Superresolution microscopy reveals nanometer-scale reorganization of inhibitory natural killer cell receptors upon activation of NKG2D

Histocompatibility in Botryllus schlosseri and the origins of adaptive immunity

The basal chordate, Botryllus schlosseri, undergoes a natural transplantation reaction that is controlled by a single, highly polymorphic locus called the fuhc. The fuhc is one of the most polymorphic loci ever described, with most populations having hundreds of alleles, and up to a thousand found worldwide. Two individuals are compatible if they share one or both alleles, while those with no shared alleles are incompatible; thus, Botryllus uses a missing-self recognition strategy to discriminate between up to a thousand histocompatibility ligands. Remarkably, this discriminatory capability, which rivals that of vertebrate adaptive immunity, is carried out by germline-encoded receptors; thus, the mechanisms that establish and maintain this remarkable specificity are not understood. Multiple complete haplotypes of the fuhc locus have recently been sequenced, and at least seven genes with characteristics that suggest a role in allorecognition have been identified, including ligands, receptors, and intracellular proteins that likely organize and tune signal transduction complexes. This includes a new receptor family called the fester co-receptors (FcoRs) that encode ITIM and hemITAM domains, linking allorecognition in Botryllus to canonical immune transduction pathways. This review will summarize our current understanding and working hypotheses on the cellular and molecular mechanisms that control this innate, highly polymorphic allorecognition response, and how those may have been co-opted during the evolution of adaptive immunity.

Spatial statistics of submicron size clusters of activating and inhibitory Natural Killer cell receptors in the resting state regulate early time signal discrimination

Natural Killer (NK) cells are lymphocytes of the innate immunity and sense healthy or diseased target cells with activating and inhibitory NK cell receptor (NKR) molecules expressed on the cell surface. The protection provided by NK cells against viral infections and tumors critically depends on their ability to distinguish healthy cells from diseased target cells that express 100-fold more activating ligands. NK cell signaling and activation depend on integrating opposing signals initiated by activating and inhibitory NKRs interacting with the cognate ligands expressed on target cells. A wide range of imaging experiments have demonstrated aggregation of both activating and inhibitory NKRs in the plasma membrane on submicron scales in resting NK cells. How do these submicron size NKR clusters formed in the resting state affect signal discrimination? Using in silico mechanistic signaling modeling with information theory and published superresolution imaging data for two well-studied human NKRs, activating NKG2D and inhibitory KIR2DL1, we show that early time signal discrimination by NK cells depends on the spatial statistics of these clusters. When NKG2D and KIR2DL1 clusters are disjoint in the resting state, these clusters help NK cells to discriminate between target cells expressing low and high doses of the activating cognate ligand, whereas, when the NKR clusters fully overlap the NK cells are unable to distinguish between healthy and diseased target cells. Therefore, the spatial statistics of submicron scale clusters of activating and inhibitory NKRs at the resting state provides an additional layer of control for signal discrimination in NK cells.

Super-resolution microscopy unveils the nanoscale organization and self-limiting clustering of CD47 in human erythrocytes

The transmembrane protein CD47, an innate immune checkpoint protein, plays a pivotal role in preventing healthy erythrocytes from immune clearance. Our study utilized stochastic optical reconstruction microscopy (STORM) and single-molecule analysis to investigate the distribution of CD47 on the human erythrocyte membrane. Contrary to previous findings in mouse erythrocytes, we discovered that CD47 exists in randomly distributed monomers rather than in clusters across the human erythrocyte membrane. Using secondary antibody-induced crosslinking, we found that CD47 aggregates into stable clusters within minutes. By comparing these STORM results with those of the fully mobile protein CD59 and the cytoskeleton-bound membrane protein glycophorin C under similar conditions, as well as devising two-color STORM co-labeling and co-clustering experiments, we further quantitatively revealed an intermediate, self-limiting clustering behavior of CD47, elucidating its fractional (∼14%) attachment to the cytoskeleton. Moreover, we report reductions in both the amount of CD47 and its clustering capability in aged erythrocytes, providing new insight into erythrocyte senescence. Together, the combination of STORM and secondary antibody-based crosslinking unveils the unique self-limiting clustering behavior of CD47 due to its fractional cytoskeleton attachment.

Spatial localization of CD16a at the human NK cell ADCC lytic synapse

Natural Killer (NK) cells utilize effector functions, including antibody-dependent cellular cytotoxicity (ADCC), for the clearance of viral infection and cellular malignancies. NK cell ADCC is mediated by FcγRIIIa (CD16a) binding to the fragment crystallizable (Fc) region of immunoglobulin G (IgG) within immune complexes on a target cell surface. While antibody-induced clustering of CD16a is thought to drive ADCC, the molecular basis for this activity has not been fully described. Here we use MINFLUX nanoscopy to map the spatial distribution of stoichiometrically labeled CD16a across the NK cell membrane, revealing the presence of pairs of CD16a molecules with intra-doublet distance of approximately 17 nm. NK cells activated on supported lipid bilayers by Trastuzumab results in an increase of synaptic regions with greater CD16a density. Our results provide the highest spatial resolution yet described for CD16a imaging, offering new insight into how CD16a organization within the immune synapse could influence ADCC activity. MINFLUX holds great promise to further unravel the molecular details driving CD16a-based activation of NK cells.

Membrane Fluctuation Model for Understanding the Effect of Receptor Nanoclustering on the Activation of Natural Killer Cells through Biomechanical Feedback

We investigated the role of ligand clustering and density in the activation of natural killer (NK) cells. To that end, we designed reductionist arrays of nanopatterned ligands arranged with different cluster geometries and densities and probed their effects on NK cell activation. We used these arrays as an artificial microenvironment for the stimulation of NK cells and studied the effect of the array geometry on the NK cell immune response. We found that ligand density significantly regulated NK cell activation while ligand clustering had an impact only at a specific density threshold. We also rationalized these findings by introducing a theoretical membrane fluctuation model that considers biomechanical feedback between ligand-receptor bonds and the cell membrane. These findings provide important insight into NK cell mechanobiology, which is fundamentally important and essential for designing immunotherapeutic strategies targeting cancer.

