Membrane potential mediates the cellular response to mechanical pressure

Abstract

Mechanical forces have been shown to influence cellular decisions to grow, die, or differentiate, through largely mysterious mechanisms. Separately, changes in resting membrane potential have been observed in development, differentiation, regeneration, and cancer. We now demonstrate that membrane potential is the central mediator of cellular response to mechanical pressure. We show that mechanical forces acting on the cell change cellular biomass density, which in turn alters membrane potential. Membrane potential then regulates cell number density in epithelia by controlling cell growth, proliferation, and cell elimination. Mechanistically, we show that changes in membrane potential control signaling through the Hippo and MAPK pathways, and potentially other signaling pathways that originate at the cell membrane. While many molecular interactions are known to affect Hippo signaling, the upstream signal that activates the canonical Hippo pathway at the membrane has previously been elusive. Our results establish membrane potential as a central regulator of growth and tissue homeostasis.

Figure 1:. Membrane potential is a sensor and regulator of tissue density.

a, Biomass density increases with cell density. MDCK cells were imaged for 4 consecutive days after confluence with increasing cell number density. Left, number of cell nuclei and cellular biomass density (in units of g/ml) measured via Normalized Stimulated Raman Spectroscopy (NoRI). Below, correlation between number density (mean ± s.d., NoRI: n=8, Tomocube: n=10) and biomass density (mean ± s.d., NoRI: n=15, Tomocube: n=~20) measured using NoRI and Tomocube. Right, snapshots of biomass density in tissue simulation (mean ± s.d., n=4 simulations). b, Membrane hyperpolarization increases with cell density. Left, fluorescence of MDCK-Voltron cell. Below, log fold change in fluorescence (mean ± s.d., n=8) against number density. Right, snapshots of membrane potential in tissue simulation (mean ± s.e.m., n=4 simulations). c-d, Correlation between cell density and membrane potential in (c) MCF10A and (d) EPH4-Ev cells. Top panels: NoRI images and quantification (mean ± s.d., number density: n=~10, NoRI: n=24) of MCF10A/EpH4-Ev cells for 4 consecutive days after confluence with increasing cell number density. Bottom panels: DiOC₂(3) imaging from colony edge to colony centre. e. Feedback control loop between biomass growth and membrane potential is crucial for epithelial homeostasis. f-h, Depolarization of membrane potential by ouabain increases the biomass density (box plot, line at mean, error bars represent min to max, n=40) and number density (n = 8) of confluent cells over the homeostatic steady state limit (dotted line represents the mean homeostatic cell number density and biomass density; quantified from experiment in panel a).

Figure 2:. Cells detect and respond to mechanical forces via changes in membrane potential.

a, Schematic diagram depicting the experimental design with monolayers grown on stretchable membrane. Left: cells were grown to confluence and then 20% uniaxial stretch was applied. Right: cells were grown to confluence on a pre-stretched membrane, then the stretch was released to induce compression. b, FluoVolt images of MDCK cells before and after stretching. c, Quantification of panel b (line at mean, n=8, p=0.0006, paired t-test). d, Membrane potential predicted by the tissue simulation upon a 20% uniaxial stretch (line at mean, n=4 simulations, each point is averaged across all cells in simulation). e, DiSBAC₂(3) imaging of MDCK cells before stretching, during stretching, and after destretching showing the reversibility of membrane potential change. f, Quantification of panel e (mean ± s.d., n = 8). Increase in fluorescence intensity indicates depolarization and decrease indicates hyperpolarization. Time of stretch and destretch are indicated by cyan and yellow arrows respectively. g, Membrane potential predicted by the tissue simulation upon stretch and subsequent destretch (n=4 simulations, each point is averaged across all cells in simulation). h, NoRI images of cellular biomass in response to tissue stretch. Biomass density recovers to the initial biomass density level overnight. i, Quantification of panel h. 0 hr represents time of stretch. (n=10, p-values: 0.0006 (initial vs 0 hr), 0.0001 (0 hr vs overnight), unpaired t test). j, Tissue simulation recapitulates the drop of biomass density upon stretch and overnight recovery. (mean ± s.d., n=4 simulations) k, Rescue of destretching-induced tissue crowding by ouabain. After 16 hr, a significant number of cells had been eliminated, consistent with previous studies^,. l, Quantification of panel k (mean ± s.e.m., n = 3 experiments of 20 ROIs each, p-value < 0.0001, unpaired t-test). m, Tissue simulation recapitulates cell elimination after compression and rescue from elimination by depolarizing drugs (mean ± s.e.m., n=4 simulations).

