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Spatiotemporal dynamics of membrane surface charge regulates cell polarity and migration

Nature Cell Biology volume 24, pages 1499–1515 (2022)Cite this article

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Abstract

During cell migration and polarization, numerous signal transduction and cytoskeletal components self-organize to generate localized protrusions. Although biochemical and genetic analyses have delineated many specific interactions, how the activation and localization of so many different molecules are spatiotemporally orchestrated at the subcellular level has remained unclear. Here we show that the regulation of negative surface charge on the inner leaflet of the plasma membrane plays an integrative role in the molecular interactions. Surface charge, or zeta potential, is transiently lowered at new protrusions and within cortical waves of Ras/PI3K/TORC2/F-actin network activation. Rapid alterations of inner leaflet anionic phospholipids—such as PI(4,5)P2, PI(3,4)P2, phosphatidylserine and phosphatidic acid—collectively contribute to the surface charge changes. Abruptly reducing the surface charge by recruiting positively charged optogenetic actuators was sufficient to trigger the entire biochemical network, initiate de novo protrusions and abrogate pre-existing polarity. These effects were blocked by genetic or pharmacological inhibition of key signalling components such as AKT and PI3K/TORC2. Conversely, increasing the negative surface charge deactivated the network and locally suppressed chemoattractant-induced protrusions or subverted EGF-induced ERK activation. Computational simulations involving excitable biochemical networks demonstrated that slight changes in feedback loops, induced by recruitment of the charged actuators, could lead to outsized effects on system activation. We propose that key signalling network components act on, and are in turn acted upon, by surface charge, closing feedback loops, which bring about the global-scale molecular self-organization required for spontaneous protrusion formation, cell migration and polarity establishment.

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Fig. 1: Multiple anionic phospholipids dynamically self-organize to the back-state regions of the membrane.
Fig. 2: The back state regions of the membrane maintains a higher negative surface charge on the inner leaflet compared to the front state regions.
Fig. 3: Dynamics of the inner-membrane surface-charge sensor R(+8)-Pre in different anionic phospholipid-depleted cells.
Fig. 4: Localized lowering of the membrane surface charge can trigger de novo protrusion generation from the area of the reduced surface charge.
Fig. 5: Global lowering of the negative surface charge of the membrane can abolish the pre-existing polarity by consistently generating new protrusions from the back-state regions.
Fig. 6: The phenotypic changes induced by Opto-ACTU+ recruitment are mediated by the Ras/PI3K/Akt/TORC2/F-actin network.
Fig. 7: In silico reduction of the membrane surface charge recreates the polarity breaking and demonstrates increased activity over the membrane.
Fig. 8: Increased negative surface potential in the inner membrane suppresses protrusions in macrophages and, separately, deactivates EGF-induced ERK activity in epithelial cells.

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Data availability

Source data are provided with this paper. All other data supporting the findings of this study are available from the corresponding author on reasonable request.

Code availability

Computational simulation codes are available on GitHub: https://github.com/tatsatb/Simulation-of-Membrane-Surface-Charge-Perturbation. Any additional information will be available from the corresponding author on reasonable request.

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Acknowledgements

We thank S. Grinstein (Hospital for Sick Children, University of Toronto) for stimulating discussions. We thank M. Kozlov (Tel Aviv University) for helping us with the resident charge calculation. We thank D. Andrew, C.-H. Huang, all of the members of the Devreotes and Iglesias laboratories as well as the members of the D. Robinson and M. Iijima laboratories (School of Medicine, Johns Hopkins University) for their valuable suggestions. We thank Y. Long and Y. Deng (Devreotes laboratory) for helping with some experiments. We thank N. Gautam (Washington University School of Medicine in St. Louis) and R. R. Kay (MRC LMB) for providing cells. We thank G. Du (McGovern Medical School, UTHealth) and A. Müller-Taubenberger (LMU Munich) for sharing plasmids. We thank Addgene and dictyBase for providing the plasmids and resources. This work was supported by NIH grant nos R35 GM118177 (to P.N.D.), DARPA HR0011-16-C-0139 (to P.A.I. and P.N.D.) and AFOSR MURI FA95501610052 (to P.N.D.) as well as NIH grant S10 OD016374 (to S. Kuo of the JHU Microscope Facility).

