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Non-canonical function of IRE1α determines mitochondria-associated endoplasmic reticulum composition to control calcium transfer and bioenergetics

Nature Cell Biology volume 21, pages 755–767 (2019)Cite this article

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A Publisher Correction to this article was published on 14 June 2019

This article has been updated

Abstract

Mitochondria-associated membranes (MAMs) are central microdomains that fine-tune bioenergetics by the local transfer of calcium from the endoplasmic reticulum to the mitochondrial matrix. Here, we report an unexpected function of the endoplasmic reticulum stress transducer IRE1α as a structural determinant of MAMs that controls mitochondrial calcium uptake. IRE1α deficiency resulted in marked alterations in mitochondrial physiology and energy metabolism under resting conditions. IRE1α determined the distribution of inositol-1,4,5-trisphosphate receptors at MAMs by operating as a scaffold. Using mutagenesis analysis, we separated the housekeeping activity of IRE1α at MAMs from its canonical role in the unfolded protein response. These observations were validated in vivo in the liver of IRE1α conditional knockout mice, revealing broad implications for cellular metabolism. Our results support an alternative function of IRE1α in orchestrating the communication between the endoplasmic reticulum and mitochondria to sustain bioenergetics.

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Fig. 1: IRE1α is located at MAMs and enhances mitochondrial calcium uptake.
Fig. 2: IRE1α expression bursts basal mitochondrial bioenergetics.
Fig. 3: IRE1α controls the distribution of InsP3Rs at MAMs.
Fig. 4: IRE1α physically interacts with InsP3Rs and controls mitochondrial calcium uptake independent of its enzymatic activities.
Fig. 5: Upregulation of endogenous InsP3Rs rescue mitochondrial calcium uptake in IRE1α-deficient cells.
Fig. 6: IRE1α is required for the localization of InsP3R1 at MAMs in vivo.
Fig. 7: IRE1α expression regulates liver metabolism.

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Data availability

Mass spectrometry data have been deposited in ProteomeXchange (PXD013313). Metabolomics data have been deposited as a Mendeley dataset at https://data.mendeley.com/ (https://doi.org/10.17632/dtdf7wk3mb.1). Source data for Figs. 1–7 and for Supplementary Figs. 1–4 and 7 have been provided in Supplementary Table 6. Source data for Fig. 6 and Supplementary Fig. 6 have been provided in Supplementary Tables 3 and 4. Source data for Fig. 7 and Supplementary Fig. 7 can be found in Supplementary Table 5. All data that support the findings of this study are available from the corresponding author on reasonable request.

Change history

  • 04 June 2019

    An incorrect supplementary file was initially published with this article. The correct file has now been uploaded.

  • 14 June 2019

    An amendment to this paper has been published and can be accessed via a link at the top of the paper.

References

  1. Rwland, A. A. & Voeltz, G. K. Endoplasmic reticulum–mitochondria contacts: function of the junction. Nat. Rev. Mol. Cell Biol. 13, 607–625 (2012).

    Article  Google Scholar 

  2. Wang, M. & Kaufman, R. J. Protein misfolding in the endoplasmic reticulum as a conduit to human disease. Nature 529, 326–335 (2016).

    Article  CAS  PubMed  Google Scholar 

  3. Hetz, C. & Papa, F. R. The unfolded protein response and cell fate control. Mol. Cell 69, 169–181 (2018).

  4. Oakes, S. A. & Papa, F. R. The role of endoplasmic reticulum stress in human pathology. Annu. Rev. Pathol. Mech. Dis. 10, 173–194 (2015).

    Article  CAS  Google Scholar 

  5. Wu, H., Carvalho, P. & Voeltz, G. K. Here, there, and everywhere: the importance of ER membrane contact sites. Science 361, eean5835 (2018).

    Article  Google Scholar 

  6. Gutiérrez, T. & Simmen, T. Endoplasmic reticulum chaperones tweak the mitochondrial calcium rheostat to control metabolism and cell death. Cell Calcium 70, 64–75 (2017).

    Article  PubMed  Google Scholar 

  7. Carreras-Sureda, A., Pihán, P. & Hetz, C. Calcium signaling at the endoplasmic reticulum: fine-tuning stress responses. Cell Calcium 70, 24–31 (2017).

    Article  PubMed  Google Scholar 

  8. Phillips, M. J. & Voeltz, G. K. Structure and function of ER membrane contact sites with other organelles. Nat. Rev. Mol. Cell Biol. 17, 69–82 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  9. Rizzuto, R., De Stefani, D., Raffaello, A. & Mammucari, C. Mitochondria as sensors and regulators of calcium signalling. Nat. Rev. Mol. Cell Biol. 13, 566–578 (2012).

    Article  CAS  PubMed  Google Scholar 

  10. Giorgi, C., Marchi, S. & Pinton, P. The machineries, regulation and cellular functions of mitochondrial calcium. Nat. Rev. Mol. Cell Biol. 19, 713–730 (2018).