The Power of Three: Nanomaterials for Natural Killer (NK) Cell Immunoengineering Maximize Their Potency if They Exploit Multireceptor Stimulation

Many emerging cancer treatments are immunotherapies that modulate Natural Killer- (NK) or T cell activation, posing a challenge to develop immunoengineering nanomaterials that improve on the performance of molecular reagents. In physiological activation, multiple immunoreceptors signal in consort; however, current biomaterials do not replicate this. Here, NK cells are created for the first time, activating bionanomaterials that stimulate >2 immunoreceptors. Nanoclusters of monoclonal antibodies (mAb), templated by nanoscale graphene oxide sheets (NGO) (≈75 nm size), are exploited. To inform nanoreagent design, a model system of planar substrates with anchored mAb is first investigated. Combining mAb that stimulates three NK cell activating receptors (αNKP46 + αNKG2D + αDNAM-1), activated NK cells act more potently than any single receptor or pair. Applying this insight, an NGO-mAb nanocluster combining three distinct mAb: NGO-mAb(αNKP46 + αNKG2D + αDNAM-1) is created. This construct is potent and outperforms single-receptor-simulating nanoclusters, activating nearly twice as many NK cells as NGO-mAb(αNKP46) at a similar mAb dose or delivering similar activation at 10× lower dosage. Further, NGO-mAb are more potent than planar substrates for both single- and triple-mAb stimulation. These results imply a new concept for immunoengineering biomaterials: both nanoclustering and multi-receptor stimulation should be incorporated for maximum effect.

Nanometer-scale distribution of PD-1 in the melanoma tumor microenvironment

The nanometer-scale spatial organization of immune receptors plays a role in cell activation and suppression. While the connection between this spatial organization and cell signaling events is emerging from cell culture experiments, how these results translate to more physiologically relevant settings like the tumor microenvironment remains poorly understood due to the challenges of high-resolution imaging in vivo. Here we perform super-resolution immunofluorescence microscopy of human melanoma tissue sections to examine the spatial organization of the immune checkpoint inhibitor programmed cell death 1 (PD-1). We show that PD-1 exhibits a variety of organizations ranging from nanometer-scale clusters to more uniform membrane labeling. Our results demonstrate the capability of super-resolution imaging to examine the spatial organization of immune checkpoint markers in the tumor microenvironment, suggesting a future direction for both clinical and immunology research.

Human natural killer cells: Form, function, and development

Human natural killer (NK) cells are innate lymphoid cells that mediate important effector functions in the control of viral infection and malignancy. Their ability to distinguish "self" from "nonself" and lyse virally infected and tumorigenic cells through germline-encoded receptors makes them important players in maintaining human health and a powerful tool for immunotherapeutic applications and fighting disease. This review introduces our current understanding of NK cell biology, including key facets of NK cell differentiation and the acquisition and execution of NK cell effector function. Further, it addresses the clinical relevance of NK cells in both primary immunodeficiency and immunotherapy. It is intended to provide an up-to-date and comprehensive overview of this important and interesting innate immune effector cell subset.

Structure of the human NK cell NKR-P1:LLT1 receptor:ligand complex reveals clustering in the immune synapse

Signaling by the human C-type lectin-like receptor, natural killer (NK) cell inhibitory receptor NKR-P1, has a critical role in many immune-related diseases and cancer. C-type lectin-like receptors have weak affinities to their ligands; therefore, setting up a comprehensive model of NKR-P1-LLT1 interactions that considers the natural state of the receptor on the cell surface is necessary to understand its functions. Here we report the crystal structures of the NKR-P1 and NKR-P1:LLT1 complexes, which provides evidence that NKR-P1 forms homodimers in an unexpected arrangement to enable LLT1 binding in two modes, bridging two LLT1 molecules. These interaction clusters are suggestive of an inhibitory immune synapse. By observing the formation of these clusters in solution using SEC-SAXS analysis, by dSTORM super-resolution microscopy on the cell surface, and by following their role in receptor signaling with freshly isolated NK cells, we show that only the ligation of both LLT1 binding interfaces leads to effective NKR-P1 inhibitory signaling. In summary, our findings collectively support a model of NKR-P1:LLT1 clustering, which allows the interacting proteins to overcome weak ligand-receptor affinity and to trigger signal transduction upon cellular contact in the immune synapse.

NKR-P1 is an inhibitory receptor on the surface of natural killer cells, and its engagement with the ligand LLT1 on activated monocytes and B cells triggers NK cell self-tolerance and other immunological processes. Here authors set up a comprehensive, structure-based model of NKR-P1-LLT1 interaction that involves NKR-P1 homodimer formation and subsequent bridging of two LLT1 molecules.

Radius measurement via super-resolution microscopy enables the development of a variable radii proximity labeling platform

The elucidation of protein interaction networks is critical to understanding fundamental biology as well as developing new therapeutics. Proximity labeling platforms (PLPs) are state-of-the-art technologies that enable the discovery and delineation of biomolecular networks through the identification of protein-protein interactions. These platforms work via catalytic generation of reactive probes at a biological region of interest; these probes then diffuse through solution and covalently "tag" proximal biomolecules. The physical distance that the probes diffuse determines the effective labeling radius of the PLP and is a critical parameter that influences the scale and resolution of interactome mapping. As such, by expanding the degrees of labeling resolution offered by PLPs, it is possible to better capture the various size scales of interactomes. At present, however, there is little quantitative understanding of the labeling radii of different PLPs. Here, we report the development of a superresolution microscopy-based assay for the direct quantification of PLP labeling radii. Using this assay, we provide direct extracellular measurements of the labeling radii of state-of-the-art antibody-targeted PLPs, including the peroxidase-based phenoxy radical platform (269 ± 41 nm) and the high-resolution iridium-catalyzed µMap technology (54 ± 12 nm). Last, we apply these insights to the development of a molecular diffusion-based approach to tuning PLP resolution and introduce a new aryl-azide-based µMap platform with an intermediate labeling radius (80 ± 28 nm).

Nanoscale Colocalization of NK Cell Activating and Inhibitory Receptors Controls Signal Integration

Natural killer (NK) cell responses depend on the balance of signals from inhibitory and activating receptors. However, how the integration of antagonistic signals occurs upon NK cell-target cell interaction is not fully understood. Here we provide evidence that NK cell inhibition via the inhibitory receptor Ly49A is dependent on its relative colocalization at the nanometer scale with the activating receptor NKG2D upon immune synapse (IS) formation. NKG2D and Ly49A signal integration and colocalization were studied using NKG2D-GFP and Ly49A-RFP-expressing primary NK cells, forming ISs with NIH3T3 target cells, with or without the expression of single-chain trimer (SCT) H2-Dd and an extended form of SCT H2-Dd-CD4 MHC-I molecules. Nanoscale colocalization was assessed by Förster resonance energy transfer between NKG2D-GFP and Ly49A-RFP and measured for each synapse. In the presence of their respective cognate ligands, NKG2D and Ly49A colocalize at the nanometer scale, leading to NK cell inhibition. However, increasing the size of the Ly49A ligand reduced the nanoscale colocalization with NKG2D, consequently impairing Ly49A-mediated inhibition. Thus, our data shows that NK cell signal integration is critically dependent on the dimensions of NK cell ligand-receptor pairs by affecting their relative nanometer-scale colocalization at the IS. Our results together suggest that the balance of NK cell signals and NK cell responses is determined by the relative nanoscale colocalization of activating and inhibitory receptors in the immune synapse.

