scale organizing principle that governs cellular information flow

The language of biology at the scale of the cell is constituted of alphabets represented by biomolecules. These are stitched together in a variety of ways to create meaning. We argue that the phrases of this language are nanoscale molecular assemblies or nano-hubs for the purpose of information flow. At the cell surface information is sensed and processed via membrane receptors, often configured as multimers. These nano-assemblies serve as receiver nano-hubs, which are flexibly configured with additional nano-hubs that we term modifiers and transducers. This framework serves to process information that is transmitted for execution inside the cell. Here, we explore some examples about how nano-hubs are built and how they may contribute to cellular information flow.

Modulation of bacterial membrane proteins activity by clustering into plasma membrane nanodomains

Recent research has demonstrated specific protein clustering within membrane subdomains in bacteria, challenging the long-held belief that prokaryotes lack these subdomains. This mini review provides examples of bacterial membrane protein clustering, discussing the benefits of protein assembly in membranes and highlighting how clustering regulates protein activity.

Influenza A Virus Infection Alters Lipid Packing and Surface Electrostatic Potential of the Host Plasma Membrane

The pathogenesis of influenza A viruses (IAVs) is influenced by several factors, including IAV strain origin and reassortment, tissue tropism and host type. While such factors were mostly investigated in the context of virus entry, fusion and replication, little is known about the viral-induced changes to the host lipid membranes which might be relevant in the context of virion assembly. In this work, we applied several biophysical fluorescence microscope techniques (i.e., Förster energy resonance transfer, generalized polarization imaging and scanning fluorescence correlation spectroscopy) to quantify the effect of infection by two IAV strains of different origin on the plasma membrane (PM) of avian and human cell lines. We found that IAV infection affects the membrane charge of the inner leaflet of the PM. Moreover, we showed that IAV infection impacts lipid-lipid interactions by decreasing membrane fluidity and increasing lipid packing. Because of such alterations, diffusive dynamics of membrane-associated proteins are hindered. Taken together, our results indicate that the infection of avian and human cell lines with IAV strains of different origins had similar effects on the biophysical properties of the PM.

Metabolic glycan labeling immobilizes dendritic cell membrane and enhances antitumor efficacy of dendritic cell vaccine

Dendritic cell (DC) vaccine was among the first FDA-approved cancer immunotherapies, but has been limited by the modest cytotoxic T lymphocyte (CTL) response and therapeutic efficacy. Here we report a facile metabolic labeling approach that enables targeted modulation of adoptively transferred DCs for developing enhanced DC vaccines. We show that metabolic glycan labeling can reduce the membrane mobility of DCs, which activates DCs and improves the antigen presentation and subsequent T cell priming property of DCs. Metabolic glycan labeling itself can enhance the antitumor efficacy of DC vaccines. In addition, the cell-surface chemical tags (e.g., azido groups) introduced via metabolic glycan labeling also enable in vivo conjugation of cytokines onto adoptively transferred DCs, which further enhances CTL response and antitumor efficacy. Our DC labeling and targeting technology provides a strategy to improve the therapeutic efficacy of DC vaccines, with minimal interference upon the clinical manufacturing process.

Assembly Characterization of Human Equilibrium Nucleoside Transporter 1 (hENT1) by Inhibitor Probe-Based dSTORM Imaging

Nucleoside transporters (NTs) play an important role in the metabolism of nucleoside substances and the efficacy of nucleoside drugs. Its spatial information related to biofunctions at the single-molecule level remains unclear, owing to the limitation of the existing labeling methods and traditional imaging methods. Therefore, we synthesize the inhibitor-based fluorescent probe SAENTA-Cy5 and apply direct stochastic optical reconstruction microscopy (dSTORM) to conduct refined observation of human equilibrative nucleoside transporter 1 (hENT1), the most important and famous member of NTs. We first demonstrate the labeling specificity and superiority of SAENTA-Cy5 to the antibody probe. Then, we found different assembly patterns of hENT1 on the apical and basal membranes, which are further investigated to be caused by varying associations of membrane carbohydrates, membrane classical functional domains (lipid rafts), and associated membrane proteins (EpCAM). Our work provides an efficient method for labeling hENT1, which contributes to realize fine observation of NTs. The findings on the assembly features and potential assembly mechanism of hENT1 promote a better understanding of its biofunction, which facilitates further investigations on how NTs work in the metabolism of nucleoside and nucleoside analogues.

The Fluid-Mosaic model of cell membranes: A brief introduction, historical features, some general principles, and its adaptation to current information

The Fluid-Mosaic Membrane (FMM) model was originally proposed as a general, nanometer-scale representation of cell membranes (Singer and Nicolson, 1972). The FMM model was based on some general principles, such as thermodynamic considerations, intercalation of globular proteins into a lipid bilayer, independent protein and lipid dynamics, cooperativity and other characteristics. Other models had trimolecular structures or membrane globular lipoprotein units. These latter models were flawed, because they did not allow autonomous lipids, membrane domains or discrete lateral dynamics. The FMM model was also consistent with membrane asymmetry, cis- and trans-membrane linkages and associations of membrane components into multi-molecular complexes and domains. It has remained useful for explaining the basic organizational principles and properties of various biological membranes. New information has been added, such as membrane-associated cytoskeletal assemblies, extracellular matrix interactions, transmembrane controls, specialized lipid-protein domains that differ in compositions, rotational and lateral mobilities, lifetimes, functions, and other characteristics. The presence of dense, structured membrane domains has reduced significantly the extent of fluid-lipid membrane areas, and the FMM model is now considered to be more mosaic and dense than the original proposal.

