Abstract
Fructose consumption is linked to the rising incidence of obesity and cancer, which are two of the leading causes of morbidity and mortality globally1,2. Dietary fructose metabolism begins at the epithelium of the small intestine, where fructose is transported by glucose transporter type 5 (GLUT5; encoded by SLC2A5) and phosphorylated by ketohexokinase to form fructose 1-phosphate, which accumulates to high levels in the cell3,4. Although this pathway has been implicated in obesity and tumour promotion, the exact mechanism that drives these pathologies in the intestine remains unclear. Here we show that dietary fructose improves the survival of intestinal cells and increases intestinal villus length in several mouse models. The increase in villus length expands the surface area of the gut and increases nutrient absorption and adiposity in mice that are fed a high-fat diet. In hypoxic intestinal cells, fructose 1-phosphate inhibits the M2 isoform of pyruvate kinase to promote cell survival5,6,7. Genetic ablation of ketohexokinase or stimulation of pyruvate kinase prevents villus elongation and abolishes the nutrient absorption and tumour growth that are induced by feeding mice with high-fructose corn syrup. The ability of fructose to promote cell survival through an allosteric metabolite thus provides additional insights into the excess adiposity generated by a Western diet, and a compelling explanation for the promotion of tumour growth by high-fructose corn syrup.
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Data availability
Additional data that support the findings of this study are available from the corresponding author upon reasonable request. Source data are provided with this paper.
Code availability
Villi analysis code, licensing information, and instructions for use are available at https://github.com/sam-taylor/VilliQuant.
References
Bray, G. A., Nielsen, S. J. & Popkin, B. M. Consumption of high-fructose corn syrup in beverages may play a role in the epidemic of obesity. Am. J. Clin. Nutr. 79, 537–543 (2004).
Joh, H.-K. et al. Simple sugar and sugar-sweetened beverage intake during adolescence and risk of colorectal cancer precursors. Gastroenterology 161, 128–142 (2021).
Miller. M., Craig, J. W., Drucker, W. R. & Woodward, H. Jr. The metabolism of fructose in man. Yale J. Biol. Med. 29, 335–360 (1956).
Jang, C. et al. The small intestine converts dietary fructose into glucose and organic acids. Cell Metab. 27, 351–361 (2018).
Anastasiou, D. et al. Inhibition of pyruvate kinase M2 by reactive oxygen species contributes to cellular antioxidant responses. Science 334, 1278–1283 (2011).
Nguyen, A. et al. PKLR promotes colorectal cancer liver colonization through induction of glutathione synthesis. J. Clin. Invest. 126, 681–694 (2016).
Anastasiou, D. et al. Pyruvate kinase M2 activators promote tetramer formation and suppress tumorigenesis. Nat. Chem. Biol. 8, 839–847 (2012).
Port, A. M., Ruth, M. R. & Istfan, N. W. Fructose consumption and cancer: is there a connection? Curr. Opin. Endocrinol. Diabetes Obes. 19, 367–374 (2012).
Parikh, N. I. et al. Increasing trends in incidence of overweight and obesity over 5 decades. Am. J. Med. 120, 242–250 (2007).
Liu, P. H. et al. Association of obesity with risk of early-onset colorectal cancer among women. JAMA Oncol. 5, 37–44 (2019).
Siegel, R. L. et al. Colorectal cancer incidence patterns in the United States, 1974–2013. J. Natl. Cancer Inst. 109, djw322 (2017).
Tasevska, N. et al. Sugars in diet and risk of cancer in the NIH-AARP Diet and Health Study. Int. J. Cancer 130, 159–169 (2012).
Bostick, R. M. et al. Sugar, meat, and fat intake, and non-dietary risk factors for colon cancer incidence in Iowa women (United States). Cancer Causes Control 5, 38–52 (1994).
Meyerhardt, J. A. et al. Dietary glycemic load and cancer recurrence and survival in patients with stage III colon cancer: findings from CALGB 89803. J. Natl. Cancer Inst. 104, 1702–1711 (2012).
Goncalves, M. D. et al. High-fructose corn syrup enhances intestinal tumor growth in mice. Science 363, 1345–1349 (2019).
Bu, P. et al. Aldolase B-mediated fructose metabolism drives metabolic reprogramming of colon cancer liver metastasis. Cell Metab. 27, 1249–1262 (2018).
Hall, P. A., Coates, P. J., Ansari, B. & Hopwood, D. Regulation of cell number in the mammalian gastrointestinal tract: the importance of apoptosis. J. Cell Sci. 107, 3569–3577 (1994).