Spatially resolved in silico modeling of NKG2D signaling kinetics suggests a key role of NKG2D and Vav1 Co-clustering in generating natural killer cell activation

Natural Killer (NK) cells provide key resistance against viral infections and tumors. A diverse set of activating and inhibitory NK cell receptors (NKRs) interact with cognate ligands presented by target host cells, where integration of dueling signals initiated by the ligand-NKR interactions determines NK cell activation or tolerance. Imaging experiments over decades have shown micron and sub-micron scale spatial clustering of activating and inhibitory NKRs. The mechanistic roles of these clusters in affecting downstream signaling and activation are often unclear. To this end, we developed a predictive in silico framework by combining spatially resolved mechanistic agent based modeling, published TIRF imaging data, and parameter estimation to determine mechanisms by which formation and spatial movements of activating NKG2D microclusters affect early time NKG2D signaling kinetics in a human cell line NKL. We show co-clustering of NKG2D and the guanosine nucleotide exchange factor Vav1 in NKG2D microclusters plays a dominant role over ligand (ULBP3) rebinding in increasing production of phospho-Vav1(pVav1), an activation marker of early NKG2D signaling. The in silico model successfully predicts several scenarios of inhibition of NKG2D signaling and time course of NKG2D spatial clustering over a short (~3 min) interval. Modeling shows the presence of a spatial positive feedback relating formation and centripetal movements of NKG2D microclusters, and pVav1 production offers flexibility towards suppression of activating signals by inhibitory KIR ligands organized in inhomogeneous spatial patterns (e.g., a ring). Our in silico framework marks a major improvement in developing spatiotemporal signaling models with quantitatively estimated model parameters using imaging data.

Natural Killer cells are lymphocytes of our innate immunity and provide important resistance against viral infections and tumors. NK cells scan the local environment with diverse activating and inhibitory NK cell receptors (NKRs) and remain tolerized or lyse target cells expressing cognate ligands to NKRs. NKRs have been found to form micron sized clusters (or microclusters) as they interact with cognate ligands, and mechanisms regarding how the formation and movements of these microclusters influence NK cell signaling and activation, specifically related to activating NKRs, are often unclear. To this end, we develop a predictive spatially resolved early-time NK cell signaling model to study the interplay between membrane-proximal biochemical signaling events and the kinetics of microclusters of activating NKG2D and inhibitory KIR2DL2 receptors. We used published TIRF imaging data to validate our in silico models and estimate model parameters. Predictions from multiple in silico models are tested against a variety of data obtained from published imaging experiments and immunoassays. Our analysis suggests co-clustering of NKG2D and the guanosine nucleotide exchange factor Vav1 in the microclusters plays a major role in enhancing downstream activating signals. The developed framework can be extended to describe spatiotemporal signaling for other activating NKRs including CD16.

Understanding immune signaling using advanced imaging techniques

Advanced imaging is key for visualizing the spatiotemporal regulation of immune signaling which is a complex process involving multiple players tightly regulated in space and time. Imaging techniques vary in their spatial resolution, spanning from nanometers to micrometers, and in their temporal resolution, ranging from microseconds to hours. In this review, we summarize state-of-the-art imaging methodologies and provide recent examples on how they helped to unravel the mysteries of immune signaling. Finally, we discuss the limitations of current technologies and share our insights on how to overcome these limitations to visualize immune signaling with unprecedented fidelity.

Label-Free Analysis of Cell Membrane Proteins via Evanescent Field Excited Surface-Enhanced Raman Scattering

Challenges in studying the structures and functions of cell membrane proteins lie in their lipophilicity, which makes them hard to be stabilized, crystallized, and expressed by E. coli. Herein, we propose an evanescent field excited surface-enhanced Raman scattering (EF-SERS) strategy for label-free analysis of membrane proteins in situ. Extracted cell membranes tightly wrapped the metal nanoparticles by an extruder, which ensures the SERS signals of the membrane proteins precisely benefit from the localized surface plasmons (LSPs). The leaky mode of a waveguide was employed to improve the plasmon excitation coupling. Thus, the LSPs and waveguide modes together enable the achievement of high-quality SERS profiles of membrane proteins. By spectral analysis, the structural changes of membrane proteins can be deeply understood at the molecular level. This method has broader applicability in establishing the Ramanomics of membrane proteins and unraveling the exact changes of membrane proteins during physiological processes.

Super-Resolution Imaging Approaches for Quantifying F-Actin in Immune Cells

Immune cells comprise a diverse set of cells that undergo a complex array of biological processes that must be tightly regulated. A key component of cellular machinery that achieves this is the cytoskeleton. Therefore, imaging and quantitatively describing the architecture and dynamics of the cytoskeleton is an important research goal. Optical microscopy is well suited to this task. Here, we review the latest in the state-of-the-art methodology for labeling the cytoskeleton, fluorescence microscopy hardware suitable for such imaging and quantitative statistical analysis software applicable to describing cytoskeletal structures. We also highlight ongoing challenges and areas for future development.

Rapid statistical discrimination of fluorescence images of T cell receptors on immobilizing surfaces with different coating conditions

The spatial organization of T cell receptors (TCRs) correlates with membrane-associated signal amplification, dispersion, and regulation during T cell activation. Despite its potential clinical importance, quantitative analysis of the spatial arrangement of TCRs from standard fluorescence images remains difficult. Here, we report Statistical Classification Analyses of Membrane Protein Images or SCAMPI as a technique capable of analyzing the spatial arrangement of TCRs on the plasma membrane of T cells. We leveraged medical image analysis techniques that utilize pixel-based values. We transformed grayscale pixel values from fluorescence images of TCRs into estimated model parameters of partial differential equations. The estimated model parameters enabled an accurate classification using linear discrimination techniques, including Fisher Linear Discriminant (FLD) and Logistic Regression (LR). In a proof-of-principle study, we modeled and discriminated images of fluorescently tagged TCRs from Jurkat T cells on uncoated cover glass surfaces (Null) or coated cover glass surfaces with either positively charged poly-L-lysine (PLL) or TCR cross-linking anti-CD3 antibodies (OKT3). Using 80 training images and 20 test images per class, our statistical technique achieved 85% discrimination accuracy for both OKT3 versus PLL and OKT3 versus Null conditions. The run time of image data download, model construction, and image discrimination was 21.89 s on a laptop computer, comprised of 20.43 s for image data download, 1.30 s on the FLD-SCAMPI analysis, and 0.16 s on the LR-SCAMPI analysis. SCAMPI represents an alternative approach to morphology-based qualifications for discriminating complex patterns of membrane proteins conditioned on a small sample size and fast runtime. The technique paves pathways to characterize various physiological and pathological conditions using the spatial organization of TCRs from patient T cells.

