Date

October 11, 2025

Source

Nature

Categories

The secreted metabolite sensor CtBP2 links metabolism to healthy lifespan

Data availability

The data showing the relationships between serum CtBP2 and health conditions are available under controlled access due to privacy and ethical considerations. Requests for access to data subject to privacy and ethical considerations should be made to the corresponding author, M.S. ([email protected]), and will be considered on a case-by-case basis, subject to reasonable restrictions and timelines. All other datasets not subject to data sharing restrictions are freely available upon reasonable request from the corresponding author. Our RNA-seq dataset has been deposited in the NCBI Gene Expression Omnibus under accession no. GSE282176. Our proteomics dataset has been deposited in the ProteomeXchange Consortium via the PRIDE60 partner repository with the dataset identifier PXD066696. The metabolomics dataset has been deposited in the Metabolomics Workbench under study ID ST004082 and is accessible at https://doi.org/10.21228/M8BV8N. Source data are provided with this paper.

References

  1. Rutledge, J., Oh, H. & Wyss-Coray, T. Measuring biological age using omics data. Nat. Rev. Genet. 23, 715–727 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  2. Hagberg, C. E. & Spalding, K. L. White adipocyte dysfunction and obesity-associated pathologies in humans. Nat. Rev. Mol. Cell Biol. 25, 270–289 (2024).

    Article  CAS  PubMed  Google Scholar 

  3. Hardie, D. G., Ross, F. A. & Hawley, S. A. AMPK: a nutrient and energy sensor that maintains energy homeostasis. Nat. Rev. Mol. Cell Biol. 13, 251–262 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Amorim, J. A. et al. Mitochondrial and metabolic dysfunction in ageing and age-related diseases. Nat. Rev. Endocrinol. 18, 243–258 (2022).

    Article  PubMed  PubMed Central  Google Scholar 

  5. Calubag, M. F., Robbins, P. D. & Lamming, D. W. A nutrigeroscience approach: dietary macronutrients and cellular senescence. Cell Metab. 36, 1914–1944 (2024).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Cheng, L. & Hill, A. F. Therapeutically harnessing extracellular vesicles. Nat. Rev. Drug Discov. 21, 379–399 (2022).

    Article  CAS  PubMed  Google Scholar 

  7. Moreno-Gonzalo, O., Villarroya-Beltri, C. & Sánchez-Madrid, F. Post-translational modifications of exosomal proteins. Front. Immunol. 5, 383 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  8. Moreno-Gonzalo, O., Fernandez-Delgado, I. & Sanchez-Madrid, F. Post-translational add-ons mark the path in exosomal protein sorting. Cell. Mol. Life Sci. 75, 1–19 (2018).

    Article  CAS  PubMed  Google Scholar 

  9. Sekiya, M. et al. C-terminal binding protein 2 emerges as a critical player linking metabolic imbalance to the pathogenesis of obesity. J. Atheroscler. Thromb. 31, 109–116 (2024).

    Article  CAS  PubMed  Google Scholar 

  10. Chinnadurai, G. Transcriptional regulation by C-terminal binding proteins. Int. J. Biochem. Cell Biol. 39, 1593–1607 (2007).

    Article  CAS  PubMed  Google Scholar 

  11. Zhang, Q., Piston, D. W. & Goodman, R. H. Regulation of corepressor function by nuclear NADH. Science 295, 1895–1897 (2002).

