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Quantitative flux analysis in mammals

Abstract

Altered metabolic activity contributes to the pathogenesis of a number of diseases, including diabetes, heart failure, cancer, fibrosis and neurodegeneration. These diseases, and organismal metabolism more generally, are only partially recapitulated by cell culture models. Accordingly, it is important to measure metabolism in vivo. Over the past century, researchers studying glucose homeostasis have developed strategies for the measurement of tissue-specific and whole-body metabolic activity (pathway fluxes). The power of these strategies has been augmented by recent advances in metabolomics technologies. Here, we review techniques for measuring metabolic fluxes in intact mammals and discuss how to analyse and interpret the results. In tandem, we describe important findings from these techniques, and suggest promising avenues for their future application. Given the broad importance of metabolism to health and disease, more widespread application of these methods holds the potential to accelerate biomedical progress.

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Fig. 1: Mammalian metabolic fluxes.
Fig. 2: Measuring net tissue fluxes using arteriovenous sampling.
Fig. 3: Measuring circulatory turnover flux using tracer infusion.
Fig. 4: Pre-steady-state versus steady-state measurements of tissue metabolite labelling.
Fig. 5: Measuring sources of tissue metabolites using tracer infusion.

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References

  1. Fenn, J. B., Mann, M., Meng, C. K., Wong, S. F. & Whitehouse, C. M. Electrospray ionization—principles and practice. Mass Spectrom. Rev. 9, 37–70 (1990).

    Article  CAS  Google Scholar 

  2. Tanaka, K. et al. Protein and polymer analyses up to m/z 100 000 by laser ionization time-of-flight mass spectrometry. Rapid Commun. Mass Spectrom. 2, 151–153 (1988).

    Article  CAS  Google Scholar 

  3. Wolfe, R. R. Tracers in Metabolic Research: Radioisotope and Stable Isotope/Mass Spectometry Methods (A.R. Liss, 1984).

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

    Article  CAS  PubMed  Google Scholar 

  5. Fernández-García, J., Altea-Manzano, P., Pranzini, E. & Fendt, S.-M. Stable isotopes for tracing mammalian-cell metabolism in vivo. Trends Biochem. Sci. 45, 185–201 (2020).

    Article  PubMed  CAS  Google Scholar 

  6. Jain, M. et al. Metabolite profiling identifies a key role for glycine in rapid cancer cell proliferation. Science 336, 1040–1044 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Frauwirth, K. A. et al. The CD28 signaling pathway regulates glucose metabolism. Immunity 16, 769–777 (2002).

    Article  CAS  PubMed  Google Scholar 

  8. Felig, P., Pozefsk, T., Marlis, E. & Cahill, G. F. Alanine: key role in gluconeogenesis. Science 167, 1003–1004 (1970).

    Article  CAS  PubMed  Google Scholar 

  9. Ivanisevic, J. et al. Arteriovenous blood metabolomics: a readout of intra-tissue metabostasis. Sci. Rep. 5, 12757 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Jang, C. et al. Metabolite exchange between mammalian organs quantified in pigs. Cell Metab. 30, 594–606.e3 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Owen, O. E. et al. Brain metabolism during fasting. J. Clin. Invest. 46, 1589–1595 (1967).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Wilmore, D. W., Aulick, L. H., Mason, A. D. & Pruitt, B. A. Influence of the burn wound on local and systemic responses to injury. Ann. Surg. 186, 444–456 (1977).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Wilmore, D. W. et al. Effect of injury and infection on visceral metabolism and circulation. Ann. Surg. 192, 491–504 (1980).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Wahren, J., Felig, P., Ahlborg, G. & Jorfeldt, L. Glucose metabolism during leg exercise in man. J. Clin. Invest. 50, 2715–2725 (1971).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Murashige, D. et al. Comprehensive quantification of fuel use by the failing and nonfailing human heart. Science 370, 364–368 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Rennie, M. J. et al. Effect of exercise on protein turnover in man. Clin. Sci. 61, 627–639 (1981).

