Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Article
  • Published:

Glutamine-driven reductive TCA cycle metabolism supports aged muscle stem cell function via de novo lipogenesis

Nature Aging (2026) Cite this article

Subjects

Abstract

Sarcopenia and the age-related decline in muscular strength and regenerative capacity contribute directly to loss of autonomy, greater risk for hospitalization and healthcare utilization. One contributing cellular phenotype associated with skeletal muscle aging is a loss in the function and number of resident muscle stem cells (MuSCs) or satellite cells. MuSC activation leads to dramatic changes in cellular architecture and metabolic reprogramming, including both mitochondrial biogenesis and increased glycolysis. Despite these changes to increase energy production, high energy demands may not be fully met during periods of MuSC activation. Here we used in vitro and in vivo approaches in mice to demonstrate the function of glutaminase for age-related changes in MuSC function. By combining fluorescence-activated cell sorting (FACS) isolation with metabolomics and stable isotope tracing, we show an age-related decline in reductive (counterclockwise) flux of glutamine through the tricarboxylic acid (TCA) cycle, a pathway by which MuSCs build cellular fatty acid stores as necessary biomass for MuSC function.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on SpringerLink
  • Instant access to the full article PDF.

USD 39.95

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: MuSCs require glutamine for successful activation in vitro.
The alternative text for this image may have been generated using AI.
Fig. 2: MuSC GLS is required for successful activation and regeneration in vivo.
The alternative text for this image may have been generated using AI.
Fig. 3: GLS is deficient in old MuSCs and is sufficient to enhance MuSC transplantation.
The alternative text for this image may have been generated using AI.
Fig. 4: Aged MuSCs have proportionately lower reductive glutamine flux during activation.
The alternative text for this image may have been generated using AI.
Fig. 5: IDH2 supports reductive glutamine metabolism to support cellular fatty acid pool.
The alternative text for this image may have been generated using AI.
Fig. 6: Reductive glutamine flux supports MuSC activation via DNL.
The alternative text for this image may have been generated using AI.

Similar content being viewed by others

Data availability

All source data will be provided as a Source Data file. Other data will be available from the corresponding author upon reasonable request.

References

  1. Martinez, B. P. et al. Frequency of sarcopenia and associated factors among hospitalized elderly patients. BMC Musculoskelet. Disord. 16, 108 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  2. Janssen, I., Shepard, D. S., Katzmarzyk, P. T. & Roubenoff, R. The healthcare costs of sarcopenia in the United States. J. Am. Geriatr. Soc. 52, 80–85 (2004).

    Article  PubMed  Google Scholar 

  3. Masschelein, E. et al. Exercise promotes satellite cell contribution to myofibers in a load-dependent manner. Skelet. Muscle 10, 21 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Folmes, C. D., Dzeja, P. P., Nelson, T. J. & Terzic, A. Metabolic plasticity in stem cell homeostasis and differentiation. Cell Stem Cell 11, 596–606 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Pala, F. et al. Distinct metabolic states govern skeletal muscle stem cell fates during prenatal and postnatal myogenesis. J. Cell Sci. 131, jcs212977 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  6. Tang, A. H. & Rando, T. A. Induction of autophagy supports the bioenergetic demands of quiescent muscle stem cell activation. EMBO J. 33, 2782–2797 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Ryall, J. G. et al. The NAD+-dependent SIRT1 deacetylase translates a metabolic switch into regulatory epigenetics in skeletal muscle stem cells. Cell Stem Cell 16, 171–183 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. White, J. P. et al. The AMPK/p27Kip1 axis regulates autophagy/apoptosis decisions in aged skeletal muscle stem cells. Stem Cell Rep. 11, 425–439 (2018).

    Article  CAS  Google Scholar 

  9. Theret, M. et al. AMPKα1-LDH pathway regulates muscle stem cell self-renewal by controlling metabolic homeostasis. EMBO J.36, 1946–1962 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Yoo, H. C., Yu, Y. C., Sung, Y. & Han, J. M. Glutamine reliance in cell metabolism. Exp. Mol. Med. 52, 1496–1516 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Yu, Y. et al. Glutamine metabolism regulates proliferation and lineage allocation in skeletal stem cells. Cell Metab. 29, 966–978 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Soro-Arnáiz, I. et al. GLUD1 determines murine muscle stem cell fate by controlling mitochondrial glutamate levels. Dev. Cell 59, 2850–2865 (2024).

