Abstract

The mechanically-activated ion channel Piezo1 is involved in numerous physiological processes. Piezo1 is activated by diverse mechanical cues and is gated by membrane tension. The channel has been found to be mobile in the plasma membrane. We employed single particle tracking (SPT) of endogenously-expressed, tdTomato-tagged Piezo1 using Total Internal Reflection Fluorescence Microscopy in two cell types, mouse embryonic fibroblasts and liver sinusoidal endothelial cells. Application of SPT unveiled a surprising heterogeneity of Piezo1 mobility in the plasma membrane. Leveraging a machine learning technique, Piezo1 trajectories were sorted into distinct classes (“mobile,” “intermediate,” and “trapped”) by partitioning features that describe the geometric properties of a trajectory. To evaluate the effects of the plasma membrane properties on Piezo1 diffusion, we manipulated membrane composition by depleting or supplementing cholesterol or by adding margaric acid to stiffen the membrane. To address effects of channel activation on Piezo1 mobility, we treated cells with Yoda1, a Piezo1 agonist, and GsMTx-4, a channel inhibitor. We collected thousands of trajectories for each condition, and found that “mobile” Piezo1 in cells supplemented with cholesterol or margaric acid exhibited decreased mobility, whereas Piezo1 in cholesterol-depleted membranes demonstrated increased mobility, compared to their respective controls. Additionally, activation by Yoda1 increased Piezo1 mobility and inhibition by GsMTx-4 decreased Piezo1 mobility compared to their respective controls. The “mobile” trajectories were analyzed further by fitting the time-averaged mean-squared displacement as a function of lag time to a power-law model, revealing Piezo1 consistently exhibits anomalous subdiffusion. This suggests Piezo1 is not freely mobile, but that its mobility may be hindered by subcellular interactions. These studies illuminate the fundamental properties governing Piezo1 diffusion in the plasma membrane and set the stage to determine how specific cellular interactions may influence channel activity and mobility.

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