    Article  CAS  Google Scholar 

  17. Taylor, R. et al. Direct assessment of liver glycogen storage by 13C nuclear magnetic resonance spectroscopy and regulation of glucose homeostasis after a mixed meal in normal subjects. J. Clin. Invest. 97, 126–132 (1996).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Wagenmakers, A. J. M. Tracers to investigate protein and amino acid metabolism in human subjects. Proc. Nutr. Soc. 58, 987–1000 (1999).

    Article  CAS  PubMed  Google Scholar 

  19. Ayala, J. E., Bracy, D. P., McGuinness, O. P. & Wasserman, D. H. Considerations in the design of hyperinsulinemic–euglycemic clamps in the conscious mouse. Diabetes 55, 390–397 (2006).

    Article  CAS  PubMed  Google Scholar 

  20. Hundal, R. S. et al. Mechanism by which metformin reduces glucose production in type 2 diabetes. Diabetes 49, 2063–2069 (2000).

    Article  CAS  PubMed  Google Scholar 

  21. Lee-Young, R. S. et al. Skeletal muscle AMP-activated protein kinase is essential for the metabolic response to exercise in vivo. J. Biol. Chem. 284, 23925–23934 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Laughlin, M. H. & Armstrong, R. B. Muscular blood flow distribution patterns as a function of running speed in rats. Am. J. Physiol. Heart Circ. Physiol. 243, H296–H306 (1982).

    Article  CAS  Google Scholar 

  23. Sjøberg, K. A., Rattigan, S., Hiscock, N., Richter, E. A. & Kiens, B. A new method to study changes in microvascular blood volume in muscle and adipose tissue: real-time imaging in humans and rat. Am. J. Physiol. Heart Circ. Physiol. 301, H450–H458 (2011).

    Article  PubMed  CAS  Google Scholar 

  24. Wei, K. et al. Quantification of myocardial blood flow with ultrasound-induced destruction of microbubbles administered as a constant venous infusion. Circulation 97, 473–483 (1998).

    Article  CAS  PubMed  Google Scholar 

  25. Brown, R. P., Delp, M. D., Lindstedt, S. L., Rhomberg, L. R. & Beliles, R. P. Physiological parameter values for physiologically based pharmacokinetic models. Toxicol. Ind. Health 13, 407–484 (1997).

    Article  CAS  PubMed  Google Scholar 

  26. Berne, R. M. Regulation of coronary blood flow. Physiol. Rev. 44, 1–29 (1964).

    Article  CAS  PubMed  Google Scholar 

  27. Høst, U. et al. Haemodynamic effects of eating: the role of meal composition. Clin. Sci. 90, 269–276 (1996).

    Article  Google Scholar 

  28. Lang, C. H., Bagby, G. J., Ferguson, J. L. & Spitzer, J. J. Cardiac output and redistribution of organ blood flow in hypermetabolic sepsis. Am. J. Physiol. Regul. Integr. Comp. Physiol. 246, R331–R337 (1984).

    Article  CAS  Google Scholar 

  29. Tabata, H., Kitamura, T. & Nagamatsu, N. Comparison of effects of restraint, cage transportation, anaesthesia and repeated bleeding on plasma glucose levels between mice and rats. Lab. Anim. 32, 143–148 (1998).

    Article  CAS  PubMed  Google Scholar 

  30. Ensinger, H., Weichel, T., Lindner, K. H., Grünert, A. & Ahnefeld, F. W. Effects of norepinephrine, epinephrine, and dopamine infusions on oxygen consumption in volunteers. Crit. Care Med. 21, 1502–1508 (1993).

    Article  CAS  PubMed  Google Scholar 

  31. Ghosal, S. et al. Mouse handling limits the impact of stress on metabolic endpoints. Physiol. Behav. 150, 31–37 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Schoenheimer, R. & Rittenberg, D. Deuterium as an indicator in the study of intermediary metabolism. 3. The role of the fat tissues. J. Biol. Chem. 111, 175–181 (1935).