A framework for evaluating the performance of SMLM cluster analysis algorithms

Single-molecule localization microscopy (SMLM) generates data in the form of coordinates of localized fluorophores. Cluster analysis is an attractive route for extracting biologically meaningful information from such data and has been widely applied. Despite a range of cluster analysis algorithms, there exists no consensus framework for the evaluation of their performance. Here, we use a systematic approach based on two metrics to score the success of clustering algorithms in simulated conditions mimicking experimental data. We demonstrate the framework using seven diverse analysis algorithms: DBSCAN, ToMATo, KDE, FOCAL, CAML, ClusterViSu and SR-Tesseler. Given that the best performer depended on the underlying distribution of localizations, we demonstrate an analysis pipeline based on statistical similarity measures that enables the selection of the most appropriate algorithm, and the optimized analysis parameters for real SMLM data. We propose that these standard simulated conditions, metrics and analysis pipeline become the basis for future analysis algorithm development and evaluation.

Lifetime of actin-dependent protein nanoclusters

Protein nanoclusters (PNCs) are dynamic collections of a few proteins that spatially organize in nanometer-length clusters. PNCs are one of the principal forms of spatial organization of membrane proteins, and they have been shown or hypothesized to be important in various cellular processes, including cell signaling. PNCs show remarkable diversity in size, shape, and lifetime. In particular, the lifetime of PNCs can vary over a wide range of timescales. The diversity in size and shape can be explained by the interaction of the clustering proteins with the actin cytoskeleton or the lipid membrane, but very little is known about the processes that determine the lifetime of the nanoclusters. In this paper, using mathematical modeling of the cluster dynamics, we model the biophysical processes that determine the lifetime of actin-dependent PNCs. In particular, we investigated the role of actin aster fragmentation, which had been suggested to be a key determinant of the PNC lifetime, and we found that it is important only for a small class of PNCs. A simple extension of our model allowed us to investigate the kinetics of protein-ligand interaction near PNCs. We found an anomalous increase in the lifetime of ligands near PNCs, which agrees remarkably well with experimental data on RAS-RAF kinetics. In particular, analysis of the RAS-RAF data through our model provides falsifiable predictions and novel hypotheses that will not only shed light on the role of RAS-RAF kinetics in various cancers, but also will be useful in studying membrane protein clustering in general.

Impact of sphingomyelin acyl chain heterogeneity upon properties of raft-like membranes

Sphingomyelin (SM) is a main component of lipid rafts and characteristic of abundance of long and saturated acyl chains. Recently, we reported that fluorescence-labeled lipids including C16:0 and C18:0SMs retained membrane behaviors of inherent lipids. Here, we newly prepared fluorescent SMs with longer acyl chains, C22:0 and C24:1, for observing their partition and diffusion in SM/cholesterol (chol)/dioleoylphosphatidylcholine (DOPC) bilayers. Although fluorescent C24:1SM underwent a uniform distribution between ordered (Lo) and disordered (Ld) phases, other fluorescent SMs with saturated acyl chains were preferentially distributed in the Lo phase. Interestingly, when the acyl chains of fluorescent and membrane SMs are different, distribution of fluorescent SM to the Lo phase was reduced compared to when the acyl chains are the same. This tendency was also observed for C16:0SM/C22:0SM/chol/DOPC quaternary bilayers, where the minor SM was more excluded out of the Lo phase than the major SM. We also found that the coexistence of SMs induces SM efflux out of the Lo phase and simultaneous DOPC influx to the Lo phase, consequently reducing the difference in fluidity between the two phases. These results suggest that physicochemical properties of lipid rafts are regulated by the acyl chain heterogeneity of SMs.

Biofunctional Nanodot Arrays in Living Cells Uncover Synergistic Co-Condensation of Wnt Signalodroplets

Qualitative and quantitative analysis of transient signaling platforms in the plasma membrane has remained a key experimental challenge. Here, biofunctional nanodot arrays (bNDAs) are developed to spatially control dimerization and clustering of cell surface receptors at the nanoscale. High-contrast bNDAs with spot diameters of ≈300 nm are obtained by capillary nanostamping of bovine serum albumin bioconjugates, which are subsequently biofunctionalized by reaction with tandem anti-green fluorescence protein (GFP) clamp fusions. Spatially controlled assembly of active Wnt signalosomes is achieved at the nanoscale in the plasma membrane of live cells by capturing the co-receptor Lrp6 into bNDAs via an extracellular GFP tag. Strikingly, co-recruitment is observed of co-receptor Frizzled-8 as well as the cytosolic scaffold proteins Axin-1 and Disheveled-2 into Lrp6 nanodots in the absence of ligand. Density variation and the high dynamics of effector proteins uncover highly cooperative liquid-liquid phase separation (LLPS)-driven assembly of Wnt "signalodroplets" at the plasma membrane, pinpointing the synergistic effects of LLPS for Wnt signaling amplification. These insights highlight the potential of bNDAs for systematically interrogating nanoscale signaling platforms and condensation at the plasma membrane of live cells.