Author information

Author notes

  1. These authors contributed equally: Debojyoti Biswas, Dhiman Sankar Pal.

Authors and Affiliations

  1. Department of Cell Biology and Center for Cell Dynamics, School of Medicine, Johns Hopkins University, Baltimore, MD, USA

    Tatsat Banerjee, Dhiman Sankar Pal, Yuchuan Miao, Pablo A. Iglesias & Peter N. Devreotes

  2. Department of Chemical and Biomolecular Engineering, Whiting School of Engineering, Johns Hopkins University, Baltimore, MD, USA

    Tatsat Banerjee

  3. Department of Electrical and Computer Engineering, Whiting School of Engineering, Johns Hopkins University, Baltimore, MD, USA

    Debojyoti Biswas & Pablo A. Iglesias

  4. Department of Biological Chemistry, School of Medicine, Johns Hopkins University, Baltimore, MD, USA

    Yuchuan Miao & Peter N. Devreotes

Authors
  1. Tatsat Banerjee
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  2. Debojyoti Biswas
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  3. Dhiman Sankar Pal
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  4. Yuchuan Miao
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  5. Pablo A. Iglesias
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  6. Peter N. Devreotes
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Contributions

T.B. and P.N.D. conceptualized the overall study. T.B. designed and performed all Dictyostelium experiments. D.S.P. introduced and developed the mammalian cell culture model and T.B. and D.S.P. together designed and carried out the mammalian experiments. Y.M. provided resources and contributed to the experiments. D.B. and P.A.I. developed the software to compute the CP index and performed localization analyses. T.B. quantified and analysed other results, with input from the other authors. D.B. and P.A.I. developed the computational models and D.B. conducted all of the simulations. T.B., P.N.D., D.S.P., D.B. and P.A.I. wrote the manuscript. P.N.D. and P.A.I. supervised the study.

Corresponding author

Correspondence to Peter N. Devreotes.

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Extended data

Extended Data Fig. 1 Cells generate two mutually exclusive dynamic states in the membrane during migration and ventral wave propagation.

(a) Coordinated localization dynamics of signalling (PIP3) and cytoskeletal components (F-actin) in migrating Dictyostelium cell protrusions. Top panel: Live-cell images (Arrowheads: Protrusions enriched in both F-actin and PIP3). Bottom panel: 360° membrane kymographs showing consistency of coordination. Here and in all other kymographs, numbers on the left denote time in seconds, unless otherwise mentioned. Throughout this study, PIP3 level is marked by PHcrac in Dictyostelium and by PHAKT in macrophages, whereas, newly polymerizing F-actin is marked by LimEΔcoil (‘LimE’ hereafter) in Dictyostelium and by Lifeact in macrophages. (b, c) Coordinated propagation of signalling (PIP3) and cytoskeletal (F-actin) components in ventral-surface cortical waves of Dictyostelium (b) and RAW 264.7 macrophages (c). Top two panels show live-cell images and bottom panels show line-scan intensity profile along the solid white lines. Similar convention is followed throughout this article. (d, e) Activated Ras and PIP3 colocalizing in the protrusions (d), whereas PTEN selectively dissociating from it (e), in migrating Dictyostelium cells. Left: Live-cell images, Right: 360° membrane kymographs. Arrowheads: Protrusions/front-states. Throughout this study, Ras-Binding Domain of Raf1 (RBD) was used as a detector of Ras activation. (f, g) In propagating waves of Dictyostelium, activated Ras and PIP3 dynamically co-localized and defined the front-state regions (f), whereas PIP3 and PTEN exhibit consistent complementarity (g). Live-cell images, line-scan intensity profiles, and line kymographs are shown. (h) Complementary distribution of PIP3 and PTEN is independent of cytoskeleton. Here Dictyostelium cells are imaged in presence of Latrunculin A (F-actin polymerization inhibitor). Arrowheads denoting front-states. (i) Schematic showing the front-back complementary patterning in three different scenarios: migrating cell protrusions, cytoskeleton-independent cortical symmetry breaking, and propagating ventral waves. For first two cases, we could study a 1D profile, whereas for ventral waves, we observed a 2D profile at the substrate-attached surface. Several examples of established signalling and cytoskeletal components are listed and categorized. In all situations, when a front-state was created from the back/basal state of the membrane, back markers moved away from that particular domain, maintaining complementarity. All scale bars are 10 μm.