    Article  Google Scholar 

  33. Hui, S. et al. Glucose feeds the TCA cycle via circulating lactate. Nature 551, 115–118 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  34. Searle, G. L., Strisower, E. H. & Chaikoff, I. L. Glucose pool and glucose space in the normal and diabetic dog. Am. J. Physiol. 176, 190–194 (1954).

    Article  CAS  PubMed  Google Scholar 

  35. Searle, G. L., Strisower, E. H. & Chaikoff, I. L. Determination of rates of glucose oxidation in normal and diabetic dogs by a technique involving continuous Injection of C14-glucose. Am. J. Physiol. 185, 589–594 (1956).

    Article  CAS  PubMed  Google Scholar 

  36. Ayala, J. E. et al. Standard operating procedures for describing and performing metabolic tests of glucose homeostasis in mice. Dis. Models Mech. 3, 525–534 (2010).

    Article  CAS  Google Scholar 

  37. Sherwin, R. S. et al. A model of the kinetics of insulin in man. J. Clin. Invest. 53, 1481–1492 (1974).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Stanley, W. C. et al. Lactate extraction during net lactate release in legs of humans during exercise. J. Appl. Physiol. 60, 1116–1120 (1986).

    Article  CAS  PubMed  Google Scholar 

  39. 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).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. Donovan, C. M. & Brooks, G. A. Endurance training affects lactate clearance, not lactate production. Am. J. Physiol. Endocrinol. Metab. 244, E83–E92 (1983).

    Article  CAS  Google Scholar 

  41. Brooks, G. A. The science and translation of lactate shuttle theory. Cell Metab. 27, 757–785 (2018).

    Article  CAS  PubMed  Google Scholar 

  42. Bergman, B. C. et al. Muscle net glucose uptake and glucose kinetics after endurance training in men. Am. J. Physiol. Endocrinol. Metab. 277, E81–E92 (1999).

    Article  CAS  Google Scholar 

  43. Bergman, B. C. et al. Active muscle and whole body lactate kinetics after endurance training in men. J. Appl. Physiol. 87, 1684–1696 (1999).

    Article  CAS  PubMed  Google Scholar 

  44. Sahlin, K. Lactate production cannot be measured with tracer techniques. Am. J. Physiol. Endocrinol. Metab. 252, E439–E440 (1987).

    Article  CAS  Google Scholar 

  45. Donnelly, K. L. et al. Sources of fatty acids stored in liver and secreted via lipoproteins in patients with nonalcoholic fatty liver disease. J. Clin. Invest. 115, 1343–1351 (2005).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Landau, B. R. et al. Glycerol production and utilization in humans: sites and quantitation. Am. J. Physiol. Endocrinol. Metab. 271, E1110–E1117 (1996).

    Article  CAS  Google Scholar 

  47. Klein, S., Young, V. R., Blackburn, G. L., Bistrian, B. R. & Wolfe, R. R. Palmitate and glycerol kinetics during brief starvation in normal weight young adult and elderly subjects. J. Clin. Invest. 78, 928–933 (1986).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Perry, R. J. et al. Leptin mediates a glucose–fatty acid cycle to maintain glucose homeostasis in starvation. Cell 172, 234–248.e17 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Neinast, M. D. et al. Quantitative analysis of the whole-body metabolic fate of branched-chain amino acids. Cell Metab. 29, 417–429.e4 (2019).

    Article  CAS  PubMed  Google Scholar 

  50. Matthews, D. E. et al. Regulation of leucine metabolism in man: a stable isotope study. Science 214, 1129–1131 (1981).

    Article  CAS  PubMed  Google Scholar 

  51. Waterlow, J. C. Whole-body protein turnover in humans—past, present, and future. Annu. Rev. Nutr. 15, 57–92 (1995).

    Article  CAS  PubMed  Google Scholar 

  52. Wolfe, R. R., Goodenough, R. D., Burke, J. F. & Wolfe, M. H. Response of protein and urea kinetics in burn patients to different levels of protein intake. Ann. Surg. 197, 163–171 (1983).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  53. Hui, S. et al. Quantitative fluxomics of circulating metabolites. Cell Metab. 32, 676–688.e4 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  54. Sprinson, D. B. & Rittenberg, D. The rate of interaction of the ammo acids of the diet with the tissue proteins. J. Biol. Chem. 180, 715–726 (1949).

