Phagocytic receptors must diffuse laterally to become activated upon clustering by multivalent targets. Receptor diffusion, however, can be obstructed by transmembrane proteins ("pickets") that are immobilized by interacting with the cortical cytoskeleton. The molecular identity of these pickets and their role in phagocytosis have not been defined. We used single-molecule tracking to study the interaction between Fcγ receptors and CD44, an abundant transmembrane protein capable of indirect association with F-actin, hence likely to serve as a picket. CD44 tethers reversibly to formin-induced actin filaments, curtailing receptor diffusion. Such linear filaments predominate in the trailing end of polarized macrophages, where receptor mobility was minimal. Conversely, receptors were most mobile at the leading edge, where Arp2/3-driven actin branching predominates. CD44 binds hyaluronan, anchoring a pericellular coat that also limits receptor displacement and obstructs access to phagocytic targets. Force must be applied to traverse the pericellular barrier, enabling receptors to engage their targets.

Molecular interactions are often transient and might change within the window of observation, leading to changes in molecule movement. Therefore, accurate motion analysis often requires transient motion classification. Here we present an accurate and computationally efficient transient mobility analysis framework, termed "divide-and-conquer moment scaling spectrum" (DC-MSS). DC-MSS works in a multistep fashion: 1) it utilizes a local movement descriptor throughout a track to divide it into initial segments of putatively different motion classes; 2) it classifies these segments via moment scaling spectrum (MSS) analysis of molecule displacements; and 3) it uses the MSS analysis results to refine the track segmentation. This strategy uncouples the initial identification of motion switches from motion classification, allowing DC-MSS to circumvent the sensitivity-accuracy tradeoff of classic rolling window approaches for transient motion analysis, while at the same time harnessing the classification power of MSS analysis. Testing of DC-MSS demonstrates that it detects switches among free diffusion, confined diffusion, directed diffusion, and immobility with great sensitivity. To illustrate the utility of DC-MSS, we have applied it to single-particle tracks of the transmembrane protein CD44 on the surface of macrophages, revealing actin cortex-dependent transient mobility changes.

During T cell activation, biomolecular condensates form at the immunological synapse (IS) through multivalency-driven phase separation of LAT, Grb2, Sos1, SLP-76, Nck, and WASP. These condensates move radially at the IS, traversing successive radially-oriented and concentric actin networks. To understand this movement, we biochemically reconstituted LAT condensates with actomyosin filaments. We found that basic regions of Nck and N-WASP/WASP promote association and co-movement of LAT condensates with actin, indicating conversion of weak individual affinities to high collective affinity upon phase separation. Condensates lacking these components were propelled differently, without strong actin adhesion. In cells, LAT condensates lost Nck as radial actin transitioned to the concentric network, and engineered condensates constitutively binding actin moved aberrantly. Our data show that Nck and WASP form a clutch between LAT condensates and actin in vitro and suggest that compositional changes may enable condensate movement by distinct actin networks in different regions of the IS.

Nanoclustering is an emerging organizational principle for membraneassociated proteins. The functional consequences of nanoclustering for receptor signaling remain largely unknown. Here, we applied quantitative multi-channel high-and super-resolution imaging to analyze the endothelial cell surface receptor CD36, the clustering of which upon binding to multivalent ligands, such as the anti-angiogenic factor thrombospondin-1 (TSP-1), is thought to be crucial for signaling. We found that a substantial fraction of unligated CD36 exists in nanoclusters, which not only promote TSP-1 binding but are also enriched with the downstream effector Fyn. Exposure to multivalent ligands (TSP-1 or anti-CD36 IgM) that result in larger and denser CD36 clusters activates Fyn. Conversely, pharmacological perturbations that prevent the enhancement of CD36 clustering by TSP-1 abrogate Fyn activation. In both cases, there is no detectable change in Fyn enrichment at CD36 nanoclusters. These observations reveal a crucial role for the basal organization of a receptor into nanoclusters that are enriched with the signal-transducing downstream effectors of that receptor, such that enhancement of clustering by multivalent ligands is necessary and sufficient to activate the downstream effector without the need for its de novo recruitment.

No abstract

Biomolecular condensates play important roles in eukaryotic cells by concentrating molecules into foci without a surrounding membrane. During T cell activation, biomolecular condensates form at the immunological synapse (IS) through multivalency-driven phase separation of the adaptor protein LAT and its binding partners Grb2, Sos1, SLP-76, Nck and WASP. These condensates move radially at the IS, traversing a radially-oriented and then a concentric actin network. To understand the persistent radial movement, we biochemically reconstituted LAT condensates with mobile actomyosin filaments. We found that basic regions of Nck and N-WASP promote strong association and co-movement of LAT condensates with actin. Condensates lacking these components were instead propelled by steric interactions. In cells, LAT condensates lost Nck while traversing the boundary between the two actin networks, and condensates engineered to constitutively bind actin moved aberrantly. We propose that Nck and WASP form a clutch between LAT condensates and actin, and changes in composition enable condensate movement by distinct actin networks in different regions of the IS.

SUMMARY The dynamic nanoscale organization of cell surface receptors plays an important role in signaling. We determine this organization and its relation to activation of VEGF receptor-2 (VEGFR-2), a critical receptor tyrosine kinase in endothelial cells (ECs), by combining single-molecule imaging of endogenous VEGFR-2 in live ECs with multiscale computational analysis. We find that surface VEGFR-2 can be mobile or exhibit restricted mobility and be monomeric or non-monomeric, with a complex interplay between the two. This basal heterogeneity results in heterogeneity in the sequence of steps leading to VEGFR-2 activation by VEGF. Specifically, we find that VEGF can bind to monomeric and non-monomeric VEGFR-2 and that, when binding to monomeric VEGFR-2, its effect on dimerization depends on the mobility of VEGFR-2. Our study highlights the dynamic and heterogeneous nature of cell surface receptor organization and the need for multiscale, single-molecule-based analysis to determine its relationship to receptor activation and signaling.

Although pathology of tauopathies is characterized by abnormal tau protein aggregation in both gray and white matter regions of the brain, neuropathological investigations have generally focused on abnormalities in the cerebral cortex because the canonical aggregates that form the diagnostic criteria for these disorders predominate there. This corticocentric focus tends to deemphasize the relevance of the more complex white matter pathologies, which remain less well characterized and understood. We took a data-driven machine-learning approach to identify novel disease-specific morphologic signatures of white matter aggregates in three tauopathies: Alzheimer disease (AD), progressive supranuclear palsy (PSP), and corticobasal degeneration (CBD). We developed automated approaches using whole slide images of tau immunostained sections from 49 human autopsy brains (16 AD,13 CBD, 20 PSP) to identify cortex/white matter regions and individual tau aggregates, and compared tau-aggregate morphology across these diseases. Tau burden in the gray and white matter for individual subjects strongly correlated in a highly disease-specific fashion. We discovered previously unrecognized tau morphologies for AD, CBD and PSP that may be of importance in disease classification. Intriguingly, our models classified diseases equally well based on either white or gray matter tau staining. Our results suggest that tau pathology in white matter is informative, disease-specific, and linked to gray matter pathology. Machine learning has the potential to reveal latent information in histologic images that may represent previously unrecognized patterns of neuropathology, and additional studies of tau pathology in white matter could improve diagnostic accuracy.