Israelsen, W. J. & Vander Heiden, M. G. Pyruvate kinase: Function, regulation and role in cancer. Semin. Cell Dev. Biol. 43, 43–51 (2015).
Yang, H., Wang, X., Xiong, X. & Yin, Y. Energy metabolism in intestinal epithelial cells during maturation along the crypt-villus axis. Sci. Rep. 6, 31917 (2016).
Christofk, H. R., Vander Heiden, M. G., Wu, N., Asara, J. M. & Cantley, L. C. Pyruvate kinase M2 is a phosphotyrosine-binding protein. Nature 452, 181–186 (2008).
Luo, W. et al. Pyruvate kinase M2 is a PHD3-stimulated coactivator for hypoxia-inducible factor 1. Cell 145, 732–744 (2011).
Schwitalla, S. et al. Intestinal tumorigenesis initiated by dedifferentiation and acquisition of stem-cell-like properties. Cell 152, 25–38 (2013).
Schatoff, E. M. et al. Distinct colorectal cancer–associated APC mutations dictate response to tankyrase inhibition. Cancer Discov. 9, 1358–1371 (2019).
Kucharzewska, P., Christianson, H. C. & Belting, M. Global profiling of metabolic adaptation to hypoxic stress in human glioblastoma cells. PLoS ONE 10, e0116740 (2015).
Armitage, E. G. et al. Metabolic profiling reveals potential metabolic markers associated with hypoxia inducible factor-mediated signalling in hypoxic cancer cells. Sci. Rep. 5, 15649 (2015).
Mirtschink, P. et al. HIF-driven SF3B1 induces KHK-C to enforce fructolysis and heart disease. Nature 522, 444–449 (2015).
Park, T. J. et al. Fructose-driven glycolysis supports anoxia resistance in the naked mole-rat. Science 356, 307–311 (2017).
Goran, M. I., Martin, A. A., Alderete, T. L., Fujiwara, H. & Fields, D. A. Fructose in breast milk is positively associated with infant body composition at 6 months of age. Nutrients 9, 146 (2017).
Denyes, A. & Carter, J. D. Utilization of acetate-1-C-14 by hepatic tissue from cold-exposed and hibernating hamsters. Am. J. Physiol. 200, 1043–1046 (1961).
Diggle, C. P. et al. Ketohexokinase: expression and localization of the principal fructose-metabolizing enzyme. J. Histochem. Cytochem. 57, 763–774 (2009).
Macenko, M. et al. A method for normalizing histology slides for quantitative analysis. In 2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro 1107–1110 (IEEE, 2009).
MATLAB v.9.7.0.1190202 (R2019b) (The MathWorks Inc., 2018).
Mystkowski, P. et al. Validation of whole-body magnetic resonance spectroscopy as a tool to assess murine body composition. Int. J. Obes. 24, 719–724 (2000).
Millar, J. S., Cromley, D. A., McCoy, M. G., Rader, D. J. & Billheimer, J. T. Determining hepatic triglyceride production in mice: comparison of poloxamer 407 with Triton WR-1339. J. Lipid Res. 46, 2023–2028 (2005).
Krisko, T. I. et al. Dissociation of adaptive thermogenesis from glucose homeostasis in microbiome-deficient mice. Cell Metab. 31, 592–604 (2020).
Weir, J. B. New methods for calculating metabolic rate with special reference to protein metabolism. J. Physiol. 109, 1–9 (1949).
Staffas, A. et al. Nutritional support from the intestinal microbiota improves hematopoietic reconstitution after bone marrow transplantation in mice. Cell Host Microbe 23, 447–457 (2018).
Nalapareddy, K. et al. Canonical Wnt signaling ameliorates aging of intestinal stem cells. Cell Rep. 18, 2608–2621 (2017).
Raleigh, J. A. & Koch, C. J. Importance of thiols in the reductive binding of 2-nitroimidazoles to macromolecules. Biochem. Pharmacol. 40, 2457–2464 (1990).
O’Rourke, K. P., Dow, L. E. & Lowe, S. W. Immunofluorescent staining of mouse intestinal stem cells. Bio Protoc. 6, e1732 (2016).
White, R., Yaeger, D. & Stavrianeas, S. Determination of blood lactate concentration: reliability and validity of a lactate oxidase-based method. Int. J. Exerc. Sci. 2, 2 (2009).