    Article  CAS  PubMed  Google Scholar 

  11. Izzo, V., Bravo-San Pedro, J. M., Sica, V., Kroemer, G. & Galluzzi, L. Mitochondrial permeability transition: new findings and persisting uncertainties. Trends Cell Biol. 26, 655–667 (2016).

    Article  CAS  PubMed  Google Scholar 

  12. de Brito, O. M. & Scorrano, L. Mitofusin 2 tethers endoplasmic reticulum to mitochondria. Nature 456, 605–610 (2008).

    Article  PubMed  Google Scholar 

  13. Ngoh, G. A., Papanicolaou, K. N. & Walsh, K. Loss of mitofusin 2 promotes endoplasmic reticulum stress. J. Biol. Chem. 287, 20321–20332 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Muñoz, J. P. & Zorzano, A. Mfn2 modulates the unfolded protein response. Cell Cycle 13, 491–492 (2014).

    Article  PubMed  Google Scholar 

  15. Carreras-Sureda, A., Pihán, P. & Hetz, C. The unfolded protein response: at the intersection between endoplasmic reticulum function and mitochondrial bioenergetics. Front. Oncol. 7, 55 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  16. Verfaillie, T. et al. PERK is required at the ER-mitochondrial contact sites to convey apoptosis after ROS-based ER stress. Cell Death Differ. 19, 1880–1891 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Muñoz, J. P. et al. Mfn2 modulates the UPR and mitochondrial function via repression of PERK. EMBO J. 32, 2348–2361 (2013).

    Article  PubMed  PubMed Central  Google Scholar 

  18. Lebeau, J. et al. The PERK arm of the unfolded protein response regulates mitochondrial morphology during acute endoplasmic reticulum stress. Cell Rep. 22, 2827–2836 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Hetz, C. The unfolded protein response: controlling cell fate decisions under ER stress and beyond. Nat. Rev. Mol. Cell Biol. 13, 89–102 (2012).

    Article  CAS  PubMed  Google Scholar 

  20. Hayashi, T. & Su, T. P. Sigma-1 receptor chaperones at the ER-mitochondrion interface regulate Ca2+ signaling and cell survival. Cell 131, 596–610 (2007).

    Article  CAS  Google Scholar 

  21. Mori, T., Hayashi, T., Hayashi, E. & Su, T.-P. Sigma-1 receptor chaperone at the ER-mitochondrion interface mediates the mitochondrion-ER-nucleus signaling for cellular survival. PLoS ONE 8, e76941 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Wieckowski, M. R., Giorgi, C., Lebiedzinska, M., Duszynski, J. & Pinton, P. Isolation of mitochondria-associated membranes and mitochondria from animal tissues and cells. Nat. Protoc. 4, 1582–1590 (2009).

    Article  CAS  PubMed  Google Scholar 

  23. Sepulveda, D. et al. Interactome screening identifies the ER luminal chaperone Hsp47 as a regulator of the unfolded protein response transducer IRE1α. Mol. Cell 69, 238–252 (2018).

    Article  CAS  PubMed  Google Scholar 

  24. Bae, Y. S. et al. Identification of a compound that directly stimulates phospholipase C activity. Mol. Pharmacol. 63, 1043–1050 (2003).

    Article  CAS  PubMed  Google Scholar 

  25. Suzuki, J. et al. Imaging intraorganellar Ca2+ at subcellular resolution using CEPIA. Nat. Commun. 5, 4153 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Oakes, S. A. et al. Proapoptotic BAX and BAK regulate the type 1 inositol trisphosphate receptor and calcium leak from the endoplasmic reticulum. Proc. Natl Acad. Sci. USA 102, 105–110 (2005).

    Article  CAS  PubMed  Google Scholar 

  27. Thrower, E. C. et al. Interaction of luminal calcium and cytosolic ATP in the control of type 1 inositol (1,4,5)-trisphosphate receptor channels. J. Biol. Chem. 275, 36049–36055 (2000).

    Article  CAS  PubMed  Google Scholar 

  28. Imamura, H. et al. Visualization of ATP levels inside single living cells with fluorescence resonance energy transfer-based genetically encoded indicators. Proc. Natl Acad. Sci. USA 106, 15651–15656 (2009).

    Article  CAS  PubMed  Google Scholar 

  29. Mihaylova, M. M. & Shaw, R. J. The AMPK signalling pathway coordinates cell growth, autophagy and metabolism. Nat. Cell Biol. 13, 1016–1023 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Cárdenas, C. et al. Essential regulation of cell bioenergetics by constitutive InsP3 receptor Ca2+ transfer to mitochondria. Cell 142, 270–283 (2010).

    Article  PubMed  PubMed Central  Google Scholar 

  31. Friedman, J. R. et al. ER tubules mark sites of mitochondrial division. Science 334, 358–362 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Westermann, B. Bioenergetic role of mitochondrial fusion and fission. Biochim. Biophys. Acta Bioenerg. 1817, 1833–1838 (2012).

