Visualizing PIEZO1 Localization and Activity in hiPSC-Derived Single Cells and Organoids with HaloTag Technology

PIEZO1 is critical to numerous physiological processes, transducing diverse mechanical stimuli into electrical and chemical signals. Recent studies underscore the importance of visualizing endogenous PIEZO1 activity and localization to understand its functional roles. To enable physiologically and clinically relevant studies on human PIEZO1, we genetically engineered human induced pluripotent stem cells (hiPSCs) to express a HaloTag fused to endogenous PIEZO1. Combined with advanced imaging, our chemogenetic platform allows precise visualization of PIEZO1 localization dynamics in various cell types. Furthermore, the PIEZO1-HaloTag hiPSC technology facilitates the non-invasive monitoring of channel activity across diverse cell types using Ca2+-sensitive HaloTag ligands, achieving temporal resolution approaching that of patch clamp electrophysiology. Finally, we used lightsheet imaging of hiPSC-derived neural organoids to achieve molecular scale imaging of PIEZO1 in three-dimensional tissue organoids. Our advances offer a novel platform for studying PIEZO1 mechanotransduction in human cells and tissues, with potential for elucidating disease mechanisms and targeted therapeutic development.

Images were acquired at a frame rate of 200 fps.Intensity profiles were plotted from tracked immobile puncta.All traces are 30 s long (black) with a zoom in of a 3-s portion (red).Rightmost panels show an all-points histogram of intensity levels for the entirety of the 30-s recording.

A size-and time-based detection filtering method removed spurious puncta detections in JF635-labeled MNRs
Lightsheet imaging of PIEZO1-HaloTag in micropatterned neural rosettes (MNRs) allowed us to study PIEZO1 localization and activity in an in vitro model of human neural development.Specifically, we used this system to determine the localization of PIEZO1-HaloTag puncta relative to the lumen border or the outer edge of the MNR (see main Figure 5D-G).
To study puncta localization, we first used the ThunderSTORM detection algorithm (Ovesný et al. 2014) to detect puncta in JF635-labeled PIEZO1-HaloTag MNRs; JF635-labeled PIEZO1-HaloTag KO MNRs as well as unlabeled PIEZO1-HaloTag MNRs served as controls (see Methods).PIEZO1-HaloTag MNRs displayed 1.9 times more detections per MNR than PIEZO1-HaloTag KO MNRs, and a similar number of detections as unlabeled PIEZO1-HaloTag MNRs (calculated from the median values of each condition, see Supplemental Fig. 19A).However, many of the detected puncta were attributed to spurious detections, which were common across all three conditions.We identified three types of such spurious detections: detections within autofluorescence spots, detections due to unbound JF ligand remaining after wash steps, and false positive detections within the ThunderSTORM detection algorithm.Therefore, we developed a method to computationally filter out these spurious detections and enrich the pool of detections representing bona fide PIEZO1-HaloTag puncta.
We observed spurious detections within large autofluorescence spots, i.e. spots, also present in control KO and unlabeled MNRs (Supplemental Fig. 19B-D).These spots were immobile, presented stable intensity profiles over time (except for a progressive intensity decrease due to photobleaching), and were much larger than PIEZO1-HaloTag puncta.Therefore, we applied a first filtering step based on the size of the detected puncta, in which we removed any initial detections that had a standard deviation () of their Gaussian fit larger than 280 nm.This step successfully removed most detections that were located within autofluorescence spots (Supplemental Fig. 19B-D).After size-based filtering, there were 2.8 times more detections retained in JF635 PIEZO1-HaloTag MNRs than in JF635 PIEZO1-HaloTag KO MNRs; and 3.6 times more than in unlabeled PIEZO1-HaloTag MNRs (Supplemental Fig. 12E).Therefore, the size-based filtering step already removed a large number of spurious detections.
Besides detections in autofluorescence spots, we observed spurious detections corresponding either to unbound JF635 HTL or to small local background fluctuations being detected as puncta (Supplemental Fig. 19B-D).These detections generally appeared for only one or two frames, while bona fide PIEZO1-HaloTag puncta observed in JF635 PIEZO1-HaloTag MNRs tended to last several frames (Supplemental Fig. 19F).We thus used the FLIKA algorithm to track puncta over time and then applied a second, time-based filtering step designed to remove spurious detections that lasted only for one or two frames of imaging (Supplemental Fig. 19B-D).
After these two filtering steps, JF635 PIEZO1-HaloTag MNRs contained 9.6 times more puncta than JF635 PIEZO1-HaloTag KO MNRs, and 6.9 times more than unlabeled PIEZO1-HaloTag MNRs (Supplemental Fig. 19G).Therefore, our puncta filtering method allowed us to remove detections that were not representative of bona fide PIEZO1 puncta, and to retain detections representative of PIEZO1 puncta for further analysis.