    Article  CAS  PubMed  Google Scholar 

  12. Madison, D. L., Wirz, J. A., Siess, D. & Lundblad, J. R. Nicotinamide adenine dinucleotide-induced multimerization of the co-repressor CtBP1 relies on a switching tryptophan. J. Biol. Chem. 288, 27836–27848 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Bellesis, A. G., Jecrois, A. M., Hayes, J. A., Schiffer, C. A. & Royer, W. E. Jr. Assembly of human C-terminal binding protein (CtBP) into tetramers. J. Biol. Chem. 293, 9101–9112 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Sekiya, M. et al. The transcriptional corepressor CtBP2 serves as a metabolite sensor orchestrating hepatic glucose and lipid homeostasis. Nat. Commun. 12, 6315 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Saito, K. et al. Obesity-induced metabolic imbalance allosterically modulates CtBP2 to inhibit PPAR-α transcriptional activity. J. Biol. Chem. 299, 104890 (2023).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Sekiya, M. et al. Loss of CtBP2 may be a mechanistic link between metabolic derangements and progressive impairment of pancreatic β cell function. Cell Rep. 42, 112914 (2023).

    Article  CAS  PubMed  Google Scholar 

  17. Hildebrand, J. D. & Soriano, P. Overlapping and unique roles for C-terminal binding protein 1 (CtBP1) and CtBP2 during mouse development. Mol. Cell. Biol. 22, 5296–5307 (2002).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Kanehisa, M., Goto, S., Kawashima, S. & Nakaya, A. The KEGG databases at GenomeNet. Nucleic Acids Res. 30, 42–46 (2002).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Théry, C., Zitvogel, L. & Amigorena, S. Exosomes: composition, biogenesis and function. Nat. Rev. Immunol. 2, 569–579 (2002).

    Article  PubMed  Google Scholar 

  20. Williamson, D. H., Lund, P. & Krebs, H. A. The redox state of free nicotinamide-adenine dinucleotide in the cytoplasm and mitochondria of rat liver. Biochem. J. 103, 514–527 (1967).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Vitvitsky, V. et al. The mitochondrial NADH pool is involved in hydrogen sulfide signaling and stimulation of aerobic glycolysis. J. Biol. Chem. 296, 100736 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Villarroya-Beltri, C., Baixauli, F., Gutiérrez-Vázquez, C., Sánchez-Madrid, F. & Mittelbrunn, M. Sorting it out: regulation of exosome loading. Semin. Cancer Biol. 28, 3–13 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Mathieu, M., Martin-Jaular, L., Lavieu, G. & Théry, C. Specificities of secretion and uptake of exosomes and other extracellular vesicles for cell-to-cell communication. Nat. Cell Biol. 21, 9–17 (2019).

    Article  CAS  PubMed  Google Scholar 

  24. Mathieu, M. et al. Specificities of exosome versus small ectosome secretion revealed by live intracellular tracking of CD63 and CD9. Nat. Commun. 12, 4389 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Mathivanan, S. & Simpson, R. J. ExoCarta: a compendium of exosomal proteins and RNA. Proteomics 9, 4997–5000 (2009).

    Article  CAS  PubMed  Google Scholar 

  26. Rotin, D. & Kumar, S. Physiological functions of the HECT family of ubiquitin ligases. Nat. Rev. Mol. Cell Biol. 10, 398–409 (2009).

    Article  CAS  PubMed  Google Scholar 

  27. Metzger, M. B., Pruneda, J. N., Klevit, R. E. & Weissman, A. M. RING-type E3 ligases: master manipulators of E2 ubiquitin-conjugating enzymes and ubiquitination. Biochim. Biophys. Acta 1843, 47–60 (2014).

    Article  CAS  PubMed  Google Scholar 

  28. Kolluru, G. K., Shackelford, R. E., Shen, X., Dominic, P. & Kevil, C. G. Sulfide regulation of cardiovascular function in health and disease. Nat. Rev. Cardiol. 20, 109–125 (2023).

    Article  CAS  PubMed  Google Scholar 

  29. Hine, C. et al. Endogenous hydrogen sulfide production is essential for dietary restriction benefits. Cell 160, 132–144 (2015).

