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SIRT2 counteracts primate cardiac aging via deacetylation of STAT3 that silences CDKN2B

Nature Aging volume 3, pages 1269–1287 (2023)Cite this article

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Abstract

Aging is a major risk factor contributing to pathophysiological changes in the heart, yet its intrinsic mechanisms have been largely unexplored in primates. In this study, we investigated the hypertrophic and senescence phenotypes in the hearts of aged cynomolgus monkeys as well as the transcriptomic and proteomic landscapes of young and aged primate hearts. SIRT2 was identified as a key protein decreased in aged monkey hearts, and engineered SIRT2 deficiency in human pluripotent stem cell-derived cardiomyocytes recapitulated key senescence features of primate heart aging. Further investigations revealed that loss of SIRT2 in human cardiomyocytes led to the hyperacetylation of STAT3, which transcriptionally activated CDKN2B and, in turn, triggered cardiomyocyte degeneration. Intra-myocardial injection of lentiviruses expressing SIRT2 ameliorated age-related cardiac dysfunction in mice. Taken together, our study provides valuable resources for decoding primate cardiac aging and identifies the SIRT2–STAT3–CDKN2B regulatory axis as a potential therapeutic target against human cardiac aging and aging-related cardiovascular diseases.

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Fig. 1: Phenotypic alterations in aged NHP heart.
Fig. 2: SIRT2 counteracts primate heart aging.
Fig. 3: SIRT2 knockout induces senescence and functional decline in human cardiomyocytes.
Fig. 4: STAT3 potentially mediates transcriptional perturbation induced by SIRT2 deficiency.
Fig. 5: SIRT2 deacetylates STAT3 on Lys685.
Fig. 6: Lys685-acetylated STAT3 transcriptionally activates CDKN2B.
Fig. 7: CDKN2B knockdown or SIRT2 overexpression ameliorates cardiac aging phenotype.

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Data availability

The transcriptomic data obtained in the study have been deposited in the Genome Sequence Archive97 in the National Genomics Data Center, Beijing Institute of Genomics (China National Center for Bioinformation), of the Chinese Academy of Sciences, under accession number HRA002883 (human cardiomyocytes) and CRA007858 (monkey hearts). The proteomic data have been deposited to the ProteomeXchange Consortium via the iProX partner repository98 under accession numbers PXD036689 and PXD036693.

Code availability

Codes used for the analysis of RNA sequencing in this study are available at https://github.com/Ykk151/Primate_Heart_aging.

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Acknowledgements

We would like to thank Ruoqi Wang (Institute of Biophysics, Chinese Academy of Sciences) for the help with the generation of SIRT2-deficient hESCs. We thank the Center for Biological Imaging, Institute of Biophysics, Chinese Academy of Sciences, for the TEM analysis, and we are grateful to C. Peng for the TEM sample preparation and X. Li for help with the TEM operation. We thank S. Li, X. Zhu, J. Hao and Y. Teng (the Center of Imaging facility of the Institute of Zoology and Institute of Biophysics, Chinese Academy of Sciences) for help with imaging scanning as well as L. Wang for help with the echocardiography analysis. We thank J. Wang for help with the LC–MS/MS assay and J. Jia for help with the FACS experiment. We thank F. Liu, J. Jia and C. Xie for help with animal experiments; D. Lv and C. Zhang for help with the H&E assay; and L. Bai, Q. Chu, J. Lu, L. Tian, S. Qiao, Y. Yang, X. Chen, J. Chen, R. Bai and S. Ma for administrative assistance. Figures 1a, 3a, 5a,g and 7a,e,i, Extended Data Fig. 9a and Supplementary Fig. 1 were created with BioRender. This work was supported by the National Key Research and Development Program of China (2022YFA1103700 to W.Z. and J.Q.), the National Natural Science Foundation of China (91949209 to J.Q. and 32000510 to Y.F.), the National Key Research and Development Program of China (2022YFC3602500 to Y. Ye; 2020YFA0804000 to G.-H.L. and S.W.; 2020YFA0112200 to G.-H.L.; 2021YFF1201000 to W.Z.; the STI2030-Major Projects-2021ZD0202400 to S.W.; and 2022YFA1104700 to Y. Ye), the National Natural Science Foundation of China (81921006 to G.-H.L., J.Q. and M.S.; 82125011 to J.Q.; 92149301 to G.-H.L. and S.W.; 92168201 to G.-H.L.; 92049304 to J.Q.; 92049116 to W.Z.; 32121001 to W.Z.; 82192863 to W.Z.; 82122024 to S.W.; 82071588 to S.W.; 81601233 to Y. Ye; and 82201714 to D.H.), the Strategic Priority Research Program of the Chinese Academy of Sciences (XDA16000000 to G.-H.L., J.Q., M.S., W.Z. and S.W.), the Chinese Academy of Sciences Project for Young Scientists in Basic Research (YSBR-076 to G.-H.L., J.Q. and M.S. and YSBR-012 to W.Z.), the Program of the Beijing Natural Science Foundation (Z190019 to G.-H.L. and W.Z. and JQ20031 to M.S.), the Project for Technology Development of Beijing-affiliated Medical Research Institutes (11000023T000002036310 to S.W.), the Youth Innovation Promotion Association of the Chinese Academy of Sciences (E1CAZW0401 to W.Z.), the Young Elite Scientists Sponsorship Program by CAST (YESS20200012 to S.W.), the Informatization Plan of the Chinese Academy of Sciences (CAS-WX2021SF-0301 to G.-H.L.; CAS-WX2022SDC-XK14 to G.-H.L.; and CAS-WX2021SF-0101 to J.Q.), the Tencent Foundation (2021-1045 to G.-H.L.), the Excellent Young Talents Program of Capital Medical University (12300927 to S.W.), the Excellent Young Talents Training Program for the Construction of Beijing Municipal University Teacher Team (BPHR202203105 to S.W.), the Pilot Project for Public Welfare Development and Reform of Beijing-affiliated Medical Research Institutes (11000022T000000461062 to S.W.) and the Fellowship of China Postdoctoral Science Foundation (2022M712216 to D.H.). The funders had no role in study design, data collection and analysis, the decision to publish or the preparation of the manuscript.