Supplementary Results
A size-and intensity-based detection filtering method removed spurious puncta detections in JF646-BAPTA-labeled NMRs Light-sheet imaging of MNRs labeled with JF646-BAPTA HTL also enabled us to quantify the spatial distribution of active puncta in the neural organoids.Before analyzing the data, we conducted two filtering steps to remove spurious detections.The first step was identical to the size-based step used for JF635 samples above, while the second step was tailored to the highly variable intensity profiles displayed by BAPTA HTL ligands.
Because BAPTA probes flicker quickly over time (see kymograph in main Fig. 5F), the second filtering step was based on puncta integrated intensity (the sum of intensity values for all pixels under the Gaussian curve fitted to each detected puncta) rather than track duration (Supplemental Fig. 20B-D).Here we removed puncta with a value of integrated intensity lower than ~77 photons, based on the distribution of integrated intensity values retained after the size-based filtering step (Supplemental Fig. 20F).Relative frequency histograms of integrated intensity values showed large proportions of puncta contained under the 77-photon threshold, in particular for negative control samples.After filtering these spurious puncta out based on this intensity threshold, JF646-BAPTA PIEZO1-HaloTag MNRs had 2.6 times more localizations than JF646-BAPTA PIEZO1-HaloTag KO MNRs, and 2 times more than unlabeled PIEZO1-HaloTag MNRs (Supplemental Fig. 20G).Only detections that were both small enough in spatial spread and bright enough to represent active PIEZO1 puncta were then retained for analysis of active punta localization in MNRs.Therefore, while this approach did not remove as many spurious detections as the time-based filtering applied to JF635-labeled samples above, intensity-based filtering also successfully retained bona fide active PIEZO1-HaloTag puncta.

Supplemental Figure 5 .
Motility of PIEZO puncta is not determined by association with the ER.Panels show representative TIRF images of multiple positions within PIEZO1-HaloTag endothelial cells labeled with ER tracker 488 dye (grayscale) overlaid with trajectories of JF646 HTL PIEZO1-HaloTag puncta.Trajectories are color-coded by path length as in Fig. 2 (magenta: mobile, yellow: immobile).Some mobile and immobile trajectories overlap with the ER signal while others localize to ER-free regions.Supplemental Figure 6.Fluorescence signals from monomeric cytoplasmic HaloTag imaged at different free Ca 2+ concentrations.WTC-11 hiPSCs were transfected with plasmids expressing cytoplasmic HaloTag and then labeled with a 1:1 mixture of JF549 and JF646-BAPTA.Labeled cells were fixed, permeabilized and imaged for 10 s at 200fps. A. Representative TIRF maximum intensity projection image of JF549 HTL (left).Fluorescence intensities over time for three representative JF549 puncta along with all-point amplitude histograms (right).Note the stable fluorescence intensity over time.B. Fixed and permeabilized samples were exposed to increasing levels of free Ca 2+ .Representative TIRF maximum intensity projection images of JF646-BAPTA HTL at different Ca 2+ concentrations.C. Fluorescence intensities over time for four representative JF646-BAPTA puncta for different Ca 2+ concentrations, along with all-point amplitude histograms.Note the increased occupancy at higher fluorescence intensity with increase in Ca 2+ .activity traces from untreated PIEZO1-HaloTag.Representative background-subtracted fluorescence intensity traces of 21 untreated immobile PIEZO1-HaloTag puncta from 3 independent TIRF imaging experiments of hiPSC-derived endothelial cells labeled with the Ca 2+ -sensitive JF646-BAPTA HTL.Images were acquired at a frame rate of 200 fps.Intensity profiles were plotted from tracked immobile puncta.All traces are 30 s long (black) with a zoom in of a 3-s portion (red).Rightmost panels show an all-points histogram of intensity levels for the entirety of the 30-s recording.activity traces from PIEZO1-HaloTag treated with vehicle control, DMSO.Representative background-subtracted fluorescence intensity traces of 21 immobile PIEZO1-HaloTag puncta from 3 independent TIRF imaging experiments of hiPSC-derived endothelial cells labeled with the Ca 2+ -sensitive JF646-BAPTA HTL and treated with vehicle control, DMSO.Intensity profiles were plotted from tracked immobile puncta.All traces are 30 s long (black) with a zoom in of a 3-s portion (red).Rightmost panels show an all-points histogram of intensity levels for the entirety of the 30-s recording.activity traces from PIEZO1-HaloTag treated with 2 µM of Yoda1.Representative background-subtracted fluorescence intensity traces of 21 immobile PIEZO1-HaloTag puncta from 3 independent TIRF imaging experiments of hiPSC-derived endothelial cells labeled with the Ca 2+ -sensitive JF646-BAPTA HTL and treated with 2 µM Yoda1.
500-fps activity traces from PIEZO1-HaloTag neural stem cells.Representative background-subtracted fluorescence intensity traces of 45 immobile PIEZO1-HaloTag puncta from TIRF imaging of hiPSC-derived neural stem cells labeled with the Ca 2+ -sensitive JF646-BAPTA HTL.Intensity profiles were plotted from tracked immobile puncta.All traces shown are 10 seconds long (black) with a zoom in of a 0.5-second portion (red).Rightmost panels show an all-points histogram of intensity levels for the entirety of the 10-second recording.