Skip to main content

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

  • Article
  • Published:

Energy-stress-mediated AMPK activation inhibits ferroptosis

Abstract

Energy stress depletes ATP and induces cell death. Here we identify an unexpected inhibitory role of energy stress on ferroptosis, a form of regulated cell death induced by iron-dependent lipid peroxidation. We found that ferroptotic cell death and lipid peroxidation can be inhibited by treatments that induce or mimic energy stress. Inactivation of AMP-activated protein kinase (AMPK), a sensor of cellular energy status, largely abolishes the protective effects of energy stress on ferroptosis in vitro and on ferroptosis-associated renal ischaemia–reperfusion injury in vivo. Cancer cells with high basal AMPK activation are resistant to ferroptosis and AMPK inactivation sensitizes these cells to ferroptosis. Functional and lipidomic analyses further link AMPK regulation of ferroptosis to AMPK-mediated phosphorylation of acetyl-CoA carboxylase and polyunsaturated fatty acid biosynthesis. Our study demonstrates that energy stress inhibits ferroptosis partly through AMPK and reveals an unexpected coupling between ferroptosis and AMPK-mediated energy-stress signalling.

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

Access options

Buy this article

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

Fig. 1: Energy stress inhibits ferroptotic cell death.
Fig. 2: Energy stress inhibits ferroptotic cell death partly through AMPK.
Fig. 3: AMPK inactivation sensitizes cells to ferroptotic cell death.
Fig. 4: AMPK-mediated phosphorylation of ACC inhibits ferroptosis.
Fig. 5: AMPK regulates PUFA-containing lipid accumulation.
Fig. 6: AMPK activation protects from renal IRI.

Similar content being viewed by others

Data availability

The mass spectrometry raw data files and metadata have been deposited in the EMBL-EBI MetaboLights database with the identifier MTBLS1399. All data supporting the findings of this study are available from the corresponding author on reasonable request. Source data for Figs. 1–6 and Extended Data Figs. 1–3 and 5–8 are presented with the paper.

References

  1. Green, D. R., Galluzzi, L. & Kroemer, G. Cell biology. Metabolic control of cell death. Science 345, 1250256 (2014).

    PubMed  PubMed Central  Google Scholar 

  2. Hardie, D. G., Ross, F. A. & Hawley, S. A. AMPK: a nutrient and energy sensor that maintains energy homeostasis. Nat. Rev. Mol. Cell Biol. 13, 251–262 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  3. Hardie, D. G., Schaffer, B. E. & Brunet, A. AMPK: an energy-sensing pathway with multiple inputs and outputs. Trends Cell Biol. 26, 190–201 (2015).

    PubMed  PubMed Central  Google Scholar 

  4. El Mjiyad, N., Caro-Maldonado, A., Ramirez-Peinado, S. & Munoz-Pinedo, C. Sugar-free approaches to cancer cell killing. Oncogene 30, 253–264 (2011).

    CAS  PubMed  Google Scholar 

  5. Lin, A. et al. The FoxO-BNIP3 axis exerts a unique regulation of mTORC1 and cell survival under energy stress. Oncogene 33, 3183–3194 (2014).

    CAS  PubMed  Google Scholar 

  6. Dixon, S. J. et al. Ferroptosis: an iron-dependent form of nonapoptotic cell death. Cell 149, 1060–1072 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  7. Xie, Y. et al. Ferroptosis: process and function. Cell Death Differ. 23, 369–379 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  8. Cao, J. Y. & Dixon, S. J. Mechanisms of ferroptosis. Cell. Mol. Life Sci. 73, 2195–2209 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  9. Yang, W. S. & Stockwell, B. R. Ferroptosis: death by lipid peroxidation. Trends Cell Biol. 26, 165–176 (2016).

    CAS  PubMed  Google Scholar 

  10. Stockwell, B. R. et al. Ferroptosis: a regulated cell death nexus linking metabolism, redox biology, and disease. Cell 171, 273–285 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  11. Jiang, L. et al. Ferroptosis as a p53-mediated activity during tumour suppression. Nature 520, 57–62 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  12. Gao, M., Monian, P., Quadri, N., Ramasamy, R. & Jiang, X. Glutaminolysis and transferrin regulate ferroptosis. Mol. Cell 59, 298–308 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  13. Linkermann, A. et al. Synchronized renal tubular cell death involves ferroptosis. Proc. Natl Acad. Sci. USA 111, 16836–16841 (2014).