Mass spectrometry and the cellular surfaceome

The collection of exposed plasma membrane proteins, collectively termed the surfaceome, is involved in multiple vital cellular processes, such as the communication of cells with their surroundings and the regulation of transport across the lipid bilayer. The surfaceome also plays key roles in the immune system by recognizing and presenting antigens, with its possible malfunctioning linked to disease. Surface proteins have long been explored as potential cell markers, disease biomarkers, and therapeutic drug targets. Despite its importance, a detailed study of the surfaceome continues to pose major challenges for mass spectrometry-driven proteomics due to the inherent biophysical characteristics of surface proteins. Their inefficient extraction from hydrophobic membranes to an aqueous medium and their lower abundance compared to intracellular proteins hamper the analysis of surface proteins, which are therefore usually underrepresented in proteomic datasets. To tackle such problems, several innovative analytical methodologies have been developed. This review aims at providing an extensive overview of the different methods for surfaceome analysis, with respective considerations for downstream mass spectrometry-based proteomics.

CD28 and chemokine receptors: Signalling amplifiers at the immunological synapse

T cells are master regulators of the immune response tuning, among others, B cells, macrophages and NK cells. To exert their functions requiring high sensibility and specificity, T cells need to integrate different stimuli from the surrounding microenvironment. A finely tuned signalling compartmentalization orchestrated in dynamic platforms is an essential requirement for the proper and efficient response of these cells to distinct triggers. During years, several studies have depicted the pivotal role of the cytoskeleton and lipid microdomains in controlling signalling compartmentalization during T cell activation and functions. Here, we discuss mechanisms responsible for signalling amplification and compartmentalization in T cell activation, focusing on the role of CD28, chemokine receptors and the actin cytoskeleton. We also take into account the detrimental effect of mutations carried by distinct signalling proteins giving rise to syndromes characterized by defects in T cell functionality.

Fifty Years of the Fluid–Mosaic Model of Biomembrane Structure and Organization and Its Importance in Biomedicine with Particular Emphasis on Membrane Lipid Replacement

The Fluid–Mosaic Model has been the accepted general or basic model for biomembrane structure and organization for the last 50 years. In order to establish a basic model for biomembranes, some general principles had to be established, such as thermodynamic assumptions, various molecular interactions, component dynamics, macromolecular organization and other features. Previous researchers placed most membrane proteins on the exterior and interior surfaces of lipid bilayers to form trimolecular structures or as lipoprotein units arranged as modular sheets. Such membrane models were structurally and thermodynamically unsound and did not allow independent lipid and protein lateral movements. The Fluid–Mosaic Membrane Model was the only model that accounted for these and other characteristics, such as membrane asymmetry, variable lateral movements of membrane components, cis- and transmembrane linkages and dynamic associations of membrane components into multimolecular complexes. The original version of the Fluid–Mosaic Membrane Model was never proposed as the ultimate molecular description of all biomembranes, but it did provide a basic framework for nanometer-scale biomembrane organization and dynamics. Because this model was based on available 1960s-era data, it could not explain all of the properties of various biomembranes discovered in subsequent years. However, the fundamental organizational and dynamic aspects of this model remain relevant to this day. After the first generation of this model was published, additional data on various structures associated with membranes were included, resulting in the addition of membrane-associated cytoskeletal, extracellular matrix and other structures, specialized lipid–lipid and lipid–protein domains, and other configurations that can affect membrane dynamics. The presence of such specialized membrane domains has significantly reduced the extent of the fluid lipid membrane matrix as first proposed, and biomembranes are now considered to be less fluid and more mosaic with some fluid areas, rather than a fluid matrix with predominantly mobile components. However, the fluid–lipid matrix regions remain very important in biomembranes, especially those involved in the binding and release of membrane lipid vesicles and the uptake of various nutrients. Membrane phospholipids can associate spontaneously to form lipid structures and vesicles that can fuse with various cellular membranes to transport lipids and other nutrients into cells and organelles and expel damaged lipids and toxic hydrophobic molecules from cells and tissues. This process and the clinical use of membrane phospholipid supplements has important implications for chronic illnesses and the support of healthy mitochondria, plasma membranes and other cellular membrane structures.

A coordinate-based co-localization index to quantify and visualize spatial associations in single-molecule localization microscopy

Visualizing the subcellular distribution of proteins and determining whether specific proteins co-localize is one of the main strategies in determining the organization and potential interactions of protein complexes in biological samples. The development of super-resolution microscopy techniques such as single-molecule localization microscopy (SMLM) has tremendously increased the ability to resolve protein distribution at nanometer resolution. As super-resolution imaging techniques are becoming instrumental in revealing novel biological insights, new quantitative approaches that exploit the unique nature of SMLM datasets are required. Here, we present a new, local density-based algorithm to quantify co-localization in dual-color SMLM datasets. We show that this method is broadly applicable and only requires molecular coordinates and their localization precision as inputs. Using simulated point patterns, we show that this method robustly measures the co-localization in dual-color SMLM datasets, independent of localization density, but with high sensitivity towards local enrichments. We further validated our method using SMLM imaging of the microtubule network in epithelial cells and used it to study the spatial association between proteins at neuronal synapses. Together, we present a simple and easy-to-use, but powerful method to analyze the spatial association of molecules in dual-color SMLM datasets.