    Article  CAS  Google Scholar 

  33. Cogliati, S. et al. Mitochondrial cristae shape determines respiratory chain supercomplexes assembly and respiratory efficiency. Cell 155, 160–171 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Bravo, R. et al. Increased ER-mitochondrial coupling promotes mitochondrial respiration and bioenergetics during early phases of ER stress. J. Cell Sci. 124, 2143–2152 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Csordás, G. et al. Imaging interorganelle contacts and local calcium dynamics at the ER-mitochondrial interface. Mol. Cell 39, 121–132 (2010).

    Article  PubMed  PubMed Central  Google Scholar 

  36. Giacomello, M. & Pellegrini, L. The coming of age of the mitochondria–ER contact: a matter of thickness. Cell Death Differ. 23, 1417 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Cieri, D. et al. SPLICS: a split green fluorescent protein-based contact site sensor for narrow and wide heterotypic organelle juxtaposition. Cell Death Differ. 25, 1–15 (2017).

    Google Scholar 

  38. Xue, Z. et al. A conserved structural determinant located at the interdomain region of mammalian inositol-requiring enzyme 1α. J. Biol. Chem. 286, 30859–30866 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Fan, G. et al. Gating machinery of InsP3R channels revealed by electron cryomicroscopy. Nature 527, 336–341 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. Yamazaki, H., Chan, J., Ikura, M., Michikawa, T. & Mikoshiba, K. Tyr-167/Trp-168 in type 1/3 inositol 1,4,5-trisphosphate receptor mediates functional coupling between ligand binding and channel opening. J. Biol. Chem. 285, 36081–36091 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Kuhn, R., Schwenk, F., Aguet, M. & Rajewsky, K. Inducible gene targeting in mice. Science 269, 1427–1429 (1995).

    Article  CAS  PubMed  Google Scholar 

  42. Iwawaki, T., Akai, R., Yamanaka, S. & Kohno, K. Function of IRE1 alpha in the placenta is essential for placental development and embryonic viability. Proc. Natl Acad. Sci. USA 106, 16657–16662 (2009).

    Article  CAS  PubMed  Google Scholar 

  43. Zhang, K. et al. The unfolded protein response transducer IRE1α prevents ER stress-induced hepatic steatosis. EMBO J. 30, 1357–1375 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Sala-Vila, A. et al. Interplay between hepatic mitochondria-associated membranes, lipid metabolism and caveolin-1 in mice. Sci. Rep. 6, 27351 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Poston, C. N., Krishnan, S. C. & Bazemore-Walker, C. R. In-depth proteomic analysis of mammalian mitochondria-associated membranes (MAM). J. Proteom. 79, 219–230 (2013).

    Article  CAS  Google Scholar 

  46. Jouaville, L. S., Pinton, P., Bastianutto, C., Rutter, G. A. & Rizzuto, R. Regulation of mitochondrial ATP synthesis by calcium: evidence for a long-term metabolic priming. Proc. Natl Acad. Sci. USA 96, 13807–13812 (1999).

    Article  CAS  PubMed  Google Scholar 

  47. Tubbs, E. et al. Mitochondria-associated endoplasmic reticulum membrane (MAM) integrity is required for insulin signaling and is implicated in hepatic insulin resistance. Diabetes 63, 3279–3294 (2014).

    Article  CAS  PubMed  Google Scholar 

  48. Arruda, A. P. et al. Chronic enrichment of hepatic endoplasmic reticulum-mitochondria contact leads to mitochondrial dysfunction in obesity. Nat. Med. 20, 1427–1435 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Hetz, C., Chevet, E. & Oakes, S. A. Proteostasis control by the unfolded protein response. Nat. Cell Biol. 17, 829–838 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Hetz, C. & Glimcher, L. H. Fine-tuning of the unfolded protein response: assembling the IRE1alpha interactome. Mol. Cell 35, 551–561 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  51. Arruda, A. P. & Hotamisligil, G. S. Calcium homeostasis and organelle function in the pathogenesis of obesity and diabetes. Cell Metab. 22, 381–397 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  52. Fink, E. E. et al. XBP1-KLF9 axis acts as a molecular rheostat to control the transition from adaptive to cytotoxic unfolded protein response. Cell Rep. 25, 212–223 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  53. Song, M. et al. IRE1α–XBP1 controls T cell function in ovarian cancer by regulating mitochondrial activity. Nature 562, 423–428 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  54. Calfon, M. et al. IRE1 couples endoplasmic reticulum load to secretory capacity by processing the XBP-1 mRNA. Nature 415, 92–96 (2002).