    CAS  PubMed  Google Scholar 

  14. Zhang, Y. et al. BAP1 links metabolic regulation of ferroptosis to tumour suppression. Nat. Cell Biol. 20, 1181–1192 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  15. Chen, L., Hambright, W. S., Na, R. & Ran, Q. Ablation of the ferroptosis inhibitor glutathione peroxidase 4 in neurons results in rapid motor neuron degeneration and paralysis. J. Biol. Chem. 290, 28097–28106 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  16. Do Van, B. et al. Ferroptosis, a newly characterized form of cell death in Parkinson’s disease that is regulated by PKC. Neurobiol. Dis. 94, 169–178 (2016).

    PubMed  Google Scholar 

  17. Shimada, K. et al. Global survey of cell death mechanisms reveals metabolic regulation of ferroptosis. Nat. Chem. Biol. 12, 497–503 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  18. Yang, W. S. et al. Regulation of ferroptotic cancer cell death by GPX4. Cell 156, 317–331 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  19. Friedmann Angeli, J. P. et al. Inactivation of the ferroptosis regulator Gpx4 triggers acute renal failure in mice. Nat. Cell Biol. 16, 1180–1191 (2014).

    CAS  PubMed  Google Scholar 

  20. Koppula, P., Zhang, Y., Zhuang, L. & Gan, B. Amino acid transporter SLC7A11/xCT at the crossroads of regulating redox homeostasis and nutrient dependency of cancer. Cancer Commun. 38, 12 (2018).

    Google Scholar 

  21. Dai, F. et al. BAP1 inhibits the ER stress gene regulatory network and modulates metabolic stress response. Proc. Natl Acad. Sci. USA 114, 3192–3197 (2017).

    CAS  PubMed  Google Scholar 

  22. Hay, N. Reprogramming glucose metabolism in cancer: can it be exploited for cancer therapy? Nat. Rev. Cancer 16, 635–649 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  23. Inoki, K., Zhu, T. & Guan, K. L. TSC2 mediates cellular energy response to control cell growth and survival. Cell 115, 577–590 (2003).

    CAS  PubMed  Google Scholar 

  24. Shaw, R. J. et al. The tumor suppressor LKB1 kinase directly activates AMP-activated kinase and regulates apoptosis in response to energy stress. Proc. Natl Acad. Sci. USA 101, 3329–3335 (2004).

    CAS  PubMed  Google Scholar 

  25. Liu, X. et al. LncRNA NBR2 engages a metabolic checkpoint by regulating AMPK under energy stress. Nat. Cell Biol. 18, 431–442 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  26. Hou, W. et al. Autophagy promotes ferroptosis by degradation of ferritin. Autophagy 12, 1425–1428 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  27. Gao, M. et al. Ferroptosis is an autophagic cell death process. Cell Res. 26, 1021–1032 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  28. Bianchi, A., Evans, J. L., Nordlund, A. C., Watts, T. D. & Witters, L. A. Acetyl-CoA carboxylase in reuber hepatoma cells: variation in enzyme activity, insulin regulation, and cellular lipid content. J. Cell. Biochem. 48, 86–97 (1992).

    CAS  PubMed  Google Scholar 

  29. Houde, V. P. et al. AMPK β1 reduces tumor progression and improves survival in p53 null mice. Mol. Oncol. 11, 1143–1155 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  30. Fullerton, M. D. et al. Single phosphorylation sites in Acc1 and Acc2 regulate lipid homeostasis and the insulin-sensitizing effects of metformin. Nat. Med. 19, 1649–1654 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  31. Yang, W. S. et al. Peroxidation of polyunsaturated fatty acids by lipoxygenases drives ferroptosis. Proc. Natl Acad. Sci. USA 113, E4966–E4975 (2016).

    CAS  PubMed  Google Scholar 

  32. Skouta, R. et al. Ferrostatins inhibit oxidative lipid damage and cell death in diverse disease models. J. Am. Chem. Soc. 136, 4551–4556 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  33. Kagan, V. E. et al. Oxidized arachidonic and adrenic PEs navigate cells to ferroptosis. Nat. Chem. Biol. 13, 81–90 (2017).

    CAS  PubMed  Google Scholar 

  34. Doll, S. et al. ACSL4 dictates ferroptosis sensitivity by shaping cellular lipid composition. Nat. Chem. Biol. 13, 91–98 (2017).