Molecular-scale spatio-chemical control of the activating-inhibitory signal integration in NK cells

The role of juxtaposition of activating and inhibitory receptors in signal inhibition of cytotoxic lymphocytes remains strongly debated. The challenge lies in the lack of tools that allow simultaneous spatial manipulation of signaling molecules. To circumvent this, we produced a nanoengineered multifunctional platform with molecular-scale spatial control of ligands, which was applied to elucidate KIR2DL1-mediated inhibition of NKG2D signaling-receptors of natural killer cells. This platform was conceived by bimetallic nanodot patterning with molecular-scale registry, followed by a ternary functionalization with distinct moieties. We found that a 40-nm gap between activating and inhibitory ligands provided optimal inhibitory conditions. Supported by theoretical modeling, we interpret these findings as a consequence of the size mismatch and conformational flexibility of ligands in their spatial interaction. This highly versatile approach provides an important insight into the spatial mechanism of inhibitory immune checkpoints, which is essential for the rational design of future immunotherapies.

Predicting the membrane permeability of organic fluorescent probes by the deep neural network based lipophilicity descriptor DeepFl-LogP

Light microscopy has become an indispensable tool for the life sciences, as it enables the rapid acquisition of three-dimensional images from the interior of living cells/tissues. Over the last decades, super-resolution light microscopy techniques have been developed, which allow a resolution up to an order of magnitude higher than that of conventional light microscopy. Those techniques require labelling of cellular structures with fluorescent probes exhibiting specific properties, which are supplied from outside and therefore have to surpass cell membranes. Currently, major efforts are undertaken to develop probes which can surpass cell membranes and exhibit the photophysical properties required for super-resolution imaging. However, the process of probe development is still based on a tedious and time consuming manual screening. An accurate computer based model that enables the prediction of the cell permeability based on their chemical structure would therefore be an invaluable asset for the development of fluorescent probes. Unfortunately, current models, which are based on multiple molecular descriptors, are not well suited for this task as they require high effort in the usage and exhibit moderate accuracy in their prediction. Here, we present a novel fragment based lipophilicity descriptor DeepFL-LogP, which was developed on the basis of a deep neural network. DeepFL-LogP exhibits excellent correlation with the experimental partition coefficient reference data (R2 = 0.892 and MSE = 0.359) of drug-like substances. Further a simple threshold permeability model on the basis of this descriptor allows to categorize the permeability of fluorescent probes with 96% accuracy. This novel descriptor is expected to largely simplify and speed up the development process for novel cell permeable fluorophores.

The Role of Protein and Lipid Clustering in Lymphocyte Activation

Lymphocytes must strike a delicate balance between activating in response to signals from potentially pathogenic organisms and avoiding activation from stimuli emanating from the body's own cells. For cells, such as T or B cells, maximizing the efficiency and fidelity, whilst minimizing the crosstalk, of complex signaling pathways is crucial. One way of achieving this control is by carefully orchestrating the spatiotemporal organization of signaling molecules, thereby regulating the rates of protein-protein interactions. This is particularly true at the plasma membrane where proximal signaling events take place and the phenomenon of protein microclustering has been extensively observed and characterized. This review will focus on what is known about the heterogeneous distribution of proteins and lipids at the cell surface, illustrating how such distributions can influence signaling in health and disease. We particularly focus on nanoscale molecular organization, which has recently become accessible for study through advances in microscope technology and analysis methodology.

The Role of the Cytoskeleton in Regulating the Natural Killer Cell Immune Response in Health and Disease: From Signaling Dynamics to Function

Natural killer (NK) cells are innate lymphoid cells, which play key roles in elimination of virally infected and malignant cells. The balance between activating and inhibitory signals derived from NK surface receptors govern the NK cell immune response. The cytoskeleton facilitates most NK cell effector functions, such as motility, infiltration, conjugation with target cells, immunological synapse assembly, and cytotoxicity. Though many studies have characterized signaling pathways that promote actin reorganization in immune cells, it is not completely clear how particular cytoskeletal architectures at the immunological synapse promote effector functions, and how cytoskeletal dynamics impact downstream signaling pathways and activation. Moreover, pioneering studies employing advanced imaging techniques have only begun to uncover the architectural complexity dictating the NK cell activation threshold; it is becoming clear that a distinct organization of the cytoskeleton and signaling receptors at the NK immunological synapse plays a decisive role in activation and tolerance. Here, we review the roles of the actin cytoskeleton in NK cells. We focus on how actin dynamics impact cytolytic granule secretion, NK cell motility, and NK cell infiltration through tissues into inflammatory sites. We will also describe the additional cytoskeletal components, non-muscle Myosin II and microtubules that play pivotal roles in NK cell activity. Furthermore, special emphasis will be placed on the role of the cytoskeleton in assembly of immunological synapses, and how mutations or downregulation of cytoskeletal accessory proteins impact NK cell function in health and disease.

Advancing Cell-Instructive Biomaterials Through Increased Understanding of Cell Receptor Spacing and Material Surface Functionalization

Abstract

Regenerative medicine is aimed at restoring normal tissue function and can benefit from the application of tissue engineering and nano-therapeutics. In order for regenerative therapies to be effective, the spatiotemporal integration of tissue-engineered scaffolds by the native tissue, and the binding/release of therapeutic payloads by nano-materials, must be tightly controlled at the nanoscale in order to direct cell fate. However, due to a lack of insight regarding cell–material interactions at the nanoscale and subsequent downstream signaling, the clinical translation of regenerative therapies is limited due to poor material integration, rapid clearance, and complications such as graft-versus-host disease. This review paper is intended to outline our current understanding of cell–material interactions with the aim of highlighting potential areas for knowledge advancement or application in the field of regenerative medicine. This is achieved by reviewing the nanoscale organization of key cell surface receptors, the current techniques used to control the presentation of cell-interactive molecules on material surfaces, and the most advanced techniques for characterizing the interactions that occur between cell surface receptors and materials intended for use in regenerative medicine.

Lay Summary

The combination of biology, chemistry, materials science, and imaging technology affords exciting opportunities to better diagnose and treat a wide range of diseases. Recent advances in imaging technologies have enabled better understanding of the specific interactions that occur between human cells and their immediate surroundings in both health and disease. This biological understanding can be used to design smart therapies and tissue replacements that better mimic native tissue. Here, we discuss the advances in molecular biology and technologies that can be employed to functionalize materials and characterize their interaction with biological entities to facilitate the design of more sophisticated medical therapies.