Ashizawa, K., McPhie, P., Lin, K.-H. & Cheng, S.-Y. An in vitro novel mechanism of regulating the activity of pyruvate kinase M2 by thyroid hormone and fructose 1, 6-bisphosphate. Biochemistry 30, 7105–7111 (1991).
Adelman, R. C., Ballard, F. J. & Weinhouse, S. Purification and properties of rat liver fructokinase. J. Biol. Chem. 242, 3360–3365 (1967).
Al-Ani, A. et al. Oxygenation in cell culture: Critical parameters for reproducibility are routinely not reported. PLoS ONE 13, e0204269 (2018).
Sullivan, M. R. et al. Quantification of microenvironmental metabolites in murine cancers reveals determinants of tumor nutrient availability. eLife 8, e44235 (2019).
Smith, C. A., Want, E. J., O’Maille, G., Abagyan, R. & Siuzdak, G. XCMS: processing mass spectrometry data for metabolite profiling using nonlinear peak alignment, matching, and identification. Anal. Chem. 78, 779–787 (2006).
Huang, X. et al. X13CMS: global tracking of isotopic labels in untargeted metabolomics. Anal. Chem. 86, 1632–1639 (2014).
Fernandez-Martinez, J., Lacava, J. & Rout, M. P. Density gradient ultracentrifugation to isolate endogenous protein complexes after affinity capture. Cold Spring Harb. Protoc. https://doi.org/10.1101/pdb.prot087957 (2016).
Acknowledgements
We acknowledge C. Gurbatri for her assistance in figure preparation, M. Lyashenko for his technical assistance with experiment replication and Y.-T. Chen for his pathological review of the primary human CRC tissue. We thank J. Yun for her discussions, which informed the early development of this work. Khk−/− mice were provided by D. T. Bonthron and R. J. Johnson. Glut5−/− mice were provided by R.P. Ferraris and St. Jude’s Children’s Research Hospital. S.R.T. and E.M.S. were supported by a Medical Scientist Training Program grant from the National Institute of General Medical Sciences of the National Institutes of Health under award number T32GM007739 to the Weill Cornell–Rockefeller–Sloan Kettering Tri-Institutional MD–PhD Program. This work was supported by NIH R35 CA197588 (L.C.C.), SU2C-AACR-DT22-17 (L.C.C.), NIH K08 CA230318 (M.D.G.), R25 AI140472 (K.Y.R.), a grant from the Lung Cancer Research Foundation and institutional funds from Weill Cornell Medicine.
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Authors and Affiliations
Contributions
S.R.T. and M.D.G. contributed to the conception and design of the study. S.R.T., A.J.D., L.E.D., K.Y.R., L.C.C. and M.D.G. contributed ideas that formulated the overarching research goals and aims. E.M.S. and L.E.D. generated and provided the ApcQ1405X/+ mouse model and guided its experimental use. S.R.T., N.V. and J.L.J. contributed to the structural and biochemical assays of pyruvate kinase. M.A.S. collected and provided the primary human tumour samples. A.J.D. provided the Glut5−/− mouse model and ideas that guided the initial phenotyping of the wild-type mice that were fed fructose. S.R.T., S.R. and N.J.F. performed programming, software development and implementation of the computer code and supporting algorithms. S.R.T., S.R. and S.-K.H. conducted mouse physiology studies and performed necropsy and tissue analysis. S.R.T. and A.K. performed the mouse intestinal organoid experiments under the guidance of L.E.D. S.R.T. and N.N. performed and analysed the LC–MS metabolomics experiments under the guidance of K.Y.R. and M.D.G. R.J.L. performed mutagenesis and generated recombinant pyruvate kinase. R.P. performed KHK activity assays. R.P.S. assisted with targeted isoform sequencing. S.R.T. performed all other experiments. S.R.T. and M.D.G. wrote the manuscript and verified the overall replication and reproducibility of results, experiments and other research outputs.
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Competing interests
L.C.C. is a founder, shareholder and member of the scientific advisory board of Agios Pharmaceuticals and a founder and former member of the scientific advisory board of Ravenna Pharmaceuticals (previously Petra Pharmaceuticals). These companies are developing therapies for cancer. L.C.C. has received research funding from Ravenna Pharmaceuticals. L.C.C. and M.D.G. are co-founders and shareholders of Faeth Therapeutics, which is developing therapies for cancer. M.D.G. has received speaking and/or consulting fees from Pfizer, Novartis, Petra Pharmaceuticals, Faeth Therapeutics and TruMacro Nutrition. The laboratory of M.D.G. has received financial support from Pfizer. All other authors report no competing interests.