A Brief Introduction to Some Aspects of the Fluid-Mosaic Model of Cell Membrane Structure and Its Importance in Membrane Lipid Replacement

Early cell membrane models placed most proteins external to lipid bilayers in trimolecular structures or as modular lipoprotein units. These thermodynamically untenable structures did not allow lipid lateral movements independent of membrane proteins. The Fluid-Mosaic Membrane Model accounted for these and other properties, such as membrane asymmetry, variable lateral mobilities of membrane components and their associations with dynamic complexes. Integral membrane proteins can transform into globular structures that are intercalated to various degrees into a heterogeneous lipid bilayer matrix. This simplified version of cell membrane structure was never proposed as the ultimate biomembrane description, but it provided a basic nanometer scale framework for membrane organization. Subsequently, the structures associated with membranes were considered, including peripheral membrane proteins, and cytoskeletal and extracellular matrix components that restricted lateral mobility. In addition, lipid-lipid and lipid-protein membrane domains, essential for cellular signaling, were proposed and eventually discovered. The presence of specialized membrane domains significantly reduced the extent of the fluid lipid matrix, so membranes have become more mosaic with some fluid areas over time. However, the fluid regions of membranes are very important in lipid transport and exchange. Various lipid globules, droplets, vesicles and other membranes can fuse to incorporate new lipids or expel damaged lipids from membranes, or they can be internalized in endosomes that eventually fuse with other internal vesicles and membranes. They can also be externalized in a reverse process and released as extracellular vesicles and exosomes. In this Special Issue, the use of membrane phospholipids to modify cellular membranes in order to modulate clinically relevant host properties is considered.

How Blinking Affects Photon Correlations in Multichromophoric Nanoparticles

A single chromophore can only emit a maximum of one single photon per excitation cycle. This limitation results in a phenomenon commonly referred to as photon antibunching (pAB). When multiple chromophores contribute to the fluorescence measured, the degree of pAB has been used as a metric to "count" the number of chromophores. But the fact that chromophores can switch randomly between bright and dark states also impacts pAB and can lead to incorrect chromophore numbers being determined from pAB measurements. By both simulations and experiment, we demonstrate how pAB is affected by independent and collective chromophore blinking, enabling us to formulate universal guidelines for correct interpretation of pAB measurements. We use DNA-origami nanostructures to design multichromophoric model systems that exhibit either independent or collective chromophore blinking. Two approaches are presented that can distinguish experimentally between these two blinking mechanisms. The first one utilizes the different excitation intensity dependence on the blinking mechanisms. The second approach exploits the fact that collective blinking implies energy transfer to a quenching moiety, which is a time-dependent process. In pulsed-excitation experiments, the degree of collective blinking can therefore be altered by time gating the fluorescence photon stream, enabling us to extract the energy-transfer rate to a quencher. The ability to distinguish between different blinking mechanisms is valuable in materials science, such as for multichromophoric nanoparticles like conjugated-polymer chains as well as in biophysics, for example, for quantitative analysis of protein assemblies by counting chromophores.

Defining raft domains in the plasma membrane

Many plasma membrane (PM) functions depend on the cholesterol concentration in the PM in strikingly nonlinear, cooperative ways: fully functional in the presence of physiological cholesterol levels (35~45 mol%), and nonfunctional below 25 mol% cholesterol; namely, still in the presence of high concentrations of cholesterol. This suggests the involvement of cholesterol-based complexes/domains formed cooperatively. In this review, by examining the results obtained by using fluorescent lipid analogs and avoiding the trap of circular logic, often found in the raft literature, we point out the fundamental similarities of liquid-ordered (Lo)-phase domains in giant unilamellar vesicles, Lo-phase-like domains formed at lower temperatures in giant PM vesicles, and detergent-resistant membranes: these domains are formed by cooperative interactions of cholesterol, saturated acyl chains, and unsaturated acyl chains, in the presence of >25 mol% cholesterol. The literature contains evidence, indicating that the domains formed by the same basic cooperative molecular interactions exist and play essential roles in signal transduction in the PM. Therefore, as a working definition, we propose that raft domains in the PM are liquid-like molecular complexes/domains formed by cooperative interactions of cholesterol with saturated acyl chains as well as unsaturated acyl chains, due to saturated acyl chains' weak multiple accommodating interactions with cholesterol and cholesterol's low miscibility with unsaturated acyl chains and TM proteins. Molecules move within raft domains and exchange with those in the bulk PM. We provide a logically established collection of fluorescent lipid probes that preferentially partition into raft and non-raft domains, as defined here, in the PM.

Membrane signalosome: where biophysics meets systems biology

We opine on the recent advances in experiments and modeling of modular signaling complexes assembled on mammalian cell membranes (membrane signalosomes) in the context of several applications including intracellular trafficking, cell migration, and immune response. Characterizing the individual components of the membrane assemblies at the nanoscale, ranging from protein-lipid and protein-protein interactions, to membrane morphology, and the energetics of emergent assemblies at the subcellular to cellular scales pose significant challenges. Overcoming these challenges through the iterative coupling of multiscale modeling and experiment can be transformative in terms of addressing the gaps between structural biology and super-resolution microscopy, as it holds the key to the discovery of fundamental mechanisms behind the emergence of function in the membrane signalosome.

Formin nanoclustering-mediated actin assembly during plant flagellin and DSF signaling

Plants respond to bacterial infection acutely with actin remodeling during plant immune responses. The mechanisms by which bacterial virulence factors (VFs) modulate plant actin polymerization remain enigmatic. Here, we show that plant-type-I formin serves as the molecular sensor for actin remodeling in response to two bacterial VFs: Xanthomonas campestris pv. campestris (Xcc) diffusible signal factor (DSF), and pathogen-associated molecular pattern (PAMP) flagellin in pattern-triggered immunity (PTI). Both VFs regulate actin assembly by tuning the clustering and nucleation activity of formin on the plasma membrane (PM) at the nano-sized scale. By being integrated within the cell-wall-PM-actin cytoskeleton (CW-PM-AC) continuum, the dynamic behavior and function of formins are highly dependent on each scaffold layer's composition within the CW-PM-AC continuum during both DSF and PTI signaling. Our results reveal a central mechanism for rapid actin remodeling during plant-bacteria interactions, in which bacterial signaling molecules fine tune plant formin nanoclustering in a host mechanical-structure-dependent manner.

Cellular self-organization: generating order from the abyss

While the organization of inanimate systems such as gases or liquids is predominantly thermodynamically driven—a mixture of two gases will tend to mix until they reach equilibrium—biological systems frequently exhibit organization that is far from a well-mixed equilibrium. The anisotropies displayed by cells are evident in some of the dynamic processes that constitute life including cell development, movement, and division. These anisotropies operate at different length-scales, from the meso- to the nanoscale, and are proposed to reflect self-organization, a characteristic of living systems that is becoming accessible to reconstitution from purified components, and thus a more thorough understanding. Here, some examples of self-organization underlying cellular anisotropies at the cellular level are reviewed, with an emphasis on Rho-family GTPases operating at the plasma membrane. Given the technical challenges of studying these dynamic proteins, some of the successful approaches that are being employed to study their self-organization will also be considered.

Quantitative Proteomics Links the LRRC59 Interactome to mRNA Translation on the ER Membrane

Protein synthesis on the endoplasmic reticulum (ER) requires the dynamic coordination of numerous cellular components. Together, resident ER membrane proteins, cytoplasmic translation factors, and both integral membrane and cytosolic RNA-binding proteins operate in concert with membrane-associated ribosomes to facilitate ER-localized translation. Little is known, however, regarding the spatial organization of ER-localized translation. This question is of growing significance as it is now known that ER-bound ribosomes contribute to secretory, integral membrane, and cytosolic protein synthesis alike. To explore this question, we utilized quantitative proximity proteomics to identify neighboring protein networks for the candidate ribosome interactors SEC61β (subunit of the protein translocase), RPN1 (oligosaccharyltransferase subunit), SEC62 (translocation integral membrane protein), and LRRC59 (ribosome binding integral membrane protein). Biotin labeling time course studies of the four BioID reporters revealed distinct labeling patterns that intensified but only modestly diversified as a function of labeling time, suggesting that the ER membrane is organized into discrete protein interaction domains. Whereas SEC61β and RPN1 reporters identified translocon-associated networks, SEC62 and LRRC59 reporters revealed divergent protein interactomes. Notably, the SEC62 interactome is enriched in redox-linked proteins and ER luminal chaperones, with the latter likely representing proximity to an ER luminal chaperone reflux pathway. In contrast, the LRRC59 interactome is highly enriched in SRP pathway components, translation factors, and ER-localized RNA-binding proteins, uncovering a functional link between LRRC59 and mRNA translation regulation. Importantly, analysis of the LRRC59 interactome by native immunoprecipitation identified similar protein and functional enrichments. Moreover, [³⁵S]-methionine incorporation assays revealed that siRNA silencing of LRRC59 expression reduced steady state translation levels on the ER by ca. 50%, and also impacted steady state translation levels in the cytosol compartment. Collectively, these data reveal a functional domain organization for the ER and identify a key role for LRRC59 in the organization and regulation of local translation.

Structural basis of liprin-α-promoted LAR-RPTP clustering for modulation of phosphatase activity

Leukocyte common antigen-related receptor protein tyrosine phosphatases (LAR-RPTPs) are cell adhesion molecules involved in mediating neuronal development. The binding of LAR-RPTPs to extracellular ligands induces local clustering of LAR-RPTPs to regulate axon growth and synaptogenesis. LAR-RPTPs interact with synaptic liprin-α proteins via the two cytoplasmic phosphatase domains, D1 and D2. Here we solve the crystal structure of LAR_D1D2 in complex with the SAM repeats of liprin-α3, uncovering a conserved two-site binding mode. Cellular analysis shows that liprin-αs robustly promote clustering of LAR in cells by both the liprin-α/LAR interaction and the oligomerization of liprin-α. Structural analysis reveals a unique homophilic interaction of LAR via the catalytically active D1 domains. Disruption of the D1/D1 interaction diminishes the liprin-α-promoted LAR clustering and increases tyrosine dephosphorylation, demonstrating that the phosphatase activity of LAR is negatively regulated by forming clusters. Additionally, we find that the binding of LAR to liprin-α allosterically regulates the liprin-α/liprin-β interaction.