    Article  CAS  PubMed  Google Scholar 

  55. Golden, S., Chenoweth, M., Dunn, A., Okajima, F. & Katz, J. Metabolism of tritium- and 14C-labeled alanine in rats. Am. J. Physiol. Endocrinol. Metab. 241, E121–E128 (1981).

    Article  CAS  Google Scholar 

  56. 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).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  57. Rendina, A. R., Hermes, J. D. & Cleland, W. W. Use of multiple isotope effects to study the mechanism of 6-phosphogluconate dehydrogenase. Biochemistry 23, 6257–6262 (1984).

    Article  CAS  PubMed  Google Scholar 

  58. Zhang, Z., Chen, L., Liu, L., Su, X. & Rabinowitz, J. D. Chemical basis for deuterium labeling of fat and NADPH. J. Am. Chem. Soc. 139, 14368–14371 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  59. Schoenheimer, R. & Rittenberg, D. Deuterium as an indicator in the study of intermediary metabolism. 9. The conversion of stearic acid into palmitic acid in the organism. J. Biol. Chem. 120, 155–165 (1937).

    Article  CAS  Google Scholar 

  60. Lau, A. N. et al. Dissecting cell-type-specific metabolism in pancreatic ductal adenocarcinoma. eLife 9, e56782 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  61. Ma, E. H. et al. Metabolic profiling using stable isotope tracing reveals distinct patterns of glucose utilization by physiologically activated CD8+ T cells. Immunity 51, 856–870.e5 (2019).

    Article  CAS  PubMed  Google Scholar 

  62. Zhang, L. et al. Spectral tracing of deuterium for imaging glucose metabolism. Nat. Biomed. Eng. 3, 402–413 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  63. DeBerardinis, R. J. et al. Beyond aerobic glycolysis: transformed cells can engage in glutamine metabolism that exceeds the requirement for protein and nucleotide synthesis. Proc. Natl Acad. Sci. USA 104, 19345–19350 (2007).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  67. Faubert, B. et al. Lactate metabolism in human lung tumors. Cell 171, 358–371.e9 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  68. Brunt, E. M. et al. Nonalcoholic fatty liver disease. Nat. Rev. Dis. Prim. 1, 15080 (2015).

    Article  PubMed  Google Scholar 

  69. Hudgins, L. C. et al. Relationship between carbohydrate-induced hypertriglyceridemia and fatty acid synthesis in lean and obese subjects. J. Lipid Res. 41, 595–604 (2000).

    Article  CAS  PubMed  Google Scholar 

  70. Lambert, J. E., Ramos–Roman, M. A., Browning, J. D. & Parks, E. J. Increased de novo lipogenesis is a distinct characteristic of individuals with nonalcoholic fatty liver disease. Gastroenterology 146, 726–735 (2014).

    Article  CAS  PubMed  Google Scholar 

  71. Lu, W. et al. Metabolite measurement: pitfalls to avoid and practices to follow. Annu. Rev. Biochem. 86, 277–304 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  72. TeSlaa, T. et al. The source of glycolytic intermediates in mammalian tissues. Cell Metab. 33, 367–378 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  73. Previs, S. F. & Kelley, D. E. Tracer-based assessments of hepatic anaplerotic and TCA cycle flux: practicality, stoichiometry, and hidden assumptions. Am. J. Physiol. Endocrinol. Metab. 309, E727–E735 (2015).

    Article  CAS  PubMed  Google Scholar 

  74. Patgiri, A. et al. An engineered enzyme that targets circulating lactate to alleviate intracellular NADH:NAD+ imbalance. Nat. Biotechnol. 38, 309–313 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  75. Cham, C. M. & Gajewski, T. F. Glucose availability regulates IFN-γ production and p70S6 kinase activation in CD8+ effector T cells. J. Immunol. 174, 4670–4677 (2005).