A Review of Super-Resolution Single-Molecule Localization Microscopy Cluster Analysis and Quantification Methods

Single-molecule localization microscopy (SMLM) is a relatively new imaging modality, winning the 2014 Nobel Prize in Chemistry, and considered as one of the key super-resolution techniques. SMLM resolution goes beyond the diffraction limit of light microscopy and achieves resolution on the order of 10-20 nm. SMLM thus enables imaging single molecules and study of the low-level molecular interactions at the subcellular level. In contrast to standard microscopy imaging that produces 2D pixel or 3D voxel grid data, SMLM generates big data of 2D or 3D point clouds with millions of localizations and associated uncertainties. This unprecedented breakthrough in imaging helps researchers employ SMLM in many fields within biology and medicine, such as studying cancerous cells and cell-mediated immunity and accelerating drug discovery. However, SMLM data quantification and interpretation methods have yet to keep pace with the rapid advancement of SMLM imaging. Researchers have been actively exploring new computational methods for SMLM data analysis to extract biosignatures of various biological structures and functions. In this survey, we describe the state-of-the-art clustering methods adopted to analyze and quantify SMLM data and examine the capabilities and shortcomings of the surveyed methods. We classify the methods according to (1) the biological application (i.e., the imaged molecules/structures), (2) the data acquisition (such as imaging modality, dimension, resolution, and number of localizations), and (3) the analysis details (2D versus 3D, field of view versus region of interest, use of machine-learning and multi-scale analysis, biosignature extraction, etc.). We observe that the majority of methods that are based on second-order statistics are sensitive to noise and imaging artifacts, have not been applied to 3D data, do not leverage machine-learning formulations, and are not scalable for big-data analysis. Finally, we summarize state-of-the-art methodology, discuss some key open challenges, and identify future opportunities for better modeling and design of an integrated computational pipeline to address the key challenges.

An agent-based model of molecular aggregation at the cell membrane

Molecular clustering at the plasma membrane has long been identified as a key process and is associated with regulating signalling pathways across cell types. Recent advances in microscopy, in particular the rise of super-resolution, have allowed the experimental observation of nanoscale molecular clusters in the plasma membrane. However, modelling approaches capable of recapitulating these observations are in their infancy, partly because of the extremely complex array of biophysical factors which influence molecular distributions and dynamics in the plasma membrane. We propose here a highly abstracted approach: an agent-based model dedicated to the study of molecular aggregation at the plasma membrane. We show that when molecules are modelled as though they can act (diffuse) in a manner which is influenced by their molecular neighbourhood, many of the distributions observed in cells can be recapitulated, even though such sensing and response is not possible for real membrane molecules. As such, agent-based offers a unique platform which may lead to a new understanding of how molecular clustering in extremely complex molecular environments can be abstracted, simulated and interpreted using simple rules.

Genetic diversity affects the nanoscale membrane organization and signaling of natural killer cell receptors

Genetic diversity in human natural killer (NK) cell receptors is linked to resistance and susceptibility to many diseases. Here, we tested the effect of this diversity on the nanoscale organization of killer cell immunoglobulin-like receptors (KIRs). Using superresolution microscopy, we found that inhibitory KIRs encoded by different genes and alleles were organized differently at the surface of primary human NK cells. KIRs that were found at low abundance assembled into smaller clusters than those formed by KIRs that were more highly abundant, and at low abundance, there was a greater proportion of KIRs in clusters. Upon receptor triggering, a structured interface called the immune synapse assembles, which facilitates signal integration and controls NK cell responses. Here, triggering of low-abundance receptors resulted in less phosphorylation of the downstream phosphatase SHP-1 but more phosphorylation of the adaptor protein Crk than did triggering of high-abundance receptors. In cells with greater KIR abundance, SHP-1 dephosphorylated Crk, which potentiated NK cell spreading during activation. Thus, genetic variation modulates both the abundance and nanoscale organization of inhibitory KIRs. That is, as well as the number of receptors at the cell surface varying with genotype, the way in which these receptors are organized in the membrane also varies. Essentially, a change in the average surface abundance of a protein at the cell surface is a coarse descriptor entwined with changes in local nanoscale clustering. Together, our data indicate that genetic diversity in inhibitory KIRs affects membrane-proximal signaling and, unexpectedly, the formation of activating immune synapses.

Caveolae and scaffold detection from single molecule localization microscopy data using deep learning

Caveolae are plasma membrane invaginations whose formation requires caveolin-1 (Cav1), the adaptor protein polymerase I, and the transcript release factor (PTRF or CAVIN1). Caveolae have an important role in cell functioning, signaling, and disease. In the absence of CAVIN1/PTRF, Cav1 forms non-caveolar membrane domains called scaffolds. In this work, we train machine learning models to automatically distinguish between caveolae and scaffolds from single molecule localization microscopy (SMLM) data. We apply machine learning algorithms to discriminate biological structures from SMLM data. Our work is the first that is leveraging machine learning approaches (including deep learning models) to automatically identifying biological structures from SMLM data. In particular, we develop and compare three binary classification methods to identify whether or not a given 3D cluster of Cav1 proteins is a caveolae. The first uses a random forest classifier applied to 28 hand-crafted/designed features, the second uses a convolutional neural net (CNN) applied to a projection of the point clouds onto three planes, and the third uses a PointNet model, a recent development that can directly take point clouds as its input. We validate our methods on a dataset of super-resolution microscopy images of PC3 prostate cancer cells labeled for Cav1. Specifically, we have images from two cell populations: 10 PC3 and 10 CAVIN1/PTRF-transfected PC3 cells (PC3-PTRF cells) that form caveolae. We obtained a balanced set of 1714 different cellular structures. Our results show that both the random forest on hand-designed features and the deep learning approach achieve high accuracy in distinguishing the intrinsic features of the caveolae and non-caveolae biological structures. More specifically, both random forest and deep CNN classifiers achieve classification accuracy reaching 94% on our test set, while the PointNet model only reached 83% accuracy. We also discuss the pros and cons of the different approaches.

Data analysis to modeling to building theory in NK cell biology and beyond: How can computational modeling contribute?

The use of mathematical and computational tools in investigating Natural Killer (NK) cell biology and in general the immune system has increased steadily in the last few decades. However, unlike the physical sciences, there is a persistent ambivalence, which however is increasingly diminishing, in the biology community toward appreciating the utility of quantitative tools in addressing questions of biological importance. We survey some of the recent developments in the application of quantitative approaches for investigating different problems in NK cell biology and evaluate opportunities and challenges of using quantitative methods in providing biological insights in NK cell biology.

Mechanoimmunology: molecular-scale forces govern immune cell functions

Immune cell recognition of antigens is a pivotal process in initiating immune responses against injury, pathogens, and cancers. Breakthroughs over the past decade support a major role for mechanical forces in immune responses, laying the foundation for the emerging field of mechanoimmunology. In this Perspective, we discuss the mechanical forces acting at the level of ligand–receptor interactions and how they underpin receptor triggering, signal initiation, and immune cell activation. We also highlight the novel biophysical tools and advanced imaging techniques that have afforded us the recent progress in our understanding of the role of forces in immune cell functions.

