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CD63 sorts cholesterol into endosomes for storage and distribution via exosomes

Nature Cell Biology volume 26, pages 1093–1109 (2024)Cite this article

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Abstract

Extracellular vesicles such as exosomes are now recognized as key players in intercellular communication. Their role is influenced by the specific repertoires of proteins and lipids, which are enriched when they are generated as intraluminal vesicles (ILVs) in multivesicular endosomes. Here we report that a key component of small extracellular vesicles, the tetraspanin CD63, sorts cholesterol to ILVs, generating a pool that can be mobilized by the NPC1/2 complex, and exported via exosomes to recipient cells. In the absence of CD63, cholesterol is retrieved from the endosomes by actin-dependent vesicular transport, placing CD63 and cholesterol at the centre of a balance between inward and outward budding of endomembranes. These results establish CD63 as a lipid-sorting mechanism within endosomes, and show that ILVs and exosomes are alternative providers of cholesterol.

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Fig. 1: Characterization of WT and CD63 KO HeLa and MNT-1 cells and sEVs.
Fig. 2: Proteome analysis of WT and CD63 KO HeLa and MNT-1 cells and sEVs.
Fig. 3: Lipidome analysis of WT and CD63 KO HeLa and MNT-1 cells and sEVs.
Fig. 4: Cholesterol localization in WT and CD63 KO HeLa cells.
Fig. 5: Absence of CD63 induces accumulation of cholesterol at the Golgi apparatus and actin-dependent endosomal tubulations.
Fig. 6: CD63 presents an intramembrane cavity able to accommodate cholesterol.
Fig. 7: CD63 modulates cholesterol trafficking to sEVs and exosomes, affecting their biophysical properties.
Fig. 8: CD63 sEVs can transfer cholesterol to recipient cells.

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Data availability

The mass spectrometry proteomics raw data have been deposited to the ProteomeXchange Consortium via the PRIDE partner repository. The datasets are publicly available at the following links. ProteomeXchange title: Human – Cells and Extracellular vesicles of Hela and MNT-1 WT vs CD63 KO Proteomes 1: ProteomeXchange accession PXD037146, project webpage http://www.ebi.ac.uk/pride/archive/projects/PXD037146, FTP download https://ftp.pride.ebi.ac.uk/pride/data/archive/2024/04/PXD037146. ProteomeXchange title: Human – Cells and Extracellular vesicles of Hela and MNT-1 WT vs CD63 KO Proteomes 2: ProteomeXchange accession PXD037147, project webpage http://www.ebi.ac.uk/pride/archive/projects/PXD037147, FTP download https://ftp.pride.ebi.ac.uk/pride/data/archive/2024/04/PXD037147. ProteomeXchange title: Human – Cells and Extracellular vesicles of Hela and MNT-1 WT vs CD63 KO Exosomes: ProteomeXchange accession PXD037149, project webpage http://www.ebi.ac.uk/pride/archive/projects/PXD037149, FTP download https://ftp.pride.ebi.ac.uk/pride/data/archive/2024/04/PXD037149. UniProt accession codes: Homo Sapiens (UP000005640), P08962 for CD63, P60033 for CD81 and P21926 for CD9. Lipidomics datasets have been included in full in the Supplementary tables, provided as source data. All relevant data are included in the Article. Data supporting the findings of this study are available from the corresponding author on reasonable request. Source data are provided with this paper.