    CAS  PubMed  Google Scholar 

  35. Chhipa, R. R. et al. AMP kinase promotes glioblastoma bioenergetics and tumour growth. Nat. Cell Biol. 20, 823–835 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  36. Wang, L. T. et al. Protective role of AMP-activated protein kinase-evoked autophagy on an in vitro model of ischemia/reperfusion-induced renal tubular cell injury. PLoS ONE 8, e79814 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  37. Decleves, A. E., Sharma, K. & Satriano, J. Beneficial effects of AMP-activated protein kinase agonists in kidney ischemia-reperfusion: autophagy and cellular stress markers. Nephron Exp. Nephrol. 128, 98–110 (2014).

    CAS  Google Scholar 

  38. Boroughs, L. K. & DeBerardinis, R. J. Metabolic pathways promoting cancer cell survival and growth. Nat. Cell Biol. 17, 351–359 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  39. Gao, M. et al. Role of mitochondria in ferroptosis. Mol. Cell 73, 354–363 (2019).

    CAS  PubMed  Google Scholar 

  40. Herzig, S. & Shaw, R. J. AMPK: guardian of metabolism and mitochondrial homeostasis. Nat. Rev. Mol. Cell Biol. 19, 121–135 (2018).

    CAS  PubMed  Google Scholar 

  41. Song, X. et al. AMPK-mediated BECN1 phosphorylation promotes ferroptosis by directly blocking system Xc - activity. Curr. Biol. 28, 2388–2399 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  42. Zhang, Y., Zhuang, L. & Gan, B. BAP1 suppresses tumor development by inducing ferroptosis upon SLC7A11 repression. Mol. Cell. Oncol. 6, 1536845 (2019).

    PubMed  Google Scholar 

  43. Liu, T., Jiang, L., Tavana, O. & Gu, W. The deubiquitylase OTUB1 mediates ferroptosis via stabilization of SLC7A11. Cancer Res. 79, 1913–1924 (2019).

    CAS  PubMed  Google Scholar 

  44. Chu, B. et al. ALOX12 is required for p53-mediated tumour suppression through a distinct ferroptosis pathway. Nat. Cell Biol. 21, 579–591 (2019).

    CAS  PubMed  PubMed Central  Google Scholar 

  45. Gan, B. DUBbing ferroptosis in cancer cells. Cancer Res. 79, 1749–1750 (2019).

    CAS  PubMed  Google Scholar 

  46. Hardie, D. G. Molecular pathways: is AMPK a friend or a foe in cancer? Clin. Cancer Res. 21, 3836–3840 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  47. Shackelford, D. B. & Shaw, R. J. The LKB1–AMPK pathway: metabolism and growth control in tumour suppression. Nat. Rev. Cancer 9, 563–575 (2009).

    CAS  PubMed  PubMed Central  Google Scholar 

  48. Saito, Y., Chapple, R. H., Lin, A., Kitano, A. & Nakada, D. AMPK protects leukemia-initiating cells in myeloid leukemias from metabolic stress in the bone marrow. Cell Stem Cell 17, 585–596 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  49. Kishton, R. J. et al. AMPK is essential to balance glycolysis and mitochondrial metabolism to control T-ALL cell stress and survival. Cell Metab. 23, 649–662 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  50. Eichner, L. J. et al. Genetic analysis reveals AMPK is required to support tumor growth in murine Kras-dependent lung cancer models. Cell Metab. 29, 285–302 (2018).

    PubMed  PubMed Central  Google Scholar 

  51. Jeon, S. M., Chandel, N. S. & Hay, N. AMPK regulates NADPH homeostasis to promote tumour cell survival during energy stress. Nature 485, 661–665 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  52. Ross, F. A., MacKintosh, C. & Hardie, D. G. AMP-activated protein kinase: a cellular energy sensor that comes in 12 flavours. FEBS J. 283, 2987–3001 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  53. Gan, B. et al. mTORC1-dependent and -independent regulation of stem cell renewal, differentiation, and mobilization. Proc. Natl Acad. Sci. USA 105, 19384–19389 (2008).

    CAS  PubMed  Google Scholar 

  54. Gan, B. et al. FoxOs enforce a progression checkpoint to constrain mTORC1-activated renal tumorigenesis. Cancer Cell 18, 472–484 (2010).

