Glucose feeds the TCA cycle via circulating lactate

  • Nature volume 551, pages 115118 (02 November 2017)
  • doi:10.1038/nature24057
  • Download Citation
Published online:


Mammalian tissues are fuelled by circulating nutrients, including glucose, amino acids, and various intermediary metabolites. Under aerobic conditions, glucose is generally assumed to be burned fully by tissues via the tricarboxylic acid cycle (TCA cycle) to carbon dioxide. Alternatively, glucose can be catabolized anaerobically via glycolysis to lactate, which is itself also a potential nutrient for tissues1 and tumours2,3,4,5. The quantitative relevance of circulating lactate or other metabolic intermediates as fuels remains unclear. Here we systematically examine the fluxes of circulating metabolites in mice, and find that lactate can be a primary source of carbon for the TCA cycle and thus of energy. Intravenous infusions of 13C-labelled nutrients reveal that, on a molar basis, the circulatory turnover flux of lactate is the highest of all metabolites and exceeds that of glucose by 1.1-fold in fed mice and 2.5-fold in fasting mice; lactate is made primarily from glucose but also from other sources. In both fed and fasted mice, 13C-lactate extensively labels TCA cycle intermediates in all tissues. Quantitative analysis reveals that during the fasted state, the contribution of glucose to tissue TCA metabolism is primarily indirect (via circulating lactate) in all tissues except the brain. In genetically engineered lung and pancreatic cancer tumours in fasted mice, the contribution of circulating lactate to TCA cycle intermediates exceeds that of glucose, with glutamine making a larger contribution than lactate in pancreatic cancer. Thus, glycolysis and the TCA cycle are uncoupled at the level of lactate, which is a primary circulating TCA substrate in most tissues and tumours.

  • Subscribe to Nature for full access:



Additional access options:

Already a subscriber?  Log in  now or  Register  for online access.


  1. 1.

    Lactate kinetics in human tissues at rest and during exercise. Acta Physiol. (Oxf.) 199, 499–508 (2010)

  2. 2.

    et al. Targeting lactate-fueled respiration selectively kills hypoxic tumor cells in mice. J. Clin. Invest. 118, 3930–3942 (2008)

  3. 3.

    et al. Catabolism of exogenous lactate reveals it as a legitimate metabolic substrate in breast cancer. PLoS One 8, e75154 (2013)

  4. 4.

    Pyruvate into lactate and back: from the Warburg effect to symbiotic energy fuel exchange in cancer cells. Radiother. Oncol. 92, 329–333 (2009)

  5. 5.

    et al. Metabolic heterogeneity in human lung tumors. Cell 164, 681–694 (2016)

  6. 6.

    et al. MMMDB: mouse multiple tissue metabolome database. Nucleic Acids Res. 40, D809–D814 (2012)

  7. 7.

    & Using isotope tracers to study metabolism: application in mouse models. Metab. Eng. 6, 25–35 (2004)

  8. 8.

    , & Metabolic interrelations of glucose and lactate in sheep. Biochem. J. 88, 243–248 (1963)

  9. 9.

    , & Turnover of lactic acid in normal and diabetic dogs calculated by two tracer methods. Am. J. Physiol. 212, 1179–1184 (1967)

  10. 10.

    & Determination of lactate kinetics in the human analysis of data from single injection vs. continuous infusion methods. Proc. Soc. Exp. Biol. Med. 139, 1002–1006 (1972)

  11. 11.

    , , , & Metabolism of 3H- and 14C-labelled lactate in starved rats. Biochem. J. 194, 525–540 (1981)

  12. 12.

    , , & The determination of lactate turnover in vivo with 3H- and 14C-labelled lactate. The significance of sites of tracer administration and sampling. Biochem. J. 194, 513–524 (1981)

  13. 13.

    & Sample site selection for tracer studies applying a unidirectional circulatory approach. Am. J. Physiol. 253, E173–E178 (1987)

  14. 14.