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Acknowledgements

This work was funded by the Institut Curie International PhD Program (to R.P.), the Fondation ARC pour la Recherche sur le Cancer (DOC20180507506 to R.P. and PGA1 RF20190208474 to M.C.), the Fondation pour la Recherche Médicale (AJE20160635884 to G.v.N.), the Institut National du Cancer (grant no. 2019-125 PLBIO19°059), ANR (ANR-20-CE18-0026-01 to G.v.N. and ANR-18-CE13-0017-02 to E.R.), Région Ile-de-France and Fondation pour la Recherche Médicale grants (to D.L.) and the STW Cancer-ID program (project no. 14192 to W.H.R.). We thank the Cell and Tissue Imaging core facility (PICT IBiSA) and Nikon Imaging Centre at Institut Curie–CNRS, member of the French National Research Infrastructure France–BioImaging (ANR-10-INBS-04) and the NeurImag core facility team for their technical and scientific support. NeurImag is part of IPNP, Inserm U1266 and Université Paris Cité and a member of the national infrastructure France-BioImaging supported by the French National Research Agency (ANR-10-INBS-04). We also thank the Leducq establishment for funding the Leica SP8 confocal/STED 3DX system, the Bettencourt Foundation for funding the Leica/Yokogawa spinning disc system, A. Canette and M. Trichet at the Service de Microscopie Électronique (SME) de l’Institut de Biologie Paris-Seine, and C. Durieu at ImagoSeine core facility of Institut Jacques Monod, member of France–BioImaging (ANR-10-INBS-04) and IBiSA, with the support of Labex ‘Who Am I’, Inserm Plan Cancer, Region Ile-de-France and Fondation Bettencourt Schueller. We thank the Structure and Membrane Compartment laboratory and the Endosomal Dynamic in Neuropathies laboratory for insightful discussions. We thank F. Alpy for discussions and providing essential reagents.

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  1. These authors contributed equally: Roberta Palmulli, Mickaël Couty.

Authors and Affiliations

  1. Institut Curie, PSL Research University, CNRS, UMR144, 26 rue d’Ulm, 75248, Paris Cedex 05, France

    Roberta Palmulli, Graça Raposo & Guillaume van Niel

  2. Institute of Psychiatry and Neuroscience of Paris (IPNP), Université de Paris, Paris, France

    Roberta Palmulli, Mickaël Couty, Frederik J. Verweij, Matteo Tantucci & Guillaume van Niel

  3. CRCI2NA, Nantes Université, Inserm UMR1307, CNRS UMR6075, Université d’Angers, Nantes, France

    Mickaël Couty & Guillaume van Niel

  4. Moleculaire Biofysica, Zernike Instituut, Rijksuniversiteit Groningen, Groningen, The Netherlands

    Melissa C. Piontek, Sajitha Sasidharan & Wouter H. Roos

  5. Foundation for Innovation in Cardiometabolism and Nutrition (IHU ICAN, ICAN OMICS and ICAN I/O), F-75013, Paris, France

    Maharajah Ponnaiah & Marie Lhomme

  6. CurieCoreTech Spectrométrie de Masse Protéomique, Institut Curie, PSL Research University, Paris, France

    Florent Dingli & Damarys Loew

  7. Centre d’Immunologie et des Maladies Infectieuses (CIMI), Sorbonne Université, Inserm, Paris, France

    Stéphanie Charrin & Eric Rubinstein

  8. ICAN, National Institute for Health and Medical Research, Paris, France

    Anatol Kontush

  9. Institut Curie, PSL Research University, CNRS, UMR144, Cell and Tissue Imaging Facility (PICT-IBiSA), 26, rue d’Ulm, 75248, Paris Cedex 05, France

    Graça Raposo

  10. GHU-Paris Psychiatrie et Neurosciences, Hôpital Sainte Anne, Paris, France

    Guillaume van Niel

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  1. Roberta Palmulli
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Contributions

R.P., M.C. and G.v.N. designed, performed and analysed most of the experiments. R.P. and G.v.N. wrote the paper with help from M.C., M.C.P. and W.H.R. M.C.P., S.S. and W.H.R. performed and analysed atomic force microscopy. F.D. and D.L. performed and analysed proteome mass spectrometry. M.P., M.L. and A.K. performed lipidomic analysis and/or analysed lipidomic data. F.J.V., S.C., M.T. and E.R. performed experiments and/or generated tools and cell lines. G.R. and G.v.N. acquired funding. G.v.N. conceived and supervised the study. All authors read and approved the paper.

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Correspondence to Guillaume van Niel.