Author information

Author notes

  1. These authors contributed equally: Yanxia Ye, Kuan Yang, Haisong Liu, Yang Yu, Moshi Song.

Authors and Affiliations

  1. State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, China

    Yanxia Ye, Zunpeng Liu, Qun Chu & Jing Qu

  2. Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, China

    Yanxia Ye, Moshi Song, Yiyuan Zhang, Qun Chu, Yaobin Jing, Jing Qu & Guang-Hui Liu

  3. Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, China

    Yanxia Ye, Moshi Song, Yiyuan Zhang, Zunpeng Liu, Qun Chu, Yaobin Jing, Jing Qu, Weiqi Zhang & Guang-Hui Liu

  4. CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, China

    Kuan Yang, Moshi Song, Yanling Fan & Weiqi Zhang

  5. University of Chinese Academy of Sciences, Beijing, China

    Kuan Yang, Zunpeng Liu, Sheng Zhang, Yaobin Jing, Jing Qu, Weiqi Zhang & Guang-Hui Liu

  6. Sino-Danish College, University of Chinese Academy of Sciences, Beijing, China

    Kuan Yang & Weiqi Zhang

  7. School of Biomedical Sciences, Hunan University, Changsha, China

    Haisong Liu

  8. Beijing Key Laboratory of Reproductive Endocrinology and Assisted Reproductive Technology and Key Laboratory of Assisted Reproduction, Ministry of Education, Center of Reproductive Medicine, Department of Obstetrics and Gynecology, Peking University Third Hospital, Beijing, China

    Yang Yu

  9. Clinical Stem Cell Research Center, Peking University Third Hospital, Beijing, China

    Yang Yu

  10. State Key Laboratory of Membrane Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, China

    Moshi Song, Yiyuan Zhang, Sheng Zhang, Yaobin Jing & Guang-Hui Liu

  11. Advanced Innovation Center for Human Brain Protection, and National Clinical Research Center for Geriatric Disorders, Xuanwu Hospital Capital Medical University, Beijing, China

    Daoyuan Huang, Jinghui Lei, Si Wang & Guang-Hui Liu

  12. Aging Translational Medicine Center, International Center for Aging and Cancer, Xuanwu Hospital, Capital Medical University, Beijing, China

    Daoyuan Huang, Jinghui Lei, Si Wang & Guang-Hui Liu

  13. The Fifth People’s Hospital of Chongqing, Chongqing, China

    Qun Chu & Si Wang

  14. State Key Laboratory of Brain and Cognitive Science, CAS Center for Excellence in Brain Science and Intelligence Technology, Institute of Brain-Intelligence Technology (Shanghai), Institute of Biophysics, Chinese Academy of Sciences, Beijing, China