    Article  CAS  PubMed  Google Scholar 

  30. Timmers, S., Auwerx, J. & Schrauwen, P. The journey of resveratrol from yeast to human. Aging 4, 146–158 (2012).

    Article  PubMed  PubMed Central  Google Scholar 

  31. Moon, D. O. A comprehensive review of the effects of resveratrol on glucose metabolism: unveiling the molecular pathways and therapeutic potential in diabetes management. Mol. Biol. Rep. 50, 8743–8755 (2023).

    Article  CAS  PubMed  Google Scholar 

  32. Jang, M. et al. Cancer chemopreventive activity of resveratrol, a natural product derived from grapes. Science 275, 218–220 (1997).

    Article  CAS  PubMed  Google Scholar 

  33. Foretz, M., Guigas, B. & Viollet, B. Metformin: update on mechanisms of action and repurposing potential. Nat. Rev. Endocrinol. 19, 460–476 (2023).

    Article  CAS  PubMed  Google Scholar 

  34. O’Brien, K., Ughetto, S., Mahjoum, S., Nair, A. V. & Breakefield, X. O. Uptake, functionality, and re-release of extracellular vesicle-encapsulated cargo. Cell Rep. 39, 110651 (2022).

    Article  PubMed  PubMed Central  Google Scholar 

  35. Sari, L. N. et al. Label-free imaging of cellular organization in living mammalian cells via external apodization phase-contrast microscopy. Preprint at bioRxiv https://doi.org/10.1101/2024.03.01.582671 (2024).

  36. Akter, F. et al. Multi-cell line analysis of lysosomal proteomes reveals unique features and novel lysosomal proteins. Mol. Cell. Proteomics 22, 100509 (2023).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Hall, R., Yuan, S., Wood, K., Katona, M. & Straub, A. C. Cytochrome b5 reductases: redox regulators of cell homeostasis. J. Biol. Chem. 298, 102654 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Pang, Z. et al. MetaboAnalyst 6.0: towards a unified platform for metabolomics data processing, analysis and interpretation. Nucleic Acids Res. 52, W398–W406 (2024).

    Article  PubMed  PubMed Central  Google Scholar 

  39. Huo, A. & Xiong, X. PAICS as a potential target for cancer therapy linking purine biosynthesis to cancer progression. Life Sci. 331, 122070 (2023).

    Article  CAS  PubMed  Google Scholar 

  40. Martin-Montalvo, A. et al. Cytochrome b5 reductase and the control of lipid metabolism and healthspan. npj Aging Mech. Dis. 2, 16006 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  41. Ribeiro, R. et al. In vivo cyclic induction of the FOXM1 transcription factor delays natural and progeroid aging phenotypes and extends healthspan. Nat. Aging 2, 397–411 (2022).

    Article  CAS  PubMed  Google Scholar 

  42. Burkewitz, K., Zhang, Y. & Mair, W. B. AMPK at the nexus of energetics and aging. Cell Metab. 20, 10–25 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. Goodman, R. P. et al. Hepatic NADH reductive stress underlies common variation in metabolic traits. Nature 583, 122–126 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Wang, Y. & Hekimi, S. Understanding ubiquinone. Trends Cell Biol. 26, 367–378 (2016).

    Article  CAS  PubMed  Google Scholar 

  45. Linster, C. L. & Van Schaftingen, E. Vitamin C. Biosynthesis, recycling and degradation in mammals. FEBS J. 274, 1–22 (2007).

    Article  CAS  PubMed  Google Scholar 

  46. Kainoh, K. et al. CtBP2 confers protection against oxidative stress through interactions with NRF1 and NRF2. Biochem. Biophys. Res. Commun. 562, 146–153 (2021).

    Article  CAS  PubMed  Google Scholar 

  47. Wang, M., Tang, W. & Zhu, Y. Z. An update on AMPK in hydrogen sulfide pharmacology. Front. Pharmacol. 8, 810 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  48. Di Francesco, A. et al. Dietary restriction impacts health and lifespan of genetically diverse mice. Nature 634, 684–692 (2024).