HLA-B and HLA-C Differ in Their Nanoscale Organization at Cell Surfaces

The particular HLA class I variants an individual carries influences their resistance and susceptibility to a multitude of diseases. Expression level and variation in the peptide binding region correlates with, for example, a person's progression to AIDS after HIV infection. One factor which has not yet been addressed is whether or not different HLA class I proteins organize differently in the cell membrane on a nanoscale. Here, we examined the organization of three HLA-B allotypes (B^*2705, B^*5301, and B^*5701) and two HLA-C allotypes (C^*0602 and C^*0702) in the membrane of 721.221 cells which otherwise lack expression of HLA-B or HLA-C. All these allotypes are ligands for the T cell receptor and leukocyte immunoglobulin-like receptors, but additionally, the HLA-B allotypes are ligands for the killer-cell immunoglobulin-like receptor family member KIR3DL1, HLA-C^*0602 is a ligand for KIR2DL1, and HLA-C^*0702 is a ligand for KIR2DL2/3. Using super-resolution microscopy, we found that both HLA-B and HLA-C formed more clusters and a greater proportion of HLA contributed to clusters, when expressed at lower levels. Thus, HLA class I organization is a covariate in genetic association studies of HLA class I expression level with disease progression. Surprisingly, we also found that HLA-C was more clustered than HLA-B when expression level was controlled. HLA-C consistently formed larger and more numerous clusters than HLA-B and a greater proportion of HLA-C contributed to clusters than for HLA-B. We also found that the organization of HLA class I proteins varied with cell type. T cells exhibited a particularly clustered organization of HLA class I while B cells expressed a more uniform distribution. In summary, HLA class I variants are organized differently in the cell surface membrane which may impact their functions.

Immune signalling by supramolecular assemblies

Formation of supramolecular assemblies appears to be a general mechanism in immune signalling pathways. These supramolecular assemblies appear to form through a nucleated polymerization mechanism. This review examines selected immune signalling pathways that involve supramolecular assemblies, describes the concepts of protein polymerization, and discusses how those concepts of protein polymerization implicate new elegant ways for signal amplification, setting threshold and noise reduction in these pathways.

Natural killer cells' immune response requires a minimal nanoscale distribution of activating antigens

NK cells recognize cancer and viral cells by binding their activating receptors to antigens presenting on the membrane of target cells. Although the activation mechanism of NK cells is a subject of extensive research today, the role of the composition and spatial distribution of activating ligands in NK cell cytotoxicity is barely understood. In this work, we engineered a nanochip whose surface was patterned with matrices of antigens for NKG2D activating receptors. These matrices mimicked the spatial order of the surface of antigen presenting cells with molecular resolution. Using this chip, we elucidated the effect of the antigen spatial distribution on the NK cell spreading and immune activation. We found that the spatial distribution of the ligand within the 100 nm length-scale provides the minimal conditions for NKG2D regulated cell spreading. Furthermore, we found that the immune activation of NK cells requires the same minimal spatial distribution of activating ligands. Above this threshold, both spreading and activation plateaued, confirming that these two cell functions work hand in hand. Our study provides an important insight on the spatial mechanism of the cytotoxic activity of NK cells. This insight opens the way to rationally designed antitumor therapies that harness NK cytotoxicity.

Super Resolution Network Analysis Defines the Molecular Architecture of Caveolae and Caveolin-1 Scaffolds

Quantitative approaches to analyze the large data sets generated by single molecule localization super-resolution microscopy (SMLM) are limited. We developed a computational pipeline and applied it to analyzing 3D point clouds of SMLM localizations (event lists) of the caveolar coat protein, caveolin-1 (Cav1), in prostate cancer cells differentially expressing CAVIN1 (also known as PTRF), that is also required for caveolae formation. High degree (strongly-interacting) points were removed by an iterative blink merging algorithm and Cav1 network properties were compared with randomly generated networks to retain a sub-network of geometric structures (or blobs). Machine-learning based classification extracted 28 quantitative features describing the size, shape, topology and network characteristics of ∼80,000 blobs. Unsupervised clustering identified small S1A scaffolds corresponding to SDS-resistant Cav1 oligomers, as yet undescribed larger hemi-spherical S2 scaffolds and, only in CAVIN1-expressing cells, spherical, hollow caveolae. Multi-threshold modularity analysis suggests that S1A scaffolds interact to form larger scaffolds and that S1A dimers group together, in the presence of CAVIN1, to form the caveolae coat.

Activation of Human Natural Killer Cells by Graphene Oxide-Templated Antibody Nanoclusters

An emerging new paradigm is that immune cell activation is controlled by transient interactions between supramolecular assemblies of receptors and ligands. Current immunotherapy biologic pharmaceuticals that activate or desensitize NK cells are, however, individual molecules that do not replicate this nanoscale organization of proteins. Here, we use nanoscale graphene oxide (NGO) as a template to generate soluble nanoscale clusters of Natural Killer cell-activating antibodies. We control nanocluster size and molecular number to mimic reported values for cell surface proteins. These NGO-templated molecular nanoclusters, used to stimulate NK cells via the CD16 receptor, successfully induced cellular activation, indicated by degranulation of cytolytic granules and IFN-γ secretion. Importantly, activation significantly exceeded that induced by the same antibodies applied as a solution of individual molecules. These results demonstrate that future immunotherapies could be enhanced by assembling immunomodulatory drugs into nanoclusters and establish NGO-templating as a candidate technology.

Single-Molecule Light-Sheet Imaging of Suspended T Cells

Adaptive immune responses are initiated by triggering of the T cell receptor. Single-molecule imaging based on total internal reflection fluorescence microscopy at coverslip/basal cell interfaces is commonly used to study this process. These experiments have suggested, unexpectedly, that the diffusional behavior and organization of signaling proteins and receptors may be constrained before activation. However, it is unclear to what extent the molecular behavior and cell state is affected by the imaging conditions, i.e., by the presence of a supporting surface. In this study, we implemented single-molecule light-sheet microscopy, which enables single receptors to be directly visualized at any plane in a cell to study protein dynamics and organization in live, resting T cells. The light sheet enabled the acquisition of high-quality single-molecule fluorescence images that were comparable to those of total internal reflection fluorescence microscopy. By comparing the apical and basal surfaces of surface-contacting T cells using single-molecule light-sheet microscopy, we found that most coated-glass surfaces and supported lipid bilayers profoundly affected the diffusion of membrane proteins (T cell receptor and CD45) and that all the surfaces induced calcium influx to various degrees. Our results suggest that, when studying resting T cells, surfaces are best avoided, which we achieve here by suspending cells in agarose.