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Extended data

Extended Data Fig. 1 Characterization of WT, CD63 KO, siRNA treated, cells and sEVs.

a. NTA analysis of sEVs derived from WT or CD63 KO HeLa cells and isolated by SEC. Average number of particles/ml (n = 7 independent experiments, Ordinary one-way ANOVA, ns P = 0.6449 and ns P = 0.9359). b. DLS analysis of sEVs derived from WT or CD63 KO HeLa cells grown in FBS supplemented media. Average number of particles/ml (n = 5 independent experiments, two-tailed unpaired t test, ns P = 0.9135). c. DLS analysis of sEVs derived from WT or CD63 KO HeLa or MNT-1 cells grown in LPDS. Average number of particles/ml (n = 5 independent experiments, two-tailed Mann-Whitney test for Hela cells, ns P = 0.5952; two-tailed unpaired t test for MNT-1 cells, ns P = 0.3579). d. Western blot analysis of cell lysates and sEVs derived from Ctrl or CD63 siRNA-treated MNT-1 cells and isolated by ultracentrifugation. Quantification of protein content normalized to Ctrl siRNA-treated MNT-1 for cell lysates (n= independent experiments, n = 5 for CD9, n = 6 for alix, syntenin, n = 7 for CD63, ApoE, unpaired multiple t test, **** P = 0.000027) and for sEVs (n = independent experiments, n = 3 for CD9, n = 5 for other markers, unpaired multiple t test, ** CD63 P = 0.01129, ** ApoE P = 0.0065). e. NTA analysis of sEVs derived from Ctrl or CD63 siRNA-treated MNT-1 cells and isolated by ultracentrifugation. Average number of particles/ml (mean of 2 independent experiments) or size distribution (data are presented as the mean of 2 independent experiments). Data are presented as mean values +/− SEM. Source numerical data and unprocessed blots are available in source data.

Source data

Extended Data Fig. 2 Proteomic analysis of WT and CD63 KO cells and sEVs.

a. Volcano plot of proteins identified by at least 2 peptides in at least 3 replicates. Shown are the fold changes of peptide abundance between WT or CD63 KO HeLa cells and the p-value of this quantification. b. List of proteins enriched in WT HeLa cell proteome. List of Cellular components GO terms in WT HeLa cells. c. Volcano plot of proteins identified by at least 2 peptides in at least 3 replicates. Shown are the fold changes of peptide abundance between WT or CD63 KO HeLa sEVs and the p-value of this quantification. d. List of proteins enriched in WT HeLa sEVs proteome. List of Cellular components GO terms in WT HeLa sEVs. e. Volcano plot of proteins identified by at least 2 peptides in at least 3 replicates. Shown are the fold changes of peptide abundance between WT or CD63 KO MNT-1 cells and the p-value of this quantification. f. List of proteins enriched in WT MNT-1 cell proteome. List of Cellular components GO terms in WT MNT-1 cells. g. Volcano plot of proteins identified by at least 2 peptides in at least 3 replicates. Shown are the fold changes of peptide abundance between WT or CD63 KO MNT-1 sEVs and the p-value of this quantification. h. List of proteins enriched in WT MNT-1 sEVs. List of Cellular components GO terms in WT MNT-1 sEVs. A linear model (adjusted on peptides and biological replicates) was performed, and a two sided T-test was applied on the fold change estimated by the model. The p-values were then adjusted using the Benjamini–Hochberg FDR procedure. Source numerical data are available in source data.

Source data

Extended Data Fig. 3 Lipidomic analysis of WT, CD63 KO cells and sEVs.

a. Clustered heatmap of significantly altered lipid features (following FDR correction) identified in WT or CD63 KO HeLa cells (n = independent experiments, 3 for WT and 7 for KO, two-tailed Mann–Whitney test). b. Clustered heatmap of significantly altered lipid features (following FDR correction) identified in WT or CD63 KO MNT-1 cells (n = 3 independent experiments, two-tailed Mann-Whitney test). P values: *P = < 0.05, **P = < 0.01, ***P = < 0.001. Source numerical data are available in source data.

Source data

Extended Data Fig. 4 Cholesterol trafficking in WT, CD63 KO, and siRNA treated cells.