    Article  PubMed  PubMed Central  Google Scholar 

  49. Gong, T. et al. TMSB4Y restrains sphingomyelin synthesis via de novo purine synthesis to exert a tumor suppressor function in male esophageal squamous cell carcinoma. Oncogene 43, 3660–3672 (2024).

    Article  CAS  PubMed  Google Scholar 

  50. Liang, C. et al. Formation of I2+III2 supercomplex rescues respiratory chain defects. Cell Metab. 37, 441–459 (2025).

    Article  CAS  PubMed  Google Scholar 

  51. López-Otín, C., Blasco, M. A., Partridge, L., Serrano, M. & Kroemer, G. Hallmarks of aging: an expanding universe. Cell 186, 243–278 (2023).

    Article  PubMed  Google Scholar 

  52. Niwa, H. et al. An efficient gene-trap method using poly A trap vectors and characterization of gene-trap events. J. Biochem. 113, 343–349 (1993).

    Article  CAS  PubMed  Google Scholar 

  53. Kamran, P. et al. Parabiosis in mice: a detailed protocol. J. Vis. Exp. https://doi.org/10.3791/50556 (2013).

    Article  PubMed  PubMed Central  Google Scholar 

  54. Matsuzaka, T. et al. Crucial role of a long-chain fatty acid elongase, Elovl6, in obesity-induced insulin resistance. Nat. Med. 13, 1193–1202 (2007).

    Article  CAS  PubMed  Google Scholar 

  55. Li, R. & Kast, J. Biotin switch assays for quantitation of reversible cysteine oxidation. Methods Enzymol. 585, 269–284 (2017).

    Article  CAS  PubMed  Google Scholar 

  56. Masuda, T., Tomita, M. & Ishihama, Y. Phase transfer surfactant-aided trypsin digestion for membrane proteome analysis. J. Proteome Res. 7, 731–740 (2008).

    Article  CAS  PubMed  Google Scholar 

  57. Yu, Y. et al. Hepatocyte-like cells differentiated from human induced pluripotent stem cells: relevance to cellular therapies. Stem Cell Res. 9, 196–207 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  58. Rahaman, M. M. et al. Structure guided chemical modifications of propylthiouracil reveal novel small molecule inhibitors of cytochrome b5 reductase 3 that increase nitric oxide bioavailability. J. Biol. Chem. 290, 16861–16872 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  59. Abramson, J. et al. Accurate structure prediction of biomolecular interactions with AlphaFold 3. Nature 630, 493–500 (2024).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  60. Perez-Riverol, Y. et al. The PRIDE database at 20 years: 2025 update. Nucleic Acids Res. 53, D543–D553 (2025).

    Article  PubMed  Google Scholar 

  61. Haneda, M. et al. A new Classification of Diabetic Nephropathy 2014: a report from Joint Committee on Diabetic Nephropathy. J. Diabetes Investig. 6, 242–246 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

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Acknowledgements

We thank the members of the Shimano laboratory for their contributions and invaluable discussions. We thank K. Inouye (Harvard University) for editing our paper. We thank K. Ohkubo and C. Fukui (University of Tsukuba) for their technical assistance. This work was supported by the Japan Promotion of Science (grant numbers 20K08855 and 23K18270 to M.S.), the Japan Agency for Medical Research and Development under grant numbers JP18gm5910007, JP25gm6710004 and JP22ek0210175, the Takeda Science Foundation, the Ono Medical Research Foundation, the Manpei Suzuki Diabetes Foundation and the Japan Diabetes Foundation (to M.S.).

