Glucose feeds the TCA cycle via circulating lactate

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Abstract

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.

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Figure 1: Turnover fluxes of circulating metabolites in fasting mice.
Figure 2: In fasting mice, glucose labels TCA intermediates through circulating lactate in all tissues except the brain.
Figure 3: In fed mice, in all tissues except brain and muscle, glucose labels TCA intermediates mostly through circulating lactate.
Figure 4: Circulating lactate is a primary TCA substrate in tumours.

References

  1. 1

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

  2. 2

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

  3. 3

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

  4. 4

    Feron, O. 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

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

  6. 6

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

  7. 7

    McCabe, B. J. & Previs, S. F. Using isotope tracers to study metabolism: application in mouse models. Metab. Eng. 6, 25–35 (2004)

  8. 8

    Annison, E. F., Lindsay, D. B. & White, R. R. Metabolic interrelations of glucose and lactate in sheep. Biochem. J. 88, 243–248 (1963)

  9. 9

    Forbath, N., Kenshole, A. B. & Hetenyi, G. Jr. Turnover of lactic acid in normal and diabetic dogs calculated by two tracer methods. Am. J. Physiol. 212, 1179–1184 (1967)

  10. 10

    Searle, G. L. & Cavalieri, R. R. 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

    Okajima, F., Chenoweth, M., Rognstad, R., Dunn, A. & Katz, J. Metabolism of 3H- and 14C-labelled lactate in starved rats. Biochem. J. 194, 525–540 (1981)

  12. 12

    Katz, J., Okajima, F., Chenoweth, M. & Dunn, A. 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

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

  14. 14

    Binder, N. D., Day, D., Battaglia, F. C., Meschia, G. & Sparks, J. W. Role of the circulation in measurement of lactate turnover rate. J. Appl. Physiol. 70, 1469–1476 (1991)

  15. 15

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

  16. 16

    Sacca, L., Toffolo, G. & Cobelli, C. 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

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

  18. 18

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

  19. 19

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

  20. 20

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

  21. 21

    Vander Heiden, M. G., Cantley, L. C. & Thompson, C. B. Understanding the Warburg effect: the metabolic requirements of cell proliferation. Science 324, 1029–1033 (2009)

  22. 22

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

  23. 23

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

  24. 24

    Brooks, G. in Circulation, Respiration, and Metabolism (ed. Gilles, R. ) 208–218 (Springer, 1985)

  25. 25

    Whitaker-Menezes, D. 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

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

  27. 27

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

  28. 28

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

  29. 29

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

  30. 30

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

  31. 31

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

  32. 32

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

  33. 33

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

  34. 34

    Bardeesy, N. 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

    Melamud, E., Vastag, L. & Rabinowitz, J. D. Metabolomic analysis and visualization engine for LC–MS data. Anal. Chem. 82, 9818–9826 (2010)

  36. 36

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

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Acknowledgements

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

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.

Correspondence to Joshua D. Rabinowitz.

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The authors declare no competing financial interests.

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

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Extended data figures and tables

Extended Data Figure 1 Abundant metabolites in mouse plasma.

Metabolites (n = 39) with reported concentration greater than 30 μM in mouse plasma. Left bar graph shows those >100 μM (n = 17) and right bar graph those between 30 μM and 100 μM (n = 22). Most of the data are from the Mouse Multiple Tissue Metabolome Database (http://mmdb.iab.keio.ac.jp) (n = 2 mice), except for glucose (n = 6 mice), acetate (n = 3 mice), and glycerol (n = 3 mice), whose concentrations were determined in this study. The metabolites shown with red bars (n = 30) are those whose turnover fluxes have been determined (Table 1). Values are mean ± s.d. The concentration cut off of 30 μM was calculated using equation (1) where we used a cardiac output of 0.5 ml g−1 min−1 (see Supplementary Note 1 for references) and a turnover flux equating to 10% of glucose Fcirc.