Extended Data Fig. 2 Developing conditional probability index as a metric to quantify the extent of co-localization and complementary localization.

(a) Schematics showing the application of the concepts of conditional probability in quantifying the degree of co-localization between two entities, R and G. The regions of the high enrichments of the species R and G are denoted as Rhigh and Ghigh whereas the depleted states are denoted as Rlow and Glow, respectively (top panels). The overlapped region (yellow in the bottom left panel) denotes Rhigh∩Ghigh. The other necessary probabilities are also shown which are required in the computation of the respective Conditional Probability Index (CP index). (b) The mathematical description of the CP index. As usual, P(Rhigh | Ghigh) denotes Probability of selecting Rhigh, given Ghigh is already selected. Rest of the expression follow the same standard convention (please see methods for details). (c, d) Time series plots of CP indices of established back protein PTEN (c) and established front sensor RBD (d); number of cells nc = 15 for RBD (c) and nc = 17 for PTEN (d). Throughout this paper, to generate CP index time-plots, each cell was analysed for nf = 20 frames; data are mean ± s.e.m. Top panels show representative images of ventral waves in Dictyostelium cells coexpressing either PHCrac and RBD (c) or PHCrac and PTEN (d). Note that the CP index value of PTEN is negative and RBD is positive which demonstrate their back-state and front-state localization, respectively. Throughout this paper, all CP indices are calculated with respect to PIP3.

Source data

Extended Data Fig. 3 PI(4,5)P2, PI(3,4)P2, PS, and PA exhibit consistent yet dynamic back-state distribution.

(a) Representative line-kymograph of ventral waves in RAW 264.7 macrophages coexpressing PI(4,5)P2 biosensor (GFP–PHPLCδ), and PIP3 biosensor (PHAKT-mCherry). Time-lapse images and line-scan intensity profiles were shown in Fig. 1c. (b) Representative line-kymograph of ventral waves in Dictyostelium cells coexpressing PI(3,4)P2 biosensor (PHCynA-KikGR) and PIP3 biosensor (PHCrac-mCherry). Time-lapse images and line-scan intensity profiles were shown in Fig. 1d. (c) Representative line kymographs of ventral wave pattern shown in Dictyostelium cells coexpressing PS biosensor (GFP–LactC2) and PIP3 biosensor, (PHCrac-mCherry). Time-lapse images and line-scan intensity profiles were shown in Fig. 1g. (d) Representative line kymographs of ventral wave pattern in RAW 264.7 macrophage cells coexpressing PS biosensor (GFP–LactC2) and PIP3 biosensor, (PHAKT-mCherry). Time-lapse images and line-scan intensity profiles were shown in Fig. 1h. (e) Representative line kymographs of ventral wave pattern in Dictyostelium cells coexpressing PA biosensor (GFP-Spo20) and PIP3 biosensor (PHCrac-mCherry). Time-lapse images and line-scan intensity profiles were shown in Fig. 1j. (f) Time-lapse images of migrating Dictyostelium cells coexpressing GFP-Spo20 and PHcrac-mCherry. White arrows: Protrusions where PIP3 is enriched and PA is depleted. Blue arrows: Spo20 returned back to the membrane as protrusions were eventually retracted and membrane domain returned to its basal back-state. (g) Box and Whisker plot of time-averaged CP indices of four anionic phospholipids (PI(4,5)P2, PI(3,4)P2, PS, and PA), together with uniform membrane marker control cAR1, back protein PTEN, and front sensor RBD; nc = 16 cells for PI(4,5)P2/PHPLCδ, nc = 10 cells for PI(3,4)P2/PHCynA, nc = 15 cells for PS/LactC2, nc = 16 cells for PS/Spo20, nc = 20 cells for cAR1, nc = 17 cells for PTEN, nc = 15 cells for RBD. As mentioned earlier, to generate each data point, nf = 20 frames were averaged for the above-mentioned number of cells.

Source data

Extended Data Fig. 4 Spatiotemporal organization of different mutated charge sensors and uniform membrane controls.