Author information

Authors and Affiliations

  1. Department of Endocrinology and Metabolism, Institute of Medicine, University of Tsukuba, Tsukuba, Japan

    Motohiro Sekiya, Kenta Kainoh, Wanpei Chen, Daichi Yamazaki, Tomomi Tsuyuzaki, Yuto Kobari, Ayumi Nakata, Kenji Saito, Nao Aono-Soma, Ali Majid, Hiroshi Ohno, Takafumi Miyamoto, Takashi Matsuzaka, Rikako Nakajima, Takaaki Matsuda, Yuki Murayama, Yoko Sugano, Yoshinori Osaki, Hitoshi Iwasaki & Hitoshi Shimano

  2. Transborder Medical Research Center, University of Tsukuba, Tsukuba, Japan

    Takashi Matsuzaka

Authors

  1. Motohiro Sekiya
  2. Kenta Kainoh
  3. Wanpei Chen
  4. Daichi Yamazaki
  5. Tomomi Tsuyuzaki
  6. Yuto Kobari
  7. Ayumi Nakata
  8. Kenji Saito
  9. Nao Aono-Soma
  10. Ali Majid
  11. Hiroshi Ohno
  12. Takafumi Miyamoto
  13. Takashi Matsuzaka
  14. Rikako Nakajima
  15. Takaaki Matsuda
  16. Yuki Murayama
  17. Yoko Sugano
  18. Yoshinori Osaki
  19. Hitoshi Iwasaki
  20. Hitoshi Shimano

Contributions

M.S. performed most of the experiments. K.K. performed critical preliminary experiments that helped shape the direction of this study. W.C. supported the in vivo experiments. D.Y., T.T., Y.K., A.N., K.S., N.A.-S. and A.M. performed basic experiments that helped to draw conclusions. T. Miyamoto performed live-cell imaging. T. Matsuzaka isolated primary mouse hepatocytes. H.O., R.N., T. Matsuda, Y.M., Y.S., Y.O. and H.I. provided intellectual advice. H.S. supervised the project. M.S. conceived and designed the study and wrote the paper.

Corresponding author

Correspondence to Motohiro Sekiya.

Ethics declarations

Competing interests

The authors declare that a domestic patent application (patent application no. 2025-012235) related to this work has been filed by the University of Tsukuba, with M.S. as an inventor. The patent is under review and has not yet been granted. The other authors declare no competing interests.

Peer review

Peer review information

Nature Aging thanks Xi Chen, Shaodong Guo and Changjun Li for their contribution to the peer review of this work.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data

Extended Data Fig. 1 Disruption of the metabolite-sensing pocket of CtBP2 leads to embryonic sublethality.

a. Ten micrograms of exosomes from HEK293 cells were incubated with or without Triton X-100 (TX100) or proteinase K (proK) for 15 min at 37 °C. Subsequently, proteinase K was inactivated by adding 5 mM PMSF. b. HEK293 cells were stimulated with increasing concentrations of lactate as in Fig. 1f, and secretion of exosome markers was examined. c. Targeting strategy for Rossmann fold mutation knock-in mice. Cre-mediated excision of wild-type exon 5–9 (yellow boxes) results in expression of the Rossmann fold mutant CtBP2 (exon 5–9 are indicated by green boxes). HA-tag was fused to C-termini of both wild-type and mutant CtBP2 (purple boxes). d. Parental genotypes and allele frequencies in progenies. e. A representative picture of uterus (E12.5). Dead embryos are indicated by yellow arrows. f,g. A representative picture of WT/WT and Mut/Mut mice and their body weights (male) measured at 6 weeks of age (n= 13, 14 and 5 for WT/WT, WT/Mut and Mut/Mut, respectively, p = 0.0054). h,i. Body weights (8 weeks of age, h) and serum CtBP2 levels (i) of inducible Mut/Mut mice (CAGG-Cre ERTM +) along with those of their control mice (CAGG-Cre ERTM). Data are expressed as mean ± SEM. ** denotes p < 0.01. Statistical analyses are as follows: one-way ANOVA followed by Tukey’s test (g) and two-sided Student’s t-test (h).

