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The Rubicon–WIPI axis regulates exosome biogenesis during ageing

Nature Cell Biology volume 26, pages 1558–1570 (2024)Cite this article

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Abstract

Cells release intraluminal vesicles in multivesicular bodies as exosomes to communicate with other cells. Although recent studies suggest an intimate link between exosome biogenesis and autophagy, the detailed mechanism is not fully understood. Here we employed comprehensive RNA interference screening for autophagy-related factors and discovered that Rubicon, a negative regulator of autophagy, is essential for exosome release. Rubicon recruits WIPI2d to endosomes to promote exosome biogenesis. Interactome analysis of WIPI2d identified the ESCRT components that are required for intraluminal vesicle formation. Notably, we found that Rubicon is required for an age-dependent increase of exosome release in mice. In addition, small RNA sequencing of serum exosomes revealed that Rubicon determines the fate of exosomal microRNAs associated with cellular senescence and longevity pathways. Taken together, our current results suggest that the Rubicon–WIPI axis functions as a key regulator of exosome biogenesis and is responsible for age-dependent changes in exosome quantity and quality.

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Fig. 1: RNAi screening reveals that Rubicon promotes exosome secretion.
Fig. 2: WIPI2 interacts with Rubicon and is required for exosome secretion.
Fig. 3: The Rubicon–WIPI axis is required for MVB formation.
Fig. 4: WIPI2 interacts with multiple ESCRT components in a Rubicon-dependent manner.
Fig. 5: Rubicon is necessary for an age-dependent increase in serum exosomes in mice.
Fig. 6: Loss of Rubicon alleviates age-dependent alteration of the exosomal miRNA profile.

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Data availability

The mass spectrometry proteomics data have been deposited in the ProteomeXchange Consortium via the jPOST partner repository with the dataset identifiers PXD043695, PXD043701 and PXD051908. RNA-seq data have been deposited in the National Center for Biotechnology Information Gene Expression Omnibus (https://www.ncbi.nlm.nih.gov/geo/) with the accession number GSE262794. Source data are provided with this paper. All of the other data supporting the findings of this study are available from the corresponding author upon reasonable request.

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Acknowledgements

We thank S. Shimizu (Tokyo Medical and Dental University) for providing the Wipi2 KO MEFs and A. Nakagawa (Osaka University) for materials and technical assistance with the gel filtration experiments. We thank G. Bravin (Osaka University) for assistance with the gel filtration experiments. We also thank the Center for Medical Research and Education and CoMIT Omics Center for technical support and access to experimental equipment. T.Yoshimori is supported by JST CREST (grant number JPMJCR17H6), JSPS KAKENHI (22H04982) and AMED (grant number JP21gm5010001). S.N. is supported by AMED-PRIME (20gm6110003h0004). T.K. is supported by JSPS KAKENHI (20K05839). K.Y. is supported by JSPS KAKENHI (22J12444).

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Authors and Affiliations

  1. Department of Genetics, Graduate School of Medicine, Osaka University, Suita, Japan

    Kyosuke Yanagawa, Akiko Kuma, Maho Hamasaki, Shuhei Nakamura, Tatsuya Kaminishi, Takayuki Shima, Keisuke Tabata, Miki Iwatani, Nao Bekku & Tamotsu Yoshimori

  2. Department of Cardiovascular Medicine, Graduate School of Medicine, Osaka University, Suita, Japan

    Kyosuke Yanagawa & Yasushi Sakata

  3. Health Promotion System Science, Graduate School of Medicine, Osaka University, Suita, Japan

    Akiko Kuma & Tamotsu Yoshimori

  4. Laboratory of Intracellular Membrane Dynamics, Graduate School of Frontier Biosciences, Osaka University, Suita, Japan