Figure 3:. A mechanically induced depolarization wave enhances wound healing.

a, Upper panel: DiSBAC₂(3) and fluorescently labeled membrane images of MDCK cells imaged over 3 hours after scratch wound. A depolarization wave was observed from the wound edge up to several layers deep into the tissue. Lower panel: Membrane potential from the tissue simulation over the course of wound healing. b, Quantification of membrane potential as a function of distance from scratch wound at different times (mean ± s.d., n=4 rectangular ROIs of 100 μm width). c, Quantification of cell area shows expansion of cells during wound healing (mean ± s.d., n=9). d, Upper panel: NoRI images over the course of wound healing. Lower panel: Biomass density from the tissue simulation over the course of wound healing. e. Quantification of cellular biomass density as a function of distance from scratch wound at different times after wounding (mean ± s.d., n=4 rectangular ROIs of 50 μm width). f, Representative images of control, depolarizing drug treatment (ouabain) and hyperpolarizing drug treatment (valinomycin) during wound healing. Wound border outlines were generated using the Wound healing size tool. g, Quantification of wound area closure as a function of time (mean ± s.d., n=2 wells). Depolarization resulted in faster wound healing (ouabain, red circles), as compared to the untreated control (cyan circles). Hyperpolarization (valinomycin, yellow circles, 5% PEG, green circles) resulted in slower wound healing. h, Schematic diagram showing the experimental set up for Xenopus embryo tail amputation. i, Brightfield and membrane potential (DiSBAC2(3)) images of Xenopus wound edge, 10 minutes post-amputation. Cell layers are progressively depolarized from deep tissue towards the wound edge. j, NoRI images of Xenopus tail amputation, 0 min and 10 min post-cut. The closest cell layer becomes dilute in biomass density immediately after the cut, and 5–6 cell layers become dilute in 10 minutes. Images represent different Xenopus embryos amputated and fixed at the specified times.

Figure 4:. Hippo and MAPK pathways mediate membrane potential signaling.

a, YAP immunostaining and fluorescent nuclei images in low density (top panel) and high density MDCK monolayers (bottom panel). b, Quantification of nuclear/cytoplasmic YAP ratio as a function of cell number density. (mean ± s.d., n = 20337, cells binned together by local number density). c, Schematic representation of YAP localization at different cell number densities. d-g, Immunostaining of MDCK cells for YAP and phosphorylated JNK (pJNK) under sparse (left panels) and dense (right panels) conditions with corresponding drug perturbations.d-e, the nucleus/cytoplasm ratio of YAP is measured. d, In Sparse cells, YAP localizes to the nucleus and induction of hyperpolarization significantly promotes nuclear exclusion of YAP. e, in dense confluent cells, depolarization by ouabain inhibits nuclear exclusion of YAP as compared to the control. In the plots, the line is at mean, n=24, and p-value is measured with an unpaired t-test and is <0.0001 unless otherwise specified. f, pJNK predominantly localized in cytoplasm in sparse MDCK cells. Induction of hyperpolarization by valinomycin promotes increased nuclear localization of pJNK. g, In dense confluent cells, depolarization by ouabain promotes nuclear exclusion of pJNK as compared to the control. h, JNK inhibition promotes significant nuclear exclusion of YAP in sparse MDCK cells. i, In Eph4-1424 cells, YAP nuclear localization follows the canonical density dependence of YAP nuclear-cytoplasmic shuttling. j-k, YAP immunostaining of sparse MDCK/MCF10A cells with control, valinomycin, and valinomycin with MST inhibitor (XMU-MP-1) conditions. The p-value between sparse and valinomycin+MSTi conditions is 0.0092. l, Sparse MCF10A cells with and without FAT1 knockdown (KD) are stained for FAT1 and YAP under control and valinomycin conditions. The nucleus/cytoplasm ratio for FAT1KD cells under control vs valinomycin has a p-value of 0.558 (ns). l, MST1 immunostaining of MCF10A/MDCK cells under sparse control, sparse valinomycin, dense control, and dense ouabain conditions. White arrows highlight areas of increased MST1 organized membrane clusters. For quantifications in panels. m, localization of MST1 in individual cells in randomized fields of view were analyzed. The line is at mean, n=4 ROIs, and p-value is measured with an unpaired t-test. The p-value is 0.0012 for MDCK sparse control v. valinomycin and <0.0001 for other plots. n, Schematic diagram summarizing signal transduction mechanism mediated by membrane potential. Depolarization of membrane potential activates cytoplasmic pJNK, which activates LIMD1 to inhibit LATS1, causing YAP to translocate to the nucleus. In parallel, hyperpolarization of membrane potential causes MST1 to colocalizes with the c-terminus tail of FAT1, assembling the Hippo signalome. This Hippo ‘on’ state prevents the nuclear translocation of YAP.