    Article  CAS  PubMed  Google Scholar 

  76. Flores, A. et al. Lactate dehydrogenase activity drives hair follicle stem cell activation. Nat. Cell Biol. 19, 1017–1026 (2017).

    Article  CAS  PubMed  Google Scholar 

  77. Schell, J. C. et al. Control of intestinal stem cell function and proliferation by mitochondrial pyruvate metabolism. Nat. Cell Biol. 19, 1027–1036 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  78. Ryan, D. J., Spraggins, J. M. & Caprioli, R. M. Protein identification strategies in MALDI imaging mass spectrometry: a brief review. Curr. Opin. Chem. Biol. 48, 64–72 (2019).

    Article  CAS  PubMed  Google Scholar 

  79. Abu-Remaileh, M. et al. Lysosomal metabolomics reveals V-ATPase- and mTOR-dependent regulation of amino acid efflux from lysosomes. Science 358, 807–813 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  80. Chen, W. W., Freinkman, E., Wang, T., Birsoy, K. & Sabatini, D. M. Absolute quantification of matrix metabolites reveals the dynamics of mitochondrial metabolism. Cell 166, 1324–1337.e11 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  81. Lee, W. D., Mukha, D., Aizenshtein, E. & Shlomi, T. Spatial-fluxomics provides a subcellular-compartmentalized view of reductive glutamine metabolism in cancer cells. Nat. Commun. 10, 1351 (2019).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  82. Orth, J. D., Thiele, I. & Palsson, B. Ø. What is flux balance analysis? Nat. Biotechnol. 28, 245–248 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  83. Metallo, C. M. et al. Reductive glutamine metabolism by IDH1 mediates lipogenesis under hypoxia. Nature 481, 380–384 (2012).

    Article  CAS  Google Scholar 

  84. Lu, H. et al. A consensus S. cerevisiae metabolic model Yeast8 and its ecosystem for comprehensively probing cellular metabolism. Nat. Commun. 10, 3586 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  85. Blank, L. M., Kuepfer, L. & Sauer, U. Large-scale 13C-flux analysis reveals mechanistic principles of metabolic network robustness to null mutations in yeast. Genome Biol. 6, R49 (2005).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  86. Shlomi, T., Cabili, M. N., Herrgård, M. J., Palsson, B. Ø. & Ruppin, E. Network-based prediction of human tissue-specific metabolism. Nat. Biotechnol. 26, 1003–1010 (2008).

    Article  CAS  PubMed  Google Scholar 

  87. Kacser, H., Burns, J. A., Kacser, H. & Fell, D. A. The control of flux. Biochem. Soc. Trans. 23, 341–366 (1995).

    Article  CAS  PubMed  Google Scholar 

  88. Emwas, A.-H. M. The strengths and weaknesses of NMR spectroscopy and mass spectrometry with particular focus on metabolomics research. In Metabonomics: Methods and Protocols Vol. 1277 (ed. Bjerrum, J. T.) 161–193 (Humana, 2015).

  89. Su, X., Lu, W. & Rabinowitz, J. D.Metabolite spectral accuracy on orbitraps.Anal. Chem. 89, 5940–5948 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  90. Bajad, S. U. et al. Separation and quantitation of water soluble cellular metabolites by hydrophilic interaction chromatography-tandem mass spectrometry. J. Chromatogr. A 1125, 76–88 (2006).

    Article  CAS  PubMed  Google Scholar 

  91. Zhang, Y. et al. Comparing stable isotope enrichment by gas chromatography with time-of-flight, quadrupole time-of-flight, and quadrupole mass spectrometry. Anal. Chem. 93, 2174–2182 (2021).

    Article  CAS  PubMed  Google Scholar 

  92. Perseghin, G. et al. Increased glucose transport—phosphorylation and muscle glycogen synthesis after exercise training in insulin-resistant subjects. N. Engl. J. Med. 335, 1357–1362 (1996).

