Single-molecule (SM) imaging (SMI)-based approaches have the powerful ability to capture receptor interactions - necessary for cell signaling - in their native live-cell environment. Yet, due to substoichiometric labeling, SMI generally provides only partial information on these interactions. We developed Deep-FISIK, which utilizes graph neural networks and multi-head attention for message-passing, to predict from SMI data the kinetics of homotypic interactions of the full receptor system. The input to Deep-FISIK are the SM detections in SMI experiments, without the need for explicit tracking. Thus, Deep-FISIK is compatible with labeling a higher fraction of receptors in the SMI experiments, increasing the prediction accuracy of the interaction kinetics parameters. Deep-FISIK's performance is robust in the presence of a variety of deviations from the training data, indicating Deep-FISIK's applicability to many receptor systems and SMI experiments.

Submembrane cortical actin (CA) plays a large role in regulating the dynamic organization of cell surface receptors, which in turn regulates receptor signaling. Many receptors have short intracellular domains and no known link to actin. Here, we identified the β1-integrin subunit and several tetraspanins (CD9, CD81, and CD151) as part of the hitherto unknown molecular link between the receptor CD36 and CA. Our data indicate that CD36 in vascular endothelial cells interacts with these proteins, with stronger interactions near the cell edge. Compromising these interactions via the point mutation G12V in the N-terminal transmembrane domain of CD36 alters the dynamic organization of CD36 on the cell surface and weakens its coupling to CA dynamics. Moreover, it abolishes thrombospondin-1-induced CD36 signaling through the Src family kinase Fyn. Given their many interactions with transmembrane proteins, tetraspanins and integrins may provide a ubiquitous mechanism for plasma membrane-CA coupling.

Single-pass transmembrane proteins neuroligin (NL) and neurexin (NRX) constitute a pair of synaptic adhesion molecules that are essential for the formation of functional synapses. Binding affinities vary by ~1000-fold between combinations of NL and NRX subtypes, which contribute to chemical and spatial specificities. Among major NL-NRX subtypes, NL2 and NRXβ1 have the lowest affinity. Here, we report structures of NL2 in complex with NRXβ1 in several conformations, along with NL2 alone. We identify mechanisms underlying the modulation of NL-NRX affinities and how the weaker NL2-NRXβ1 interaction alone is capable of tethering lipid membranes. We further show that NL2 and NRXβ1 cluster at intercellular junctions and recruit the master postsynaptic scaffolding protein gephyrin, which further clusters neurotransmitter receptors. These findings suggest a dual role of the NL2-NRXβ1 interaction—both as mechanical tether and as signaling receptor—to ensure correct spatial and chemical coordination between two cells to generate functional synapses.

Inter-receptor interactions play a key role in cell signaling in response to external stimuli. For quantitative understanding and modeling of transmembrane signal transduction, it is necessary to quantify receptor interaction kinetics (i.e., association and dissociation rate constants) on the cell surface. Live-cell single-molecule imaging (SMI) has the powerful ability to capture transient receptor interaction events in their native cellular environment with high spatiotemporal resolution. However, it reveals these interactions for the labeled subset only, which is a small fraction of the full population of receptors. We have previously shown that mathematical modeling, combined with SMI data, offers a route to compensate for this lost information and infer the population-level receptor interaction kinetics from SMI data. Here, we applied this approach to vascular endothelial growth factor receptor 2 (VEGFR2), both wild-type full-length VEGFR2 (FLR2)—the dimerization of which is necessary for activation—and a truncated mutant consisting of the extracellular and transmembrane domains (ECTM), which has been shown to exhibit reduced homotypic interactions in the absence of ligand. We developed a stochastic mathematical model mimicking VEGFR2 diffusion and homotypic interactions and determined the unknown model parameters (most importantly, association and dissociation rate constants) through a combination of direct experimental measurements and stochastic model calibration. As expected, we found that ECTM was primarily monomeric, while FLR2 exhibited substantial reversible dimerization. Importantly, our inference revealed that the difference between FLR2 and ECTM was primarily in their dimer association rate constant, which was about an order of magnitude higher for FLR2 than for ECTM. To our knowledge, this is the first time that the dimerization kinetics of VEGFR2, i.e., its association and dissociation rate constants, have been measured in intact live cells.

