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Membrane phase separation drives responsive assembly of receptor signaling domains

Nature Chemical Biology volume 19, pages 750–758 (2023)Cite this article

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Abstract

Plasma membrane heterogeneity has been tied to a litany of cellular functions and is often explained by analogy to membrane phase separation; however, models based on phase separation alone fall short of describing the rich organization available within cell membranes. Here we present comprehensive experimental evidence motivating an updated model of plasma membrane heterogeneity in which membrane domains assemble in response to protein scaffolds. Quantitative super-resolution nanoscopy measurements in live B lymphocytes detect membrane domains that emerge upon clustering B cell receptors (BCRs). These domains enrich and retain membrane proteins based on their preference for the liquid-ordered phase. Unlike phase-separated membranes that consist of binary phases with defined compositions, membrane composition at BCR clusters is modulated through the protein constituents in clusters and the composition of the membrane overall. This tunable domain structure is detected through the variable sorting of membrane probes and impacts the magnitude of BCR activation.

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Fig. 1: BCR clustering produces membrane domains that differently sort plasma membrane-anchored fluorescent proteins.
Fig. 2: Anchor concentrations near receptor clusters are quantitatively predicted by GPMV partitioning measurements.
Fig. 3: BCR phosphorylation is modulated by perturbations of domain contrast.
Fig. 4: Relative anchor mobility is predicted by Lo enrichment.
Fig. 5: A model for adaptive membrane organization.

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Data availability

A subset of the data used in this study (localizations and regions of interests) is available along with data analysis scripts at https://github.com/VeatchLab/smlm-analysis. All raw localizations, regions of interest and .fcs data are available at https://zenodo.org/record/7508426 (https://doi.org/10.5281/zenodo.7508426).

Code availability

Algorithms used by custom analysis code are described in detail in the Methods, and most have been reported previously17,18,19. Analysis code, sample data and example analysis scripts are available at https://zenodo.org/record/7478055 (https://doi.org/10.5281/zenodo.7478055). Updated versions may be available at https://github.com/VeatchLab/smlm-analysis.

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Acknowledgements

We thank B. Machta, T. Shaw, I. Graf, N. Bag and B. Baird for helpful conversations and A. Stoddard with assistance preparing minimal co-receptor constructs and transduced cell lines. Research was supported by grants from the National Institutes of Health (GM110052 to S.L.V. and GM134949 and GM124072 to I.L.), the National Science Foundation (MCB1552439 to S.L.V.), the American Cancer Society (PF1800401CCE to S.A.S.), the Volkswagen Foundation (grant 93091 to I.L.) and the Human Frontier Science Program (RGP0059/2019 to I.L.).

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  1. Sarah A. Shelby

    Present address: Department of Biochemistry & Cellular and Molecular Biology, University of Tennessee Knoxville, Knoxville, TN, USA

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  1. Program in Biophysics, University of Michigan, Ann Arbor, MI, USA

    Sarah A. Shelby, Kathleen C. Wisser & Sarah L. Veatch

  2. Department of Molecular Physiology and Biological Physics, University of Virginia, Charlottesville, VA, USA

    Ivan Castello-Serrano & Ilya Levental

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Contributions

S.A.S. conducted all single-molecule microscopy and flow cytometry experiments, including sample preparation and imaging. S.A.S. conjugated fluorophores to antibodies used for imaging. K.W. performed the calcium mobilization measurement and prepared the majority of mEos3.2 tagged anchor constructs using molecular biology. I.C.S. conducted all phase partitioning measurements in isolated plasma membrane vesicles and quantified results. S.A.S. prepared individual single-molecule images in cells for further analysis (single-molecule localization, defining regions of interest, etc.), and S.L.V. and S.A.S. conducted analysis on the dataset as a whole (merging across cells, defining correlations, statistical calculations, etc.). S.L.V. conducted the diffusion analysis. S.A.S. and S.L.V. analyzed the flow cytometry results. S.A.S. and S.L.V. conceptualized the manuscript. S.L.V. and I.L. supervised the work. S.A.S. and S.L.V. wrote the manuscript and prepared all figures, with review and editing support from I.L.

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Correspondence to Sarah L. Veatch.