    Article  PubMed  Google Scholar 

  13. Mullen, A. R. et al. Reductive carboxylation supports growth in tumour cells with defective mitochondria. Nature 481, 385–388 (2011).

    Article  PubMed  PubMed Central  Google Scholar 

  14. Mademtzoglou, D., Geara, P., Mourikis, P. & Relaix, F. Pax7 haploinsufficiency impairs muscle stem cell function in Cre-recombinase mice and underscores the importance of appropriate controls. Stem Cell Res. Ther. 14, 294 (2023).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Lai, Y. et al. Multimodal cell atlas of the ageing human skeletal muscle. Nature 629, 154–164 (2024).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Zhang, G. F. et al. Reductive TCA cycle metabolism fuels glutamine- and glucose-stimulated insulin secretion. Cell Metab. 33, 804–817 (2021).

    Article  CAS  PubMed  Google Scholar 

  17. Koves, T. R. et al. Mitochondrial overload and incomplete fatty acid oxidation contribute to skeletal muscle insulin resistance. Cell Metab. 7, 45–56 (2008).

    Article  CAS  PubMed  Google Scholar 

  18. Seiler, S. E. et al. Obesity and lipid stress inhibit carnitine acetyltransferase activity. J. Lipid Res. 55, 635–644 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Kang, J. et al. Depletion of SAM leading to loss of heterochromatin drives muscle stem cell ageing. Nat Metab. 6, 153–168 (2024).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Ciuffoli, V. et al. Psat1-generated α-ketoglutarate and glutamine promote muscle stem cell activation and regeneration. Genes Dev. 38, 151–167 (2024).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Castegna, A. & Menga, A. Glutamine synthetase: localization dictates outcome. Genes (Basel) 9, 108 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  22. Holleran, A. L., Briscoe, D. A., Fiskum, G. & Kelleher, J. K. Glutamine metabolism in AS-30D hepatoma cells. Evidence for its conversion into lipids via reductive carboxylation. Mol. Cell. Biochem. 152, 95–101 (1995).

    Article  CAS  PubMed  Google Scholar 

  23. Machado, L. et al. Tissue damage induces a conserved stress response that initiates quiescent muscle stem cell activation. Cell Stem Cell 28, 1125–1135 (2021).

    Article  CAS  PubMed  Google Scholar 

  24. van Velthoven, C. T. J., de Morree, A., Egner, I. M., Brett, J. O. & Rando, T. A. Transcriptional profiling of quiescent muscle stem cells in vivo. Cell Rep. 21, 1994–2004 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  25. Urbani, L., Piccoli, M., Franzin, C., Pozzobon, M. & De Coppi, P. Hypoxia increases mouse satellite cell clone proliferation maintaining both in vitro and in vivo heterogeneity and myogenic potential. PLoS ONE 7, e49860 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Liu, W. et al. Hypoxia promotes satellite cell self-renewal and enhances the efficiency of myoblast transplantation. Development 139, 2857–2865 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Xie, L. et al. Transient HIF2A inhibition promotes satellite cell proliferation and muscle regeneration. J. Clin. Invest. 128, 2339–2355 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  28. Shang, M. et al. Macrophage-derived glutamine boosts satellite cells and muscle regeneration. Nature 587, 626–631 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Brack, A. S. et al. Increased Wnt signaling during aging alters muscle stem cell fate and increases fibrosis. Science317, 807–810 (2007).

    Article  CAS  PubMed  Google Scholar 

  30. Lazure, F. et al. Transcriptional reprogramming of skeletal muscle stem cells by the niche environment. Nat. Commun. 14, 535 (2023).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Cerletti, M., Jang, Y. C., Finley, L. W., Haigis, M. C. & Wagers, A. J. Short-term calorie restriction enhances skeletal muscle stem cell function. Cell Stem Cell 10, 515–519 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Kneppers, A. et al. AMPKα2 is a skeletal muscle stem cell intrinsic regulator of myonuclear accretion. iScience 26, 108343 (2023).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. García-Prat, L. et al. Autophagy maintains stemness by preventing senescence. Nature 529, 37–42 (2016).

    Article  PubMed  Google Scholar 

  34. García-Prat, L. et al. FoxO maintains a genuine muscle stem-cell quiescent state until geriatric age. Nat. Cell Biol. 22, 1307–1318 (2020).