    Article  CAS  PubMed  Google Scholar 

  55. Rodriguez, D. A. et al. BH3-only proteins are part of a regulatory network that control the sustained signalling of the unfolded protein response sensor IRE1α. EMBO J. 31, 2322–2335 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  56. Hetz, C. et al. Proapoptotic BAX and BAK modulate the unfolded protein response by a direct interaction with IRE1α. Science 312, 572–576 (2006).

    Article  CAS  PubMed  Google Scholar 

  57. Ryno, L. M. et al. Characterizing the altered cellular proteome induced by the stress-independent activation of heat shock factor 1. ACS Chem. Biol. 9, 1273–1283 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  58. Parys, J. B. et al. Rat basophilic leukemia cells as model system for inositol 1,4,5-trisphosphate receptor IV, a receptor of the type II family: functional comparison and immunological detection. Cell Calcium 17, 239–249 (1995).

    Article  CAS  PubMed  Google Scholar 

  59. Wuytack, F., Eggermont, J. A., Raeymaekers, L., Plessers, L. & Casteels, R. Antibodies against the non-muscle isoform of the endoplasmic reticulum Ca2(+)-transport ATPase. Biochem. J. 264, 765–769 (1989).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  60. Nixon-Abell, J. et al. Increased spatiotemporal resolution reveals highly dynamic dense tubular matrices in the peripheral ER. Science 354, aaf3928 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  61. Tovey, S. C. & Taylor, C. W. High-throughput functional assays of IP3-evoked Ca2+ release. Cold Spring Harb. Protoc. 2013, 930–937 (2013).

    Article  PubMed  Google Scholar 

  62. Luyten, T., Bultynck, G., Parys, J. B., De Smedt, H. & Missiaen, L. Measurement of intracellular Ca2+ release in permeabilized cells using 45Ca2+. Cold Spring Harb. Protoc. 2014, 289–294 (2014).

    PubMed  Google Scholar 

  63. Xian, S., Shang, D., Kong, G. & Tian, Y. FOXJ1 promotes bladder cancer cell growth and regulates Warburg effect. Biochem. Biophys. Res. Commun. 495, 988–994 (2018).

    Article  CAS  PubMed  Google Scholar 

  64. Jara, C., Aránguiz, A., Cerpa, W., Tapia-Rojas, C. & Quintanilla, R. A. Genetic ablation of tau improves mitochondrial function and cognitive abilities in the hippocampus. Redox Biol. 18, 279–294 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  65. Pietrocola, F. et al. Metabolic effects of fasting on human and mouse blood in vivo. Autophagy 13, 567–578 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  66. Xia, J. & Wishart, D. S. Web-based inference of biological patterns, functions and pathways from metabolomic data using MetaboAnalyst. Nat. Protoc. 6, 743–760 (2011).

    Article  CAS  PubMed  Google Scholar 

Download references

Acknowledgements

We thank S. Lavandero, D. Rojas-Rivera and M. Chiong for initial feedback in this project and for sharing reagents, T. Iwawaki for providing IRE1α null animals and L. Qi for providing IRE1α mutant constructs, G. Hajnoczky for MAM linker constructs, T. Calì and M. Brini for the SPLICS constructs, D. Ron for providing IRE1α null MEFs, J. Ponce for animal care, and N. Bossut, F. Aprahamian, A. Florizoone, M. Crabbe, K. Welkenhuyzen, C. Villablanca, T. Vervliet and T. Luyten for their support. This work was funded by FONDECYT 1140549, FONDAP program 15150012, the Millennium Institute P09-015-F and the European Commission R&D MSCA-RISE 734749 (to C.H.); the Michael J. Fox Foundation for Parkinson’s Research target validation grant number 9277, FONDEF ID16I10223, FONDEF D11E1007, US Office of Naval Research-Global N62909-16-1-2003, US Air Force Office of Scientific Research FA9550-16-1-0384, ALSRP Therapeutic Idea Award AL150111, Muscular Dystrophy Association 382453, Seed grant Leading House for the Latin American Region, Switzerland and CONICYT-Brazil 441921/2016-7 (to C.H.), FONDECYT 1160332 and FONDAP15150012 (to J.C.C.); the Spanish Ministry of Economy and Competitiveness SAF2014-52228-R, Unidad de Excelencia María de Maeztu, funded by the MINECO (ref: MDM-2014-0370) and Fundació la Marató de TV3 20134030 (to R.V.); NIH NS095892 (to R.L.W.); FONDECYT 11180825 (to H.U.); FONDECYT 3150113 and EMBO ASTF 385-2016 (to A.C.-S.); FONDECYT 3140355 (to E.R.-F.); FONDECYT 3140458 and 11170291 (to F.J.); FONDECYT 3180427 (to Y.H.); FONDECYT 3190738 (to A.S.-C.); FONDECYT 11170546 and CONICYT PAI 77170091 (to C.T.-R.); R01DK113171, R01CA198103 and R01DK103185 (to R.J.K.); FONDECYT 1150766 (to F.A.C.); the Research Council KU Leuven grant OT14/101 (to G.B.); the Research Foundation – Flanders (FWO) G.0C91.14N, G.0A34.16N and the FWO Scientific Research Community “Ca2+ signaling in health, disease and therapy” W0.019.17 (to G.B.); FWO (G049817N, G076617N) and KU Leuven (C16/15/073) (to P.A.); a FWO doctorate fellowship (to M.K.); the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant 675448 (to M.L.S.); CONICYT fellowship PCHA/Doctorado Nacional/2016-21160232 (to M.G.-Q.); the George E. Hewitt Foundation for a postdoctoral fellowship (to D.E.M.); Ligue contre le Cancer (équipe labellisée); Agence National de la Recherche – Projets blancs; under the frame of E-Rare-2, the ERA-Net for Research on Rare Diseases; Association pour la recherche sur le cancer; Cancéropôle Ile-de-France; Chancelerie des universités de Paris (Legs Poix), Fondation pour la Recherche Médicale; a donation from Elior; the European Research Area Network on Cardiovascular Diseases (MINOTAUR), Gustave Roussy Odyssea, the European Union Horizon 2020 Project Oncobiome; Fondation Carrefour; High-end Foreign Expert Program in China (GDW20171100085); Institut National du Cancer; Inserm (HTE); Institut Universitaire de France; LeDucq Foundation; the LabEx Immuno-Oncology; the RHU Torino Lumière; the Seerave Foundation; the SIRIC Stratified Oncology Cell DNA Repair and Tumor Immune Elimination; and the SIRIC Cancer Research and Personalized Medicine (to G.K.).

