Single-particle tracking and machine-learning classification reveals heterogeneous Piezo1 diffusion

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.

PIEZO1-HaloTag hiPSCs: Bridging Molecular, Cellular and Tissue Imaging

“…PIEZO1 has been shown to be mobile in the plasma membrane 30,32,42,43 and we confirmed this in hiPSC-derived neural stem cells, keratinocytes, and endothelial cells differentiated from PIEZO1-HaloTag hiPSCs and labeled with JF646 HTL (Supplemental Videos 1, 2, and 3). Studies on the mobility of the endogenous channel have utilized cells harvested from a PIEZO1-tdTomato knock-in mouse 30,42 where the tdTomato fluorescent protein is limited by rapid photobleaching and low signal-to-noise ratio. We compared the spatial and temporal resolution of data obtained from PIEZO1-tdTomato and PIEZO1-HaloTag endothelial cells (Fig.…”

“…Visual inspection of the trajectories revealed the presence of two distinct populations of puncta: those that appeared immobile and others that were highly motile (Fig. 2D), concordant with recent findings by Tyagi et al 42 .We then calculated Single Lag Displacements (SLD), i.e the distance covered by a punctum between consecutive frames, and generated a cumulative distribution function (CDF) of SLD 2 from the individual PIEZO1 trajectories (Fig. 2E).…”

“…In contrast, PIEZO1-HaloTag Knockout hiPSCs and wild-type WTC-11 hiPSCs both showed little or no punctate staining. To confirm the specific labeling of PIEZO1-HaloTag channels in the differentiated progeny of PIEZO1-HaloTag hiPSCs, we differentiated PIEZO1-HaloTag hiPSCs into three cell types which are known to express PIEZO1: endothelial cells 42 , keratinocytes 13 , and neural stem cells 30 (Fig. 1F, Supplemental Fig.…”

“…Our model also offers the flexibility to differentiate into multiple cell types and tissue organoids, providing a more comprehensive understanding of PIEZO1 dynamics compared to previous studies limited to single cell types. The superior brightness and photostability of the Janelia Fluor HTLs allowed us to capture PIEZO1 localization dynamics with higher precision than previous PIEZO1-tdTomato models 13,30,42 , revealing two distinct mobility behaviors and allowing imaging of the rear-enrichment of PIEZO1 in migrating cells with greater temporal resolution than previously possible 13 . Thus, our tool paves the road for a new generation of studies to examine PIEZO1 dynamics under a variety of physiological conditions.…”