    CAS  PubMed  PubMed Central  Google Scholar 

  55. Lee, H. et al. BAF180 regulates cellular senescence and hematopoietic stem cell homeostasis through p21. Oncotarget 7, 19134–19146 (2016).

    PubMed  PubMed Central  Google Scholar 

  56. Chauhan, A. S. et al. STIM2 interacts with AMPK and regulates calcium-induced AMPK activation. FASEB J. 33, 2957–2970 (2019).

    CAS  PubMed  Google Scholar 

  57. Xiao, Z. D. et al. Energy stress-induced lncRNA FILNC1 represses c-Myc-mediated energy metabolism and inhibits renal tumor development. Nat. Commun. 8, 783 (2017).

    PubMed  PubMed Central  Google Scholar 

  58. Liu, X. & Gan, B. lncRNA NBR2 modulates cancer cell sensitivity to phenformin through GLUT1. Cell Cycle 15, 3471–3481 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  59. Koppula, P., Zhang, Y., Shi, J., Li, W. & Gan, B. The glutamate/cystine antiporter SLC7A11/xCT enhances cancer cell dependency on glucose by exporting glutamate. J. Biol. Chem. 292, 14240–14249 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  60. Zhang, Y., Koppula, P. & Gan, B. Regulation of H2A ubiquitination and SLC7A11 expression by BAP1 and PRC1. Cell Cycle1–11 (2019).

  61. Gan, B. et al. Lkb1 regulates quiescence and metabolic homeostasis of haematopoietic stem cells. Nature 468, 701–704 (2010).

    CAS  PubMed  PubMed Central  Google Scholar 

  62. Lin, A. et al. FoxO transcription factors promote AKT Ser473 phosphorylation and renal tumor growth in response to pharmacological inhibition of the PI3K–AKT pathway. Cancer Res. 74, 1682–1693 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  63. Gan, B., Yoo, Y. & Guan, J. L. Association of focal adhesion kinase with tuberous sclerosis complex 2 in the regulation of s6 kinase activation and cell growth. J. Biol. Chem. 281, 37321–37329 (2006).

    CAS  PubMed  Google Scholar 

  64. Gan, B., Melkoumian, Z. K., Wu, X., Guan, K. L. & Guan, J. L. Identification of FIP200 interaction with the TSC1–TSC2 complex and its role in regulation of cell size control. J. Cell Biol. 170, 379–389 (2005).

    CAS  PubMed  PubMed Central  Google Scholar 

  65. Matyash, V., Liebisch, G., Kurzchalia, T. V., Shevchenko, A. & Schwudke, D. Lipid extraction by methyl-tert-butyl ether for high-throughput lipidomics. J. Lipid Res. 49, 1137–1146 (2008).

    CAS  PubMed  PubMed Central  Google Scholar 

  66. Zhang, Y. et al. Imidazole ketone erastin induces ferroptosis and slows tumor growth in a mouse lymphoma model. Cell Chem. Biol. 26, 623–633 (2019).

    CAS  PubMed  Google Scholar 

  67. 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).

    CAS  PubMed  Google Scholar 

  68. Tautenhahn, R., Bottcher, C. & Neumann, S. Highly sensitive feature detection for high resolution LC/MS. BMC Bioinformatics 9, 504 (2008).

    PubMed  PubMed Central  Google Scholar 

  69. Chong, J. et al. MetaboAnalyst 4.0: towards more transparent and integrative metabolomics analysis. Nucleic Acids Res. 46, W486–W494 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  70. Montenegro-Burke, J. R., Guijas, C. & Siuzdak, G. METLIN: a tandem mass spectral library of standards. Methods Mol. Biol. 2104, 149–163 (2020).

    PubMed  Google Scholar 

  71. Fahy, E. et al. Update of the LIPID MAPS comprehensive classification system for lipids. J. Lipid Res. 50, S9–S14 (2009).