    Article  PubMed  Google Scholar 

  35. Kim, D., Jitrapakdee, S. & Thompson, M. Differential regulation of the promoter activity of the mouse UCP2 and UCP3 genes by MyoD and myogenin. J. Biochem. Mol. Biol. 40, 921–927 (2007).

    CAS  PubMed  Google Scholar 

  36. Chen, X. et al. In vitro evidence suggests that miR-133a-mediated regulation of uncoupling protein 2 (UCP2) is an indispensable step in myogenic differentiation. J. Biol. Chem. 284, 5362–5369 (2009).

    Article  CAS  PubMed  Google Scholar 

  37. McKellar, D. W. et al. Large-scale integration of single-cell transcriptomic data captures transitional progenitor states in mouse skeletal muscle regeneration. Commun. Biol. 4, 1280 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Liu, L., Cheung, T. H., Charville, G. W. & Rando, T. A. Isolation of skeletal muscle stem cells by fluorescence-activated cell sorting. Nat. Protoc. 10, 1612–1624 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Ly, C. H. & Ryall, J. G. Measuring mitochondrial substrate utilization in skeletal muscle stem cells. Methods Mol. Biol. 1668, 61–73 (2017).

    Article  CAS  PubMed  Google Scholar 

  40. Yue, F. et al. Lipid droplet dynamics regulate adult muscle stem cell fate. Cell Rep. 38, 110267 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. White, P. J. et al. The BCKDH kinase and phosphatase integrate BCAA and lipid metabolism via regulation of ATP-citrate lyase. Cell Metab. 27, 1281–1293 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Yenilmez, B. et al. Paradoxical activation of transcription factor SREBP1c and de novo lipogenesis by hepatocyte-selective ATP-citrate lyase depletion in obese mice. J. Biol. Chem. 298, 102401 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. Scholtens, D. M. et al. Metabolomics reveals broad-scale metabolic perturbations in hyperglycemic mothers during pregnancy. Diabetes Care 37, 158–166 (2014).

    Article  CAS  PubMed  Google Scholar 

  44. Parry, T. L. et al. Untargeted metabolomics analysis of ischemia-reperfusion-injured hearts ex vivo from sedentary and exercise-trained rats. Metabolomics 14, 8 (2018).

    Article  PubMed  Google Scholar 

  45. Liu, Y. et al. Metabolomic and genetic associations with insulin resistance in pregnancy. Diabetologia 63, 1783–1795 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Gooding, J. R. et al. Adenylosuccinate is an insulin secretagogue derived from glucose-induced purine metabolism. Cell Rep. 13, 157–167 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Baht, G. S. et al. Meteorin-like facilitates skeletal muscle repair through a Stat3/IGF-1 mechanism. Nat. Metab. 2, 278–289 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Lee, D. E. et al. Meteorin-like is an injectable peptide that can enhance regeneration in aged muscle through immune-driven fibro/adipogenic progenitor signaling. Nat. Commun. 13, 7613 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Lee, D. E. et al. Mitochondrial mRNA translation initiation contributes to oxidative metabolism in the myocardia of aged, obese mice. Exp. Gerontol. 121, 62–70 (2019).

    Article  CAS  PubMed  Google Scholar 

  50. Lee, D. E. et al. Translational machinery of mitochondrial mRNA is promoted by physical activity in Western diet-induced obese mice. Acta Physiol. (Oxf.) 218, 167–177 (2016).

    Article  CAS  PubMed  Google Scholar 

Download references

Acknowledgements

This work was supported by the following awards: National Institutes of Health (NIH)/National Institute on Aging (NIA) grant K01AG056664 (J.P.W.), grant R21AG065943 (J.P.W.), NIH training grant T32HL007057 (D.E.L.), grant K01AG088232 (D.E.L.), Borden’s Scholar Award (D.E.L.), NIH/National Institute of Dental and Craniofacial Research (NIDCR) grant K08DE031029 (L.K.M.), NIH/National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) grant R01DK132819 (S.K.), NIH grant DK046092 (C.B.N.) and Duke Aging Center/Pepper Center grant P30-AG028716 (J.R.B.). The metabolomic and metabolic flux analyses reported here were supported by funding from the North Carolina Diabetes Research Center NIDDK grant P30DK124723 (C.B.N.). The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript.