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Nature Chemical Biology thanks Toshihide Kobayashi, Pieta Mattila and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Extended data

Extended Data Fig. 1 Estimating the size of BCR clusters.

a, BCR auto-correlation functions, g(r, τ), for a single cell expressing the M anchor between 2 and 10 min after BCR crosslinking. Curves are fit at fixed τ to \(g\left( {r,\tau } \right) = 1 + A \times {{{\mathrm{exp}}}}\left\{ { - \frac{{r^2}}{{4\sigma ^2}}} \right\}\) to extract the amplitude (A) and range (σ) of correlations. b, Plots of A versus τ for the same cell. We attribute the large amplitude at short τ (<0.1 s) to multiple sequential observations of the same fluorophore, while correlations at larger τ (>0.1 s) largely arise from different fluorophores in the same BCR cluster. c, Plots showing the σ versus τ for the same cell. At short τ (<0.1 s), the range of correlations reports on the localization precision of the measurement. At larger τ (>0.1 s), σ reflects the size of BCR clusters convoluted with the motion of clusters, which tends to further broaden g(r) at long τ. Based on this we estimate average BCR cluster radius in this cell to be near 34 nm, which is roughly σ(0.1 s). d, A histogram showing the distribution of σ(0.1 s) extracted from BCR autocorrelations over 125 cells from Fig. 1 has a mean and s.e.m. of 33 ± 4 nm.

Extended Data Fig. 2 Representative images from cells expressing minimal anchors reconstructed using localizations acquired between 2 and 10 min after BCR clustering.

Reconstructed images of representative B cells expressing mEos3.2 conjugated to the indicated anchor (pseudo-colored green) from localizations acquired between 2 and 10 min after BCR clustering. Cells are labeled with biotinylated and SiR-labeled Fab anti-IgMµ (pseudo-colored magenta) that is crosslinked with soluble streptavidin. Scale bars are 1 μm in the main figures and 10 μm in the insets. The cell shown is representative of the total number of cells imaged for each anchor that is shown in Supplementary Fig. 3.

Extended Data Fig. 3 Steady-state cross-correlation functions in cells before and after BCR crosslinking.

a, Average cross-correlation functions, c(r), between BCR and anchors in cells prior to BCR crosslinking (-Ag) or between 2 and 10 min after streptavidin addition (+Ag). Points represent the average over multiple cells and the shaded region represents the s.e.m.. Cell numbers interrogated for each anchor and distributions of c(r < 50 nm) are shown in Supplementary Fig. 3. b, c, Mean and s.e.m. for c(r < 50 nm) for cells imaged prior to BCR crosslinking (b) or between 2 and 10 min after BCR crosslinking (c) replotted from part a. All anchors show weak co-localization with unclustered BCR (c(r < 50 nm) close to 1.1). Amplitudes are more varied across anchors after BCR crosslinking. Anchor labels ending in * indicate that values are from experiments where BCR was clustered in the presence of 5 µM PP2. Distributions of c(r < 50 nm) values across anchors are presented in Supplementary Fig. 3.

Extended Data Fig. 4 trPAG experiences specific, stimulation dependent interactions that contribute to its organization.

a, Changes in cross-correlation amplitudes (mean and s.e.m. Δc(r < 50 nm) over at least 6 cells replotted from Fig. 1) for BCR and select transmembrane anchors both in the presence and absence of 5 µM PP2. The exact number of cells in each condition are presented in Supplementary Fig. 3. trPAG was also imaged alongside clustered CTxB (×CTxB) in cells with (+Ag; n = 4) and without (n = 10) BCR clustering. P values shown are assessed using a two-tailed ttest. b, PP2 treatment brings trPAG partitioning in-line with the correlations for transmembrane anchors redrawn from Fig. 2d. Points are means and s.e.m. redrawn from Fig. 2d and red line is linear fit to transmembrane anchors with the red shaded region representing the 95% confidence interval of the linear fit, also replotted from Fig. 2d. c, d, Cells expressing trPAG were chemically fixed either without BCR crosslinking (-Ag) or 5 min after BCR crosslinking (+Ag). Points represent mean and s.e.m. over multiple cells (N shown in legends). Either Caveolin 1 (Cav1; c) or Focal Adhesion Kinase (FAK; d) were labeled post-fixation with specific primary and secondary antibodies. A subset of trPAG localizes with adhesive structures labeled by FAK (d), suggesting a stimulation dependent interaction gives rise to deviations from trends exhibited by other transmembrane anchors. Together, these results indicate that trPAG experiences stimulation dependent interactions not found for trLAT or GPI that lead it to localize away from BCR clusters (a,b).

Extended Data Fig. 5 Representative images of GPMVs containing all anchors.

Schematic representation of anchors above images of representative GPMVs and intensity traces. Vesicles are representative of 30 vesicles imaged over 3 distinct experiments for each anchor.

Extended Data Fig. 6 Correlations between GPMV and BCR partitioning of membrane anchors before and after BCR clustering.