(a) Representative live-cell images of Dictyostelium cells coexpressing GFP–R( + 8)-Pre and PHCrac-mCherry under chemotactic gradient stimulation. Solid magenta arrowhead indicates the direction of micropipette (filled with 1 μM cAMP) for gradient stimulation. Dashed magenta arrowhead indicates the introduction of needle (t = 0 s) which is manifested by the transient global response in PHCrac channel. Cells were pre-treated with Latrunculin A. (b-d) Live-cell time-lapse images and line scan intensity profiles of Dictyostelium cells expressing PHcrac-mCherry, along with GFP–R( + 7)-Pre (b) or GFP–R( + 4)-Pre (c) or GFP–R( + 2)-Pre (d), during ventral wave propagation, displaying decreasing extent of back-state preference of the surface charge sensors. The first time points were showed in Fig. 2j (in grayscale colourmap). (e, f) The 360° membrane kymographs of cells shown in Fig. 2k, indicating R( + 7)-Pre consistently moves away from PIP3-rich protrusions (e, whereas R( + 2)-Pre is uniform over the cortex (f). (g) Live-cell images, line scan intensity profiles, and representative line kymographs of ventral waves in Dictyostelium cells coexpressing PHcrac-mCherry and membrane marker cAR1-GFP, demonstrating that cAR1 does not distribute to front- or back- state regions and it is consistently uniform over the membrane. (h) Live-cell time-lapse images of migrating Dictyostelium cells coexpressing PHcrac-mCherry and cAR1-GFP showing cAR1 is symmetric over the membrane. Black arrows: PIP3- rich protrusions where cAR1 was present as well. (i) Live-cell images, linescan intensity profiles, and representative line kymographs of ventral waves in RAW 264.7 cells coexpressing PHAKT-mCherry and membrane marker, LYN-GFP, showing consistent uniform profile of LYN over the membrane and no depletion in front-state area. (j) Live-cell time-lapse images of migrating Dictyostelium cells coexpressing PHcrac-mCherry and GFP–Palm/Pre, showing a symmetric profile of Palm/Pre over the membrane. Black arrows: Protrusions/front-states. In (g-j), the “Fire invert” LUT of Fiji/ImageJ was used so that it can clearly show any small inhomogeneity. For exact sequence details, please see Supplementary Table S1.

Extended Data Fig. 5 Different polybasic sequences localize to back-state regions depending on their charge, irrespective of their exact amino-acid sequences.

(a, b) Representative live-cell images, line scan intensity profiles, and representative line kymographs of Dictyostelium cells coexpressing PHCrac-mCherry and GFP-RacGCT (a) or GFP-PTEN1-18-CAAX (b), demonstrating consistent dynamic back distribution for RacGCT and limited back distribution for PTEN1-18-CAAX in ventral waves. For exact sequence details, please see Supplementary Table S1. (c, d) Representative live-cell time-lapse images showing distribution of RacGCT (c) or PTEN1-18-CAAX (d) in migrating Dictyostelium cells (coexpressing PHCrac-mCherry), demonstrating localization profiles analogous to (a, b). (e, f) Time series plots of CP index of RacGCT (e) and PTEN1-18-CAAX (f) show the extent of back localization; nc = 17 for RacGCT (e), nc = 12 for PTEN1-18-CAAX (f); mean ± s.e.m. (g) Comparison of localization profile by box plot of time-averaged CP indices of all surface charge sensors, together with uniform membrane marker controls, back protein PTEN, and front sensor RBD; R( + 8)-Pre: nc = 30, R( + 7)-Pre: nc = 23, R( + 4)-Pre: nc = 20, R( + 2)-Pre: nc = 12, RacGCT: nc = 17, PTEN1-18-CAAX:nc = 12, cAR1: nc = 20, Palm/Pre: nc = 11, PTEN: nc = 17, RBD: nc = 15. Box and whiskers are graphed as per Tukey’s method. All p-values by Mann-Whitney-Wilcoxon test.

Source data

Extended Data Fig. 6 Dynamics of surface charge sensor in PI(4,5)P2 and PI(3,4)P2 depleted cells.