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Peer review information Nature thanks Dimitrios Anastasiou, M. Mahmood Hussain 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 Fig. 1 Image segmentation avoids the pitfalls of manual villi measurement.
a, Stain-normalized H&E images of Swiss-rolled intestines were loaded into image-analysis software, which was used to manually measure the length of the gut section (dotted black line). b, Image segmentation isolates villi (white) while excluding other tissues such as lymph nodes, pancreas and intestinal crypts. c, Intra-operator variation is a source of measurement error in manual villi measurements. The x and y axes represent measurements taken by the same analyst at different times. d, Inter-operator variation is another source of measurement error in manual villi measurements. The x and y axes represent measurements taken by different analysts. e, f, Intra- and inter-operator variation are minimized when using the semi-automated protocol. The comparisons in e, f are the same as in c, d; however, the only manual measurement in the semi-automated method is the measurement of the whole gut section length. g, Automated and manual measurements correlate. The x and y axes represent measurements obtained from the manual and semi-automated protocols, respectively. h, Mice from various genetic backgrounds were fed HFCS and the mean villus length in the duodenal intestinal epithelium was measured using a custom analysis algorithm (mice per group: left to right (H2O|HFCS): 4|5, 5|5, 10|10, 10|10, 9|5). c–g, Each point represents a distinct image; dotted line: unity; R2 is displayed for the linear regression fit of the data. h, Two-way ANOVA followed by Holm–Sidak post-hoc test for multiple comparisons. *P < 0.05, **P < 0.01, ***P < 0.001. Error bars represent ± s.e.m. See Source Data for exact P values for all figures.
Extended Data Fig. 2 Dietary fructose promotes weight gain and adiposity independent of caloric intake.
a, Mice fed normal chow with or without 25% HFCS ad libitum were weighed weekly for six weeks. b–d, Total, lean and fat body mass were measured before and five weeks after mice were placed on diets. e–g, Total consumption of chow and fluid was measured weekly to calculate caloric consumption (n = 5 serial measurements per group). h, i, Tissues from mice on the indicated diets were collected and weighed and the liver was assayed for triglyceride content. WAT, white adipose tissue from the left or right gonadal fat depot. j, After five weeks, mice were fasted and blood glucose was measured by glucometer (a–j, 5 mice per group). k, A lipid tolerance test was performed on wild-type female mice fed HFCS (n = 3 mice per group). l, Mice treated with water or HFCS were fasted and then given an intraperitoneal injection of poloxamer 407. One hour later, triglyceride levels were measured from the serum and the mice were given an oral olive oil bolus. Two hours later, serum triglyceride levels were measured again (n = 7 (H2O) and n = 5 (HFCS) mice per group). m, Mice fed fructose-free control diets (control), high-fat diets consisting of 45% kcal from fat (HF), and high-fat diets with sucrose in place of glucose as the main sugar (HFHS) were monitored weekly for chow consumption by cage (n = 3 repeated measurements per group). n, Total, lean and fat body mass were measured after five weeks on the diet. Statistical comparisons are made against control fat mass (n = 5 mice per group). o, After four weeks on the diet, mice were fasted and blood glucose was measured with a glucometer (n = 3 mice per group). p–r, After euthanasia, tissues were collected and weighed, liver tissue was homogenized and assayed for triglyceride content, mouse intestines were excised en bloc and the intestinal length was measured using ImageJ software (n = 5 (p, r) and n = 4 (q) mice per group). s, Mice treated with high-fat or high-fat high-sucrose diets for two weeks were housed in metabolic cages and food intake over 24 h was measured. t, O2 consumption and CO2 production were measured to calculate the respiratory exchange ratio. u, v, Total distance travelled was also measured (u), as was hourly energy expenditure (v), which was calculated using the Weir equation8. w–z, Mice were individually housed and faecal matter was collected over a 24-h period (w), dried (x) and then analysed by bomb calorimetry to measure energy content and energy loss over the collection period (y, z) (s–z, 4 mice per group). b, c, h, n, Two-way ANOVA followed by Holm–Sidak post-hoc test for multiple comparisons; d–g, i, j, l, s–u, w–z, Student’s two-sided t-test; k, m, o, q, one-way ANOVA followed by Holm–Sidak post-hoc test for multiple comparisons. NS, not significant; *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001. All data are mean± s.e.m.