Points represent mean and s.e.m. of c(r < 50 nm) replotted from Extended data Fig. 3b (left) and c (right) versus means and s.e.m. of Lo enrichment from GPMV measurements replotted from Fig. 2b. Cell numbers for each condition are shown in Supplementary Fig. 3. trPAG* values were obtained from experiments where BCR was clustered in the presence of 5 µM PP2. Trends are fit to a linear model and the significance is assessed with a P value of the two-sided hypothesis test against the hypothesis of no correlation (lower values indicate greater significance), and an f-statistic that reports how well the variance in the data is described by the linear fit (higher values indicate greater significance). Gray shaded regions indicate the 95% confidence interval of the linear fit.

Extended Data Fig. 7 Alcohol treatments that modulate BCR cluster domain contrast also modulate downstream Ca2+ mobilization responses.

a, Representative calcium mobilization traces for CH27 cells pretreated with n-alcohols and stimulated with 2.5 µg/ml F(ab’)2 fragments against the µ subunit of IgM BCR, as measured by the calcium-sensitive dye Flou-4 AM (left). Baseline drift was corrected by fitting a line to the Fluo-4 fluorescence trace prior to antigen addition and dividing the entire fluorescence trace by this baseline. Hexadecanol (hex) or octanol (oct) were added from stock solutions in DMSO, or an equivalent final concentration of DMSO was added as a carrier control. Points are mean and s.e.m. from two technical replicates per condition. (Right) Maximum fluorescence signal from calcium traces normalized to maximum values for the DMSO treated control. Cells were stimulated with varied F(ab’)2 concentrations (3.6, 3, 2.5 and 10 µg/ml). Peak values of fluorescence fold increase traces for hexadecanol or octanol-treated cells were normalized by peak values for DMSO-treated cells recorded during the same experiment with equivalent stimulation conditions. Colored symbols show mean and SE of 4 independent measurements. b, Calcium mobilization was measured and quantified as in a, but cells were stimulated via the PC-specific BCRs expressed by the CH27 cell line by addition of 100 nm lipid vesicles containing POPC lipids at 300 µg/ml (right). Same as in a but cells were stimulated with either 300 µg/ml POPC vesicles or vesicles composed of 1:1 mixture of POPC and 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphoethanolamine. Colored symbols show mean and SE of 4 independent measurements. In both a and b, P values from a single-tailed t-test estimate the significance of deviations of responses of treated cells compared to the (normalized) DMSO control, while a two-tailed t-test is used to compare responses in Hex and Oct treated cells.

Extended Data Fig. 8 Alcohol treatments that modulate domain contrast also modulate TCR phosphorylation in Jurkat cells.

a, Representative histograms from flow cytometry measurements of pTCR staining (log axis scale). Jurkat cells were pre-treated with either hexadecanol (Hex; top) or octanol (Oct; bottom) before co-stimulation through the T cell receptor (CD3) and CD28 coreceptor with primary (α) and secondary (2°) antibodies. Phospho-TCR is labeled using an antibody against the phosphorylated form of Y142 on CD3ζ. b, Summary of pTCR levels of various treatments normalized to pTCR levels of DMSO treated (control) cells stimulated with anti-CD3, anti-CD28, and secondary antibodies. Large points represent mean and s.e.m. over three independent measurements for each condition. P values from a single-tailed t-test estimate the significance of deviations of responses of treated cells compared to the (normalized) DMSO control, while a two-tailed t-test is used to compare responses in Hex and Oct treated cells.

Extended Data Fig. 9 Moving mEos3.2 probe to the extracellular terminus slows diffusion (D) and increases the population of confined diffusers (α) for both trLAT and trCD4.

a, Diffusion coefficients (D) for the mobile component and the fraction of molecules in the confined state (α) are plotted versus Lo enrichment in GPMVs. Points for D and α are averages and s.e.m. over values extracted from single cells, and Lo enrichment is mean and s.e.m. replotted from Fig. 2b. Most points are replotted from Fig. 4a. Constructs with extracellular mEos3.2 are shown as open symbols and arrows highlight the change for trLAT and trCD4 when the probe is moved from the cytoplasmic side of the transmembrane anchor (trLAT and trCD4) to the extracellular space (trLATo and trCD4o). Cell numbers for each condition are shown in Supplementary Fig. 3 other than trLATo (n = 5) and trCD4o (n = 3). b, Probe enrichment at BCR clusters for trLAT and trCD4 anchors with intracellular or extracellular probes. Large points indicate mean and s.e.m. over values in individual cells, with cell numbers indicated. Repositioning the probe does not significantly impact probe enrichment at BCR clusters as evaluated using a two-tailed t-test. For these anchors, positioning mEos3.2 on the extracellular face dramatically impacts anchor surface expression, leading to large statistical errors.

Extended Data Fig. 10 Summary of fit parameters describing anchor mobility at τ = 15 ms.