a. Clustered heatmap of significantly altered lipid features (following FDR correction) identified in WT or CD63 KO HeLa sEVs (n = 8 independent experiments, two-tailed Student’s paired t test). b. Clustered heatmap of significantly altered lipid features (following FDR correction) identified in WT or CD63 KO MNT-1 sEVs (n = 5 independent experiments, two-tailed Student’s paired t test). c. PC/PE molar ratio in HeLa cells and sEVs (n = 3 independent experiments for WT cells (min, Q1-min, median-Q1, Q3-median, max-Q3; (2.75, 0.3, 0.3, 0.13, 0.13)), n = 7 independent experiments for KO cells (min, Q1-min, median-Q1, Q3-median, max-Q3; (3.03, 0.21, 0.29, 1.06, 0.59)), n = 4 independent experiments for WT sEVs (min, Q1-min, median-Q1, Q3-median, max-Q3; (1.47, 0.06, 0.05, 0.14, 0.32)), n = 8 independent experiments for KO sEVs (min, Q1-min, median-Q1, Q3-median, max-Q3; (1.63, 0.36, 0.08, 0.15, 0.28)), two-tailed student t test). d. PC/PE molar ratio in MNT-1 cells and sEVs (n = 3 independent experiments for WT cells (min, Q1-min, median-Q1, Q3-median, max-Q3; (5.48, 0.1, 0.11, 0.47, 0.47)), n = 3 independent experiments for KO cells (min, Q1-min, median-Q1, Q3-median, max-Q3; (0.13, 2.59, 0.99, 0.2, 0.22)), (n = 5 independent experiments for WT sEVs (min, Q1-min, median-Q1, Q3-median, max-Q3; (2.72, 0.12, 0.32, 0.55, 1.04)), n = 5 independent experiments for KO sEVs, (min, Q1-min, median-Q1, Q3-median, max-Q3; (3.14, 0.05, 0.05, 0.51, 0.47)) two-tailed student t test). P values: *P = < 0.05, **P = < 0.01, ***P = < 0.001. Source numerical data are available in source data.

Source data

Extended Data Fig. 5 Effect of CD63 depletion on the anterograde and retrograde trafficking of cargoes.

a. HeLa cells WT or CD63 KO were grown in FBS, processed for ultrathin cryo-sectioning and immunogold labeled with D4-GFP (PAG 10 nm) and CD63 (PAG 5 nm). Bars = 200 nm. Representative of 2 independent experiments. b. Cholesterol content of WT and CD63 KO HeLa or MNT-1 cells measured by Amplex Red assay. (n = 3 independent experiments, Mann-Whitney test for HeLa, ns P > 0.9999, unpaired t test for MNT-1, ns P = 0.9256). c. Western blot analysis of WT or CD63 KO HeLa cell lysates. Quantification of protein content, shown as the ratio between nuclear SREBP2 and total SREBP2, normalized to HeLa WT (n = 3 independent experiments, Ordinary one-way ANOVA, ns P = 0.4827 and 0.5698). d. Localization of Nile Red (staining lipid droplets) in WT and CD63 KO HeLa cells. Bars=10 µm. Quantification of Nile Red fluorescence intensity (n= number of cells, H WT n = 27, H CD63 KO#1 n = 25, H CD63 KO#2 n = 35, from 1 independent experiment, Ordinary one-way ANOVA, ns P > 0.05). e. WT or CD63 KO MNT-1 cells were grown in LPDS, processed for ultrathin cryo-sectioning and immunogold labeled with D4-GFP (PAG 10 nm). White arrows indicate MVEs containing cholesterol. Bars=200 nm. Representative of 2 independent experiments. f. Ctrl or CD63 siRNA-treated MNT-1 cells were grown in LPDS, processed for ultrathin cryo-sectioning and immunogold labeled with D4-GFP (PAG 10 nm) and CD63 (PAG 5 nm). White arrows indicate MVEs and black arrows Golgi stacks enriched in cholesterol. Bars=500 nm. Representative of 2 independent experiments. g. Localization of cholesterol stained with D4-GFP in WT or CD63 KO non-permeabilized Hela cells, Bars=10 µm. Quantification of D4-GFP intensity of fluorescence (n = 42 WT cells and, n = 89 KO cells pooled across 2 independent experiments, two-tailed Mann-Whitney test, **** P < 0.0001). Data are presented as mean values +/− SEM. Source numerical data and unprocessed blots are available in source data.