    Article  CAS  PubMed  Google Scholar 

  93. Zabielski, P. et al. Comparison of different mass spectrometry techniques in the measurement of L-[ring-13C6]phenylalanine incorporation into mixed muscle proteins. J. Mass Spectrom. 48, 269–275 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  94. Wolfe, R. R. Measurement of urea kinetics in vivo by means of a constant tracer infusion of di-15N-urea. Am. J. Physiol. Endocrinol. Metab. 240, E428–E434 (1981).

    Article  CAS  Google Scholar 

  95. Institute of Medicine (US) Committee on Military Nutrition Research. Emerging Technologies for Nutrition Research: Potential for Assessing Military Performance Capability (US National Academies Press, 1997).

  96. Emwas, A.-H. et al. NMR spectroscopy for metabolomics research. Metabolites 9, 123 (2019).

    Article  CAS  PubMed Central  Google Scholar 

  97. Lin, P., Lane, A. N. & Fan, T. W.-M. Stable isotope-resolved metabolomics by NMR. Methods Mol. Biol. 2037, 151–168 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  98. Roden, M. et al. Mechanism of free fatty acid-induced insulin resistance in humans. J. Clin. Invest. 97, 2859–2865 (1996).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  99. Befroy, D. E. et al. Direct assessment of hepatic mitochondrial oxidative and anaplerotic fluxes in humans using dynamic 13C magnetic resonance spectroscopy. Nat. Med. 20, 98–102 (2014).

    Article  CAS  PubMed  Google Scholar 

  100. Mason, G. F. et al. Simultaneous determination of the rates of the TCA cycle, glucose utilization, α-ketoglutarate/glutamate exchange, and glutamine synthesis in human brain by NMR. J. Cereb. Blood Flow. Metab. 15, 12–25 (1995).

    Article  CAS  PubMed  Google Scholar 

  101. Landau, B. R. et al. 14C-labeled propionate metabolism in vivo and estimates of hepatic gluconeogenesis relative to Krebs cycle flux. Am. J. Physiol. 265, E636–E647 (1993).

    CAS  PubMed  Google Scholar 

  102. Brindle, K. M. Imaging metabolism with hyperpolarized 13C-labeled cell substrates. J. Am. Chem. Soc. 137, 6418–6427 (2015).

    Article  CAS  PubMed  Google Scholar 

  103. Witney, T. H. & Brindle, K. M. Imaging tumour cell metabolism using hyperpolarized 13C magnetic resonance spectroscopy. Biochem. Soc. Trans. 38, 1220–1224 (2010).

    Article  CAS  PubMed  Google Scholar 

  104. Deh, K. et al. Dynamic volumetric hyperpolarized 13C imaging with multi-echo EPI. Magn. Reson. Med. 85, 978–986 (2021).

    Article  CAS  PubMed  Google Scholar 

  105. Kernstine, K. H. et al. Does tumor FDG-PET avidity represent enhanced glycolytic metabolism in non-small cell lung cancer? Ann. Thorac. Surg. 109, 1019–1025 (2020).

    Article  PubMed  Google Scholar 

  106. Chen, D. L. et al. Increased T cell glucose uptake reflects acute rejection in lung grafts. Am. J. Transplant. 13, 2540–2549 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  107. Frayn, K. N., Coppack, S. W., Humphreys, S. M., Clark, M. L. & Evans, R. D. Periprandial regulation of lipid metabolism in insulin-treated diabetes mellitus. Metabolism 42, 504–510 (1993).

    Article  CAS  PubMed  Google Scholar 

  108. DeFronzo, R. A., Tobin, J. D. & Andres, R.Glucose clamp technique: a method for quantifying insulin secretion and resistance. Am. J. Physiol. Endocrinol. Metab. 237, E214–E223 (1979).

    Article  CAS  Google Scholar 

  109. Elahi, D. In praise of the hyperglycemic clamp. A method for assessment of β-cell sensitivity and insulin resistance. Diabetes Care 19, 278–286 (1996).