Extended Data Figure 2 Determination of turnover flux with isotopic tracing.

a, Illustration of the mouse infusion experimental setup. b, Relative total ion counts (TICs) of serum glucose and lactate during 13C-glucose infusion (individual mouse data are shown for three mice for each condition). c, Relative TICs of serum glucose and lactate during 13C-lactate infusion. d, Glucose (n = 16 for 1× and n = 6 for 0.5×; P = 0.61) and lactate (n = 18 for 1× and n = 6 for 0.5×; P = 0.50) turnover fluxes determined using two different infusion rates (mean ± s.d.). P values were determined by a two-tailed unpaired Student’s t-test. The 1× infusion rates are listed in Supplementary Table 1. Source data

Extended Data Figure 3 Measurement of lactate turnover flux.

a, The dependence of lactate turnover flux (Fcirc) on the exchanging flux (forward (Jf) and reverse (Jr)) between circulating lactate and tissue pyruvate. Rapid exchanging flux does not lead to infinitely fast lactate turnover flux. Instead, it leads to a lactate turnover flux approaching the net production rate of pyruvate (Jg), as illustrated in lower panel. Jt is the pyruvate flux going to the TCA cycle. See Supplementary Note 2 for derivation. b, Spatial dependence of tracer enrichment. Labelling (L(x)) decreases in an exponential manner across a tissue capillary bed (shown schematically in the shading of the cylinder representing tissue) with the extent of arteriovenous difference in tracer labelling depending on the metabolic transformation rate (k) relative to the volumetric blood flow rate (q = Q/V; V is tissue volume) as shown in the equation. La and Lv are labelled fraction in the artery and the vein, respectively. See Supplementary Note 1. c, Lactate labelled fraction in arterial (carotid artery; n = 8 mice, mean ± s.d.) and venous (tail vein and vena cava; n = 3 mice, mean ± s.d.) serum samples, and in tail snip serum sample (n = 3 mice, mean ± s.d.). For comparison of tail snip to vena cava only, samples were collected under anaesthesia to allow access to the inferior vena cava. The difference in lactate labelling between the carotid artery and tail snip can be used to calculate lactate Fcirc using equation (3). With Q = 0.53 ± 0.11 ml min−1 g−1 and C = 2.5 ± 0.2 mM, together with , we get lactate Fcirc as 398 ± 88 nmol min−1 g−1 in the fasted state, which is comparable to the value of 374 ± 112 nmol min−1 g−1 obtained with equation (2). See Supplementary Note 1 for details. Source data

Extended Data Figure 4 Isotopic labelling of tissue TCA intermediates reaches steady state after 2.5-h infusion of 13C-glucose.

a, Comparison of normalized labelling of tissue malate after 2.5 h (n = 5 mice; mean ± s.d.) and after 5 h of [U-13C]glucose infusion (n = 3 mice; mean ± s.d.). P values were determined by an unpaired Student’s t-test, corrected for multiple comparisons using the Holm–Sidak method. Normalized labelling is the fraction of 13C atoms in a metabolite divided by the fraction of 13C atoms in serum glucose. None of the differences are significant (P > 0.14 for the brain and liver, and P > 0.98 for other tissues). b, Comparison of normalized labelling of tissue succinate after 2.5 h (n = 5 mice; mean ± s.d.) and after 5 h of [U-13C]glucose infusion (n = 3 mice; mean ± s.d.). None of the differences are significant (P > 0.18 for the brain and liver, and P > 0.85 for other tissues). Source data

Extended Data Figure 5 Isotope labelling of central carbon metabolites by 13C-glucose and 13C-lactate.