    Sheng Zhang

  15. Altos Labs, Inc., San Diego, CA, USA

    Concepcion Rodriguez Esteban & Juan Carlos Izpisua Belmonte

Authors
  1. Yanxia Ye
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  2. Kuan Yang
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  3. Haisong Liu
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  4. Yang Yu
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  5. Moshi Song
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  6. Daoyuan Huang
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  7. Jinghui Lei
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  8. Yiyuan Zhang
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  9. Zunpeng Liu
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  10. Qun Chu
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  11. Yanling Fan
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  12. Sheng Zhang
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  13. Yaobin Jing
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  14. Concepcion Rodriguez Esteban
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  15. Si Wang
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  16. Juan Carlos Izpisua Belmonte
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  17. Jing Qu
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  18. Weiqi Zhang
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  19. Guang-Hui Liu
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Contributions

G.-H.L., J.Q. and W.Z. conceived the work and supervised the overall experiments. Y. Ye performed the experiments related to the phenotypic and mechanistic analyses, including western blotting, ChIP–qPCR, co-IP, immunofluorescence and immunohistochemistry staining, cardiomyocyte differentiation, plasmid construction and animal experiments. K.Y. performed bioinformatic analyses. H.L., Y. Yu and M.S. performed the manuscript writing. D.H. performed the co-IP experiments. J.L. performed the animal experiments. Y.Z. performed the H&E, immunofluorescence, Masson’s trichrome staining in cynomolgus monkeys and Ki67 staining in hESCs. Z.L. helped with the bioinformatic analyses. Q.C. performed the immunofluorescence staining of teratomas. Y.F., S.Z. and Y.J. helped with the sample preparation. C.R.E., S.W. and J.C.I.B. helped with supervision of the project. G.-H.L., J.Q., W.Z., Y. Ye, K.Y., H.L., Y. Yu and M.S. performed manuscript writing, reviewing and editing. All authors reviewed the manuscript.

Corresponding authors

Correspondence to Jing Qu, Weiqi Zhang or Guang-Hui Liu.

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Competing interests

J.C.I.B. is an employee of Altos Labs. The other authors declare no competing interests.

Peer review

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Nature Aging thanks Laura Cox, Mark Sussman and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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

Extended data

Extended Data Fig. 1 Proteomic analysis of aged and young monkey hearts.

a, Box plot showing the normalized intensities for each replicate in proteomics of young and aged monkey hearts. The boxes show the median values (centre line) and interquartile ranges. The whiskers extend from the quartile to the minimum and maximum values. b, Bar plot showing the distribution of the number of peptides in identified proteins of proteomics of young and aged monkey hearts. c, Heatmap showing the Euclidean distance for proteomic data between young and aged monkey hearts. The color key of the Euclidean distance from blue to white indicates strong to weak correlations. d, Principal component analysis of proteomic data between young and aged monkey hearts. e, Heatmap showing the DEPs overlapped with the epigenetic regulation-associated genes in aged monkey hearts. The color key from blue to purple indicates log2(fold change) from low to high. f, Left, box plot showing the protein level of SIRT2 in young and aged female monkey hearts. Right, box plot showing the protein level of SIRT2 in young and aged male monkey hearts. The boxes show the median values (centre line) and interquartile ranges. The whiskers extend from the quartile to the minimum and maximum values. Two-tailed Student’s t-test, n = 3 replicates per group. g, Western blotting of SIRT2 in young and aged female or male monkey hearts. Data are presented as the mean ± s.e.m., two-tailed Student’s t-test. n = 4 biological replicates. h, Network plot showing DEPs that are common to the aged monkey hearts and plasma of aging individuals or patients with cardiovascular diseases. Node colors from blue to purple indicate log2(fold change) from low to high. i, Point plot showing DEPs that have not been annotated with four aging-related cardiovascular diseases. Point size indicates absolute log2(fold change).