Diffusion coefficients (D) for the mobile component, the fraction of molecules in the confined state (α), and the confinement radius averaged over cells expressing the specified anchor for all conditions investigated. In all panels, vertical positions are means and s.e.m. of the specified parameter over multiple cells, with cell numbers for each anchor reported in Supplementary Fig. 3. Horizontal positions for all panels are means and s.e.m. replotted from Fig. 2b. Anchor labels ending in * indicate that values are from experiments where BCR was clustered in the presence of 5 µM PP2. For the condition ‘BCR proximal’, anchor localizations found within 100 nm of a BCR localization are cross-correlated with all anchor localizations as described in Methods. The fitting of BCR proximal curves was accomplished by fixing the confinement radius to the value obtained for all trajectories (τ = 2–10 min) to improve the robustness of fitting to correlation functions with reduced signal to noise. Trends in α and confinement radius are fit to a linear model and the significance is assessed with a P value of the two-sided hypothesis test against the hypothesis of no correlation (lower values indicate greater significance), and an f-statistic reports how well the variance in the data is described by the linear fit (higher values indicate greater significance). All points are included in the linear fit. Shaded regions indicate the 95% confidence interval of the fit.

Supplementary information

Supplementary Information

Supplementary Tables 1 and 2, Supplementary Figs. 1–14 and Supplementary Note 1

Reporting Summary

Single-molecule motions of BCR and PM before BCR crosslinking. Time-lapse video showing reconstructed single-molecule positions evolving in time for BCR (magenta) and PM (green) for the same PM-expressing cell shown in Fig. 1a. These localizations were acquired <1 min before the addition of streptavidin. Localizations are drawn on a reconstructed image of all PM localizations for this cell. The movie is displayed with a frame rate that is 5× slower than real time. Images were acquired at nearly 50 frames per second under total internal reflection illumination. Scale bar is 5 µm.

Single-molecule motions of BCR and PM after BCR crosslinking. Time-lapse video showing reconstructed single-molecule positions evolving in time for BCR (magenta) and PM (green) for the same PM-expressing cell shown in Fig. 1a. These localizations were acquired ~2 min after addition of streptavidin. Localizations are drawn on a reconstructed image of all PM localizations for this cell. The movie is displayed with a frame rate that is 5× slower than real time. Images were acquired at nearly 50 frames per second under total internal reflection illumination. Scale bar is 5 µm.

Single-molecule motions of BCR and M before BCR crosslinking. Time-lapse video showing reconstructed single-molecule positions evolving in time for BCR (magenta) and M (green) for the same M-expressing cell shown in Fig. 1a. These localizations were acquired <1 min before the addition of streptavidin. Localizations are drawn on a reconstructed image of all M localizations for this cell. The movie is displayed with a frame rate that is 5× slower than real time. Images were acquired at nearly 50 frames per second under total internal reflection illumination. Scale bar is 5 µm.

Single-molecule motions of BCR and M after BCR crosslinking. Time-lapse video showing reconstructed single-molecule positions evolving in time for BCR (magenta) and M (green) for the same M-expressing cell shown in Fig. 1a. These localizations were acquired ~2 min after addition of streptavidin. Localizations are drawn on a reconstructed image of all M localizations for this cell. The movie is displayed with a frame rate that is 5× slower than real time. Images were acquired at nearly 50 frames per second under total internal reflection illumination. Scale bar is 5 µm.

Time lapse of BCR and PM organization before and after BCR crosslinking. Time-lapse movie composed of reconstructed images of BCR (magenta) and PM (green) from the same representative cell shown in Fig. 1a, shown here at higher time resolution to demonstrate how BCR and PM organization evolve over time. Each sequential image is reconstructed from a window of 750 frames (~20 seconds) incremented by 250 (~6 seconds) frames for each image. The entire time lapse spans the length of the live cell experiment, and the real time of data acquisition is shown in the bottom left, where 0 min corresponds to streptavidin addition. Before streptavidin addition, both BCR and PM are relatively uniformly distributed across the plasma membrane. After streptavidin addition, BCR rapidly forms tight clusters. BCR clusters are relatively immobile compared to PM but do exhibit dynamics that are evident in the time lapse. Scale bar is 5 µm.

Time lapse of BCR and M organization before and after BCR crosslinking. Time-lapse movie composed of reconstructed images of BCR (magenta) and M (green) from the same representative cell shown in Fig. 1a. Parameters for reconstruction of individual frames of the time lapse are the same as in Supplementary Movie 3, and the time lapse shows similar organization of BCR and M before and after streptavidin addition. Time before and after streptavidin addition are shown in the bottom left, and the scale bar is 5 µm.

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Shelby, S.A., Castello-Serrano, I., Wisser, K.C. et al. Membrane phase separation drives responsive assembly of receptor signaling domains. Nat Chem Biol 19, 750–758 (2023). https://doi.org/10.1038/s41589-023-01268-8

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