Source data

Extended Data Fig. 2 CtBP2 interacts with HECT ligases to be monoubiquitinated, a sorting signal for the exosome secretion pathway.

a. A Venn diagram showing the screening process to identify proteins with the dual characteristics of CtBP2 binding capability and residence in exosomes. b. CtBP2 and HECT ligases were exogenously expressed in HEK293 cells, and their interactions were determined. Domain structures of HECT ligases are depicted as rectangles in different colors above the blots (orange: C2 domain, black: WW domain, blue: HECT domain, X in red: PXDL motifs mutated in the mutants of HECT ligases (Mut)). c. Interactions between CtBP2 and SMURF1 or WWP2 at the protein level using purified recombinant proteins. d. Knockdown efficiencies of our siRNAs (n = 4, technical replicates, p < 0.0001). Data are expressed as mean ± SEM. ** denotes p < 0.01 analyzed by two-sided Student’s t-test (d).

Source data

Extended Data Fig. 3 Multiple lysine residues of CtBP2 can be monoubiquitinated.

a, b. The effects of lysine mutations on CtBP2 monoubiquitination (a) and secretion (b). Various lysine residues in CtBP2 were mutated to arginine. The expression of endogenous human CtBP2 (hCtBP2) in HEK293 cells was suppressed, and lysine mutants along with wild-type (WT) mouse CtBP2 (mCtBP2) were re-expressed (b). The following lysine residues were mutated to arginine: #1; K6R, #2; K8R, #3; K10R, #4; K96R, #5; K200R, #6; K279R, #7; K286R, #8; K311R, #9; K359R and #10; K434R. c. Ubiquitin modifications of intracellular and exosomal CtBP2. Cell lysates and exosomes were prepared from HEK293 cells expressing wild-type CtBP2-HA, and CtBP2 proteins were affinity-purified with the HA-tag. Ubiquitin modifications were detected by ubiquitin-specific antibody. Reflecting the activated status of CtBP2 in exosomes, multimerized forms of CtBP2 were detected (indicated as Multimer and Dimer).

Source data

Extended Data Fig. 4 CtBP2 can be secreted from and taken up into various tissues.

a. We examined serum CtBP2 levels of various tissue-specific CtBP2 knockout (KO) along with their control (flox) mice. b. Heterochronic parabiosis experiments. WT↔WT and HA↔WT denote mice used for parabiosis experiments: surgical union of two female wild-type mice (WT↔WT) and that of a female CtBP2-HA knock-in mouse with a female wild-type mouse (HA↔WT). The WT and HA labels below indicate the genotypes of mice from which samples were collected. Tissue samples were collected five weeks after the surgery.

Source data

Extended Data Fig. 5 The impact of exosomal CtBP2 on aging processes.

ah. Either C+ or C- exosomes (100 μg/mouse) were administered to aged mice (18 months old) twice per week for three months. Glucose metabolism (glucose tolerance test (GTT) (a, n = 11 and 13 for C+ and C-), insulin tolerance test (ITT) (b. raw values, c. normalized to 100% of initial values, n = 11 and 13 for C+ and C-), energy expenditure (d. VO2, e. VCO2, f. respiratory quotient (RQ), n = 10 and 7 for C+ and C-), and body weight change (g, h) (n = 9 and 12 for C+ and C-. Graphs show body weight of the same individual mice before and after C+ or C- exosome treatment.). i,j. IMR90 cells were treated with C+ or C- exosomes (200 μg/ml) for 36 h. i. Mitochondrial mass was estimated by measuring mitochondrial DNAs (mitochondrial NADH dehydrogenase subunit 1 and 5, ND1 and ND5, respectively), normalized to nuclear genomic DNA (GAPDH) (n = 4, technical replicate). j. Expression of mitochondrial electron transport chain and other mitochondria-specific proteins. k. Validation of CtBP2 ELISA. Specificity for CtBP2 was ensured by measuring serially diluted recombinant CtBP1 and CtBP2 proteins. l. Human female subjects between 30 and 69 years of age were classified into two groups on the basis of whether they belonged to long-lived or short-lived family (details described in the Methods, n = 31 and 35 for long-lived and short-lived) and their serum CtBP2 levels were determined (p = 0.039). m. Scatter plot of the relationship between serum CtBP2 levels and age. Samples from subjects over 90 years old (n = 23) were added to those analyzed in Extended Data Fig. 5l. n. Serum CtBP2 levels were determined before and 2 h after consumption of calorie-restricted meals in male and female subjects with diabetes (n = 32 and 13 for male and female subjects). Data are expressed as mean ± SEM. * denotes p < 0.05. Statistical analyses are as follows: two-sided Student’s t-test (l) and linear regression (m).