Author information

Authors and Affiliations

  1. Biomedical Neuroscience Institute, Faculty of Medicine, University of Chile, Santiago, Chile

    Amado Carreras-Sureda, Hery Urra, Alfredo Sagredo, Younis Hazari, Philippe Pihán, Matías González-Quiroz & Claudio Hetz

  2. FONDAP Geroscience Center for Brain Health and Metabolism, Santiago, Chile

    Amado Carreras-Sureda, Fabián Jaña, Hery Urra, Alfredo Sagredo, Galdo Bustos, Younis Hazari, Philippe Pihán, Matías González-Quiroz, Christian Gonzalez-Billault, Felipe A. Court, J. César Cárdenas & Claudio Hetz

  3. Program of Cellular and Molecular Biology, Institute of Biomedical Sciences, University of Chile, Santiago, Chile

    Amado Carreras-Sureda, Hery Urra, Alfredo Sagredo, Younis Hazari, Philippe Pihán, Matías González-Quiroz & Claudio Hetz

  4. Anatomy and Developmental Biology Program, Institute of Biomedical Sciences, University of Chile, Santiago, Chile

    Fabián Jaña, Galdo Bustos & J. César Cárdenas

  5. Equipe Labellisée par la Ligue contre le cancer, Université Paris Descartes, Université Sorbonne Paris Cité, Université Paris Diderot, Sorbonne Université, INSERM U1138, Centre de Recherche des Cordeliers, Paris, France

    Sylvere Durand & Guido Kroemer

  6. Metabolomics and Cell Biology Platforms, Institut Gustave Roussy, Villejuif, France

    Sylvere Durand & Guido Kroemer

  7. Department of Molecular Medicine, The Scripps Research Institute, La Jolla, CA, USA

    David E. Mortenson & R. Luke Wiseman

  8. Center for Integrative Biology, Faculty of Sciences, Universidad Mayor, Santiago, Chile

    Galdo Bustos, Felipe A. Court & J. César Cárdenas

  9. Center for Aging and Regeneration, Department of Cell and Molecular Biology, Faculty of Biological Sciences, Pontifical Catholic University of Chile, Santiago, Chile

    Eva Ramos-Fernández & Nibaldo C. Inestrosa

  10. Laboratory of Cell Death Research and Therapy, Department of Cellular and Molecular Medicine, VIB-KU Leuven Center for Cancer Biology, KU Leuven, Leuven, Belgium

    Maria L. Sassano, Alexander R. van Vliet & Patrizia Agostinis

  11. Laboratory of Neurobiology of Aging, Centro de Biología Celular y Biomedicina, Facultad de Medicina y Ciencia, Universidad San Sebastián, Santiago, Chile

    Angie K. Torres & Cheril Tapia-Rojas

  12. Laboratory of Molecular and Cellular Signaling, Department of Cellular and Molecular Medicine and Leuven Kanker Instituut, KU Leuven, Leuven, Belgium

    Martijn Kerkhofs

  13. Laboratory of Molecular Physiology, Department of Experimental and Health Sciences, Universitat Pompeu Fabra, Barcelona, Spain