    PubMed  PubMed Central  Google Scholar 

  72. Wishart, D. S. et al. HMDB 4.0: the human metabolome database for 2018. Nucleic Acids Res. 46, D608–D617 (2018).

    CAS  PubMed  Google Scholar 

Download references

Acknowledgements

We thank L. Brown for providing access to the instrumentation for the lipidomics experiments. This research was supported by the Andrew Sabin Family Fellow Award and the Bridge Fund from The University of Texas MD Anderson Cancer Center (to B.G.) and grants from the National Institutes of Health (grant no. R01CA181196 to B.G.; grant nos. R35CA209896, 1R61NS109407 and P01CA087497 to B.R.S.; grant nos. R01CA166051 and R01CA181029 to L.M.). J.K.M. is supported by the Susan G. Komen PDF Basic/Translational and Clinical Funding Program (grant no. PDF17487931). T.F.W. is supported in part by the DOD (grant no. 1W81XWH-18–1–0573), the National Institutes of Health and NCI (grant no. 1R01CA215226), The Welch Foundation (grant no. Q-0007) and the McNair Medical Institute. G.R.S. is supported by a Canada Research Chair and the J. Bruce Duncan Chair in Metabolic Diseases and research grants from the Canadian Institutes of Health Research (grant no. 201709FDN-CEBA-116200) and Diabetes Canada (grant no. DI-5-17-5302-GS). B.G. is an Andrew Sabin Family Fellow. This research was also supported by the National Institutes of Health Cancer Center Support Grant P30CA016672 to The University of Texas MD Anderson Cancer Center.

Author information

Authors and Affiliations

Authors

Contributions

H.L. performed most of the experiments with assistance from Y.Z., J.K.M., J.K. and L.Z. F.Z. conducted the lipidomic analysis under the direction of B.R.S. G.R.S. provided ACC DKI MEFs. D.N. provided AMPKα1/α2L/L MEFs and the mouse model. S.T. and T.F.W. provided the inducible Cas9 vector. L.M. helped with the discussion and interpretation of results. B.G. and B.R.S. designed experiments and supervised the study. B.G. wrote most of the manuscript with assistance from H.L., F.Z. and B.R.S. All authors commented on the manuscript.

Corresponding authors

Correspondence to Brent R. Stockwell or Boyi Gan.

Ethics declarations

Competing interests

B.R.S. holds equity in and serves as a consultant to Inzen Therapeutics and is an inventor on patents and patent applications related to ferroptosis. The other authors declare no competing financial interests.

Additional information

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

Extended data

Extended Data Fig. 1 Energy stress inhibits ferroptosis.

a, Immunoblot analysis in MEFs treated with 2 μM erastin (16 h), cystine free media (8 h), 100 nM RSL3 (16 h), or 1 μM of staurosporine (STS, 2 h). b, Cell death measurement in MEFs treated with 2 μM erastin and cell death inhibitors for 16 h. Ferr-1: 1 μM ferrostatin-1; DFO: 100 μM deferoxamine; Z-V: 20 μM Z-VAD-FMK; Nec: 2 μM necrostatin-1; NAC: 5 mM N-acetyl cysteine. c, Cell death measurement in MEFs cultured in 25 or 0 mM glucose-containing medium with erastin and/or Ferrostatin-1 for the indicated times. d, Immunoblot analysis in MEFs treated as in a, or glucose starvation for 48 h. e, Cell death measurement in MEFs cultured in cystine free media with cell death inhibitors for 8 h. f, g, Intracellular ATP levels (f) and cell death measurement (g) in MEFs cultured with the indicated concentrations of glucose for 16 h. hk, The measurement of cell death (h, j) and lipid peroxidation (i, k) in Caki-1 or BJ cells. Cells were treated with A769662 (200 μM), AICAR (2 mM), 2DG (5 mM), 0 mM glucose with simultaneous treatment of 2 μM erastin for 24 h (cell death) and 16 h (Lipid peroxidation). P values correspond to the comparison between control and each treatment in red bars. l, Immunoblot showing the levels of AMPK T172 phosphorylation. MEFs cells were treated as in hk and compound C (5 μM) for 16 h. m, Cell death measurement in AMPK WT and DKO MEFs treated with 2 μM erastin and 2 mM of AICAR for 16 h. n, Cell death measurement in AMPK WT and DKO MEFs treated with erastin at the indicated concentrations for 16 h. P values correspond to the comparison between AMPK WT and DKO at indicated erastin concentrations. Data show the mean ± s.d., n = 3 independent experiments. Statistical analysis was performed using unpaired, two-tailed t-test. Numerical source data are provided in Source Data Extended Data Fig. 1. Scanned images of unprocessed blots are shown in Source Data Extended Data Fig. 1.