Source data

Extended Data Fig. 2 Characterizing hESCs and analysis of p21 expression in human cardiomyocytes.

a, Schematic diagram of SIRT2 knockout strategy through CRISPR-Cas9-mediated non-homologous end joining (NHEJ) in SIRT2+/+ hESCs. b, Western blotting of SIRT2 in SIRT2+/+ and SIRT2-/- hESCs. GAPDH was used as the control. c, Karyotype analysis of SIRT2-/- hESCs (female). d, Immunofluorescence analysis of TuJ1, SMA, and FOXA2 to evaluate the differentiation potential of SIRT2+/+ and SIRT2-/- hESCs toward lineages of all three germ layers, that is, ectoderm, mesoderm, and endoderm, respectively. Scale bars, 50 μm. e, Immunofluorescence analysis of Ki67 expression in SIRT2+/+ and SIRT2-/- hESCs. Scale bars, 25 μm. f, Flow cytometry gating strategy for Fig. 3b. g, Western blotting of p21 in SIRT2+/+ and SIRT2-/- human cardiomyocytes (whole blot). GAPDH was used as the control. h, Flow cytometry gating strategy for Fig. 3l. Two-tailed Student’s t-test was used for statistical analysis. Data are presented as the mean ± s.e.m. Data are representative of 3 independent experiments in b. n = 5 biological replicates in e. Data are representative of 5 independent experiments in g. hCardiomyocyte, human cardiomyocyte.

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Extended Data Fig. 3 Transcriptomic analysis of human cardiomyocytes and monkey hearts.

a, Bar plot showing the percentage of duplicate reads, GC content and total sequences for RNA-seq of SIRT2-/- and SIRT2+/+ human cardiomyocytes. b, Bar plot showing the percentage of duplicate reads, GC content and total sequences for RNA-seq of young and aged monkey hearts. c, Bar plot showing representative GO terms enriched by DEGs in SIRT2-/- human cardiomyocytes. Key DEGs enriched in the indicated terms are listed. d, Bar plot showing representative GO terms enriched by DEGs in aged monkey hearts. Key DEGs enriched in the indicated terms are listed. hCardiomyocyte, human cardiomyocyte; mkHeart, monkey heart.

Extended Data Fig. 4 Gene set analysis and TF analysis in aged monkey hearts and SIRT2-deficient human cardiomyocytes.

a, Gene set enrichment analysis (GSEA) plot showing the upregulated calcium signaling pathway and downregulated lipid metabolism shared in aged monkey hearts and SIRT2-deficient human cardiomyocytes (hCM). b, Network plot showing STAT3 target DEGs in aged monkey hearts. Node colors from white to purple indicate log2(fold change) from low to high. c, Left, bar plot showing the TFs enriched by DEGs in aged female monkey hearts. Right, bar plot showing the TFs enriched by DEGs in aged male monkey hearts. d, Left, GSEA plot showing STAT3 target DEGs in aged female monkey hearts; Right, GSEA plot showing STAT3 target DEGs in aged male monkey hearts. hCardiomyocyte, human cardiomyocyte; mkHeart, monkey heart; NES, normalized enrichment score.

Extended Data Fig. 5 STAT3 interacts with the deacetylation-defective mutant SIRT2 (H187Y).

Co-IP analysis of STAT3 with exogenous FLAG-SIRT2-H187Y in HEK293T cells. Data are representative of 3 independent experiments.

Source data

Extended Data Fig. 6 Dissecting the SIRT2-STAT3 axis in human pluripotent stem cell-derived cardiomyocytes.

a, Violin plot showing the transcriptional levels of STAT3 in SIRT2+/+ and SIRT2-/- human cardiomyocytes. The black lines represent the mean value. FPKM, Fragments Per Kilobase per Million mapped reads. b, Verification of STAT3 mRNA expression levels by RT-qPCR in SIRT2+/+ and SIRT2-/- human cardiomyocytes. c, Western blotting of STAT3 in SIRT2+/+ and SIRT2-/- human cardiomyocytes. d,e, Western blotting of SIRT2 (d), as well as RT-qPCR analysis of the relative expression levels of BNP (e) in male hESC-derived cardiomyocytes transduced with lentiviral shRNAs targeting SIRT2 (shSIRT2) or non-targeting control (shGL2). f,g, Western blotting of SIRT2 (f), as well as RT-qPCR analysis of the relative expression levels of BNP (g) in male human induced pluripotent stem cell (hiPSC)-derived cardiomyocytes transduced with lentiviral shSIRT2 or shGL2. h,i, Western blotting showing the acetylation level of STAT3-K685 in male hESC-derived (h) or hiPSC-derived (i) cardiomyocytes transduced with lentiviral shSIRT2 or shGL2. Two-tailed Student’s t-test was used for statistical analysis in a-i. Data are presented as the mean ± s.e.m. n = 3, 4, 3, 3 biological replicates in a, b, e, g, respectively. n = 3 independent experiments in c, d, f, h and i. For western blotting, GAPDH was used as the control. hCardiomyocyte, human cardiomyocyte.