Extended Data Fig. 3 HFCS increases villus survival and expression of GLUT5 and HIF target proteins.
a, Model depicting the strategy of the BrdU tracing experiment. BrdU labels cells synthesizing DNA (brown). These cells transit up the length of the villus and away from richly oxygenated blood in 3–4 days. Unlabelled cells beyond the BrdU front at the time that mice were euthanized were thus generated before BrdU injection. b, Duodenal villus length was measured from H&E images from H2O- and HFCS-treated mouse intestine (n = 3 mice per group, 40 villi per mouse). c, Mice were administered BrdU 72 h before euthanasia, and intestines were then examined by IHC. The length of BrdU-labelled regions of the villus was measured in both treatment groups and this length was divided by the interval between injection and euthanasia to yield migration rate (n = 3 mice per group, 15–20 duodenal villi per mouse). d, e, In a separate experiment, mice were treated with H2O or HFCS and given BrdU (green) 48 h before and EdU (red) 24 h before euthanasia. Duodenal villi were then stained and imaged by immunofluorescence and analysed as in c. The difference between the BrdU and EdU lengths was divided by the interval between injections to yield the migration rate (n = 3 (H2O) and n = 4 (HFCS) mice per group, 15–20 duodenal villi per mouse). Scale bars, 100 μm. f, Mice treated with H2O or 25% HFCS were euthanized and the intestines were examined by IHC against Ki-67, CC3 and TUNEL. Scale bars, 200 μm. g, Before euthanasia, mice treated as in f were injected with pimonidazole to label tissue hypoxia. Intestines were then fixed and examined for pimonidazole intensity by IHC. Representative images are shown. Scale bars: 500 μm. h, The pimonidazole-positive area was quantified and normalized to total small intestine (SI) area (n = 5 mice per group). i, Wild-type mice treated with H2O or HFCS and total-body, constitutive Glut5−/− mice treated with HFCS were euthanized and intestines were fixed and examined by IHC. Representative images are shown. Scale bars, 200 μm (top); 50 μm (bottom). j, Wild-type mice treated with H2O or 25% HFCS ad libitum for four weeks were euthanized and intestinal epithelium was collected for western blot for indicators of cell health including markers of energy homeostasis (pACC, pAMPK) and anti-apoptotic proteins (BCL2, BCL-XL, MCL-1). k, Mice treated as in j were also euthanized and the intestinal epithelium was examined by western blot for hypoxia response proteins (ENO1, LDHA) and KHK. b, c, e, h, two-sided Student’s t-test. NS, not significant; ***P < 0.001. All data are mean ± s.e.m. For gel source data, see Supplementary Fig. 1.
Extended Data Fig. 4 Fructose enhances hypoxic cell survival.
a, At the conclusion of the experiment depicted in Fig. 2a, HCT116 cells were collected and analysed by Trypan Blue exclusion assay. Total live cells per group were counted and normalized to the fructose-free group (n = 3 biological replicates per group). b, c, HCT116 cells were plated near confluence and cultured in hypoxia with or without 10 mM fructose in the medium. Every 48 h, as indicated, the medium was exchanged with fresh oxygen-equilibrated medium. Confluence was monitored and at the conclusion of the experiment cells were analysed by Trypan Blue exclusion assay as in a (n = 3 biological replicates per group). d–f, HCT116 (d) or DLD1 (e, f) cells were cultured with glucose and either stausporin (Stau, 100 nM, apoptotic control) or fructose, in medium that also contained an Annexin V dye (d, e) and a nucleic-acid-binding cell death dye (CytoTox; f). Cells were incubated in normoxia (N) or hypoxia (H) and imaged daily by live-cell imaging. Stain intensity is reported as positive cell area per well normalized to the initial normoxic glucose control (n = 3 biological replicates per data point). g, Intestinal organoids were generated from adult B6J mice and cultured in hypoxia with or without fructose for 72 h. At experiment termination, organoids were pulsed with EdU, fixed in situ, stained for the indicated targets and examined by confocal microscopy. Representative images are shown. White arrows indicate regions with intra-organoid CC3 puncti. Scale bars, 50 μm. h, i, Organoids treated as in g were rapidly dissociated and stained for viability (via a membrane-impermeable dye) (h) and EdU (i). The resulting cell suspensions were analysed by flow cytometry. Viability is expressed as viable cells recovered per culture well, normalized to the average of the normoxic glucose controls (n = 3 progenitor mice; each pair of points represents a different mouse progenitor). In these and other in vitro assays, unless otherwise noted, glucose was replenished daily as described in the Methods. a, d, h, One-way ANOVA followed by Holm–Sidak post-hoc test for multiple comparisons; b, c, two-sided Student’s t-test; *P < 0.05, **P < 0.01, ****P < 0.0001. All data are mean ± s.e.m.
