Quantifying the extent to which points are clustered in single-molecule localization microscopy data is vital to understanding the spatial relationships between molecules in the underlying sample. Many existing computational approaches are limited in their ability to process large-scale data sets, to deal effectively with sample heterogeneity, or require subjective user-defined analysis parameters. Here, we develop a supervised machine-learning approach to cluster analysis which is fast and accurate. Trained on a variety of simulated clustered data, the neural network can classify millions of points from a typical singlemolecule localization microscopy data set, with the potential to include additional classifiers to describe different subtypes of clusters. The output can be further refined for the measurement of cluster area, shape, and point-density. We demonstrate this approach on simulated data and experimental data of the kinase Csk and the adaptor PAG in primary human T cell immunological synapses.

The cortical actin cytoskeleton has been shown to be critical for the reorganization and heterogeneity of plasma membrane components of many cells, including T cells. Building on previous studies at the T cell immunological synapse, we quantitatively assess the structure and dynamics of this meshwork using live-cell superresolution fluorescence microscopy and spatio-temporal image correlation spectroscopy. We show for the first time, to our knowledge, that not only does the dense actin cortex flow in a retrograde fashion toward the synapse center, but the plasma membrane itself shows similar behavior. Furthermore, using two-color, live-cell superresolution cross-correlation spectroscopy, we demonstrate that the two flows are correlated and, in addition, we show that coupling may extend to the outer leaflet of the plasma membrane by examining the flow of GPI-anchored proteins. Finally, we demonstrate that the actin flow is correlated with a third component, α-actinin, which upon CRISPR knockout led to reduced plasma membrane flow directionality despite increased actin flow velocity. We hypothesize that this apparent cytoskeletal-membrane coupling could provide a mechanism for driving the observed retrograde flow of signaling molecules such as the TCR, Lck, ZAP70, LAT, and SLP76.

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Single-molecule localisation microscopy (SMLM) allows the localisation of fluorophores with a precision of 10–30 nm, revealing the cell’s nanoscale architecture at the molecular level. Recently, SMLM has been extended to 3D, providing a unique insight into cellular machinery. Although cluster analysis techniques have been developed for 2D SMLM data sets, few have been applied to 3D. This lack of quantification tools can be explained by the relative novelty of imaging techniques such as interferometric photo-activated localisation microscopy (iPALM). Also, existing methods that could be extended to 3D SMLM are usually subject to user defined analysis parameters, which remains a major drawback. Here, we present a new open source cluster analysis method for 3D SMLM data, free of user definable parameters, relying on a model-based Bayesian approach which takes full account of the individual localisation precisions in all three dimensions. The accuracy and reliability of the method is validated using simulated data sets. This tool is then deployed on novel experimental data as a proof of concept, illustrating the recruitment of LAT to the T-cell immunological synapse in data acquired by iPALM providing ~10 nm isotropic resolution.

In animal cells, shape is mostly determined by the actomyosin cortex, a thin cytoskeletal network underlying the plasma membrane. Myosin motors generate tension in the cortex, and tension gradients result in cellular deformations. As such, many cell morphogenesis studies have focused on the mechanisms controlling myosin activity and recruitment to the cortex. Here, we demonstrate using super-resolution microscopy that myosin does not always overlap with actin at the cortex, but remains restricted towards the cytoplasm in cells with low cortex tension. We propose that this restricted penetration results from steric hindrance, as myosin minifilaments are considerably larger than the cortical actin meshsize. We identify myosin activity and actin network architecture as key regulators of myosin penetration into the cortex, and show that increasing myosin penetration increases cortical tension. Our study reveals that the spatial coordination of myosin and actin at the cortex regulates cell surface mechanics, and unveils an important mechanism whereby myosin size controls its action by limiting minifilament penetration into the cortical actin network. More generally, our findings suggest that protein size could regulate function in dense cytoskeletal structures.