Source data

Extended Data Fig. 2 AMPK inactivation renders cells sensitive to ferroptotic cell death.

a, Western blot showing the levels of ACC (S79) and AMPK (T172) phosphorylation in ACHN cells treated with erastin for 24 h or cultured in cystine-free media for 36 h with and without compound C (10 μM). b, Cell death measurement in AMPK WT and DKO ACHN cell lines treated with 100 nM RSL3 for 16 h. c, d, Cell death measurement in RCC4 cells treated with 10 μM of compound C, cell death inhibitors, and 5 μM of erastin for 24 h (c) or in cystine free media for 36 h (d). Ferr-1: 1 μM ferrostatin-1; Z-V: 20 μM Z-VAD-FMK; Nec: 2 μM necrostatin-1; NAC: 5 mM N-acetyl cysteine. e, Western blot showing the AMPK expression in RCC4 cell as indicated. fh, Cell death measurement in AMPK WT and DKO RCC4 cell lines treated with 5 μM of erastin for 24 h (f), cultured in cystine free media for 24 h (g), or treated with 100 nM of RSL3 for 24 h (h). ik, Lipid peroxidation measurement in AMPK WT and DKO RCC4 cells treated with 5 μM of erastin for 18 h (i), cultured in cystine free media for 18 h (j), or treated with 100 nM of RSL3 for 12 h (k). l, Cell death measurement in indicated RCC4 cells cultured with cystine free media for 24 h. Data show the mean ± s.d., n = 3 independent experiments. Statistical analysis was performed using unpaired, two-tailed t-test. Numerical source data are provided in Source Data Extended Data Fig. 2. Scanned images of unprocessed blots are shown in Source Data Extended Data Fig. 2.

Source data

Extended Data Fig. 3 AMPK regulates ferroptosis partly through AMPK-mediated phosphorylation of ACC.

a, Immunoblot blot indicating the loss of LKB1 in LKB1 KO ACHN cells generated using CRISPR/CAS9 system. b, Cell death in LKB1 WT and KO ACHN cells treated with 2 μM of erastin for 24 h and cultured in cystine free media for 24 h. c, Immunoblot blot showing mTOR inhibition in MEFs treated with rapamycin for 8 h. d, Cell death in MEFs treated with 2 μM of erastin and rapamycin for 16 h. e, The measurement of L-[14C] Cystine uptake in AMPK WT and DKO ACHN cells. f, g, The measurement of L-[14C] Cystine uptake in Caki-1 (f) and BJ (g) cells treated with 2 mM AICAR and 5 mM 2DG for 6 h. h, The histograms and bar graphs showing the levels of intracellular labile iron in AMPK WT and DKO ACHN cells. i, Cell death measurement in MEFs treated with different TOFA concentrations and 2 μM erastin. P values correspond to the comparison between 0 μM and different conentrations of TOFA under erastin treatment. j, k, Cell death measurement in Caki-1 (j) and BJ (k) cells treated with 2 μM erastin and 50 μM TOFA for 24 h. l, m, The intracellular levels of the indicated free fatty acids in MEFs treated with vehicle or 25 μM of TOFA for 8 h (l) and treated with vehicle, 2 mM AICAR, or 0 mM glucose for 8 h (m). Data show the mean ± s.d., n = 3 independent experiments. Statistical analysis was performed using unpaired, two-tailed t-test. Numerical source data are provided in Source Data Extended Data Fig. 3. Scanned images of unprocessed blots are shown in Source Data Extended Data Fig. 3.

Source data

Extended Data Fig. 4 Lipidomic analyses upon AMPK activation or inactivation.