Source data

Extended Data Fig. 6 Endosomal actin-dependent tubulation is required for cholesterol trafficking in absence of CD63.

a. Localization of VSVG-EGFP-RUSH in WT or CD63 KO HeLa cells at different time (T) points after biotin addition. Biotin was added at T = 0. Bars = 10 µm. Representative of 2 independent experiments. b, c. Pulse - chase of anti CI-M6PR antibody in WT or CD63 KO HeLa cells (b) or MNT-1 cells treated with control or CD63 siRNA (c), and IFM with secondary antibody anti-mouse for CI-M6PR. CI-M6PR staining is shown as pseudo-color. Bars = 10 µm. CI-M6PR fluorescence intensity in the whole cells or in the Golgi area was measured. Quantifications show the ratio of vesicular /Golgi fluorescence intensity associated with CI-M6PR. (H WT n = 51 cells, H CD63 KO#1 n = 55 cells, H CD63 KO#2 n = 52 cells, pooled across 3 independent experiments, Ordinary one-way ANOVA, ** P = 0.0028, **** P < 0.0001; M siCtrl n = 18 cells, M siCD63 n = 18 cells, pooled across 2 independent experiments, two-tailed unpaired Student’s t test with Welch’s correction, ns P = 0.1292). d. IFM of WT or CD63 KO MNT-1 cells and of Ctrl or CD63 siRNA treated MNT-1 cells grown in LPDS and co-stained for endogenous ApoE and TGN46. Pearson’s correlation coefficient (n = 33 cells pooled across 3 independent experiments, two-tailed unpaired Student’s t test, **** P < 0.0001). e. IFM of Ctrl or CD63 siRNA treated MNT-1 cells grown in LPDS and co-stained for endogenous ApoE and GM130. Bars=10 µm. Pearson’s correlation coefficient (M siCtrl n = 22 cells and, M siCD63 n = 15 cells pooled across 3 independent experiments, two-tailed unpaired t-test, ** P = 0.0018). f. IFM of Ctrl or CD63 siRNA treated MNT-1 cells grown in LPDS and co-stained for endogenous ApoE and LAMP-1. Bars=10 µm. Pearson’s correlation coefficient (M siCtrl n = 27 cells and, M siCD63 n = 31 cells pooled across 3 independent experiments, two-tailed unpaired Student’s t test, *** P = 0.0002). Data are presented as mean values +/− SEM. Source numerical data are available in source data.

Source data

Extended Data Fig. 7 Rescue of CD63 KO cells with WT or E217Q CD63.

a. Electron micrograph of high-pressure frozen WT or CD63 KO MNT-1 cells. Bars= 500 nm. Representative of 2 independent experiments. b. SR-IFM of WT or CD63 KO HeLa cells treated with DMSO or CK666 and co-stained for EEA1 and actin. Bars=10 µm, bars= 5 µm for magnifications. Normalized phalloidin fluorescence on EEA1-positive endosomes (n = number of endosomes, H WT DMSO n = 174, H CD63 KO#1 DMSO n = 229, H CD63 KO#2 DMSO n = 214, H WT CK666 n = 102, H CD63 KO#1 CK666 n = 104, H CD63 KO#2 CK666 n = 90; pooled across 3 independent experiments, Ordinary one-way ANOVA, ns P > 0.05, **** P < 0.001). c. SR-IFM of MNT-1 cells WT or CD63 KO and co-stained for EEA1 and actin. Bars=10 µm, bars= 5 µm for magnifications. Normalized phalloidin fluorescence on EEA1-positive endosomes (n=number of endosomes, M siCtrl n = 348, M siCD63 n = 352; pooled across 3 independent experiments, two-tailed unpaired t-test with Welch’s correction, **** P > 0.001). d. Electron micrograph of HeLa cells WT or CD63 KO treated with CK666 and analyzed by 2D EM. Bars= 200 nm. Quantification of the number of tubules/buds per endosome (n= number of MVEs, DMSO treated cells are as shown in Fig. 5f, H WT CK666 n = 15, H CD63 KO#1 CK666 n = 49, H CD63 KO#2 n = 39; pooled across 2 independent experiments, Ordinary one-way ANOVA, ns P > 0.05, * P = 0.0164, ** P = 0.0066). e. Localization of TF-chol in WT and CD63 KO cells treated with CK666. Bars = 10 µm. Representative of 2 independent experiments. f. CD63 KO HeLa cells were grown in LPDS, treated with CK666, processed for ultrathin cryo-sectioning, and immunogold labeled with D4-GFP (PAG 10 nm). Bars = 200 nm. Quantification of number of gold particles on tubules per MVE (n = number of MVEs, H WT n = 12, H CD63 KO n = 82, pooled across 2 independent experiments, two-tailed unpaired t test with Welch’s correction, **** P < 0.0001). Data are presented as mean values +/− SEM. Source numerical data are available in source data.