Extended Data Fig. 5 Hypoxia increases GLUT5 expression and KHK-A transcription.
a, HCT116 and DLD1 cells cultured at the indicated O2 concentrations with or without 10 mM fructose were lysed at 36 h and western blotted for the indicated targets. ‘+’ in the ‘%O2’ row indicates that 100 μM cobalt chloride was added to the medium at time 0. b, RNA was extracted from HCT116 cells treated in normoxia or hypoxia for 24 h and analysed by IsoSeq. The relative proportion of the A and C isoforms of KHK are shown (n = 1 biological replicate per O2 condition). c, HCT116 cells cultured in normoxia or hypoxia for 24 h were lysed and tested for KHK activity by enzymatic assay (n = 3 biological replicates). c, Two-sided student’s t-test. **P < 0.01. Data in c are mean ± s.e.m. For gel source data, see Supplementary Fig. 1.
Extended Data Fig. 6 F1P accumulates in cells and correlates with marked metabolic changes in hypoxia.
a, HCT116 cells cultured in hypoxia with fructose were labelled with various U-13C metabolites and intracellular metabolites were detected by LC–MS. The y axis reflects the fraction of the detected metabolite labelled with 13C on the number of carbons denoted by the colours to the right of each graph. The x axis denotes the labelled feed metabolite for that particular group. The graph for fructose, for example, indicates that all detected fructose ions were labelled at all 6 carbons with 13C when U-13C6 fructose was provided in the medium (n = 3 biological replicates per unique label). b, HCT116 and DLD1 cells were cultured in hypoxia with 25 mM glucose with or without 10 mM fructose. At 48 h the growth medium was assayed for glucose and fructose content. Colours indicate the initial medium formulation for each group. The x axis denotes which sugar is being measured (n = 3 (Glc) and n = 2 (Glc + Fru) biological replicates per group). c, Mouse intestinal organoids were cultured in hypoxia with 10 mM glucose with or without 10 mM fructose for 72 h. Glucose in the 3-ml culture volume was increased by 5 mM daily to account for glucose depletion. After 72 h the growth medium was assayed for sugar content (n = 3 biological replicates per group, n = 1 from each progenitor mouse). d, HCT116 cells were treated with uniformly labelled 13C-fructose or glucose and isotopologues for intracellular fructose were generated. Unless otherwise noted, each column represents an experimental group that received some form of glucose and fructose (n = 3 biological replicates per x-axis label). N, normoxia; H, hypoxia). e, f, Principal component analysis (PCA) (e) targeted heat map (f) of metabolomics data from HCT116 cells cultured at confluence in hypoxia for 36 h and then collected for LC–MS. PCA data are centred and unit-variance-scaled; heat map data are row-normalized ion abundances (n = 3 biological replicates per group; loading plots available in Supplementary Fig. 3). g, Pyruvate kinase activity was measured by enzymatic assay in lysates from HCT116 cells cultured in normoxia or hypoxia for 24 h with or without fructose. Assay wells were loaded with equal amounts of total protein for each group (n = 3 biological replicates per group). G6P, glucose 6-phosphate; G3P, glyceraldehyde 3-phosphate; 2PG, 2-phosphoglycerate; TCA: tri-carboxylic acid cycle; αKG, α-ketoglutarate; PA: phosphatidic acid; MG: monoacylglycerol; DG: diacylglycerol. g, Two-way ANOVA followed by Holm–Sidak post-hoc test for multiple comparisons. *P < 0.05. All error bars represent mean ± s.e.m.
Extended Data Fig. 7 The FBP-binding pocket of PKM2 is important for F1P inhibition.