Source data

Extended Data Fig. 6 Serum CtBP2 levels in human female subjects with diabetes.

Serum CtBP2 levels in female subjects with diabetes. a. Diabetic retinopathy (n = 133, 11 and 45 for simple, pre-proliferative and proliferative, respectively, p = 0.028). b. Diabetic nephropathy classified into 5 stages61 (n = 155, 14 and 37 for stages 1–2 (early stages), 3 (intermediate stage), and 4–5 (end-stages), respectively, p = 0.044). c. Ischemic heart disease (n = 156 and 36 for absence (-) and presence (+) of past history, p = 0.012). d. Cerebral infarction (n = 160 and 41 for absence (-) and presence (+) of past history, p = 0.077). eg. Scatter plots of the relationships between serum CtBP2 levels and age (e), eGFR (f) or PWV (g) in female subjects with diabetes (n = 223, 244 and 182 for e, f and g). h, i. Association with cigarette smoking. Cigarette smoking status (h, n= 146, 33 and 32 for never, former and current, respectively, p = 0.024) and the Brinkman index (i, n = 211). Data are expressed as mean ± SEM. * and ** denote p < 0.05 and p < 0.01, respectively. Statistical analyses are as follows: two-sided Student’s t-test (ad, h) and linear regression (eg, i).

Source data

Extended Data Fig. 7 Alterations of CtBP2 during the aging processes.

a. Senescence was induced by DNA damage in IMR90 cells. Cells were treated with doxorubicin (100 nM or 300 nM) for 24 h followed by 6 days of recovery in fresh medium. b. Tissues were collected from male young mice (7 weeks old) and male aged mice (1 year old). Expression levels of CtBP2 were determined.

Source data

Extended Data Fig. 8 Exosomal CtBP2 activates a FoxM1-PAICS-AMPK pathway.

a. Total NAD(H), NADP(H) levels and the ratios in IMR90 cells treated with C+ or C- exosomes (n = 3). Although data shown are from technical replicates, experiments were independently repeated at least once to confirm reproducibility. b. Knockdown efficiency of our siRNA targeting CYB5R3. c. Upstream regulator analysis by IPA. Table cells highlighted in red and blue are predicted to be activated and suppressed by C+ exosomes, respectively. d. Conservation of PXDL motifs in FoxM1 across different species. e. CtBP2 and/or FoxM1-FLAG were expressed in HEK293 cells as indicated, and the interaction was analyzed by co-immunoprecipitation. f. CtBP2 and/or FoxM1 were expressed in HEK293 cells to evaluate the effects on gene expression, as shown in Fig. 7f. g, h. Enrichment of CtBP2 (g) and FoxM1 (h) in the PAICS gene promoter. Publicly available ChIP-seq data were analyzed (GEO accession numbers: GSE127660 for CtBP2 in the liver, GSE221259 for CtBP2 in pancreatic β-cells, GSM7468687 for FoxM1 in renal epithelial cells, and GSE176383 for FoxM1 in hepatocytes). Data are expressed as mean ± SEM.