a, b, Schematic diagram of the experimental design of mass spectrometry-based lipidomic analysis associated with AMPK activation. Global lipidomic analysis was performed in MEFs treated with vehicle, 2 μM erastin, 200 μM A769662, or 2 μM erastin + 200 μM A769662 for 8 h (a) or in AMPK WT and DKO ACHN cells treated with vehicle or 2 μM erastin for 11 h (b). There are three biologically independent samples (Rep. 1–3) in each group (a) and four biologically independent samples (Rep. 1–4) in each group (b). Samples ran in duplicates (two technical replicates: A, B) on the UPLC-MS. c, d, Heat map of significantly changed lipid species (One-way ANOVA, FDR corrected p-value < 0.05) in MEFs treated with vehicle, 2 μM erastin, 200 μM A769662, or 2 μM erastin + 200 μM A769662 (c) or in AMPK WT and DKO ACHN cells treated with vehicle or 2 μM erastin (d) combined in both positive and negative ionization modes. Each row represents z-score-normalized intensities of the detected lipid species. Each column represents a sample. The relative abundance of each lipid is color-coded with red indicating high signal intensity and blue indicating low signal intensity. (FA, free fatty acid; Cer, ceramide; PC, phosphatidylcholine; LysoPC, lysophosphatidylcholine; PC O, ether-linked PC; PC P, plasmalogen PC; LysoPC O, ether-linked LysoPC; PE, phosphatidylethanolamine; LysoPE, lysophosphatidylethanolamine; PE O, ether-linked PE; PE P, plasmalogen PE; LysoPE O, ether-linked LysoPE; LysoPE P, plasmalogen LysoPE P; PG, phosphatidylglycerol; LysoPG, lyso phosphatidylglycerol; PI, phosphatidylinositol; LysoPI, lyso phosphatidylinositol; PA, phosphatidic acid; PS, phosphatidylserine; TAG, triacylglycerol; CE, cholesteryl ester. Lipids are annotated based on the fatty acyl compositions (for example LysoPC 16:0, 16 carbons and 0 double bond) or as sum of total number of carbons and double bonds (for example TAG 52:5, total of 52 carbons and 5 double bonds).

Extended Data Fig. 5 The levels of fatty acids were altered by AMPK activation or inactivation.

a, List of 17 lipid species significantly changed (Two-tailed, unpaired Welch’s t-test, Fold change ≥ 1.5 and FDR-corrected p-value < 0.05) in both MEFs (vehicle versus A769662) and ACHN (AMPK WT versus DKO) cells. Refer to Extended Data Fig. 4 for detailed sample information. b, c, The relative signal intensities of the indicated free fatty acids involved in long chain fatty acid biosynthesis in MEFs (b) or ACHN (c) cells with the indicated treatment and genotypes. Data show the mean ± s.d., n = 6 (b) or n = 8 (c) independent experiments. Statistical analysis was performed using unpaired, two-tailed t-test. Numerical source data are provided in Source Data Extended Data Fig. 5.

Source data

Extended Data Fig. 6 AMPK activation suppresses PUFA biosynthesis.

a, b, The relative signal intensities of PE 18:0_20:4 and PE 18:0_22:4 in MEFs treated with A769662 (a) or AMPK WT and DKO ACHN cells (b). c, Immunoblot indicating the loss of ACSL4 in AMPK DKO ACHN cells. The experiment was repeated twice, independently, with similar results. d, Cell death in AMPK DKO ACHN cells with ACSL4 WT and KO upon treatment of 2 μM erastin. e, f, The relative signal intensities of PE 18:0_22:4 (e) and PE 18:0_20:4 (f) in ACHN cells treated with 20 μM dihomo-γ-linolenic acid or arachidonic acid for 42 h. g, h, Cell viability measurement in ACHN cells incubated with palmitic acid (g) or stearic acid (h) with a series of concentration (0 μM-40 μM) and treated with or without ferrostatin-1 (Ferr-1) or erastin as indicated. i, Heat map of significantly changed lipid species (One-way ANOVA, FDR corrected p-value < 0.05) in MEFs treated with vehicle, 25 μM TOFA, 2 μM erastin, or 25 μM TOFA + 2 μM erastin combined positive and negative ionization modes. There are three biologically independent samples in each group and the samples analyzed in duplicates (technical replicates) on the UPLC-MS. Each row represents z-score-normalized relative signal intensities of the identified lipid species. Each column represents a sample. The relative abundance of each lipid is color-coded with red indicating high signal intensity and blue indicating low signal intensity. j, The relative signal intensities of the indicated fatty acids in MEFs treated with vehicle or 25 μM TOFA. Data show the mean ± s.d., n = 3 (d, g, h), n = 6 (a, e, f, j) or n = 8 (b) independent experiments. Statistical analysis was performed using unpaired, two-tailed t-test. Scanned images of unprocessed blots are shown in Source Data Extended Data Fig. 6. Numerical source data are provided in Source Data Extended Data Fig. 6.