a, Simulated binding positions and residue interactions for FBP (left) and F1P (right) in the allosteric binding pocket of PKM2. Residues 482 and 489 are components of the FBP-activation loop that are predicted to interact with FBP but not F1P. b, Purified recombinant PKM2 (rPKM2) was incubated with the indicated metabolites and separated through a sucrose gradient (also containing the indicated metabolites). Fractions were removed from the gradients and analysed by SDS–PAGE and western blot for PKM2. FBP concentration, 100 μM; F1P concentration, 500 μM. c, Recombinant PKM2 incubated with the indicated metabolites was run on a gel filtration column and subjected to SDS–PAGE and Coomassie blue staining. FBP concentration during incubation and in the column, 100 μM; F1P concentration, 500 μM. d, e, The activity of recombinant PKL and the PKM2(R489L) mutant pre-incubated with the indicated metabolites was measured by enzymatic assay (n = 3 independent reaction wells per group). The residues responsible for PKM2 binding FBP are altered in these isoforms. f–h, Recombinant PKM2 mutants with alterations to the FBP-binding pocket were generated and assayed for PK activity with the indicated metabolites added at the incubation step. FBP concentration, 100 μM; F1P concentration, 1 mM (n = 2 wells per data point). i, The activity of recombinant PK pre-incubated concurrently with the indicated metabolites or compounds was measured by enzymatic assay (n = 3 wells per group). d, e, One-way ANOVA followed by Holm–Sidak post-hoc test for multiple comparisons. *P < 0.05, **P < 0.01, ***P < 0.001. Error bars represent mean ± s.e.m. For gel source data, see Supplementary Fig. 1.
Extended Data Fig. 8 Fructose and pyruvate kinase activation modulate cell survival in hypoxia.
a, HCT116 cells were transduced with shRNA targeting a scrambled sequence (shScr) or PKM2 (shPKM2). Two weeks after transduction, parental cells as well as these modified lines were western blotted for the protein targets indicated on the left. Three separate shScr and shPKM2 subclones were analysed. Mouse gastrocnemius (gastroc.) muscle and liver tissue were used as PKM1 and PKLR controls, respectively. β-actin was used as a loading control. b, HCT116 cells expressing the indicated shRNAs were cultured in normoxia or hypoxia with or without fructose and TEPP-46 (50 μM) in the medium. Glucose was replenished daily, and confluence was monitored by live-cell imaging (n = 3 biological replicates per group). c, shScr or shPKM2-transduced HCT116 cells were cultured in hypoxia for 24 h with or without fructose or fructose and TEPP-46 (50 μM). Total cell H2O2 was then measured using a luciferase-based assay (n = 4 biological replicates per group). d, Parental HCT116 cells were subjected to the same treatment as in c, but were cultured for 72 h in normoxia or hypoxia with daily glucose replenishment (n = 4 biological replicates per group). e, HCT116 cells cultured in hypoxia for 24 h were assayed for reduced thiols (n = 5 biological replicates per group). f, HCT116 cells cultured in hypoxia were provided with 10 mM glucose, 10 mM glucose with N-acetylcysteine (NAC) or 5 mM glucose and 5 mM fructose in the medium. After 144 h the viability of the adherent cells was measured (n = 4 biological replicates per group). g, HCT116 and DLD1 cells were subjected to varying levels of hypoxia for 24 h with fructose introduced in the medium either at the time the cells were placed in hypoxia (‘+’) or as pre-treatment (‘PT+’), starting in the previous cell passage before plating the experiment and continuing through the hypoxic period (4 days total fructose exposure with the final 24 h in hypoxia). Cells were rapidly lysed at the conclusion of the experiment and analysed by western blot. h, HCT116 cells were exposed to hypoxia with or without fructose in the medium and LC–MS analysis was performed on the resulting polar extracts (n = 3 biological replicates per group). i, HCT116 cells were cultured in normoxia or hypoxia for 24 h with or without fructose. At the end of the experiment, medium samples were taken from each well and analysed by enzymatic assay for lactate content (n = 3 biological replicates per group). c, d, i, Two-way ANOVA followed by Holm–Sidak post-hoc test for multiple comparisons; e, Student’s two-sided t-test; f, one-way ANOVA followed by Holm–Sidak post-hoc test for multiple comparisons. NS, not significant; *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001. All data are mean ± s.e.m. where possible. For gel source data, see Supplementary Fig. 2.
Extended Data Fig. 9 Ablation of PKM2 in the villi results in upregulation of PKM1.