    Maho Hamasaki, Shuhei Nakamura, Keisuke Tabata & Tamotsu Yoshimori

  5. Department of Metabolic Medicine, Graduate School of Medicine, Osaka University, Suita, Japan

    Shunbun Kita & Iichiro Shimomura

  6. Tokyo New Drug Research Laboratories, Pharmaceutical Business Unit, Kowa Company, Higashimurayama, Japan

    Shunbun Kita

  7. Division of Endocrinology, Diabetes and Metabolism, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, USA

    Tadashi Yamamuro & Satoshi Oikawa

  8. Division of Cell Signaling, Fujii Memorial Institute of Medical Sciences, Institute of Advanced Medical Sciences, Tokushima University, Tokushima, Japan

    Kohei Nishino & Hidetaka Kosako

  9. Institute for Advanced Co-Creation Studies, Osaka University, Suita, Japan

    Shuhei Nakamura

  10. Department of Biochemistry, Nara Medical University, Kashihara, Japan

    Shuhei Nakamura & Takayuki Shima

  11. Research Institute for Microbial Diseases, Osaka University, Suita, Japan

    Hiroko Omori

  12. Integrated Frontier Research for Medical Science Division, Institute for Open and Transdisciplinary Research Initiatives, Osaka University, Suita, Japan

    Tatsuya Kaminishi & Tamotsu Yoshimori

  13. Waseda Institute for Sport Sciences, Waseda University, Tokorozawa, Japan

    Satoshi Oikawa

  14. Biomedical Research Institute, National Institute of Advanced Industrial Science and Technology, Tsukuba, Japan

    Yoshio Kato

  15. Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan

    Ryuya Edahiro & Yukinori Okada

  16. Department of Respiratory Medicine and Clinical Immunology, Osaka University Graduate School of Medicine, Suita, Japan

    Ryuya Edahiro

  17. i2i-Labo, Yokohama Research Center, Central Pharmaceutical Research Institute, Japan Tobacco Inc., Yokohama, Japan

    Ryosuke Kawagoe & Takako Taniguchi

  18. Division of Cellular Senescence, The Cancer Institute, Japanese Foundation for Cancer Research, Tokyo, Japan

    Yoko Tanaka & Akiko Takahashi

  19. Department of Immunology, Graduate School of Medical Sciences, Kanazawa University, Kanazawa, Japan

    Rikinari Hanayama

  20. WPI Nano Life Science Institute, Kanazawa University, Kanazawa, Japan

    Rikinari Hanayama

  21. Department of Genome Informatics, Graduate School of Medicine, University of Tokyo, Tokyo, Japan

    Yukinori Okada

  22. Laboratory for Systems Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan

    Yukinori Okada

  23. Laboratory of Statistical Immunology, WPI Immunology Frontier Research Center, Osaka University, Suita, Japan

    Yukinori Okada

  24. WPI Premium Research Institute for Human Metaverse Medicine, Osaka University, Suita, Japan

    Yukinori Okada

  25. Laboratory of Muscle Biology, Faculty of Sport Sciences, Waseda University, Tokorozawa, Japan

    Takayuki Akimoto

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Contributions

K.Y., A.K. and T. Yoshimori planned the study and designed the experiments. M.H., K.T., R.K. and T.T. conducted the interactome experiments using HeLa Kyoto cells. S.K., I.S. and R.H. supervised the exosome-related experiments. T. Yamamuro conducted the mouse experiments. K.N. and H.K. conducted the interactome experiments using MEFs. S.N. assisted with the experiments related to ATG KO cells. H.O. performed the immunoelectron microscopy. T.K. conducted the gel filtration experiments. S.O., Y.K. and T.A. generated the plasmids for the miRNA experiments and assisted with them. R.E. and Y.O. assisted with the RNA-seq. T.S., M.I. and N.B. assisted with the experiments involving cultured cells. Y.T. and A.T. assisted with the experiments related to ageing. S.N. and Y.S. provided general assistance with the manuscript. K.Y., T. Yamamuro, S.K. and T. Yoshimori wrote the manuscript.

