Abstract

The dynamic organization of receptors in the plasma membrane is crucial for ligand binding and downstream signaling. The actin cortex plays an important role in regulating cell surface receptor organization. However its role has been almost exclusively deduced via cell-wide actin perturbation experiments, which suffer from various caveats, such as lack of information about cortex dynamics and potential nonspecific effects. We have developed a quantitative imaging and computational analysis framework to derive perturbation free, explicit relationships between cell surface receptor organization and actin cortex dynamics. We use the receptor CD36 in endothelial cells as a model system, because its organization and signaling on the endothelial cell surface are thought to depend on actin. Briefly, to monitor both CD36 and actin cortex behavior at the same time in the same cell, we perform TIRF-based simultaneous single-molecule imaging of CD36 and fluorescent speckle microscopy (FSM) of actin, in live endothelial cells. Because of the disparate timescales of their dynamics, we image each at its relevant frame rate. Next, CD36 molecules are tracked to characterize their movement and clustering state to yield information about their dynamic organization, while neighboring actin behavior is characterized in the form of speckle density, movement and lifetime (reflecting actin turnover kinetics). Machine learning approaches are then applied to this multidimensional dataset to derive relationships between CD36 and actin cortex properties. Using this framework, we indeed find interdependence between CD36 and actin cortex properties. Interestingly, these inter-relationships vary based on subcellular location (cell side vs tip) and cell edge activity (actively ruffling vs quiescent). These observations highlight further the need for direct observation of these inter-relationships, instead of indirect deduction based on cell-wide perturbations that alter cell morphology and activity, leading to potentially difficult-to-interpret results.

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