a, Representative intestines from 12-week-old mice examined by IHC for the indicated targets. Scale bar, 200 μm. b, Mouse IEC lysates from wild-type mice, Vil1Cre/+;Pkm2f/f mice and wild-type mice treated with TEPP-46 were analysed by enzymatic assay for pyruvate kinase activity (mice per group: left to right: 5, 10, 5). Same final protein concentration in each reaction well. c, Wild-type and Vil1Cre/+;Pkm2f/f mice were euthanized and intestines were fixed and examined by IHC against PKM2 or PKM1, respectively. The left column shows proximal jejunum villi in each mouse, and the next two columns are high-magnification images of the distal and proximal villus in each mouse. The last column is colon epithelium. Blue arrows indicate nuclei with intense staining. Scale bars for each row are as indicated. d, Wild-type, Khk−/− and Vil1Cre/+;Pkm2f/f mice were treated with H2O or HFCS and the intestinal epithelium was examined by western blot. e, f, LDHA and ENO1 intensity were quantified relative to the β-actin loading control (mice per group: left to right: 3, 3, 3, 3, 2, 5). g, Serum triglyceride (T.G.) after a lipid challenge was measured in mice fed H2O or 25% HFCS by daily oral gavage for two weeks. Units are normalized to the initial time point to highlight changes in blood triglyceride after the bolus (mice per group; top to bottom: 7, 6, 5, 5). h, After two weeks on the diet mice were euthanized, and the gonadal fat deposits were weighed. Units represent total gonadal depot fat mass as a percentage of total body mass, normalized to H2O-treated mice (mice per group: left to right: 14, 14, 10, 5, 4, 5, 5). i, Liver was also collected and analysed for triglyceride content per gram of tissue (mice per group: left to right: 4, 4, 4, 5, 4, 5, 4). b, h, One-way ANOVA followed by Holm–Sidak post-hoc test for multiple comparisons; e, f, two-way ANOVA followed by Holm–Sidak post-hoc test for multiple comparisons. NS, not significant; *P < 0.05, **P < 0.01; all data are mean ± s.e.m. For gel source data, see Supplementary Fig. 2.
Extended Data Fig. 10 TEPP-46 ablates HFCS-induced villus elongation and tumour growth.
a, Wild-type mice provided with a daily oral gavage of HFCS or H2O mixed with DMSO or TEPP-46 were euthanized after 10 days. Intestines were collected and analysed for mean villus length. b, Villi measurements for those same sections (n = 5 mice per group). c, Mice were treated with normal chow and water for two weeks, 25% HFCS by daily gavage for two weeks or HFCS for two weeks followed by HFCS with TEPP-46 (2 mg per kg per day) for another two weeks. At the conclusion of these treatments, the mice were euthanized and small intestine villus length was examined (n = 5 mice per group). d, Mice were fed the indicated diets by oral gavage for two weeks and serum triglyceride content was measured during the fasted state (mice per group: left to right: 8, 8, 5). e, Violin plot of gene expression data from GTEX (normal human colon epithelium) and TCGA (human colon adenocarcinoma) are shown for PKM. f, Samples of colon tumour (T) and matched normal epithelium (N) from patients with CRC were lysed and analysed by western blot for pyruvate kinase isoform expression and hypoxia markers. Mouse liver and gastrocnemius are included as controls. g, Pyruvate kinase activity was measured in lysates from patient samples before and after incubation with PK activator, and the ratio of initial versus activated activity is shown (tumour and adjacent normal tissue pairs from n = 11 individuals). h–j, Single channels and composite image of normal-diet-treated ApcQ1405X/+ intestinal tumours stained with DAPI, anti-CC3 and anti-pimonidazole and examined by immunofluorescence. k–n, Fly-out panels depicting areas of CC3 and pimonidazole colocalization both along the tumour periphery (k, l) and in the tumour core (m, n). Scale bars as indicated. o, Normal-diet-treated intestinal tumours were also examined by IHC using anti-GLUT5. Scale bar, 200 μm. p, Representative H&E-stained Swiss-rolled intestines from APCQ1405X/+ mice treated with the indicated regimens. Arrows indicate tumours. Scale bars, 2 mm. q, r, H&E images of Swiss-rolled intestines were analysed for tumour burden. Each tumour in the section was counted and its cross-sectional area measured (mice per group: left to right: 6, 5, 4, 6). b, q, r, Two-way ANOVA followed by Holm–Sidak post-hoc test for multiple comparisons; c, d, one-way ANOVA followed by Holm–Sidak post-hoc test for multiple comparisons; e, g, two-sided Student’s t-test. NS, not significant; **P < 0.01, ***P < 0.001, ****P < 0.0001. All error bars represent mean ± s.e.m. For gel source data, see Supplementary Fig. 2.
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Taylor, S.R., Ramsamooj, S., Liang, R.J. et al. Dietary fructose improves intestinal cell survival and nutrient absorption. Nature 597, 263–267 (2021). https://doi.org/10.1038/s41586-021-03827-2
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DOI: https://doi.org/10.1038/s41586-021-03827-2
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