    Article  CAS  PubMed  Google Scholar 

  110. Kraegen, E. W., James, D. E., Jenkins, A. B. & Chisholm, D. J. Dose–response curves for in vivo insulin sensitivity in individual tissues in rats. Am. J. Physiol. Endocrinol. Metab. 248, E353–E362 (1985).

    Article  CAS  Google Scholar 

  111. Bonora, E. et al. Homeostasis model assessment closely mirrors the glucose clamp technique in the assessment of insulin sensitivity: studies in subjects with various degrees of glucose tolerance and insulin sensitivity. Diabetes Care 23, 57–63 (2000).

    Article  CAS  PubMed  Google Scholar 

  112. Miyazaki, Y. et al. Effect of pioglitazone on circulating adipocytokine levels and insulin sensitivity in type 2 diabetic patients. J. Clin. Endocrinol. Metab. 89, 4312–4319 (2004).

    Article  CAS  PubMed  Google Scholar 

  113. Michael, M. D. et al. Loss of insulin signaling in hepatocytes leads to severe insulin resistance and progressive hepatic dysfunction. Mol. Cell 6, 87–97 (2000).

    Article  CAS  PubMed  Google Scholar 

  114. Bali, D. et al. Animal model for maturity-onset diabetes of the young generated by disruption of the mouse glucokinase gene. J. Biol. Chem. 270, 21464–21467 (1995).

    Article  CAS  PubMed  Google Scholar 

  115. Petersen, M. C., Vatner, D. F. & Shulman, G. I. Regulation of hepatic glucose metabolism in health and disease. Nat. Rev. Endocrinol. 13, 572–587 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  116. Hellerstein, M. K. & Neese, R. A. Mass isotopomer distribution analysis: a technique for measuring biosynthesis and turnover of polymers. Am. J. Physiol. Endocrinol. Metab. 263, E988–E1001 (1992).

    Article  CAS  Google Scholar 

  117. Stanhope, K. L. et al. Consuming fructose-sweetened, not glucose-sweetened, beverages increases visceral adiposity and lipids and decreases insulin sensitivity in overweight/obese humans. J. Clin. Invest. 119, 1322–1334 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  118. Bloch, K. & Rittenberg, D. On the utilization of acetic acid for cholesterol formation. J. Biol. Chem. 145, 625–636 (1942).

    Article  CAS  Google Scholar 

  119. Shulman, G. I. et al. Quantitation of muscle glycogen synthesis in normal subjects and subjects with non-insulin-dependent diabetes by 13C nuclear magnetic resonance spectroscopy. N. Engl. J. Med. 322, 223–228 (1990).

    Article  CAS  PubMed  Google Scholar 

  120. Daurio, N. A. et al. Spatial and temporal studies of metabolic activity: contrasting biochemical kinetics in tissues and pathways during fasted and fed states. Am. J. Physiol. Endocrinol. Metab. 316, E1105–E1117 (2019).

    Article  CAS  PubMed  Google Scholar 

  121. Yuan, J., Bennett, B. D. & Rabinowitz, J. D. Kinetic flux profiling for quantitation of cellular metabolic fluxes. Nat. Protoc. 3, 1328–1340 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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Acknowledgements

We thank Yihui Shen, Wenyun Lu, Michael Neinast, Asael Roichman and other members of the Rabinowitz laboratory for helpful discussion. This work was supported by NIH Pioneer award 5DP1DK113643, Diabetes Research Center grant P30 DK019525 and Paul G. Allen Family Foundation grant 0034665 to J.D.R., NIH fellowship F32DK118856 to T.T. and Damon Runyon Cancer Research Foundation fellowship DRG-2373-19 to C.R.B.

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C.R.B., T.T. and J.D.R. conceived and wrote the review.

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Correspondence to Joshua D. Rabinowitz.

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Peer review information Nature Metabolism thanks Julian Griffin and Elizabeth Want for their contribution to the peer review of this work. Primary Handling Editor: George Caputa.

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Bartman, C.R., TeSlaa, T. & Rabinowitz, J.D. Quantitative flux analysis in mammals. Nat Metab 3, 896–908 (2021). https://doi.org/10.1038/s42255-021-00419-2

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