Leukocyte common antigen-related receptor protein tyrosine phosphatases (LAR-RPTPs) mediate guided axon growth and synapse formation and liprin-α proteins are their intracellular binding partners. Here the authors present the crystal structure of the phosphatase domains from the LAR-RPTP family member LAR bound to the SAM repeats of liprin-α3 and show that liprin-α binding enhances LAR cluster formation and reduces LAR phosphatase activity in cells.

A stochastic model of ion channel cluster formation in the plasma membrane

Ion channels are often found arranged into dense clusters in the plasma membranes of excitable cells, but the mechanisms underlying the formation and maintenance of these functional aggregates are unknown. Here, we tested the hypothesis that channel clustering is the consequence of a stochastic self-assembly process and propose a model by which channel clusters are formed and regulated in size. Our hypothesis is based on statistical analyses of the size distributions of the channel clusters we measured in neurons, ventricular myocytes, arterial smooth muscle, and heterologous cells, which in all cases were described by exponential functions, indicative of a Poisson process (i.e., clusters form in a continuous, independent, and memory-less fashion). We were able to reproduce the observed cluster distributions of five different types of channels in the membrane of excitable and tsA-201 cells in simulations using a computer model in which channels are "delivered" to the membrane at randomly assigned locations. The model's three parameters represent channel cluster nucleation, growth, and removal probabilities, the values of which were estimated based on our experimental measurements. We also determined the time course of cluster formation and membrane dwell time for CaV1.2 and TRPV4 channels expressed in tsA-201 cells to constrain our model. In addition, we elaborated a more complex version of our model that incorporated a self-regulating feedback mechanism to shape channel cluster formation. The strong inference we make from our results is that CaV1.2, CaV1.3, BK, and TRPV4 proteins are all randomly inserted into the plasma membranes of excitable cells and that they form homogeneous clusters that increase in size until they reach a steady state. Further, it appears likely that cluster size for a diverse set of membrane-bound proteins and a wide range of cell types is regulated by a common feedback mechanism.

Phase separation and clustering of an ABC transporter in Mycobacterium tuberculosis

Phase separation drives numerous cellular processes, ranging from the formation of membrane-less organelles to the cooperative assembly of signaling proteins. Features such as multivalency and intrinsic disorder that enable condensate formation are found not only in cytosolic and nuclear proteins, but also in membrane-associated proteins. The ABC transporter Rv1747, which is important for Mycobacterium tuberculosis (Mtb) growth in infected hosts, has a cytoplasmic regulatory module consisting of 2 phosphothreonine-binding Forkhead-associated domains joined by an intrinsically disordered linker with multiple phospho-acceptor threonines. Here we demonstrate that the regulatory modules of Rv1747 and its homolog in Mycobacterium smegmatis form liquid-like condensates as a function of concentration and phosphorylation. The serine/threonine kinases and sole phosphatase of Mtb tune phosphorylation-enhanced phase separation and differentially colocalize with the resulting condensates. The Rv1747 regulatory module also phase-separates on supported lipid bilayers and forms dynamic foci when expressed heterologously in live yeast and M. smegmatis cells. Consistent with these observations, single-molecule localization microscopy reveals that the endogenous Mtb transporter forms higher-order clusters within the Mycobacterium membrane. Collectively, these data suggest a key role for phase separation in the function of these mycobacterial ABC transporters and their regulation via intracellular signaling.

Frontotemporal dementia mutant Tau promotes aberrant Fyn nanoclustering in hippocampal dendritic spines

The Src kinase Fyn plays critical roles in memory formation and Alzheimer’s disease. Its targeting to neuronal dendrites is regulated by Tau via an unknown mechanism. As nanoclustering is essential for efficient signaling, we used single-molecule tracking to characterize the nanoscale distribution of Fyn in mouse hippocampal neurons, and manipulated the expression of Tau to test whether it controls Fyn nanoscale organization. We found that dendritic Fyn exhibits at least three distinct motion states, two of them associated with nanodomains. Fyn mobility decreases in dendrites during neuronal maturation, suggesting a dynamic synaptic reorganization. Removing Tau increases Fyn mobility in dendritic shafts, an effect that is rescued by re-expressing wildtype Tau. By contrast, expression of frontotemporal dementia P301L mutant Tau immobilizes Fyn in dendritic spines, affecting its motion state distribution and nanoclustering. Tau therefore controls the nanoscale organization of Fyn in dendrites, with the pathological Tau P301L mutation potentially contributing to synaptic dysfunction by promoting aberrant Fyn nanoclustering in spines.