Source data

Extended Data Fig. 9 The effects of exosomal CtBP2.

a. IMR90 cells were treated with either vehicle or recombinant CtBP2 (380 ng/ml, equivalent to the CtBP2 content in exosomal CtBP2 treatment studies) for 36 h. b. Generation of U2OS cells with stable knockdown of CtBP2. c,d. Exosomes were isolated from U2OS cells (b) and IMR90 cells were treated with those exosomes (200 μg/ml) for 36 h. Phosphorylation of AMPK (c) and PAICS gene expression (d, n = 6, technical replicate, p < 0.0001) were examined. e. Validation of our C+ and C- exosome samples subjected to the proteome analysis. f. The Liver and muscle (gastrocnemius) tissues were collected from the aged mice treated with either C+ and C- exosomes (Fig. 5b, c, Extended Data Fig. 5a–h), and levels of FoxM1-target genes were analyzed (n = 8 and 11 for C+ and C-, p = 0.0031, 0.025, 0.038 for Hjurp, Plk1, Rrm2 in muscle). g. SA-β-gal activities in tissues from aged mice treated with either C+ and C- exosomes (Fig. 5b, c, Extended Data Fig. 5a–h). Yellow scale bar = 100 μm. Data are expressed as mean ± SEM. * and ** denote p < 0.05 and p < 0.01, respectively, analyzed by two-sided Student’s t-test (d, f).

Source data

Extended Data Fig. 10 Schematic representation of our proposed model.

CtBP2 interacts with HECT E3 ligases upon metabolic activation. The monoubiquitination of CtBP2 facilitates sorting into MVB for subsequent exosomal secretion. HECT E3 ligases are sensitive to ROS which inhibits CtBP2 monoubiquitination and secretion. Exosomal CtBP2 activates CYB5R3 to shift the redox balance towards a more reductive state. The increased NADH/NAD+ ratio activates resident CtBP2 to coactivate FoxM1 together with the exosomally delivered CtBP2. The coactivated FoxM1 increases PAICS gene expression, which leads to AICAR production and AMPK activation.The image was created using BioRender.com.

Supplementary information

Reporting Summary

Supplementary Tables 1–5

Supplementary Table 1. The list of proteins potentially targeted by CtBP2. A list of human proteins with PXDL motifs that were extracted from the UniProt database using the GenomeNet motif search tool. Entry codes, protein names, gene names and lengths of the proteins are listed. Supplementary Table 2. List of proteins with dual characteristics of CtBP2 binding and exosome association. List of human proteins with PXDL motifs that could also reside in exosomes. Proteins were cataloged on the basis of the overlap between human proteins with PXDL motifs (Supplementary Table 1) and exosomal cargo proteins in the ExoCarta database. Supplementary Table 3. Clinical parameters of the patients with diabetes analyzed in this study. Clinical parameters associated with samples from patients with diabetes in this study. Data are expressed as mean ± s.e.m., analyzed by two-sided Student’s t-test. Supplementary Table 4. Metabolomic analysis of IMR-90 cells treated with exosomal CtBP2. List of the identified compound names along with their corresponding PubChem and HMDB IDs for reference, m/z values for identification and relative areas used for quantification. N.D., not detected. Supplementary Table 5. Proteome-wide analysis of C+ and C exosomes. Proteins were extracted from C+ and C exosomes, separated by SDS–PAGE. Following excision and in-gel digestion, the extracted peptides were subjected to LC–MS/MS analysis. Raw values along with UniProt protein IDs, protein names and gene names are shown. NaN, not a number, undetectable in this analysis.

Supplementary Video 1

We fluorescently labeled our C+ exosomes and chased their uptake into IMR90 cells under apodization phase-contrast microscopy.

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Sekiya, M., Kainoh, K., Chen, W. et al. The secreted metabolite sensor CtBP2 links metabolism to healthy lifespan. Nat Aging (2025). https://doi.org/10.1038/s43587-025-00973-4

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  • DOI: https://doi.org/10.1038/s43587-025-00973-4