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Meteorin-like facilitates skeletal muscle repair through a Stat3/IGF-1 mechanism

Nature Metabolism volume 2, pages 278–289 (2020)Cite this article

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Abstract

The immune system plays a multifunctional role throughout the regenerative process, regulating both pro-/anti-inflammatory phases and progenitor cell function. In the present study, we identify the myokine/cytokine Meteorin-like (Metrnl) as a critical regulator of muscle regeneration. Mice genetically lacking Metrnl have impaired muscle regeneration associated with a reduction in immune cell infiltration and an inability to transition towards an anti-inflammatory phenotype. Isochronic parabiosis, joining wild-type and whole-body Metrnl knock-out (KO) mice, returns Metrnl expression in the injured muscle and improves muscle repair, providing supportive evidence for Metrnl secretion from infiltrating immune cells. Macrophage-specific Metrnl KO mice are also deficient in muscle repair. During muscle regeneration, Metrnl works, in part, through Stat3 activation in macrophages, resulting in differentiation to an anti-inflammatory phenotype. With regard to myogenesis, Metrnl induces macrophage-dependent insulin-like growth factor 1 production, which has a direct effect on primary muscle satellite cell proliferation. Perturbations in this pathway inhibit efficacy of Metrnl in the regenerative process. Together, these studies identify Metrnl as an important regulator of muscle regeneration and a potential therapeutic target to enhance tissue repair.

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Fig. 1: Metrnl is necessary for successful muscle regeneration.
Fig. 2: Metrnl deletion alters immune cell migration and phenotype in injured muscle.
Fig. 3: Myofibre-specific Metrnl mRNA expression is not required for successful muscle regeneration.
Fig. 4: Metrnl gene expression after injury is identified in macrophage populations.
Fig. 5: Macrophage-mediated Metrnl expression is necessary for successful muscle regeneration.
Fig. 6: Metrnl signals directly to macrophages through Stat3 and indirectly to satellite cells through IGF-1.

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Data availability

All transcriptomic data generated or analysed during the present study are included in this published article (and its Supplementary information files). Additional data that support the findings of this study are available from the corresponding author on reasonable request and in GSE145236. Source data for Fig. 6 are available online.

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Acknowledgements

The authors thank Duke’s Cancer Center Flow Cytometry, Histology and Molecular Genomics Cores for support on this project. J.P.W. was supported by funds from the Duke Aging Center/Pepper Center (grant no. P30-AG028716), Borden Scholar Award through Duke University and NIH/NIA grant no. K01AG056664. V.B.K. and J.L.H. were also supported by NIH/NIA grant no. P30-AG028716. D.E.L is supported by the NIH training grant (no. T32HL007057). B.M.S. was supported by an NIH grant (no. R01DK119117).

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Authors and Affiliations

  1. Duke Molecular Physiology Institute, Duke University School of Medicine, Durham, NC, USA

    Gurpreet S. Baht, Akshay Bareja, David E. Lee, Rong Huang, Janet L. Huebner, David B. Bartlett, Jason R. Gibson, Virginia B. Kraus, Simon G. Gregory & James P. White