Packing Density of the Amyloid Precursor Protein in the Cell Membrane

Plasma membrane proteins organize into structures named compartments, microdomains, rafts, phases, crowds, or clusters. These structures are often smaller than 100 nm in diameter. Despite their importance in many cellular functions, little is known about their inner organization. For instance, how densely are molecules packed? Being aware of the protein compaction may contribute to our general understanding of why such structures exist and how they execute their functions. In this study, we have investigated plasma membrane crowds formed by the amyloid precursor protein (APP), a protein well known for its involvement in Alzheimer's disease. By combining biochemical experiments with conventional and super-resolution stimulated emission depletion microscopy, we quantitatively determined the protein packing density within APP crowds. We found that crowds occurring with reasonable frequency contain between 20 and 30 molecules occupying a spherical area with a diameter between 65 and 85 nm. Additionally, we found the vast majority of plasmalemmal APP residing in these crowds. The model suggests a high molecular density of protein material within plasmalemmal APP crowds. This should affect the protein's biochemical accessibility and processing by nonpathological α-secretases. As clustering of APP is a prerequisite for endocytic entry into the pathological processing pathway, elucidation of the packing density also provides a deeper understanding of this part of APP's life cycle.

How does T cell receptor clustering impact on signal transduction?

The essential function of the T cell receptor (TCR) is to translate the engagement of peptides on the major histocompatibility complex (pMHC) into appropriate intracellular signals through the associated cluster of differentiation 3 (CD3) complex. The spatial organization of the TCR–CD3 complex in the membrane is thought to be a key regulatory element of signal transduction, raising the question of how receptor clustering impacts on TCR triggering. How signal transduction at the TCR–CD3 complex encodes the quality and quantity of pMHC molecules is not fully understood. This question can be approached by reconstituting T cell signaling in model and cell membranes and addressed by single-molecule imaging of endogenous proteins in T cells. We highlight such methods and further discuss how TCR clustering could affect pMHC rebinding rates, the local balance between kinase and phosphatase activity and/or the lipid environment to regulate the signal efficiency of the TCR–CD3 complex. We also examine whether clustering could affect the conformation of cytoplasmic CD3 tails through a biophysical mechanism. Taken together, we highlight how the spatial organization of the TCR–CD3 complex – addressed by reconstitution approaches – has emerged as a key regulatory element in signal transduction of this archetypal immune receptor.

Dynamic pattern generation in cell membranes: Current insights into membrane organization

It has been two decades since the lipid raft hypothesis was first presented. Even today, whether these nanoscale cholesterol-rich domains are present in cell membranes is not completely resolved. However, especially in the last few years, a rich body of literature has demonstrated both the presence and the importance of non-random distribution of biomolecules on the membrane, which is the focus of this review. These new developments have pushed the experimental limits of detection and have brought us closer to observing lipid domains in the plasma membrane of live cells. Characterization of biomolecules associated with lipid rafts has revealed a deep connection between biological regulation and function and membrane compositional heterogeneities. Finally, tantalizing new developments in the field have demonstrated that lipid domains might not just be associated with the plasma membrane of eukaryotes but could potentially be a ubiquitous membrane-organizing principle in several other biological systems. This article is part of a Special Issue entitled: Emergence of Complex Behavior in Biomembranes edited by Marjorie Longo.

Active and inactive β1 integrins segregate into distinct nanoclusters in focal adhesions

Through two superresolution microscopy techniques, STED and STORM, Spiess et al. visualize the organization of integrins in focal adhesions and show that active and inactive β1 integrins assemble into distinct nanoclusters within adhesions, suggesting the existence of a novel mechanism that locally coordinates integrin activity.

Integrins are the core constituents of cell–matrix adhesion complexes such as focal adhesions (FAs) and play key roles in physiology and disease. Integrins fluctuate between active and inactive conformations, yet whether the activity state influences the spatial organization of integrins within FAs has remained unclear. In this study, we address this question and also ask whether integrin activity may be regulated either independently for each integrin molecule or through locally coordinated mechanisms. We used two distinct superresolution microscopy techniques, stochastic optical reconstruction microscopy (STORM) and stimulated emission depletion microscopy (STED), to visualize active versus inactive β1 integrins. We first reveal a spatial hierarchy of integrin organization with integrin molecules arranged in nanoclusters, which align to form linear substructures that in turn build FAs. Remarkably, within FAs, active and inactive β1 integrins segregate into distinct nanoclusters, with active integrin nanoclusters being more organized. This unexpected segregation indicates synchronization of integrin activities within nanoclusters, implying the existence of a coordinate mechanism of integrin activity regulation.

GABA Regulates Release of Inflammatory Cytokines From Peripheral Blood Mononuclear Cells and CD4+ T Cells and Is Immunosuppressive in Type 1 Diabetes

The neurotransmitter γ-aminobutyric acid (GABA) is an extracellular signaling molecule in the brain and in pancreatic islets. Here, we demonstrate that GABA regulates cytokine secretion from human peripheral blood mononuclear cells (PBMCs) and CD4⁺ T cells. In anti-CD3 stimulated PBMCs, GABA (100 nM) inhibited release of 47 cytokines in cells from patients with type 1 diabetes (T1D), but only 16 cytokines in cells from nondiabetic (ND) individuals. CD4⁺ T cells from ND individuals were grouped into responder or non-responder T cells according to effects of GABA (100 nM, 500 nM) on the cell proliferation. In the responder T cells, GABA decreased proliferation, and inhibited secretion of 37 cytokines in a concentration-dependent manner. In the non-responder T cells, GABA modulated release of 8 cytokines. GABA concentrations in plasma from T1D patients and ND individuals were correlated with 10 cytokines where 7 were increased in plasma of T1D patients. GABA inhibited secretion of 5 of these cytokines from both T1D PBMCs and ND responder T cells. The results identify GABA as a potent regulator of both Th1- and Th2-type cytokine secretion from human PBMCs and CD4⁺ T cells where GABA generally decreases the secretion.