    Rubén Vicente

  14. Degenerative Diseases Program, Sanford Burnham Prebys Medical Discovery Institute, La Jolla, CA, USA

    Randal J. Kaufman & Geert Bultynck

  15. Buck Institute for Research on Aging, Novato, CA, USA

    Christian Gonzalez-Billault & Claudio Hetz

  16. Department of Biology, Faculty of Sciences, University of Chile, Santiago, Chile

    Christian Gonzalez-Billault

  17. Pôle de Biologie, Hôpital Européen Georges Pompidou, AP-HP, Paris, France

    Guido Kroemer

  18. Karolinska Institute, Department of Women’s and Children’s Health, Karolinska University Hospital, Stockholm, Sweden

    Guido Kroemer

  19. Suzhou Institute for Systems Biology, Chinese Academy of Sciences, Suzhou, China

    Guido Kroemer

  20. Department of Chemistry and Biochemistry, University of California, Santa Barbara, CA, USA

    J. César Cárdenas

  21. Department of Immunology and Infectious Diseases, Harvard School of Public Health, Boston, MA, USA

    Claudio Hetz

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  1. Amado Carreras-Sureda
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C.H. and A.C.-S. designed the study. A.C.-S., F.J., H.U., S.D., D.E.M., A.S.-C., G.B., Y.H., E.R.-F., P.P., A.R.v.V., M.G.-Q., M.K., A.K.T., M.L.S., C.T.-R. and R.V. performed the experiments and analysed the data. A.C.-S., R.J.K., N.C.I., R.L.W., P.A., G.B., C.G.-B., F.A.C., G.K., J.C.C. and C.H., supervised the experiments and participated in their design. C.H. and A.C.-S. wrote the manuscript. All authors read and approved the final version of the manuscript.

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Correspondence to Claudio Hetz.

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Integrated supplementary information

Supplementary Figure 1 IRE1α is located at MAMs and regulates ER to mitochondria communication.

(A) IRE1α-KO cells reconstituted with IRE1α-HA or empty vector (Mock), processed for (WB) for the indicated proteins. Bottom: RT-PCR for Xbp1 mRNA splicing after 8 h of 0.5 µg/ml tunicamycin (Tm) treatment (n = 3 independent experiments). (B) CRISPR control and IRE1α KO cells, or an additional set of cells (C) were analysed as described in A (n =3 independent experiments). (D-E) CRISPR control and IRE1α KO (clone 2) cells imaged for calcium levels in the cytosol and mitochondria (arrow = 100 µM ATP). Right: maximum peak for normalized Fura2 were quantified (total cells analysed: Control 2: n = 45; IRE1α 2: n = 75). (F) WB analysis for the indicated proteins of cells described in 1G normalized to GAPDH (IP3R1: n = 6; IP3R3: n = 7: SERCA2b: n = 4; MCU: n = 7; VDAC1: n = 6; all n are biologically independent). (G) CRISPR control and IRE1α KO cells were processed as indicated in F (IP3R1: n = 5; IP3R3: n = 5; SERCA2b: n = 4; MCU: n = 3; VDAC1: n = 3; all n are biologically independent samples). (H-I) Same cells as in F were simultaneously imaged for calcium levels as in D-E (arrow = 50 µM 3M3FBS) (cells analysed: Mock: n = 93; IRE1α-HA: n = 97) (J) Maximum peak from Fura2/Rhod2 measurements from same samples as in Fig. 1e, f calculated with non-linear regression analyses to obtain correlation constant (K). (K-L) Cells were loaded with 45Ca2+ to determine ER 45Ca2+ loading at steady-state levels (K, n = 8 independent experiments) or after 5-10 minutes of 45Ca2+ loading (L, n = 4 independent experiments). (M) Unidirectional 45Ca2+ efflux from the ER loaded to 45Ca2+ steady-state levels. Graph displays normalized ER 45Ca2+ content (%) over time (n = 8 independent experiments). (N) Resting Fura2-AM ratio (340/405) measurements for the indicated cell lines (cells analysed: Mock: n = 99; IRE1α-HA: n = 109). All plots represent mean and SEM. Statistical differences were detected with unpaired two-tail Student´s t-test or Two-way ANOVA (L). Source data have been provided in Supplementary Table 6.

Supplementary Figure 2 Altered mitochondrial bioenergetics in IRE1α deficient cells.