Corresponding author

Correspondence to Tamotsu Yoshimori.

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Competing interests

T. Yoshimori is the founder of AutoPhagyGO. The remaining authors declare no competing interests.

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Nature Cell Biology thanks Harald Stenmark and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Peer reviewer reports are available.

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Extended data

Extended Data Fig. 1 Rubicon promotes exosome biogenesis independently of autophagic pathways.

(a) A schematic diagram of exosome isolation from culture medium of hMSCs transfected with siRNAs. (b) Quantification of exosomal Flot-1 levels in cells with knockdown of the genes indicated in Fig. 1a. Bars represent means ± SEM. n = 4 biologically independent experiments. *p = 0.0304 (control vs ULK1), 0.0157 (control vs ATG5) and 0.0113 (control vs ATG13), **p = 0.0073 (control vs RUBCN) by one-way ANOVA followed by Dunnet’s test. (c) Immunoblotting of the indicated proteins in the exosome fractions and WCLs obtained from control and Atg5-KO MEFs. The loading amount for each sample was set as follows: half of the exosome sample collected from 1 ml of culture medium, and 6 µg for the WCL. (d) Quantification of exosomal levels of CD63 and Flot-1 in (d). Bars represent means ± SEM. n = 3 biologically independent experiments. ***p = 0.0007, ****p < 0.0001 by a two-tailed Student’s t-test. (e) Immunoblotting of the indicated proteins in the exosome fractions and WCLs obtained from control and Fip200-KO MEFs. The loading amount for each sample was set as follows: half of the exosome sample collected from 1 ml of culture medium, and 6 µg for the WCL. (f) Quantification of exosomal levels of CD63 and Flot-1 in (f). Bars represent means ± SEM. n = 3 biologically independent experiments. ns, not significant by a two-tailed Student’s t-test. (g) Immunoblotting of the indicated proteins in the exosome fractions and WCLs obtained from control and Atg2-KO MEFs. The loading amount for each sample was set as follows: half of the exosome sample collected from 1 ml of culture medium, and 6 µg for the WCL. (h) Quantification of exosomal levels of CD63 and Flot-1 in (h). Bars represent means ± SEM. n = 3 biologically independent experiments. ns, not significant by a two-tailed Student’s t-test. (i) Immunoblotting of the indicated proteins in the exosome fractions and WCLs obtained from control and Atg14-KO MEFs. The loading amount for each sample was set as follows: half of the exosome sample collected from 1 ml of culture medium, and 6 µg for the WCL. (j) Quantification of exosomal levels of CD63, ALIX and Flot-1 in (i). Bars represent means ± SEM. n = 3 biologically independent experiments. ns, not significant by a two-tailed Student’s t-test. (k) Immunoblotting of the indicated proteins in the exosome fractions and WCLs obtained from WT or Atg16l1-KO MEFs expressing an empty plasmid ( + empty) or ATG16L1 plasmid ( + FL). The loading amount for each sample was set as follows: half of the exosome sample collected from 1 ml of culture medium, and 6 µg for the WCL. (l) Quantification of exosomal levels of CD63 in (k). Bars represent means ± SEM. n = 3 biologically independent experiments. ns, not significant; **p = 0.004 by one-way ANOVA followed by Dunnet’s test. (m) Immunoblotting of the indicated proteins in the exosome fractions and WCLs obtained from WT MEFs and Rubicon-KO MEFs expressing an empty plasmid ( + empty) or a GFP-Rubicon plasmid ( + GFP-Rubicon). The loading amount for each sample was set as follows: half of the exosome sample collected from 1 ml of culture medium, and 6 µg for the WCL. (n) Immunoblotting of the indicated proteins in the WCLs obtained from control and Rubicon-OE MEFs. The loading amount for each sample was set as 10 µg. Source unprocessed blots for (c, e, g, i, k, m, n) and source numerical data for (b, d, f, h, j, l) are available in Source Data. The biologically independent experiments were repeated twice with similar results in (m, n).