(a) Time course of membrane/cytosol ratio of PHPLCδ and Inp54p upon rapamycin addition (indicated by black dashed vertical line), in Dictyostelium cells coexpressing cAR1-FKBP-FKBP, mCherry-FBP-Inp54p, and PHPLCδ-GFP, demonstrating PHPLCδ dissociated from membrane upon PI(4,5)P2 depletion; n = 17 cells; mean ± s.e.m. (b, c) Cell tracks show the migration profile of Dictyostelium cells expressing chemically induced dimerization system cAR1-FKBP-FKBP and mCherry-FBP-Inp54p, along with PHPLCδ-GFP (b) or GFP–R( + 8)-Pre (c), before and after rapamycin induced recruitment. Tracks demonstrating similar change in migration profile in both cases, as quantified in terms of migration speed in Fig. 3d. To generate each track for nc = 32 cells (in each case), cells were followed for nf = 60 frames (7 s/frame). (d) Representative image of Dd5p4– Dictyostelium cell (where PI(3,4)P2 level is low) coexpressing GFP–R( + 8)-Pre and LimE-mRFP displaying characteristic membrane association and back localization of R( + 8)-Pre; white arrows denote F-actin rich protrusions. (e) Quantification of membrane association of R( + 8)-Pre in wild type and Dd5p4- cells, in terms of membrane/cytosol ratio; n = 29 cells in each case; p-value by Mann-Whitney-Wilcoxon test. (f) Example of a quiet or non-protrusion forming Dictyostelium cells expressing LimE-mRFP, whose outer leaflet of membrane was allowed to transiently bind with Annexin V, Alexa Fluor 488 conjugate.

Source data

Extended Data Fig. 7 Local recruitment of Opto-ACTU+ in polarized cells induce de novo generation of protrusion near recruitment area, whereas neither local nor global recruitment of uncharged control Opto-CTRL elicit any phenotypic changes.

(a) A representative example of de novo formation of protrusion from a position of choice in the back-state region of the membrane by spatially confined recruitment of Opto-ACTU+. Magenta arrows: Old protrusions, Green arrows: New protrusions. (b) A representative example of spatially confined optogenetic recruitment of Opto-CTRL demonstrating no increase in protrusion generation from the site of recruitment. In (a-b), along with the Opto-ACTU+ (a) or Opto-CTRL (b), cells were coexpressing cAR1-CIBN and LimE-Halo; the numbers on the images denote time in seconds. (c, d) Time-lapse snapshots (c) and time-stack (d) of Dictyostelium cells coexpressing Opto-CTRL and cAR1-CIBN, demonstrating the unaltered cell morphology and migration behaviour in polarized Dictyostelium cells, upon optogenetic recruitment. Numbers are time in seconds (c). 488 nm switched ON globally at t = 0 s. Yellow arrows: Opto-CTRL is uniform over cortex and did not move away from protrusions (d). (e-h) Quantification of cell morphology and migration mode in terms of cell circularity index (e), cell tracks (f), migration speed (g), and new protrusion formation frequency (h), upon Opto-CTRL recruitment (n = 25 cells). Data shown as mean ± s.e.m. over time in (e). In (f-h), for either before or after recruitment tracks, each cell tracked for nf = 40 frames (t = 320 s). Tracks were reset to the same origin in (f). For pairwise comparison, tracks are color-coded in (f) and data from same cell are connected by grey line in (g) and (h). The p-values by Mann-Whitney-Wilcoxon test.

Source data

Extended Data Fig. 8 Global recruitment of Opto-ACTU+ can cause spatiotemporally confined activation of Ras/PI3K/AKT/TORC2/F-actin network components.

(a) Intensity profiles of LimE–GFP and Opto-ACTU+ along the white lines (the images are same as shown in Fig. 6b) demonstrate that F-actin polymerizes in the domains of membrane where Opto-ACTU+ accumulates and when that leads to a protrusion, Opto-ACTU+ moves away with a short time delay. (b) 360° membrane kymograph of cell shown in Fig. 6b. (c) 360° membrane kymograph of cell shown in Fig. 6c. (d) Time-lapse live-cell images of Dictyostelium cells coexpressing Opto-ACTU+, cAR1-CIBN, and PHCrac-YFP where recruitment was started at t = 0 s. Numbers show time in seconds. The “i” and “ii” are showing two different PIP3 production events which eventually lead protrusion formation. For each event, blue arrowheads are showing the areas where Opto-ACTU+ was first accumulated which in turn became the areas of PIP3 production and eventually, after protrusion formation, Opto-ACTU+ moved away to a newer back-state area. (e) 360° membrane kymograph of cell shown in (d). (f) 360° membrane kymograph of cell shown in Fig. 6d.