Spatial and Chemical Surface Guidance of NK Cell Cytotoxic Activity

Studying how different signaling pathways spatially integrate in cells requires selective manipulation and control of different transmembrane ligand-receptor pairs at the same time. This work explores a novel method for precisely arranging two arbitrarily chosen ligands on a micron-scale two-dimensional pattern. The approach is based on lithographic patterning of Au and TiO₂ films, followed by their selective functionalization with Ni-nitrilotriacetic acid-histidine and biotin-avidin chemistries, respectively. The selectivity of chemical and biological functionalizations is demonstrated by X-ray photoelectron spectroscopy and immunofluorescence imaging, respectively. This approach is applied to produce the first type of bifunctional surfaces with controllably positioned ligands for activating the receptors of natural killer (NK) immune cells. NK cells were used as a model system to demonstrate the potency of the surface in guiding site-selective cell attachment and activation. Upon applying the suitable ligand or ligand combination, the surfaces guided the appropriate single- or bifunctional attachment and activation. These encouraging results demonstrate the effectiveness of the system as an experimental platform aimed at the comprehensive understanding of the immunological synapse. The great simplicity, modularity, and specificity of this approach make it applicable for a myriad of combinations of other biomolecules and applications, turning it into the "Swiss knife" of biointerfaces.

Natural killer cell cytotoxicity and its regulation by inhibitory receptors

Natural killer (NK) cells express an array of germ-line encoded receptors that are capable of triggering cytotoxicity. NK cells tend to express many members of a given family of signalling molecules. The presence of many activating receptors and many members of a given family of signalling molecules can enable NK cells to detect different kinds of target cells, and to mount different kinds of responses. This contributes also to the robustness of NK cells responses; cytotoxic functions of NK cells often remain unaffected in the absence of selected signalling molecules. NK cells express many MHC-I-specific inhibitory receptors. Signals from MHC-I-specific inhibitory receptors tightly control NK cell cytotoxicity and, paradoxically, maintain NK cells in a state of proper responsiveness. This review provides a brief overview of the events that underlie NK cell activation, and how signals from inhibitory receptors intercept NK cell activation to prevent inappropriate triggering of cytotoxicity.

A nanoscale reorganization of the IL-15 receptor is triggered by NKG2D in a ligand-dependent manner

Natural killer group 2D (NKG2D), an activating receptor on natural killer (NK) cells and a subset of T cells, recognizes stress-inducible proteins, including MICA and ULBP2, which are present on infected or transformed cells. Whether each NKG2D ligand (NKG2DL) has a distinct biological role is not clear. Using superresolution microscopy, we found that NKG2D is constitutively arranged in nanoclusters at the surface of human primary NK cells. Nanoclusters of NKG2D became smaller upon ligation with MICA but became larger upon activation by ULBP2. In addition, ULBP2 induced the reorganization of nanoclusters of the cytokine receptor subunit for both interleukin-2 (IL-2) and IL-15 (IL-2/IL-15Rβ), such that these cytokine receptor subunits coalesced with nanoclusters of NKG2D. Functionally, the response of NK cells activated by ULBP2 was augmented by an interaction between ULBP2-bound NKG2D and IL-15R ligated by IL-15 (trans-presented by IL-15Rα-coated surfaces). These data suggest that NKG2DLs are not equivalent in their capacity to activate NKG2D and establish a previously unknown paradigm in how ligand-induced changes to the nanoscale organization of the cell surface can affect immune responses.

Single-Molecule Localization and Structured Illumination Microscopy of Platelet Proteins

Superresolution microscopy has become increasingly widespread over the past 5 years and allows users to image biological processes below the diffraction limit of traditional fluorescence microscopy where resolution is restricted to approximately 250 nm. Superresolution refers to a wide range of techniques which employ different approaches to circumvent the diffraction limit. Two of these approaches, structured illumination microscopy (SIM) and single-molecule localization microscopy (SMLM), which provide a doubling and tenfold increase in resolution respectively, are dominating the field. This is partly because of the insights into biology they offer and partly because of their commercialization by the main microscope manufacturers. This chapter provides background to the two techniques, practical considerations for their use, and protocols for their application to platelet biology.

Membrane nanoclusters of FcγRI segregate from inhibitory SIRPα upon activation of human macrophages

Lopes et al. use superresolution microscopy to visualize the nanoscale organization of activating and inhibitory receptors on human macrophages. Nanoclusters of inhibitory SIRPα and activating FcγRI associate in the cell’s resting state, but engagement of FcγRI induces their segregation.

Signal integration between activating Fc receptors and inhibitory signal regulatory protein α (SIRPα) controls macrophage phagocytosis. Here, using dual-color direct stochastic optical reconstruction microscopy, we report that Fcγ receptor I (FcγRI), FcγRII, and SIRPα are not homogeneously distributed at macrophage surfaces but are organized in discrete nanoclusters, with a mean radius of 71 ± 11 nm, 60 ± 6 nm, and 48 ± 3 nm, respectively. Nanoclusters of FcγRI, but not FcγRII, are constitutively associated with nanoclusters of SIRPα, within 62 ± 5 nm, mediated by the actin cytoskeleton. Upon Fc receptor activation, Src-family kinase signaling leads to segregation of FcγRI and SIRPα nanoclusters to be 197 ± 3 nm apart. Co-ligation of SIRPα with CD47 abrogates nanocluster segregation. If the balance of signals favors activation, FcγRI nanoclusters reorganize into periodically spaced concentric rings. Thus, a nanometer- and micron-scale reorganization of activating and inhibitory receptors occurs at the surface of human macrophages concurrent with signal integration.

A Bayesian cluster analysis method for single-molecule localization microscopy data

Cell function is regulated by the spatiotemporal organization of the signaling machinery, and a key facet of this is molecular clustering. Here, we present a protocol for the analysis of clustering in data generated by 2D single-molecule localization microscopy (SMLM)-for example, photoactivated localization microscopy (PALM) or stochastic optical reconstruction microscopy (STORM). Three features of such data can cause standard cluster analysis approaches to be ineffective: (i) the data take the form of a list of points rather than a pixel array; (ii) there is a non-negligible unclustered background density of points that must be accounted for; and (iii) each localization has an associated uncertainty in regard to its position. These issues are overcome using a Bayesian, model-based approach. Many possible cluster configurations are proposed and scored against a generative model, which assumes Gaussian clusters overlaid on a completely spatially random (CSR) background, before every point is scrambled by its localization precision. We present the process of generating simulated and experimental data that are suitable to our algorithm, the analysis itself, and the extraction and interpretation of key cluster descriptors such as the number of clusters, cluster radii and the number of localizations per cluster. Variations in these descriptors can be interpreted as arising from changes in the organization of the cellular nanoarchitecture. The protocol requires no specific programming ability, and the processing time for one data set, typically containing 30 regions of interest, is ∼18 h; user input takes ∼1 h.