Inter-receptor interactions play a key role in receptor signaling, which is the first step in cell signaling in response to external stimuli. In the case of Vascular Endothelial Growth Factor Receptor 2 (VEGFR2), dimerization is necessary for activation. VEGFR2 undergoes reversible interactions also in the absence of ligand. For a quantitative understanding of transmembrane signal transduction, it is necessary to quantify the interaction kinetics of VEGFR2 on the cell surface. Live-cell single-molecule imaging (SMI) has the powerful ability to capture receptor interaction events in their native cellular environment with high spatiotemporal resolution. However, it reveals these interactions for only the labeled subset, which is a small fraction of the full population of receptors. We have previously shown that mathematical modeling, combined with SMI data, offers a route to compensate for this lost information and infer the population-level receptor interaction kinetics from SMI data. Here, we applied this approach to VEGFR2, both wildtype full length VEGFR2 (FLR2) and a truncated mutant consisting of its extracellular and transmembrane domains (ECTM), which has been shown to exhibit reduced homotypic interactions in the absence of ligand. We developed a stochastic mathematical model mimicking VEGFR2 diffusion and interactions and determined the unknown model parameters through a combination of direct experimental measurements and stochastic model calibration. We found that a model of dimerization was sufficient to describe VEGFR2 interactions in the absence of ligand. While ECTM was primarily monomeric, FLR2 exhibited a substantial fraction of dimers. Our inference revealed that the difference between FLR2 and ECTM was primarily in the dimer association rate constant, which was about an order of magnitude lower for ECTM than for FLR2. To our knowledge, this is the first time that the interaction kinetics of VEGFR2 have been calculated in live cells.

Signal transduction is a fundamental process that enables cells to adapt to external cues and organize adequate responses including survival, death, growth, and homeostasis. A key mechanism modulating signal transduction relies on the formation of multimolecular complexes optimized for specificity, modularity and signal amplification. The scavenger receptor CD36, which binds diverse ligands in different cellular contexts, illustrates this principle. To uncover the nature of CD36 multimolecular complexes, we employed a proximity biotinylation labeling approach on human endothelial cells, where CD36 binds to thrombospondin-1 (TSP-1) to initiate a signaling cascade promoting programmed cell death. Using biotin capture and mass spectrometry protein identification, we uncovered a list of proteins in the vicinity of CD36. This list of candidates was refined by proximity ligation assays. The relationship between key CD36 interacting molecules, in particular active integrin beta-1 (ITGB1) and CD9, was further decoded by conditional colocalization analysis, providing support for their association within a tri-molecular complex. The implication of selected candidates in the signaling function of CD36 was further evaluated using shRNA knockdown, revealing that active ITGB1 is essential for Fyn activation downstream of CD36, with the tetraspanin playing a connecting role between CD36 and active ITGB1. Our approach to investigating CD36 complexes emphasizes the complexity and fundamental role of protein-protein interactions and coordination in the context of transmembrane signal transduction.

Plasticity is a hallmark function of cancer cells, but many of the underlying mechanisms have yet to be discovered. In this study, we identify Caveolin-1, a scaffolding protein that organizes plasma membrane domains, as a context-dependent regulator of survival signaling in Ewing sarcoma (EwS). Single cell analyses reveal a distinct subpopulation of EwS cells, which highly express the surface marker CD99 as well as Caveolin-1. CD99 High cells exhibit distinct morphology, gene expression, and enhanced survival capabilities compared to CD99 Low cells, both under chemotherapeutic challenge and in vivo. Mechanistically, we show that elevated Caveolin-1 expression in CD99 High cells orchestrates PI3K/AKT survival signaling by modulating the spatial organization of PI3K activity at the cell surface. Notably, CD99 itself is not directly involved in this pathway, making it a useful independent marker for identifying these subpopulations. We propose a model where the CD99 High state establishes a Cav-1-driven signaling network to support cell survival that is distinct from the survival mechanisms of CD99 Low cells. This work reveals a dynamic state transition in EwS cells and highlights Caveolin-1 as a key driver of context-specific survival signaling.