Source data

Extended Data Fig. 7 Dissecting the SIRT2-STAT3-CDKN2B axis in monkey hearts.

a, Violin plot showing the transcriptional levels of STAT3 in young and aged monkey hearts. The black lines represent the mean value. b, Violin plot showing the protein level of STAT3 in young and aged monkey hearts. The black lines represent the mean value. c, Verification of STAT3 mRNA expression levels by RT-qPCR in the young and aged monkey hearts. d, Western blotting of STAT3 in the young and aged monkey hearts. e,f, The acetylation level of STAT3 in young and aged female (e) or male (f) monkey hearts. Lysates prepared from young and aged female or male monkey hearts were immunoprecipitated with antibodies to STAT3 and analyzed with antibodies to acetylated lysine by western blotting. g, Left, box plot showing the transcriptional level of CDKN2B in young and aged female monkey hearts; Right, box plot showing the transcriptional level of CDKN2B in young and aged male monkey hearts. The boxes show the median values (centre line) and interquartile range. The whiskers extend from the quartile to the minimum and maximum values. h, Western blotting of CDKN2B in young and aged female or male monkey hearts. Two-tailed Student’s t-test was used for statistical analysis in a-h. Data are presented as the mean ± s.e.m. n = 8 biological replicates in a, c and d. n = 6 replicates in b. n = 3 replicates in e and f, representative of 2 independent experiments, respectively. n = 4 biological replicates in g and h. For western blotting, GAPDH was used as the control. mkHeart, monkey heart.

Source data

Extended Data Fig. 8 Dissecting the SIRT2-STAT3-CDKN2B axis in human cardiomyocytes.

a,b, Western blotting of CDKN2B in male hESC-derived (a) or hiPSC-derived (b) cardiomyocytes transduced with lentiviral shSIRT2 or shGL2. c, Western blotting of CDKN2B in wildtype human cardiomyocytes transduced with lentiviruses expressing Luc, STAT3-WT, or STAT3-K685R. Two-tailed Student’s t-test was used for statistical analysis in a-c. Data are presented as the mean ± s.e.m. n = 4, 3, 3 independent experiments in a, b, c, respectively. For western blotting, GAPDH was used as the control. hCardiomyocyte, human cardiomyocyte.

Source data

Extended Data Fig. 9 CDKN2B mediates aging phenotype in human cardiomyocytes.

a-c, Schematic diagram (a), western blotting of CDKN2B (b), and immunofluorescence analysis of cTnT (c) in wildtype human cardiomyocytes transduced with lentiviruses expressing Luc or CDKN2B. Scale bars in c, 20 μm. d, SA-β-Gal staining of wildtype human cardiomyocytes transduced with lentiviruses expressing Luc or CDKN2B. Scale bars, 50 μm. e, Western blotting of CDKN2B in SIRT2-/- human cardiomyocytes transfected with vectors expressing Cas9 and sgNTC or sgCDKN2B. Two-tailed Student’s t-test was used for statistical analysis in b-e. Data are presented as the mean ± s.e.m. n = 4, 3 independent experiments in b, e, respectively. n = 100 cells examined in 3 independent experiments in c. n = 3 biological replicates in d. For western blotting, GAPDH was used as the control.

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Supplementary information

Supplementary information

Supplementary Fig. 1

Reporting Summary

Supplementary Tables

Supplementary Tables 1–6. Supplementary Table 1: Information summary of the cynomolgus monkeys used in this study. Supplementary Table 2: DEPs between aged and young cynomolgus monkey hearts. Supplementary Table 3: DEGs between aged and young cynomolgus monkey hearts or between SIRT2−/− and SIRT2+/+ human cardiomyocytes. Supplementary Table 4: The candidate SIRT2-interacting proteins identified by mass spectrometry. Supplementary Table 5: List of antibodies used in this study. Supplementary Table 6: The sequences of sgRNAs and primers used for gene editing, plasmid construction, RT–qPCR and ChIP–qPCR.

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Ye, Y., Yang, K., Liu, H. et al. SIRT2 counteracts primate cardiac aging via deacetylation of STAT3 that silences CDKN2B. Nat Aging 3, 1269–1287 (2023). https://doi.org/10.1038/s43587-023-00486-y

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