(A) ATP measurement in the indicated cell lines with a luminescence assay (n = 18 biologically independent samples). (B) Indicated cell lines imaged using AT01 cytosolic FRET probe. Scale bar = 20 µm (total cells analysed: Mock: n = 91 cells; IRE1α-HA: n = 62 cells). (C) Indicated cells were processed for WB analysis to measure pAMPK followed by quantification using total AMPK (dashed line indicated spliced gel to avoid irrelevant lanes) (n = 6 biologically independent samples). (D) Indicated cells were imaged for LC3-II immunofluorescence and confocal microscopy after 6 h treatment with or without 2 h pre-exposure to starvation (CLQ = 1 µM chloroquine, BAF = 0.1 µM bafilomycin A1). Right panel: LC3-II dot count per cell were quantified (n = 3 independent experiments; total cells analysed from left to right: 67; 89; 65; 99; 70; 91; 80; 91; 51; 103; 69; 96). Scale bar = 20 µm). (E) ATP determination of cells described in B with the indicated treatments after 24 h of 1 µM CLQ (n = 17 biologically independent samples). (F) Same cells as in E imaged with TEM. Scale bar = 4 µm. Graph bars representing the area and circularity for the indicated conditions (control: n = 55 cells; IRE1α: n = 60 cells). (G) Live imaging of CRISPR IRE1α KO cells transiently expressing KDEL-RFP with IRE1α-HA or Mock. Graph bars represent the mean for the indicated parameter (n = 3 independent experiments, Scale bar = 10 µm). (H-I) Indicated cells were imaged with TEM. Scale bar = 200 nm. Distance between cristae was determined (total mitochondria analysed: Mock: n = 36; IRE1α-HA: n = 35; Control: n = 32; IRE1α: n = 32). (J) Summary of two different approximations to quantify MAM length. (K) ER longitudinal contact distance (red arrows) was measured by the 2 approaches described in J (n = 3 independent experiments). Scale bar = 500 nm. (Total events analysed: CRISPR control: n = 17 contacts; CRISPR IRE1α: n = 28 contacts). All plots represent mean and SEM. Unpaired or paired (K) Student´s t-test was used. Source data have been provided in Supplementary Table 6.

Supplementary Figure 3 IRE1α modulates mitochondrial bioenergetics under ER stress.

(A) ATP measurements in cells treated with 100 ng/ml tunicamycin (Tm) for the indicated times (NT: n = 18; 4h: n = 12; 24h: n = 8; all n are biologically independent experiments). (B) IRE1α KO cells reconstituted with IRE1α-HA or Mock or CRISPR cells (C) were processed for western blot analyses to monitor levels of indicated proteins. Cells were treated with 100 ng/ml Tm for the indicated times (n = 3 independent experiments). (D) IRE1α KO cells were reconstituted with IRE1α-HA and processed to obtain purified MAM fractions after 4 h treatment with 1 µg/ml Tm. Fractions were analysed by western blot (WB) for indicated UPR and MAM markers (Cr: crude mitochondria; H: homogenate; M: MAMs; P: pure mitochondria; C: cytosol; E: ER) (n = 2 independent experiments). (E) Same cells described in D were treated with 0.1 µg/ml Tm for indicated time points and stained for ERp72, TOM20 and HA using indirect immunofluorescence. Scale bar = 20 µm. Confocal microscopy analysis and co-localization coefficient was calculated (n = 3) (total cells analysed for t = 0 and 16; n = 40; t = 8; n = 43). (F) IRE1α KO cells reconstituted with IRE1α-HA or empty vector (Mock) were processed to obtain subcellular fractions and analysed by WB to monitor the levels of indicated proteins. Right panel: quantification in the expression of IP3R3 normalized to calnexin (CNX) in the ER fraction (n = 6 independent experiments). (G) IRE1α KO cells reconstituted with IRE1α-HA or empty vector (Mock) transiently expressing control or 9x MAMs linker were imaged for TEM to measure MAMs width. Graph represents the frequency distribution of MAMs width. All plots represent mean and SEM. Statistical differences were detected with unpaired Student´s t-test; two-way ANOVA (A). Source data have been provided in Supplementary Table 6.

Supplementary Figure 4 IRE1α physically interacts with IP3R1.

(A) Left: scheme representing IRE1α structure and the different mutants used, including D123P, a deletion of the entire cytosolic region and a deletion of the entire N-terminal region. Right panel: cells stably expressing designated constructs described in were processed for western blot analysis to measure levels of indicated proteins (n = 3 independent experiments). (B) Left panels: IRE1α KO cells reconstituted with the indicated constructs were imaged for calcium levels in the cytosol (Fura2-AM) in a calcium free media (n = 4). Arrow = stimulation with 100 µM ATP. Right panel: The maximum peak for normalized Fura2-AM ratio is presented (total cells analysed: Mock: n = 99 cells; IRE1α-HA: n = 109 cells; IRE1α-D123P-HA: n = 78 cells; IRE1α-ΔN-HA: n = 92 cells and IRE1α-ΔC-HA: n = 91 cells). (C) IRE1α KO cells reconstituted with empty vector (Mock), IRE1α-HA, IRE1α-P830L-HA, or IRE1α-ΔC-HA were processed for western blot (WB) analysis to monitor the levels of indicated proteins. Dashed lines indicate cropped gels to eliminate irrelevant lanes from the same image (n = 2 independent experiments). (D) and (E) HEK 293T cells were transiently transfected with indicated constructs and immunoprecipitated (IP) with an anti-HA antibody. WB analysis was performed for the indicated proteins in IPs and total input (n = 2 independent experiments). (F) IRE1α KO cells reconstituted with IRE1α-HA or Mock were stained with PLA using antibodies to detect IP3R3 and VDAC1 proteins. Right panel: mean number of dot counts per cell were quantified (n = 2 independent experiments). All plots represent mean and SEM. Statistical differences were detected with ANOVA and Dunnett’s multiple comparison test. Source data have been provided in Supplementary Table 6.