Source data

Extended Data Fig. 8 Uptake of TF-cholesterol and MemBright labeled sEVs by recipient cells.

a. Localization of cholesterol stained with D4-mCherry in CD63 KO Hela cells rescued with CD63 WT or E217Q. Bars=10um. Quantification of D4-mCherry integrated density of fluorescence (n = 14 H CD63 KO + CD63 WT cells, 15 H CD63 KO + CD63 E217Q cells, pooled across 2 independent experiments, two-tailed Mann-Whitney test, ns P = 0.0848). b. Cholesterol content (Amplex Red assay) of WT or CD63 KO sEVs isolated from HeLa or MNT-1 cells grown in LPDS. Cholesterol content is normalized to the number of vesicles (g per sEV) (n = 4 independent experiments, Kruskal-Wallis test for Hela, ns P = 0.8593, ns P > 0.9999; two-tailed paired Wilcoxon test for MNT-1, ns P = 0.5000). c. Relative frequency of sEVs derived from HeLa cells (grown in LPDS) WT or CD63 KO or CD63 KO rescued with CD63 WT or E217Q in function of the number of D4 associated PAG per vesicle (2-way ANOVA, only significant results are shown, 2 independent experiments for H CD63 KO#1, H CD63 KO#2 + CD63 WT, H CD63 KO#2 + CD63 E217Q, 4 independent experiments for H WT and H CD63 KO#2, ** P = 0.0016, ** P = 0.0055,**** P < 0.0001, * P = 0.0277, *** P = 0.0010, * P = 0.0167). d. Relative frequency of sEVs derived from WT or CD63 KO MNT-1 cells (grown in LPDS) in function of the number of D4 associated PAG per vesicle (data are presented as the mean of 2 independent experiments). e. DLS analysis of sEVs derived from WT or CD63 KO HeLa cells or rescued with CD63 WT or E217Q (grown in LPDS). Average number of particles/ml (n= independent experiments, n = 5 for H WT, n = 6 for H CD63 KO, n = 3 for H CD63 KO + CD63 WT and H CD63 KO + CD63 E217Q, Kruskal-Wallis test, ns P = 0.8010, ns P > 0.9999). f. Quantification of D4 associated PAG on ILVs or MVE limiting membrane in CD63 KO Hela cells or rescued with CD63 WT or E217Q (n = n° of endosomes, CD63 KO n = 43, CD63 WT n = 37, CD63 E217Q n = 59, pooled across 2 independent experiments, Kruskal-Wallis test, ns P > 0.9999, *** P = 0.0003, **** P < 0.0001). g. DLS analysis of sEVs derived from Bafilomycin-A1 treated WT or CD63 KO HeLa (grown in LPDS). Average number of particles/ml (n = 7 independent experiments, two-tailed Mann Whitney test, ns P = 0.7104). Data are presented as mean values +/− SEM. Source numerical data are available in source data.

Source data

Extended Data Fig. 9

a. Workflow used to load sEVs with TF-chol and label them with the membrane dye MemBright-640. b. CD63 KO HeLa cells were labeled with TF-chol, sEVs containing TF-chol were isolated, labeled with MemBright-640, and incubated overnight with WT or CD63 KO HeLa cells treated with U18666A. Cells were observed using a confocal microscope. Bars = 10 µm. Representative of 2 independent experiments. c. WT or CD63 KO Hela cells were labeled with TF-chol, sEVs containing TF-chol were isolated, and incubated overnight with WT Hela cells treated with vehicle or U18666A. Cells were observed using a confocal microscope. Bars = 10 µm. Representative of 2 independent experiments.

Supplementary information

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UnprocessedBlots_Palmullietal

Unprocessed western blots.

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Palmulli, R., Couty, M., Piontek, M.C. et al. CD63 sorts cholesterol into endosomes for storage and distribution via exosomes. Nat Cell Biol 26, 1093–1109 (2024). https://doi.org/10.1038/s41556-024-01432-9

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