Extended Data Fig. 9 The effect of specific genetic and pharmacological perturbations upon the phenotypic changes induced by Opto-ACTU+ recruitment.

(a-c) Quantification of migration profile changes in terms of new protrusion formation frequency (a), speed (b), and cell tracks (c), upon Opto-ACTU+ recruitment, in PTEN– Dictyostelium cells; nc = 22 cells. (d, e) Quantification of migration profile changes in terms of new protrusion formation frequency (d) and speed (e), upon Opto-ACTU+ recruitment in Dictyostelium cells, pre-treated with PI3K inhibitor LY294002; nc = 28 cells. (f-h) Quantification of migration profile changes in terms of new protrusion formation frequency (f), speed (g), and cell tracks (h), upon Opto-ACTU+ recruitment in PTEN– Dictyostelium cells, pre-treated with LY294002; nc = 24 cells. (i) Temporally color-coded cell outlines of a representative migrating PTEN– Dictyostelium cells, pre-treated with PI3K inhibitor LY294002, showing cell morphology and migratory profile before and after 488 nm was turned on to recruit Opto-ACTU+ (corresponding to Supplementary Video S11). (j-o) Quantification of migration profile changes in terms of new protrusion formation frequency (j, l, n) and migration speed (k, m, o) upon Opto-ACTU+ recruitment under different genetic and pharmacological inhibitions. In (j-k) cells were pre-treated with PP242 to inhibit TORC2 (nc = 22 cells); in (l-m) cells were pre-treated with both LY294002 and PP242 to simultaneously block PI3K and PP242 (nc = 27 cells); in (n-o), AKT−/PKBR1− double knockout cell line was used (nc = 21 cells). For each case, each of the nc cells were tracked for nf = 40 frames (8 sec/frame was imaging frequency) and time averages were taken. Tracks were reset to the same origin in (c) and (h). For pairwise comparison, tracks are color-coded in (c) and (h). In all boxplots here, for pairwise comparison, data from same cell are connected by grey lines. The p-values by Mann-Whitney-Wilcoxon test.

Source data

Extended Data Fig. 10 Selective recruitment of uncharged control Opto-CTRL cannot suppress protrusion in RAW 264.7 macrophages or global recruitment of Opto-CTRL cannot deactivate ERK in MCF10A cells, unlike Opto-ACTU–.

(a) Representative live-cell time-lapse images of RAW 264.7 cells undergoing light-triggered spatially confined recruitment of Opto-ACTU–, followed by global stimulation with C5a-receptor agonist, demonstrating selective protrusion suppression in the site where Opto-ACTU– was locally recruited and robust protrusion formation in other areas of cortex. Time in min:sec format. Cells were coexpressing Opto-ACTU–, CIBN-CAAX, and Lifeact–mVenus. (b) Representative live-cell time-lapse images of RAW 264.7 cells undergoing light-triggered spatially confined recruitment of Opto-CTRL, followed by global stimulation by C5a-receptor agonist. Time in min:sec format. Cells were coexpressing Opto-CTRL, CIBN-CAAX, and Lifeact–mVenus. (c) Polar histogram indicating probability of protrusion formation is essentially uniform over the cortex upon global stimulation with C5a-receptor agonist, in cells where Opto-CTRL was recruited locally. nc = 12 cells, np = 59 protrusions. (d) Schematic showing coupled system of excitable network with Opto-ACTU– input along with global agonist stimulation. (e) The simulated kymographs of B (top) and \(C_m^ -\) (bottom) in response to local recruitment of Opto-ACTU–. The location of recruitment is denoted by the white dashed box. The solid black line denotes the span of global agonist stimulation. (f) Representative live-cell time-lapse images of a MCF10A cell displaying ERK-KTR maintaining its cytosolic distribution upon recruitment of Opto-CTRL to CIBN-CAAX, demonstrating no substantial ERK deactivation; cells were pre-treated with and maintained in a saturated dose of EGF throughout the experiment. Time in hr:min:sec format; 488 nm laser was first turned ON at t = 0 min. (g, h) Individual cell level changes in the nuclear/cytosolic ratio of ERK-KTR over time, upon recruitment of Opto-ACTU– (g) or Opto-CTRL (h). Population average is in Fig. 8i. The color scale shown in right is applicable to both panels.