Author information

Authors and Affiliations

  1. Sarah W. Stedman Nutrition and Metabolism Center and Duke Molecular Physiology Institute, Duke University School of Medicine, Durham, NC, USA

    David E. Lee, Lauren K. McKay, Akshay Bareja, Wentao He, Demitrius A. Hill, James R. Bain, Guo-Fang Zhang, Christopher B. Newgard & James P. White

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

    David E. Lee, JiaCheng Yang & Shihuan Kuang

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

    David E. Lee, Akshay Bareja, James R. Bain, Guo-Fang Zhang, Christopher B. Newgard & James P. White

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

    David E. Lee, James R. Bain & James P. White

  5. Department of Oral and Craniofacial Molecular Biology, Virginia Commonwealth University, Richmond, VA, USA

    Lauren K. McKay

  6. Department of Biomedical Sciences, Adams School of Dentistry, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA

    Lauren K. McKay

  7. Department of Pathology, Duke University School of Medicine, Durham, NC, USA

    Shihuan Kuang

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

    Shihuan Kuang

  9. Department of Pharmacology and Cancer Biology, Duke University School of Medicine, Durham, NC, USA

    Christopher B. Newgard

Authors
  1. David E. Lee
    View author publications

    Search author on:PubMed Google Scholar

  2. Lauren K. McKay
    View author publications

    Search author on:PubMed Google Scholar

  3. Akshay Bareja
    View author publications

    Search author on:PubMed Google Scholar

  4. JiaCheng Yang
    View author publications

    Search author on:PubMed Google Scholar

  5. Wentao He
    View author publications

    Search author on:PubMed Google Scholar

  6. Demitrius A. Hill
    View author publications

    Search author on:PubMed Google Scholar

  7. James R. Bain
    View author publications

    Search author on:PubMed Google Scholar

  8. Shihuan Kuang
    View author publications

    Search author on:PubMed Google Scholar

  9. Guo-Fang Zhang
    View author publications

    Search author on:PubMed Google Scholar

  10. Christopher B. Newgard
    View author publications

    Search author on:PubMed Google Scholar

  11. James P. White
    View author publications

    Search author on:PubMed Google Scholar

Contributions

D.E.L., J.P.W., J.R.B., G.-F.Z. and C.B.N. conceived and/or designed experiments. D.E.L., L.K.M., A.B., W.H., D.H., J.R.B., J.Y., G.-F.Z. and S.K. acquired, analyzed and/or interpreted data. D.E.L., L.K.M. and J.P.W. drafted the paper. D.E.L. and J.P.W. revised the paper. All authors approved the final version.

Corresponding author

Correspondence to James P. White.

Ethics declarations

Competing interests

C.B.N. is a paid consultant for Eli Lilly, Axcella Health, Boehringer Ingelheim and Sigilon, which were not involved and have no competing interest in the research described in this paper. The other authors declare no competing interests.

Peer review

Peer review information

Nature Aging thanks the anonymous, reviewer(s) for their contribution to the peer review of this work. Peer reviewer reports are available.

Additional information

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

Supplementary information

Supplementary Information (download PDF )

Supplementary Figs. 1−7 and unprocessed scan for Supplementary Fig. 4a.

Reporting Summary (download PDF )

Peer Review File (download PDF )

Source data

Source Data Fig. 1 (download XLSX )

Statistical source data.

Source Data Fig. 2 (download XLSX )

Statistical source data.

Source Data Fig. 3 (download XLSX )

Statistical source data.

Source Data Fig. 4 (download XLSX )

Statistical source data.

Source Data Fig. 5 (download XLSX )

Statistical source data.

Source Data Fig. 6 (download XLSX )

Statistical source data.

Source Data Fig. 7 (download TIF )

Unprocessed western blot.

Source Data Fig. 8 (download TIF )

Unprocessed western blot.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Lee, D.E., McKay, L.K., Bareja, A. et al. Glutamine-driven reductive TCA cycle metabolism supports aged muscle stem cell function via de novo lipogenesis. Nat Aging (2026). https://doi.org/10.1038/s43587-026-01120-3

Download citation

  • Received:

  • Accepted:

  • Published:

  • Version of record:

  • DOI: https://doi.org/10.1038/s43587-026-01120-3

Search

Advanced search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing