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Dissociation of muscle insulin sensitivity from exercise endurance in mice by HDAC3 depletion

Nature Medicine volume 23, pages 223234 (2017) | Download Citation

Abstract

Type 2 diabetes and insulin resistance are associated with reduced glucose utilization in the muscle and poor exercise performance. Here we find that depletion of the epigenome modifier histone deacetylase 3 (HDAC3) specifically in skeletal muscle causes severe systemic insulin resistance in mice but markedly enhances endurance and resistance to muscle fatigue, despite reducing muscle force. This seemingly paradoxical phenotype is due to lower glucose utilization and greater lipid oxidation in HDAC3-depleted muscles, a fuel switch caused by the activation of anaplerotic reactions driven by AMP deaminase 3 (Ampd3) and catabolism of branched-chain amino acids. These findings highlight the pivotal role of amino acid catabolism in muscle fatigue and type 2 diabetes pathogenesis. Further, as genome occupancy of HDAC3 in skeletal muscle is controlled by the circadian clock, these results delineate an epigenomic regulatory mechanism through which the circadian clock governs skeletal muscle bioenergetics. These findings suggest that physical exercise at certain times of the day or pharmacological targeting of HDAC3 could potentially be harnessed to alter systemic fuel metabolism and exercise performance.

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Acknowledgements

We thank S. Burden (New York University) for MLC-Cre mice, J. Hogenesch (University of Pennsylvania) for processed data from circaDB, M. Birnbaum and J. Baur (University of Pennsylvania) for helpful discussion, S. Guo (Texas A&M University) for help with the EPS procedure, P. Zhang (Baylor College of Medicine) for adenoviral plasmids, S. Hui and J. Park (Princeton University) for analysis of metabolomics data, V. Narkar (University of Texas Health Science Center) for the immunostaining protocol, M. Goncalves and C. Lanzillotta (University of Pennsylvania) for technical assistance. We thank the Penn Diabetes Center (DK19525) Functional Genomics Core for nucleotide sequencing, the Mouse Metabolic Phenotyping Core for clamp experiments, the Penn Muscle Institute Muscle Physiology Assessment Core for muscle contraction study, and the Princeton/Penn Regional Metabolomics Core for flux and lipid analysis. We thank the Baylor Diabetes Center (DK079638) Metabolism Core for Seahorse analysis and Vanderbilt MMPC (DK59637) for lipidomics analysis. The Rockefeller Proteomics Resource Center is supported by the Leona M. and Harry B. Helmsley Charitable Trust. This work was supported by NIH grants CA211437 (W.L.), DK043806 (M.A.L.) and DK099443 (Z.S.).

Author information

Author notes

    • Sungguan Hong
    • , Wenjun Zhou
    •  & Bin Fang

    These authors contributed equally to this work.

Affiliations

  1. Division of Diabetes, Endocrinology and Metabolism, Department of Medicine, Baylor College of Medicine, Houston, Texas, USA.

    • Sungguan Hong
    • , Wenjun Zhou
    • , Guolian Ding
    •  & Zheng Sun
  2. Division of Endocrinology, Diabetes, and Metabolism, Department of Medicine, and the Institute for Diabetes, Obesity, and Metabolism, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.

    • Bin Fang
    • , Manashree Damle
    • , Jennifer Jager
    • , Yuxiang Zhang
    • , Dan Feng
    • , Qingwei Chu
    •  & Mitchell A Lazar
  3. Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, New Jersey, USA.

    • Wenyun Lu
    • , Sisi Zhang
    •  & Joshua D Rabinowitz
  4. Department of Physiology and Pennsylvania Muscle Institute, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.

    • Emanuele Loro
    •  & Tejvir S Khurana
  5. International Peace Maternity and Child Health Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.

    • Guolian Ding
  6. Proteomics Resource Center, the Rockefeller University, New York, New York, USA.

    • Brian D Dill
    •  & Henrik Molina
  7. Department of Molecular and Cellular Biology, Baylor College of Medicine, Houston, Texas, USA.

    • Zheng Sun

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Contributions

Z.S. and M.A.L. conceived the study and designed experiments. S.H., W.Z., W.L., E.L., G.D., J.J., S.Z., Y.Z., D.F., Q.C., B.D.D. and Z.S. conducted experiments. S.H., W.Z., B.F., W.L., M.D., G.D., S.Z., B.D.D., H.M. and Z.S. analyzed the data. E.L., T.S.K., J.D.R., M.A.L. and Z.S. interpreted the data. M.A.L. and Z.S. acquired funding. Z.S. wrote the manuscript with input from other authors.

Competing interests

The authors declare no competing financial interests.

Corresponding authors

Correspondence to Mitchell A Lazar or Zheng Sun.

Supplementary information

PDF files

  1. 1.

    Supplementary Figures

    Supplementary Figures 1–7

Excel files

  1. 1.

    Supplementary Table 1

    Raw data of metabolomics study.

  2. 2.

    Supplementary Table 2

    Differentially expressed genes from RNA-seq.

  3. 3.

    Supplementary Table 3

    Differentially expressed proteins from proteomics.

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DOI

https://doi.org/10.1038/nm.4245

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