•

GABA regulates cytokine secretion in anti-CD3-stimulated peripheral blood mononuclear cells (PBMCs) and CD4⁺ T cells.

•

GABA inhibits secretion of 47 cytokines in PBMCs from type 1 diabetes patients.

•

GABA regulates secretion of pro- and anti-inflammatory cytokines in a concentration-dependent manner.

GABA is a signal molecule in the brain, blood and pancreatic islets where it is secreted by the insulin-producing β cells. GABA has many roles in human islets including optimizing function and survival of β cells. Bhandage et al. now show that GABA is a potent regulator of secretion of both pro- and anti-inflammatory cytokines in stimulated immune cells. In type 1 diabetes the β-cell mass is diminished and thus the protective effect of GABA in the islets although not in blood. Targeting GABA signaling in diabetes mellitus is likely to be a part of the solution when curing diabetes.

Mesoscale organization of domains in the plasma membrane - beyond the lipid raft

The plasma membrane is compartmentalized into several distinct regions or domains, which show a broad diversity in both size and lifetime. The segregation of lipids and membrane proteins is thought to be driven by the lipid composition itself, lipid-protein interactions and diffusional barriers. With regards to the lipid composition, the immiscibility of certain classes of lipids underlies the "lipid raft" concept of plasmalemmal compartmentalization. Historically, lipid rafts have been described as cholesterol and (glyco)sphingolipid-rich regions of the plasma membrane that exist as a liquid-ordered phase that are resistant to extraction with non-ionic detergents. Over the years the interest in lipid rafts grew as did the challenges with studying these nanodomains. The term lipid raft has fallen out of favor with many scientists and instead the terms "membrane raft" or "membrane nanodomain" are preferred as they connote the heterogeneity and dynamic nature of the lipid-protein assemblies. In this article, we will discuss the classical lipid raft hypothesis and its limitations. This review will also discuss alternative models of lipid-protein interactions, annular lipid shells, and larger membrane clusters. We will also discuss the mesoscale organization of plasmalemmal domains including visible structures such as clathrin-coated pits and caveolae.

Dynamics of translation can determine the spatial organization of membrane-bound proteins and their mRNA

Unlike most macromolecules that are homogeneously distributed in the bacterial cell, mRNAs that encode inner-membrane proteins can be concentrated near the inner membrane. Cotranslational insertion of the nascent peptide into the membrane brings the translating ribosome and the mRNA close to the membrane. This suggests that kinetic properties of translation can determine the spatial organization of these mRNAs and proteins, which can be modulated through posttranscriptional regulation. Here we use a simple stochastic model of translation to characterize the effect of mRNA properties on the dynamics and statistics of its spatial distribution. We show that a combination of the rate of translation initiation, the availability of secretory apparatuses, and the composition of the coding region determines the abundance of mRNAs near the membrane, as well as their residence time. We propose that the spatiotemporal dynamics of mRNAs can give rise to protein clusters on the membrane and determine their size distribution.

Subdomain 2, Not the Transmembrane Domain, Determines the Dimerization Partner of Growth Hormone Receptor and Prolactin Receptor

Growth hormone receptor (GHR) and prolactin (PRL) receptor (PRLR) are homologous transmembrane class I cytokine receptors. In humans, GH interacts with GHR homodimers or PRLR homodimers and PRL interacts with only PRLR homodimers to promote signaling. In human breast cancer cells endogenously expressing both receptors, GHR and PRLR specifically coimmunoprecipitate. We previously devised a split luciferase complementation assay to study GHR and PRLR assemblages. In this technique, firefly luciferase is split into two fragments (N- and C-terminal fragments of the luciferase), each without enzyme activity and tethered to the tails of two receptors. The fragments restore luciferase activity when brought close to each other by the receptors. Real-time ligand-induced complementation changes reflect the arrangement of receptors and indicate that GHR/PRLR is arranged as a heteromultimer comprised of GHR-GHR homodimers and PRLR-PRLR homodimers. We now dissect determinants for GHR and PRLR homodimerization versus heteroassociation. GHR and PRLR have extracellular domains comprised of the ligand-binding N-terminal subdomain 1 and a membrane-proximal subdomain 2 (S2), which fosters receptor-receptor contact. Based on previous studies of S2 versus the transmembrane domain (TMD) in GHR dimerization, we constructed GHR(PRLRS2), GHR(PRLRS2-TMD), and GHR(PRLRTMD), replacing GHR's S2 alone, S2 plus TMD, and TMD alone with PRLR's counterpart. We tested by complementation the ability of these chimeras and GHR or PRLR to homodimerize or heteroassociate. Comparing various combinations, we found GHR(PRLRS2) and GHR(PRLRS2-TMD) behaved as PRLR, whereas GHR(PRLRTMD) behaved as GHR regarding their dimerization partners. We conclude that S2 of GHR and PRLR, rather than their TMDs, determines their dimerization partner.