Source data

Extended Data Fig. 7 Lipidomics analysis in MEFs treated with A769662 or TOFA.

a, b, The relative signal intensities of the same PUFA-containing PEs in MEFs treated with 25 μM TOFA (a) or 200 μM A769662 (b). c, d, The relative signal intensities of TAGs with the same number of carbons and double bonds in MEFs treated with 25 μM TOFA (c) or 200 μM A769662 (d). Data show the mean ± s.d., n = 6 independent experiments. Statistical analysis was performed using unpaired, two-tailed t-test. Numerical source data are provided in Source Data Extended Data Fig. 7.

Source data

Extended Data Fig. 8 Renal ischemia reperfusion injury in in AMPK α1/α2L/L or AMPKα1/α2L/L, Rosa26-CreERT2 mice.

a, Immunoblot showing the levels of AMPK α expression in kidneys of three individual AMPK α1/α2L/L or AMPKα1/α2L/L, Rosa26-CreERT2 mice (referred to as AMPK WT and KO mice). The experiment was repeated three times, independently, with similar results. b, Representative images of hematoxylin and eosin (H&E) staining of the renal cortex in sham-treated and IR-operated AMPK WT or DKO mice. Damaged renal tubules are marked by black dotted lines. Scale bars, 50 μm. The experiment was repeated more than ten times, independently, with similar results. c, Representative images of H&E staining and immunohistochemical staining of 4-HNE from mouse renal cortex after IR. Damaged renal tubules are marked with black dotted lines and 4-HNE stained tubules are marked with red dotted lines. Scale bars, 50 μm. The experiment was repeated more than ten times, independently, with similar results. d, e, Representative images showing MDA immunohistochemical staining from mouse renal cortex with the indicated genotypes and treatment conditions (d; dark brown stained tubules indicate MDA positive staining, Scale bars, 50 μm). Bar graphs presenting the percentages of MDA positive tubules per visual field (e). Data show the mean ± s.d., n = 4 (AICAR) or n = 5 (vehicle) independent experiments. Statistical analysis was performed using unpaired, two-tailed t-test. Scanned images of unprocessed blots are shown in Source Data Extended Data Fig. 8. Numerical source data are provided in Source Data Extended Data Fig. 8.

Source data

Extended Data Fig. 9 A schematic model describing the roles of AMPK-mediated energy stress signaling in regulating ferroptosis.

See discussion for the detailed description. ACC: acetyl-CoA carboxylase; PUFAs: polyunsaturated fatty acids; AA: arachidonic acid; PUFA-PLs: polyunsaturated fatty acid-containing phospholipids; ACSL4: acyl-CoA synthetase long chain family member 4; LPCAT3: lysophosphatidylcholine acyltransferase 3; 15-LOX: 15-lipoxygenase.

Supplementary information

Source data

Source Data Fig. 1

Statistical source data

Source Data Fig. 1

Unprocessed western blots

Source Data Fig. 2

Statistical source data

Source Data Fig. 2

Unprocessed western blots

Source Data Fig. 3

Statistical source data

Source Data Fig. 3

Unprocessed western blots

Source Data Fig. 4

Statistical source data

Source Data Fig. 4

Unprocessed western blots

Source Data Fig. 5

Statistical source data

Source Data Fig. 6

Statistical source data

Source Data Fig. 6

Unprocessed western blots

Source Data Extended Data Fig. 1

Statistical source data

Source Data Extended Data Fig. 1

Unprocessed western blots

Source Data Extended Data Fig. 2

Statistical source data

Source Data Extended Data Fig. 2

Unprocessed western blots

Source Data Extended Data Fig. 3

Statistical source data

Source Data Extended Data Fig. 3

Unprocessed western blots

Source Data Extended Data Fig. 5

Statistical source data

Source Data Extended Data Fig. 6

Statistical source data

Source Data Extended Data Fig. 6

Unprocessed western blots

Source Data Extended Data Fig. 7

Statistical source data

Source Data Extended Data Fig. 8

Statistical source data

Source Data Extended Data Fig. 8

Unprocessed western blots

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Lee, H., Zandkarimi, F., Zhang, Y. et al. Energy-stress-mediated AMPK activation inhibits ferroptosis. Nat Cell Biol 22, 225–234 (2020). https://doi.org/10.1038/s41556-020-0461-8

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41556-020-0461-8

This article is cited by

Search

Quick links

Nature Briefing: Cancer

Sign up for the Nature Briefing: Cancer newsletter — what matters in cancer research, free to your inbox weekly.

Get what matters in cancer research, free to your inbox weekly. Sign up for Nature Briefing: Cancer