Clus-DoC: a combined cluster detection and colocalization analysis for single-molecule localization microscopy data

Advances in fluorescence microscopy are providing increasing evidence that the spatial organization of proteins in cell membranes may facilitate signal initiation and integration for appropriate cellular responses. Our understanding of how changes in spatial organization are linked to function has been hampered by the inability to directly measure signaling activity or protein association at the level of individual proteins in intact cells. Here we solve this measurement challenge by developing Clus-DoC, an analysis strategy that quantifies both the spatial distribution of a protein and its colocalization status. We apply this approach to the triggering of the T-cell receptor during T-cell activation, as well as to the functionality of focal adhesions in fibroblasts, thereby demonstrating an experimental and analytical workflow that can be used to quantify signaling activity and protein colocalization at the level of individual proteins.

Critical importance of appropriate fixation conditions for faithful imaging of receptor microclusters

Receptor clustering is known to trigger signalling events that contribute to critical changes in cellular functions. Faithful imaging of such clusters by means of fluorescence microscopy relies on the application of adequate cell fixation methods prior to immunolabelling in order to avoid artefactual redistribution by the antibodies themselves. Previous work has highlighted the inadequacy of fixation with paraformaldehyde (PFA) alone for efficient immobilisation of membrane-associated molecules, and the advantages of fixation with PFA in combination with glutaraldehyde (GA). Using fluorescence microscopy, we here highlight how inadequate fixation can lead to the formation of artefactual clustering of receptors in lymphatic endothelial cells, focussing on the transmembrane hyaluronan receptors LYVE-1 and CD44, and the homotypic adhesion molecule CD31, each of which displays their native diffuse surface distribution pattern only when visualised with the right fixation techniques, i.e. PFA/GA in combination. Fluorescence recovery after photobleaching (FRAP) confirms that the artefactual receptor clusters are indeed introduced by residual mobility. In contrast, we observed full immobilisation of membrane proteins in cells that were fixed and then subsequently permeabilised, irrespective of whether the fixative was PFA or PFA/GA in combination. Our study underlines the importance of choosing appropriate sample preparation protocols for preserving authentic receptor organisation in advanced fluorescence microscopy.

Summary: Commonly used fixation protocols during immunolabelling can result in artefactual protein distribution. We highlight the artefacts in images and provide fixation conditions for studying membrane receptor organisation.

IL-2 in the tumor microenvironment is necessary for Wiskott-Aldrich syndrome protein deficient NK cells to respond to tumors in vivo

To kill target cells, natural killer (NK) cells organize signaling from activating and inhibitory receptors to form a lytic synapse. Wiskott-Aldrich syndrome (WAS) patients have loss-of-function mutations in the actin regulator WASp and suffer from immunodeficiency with increased risk to develop lymphoreticular malignancies. NK cells from WAS patients fail to form lytic synapses, however, the functional outcome in vivo remains unknown. Here, we show that WASp KO NK cells had decreased capacity to degranulate and produce IFNγ upon NKp46 stimulation and this was associated with reduced capacity to kill MHC class I-deficient hematopoietic grafts. Pre-treatment of WASp KO NK cells with IL-2 ex vivo restored degranulation, IFNγ production, and killing of MHC class I negative hematopoietic grafts. Moreover, WASp KO mice controlled growth of A20 lymphoma cells that naturally produced IL-2. WASp KO NK cells showed increased expression of DNAM-1, LAG-3, and KLRG1, all receptors associated with cellular exhaustion and NK cell memory. NK cells isolated from WAS patient spleen cells showed increased expression of DNAM-1 and had low to negative expression of CD56, a phenotype associated with NK cells exhaustion. Finally, in a cohort of neuroblastoma patients we identified a strong correlation between WASp, IL-2, and patient survival.

Human NK cell development requires CD56-mediated motility and formation of the developmental synapse

While distinct stages of natural killer (NK) cell development have been defined, the molecular interactions that shape human NK cell maturation are poorly understood. Here we define intercellular interactions between developing NK cells and stromal cells which, through contact-dependent mechanisms, promote the generation of mature, functional human NK cells from CD34(+) precursors. We show that developing NK cells undergo unique, developmental stage-specific sustained and transient interactions with developmentally supportive stromal cells, and that the relative motility of NK cells increases as they move through development in vitro and ex vivo. These interactions include the formation of a synapse between developing NK cells and stromal cells, which we term the developmental synapse. Finally, we identify a role for CD56 in developmental synapse structure, NK cell motility and NK cell development. Thus, we define the developmental synapse leading to human NK cell functional maturation.

Superresolution imaging reveals nanometer- and micrometer-scale spatial distributions of T-cell receptors in lymph nodes

T cells become activated when T-cell receptors (TCRs) recognize agonist peptides bound to major histocompatibility complex molecules on antigen-presenting cells. T-cell activation critically relies on the spatiotemporal arrangements of TCRs on the plasma membrane. However, the molecular organizations of TCRs on lymph node-resident T cells have not yet been determined, owing to the diffraction limit of light. Here we visualized nanometer- and micrometer-scale TCR distributions in lymph nodes by light sheet direct stochastic optical reconstruction microscopy (dSTORM) and structured illumination microscopy (SIM). This dSTORM and SIM approach provides the first evidence, to our knowledge, of multiscale reorganization of TCRs during in vivo immune responses. We observed nanometer-scale plasma membrane domains, known as protein islands, on naïve T cells. These protein islands were enriched within micrometer-sized surface areas that we call territories. In vivo T-cell activation caused the TCR territories to contract, leading to the coalescence of protein islands and formation of stable TCR microclusters.

The Size of Activating and Inhibitory Killer Ig-like Receptor Nanoclusters Is Controlled by the Transmembrane Sequence and Affects Signaling

Super-resolution microscopy has revealed that immune cell receptors are organized in nanoscale clusters at cell surfaces and immune synapses. However, mechanisms and functions for this nanoscale organization remain unclear. Here, we used super-resolution microscopy to compare the surface organization of paired killer Ig-like receptors (KIR), KIR2DL1 and KIR2DS1, on human primary natural killer cells and cell lines. Activating KIR2DS1 assembled in clusters two-fold larger than its inhibitory counterpart KIR2DL1. Site-directed mutagenesis established that the size of nanoclusters is controlled by transmembrane amino acid 233, a lysine in KIR2DS1. Super-resolution microscopy also revealed two ways in which the nanoscale clustering of KIR affects signaling. First, KIR2DS1 and DAP12 nanoclusters are juxtaposed in the resting cell state but coalesce upon receptor ligation. Second, quantitative super-resolution microscopy revealed that phosphorylation of the kinase ZAP-70 or phosphatase SHP-1 is favored in larger KIR nanoclusters. Thus, the size of KIR nanoclusters depends on the transmembrane sequence and affects downstream signaling.

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Activating and inhibitory NK cell receptors have a distinct nanoscale organization

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The transmembrane sequence of KIR controls their nanoscale organization

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Nanoclusters of KIR2DS1 and its adaptor are juxtaposed but mix upon activation

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Phosphorylation of ZAP-70 or SHP-1 is favored in larger receptor nanoclusters