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Supplementary information

Supplementary Information

Supplementary Notes 1 and 2.

Reporting Summary

Supplementary Video 1

Dynamic localization of PI(4,5)P2 to the back state of the membrane in both Dictyostelium cells and RAW 264.7 macrophages. a–c, The spatiotemporal complementary patterns were observed during protrusion formation in Dictyostelium (a), ventral wave propagation in Dictyostelium (b) and ventral wave propagation in RAW 264.7 macrophages (c). PHPLCδ-GFP (left), PHcrac–mCherry (a,b(middle)), PHAkt-mCherry (c(middle)) and merged views (right) are shown. Time is shown in mm:ss format (top-left corners).

Supplementary Video 2

During ventral-wave propagation in Dictyostelium cells PI(3,4)P2 dynamically localizes to the back state of the membrane. PHCynA–KikGR (left), PHcrac–mCherry (middle) and the merged view (right) are shown. Time is shown in mm:ss format (top-left corners).

Supplementary Video 3

Dynamic preferential back-state distribution of PS in the membrane during ventral-wave propagation in Dictyostelium cells and RAW 264.7 macrophages. (a) Ventral-wave patterns in Dictyostelium. GFP–LactC2 (left), PHcrac–mCherry (middle) and a merged view (right) are shown. (b) Ventral-wave propagation in RAW 264.7 macrophages. Overall pattern in the cell (left) and the pattern in the zoomed-in area corresponding to the white rectangular boxes in the left panels (right). GFP–LactC2 (top channels) and PHAkt–mCherry (bottom channels) are shown. Scale bar, 10 μm. Time is shown in mm:ss format (top-left corners).

Supplementary Video 4

Dynamic preferential distribution of generic negative surface-charge sensor to the back state of the membrane in Dictyostelium. The spatiotemporal patterns were observed during ventral-wave propagation (a) and protrusion formation (b). GFP–R(+8)-Pre (left), PHcrac–mCherry (middle) and merged views (right) are shown. Time is shown in mm:ss format (top-left corners).

Supplementary Video 5

Dynamic preferential distribution of generic negative surface-charge sensor to the back state of the membrane in ventral waves of RAW 264.7 macrophages. GFP–R(+8)-Pre (left), PHAkt–mCherry (middle) and a merged view (right) are shown. Time is shown in mm:ss format (top-left corners).

Supplementary Video 6

Dissociation of the PI4P sensor PHOsh2X2 and PI(4,5)P2 sensor PHPLCδ following recruitment of pseudojanin by a chemically induced dimerization system in RAW 264.7 macrophages. a,b, PHOsh2X2–GFP (left) and pseudojanin (right). c,d, GFP–PHPLCδ (left) and pseudojanin (right). The RAW 264.7 cells also express Lyn-FRB. The time of rapamycin addition is indicated by the appearance of the white text ‘+Rapamycin’ in the top middle. Time is shown in mm:ss format (top-left corners).

Supplementary Video 7

Profile of membrane surface-charge sensor R(+8)-Pre following the recruitment of pseudojanin by a chemically induced dimerization system in RAW 264.7 macrophages. a,b, Two examples of pseudojanin recruitment in RAW 264.7 cells coexpressing GFP–R(+8)-Pre and Lyn-FRB. GFP–R(+8)-Pre (left) and pseudojanin (right). The time of rapamycin addition is indicated by the appearance of the white text ‘+Rapamycin’ in the top middle. Time is shown in mm:ss format (top-left corners).

Supplementary Video 8

Optically confined recruitment of Opto-ACTU+ can trigger protrusions de novo. a–d, A 488-nm laser was selectively irradiated inside the white rectangular boxes; time is indicated in seconds (top-left corner); untagged cAR1-CIBN was expressed. a,b, Two examples of Opto-ACTU+ recruitment into the back-state regions of the membrane showing the generation of new protrusions in the vicinity of the recruitment. a, The stage was moved to start recruitment at t = 0 s. LimEΔcoil (left; newly polymerized F-actin sensor) and Opto-ACTU+ (right). c,d, Two examples of Opto-CTRL recruitment in the back states of the membrane, showing no generation of new protrusions from the recruitment areas. LimEΔcoil (left; newly polymerized F-actin sensor) and Opto-CTRL (right).