  2. Department of Orthopaedic Surgery, Duke University School of Medicine, Durham, NC, USA

    Gurpreet S. Baht & Rong Huang

  3. Department of Medicine, Duke University School of Medicine, Durham, NC, USA

    Akshay Bareja, David E. Lee, Virginia B. Kraus & James P. White

  4. Genomics Institute of the Novartis Research Foundation, San Diego, CA, USA

    Rajesh R. Rao

  5. Duke Center for the Study of Aging and Human Development, Duke University School of Medicine, Durham, NC, USA

    David B. Bartlett, Virginia B. Kraus & James P. White

  6. Division of Medical Oncology, Department of Medicine, Duke University, Durham, NC, USA

    David B. Bartlett

  7. Division of Endocrinology and Metabolism, Mayo Clinic College of Medicine, Rochester, MN, USA

    Corey R. Hart & Ian R. Lanza

  8. Department of Neurology, Duke University School of Medicine, Durham, NC, USA

    Simon G. Gregory

  9. Dana-Farber Cancer Institute, Department of Cell Biology, Harvard Medical School, Boston, MA, USA

    Bruce M. Spiegelman

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Contributions

J.P.W., B.M.S. and G.S.B. conceptualized the study. J.P.W. designed research, performed biochemical, cellular and in vivo experiments, analysed the data and wrote the manuscript. D.E.L., R.R.R., A.B. and G.S.B. performed in vivo experiments. S.G.G. and J.R.G. performed single-cell experiments. D.B.B. performed cell migration assays. D.E.L. and R.H. performed and analysed in vitro experiments. J.L.H. and V.B.K. performed and/or analysed protein measurements. I.R.L. and C.R.H. supplied human muscle samples and ran gene expression analysis. J.P.W., G.S.B., A.B., R.R.R. and B.M.S. co-wrote the manuscript, with assistance from the co-authors.

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Correspondence to James P. White.

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Extended data

Extended Data Fig. 1 Metrnl mRNA expression with human muscle damage and CSA analysis of uninjured Metrnl KO muscle.

a, Human muscle Metrnl mRNA expression before and after unaccustomed resistance training (N=11/group). b, left Myofiber cross-sections from uninjured wild-type and Metrnl KO mice and right corresponding myofiber cross-sectional area (N=6/group). c, Whole muscle mRNA expression of anti-inflammatory and pro-inflammatory macrophage makers in uninjured muscle (N=4 for both groups). Scale bar is 50μm; Two-tailed, unpaired Student’s t-test (a–c). Data are presented as mean ± SE.

Extended Data Fig. 2 Skeletal muscle specific deletion of Metrnl and the chemotaxis ability of Metrnl.

a, Metrnl mRNA across tissues with or without tamoxifen treatment. Samples were harvested two weeks after tamoxifen IP injections (N=5/group). b, Migration assays using LPS and IL-4-treated macrophages. c, FACS analysis of migrating M1 or (d) M2 differentiated macrophages to recombinant Metrnl protein (N=3/group). Two-tailed, unpaired Student’s t-test (a) and ANOVA with Tukey’s post hoc comparison (c, d). Data are presented as mean ± SE.

Extended Data Fig. 3 Hematopoietic-derived Metrnl expression is necessary and sufficient for successful muscle regeneration.

a, Experimental design for the bone marrow transplant. Wild-type or Metrnl KO mice served as donor mice to wild-type or Metrnl KO recipient mice. Mice received BaCL2 injection five weeks after irradiation and recovered for 14 days before harvest. b, left GFP+ cells in circulating blood from a wild-type donor into a wild-type recipient 5 weeks after transplant. right GFP+ cells in circulating blood from a GFP donor into a wild-type recipient 5 weeks after transplant. N=5 biologically independent samples. c, GFP+ cells infiltrating muscle 1 day after injury in the respective transplant groups. N=5 biologically independent samples. Scale bar 100 µm. d, Metrnl mRNA expression. (N=5/group). e, Representative images of the respective transplantation groups 14 days after injury. N=5 biologically independent samples. f, Quantification of myofiber cross sectional area of the respective transplantation groups. (N=5/group). Scale bar 100 µm. ANOVA with Tukey’s post hoc comparison (d, f). Data are presented as mean ± SE.

Extended Data Fig. 4 Metrnl signals directly to macrophages through Stat3 and indirectly to satellite cells through IGF-1.

a, EdU incorporation in MuSCs treated with recombinant Metrnl or control 24 h in culture (N=6/group). b, untreated/M0 BMM mRNA expression of IL-10, IGF-1 and IL-6 with or without recombinant Metrnl and/or Stat inhibitors, N=3/group. c, EdU incorporation in MuSCs treated with recombinant Metrnl, IL-10 and IGF-1 for 24 h in culture. (N=6/group). d, Experimental design of BMM-conditional media treatment to MuSCs. e, EdU incorporation in media-treated MuSCs in culture for 24 h. (N=3/group). f, BrdU incorporation in satellite cells 4 days after injury with or without recombinant Metrnl or Stat3 inhibitor. (N=6/group) Two-tailed, unpaired Student’s t-test (a). One-way ANOVA with Tukey’s post hoc comparison (b–f). Data are presented as mean ± SE.

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Baht, G.S., Bareja, A., Lee, D.E. et al. Meteorin-like facilitates skeletal muscle repair through a Stat3/IGF-1 mechanism. Nat Metab 2, 278–289 (2020). https://doi.org/10.1038/s42255-020-0184-y

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