a, Normalized labelling by 13C-glucose in fasting mice (n = 3 for pyruvate, 2-oxoglutarate, and 3-phosphoglycerate, n = 4 for alanine, and n = 5 for all other metabolites; mean ± s.d.). b, Normalized labelling by 13C-lactate in fasting mice (n = 3 for 3-phosphoglycerate and n = 4 for all other metabolites; mean ± s.d.). n indicates the number of mice. For the lactate tracer studies, venous serum and tissue labelling are normalized to the arterial serum lactate labelling. Note that citrate, malate and succinate in tissues turn over sufficiently slowly that labelling is robust to the small (<90 s) delay between euthanizing the mouse and tissue harvesting. This delay may, however, result in erroneous measurements for tissue lactate, pyruvate and glycolytic intermediates. Analyses in the main text are limited to the better validated measurements of serum metabolites and tissue TCA intermediates. With this caveat in mind, it is nevertheless intriguing that lactate labelling varies markedly across tissues. After labelled glucose infusion, lactate labelling is highest in the brain, consistent with its use of glucose as a major substrate. In the kidneys lactate is strongly labelled after glucose infusion, even though TCA intermediates are more labelled after lactate infusion. A potential explanation involves tissue heterogeneity; for example, the presence both of glycolytic cells that make lactate from circulating glucose and of oxidative cells that make TCA intermediates from circulating lactate. In other tissues, such as liver, tissue lactate labelling is far below circulating lactate and very similar to TCA labelling; this may reflect mixing of carbon between lactate and TCA intermediates via gluconeogenesis or pyruvate cycling. Another factor diluting tissue lactate labelling is that, as blood passes through tissue, owing to the rapid exchange between tissue and circulating lactate, the circulating lactate loses its labelling, as is evident from the lactate arteriovenous labelling difference. Source data

Extended Data Figure 6 Concentrations of succinate, malate, and citrate in mouse plasma and tissues.

Unlike citrate, succinate and malate have substantially higher concentrations in tissues than in the bloodstream, thus making them a suitable readout for the tissue TCA cycle. Data are from the Mouse Multiple Tissue Metabolome Database (http://mmdb.iab.keio.ac.jp). Values are mean ± s.d. (n = 2 mice). Note that the y-axis is a logarithmic scale.

Extended Data Figure 7 Glucose feeds the TCA cycle via circulating lactate in anaesthetized mice.

a, Turnover fluxes of glucose (n = 4 mice, mean ± s.d.) and lactate (n = 3 mice, mean ± s.d.) in anaesthetized mice. b, Normalized labelling of serum glucose, lactate, and glutamine in anaesthetized mice with 13C-glucose infusion (n = 4 mice; mean ± s.d.) and 13C-lactate infusion (n = 3 mice; mean ± s.d.). c, Steady-state whole-body flux model summarizing glucose and lactate interconversion and their feeding to the TCA (see Supplementary Note 4). Values are mean ± s.e.m. Source data

Extended Data Figure 8 Normalized labelling of serum glutamine, glucose, and lactate, and of tissue TCA intermediates in fed mice.

a, 13C-lactate infusion (n = 5 mice). b 13C-glutamine infusion (n = 3 mice). c, 13C-glucose infusion (n = 4 mice). Bars are mean ± s.d. Source data

Extended Data Figure 9 Scatter plots of normalized labelling of TCA intermediates in the three types of tumours by 13C-glucose versus that by 13C-lactate.

a, KrasLSL-G12D/+Trp53−/− (KP) non-small cell lung cancer (n = 3 for 13C-glucose and 13C-lactate infusions, and n = 4 for 13C-glutamine infusion). b, KrasLSL-G12D/+Stk11−/− (KL) lung cancer (n = 3 mice for infusion of each tracer). c, KrasLSL-G12D/+Trp53−/−Ptf1aCRE/+ (KPf/fC) pancreatic ductal adenocarcinoma (n = 4 for 13C-glucose infusion, n = 3 for 13C-lactate and 13C-glutamine infusions). Values are mean ± s.d. Data are from Fig. 4a–c. The solid line represents the expected labelling by 13C-glucose assuming that glucose feeds the TCA cycle solely through circulating lactate. The dashed line indicates the expected labelling by 13C-lactate, assuming that lactate feeds the TCA cycle solely through circulating glucose. Source data

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Hui, S., Ghergurovich, J., Morscher, R. et al. Glucose feeds the TCA cycle via circulating lactate. Nature 551, 115–118 (2017) doi:10.1038/nature24057

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