Source data

Extended Data Fig. 2 Rubicon regulates exosome biogenesis without affecting cell viability.

(a) Left, immunoblotting of the indicated proteins in the exosome fractions and WCLs obtained from control and RUBCN-knockdown hMSCs. Right, representative image of Trypan Blue staining, live cells are marked in green and dead cells in red, in indicated cells. Scale bar, 200 μm. The loading amount for each sample was set as follows: half of the exosome sample collected from 1 ml of culture medium, and 6 µg for the WCL. (b) Left, quantification of the ratio of live cells to total cells in (o). Right, quantification of exosomal levels of CD63 and ALIX normalized by the number of live cells in (o). Bars represent means ± SEM. n = 3 biologically independent experiments. ns, not significant; *p = 0.015, **p = 0.0015 by a two-tailed Student’s t-test. (c) Relative numbers of total cells in control and RUBCN knockdown hMSCs. Bars represent means ± SEM. n = 3 biologically independent experiments. ns, not significant by a two-tailed Student’s t-test. (d) Left, ponceau S staining in the exosome fractions obtained from control and Rubicon-overexpressing MEFs. Right, representative image of Trypan Blue staining, live cells are marked in green and dead cells in red, in indicated cells. Scale bar, 200 μm. The loading amount for each sample was set as follows: half of the exosome sample collected from 1 ml of culture medium. n = 4 biologically independent experiments. (e) Left, quantification of the ratio of live cells to total cells in (r). Right, quantification of exosomal levels of ponceau S staining normalized by the number of live cells in (r). Bars represent means ± SEM. n = 4 biologically independent experiments. ns, not significant; **p = 0.0081 by a two-tailed Student’s t-test. Source unprocessed blots for (a, d) and source numerical data for (b, c, e) are available in Source Data.

Source data

Extended Data Fig. 3 Apilimod treatment promotes exosome biogenesis in a Rubicon-dependent manner.

(a) Immunofluorescent images of CD63 (magenta) and DAPI (blue) in WT, Fip200-KO, and Beclin-1-KO MEFs expressing GFP-Rubicon. Scale bars, 50 μm. (b) Quantification of the ratio of CD63- and Rubicon-positive dots relative to Rubicon-positive dots in indicated cells. Bars represent means ± SEM. n = 3 biologically independent experiments. ns, not significant by one-way ANOVA followed by Dunnet’s test. (c) A schematic diagram of pharmacological inhibition of PIKFyve by Apilimod. (d) Immunofluorescent images of CD63 (magenta) and DAPI (blue) in WT, Fip200-KO, and Beclin-1-KO MEFs expressing GFP-Rubicon with 0.5 μM Apilimod treatment for 1 hour. Scale bars, 50 μm. (e) Immunofluorescent images of CD63 (cyan) and DAPI (blue) in MEFs expressing GFP-Rubicon and mCherry-2×FYVE with Apilimod treatment. Scale bars, 50 μm (standard image), 10 μm (magnified image). (f) Immunofluorescent images of LAMP1 (magenta) and DAPI (blue) in MEFs expressing GFP-CD63 with Apilimod treatment. Scale bar, 50 μm. (g) Immunoblotting of the indicated proteins in the exosome fractions and WCLs obtained from WT and Rubicon-KO MEFs with or without Apilimod treatment. The loading amount for each sample was set as follows: half of the exosome sample collected from 1 ml of culture medium, and 6 µg for the WCL. (h) Quantification of exosomal CD63 levels in (g). Bars represent means ± SEM. n = 4 biologically independent experiments. ns, not significant; ****p < 0.0001 by two-way ANOVA. Source unprocessed blots for (g) and source numerical data for (b,h) are available in Source Data. The biologically independent experiments were repeated twice with similar results in (d-f).

Source data

Extended Data Fig. 4 Both canonical and non-canonical autophagic pathways are dispensable for exosome secretion.

(a) Immunoblotting of the indicated proteins in the exosome fractions and WCLs obtained from control, Rubicon-KO, and Beclin-1-KO MEFs. The loading amount for each sample was set as follows: half of the exosome sample collected from 1 ml of culture medium, and 6 µg for the WCL. (b) Immunoblotting of the indicated proteins in the exosome fractions and WCLs obtained from control and Uvrag-KO MEFs. The loading amount for each sample was set as follows: half of the exosome sample collected from 1 ml of culture medium, and 10 µg for the WCL. (c) Quantification of exosomal levels of CD63, Flot-1, and ALIX in (b). Bars represent means ± SEM. n = 3 biologically independent experiments. ns, not significant by a two-tailed Student’s t-test. (d) Immunoblotting of the indicated proteins in gel filtration fractions obtained from MSCs. (e) Immunoblotting of the indicated proteins in the exosome fractions and WCLs obtained from Atg16l1-KO MEFs expressing an ATG16L1 plasmid ( + FL), an empty plasmid ( + empty), or a WD-repeat domain–deleted ATG16L1 plasmid (+ΔWDR). The loading amount for each sample was set as follows: half of the exosome sample collected from 1 ml of culture medium, and 6 µg for the WCL. (f) Quantification of exosomal levels of CD63 and ALIX in (d). Bars represent means ± SEM. n = 3 biologically independent experiments. *p = 0.0166, **p = 0.0037 (CD63) and 0.0093 (ALIX), ***p = 0.0001 by one-way ANOVA followed by Dunnett’s test. Source unprocessed blots for (a, b, d, e) and source numerical data for (c, f) are available in Source Data. The biologically independent experiments were repeated twice with similar results in (a, d).

Source data

Extended Data Fig. 5 RNAi screening of exosome regulators identifies multiple candidates from Rubicon-interacting proteins.

(a) Immunoblotting of CD63 in the exosome fractions isolated from culture medium of hMSCs with knockdown of the indicated genes. The loading amount for each sample was set as follows: half of the exosome sample collected from 1 ml of culture medium. (b) A schematic diagram showing identification of WIPI2 by the interactome analysis and RNAi screen of exosome secretions. (c) The number of unique peptides and total peptides that are potential regulators of exosomes in (b), as detected in Rubicon-interactome analysis using HeLa Kyoto cells. (d) Immunoblotting of CD63 and ALIX in the exosome fractions isolated from the culture medium of hMSCs with knockdown of the indicated genes. The loading amount for each sample was set as follows: half of the exosome sample collected from 1 ml of culture medium. (e) Quantification of exosomal levels of CD63 and ALIX in (d). Bars represent means ± SEM. n = 3 biologically independent experiments. *p = 0.037 (CD63) and 0.0232 (ALIX), ****p < 0.0001 by one-way ANOVA followed by Dunnett’s test. (f) Immunoblotting of indicated proteins in hMSCs with knockdown of the indicated genes. The loading amount for each sample was set as 10 µg. Source unprocessed blots for (a, d, f) and source numerical data for (e, f) are available in Source Data. The biologically independent experiments were repeated twice with similar results in (f).

Source data

Extended Data Fig. 6 Rubicon recruits WIPI proteins to endosomes, which is necessary for exosome biogenesis.

(a) Immunoblotting of the indicated proteins in the exosome fractions and WCLs obtained from hMSCs with knockdown of the indicated genes. The loading amount for each sample was set as follows: half of the exosome sample collected from 1 ml of culture medium, and 6 µg for the WCL. (b) Quantification of exosomal levels of CD63 in (a). Bars represent means ± SEM. n = 4 biologically independent experiments. ns, not significant; *p = 0.0183 (control vs siWIPI2 #2) and 0.0160 (control vs siWIPI3) by one-way ANOVA followed by Dunnett’s test. (c) NTA of EVs purified from the cultured medium of hMSCs with knockdown of indicated genes using ultracentrifugation. n = 5 biologically independent experiments. (d) Quantification of the total particle concentration of the EVs in (c). Bars represent means. n = 5 biologically independent experiments. ns, not significant; ****p < 0.0001 by one-way ANOVA followed by Dunnett’s test. (e) Immunoprecipitation assay. HEK293T cells were transfected with the indicated plasmids for 24 hours, and then the cells were lysed and immunoprecipitated with anti-HA antibody. Precipitates were subjected to immunoblotting with the indicated antibodies. (f) Immunofluorescent images of WIPI2 (magenta) and DAPI (blue) in WT MEFs or Fip200-KO MEFs expressing GFP-Rubicon with Apilimod treatment. Scale bars, 50 μm (standard image), 10 μm (magnified image). (g) Immunofluorescence images of WIPI1 or WIPI3 (magenta) and DAPI (blue) in MEFs expressing GFP-Rubicon with Apilimod treatment. Scale bars, 50 μm (standard image), 10 μm (magnified image). (h) Immunoblotting of indicated proteins in the WCLs obtained from WT and Rubicon-KO MEFs expressing an empty plasmid (control) or an mStrawberry-WIPI2d plasmid (WIPI2 OE). The loading amount for each sample was set as 6 µg. Source unprocessed blots for (a, e, h) and source numerical data for (b-e) are available in Source Data. The biologically independent experiments were repeated twice with similar results in (e-h).

Source data

Extended Data Fig. 7 The helix-coil-rich region in Rubicon is necessary for its interaction with WIPI2.

(a) Schematic representation of Rubicon and its truncated mutants. Rubicon FL, 3×FLAG-Rubicon (1–972); ΔC, 3×FLAG-Rubicon (1–508); ΔN, Rubicon (509–972); ΔSR-N, 3×FLAG-Rubicon (1–203, 448–972); ΔCCD, 3×FLAG-Rubicon (1–504, 558–972); ΔSR-C, 3×FLAG-Rubicon (1–566, 626–972); ΔHCR, 3×FLAG-Rubicon (1-625, 761–972); ΔRHD, 3×FLAG-Rubicon (1–698). (b) Immunoprecipitation assay. HEK293T cells were transfected with HA-WIPI2d and 3×FLAG (FLAG) or the Rubicon mutant plasmids for 24 hours, and then the cells were lysed and immunoprecipitated with anti-FLAG antibody. Precipitates were subjected to immunoblotting with the indicated antibodies. (c) Immunoprecipitation assay. HEK293T cells were transfected with the indicated plasmids for 24 hours, and then the cells were lysed and immunoprecipitated with anti-FLAG antibody. Precipitates were subjected to immunoblotting with the indicated antibodies. (d) Immunoblotting of the indicated proteins in the exosome fractions and WCLs obtained from WT and Rubicon-KO MEFs expressing the indicated plasmids. The loading amount for each sample was set as follows: half of the exosome sample collected from 1 ml of culture medium, and 6 µg for the WCL. n = 3 biologically independent experiments. (e) Quantification of exosomal levels of CD63 and ALIX in (d). Bars represent means. n = 3 biologically independent experiments. ns, not significant; **p = 0.0011 (WT vs RubiconΔC in CD63), 0.0014 (WT vs empty in ALIX) and 0.0014 (WT vs RubiconΔC in ALIX), ***p = 0.0006 by one-way ANOVA followed by Dunnett’s test. (f) Immunoprecipitation assay. HEK293T cells were transfected with HA-WIPI2d and the Rubicon mutant plasmids (* represents missing transfection) for 24 hours, and then the cells were lysed and immunoprecipitated with anti-HA antibody. Precipitates were subjected to immunoblotting with the indicated antibodies. (g) Immunoprecipitation assay. HEK293T cells were transfected with the indicated plasmids for 24 hours with or without Apilimod treatment, and then the cells were lysed and immunoprecipitated with anti-FLAG antibody. Precipitates were subjected to immunoblotting with the indicated antibodies. (h) Immunoblotting of the indicated proteins in the exosome fractions and WCLs obtained from hMSCs treated with or without bafilomycin A1 for 3 hours and with knockdown of the indicated genes. The loading amount for each sample was set as follows: half of the exosome sample collected from 1 ml of culture medium, and 6 µg for the WCL. (i) Quantification of exosomal levels of CD63 in (h). Bars represent means ± SEM. n = 4 biologically independent experiments. ns, not significant; **p = 0.0086 (WIPI2 vs WIPI2 BafA1), 0.0068 (WIPI3 vs WIPI3 BafA1), 0.0096 (WIPI2 BafA1 vs WIPI2 + WIPI3 BafA1), 0.0013 (WIPI3 BafA1 vs WIPI2 + WIPI3 BafA1), ****p < 0.0001 by one-way ANOVA followed by Tukey’s test. Source unprocessed blots for (b, c, d, f, g, h) and source numerical data for (c, e, g, i) are available in Source Data. The biologically independent experiments were repeated twice with similar results in (b, c, f, g).

Source data

Extended Data Fig. 8 The Rubicon-WIPI axis is required for MVB formation.

(a) Representative electron microscopic images of multivesicular bodies (MVBs) in control and Rubicon-KO MEFs. Scale bar, 1 μm. (b) Violin plots showing the number of MVBs per cell in (a). WT, n = 11 cells, Rubicon KO, n = 35 cells, pooled across 2 biologically independent experiments. The solid line denotes the median, and dotted lines define the quartiles. (c) Immunoblotting of GFP-CD63 in the WCLs obtained from control or Rubicon-KO MEFs stably expressing GFP-CD63. The loading amount for each sample was set as 6 µg. (d) Illustration of the ESCRT machinery and MVB formation process. Red letters represent ESCRT components and associated proteins that demonstrate interaction with WIPI2d in Fig. 4a. (e) Immunoblotting of the indicated proteins in the exosome fractions and WCLs obtained from hMSCs with knockdown of the indicated genes. The loading amount for each sample was set as follows: half of the exosome sample collected from 1 ml of culture medium, and 6 µg for the WCL. (f) NTA of EVs purified from the cultured medium of hMSCs with knockdown of indicated genes using ultracentrifugation. The biologically independent experiments were repeated twice with similar results in (f). (g) Violin plot showing the total number of CD63 dots in the indicated cells in Fig. 4c. n = 21 cells, from 1 independent experiment. The solid line denotes the median, and the dotted lines define the quartiles. ns, not significant by a two-tailed Student’s t-test. (h) Immunoprecipitation assay. HEK293T cells were knocked down with the indicated genes and transfected with the indicated plasmids, and then the cells were lysed and immunoprecipitated with anti-FLAG antibody. Precipitates were subjected to immunoblotting with the indicated antibodies. (i) Immunoprecipitation assay. HEK293T cells were transfected with the indicated plasmids, and then the cells were lysed and immunoprecipitated with anti-FLAG antibody. Precipitates were subjected to immunoblotting with the indicated antibodies. Source unprocessed blots for (c, e, h, i) and source numerical data for (b, f, g, h) are available in Source Data. The biologically independent experiments were repeated twice with similar results in (c, e, h, i).

Source data

Extended Data Fig. 9 Rubicon knockout suppresses the age-related increase in exosome secretion in vivo.

(a) Body weight chart for male mice of the indicated genotypes on a normal chow diet. WT, n = 21; Rubicon-KO, n = 21. Bars represent means ± SEM. (b) Quantification of body weight of 18-month-old male mice of the indicated genotypes. WT, n = 5; Rubicon-KO, n = 4. Bars represent means ± SEM. ns, not significant; by a two-tailed Student’s t-test. (c) A schematic diagram of serum exosome isolation. (d) Serum albumin levels obtained from WT or Rubicon-KO male mice. n = 3 independent mice. Bars represent means ± SEM. ns, not significant; by a two-tailed Student’s t-test. (e) NTA of large EVs purified from serum obtained from 4- or 18-month-old male mice using a PS-affinity kit. (f) NTA of EVs purified from primary AD-MSCs obtained from 4-month-old WT or Rubicon-KO male mice using ultracentrifugation. (g) Immunoblotting of the indicated proteins in the WCLs of primary AD-MSCs obtained from 4- or 18-month-old male mice of the indicated genotypes. 4-month-old WT, n = 3; 4-month-old Rubicon-KO, n = 4; 18-month-old WT, n = 5; 18-month-old Rubicon KO, n = 4. The loading amount for each sample was set as 6 µg. (h) Quantification of Rubicon levels normalized by α-tubulin in (c). Bars represent means ± SEM. 4-months-old, n = 3; 18-months-old, n = 5; **p = 0.0075 by a two-tailed Student’s t-test. (i) Serum albumin levels obtained from indicated mice. 4-month-old WT, n = 3; 4-month-old Rubicon-KO, n = 4; 18-month-old WT, n = 5; 18-month-old Rubicon-KO, n = 4. Bars represent means ± SEM. ns, not significant; by one-way ANOVA followed by Tukey’s test. (j) Immunoblotting of the indicated proteins in the exosome fractions obtained from RPE-1 cells with the indicated DXR treatment. The loading amount for each sample was set as follows: half of the exosome sample collected from 1 ml of culture medium. Source unprocessed blots for (g, j) and source numerical data for (a, b, d, e, f, h, i) are available in Source Data. The biologically independent experiments were repeated twice with similar results in (j).

Source data

Extended Data Fig. 10 Rubicon is essential for the age-dependent alteration of the exosomal microRNA profile that promote cellular senescence.

(a) Gene ontology enrichment analysis of the target genes of the 10 miRNAs enriched in the serum EVs in Fig. 6b. X-axis, −log10 q-value of duplicate (n = 3) experiments. (b) Fold change of indicated miRNAs levels in indicated cells. Bars represent means ± SEM. n = 3 biologically independent experiments. *p = 0.0195, **p = 0.0031 by a two-tailed Student’s t-test. (c) A schematic diagram of treatment with CM of senescent donor cells to recipient cells. (d-e) Immunoprecipitation assay. HEK293T cells were transfected with the indicated plasmids, and then the cells were lysed and immunoprecipitated with anti-FLAG antibody. Precipitates were subjected to immunoblotting with the indicated antibodies. (f) Venn diagram showing the numbers of Differentially Expressed Genes (DEGs) in serum EVs from 4-month-old (young) WT relative to young Rubicon-KO (blue) and 18-month-old (aged) WT relative to aged Rubicon-KO (yellow) mice. (g) Immunoprecipitation assay. HEK293T cells were transfected with the indicated plasmids, and then the cells were lysed and immunoprecipitated with anti-HA antibody. Precipitates were subjected to immunoblotting with the indicated antibodies. Source unprocessed blots for (d, e, g) and source numerical data for (a, b) are available in Source Data. The biologically independent experiments were repeated twice with similar results in (d, e, g).

Source data

Supplementary information

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Supplementary Table 1

Interactome analysis of Rubicon using HeLa Kyoto cells.

Supplementary Table 2

Interactome analysis of Rubicon using MEFs receiving apilimod treatment.

Supplementary Table 3

Interactome analysis of WIPI2d.

Supplementary Table 4

siRNAs used in this study.

Source data

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Yanagawa, K., Kuma, A., Hamasaki, M. et al. The Rubicon–WIPI axis regulates exosome biogenesis during ageing. Nat Cell Biol 26, 1558–1570 (2024). https://doi.org/10.1038/s41556-024-01481-0

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