Supplementary Figure 5 Enhanced expression of IP3R1 reverts the defects in calcium signalling observed in IRE1α null cells.

(A) IRE1α KO cells stably expressing CRa-IP3R1 or CRa-Control were imaged for calcium in the cytosol and mitochondria simultaneously with Fura2-AM and Rhodamine2N-AM (Rhod2). Integration of the maximum peak of individual cells from Fura2-AM and Rhod2-AM signals to calculate the non-linear regression k value and SEM (n = 5 independent experiments; total cells analysed: CRa-IP3R1: n = 87 cells; CRa-Control: n = 65 cells). (B) CRa-IP3R3 or CRa-Control were stained for proximity ligation assay (PLA) with anti-IP3R3 and anti-VDAC1 antibodies and visualized by confocal microscopy. Scale bar = 10 µm. Right panel: mean dots per cell were quantified (n = 2 independent experiments). Source data have been provided in Supplementary Table 6.

Supplementary Figure 6 IRE1α regulates MAMs biology in vivo.

(A) Upper panel: scheme representing Ern1 structure and deletion strategy (Ern1ΔR). Down, left: livers from Ern1 and Ern1ΔR processed for WB for the indicated proteins. Western blot (WB) is representative of a minimum of three independent experiments. Bottom panel, right: Ern1 and Ern1ΔR mice were intraperitoneally injected with 1 mg/Kg tunicamycin (Tm) or vehicle for 6 h and then Xbp1 mRNA splicing was evaluated by RT-PCR (n = 2 independent experiments). (B) Illustration of the flow chart of the MAMs proteomics. Left: representative WB of wild-type liver subcellular fractionation highlighting the MAMs fraction. Middle: silver staining of representative MAMs fractions. Right: Venn diagram representing the intersections between the hits obtained in the MAMs proteomics of this study, with two other studies, (related to Supplementary Tables 3 and 4). (C-D) Indicated liver samples were processed to obtain subcellular fractions and analysed by WB against the indicated antibodies. (C) Total extracts (Ern1 n = 6 animals; Ern1ΔK n = 5 animals). (D) ER fraction (Ern1 n = 5 animals; Ern1ΔK n = 4 animals). (E) Indicated liver samples were processed to obtain subcellular fractions and analysed by WB for the indicated markers (Cr: crude mitochondria; H: homogenate; M: MAMs; P: pure mitochondria; C: cytosol; E: ER) Representative WB of n = 3 animals. All plots represent mean and SEM. Source data have been provided in Supplementary Tables 3 and 4.

Supplementary Figure 7 IRE1α regulates cellular metabolism in vivo.

(A) Venn diagram for metabolomics data showing the overlap in metabolites altered in Ern1ΔK and Ern1ΔR. (B-C) Pathway impact probability and significant alterations in metabolites calculated with MetaboanalystR from Supplementary Table 5. (B) Altered pathways only in Ern1ΔR (n = 3 animals per group). (C) Altered pathways only in Ern1ΔR and Ern1ΔK intersection (n = 3 and 4 animals per group, respectively). (D) Complement to Fig. 7a–d: Whiskers and dot plots of indicated metabolites comparing Ern1 and Ern1ΔK liver samples (4 animals per group). (E-F) Ern1 control and Ern1ΔK liver samples were processed to obtain total tissue homogenates (E) and isolated mitochondria (F) and analysed for mitochondrial respiration (ATP levels) and ROS production (n = 3 animals per group). Statistical differences were detected with one (D) or two –tailed (B-C) Student´s t-test. Source data have been provided in Supplementary Table 5.

Supplementary Figure 8 Unprocessed images of all gels and blots.

All gels and blots presented in this work are displayed unprocessed and labeled. The name of the main figure and panel corresponds to the processed images presented in the final manuscript. Specific lanes are indicated with a blue dashed line.

Supplementary information

Supplementary Information

Supplementary Figures 1–7, titles and legends for Supplementary Tables 1–6.

Life Sciences Reporting Summary

Supplementary Table 1

ER morphological parameters.

Supplementary Table 2

MAMs morphometric values.

Supplementary Table 3

MAM total protein list.

Supplementary Table 4

MAMs consensus proteins.

Supplementary Table 5

Metabolomics data.

Supplementary Table 6

Statistics source data.

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Carreras-Sureda, A., Jaña, F., Urra, H. et al. Non-canonical function of IRE1α determines mitochondria-associated endoplasmic reticulum composition to control calcium transfer and bioenergetics. Nat Cell Biol 21, 755–767 (2019). https://doi.org/10.1038/s41556-019-0329-y

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