Supplementary Video 9

Global recruitment of Opto-ACTU+ to the membrane in a polarized Dictyostelium cell elicits random protrusions and abrogates pre-existing polarity and persistent migration. a, Global optical recruitment of Opto-ACTU+. Opto-ACTU+ (left) and DIC (right). b, Global optical recruitment of Opto-CTRL. Opto-CTRL (left) and DIC (right). a,b, Untagged cAR1-CIBN was expressed. Time is shown in seconds (top-left corners). The time before recruitment is shown with a negative sign. The 488-nm laser was turned on at t = 0 s to initiate recruitment, as depicted by the appearance of the green text ‘488 nm ON’ (bottom middle).

Supplementary Video 10

The changes in cell morphology and migration mode following global recruitment of Opto-ACTU+ are reversible. a,b, Two examples where Opto-ACTU+ was first recruited to the membrane by turning on the 488-nm laser (recruitment initiated when the white text ‘488 nm OFF’ switched to green text ‘488 nm ON’ in the videos), which resulted increased protrusion formation, loss of polarity and impaired migration; to reverse the process, the laser was turned off (when the green text ‘488 nm ON’ switched to the white text ‘488 nm OFF’), Opto-ACTU+ returned to the cytosol, and the cell eventually regained its polarized morphology and migration behaviour. Opto-ACTU+ (left) and DIC (right). Untagged cAR1-CIBN was expressed. Time is shown in mm:ss (a) and hh:mm:ss (b) format (top-left corners).

Supplementary Video 11

Changes in the migration mode and morphology of a PTEN− Dictyostelium cell, pre-treated with the PI3K inhibitor LY294002, following global recruitment of Opto-ACTU+. Opto-ACTU+ (left) and DIC channel (right). Untagged cAR1-CIBN was expressed. Time is shown in mm:ss format (top-left corners). The 488-nm laser was turned on to initiate recruitment, as depicted by the appearance of the white text ‘488 nm ON’ (bottom middle).

Supplementary Video 12

Optically confined recruitment of Opto-ACTU− can locally suppress protrusions in RAW 264.7 macrophages. a–c, A 488-nm laser was selectively irradiated inside the white rectangular boxes; untagged CIBN-CAAX was expressed. Time is shown in mm:ss format (top-left corners). Either Opto-ACTU− (a,b) or Opto-CTRL (c) were first locally recruited before the cells were globally stimulated with a C5a-receptor agonist. The appearance of the white text ‘+C5aR Agonist’ in the videos denotes the addition of the agonist. Lifeact–mVenus (left) and Opto-ACTU− (a,b(right)) or Opto-CTRL (c(right)).

Supplementary Video 13

Global recruitment of Opto-ACTU− to the membrane of MCF10A epithelial cells can deactivate the EGF-induced ERK activation. a, Translocation of ERK-KTR from the cytosol to the nucleus following Opto-ACTU− recruitment. ERK-KTR-iRFP713 (left) and Opto-ACTU− (right). b, ERK-KTR maintained its cytosolic distribution following Opto-CTRL recruitment. ERK-KTR-iRFP713 (left) and Opto-CTRL (right). a,b, Time is shown in hh:mm:ss format (top-left corners). A 488-nm laser was globally turned on at t = 0 s (as shown by the appearance of the green text ‘488 nm ON’). Cells were pre-treated with a saturated dose of EGF and maintained in that condition throughout the experiment.

Supplementary Tables 1 and 2

Supplementary Table 1. Different charge sensors and membrane marker controls. The net charge, sequence length and exact sequence or reference are listed. Positively charged amino acids are shown in green and negatively charged amino acids in red. Supplementary Table 2. Parameter values for the computational model.

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Banerjee, T., Biswas, D., Pal, D.S. et al. Spatiotemporal dynamics of membrane surface charge regulates cell polarity and migration. Nat Cell Biol 24, 1499–1515 (2022). https://doi.org/10.1038/s41556-022-00997-7

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