    , , , & Role of the circulation in measurement of lactate turnover rate. J. Appl. Physiol. 70, 1469–1476 (1991)

  15. 15.

    Sites of infusion and sampling for measurement of rates of production in steady state. Am. J. Physiol. 263, E817–E822 (1992)

  16. 16.

    , & V–A and A–V modes in whole body and regional kinetics: domain of validity from a physiological model. Am. J. Physiol. 263, E597–E606 (1992)

  17. 17.

    Metabolic networks in motion: 13C-based flux analysis. Mol. Syst. Biol. 2, 62 (2006)

  18. 18.

    et al. A roadmap for interpreting 13C metabolite labeling patterns from cells. Curr. Opin. Biotechnol. 34, 189–201 (2015)

  19. 19.

    , & Evaluation of 13C isotopic tracers for metabolic flux analysis in mammalian cells. J. Biotechnol. 144, 167–174 (2009)

  20. 20.

    On the origin of cancer cells. Science 123, 309–314 (1956)

  21. 21.

    , & Understanding the Warburg effect: the metabolic requirements of cell proliferation. Science 324, 1029–1033 (2009)

  22. 22.

    et al. Environment impacts the metabolic dependencies of Ras-driven non-small cell lung cancer. Cell Metab. 23, 517–528 (2016)

  23. 23.

    et al. Tissue of origin dictates branched-chain amino acid metabolism in mutant Kras-driven cancers. Science 353, 1161–1165 (2016)

  24. 24.

    in Circulation, Respiration, and Metabolism (ed. ) 208–218 (Springer, 1985)

  25. 25.

    et al. Evidence for a stromal-epithelial “lactate shuttle” in human tumors: MCT4 is a marker of oxidative stress in cancer-associated fibroblasts. Cell Cycle 10, 1772–1783 (2011)

  26. 26.

    Cell–cell and intracellular lactate shuttles. J. Physiol. 587, 5591–5600 (2009)

  27. 27.

    & Lactate shuttles at a glance: from physiological paradigms to anti-cancer treatments. Dis. Model. Mech. 4, 727–732 (2011)

  28. 28.

    Lactate metabolism: a new paradigm for the third millennium. J. Physiol. 558, 5–30 (2004)

  29. 29.

    A lactatic perspective on metabolism. Med. Sci. Sports Exerc. 40, 477–485 (2008)

  30. 30.

    et al. The extracellular redox state modulates mitochondrial function, gluconeogenesis, and glycogen synthesis in murine hepatocytes. PLoS One 10, e0122818 (2015)

  31. 31.

    et al. Enhanced fatty acid flux triggered by adiponectin overexpression. Endocrinology 153, 113–122 (2012)

  32. 32.

    , & Eine einfache Technik der extrem schnellen Abkühlung größerer Gewebestücke. Pflugers Arch. Gesamte Physiol. Menschen Tiere 270, 399–412 (1960)

  33. 33.

    et al. Preinvasive and invasive ductal pancreatic cancer and its early detection in the mouse. Cancer Cell 4, 437–450 (2003)

  34. 34.

    et al. Both p16(Ink4a) and the p19(Arf)–p53 pathway constrain progression of pancreatic adenocarcinoma in the mouse. Proc. Natl Acad. Sci. USA 103, 5947–5952 (2006)

  35. 35.