The spatiotemporal organization of cell surface receptors is crucial for signaling, with cortical actin (CA) playing a pivotal role. Quantifying how CA architecture and dynamics affect cell surface receptor organization is challenging due to the high density of CA. To address this, we developed SMI-FSM, a multiscale imaging and computational analysis pipeline combining single-molecule imaging (SMI) of plasma membrane (PM) proteins and fluorescent speckle microscopy (FSM) of CA. SMI-FSM enables high-resolution characterization of the PM proteins' spatiotemporal organization in relation with CA architecture and dynamics.

Single-pass transmembrane proteins neuroligin (NL) and neurexin (NRX) constitute a pair of synaptic adhesion molecules (SAMs) that are essential for the formation of functional synapses. Binding affinities vary by ∼ 1000 folds between arrays of NL and NRX subtypes, which contribute to chemical and spatial specificities. Current structures are obtained with truncated extracellular domains of NL and NRX and are limited to the higher-affinity NL1/4-NRX complexes. How NL-NRX interaction leads to functional synapses remains unknown. Here we report structures of full-length NL2 alone, and in complex with NRX1β in several conformations, which has the lowest affinity among major NL-NRX subtypes. We show how conformational flexibilities may help in adapting local membrane geometry, and reveal mechanisms underlying variations in NL-NRX affinities modulation. We further show that, despite lower affinity, NL2-NRX1β interaction alone is capable of tethering different lipid membranes in total reconstitution, and that NL2 and NRX1β cluster at inter-cellular junctions without the need of other synaptic components. In addition, NL2 combines with the master post-synaptic scaffolding protein gephyrin and clusters neurotransmitter receptors at cellular membrane. These findings suggest dual roles of NL2 - NRX1β interaction - both as mechanical tether, and as signaling receptors, to ensure correct spatial and chemical coordination between two cells to generate function synapses.

Colocalization analysis of multicolor microscopy images is a cornerstone approach in cell biology. It provides information on the localization of molecules within subcellular compartments and allows the interrogation of known molecular interactions in their cellular context. However, almost all colocalization analyses are designed for two-color images, limiting the type of information that they reveal. Here, we describe an approach, termed "conditional colocalization analysis," for analyzing the colocalization relationships between three molecular entities in three-color microscopy images. Going beyond the question of whether colocalization is present or not, it addresses the question of whether the colocalization between two entities is influenced, positively or negatively, by their colocalization with a third entity. We benchmark the approach and showcase its application to investigate receptor-downstream adaptor colocalization relationships in the context of functionally relevant plasma membrane locations. The software for conditional colocalization analysis is available at https://github.com/kjaqaman/conditionalColoc.

The spatiotemporal organization of cell surface receptors is important for cell signaling. Cortical actin (CA), the subset of the actin cytoskeleton subjacent to the plasma membrane (PM), plays a large role in cell surface receptor organization. However, this has been shown largely through actin perturbation experiments, which raise concerns of nonspecific effects and preclude quantification of actin architecture and dynamics under unperturbed conditions. These limitations make it challenging to predict how changes in CA properties can affect receptor organization. To derive direct relationships between the architecture and dynamics of CA and the spatiotemporal organization of PM proteins, including cell surface receptors, we developed a multi scale imaging and computational analysis framework based on the integration of single-molecule imaging (SMI) of PM proteins and fluorescent speckle microscopy (FSM) of CA (combined: SMI-FSM) in the same live cell. SMI-FSM revealed differential relationships between PM proteins and CA based on the PM proteins' actin binding ability, diffusion type, and local CA density. Combining SMI-FSM with subcellular region analysis revealed differences in CA dynamics that were predictive of differences in PM protein mobility near ruffly cell edges versus closer to the cell center. SMI-FSM also highlighted the complexity of cell wide actin perturbation, where we found that global changes in actin properties caused by perturbation were not necessarily reflected in the CA properties near PM proteins, and that the changes in PM protein properties upon perturbation varied based on the local CA environment. Given the widespread use of SMI as a method to study the spatiotemporal organization of PM proteins and the versatility of SMI-FSM, we expect it to be widely applicable to enable future investigation of the influence of CA architecture and dynamics on different PM proteins, especially in the context of actin-dependent cellular processes.

The epidermal growth factor receptor (EGFR) is a central regulator of cell physiology. EGFR is activated by ligand binding, triggering receptor dimerization, activation of kinase activity, and intracellular signaling. EGFR is transiently confined within various plasma membrane nanodomains, yet how this may contribute to regulation of EGFR ligand binding is poorly understood. To resolve how EGFR nanoscale compartmentalization gates ligand binding, we developed single-particle tracking methods to track the mobility of ligand-bound and total EGFR, in combination with modeling of EGFR ligand binding. In comparison to unliganded EGFR, ligand-bound EGFR is more confined and distinctly regulated by clathrin and tetraspanin nanodomains. Ligand binding to unliganded EGFR occurs preferentially in tetraspanin nanodomains, and disruption of tetraspanin nanodomains impairs EGFR ligand binding and alters the conformation of the receptor’s ectodomain. We thus reveal a mechanism by which EGFR confinement within tetraspanin nanodomains regulates receptor signaling at the level of ligand binding.

A new geometric deep learning method can reconstruct cellular and subcellular trajectories and characterize mobility in microscopic imaging, for a broad range of challenging scenarios.

The dynamic organization of cell surface receptors plays an important role in signaling. Here we investigated the spatiotemporal organization of VEGF receptor-2 (VEGFR-2), a critical pro-angiogenic receptor tyrosine kinase in live, microvascular endothelial cells. Our study strategy combined live-cell single-molecule imaging of endogenous VEGFR-2 with computational image analysis and multiscale data analysis. We found that VEGFR-2, even in its basal, unstimulated state, possesses diffusion heterogeneity, with a mobile subpopulation and a subpopulation of restricted mobility, and assembly state heterogeneity, where receptors can be organized as monomeric or non-monomeric.

Cell surface receptor organization is influenced by many components that crowd the plasma membrane, one of which is the actin cortex (AC). While the AC is a dynamic structure, most studies to date investigating how the AC influences cell surface receptor organization have not been able to access cortical actin dynamics. The reasons are that many studies perturb the actin cytoskeleton to infer its role on receptor organization, which precludes any quantification of actin dynamics in the absence of perturbation (in addition to cytotoxicity concerns), and that the AC is too dense to resolve with conventional light microscopy.

CD36 is a cell surface receptor whose organization and signaling in multiple cell types have been shown to depend on the actin cortex, although largely through actin perturbation experiments. Perturbation experiments raise concerns of nonspecific effects, and preclude any quantification of actin dynamics. Thus, to derive explicit relationships between cell surface CD36 organization and actin cortex dynamics simultaneously in live unperturbed cells, we developed a novel imaging and computational analysis framework capable of integrating single-molecule imaging of receptor behavior and fluorescent speckle microscopy of actin cortex dynamics (SMI-FSM).

Clustering is a prominent feature of receptors at the plasma membrane (PM). It plays an important role in signaling. Liquid-liquid phase separation (LLPS) of proteins is emerging as a novel mechanism underlying the observed clustering. Receptors/transmembrane signaling proteins can be core components essential for LLPS (such as LAT or nephrin) or clients enriched at the phase-separated condensates (for example, at the postsynaptic density or at tight junctions). Condensate formation has been shown to regulate signaling in multiple ways, including by increasing protein binding avidity and by modulating the local biochemical environment. In moving forward, it is important to study protein LLPS at the PM of living cells, its interplay with other factors underlying receptor clustering, and its signaling and functional consequences.

Nuclear lamin isoforms form fibrous meshworks associated with nuclear pore complexes (NPCs). Using datasets prepared from subpixel and segmentation analyses of 3D-structured illumination microscopy images of WT and lamin isoform knockout mouse embryo fibroblasts, we determined with high precision the spatial association of NPCs with specific lamin isoform fibers. These relationships are retained in the enlarged lamin meshworks of Lmna-/- and Lmnb1-/- fibroblast nuclei. Cryo-ET observations reveal that the lamin filaments composing the fibers contact the nucleoplasmic ring of NPCs. Knockdown of the ring-associated nucleoporin ELYS induces NPC clusters that exclude lamin A/C fibers but include LB1 and LB2 fibers. Knockdown of the nucleoporin TPR or NUP153 alters the arrangement of lamin fibers and NPCs. Evidence that the number of NPCs is regulated by specific lamin isoforms is presented. Overall the results demonstrate that lamin isoforms and nucleoporins act together to maintain the normal organization of lamin meshworks and NPCs within the nuclear envelope.