    , & Metabolomic analysis and visualization engine for LC–MS data. Anal. Chem. 82, 9818–9826 (2010)

  36. 36.

    et al. An isotope-dilution, GC–MS assay for formate and its application to human and animal metabolism. Amino Acids 46, 1885–1891 (2014)

Download references


We thank C. Wright for providing the Ptf1a-cre mice; M. Sander for help and advice; and the members of the Rabinowitz laboratory and J. Baur, Z. Arany, and M. Lazar for scientific discussions. This work was supported by NIH grants 1DP1DK113643, R01 CA163591, R01 CA130893, K22 CA190521, R01 CA186043, R35 CA197699, R50 CA211437, P30 CA072720 (Metabolomics Shared Resource, Rutgers Cancer Institute of New Jersey), and 5P30 DK019525. In addition, it was supported by a Stand Up To Cancer–Cancer Research UK–Lustgarten Foundation Pancreatic Cancer Dream Team Research Grant (grant number: SU2C-AACR-DT-20-16). S.H. is a Merck Fellow of the Life Sciences Research Foundation. C.J. is a postdoctoral fellow of the American Diabetes Association.

Author information


  1. Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, New Jersey 08544, USA

    • Sheng Hui
    • , Jonathan M. Ghergurovich
    • , Raphael J. Morscher
    • , Cholsoon Jang
    • , Xin Teng
    • , Wenyun Lu
    •  & Joshua D. Rabinowitz
  2. Department of Chemistry, Princeton University, Princeton, New Jersey 08544, USA

    • Sheng Hui
    • , Raphael J. Morscher
    • , Cholsoon Jang
    • , Xin Teng
    • , Wenyun Lu
    •  & Joshua D. Rabinowitz
  3. Department of Molecular Biology, Princeton University, Princeton, New Jersey 08544, USA

    • Jonathan M. Ghergurovich
  4. Departments of Pharmacology and Medicine, Moores Cancer Center, University of California San Diego School of Medicine, La Jolla, California 92093, USA

    • Lourdes A. Esparza
    •  & Tannishtha Reya
  5. Rutgers Cancer Institute of New Jersey, New Brunswick, New Jersey 08903, USA

    • Le Zhan
    • , Jessie Yanxiang Guo
    • , Eileen White
    •  & Joshua D. Rabinowitz
  6. Department of Molecular Biology and Biochemistry, Rutgers University, Piscataway, New Jersey, 08854, USA

    • Le Zhan
    •  & Eileen White
  7. Department of Medicine, Rutgers Robert Wood Johnson Medical School, New Brunswick, New Jersey 08901, USA

    • Jessie Yanxiang Guo
  8. Department of Chemical Biology, Rutgers Ernest Mario School of Pharmacy, Piscataway, New Jersey 08854, USA

    • Jessie Yanxiang Guo


  1. Search for Sheng Hui in:

  2. Search for Jonathan M. Ghergurovich in:

  3. Search for Raphael J. Morscher in:

  4. Search for Cholsoon Jang in:

  5. Search for Xin Teng in:

  6. Search for Wenyun Lu in:

  7. Search for Lourdes A. Esparza in:

  8. Search for Tannishtha Reya in:

  9. Search for Le Zhan in:

  10. Search for Jessie Yanxiang Guo in:

  11. Search for Eileen White in:

  12. Search for Joshua D. Rabinowitz in:


S.H., R.J.M., and J.D.R. came up with the general approach. S.H., J.M.G., R.J.M., and C.J. designed and performed the wild-type mouse isotope tracing studies. J.M.G., L.A.E., and T.R. designed and performed the pancreatic cancer GEMM studies. X.T., L.Z., J.Y.G., and E.W. designed and performed the lung cancer GEMM studies. W.L. performed LC–MS analysis. S.H. and J.D.R. developed the mathematical models. S.H. and J.D.R. wrote the paper with help from all authors.

Competing interests

The authors declare no competing financial interests.

Corresponding author

Correspondence to Joshua D. Rabinowitz.

Reviewer Information Nature thanks S. Kempa, M. Yuneeva and the other anonymous reviewer(s) for their contribution to the peer review of this work.

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

Extended data

Supplementary information

PDF files

  1. 1.

    Reporting Summary

  2. 2.

    Supplementary Information

    This file contains Supplementary Notes 1-4, including Supplementary Figures and Tables.


By submitting a comment you agree to abide by our Terms and Community Guidelines. If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate.