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Enhancing mitochondrial proteostasis reduces amyloid-β proteotoxicity

Nature volume 552, pages 187–193 (2017)Cite this article

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Abstract

Alzheimer’s disease is a common and devastating disease characterized by aggregation of the amyloid-β peptide. However, we know relatively little about the underlying molecular mechanisms or how to treat patients with Alzheimer’s disease. Here we provide bioinformatic and experimental evidence of a conserved mitochondrial stress response signature present in diseases involving amyloid-β proteotoxicity in human, mouse and Caenorhabditis elegans that involves the mitochondrial unfolded protein response and mitophagy pathways. Using a worm model of amyloid-β proteotoxicity, GMC101, we recapitulated mitochondrial features and confirmed that the induction of this mitochondrial stress response was essential for the maintenance of mitochondrial proteostasis and health. Notably, increasing mitochondrial proteostasis by pharmacologically and genetically targeting mitochondrial translation and mitophagy increases the fitness and lifespan of GMC101 worms and reduces amyloid aggregation in cells, worms and in transgenic mouse models of Alzheimer’s disease. Our data support the relevance of enhancing mitochondrial proteostasis to delay amyloid-β proteotoxic diseases, such as Alzheimer’s disease.

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Figure 1: Mitochondrial dysfunction in AD is typified by a conserved MSR.
Figure 2: Mitochondrial dysfunction and reliance on atfs-1 in GMC101 worms after proteotoxic stress.
Figure 3: Inhibiting mitochondrial translation reduces Aβ proteotoxicity and aggregation in GMC101 worms and in cells.
Figure 4: NAD+ boosters reduce Aβ proteotoxicity and aggregation in GMC101 worms and cells.
Figure 5: NR reduces Aβ deposits, induces the MSR and improves contextual memory in transgenic mice with AD.

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References

  1. Alzheimer’s Association. 2016 Alzheimer’s disease facts and figures. Alzheimers Dement. 12, 459–509 (2016)

  2. Dember, L. M. Amyloidosis-associated kidney disease. J. Am. Soc. Nephrol. 17, 3458–3471 (2006)

    CAS  PubMed  Google Scholar 

  3. Askanas, V. & Engel, W. K. Sporadic inclusion-body myositis: conformational multifactorial ageing-related degenerative muscle disease associated with proteasomal and lysosomal inhibition, endoplasmic reticulum stress, and accumulation of amyloid-β42 oligomers and phosphorylated tau. Presse Med. 40, e219–e235 (2011)

    PubMed  Google Scholar 

  4. Gauthier, S. et al. Why has therapy development for dementia failed in the last two decades? Alzheimers Dement. 12, 60–64 (2016)

    PubMed  Google Scholar 

  5. Soejitno, A., Tjan, A. & Purwata, T. E. Alzheimer’s disease: lessons learned from amyloidocentric clinical trials. CNS Drugs 29, 487–502 (2015)

    PubMed  Google Scholar 

  6. Herrup, K. et al. Beyond amyloid: getting real about non-amyloid targets in Alzheimer’s disease. Alzheimers Dement. 9, 452–458 (2013)

    PubMed  PubMed Central  Google Scholar 

  7. Selfridge, J. E., E, L., Lu, J. & Swerdlow, R. H. Role of mitochondrial homeostasis and dynamics in Alzheimer’s disease. Neurobiol. Dis. 51, 3–12 (2013)

    CAS  PubMed  Google Scholar 

  8. Pellegrino, M. W. & Haynes, C. M. Mitophagy and the mitochondrial unfolded protein response in neurodegeneration and bacterial infection. BMC Biol. 13, 22 (2015)

    PubMed  PubMed Central  Google Scholar 

  9. Beck, J. S., Mufson, E. J. & Counts, S. E. Evidence for mitochondrial UPR gene activation in familial and sporadic Alzheimer’s disease. Curr. Alzheimer Res. 13, 610–614 (2016)

    CAS  PubMed  PubMed Central  Google Scholar 

  10. Mufson, E. J. et al. Mild cognitive impairment: pathology and mechanisms. Acta Neuropathol. 123, 13–30 (2012)

    CAS  PubMed  Google Scholar 

  11. Oddo, S. et al. Triple-transgenic model of Alzheimer’s disease with plaques and tangles: intracellular Aβ and synaptic dysfunction. Neuron 39, 409–421 (2003)

    CAS  PubMed  Google Scholar 

  12. Jovaisaite, V., Mouchiroud, L. & Auwerx, J. The mitochondrial unfolded protein response, a conserved stress response pathway with implications in health and disease. J. Exp. Biol. 217, 137–143 (2014)

    CAS  PubMed  PubMed Central  Google Scholar 

  13. Cohen, E., Bieschke, J., Perciavalle, R. M., Kelly, J. W. & Dillin, A. Opposing activities protect against age-onset proteotoxicity. Science 313, 1604–1610 (2006)

    ADS  CAS  PubMed  Google Scholar 

  14. Link, C. D. C. elegans models of age-associated neurodegenerative diseases: lessons from transgenic worm models of Alzheimer’s disease. Exp. Gerontol. 41, 1007–1013 (2006)

    CAS  PubMed  Google Scholar 

  15. McColl, G. et al. Utility of an improved model of amyloid-beta (Aβ1–42) toxicity in Caenorhabditis elegans for drug screening for Alzheimer’s disease. Mol. Neurodegener. 7, 57 (2012)

    CAS  PubMed  PubMed Central  Google Scholar 

  16. Mouchiroud, L. et al. The movement tracker: a flexible system for automated movement analysis in invertebrate model organisms. Curr. Protoc. Neurosci. 77, 8.37.1–8.37.21 (2016)

    Google Scholar 

  17. Nargund, A. M., Fiorese, C. J., Pellegrino, M. W., Deng, P. & Haynes, C. M. Mitochondrial and nuclear accumulation of the transcription factor ATFS-1 promotes OXPHOS recovery during the UPRmt. Mol. Cell 58, 123–133 (2015)

    CAS  PubMed  PubMed Central  Google Scholar 

  18. Nargund, A. M., Pellegrino, M. W., Fiorese, C. J., Baker, B. M. & Haynes, C. M. Mitochondrial import efficiency of ATFS-1 regulates mitochondrial UPR activation. Science 337, 587–590 (2012)

    ADS  CAS  PubMed  PubMed Central  Google Scholar 

  19. Prahlad, V. & Morimoto, R. I. Integrating the stress response: lessons for neurodegenerative diseases from C. elegans. Trends Cell Biol. 19, 52–61 (2009)

    CAS  PubMed  Google Scholar 

  20. Benedetti, C., Haynes, C. M., Yang, Y., Harding, H. P. & Ron, D. Ubiquitin-like protein 5 positively regulates chaperone gene expression in the mitochondrial unfolded protein response. Genetics 174, 229–239 (2006)

    CAS  PubMed  PubMed Central  Google Scholar 

  21. Wong, A., Boutis, P. & Hekimi, S. Mutations in the clk-1 gene of Caenorhabditis elegans affect developmental and behavioral timing. Genetics 139, 1247–1259 (1995)

    CAS  PubMed  PubMed Central  Google Scholar 

  22. Yang, W. & Hekimi, S. Two modes of mitochondrial dysfunction lead independently to lifespan extension in Caenorhabditis elegans. Aging Cell 9, 433–447 (2010)

    CAS  PubMed  Google Scholar 

  23. Houtkooper, R. H. et al. Mitonuclear protein imbalance as a conserved longevity mechanism. Nature 497, 451–457 (2013)

    ADS  CAS  PubMed  PubMed Central  Google Scholar 

  24. Moullan, N. et al. Tetracyclines disturb mitochondrial function across eukaryotic models: a call for caution in biomedical research. Cell Rep. 10, 1681–1691 (2015)

    CAS  PubMed  PubMed Central  Google Scholar 

  25. Zheng, L. et al. Macroautophagy-generated increase of lysosomal amyloid β-protein mediates oxidant-induced apoptosis of cultured neuroblastoma cells. Autophagy 7, 1528–1545 (2011)

    CAS  PubMed  PubMed Central  Google Scholar 

  26. Forloni, G., Colombo, L., Girola, L., Tagliavini, F. & Salmona, M. Anti-amyloidogenic activity of tetracyclines: studies in vitro. FEBS Lett. 487, 404–407 (2001)

    CAS  PubMed  Google Scholar 

  27. Costa, R., Speretta, E., Crowther, D. C. & Cardoso, I. Testing the therapeutic potential of doxycycline in a Drosophila melanogaster model of Alzheimer disease. J. Biol. Chem. 286, 41647–41655 (2011)

    CAS  PubMed  PubMed Central  Google Scholar 

  28. Loeb, M. B. et al. A randomized, controlled trial of doxycycline and rifampin for patients with Alzheimer’s disease. J. Am. Geriatr. Soc. 52, 381–387 (2004)

    PubMed  Google Scholar 

  29. Quirós, P. M. et al. Multi-omics analysis identifies ATF4 as a key regulator of the mitochondrial stress response in mammals. J. Cell Biol. 216, 2027–2045 (2017)

    PubMed  PubMed Central  Google Scholar 

  30. Münch, C. & Harper, J. W. Mitochondrial unfolded protein response controls matrix pre-RNA processing and translation. Nature 534, 710–713 (2016)

    ADS  PubMed  PubMed Central  Google Scholar 

  31. Bao, X. R. et al. Mitochondrial dysfunction remodels one-carbon metabolism in human cells. eLife 5, e10575 (2016)

    PubMed  PubMed Central  Google Scholar 

  32. Sidrauski, C., McGeachy, A. M., Ingolia, N. T. & Walter, P. The small molecule ISRIB reverses the effects of eIF2α phosphorylation on translation and stress granule assembly. eLife 4, e05033 (2015)

    PubMed Central  Google Scholar 

  33. Palikaras, K., Lionaki, E. & Tavernarakis, N. Coordination of mitophagy and mitochondrial biogenesis during ageing in C. elegans. Nature 521, 525–528 (2015)

    ADS  CAS  PubMed  Google Scholar 

  34. Mouchiroud, L. et al. The NAD+/sirtuin pathway modulates longevity through activation of mitochondrial UPR and FOXO signaling. Cell 154, 430–441 (2013)

    CAS  PubMed  PubMed Central  Google Scholar 

  35. Gariani, K. et al. Eliciting the mitochondrial unfolded protein response by nicotinamide adenine dinucleotide repletion reverses fatty liver disease in mice. Hepatology 63, 1190–1204 (2016)

    CAS  PubMed  Google Scholar 

  36. Zhang, H. et al. NAD+ repletion improves mitochondrial and stem cell function and enhances life span in mice. Science 352, 1436–1443 (2016)

    ADS  CAS  PubMed  Google Scholar 

  37. Fang, E. F. et al. NAD+ replenishment improves lifespan and healthspan in ataxia telangiectasia models via mitophagy and DNA repair. Cell Metab. 24, 566–581 (2016)

    CAS  PubMed  PubMed Central  Google Scholar 

  38. Corcoran, K. A., Lu, Y., Turner, R. S. & Maren, S. Overexpression of hAPPswe impairs rewarded alternation and contextual fear conditioning in a transgenic mouse model of Alzheimer’s disease. Learn. Mem. 9, 243–252 (2002)

    PubMed  PubMed Central  Google Scholar 

  39. Cenini, G., Rüb, C., Bruderek, M. & Voos, W. Amyloid β-peptides interfere with mitochondrial preprotein import competence by a coaggregation process. Mol. Biol. Cell 27, 3257–3272 (2016)

    CAS  PubMed  PubMed Central  Google Scholar 

  40. Gong, B. et al. Nicotinamide riboside restores cognition through an upregulation of proliferator-activated receptor-γ coactivator 1α regulated β-secretase 1 degradation and mitochondrial gene expression in Alzheimer’s mouse models. Neurobiol. Aging 34, 1581–1588 (2013)

    CAS  PubMed  PubMed Central  Google Scholar 

  41. Martire, S. et al. Bioenergetic impairment in animal and cellular models of Alzheimer’s disease: PARP-1 inhibition rescues metabolic dysfunctions. J. Alzheimers Dis. 54, 307–324 (2016)

    CAS  PubMed  Google Scholar 

  42. Kim, H. E. et al. Lipid biosynthesis coordinates a mitochondrial-to-cytosolic stress response. Cell 166, 1539–1552 (2016)

    CAS  PubMed  PubMed Central  Google Scholar 

  43. Wang, X. & Chen, X. J. A cytosolic network suppressing mitochondria-mediated proteostatic stress and cell death. Nature 524, 481–484 (2015)

    ADS  CAS  PubMed  PubMed Central  Google Scholar 

  44. Wrobel, L. et al. Mistargeted mitochondrial proteins activate a proteostatic response in the cytosol. Nature 524, 485–488 (2015)

    ADS  CAS  PubMed  Google Scholar 

  45. D’Amico, D., Sorrentino, V. & Auwerx, J. Cytosolic proteostasis networks of the mitochondrial stress response. Trends Biochem. Sci. 42, 712–725 (2017)

    PubMed  Google Scholar 

  46. Tiernan, C. T. et al. Protein homeostasis gene dysregulation in pretangle-bearing nucleus basalis neurons during the progression of Alzheimer’s disease. Neurobiol. Aging 42, 80–90 (2016)

    CAS  PubMed  PubMed Central  Google Scholar 

  47. Liang, W. S. et al. Alzheimer’s disease is associated with reduced expression of energy metabolism genes in posterior cingulate neurons. Proc. Natl Acad. Sci. USA 105, 4441–4446 (2008)

    ADS  CAS  PubMed  Google Scholar 

  48. Fonte, V. et al. Suppression of in vivo β-amyloid peptide toxicity by overexpression of the HSP-16.2 small chaperone protein. J. Biol. Chem. 283, 784–791 (2008)

    CAS  PubMed  Google Scholar 

  49. Kamath, R. S., Martinez-Campos, M., Zipperlen, P., Fraser, A. G. & Ahringer, J. Effectiveness of specific RNA-mediated interference through ingested double-stranded RNA in Caenorhabditis elegans. Genome Biol. 2, RESEARCH0002 (2001)

    CAS  PubMed  Google Scholar 

  50. Koopman, M. et al. A screening-based platform for the assessment of cellular respiration in Caenorhabditis elegans. Nat. Protoc. 11, 1798–1816 (2016)

    CAS  PubMed  PubMed Central  Google Scholar 

  51. Counts, S. E., Nadeem, M., Lad, S. P., Wuu, J. & Mufson, E. J. Differential expression of synaptic proteins in the frontal and temporal cortex of elderly subjects with mild cognitive impairment. J. Neuropathol. Exp. Neurol. 65, 592–601 (2006)

    CAS  PubMed  Google Scholar 

  52. Greenberg, S. A. et al. Plasma cells in muscle in inclusion body myositis and polymyositis. Neurology 65, 1782–1787 (2005)

    CAS  PubMed  Google Scholar 

  53. Zhu, W. et al. Genomic signatures characterize leukocyte infiltration in myositis muscles. BMC Med. Genomics 5, 53 (2012)

    CAS  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

We thank P. Gönczy and M. Pierron (EPFL) for sharing reagents, the Caenorhabditis Genetics Center, which is funded by NIH Office of Research Infrastructure Programs (P40 OD010440), for providing worm strains. V.S. is supported by the ‘EPFL Fellows’ program co-funded by the Marie Skłodowska-Curie, Horizon 2020 Grant agreement (665667). D.D. is supported by a fellowship funded by Associazione Italiana per la Ricerca sul Cancro (AIRC). S.E.C. is supported by NIH grants (P01AG014449, R21AG053581 and P30 AG053760). The research of J.A. is supported by the EPFL, NIH (R01AG043930), Systems X (SySX.ch 2013/153), Velux Stiftung (1019), the Jebsen Foundation and the Swiss National Science Foundation (31003A-140780).

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Author notes

  1. Mario Romani and Laurent Mouchiroud: These authors contributed equally to this work.

Authors and Affiliations

  1. Laboratory for Integrative and Systems Physiology, Institute of Bioengineering, Ecole Polytechnique Fédérale de Lausanne, Lausanne, CH-1015, Switzerland

    Vincenzo Sorrentino, Mario Romani, Laurent Mouchiroud, Hongbo Zhang, Davide D’Amico, Norman Moullan, Francesca Potenza, Solène Rietsch & Johan Auwerx

  2. Department of Translational Science and Molecular Medicine, Department of Family Medicine, Michigan State University, Grand Rapids, 49503, Michigan, USA

    John S. Beck & Scott E. Counts

  3. Proteomics Core Facility, Ecole Polytechnique Fédérale de Lausanne, Lausanne, CH-1015, Switzerland

    Adrien W. Schmid

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Contributions

V.S. and J.A. conceived and designed the project. V.S., L.M., M.R., J.S.B., H.Z., D.D., F.P., N.M., A.W.S., S.R. and S.E.C. performed the experiments. V.S., M.R. and L.M. independently replicated worm experiments in Figs 2, 3, 4. V.S., L.M. and J.A. wrote the manuscript.

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Correspondence to Johan Auwerx.

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Extended data figures and tables

Extended Data Figure 1 Mitochondrial function pathways are disrupted in patients with AD.

a, Gene set enrichment analysis of OXPHOS (false-discovery rate (FDR) = 0.051, nominal P = 0.008) and mitochondrial import (FDR = 0.295, nominal-P = 0.002) genes in human prefrontal cortex of patients with AD (GN328; healthy, n = 195; AD, n = 388 individuals). b, e, Gene set enrichment analysis of OXPHOS and mitochondrial import genes in human visual cortex (b) (GN327; healthy, n = 195; AD, n = 388) and whole brain (e) (GN314, n = 16 healthy individuals and 33 individuals with AD) of patients with AD. b, FDR = 0.754, P = 0.038 for OXPHOS, FDR = 0.657, P = 0.031 for mitochondrial import. e, FDR = 0.076, P = 0.002 for OXPHOS, FDR = 0.218, P = 0.006 for mitochondrial import. c, f, Heat maps of genes from visual cortex (c) and whole brain (f) datasets. d, g, Correlation plots of mitochondrial stress genes, UPRER and HSR levels in human visual cortex (d) and whole brain (g) from patients with AD. For further information, see Supplementary Table 5. h, Quantification of immunoblots of mtDNAJ and CLPP (n = 8 per group shown in Fig. 1d) from brains of humans with no cognitive impairment (NCI), mild-cognitive impairment (MCI) and mild to moderate AD. This experiment was performed independently twice. Data are mean ± s.e.m. ***P ≤ 0.001. Differences were assessed using two-tailed t-tests (95% confidence interval). Mito., mitochondrial. For all individual P values, see Source Data.

Source data

Extended Data Figure 2 MSR analysis and mitochondrial function in 3×TgAD mice.

a, Human APP expression in cortex tissues of wild-type and 3×TgAD mice (n = 4 mice per group). **P = 0.002. b, MSR transcript analysis from cortex tissues of wild-type (n = 4 mice) and 3×TgAD (n = 4 mice) mice at six months of age. c, Immunoblot analysis (wild-type, n = 5; 3×TgAD, n = 6, western blot of four representative mice) and quantification of the samples as in b. *P < 0.05. (P = 0.035, P = 0.029). d–f, MSR transcript analysis from cortex tissues of wild-type (d; 6 months, n = 4 mice; 9 months, n = 5 mice) and 3×TgAD (e; 6 months, n = 4 mice; 9 months, n = 5 mice) mice at six and nine months of age, and corresponding heat maps (f) representing relative variation in gene expression between groups. g, Citrate synthase activity assay in cortex tissues from wild-type and 3×TgAD mice (wild-type, n = 8 mice; 3×TgAD, n = 7 mice). *P = 0.039. Data are mean ± s.e.m. *P < 0.05; **P ≤ 0.01; ***P ≤ 0.001; n.s., not significant. Overall differences between conditions were assessed by two-way ANOVA. Differences in individual genes, proteins or between two groups were assessed using two-tailed t-tests (95% confidence interval). All experiments were performed independently twice. For uncropped gel source data, see Supplementary Fig. 1. For all individual P values, see Source Data.

Source data

Extended Data Figure 3 Characterization of Aβ proteotoxicity and stress response pathways in GMC101 worms.

a, Amyloid aggregation in CL2122 and GMC101 worms (n = 3 biologically independent samples) at 20 °C or 25 °C. b, MSR transcript analysis in worms at 20 °C (n = 3 biologically independent samples). c, Respiration assay in CL2122 and GMC101 worms (CL2122, n = 8; GMC101, n = 8 biologically independent samples). d, mitochondrial:nuclear DNA ratio in CL2122 and GMC101 worms (n = 13 animals per group). e, Citrate synthase activity in CL2122 and GMC101 worms on D1 (n = 5 biologically independent samples). **P = 0.004. f, CL2122 and GMC101 mobility (CL2122, n = 48; GMC101, n = 59 worms). g, Confocal images of D1 adult worms showing muscle cell integrity, nuclear morphology and mitochondrial networks. Scale bar, 10 μm. See Methods. h, Representative images and fraction of worms in different stages of development upon atfs-1 RNAi (n = 4 independent experiments). *P < 0.05 (larvae, P = 0.048; adults, P = 0.035). i, Transcript analysis of UPRER, HSR and daf-16 target genes (n = 3 biologically independent samples). j, Representative images and fraction of worms in different stages of development fed with atfs-1, xbp-1 and hsf-1 RNAis at 20 °C (n = 8 per group; xbp-1, n = 3 biologically independent samples). k, Amyloid aggregation upon atfs-1 RNAi (n = 2 biological replicates). l, Mobility of CL2122 fed with 50% dilution of atfs-1 RNAi (ev, n = 48; atfs-1 1/2, n = 47 worms). m, Validation of the efficacy of atfs-1 RNAi in CL2122 and GMC101 worms (n = 3 biologically independent samples). n, MSR transcript analysis of CL2122 worms upon atfs-1 RNAi (n = 3 biologically independent samples). o, Mobility of D1 adult worms fed with atfs-1 or hsf-1 RNAi at 25 °C (CL2122, ev, n = 22; atfs-1, n = 27; hsf-1, n = 28; GMC101, ev, n = 27; atfs-1, n = 21; hsf-1, n = 18; N2, ev, n = 31; atfs-1, n = 38; hsf-1, n = 27 worms). p, Validation of the efficacy of the newly generated atfs-1 #2 RNAi (n = 3 biologically independent samples). For further information, see Methods. q, Worm mobility upon atfs-1 #2 RNAi (CL2122, ev, n = 47; atfs-1 #2, n = 42; GMC101, ev, n = 55; atfs-1 #2, n = 46 worms). ev, scrambled RNAi; A.U., arbitrary units. Data are mean ± s.e.m. *P < 0.05; **P ≤ 0.01; ***P ≤ 0.001; ****P ≤ 0.0001; n.s., not significant. Overall differences between conditions were assessed by two-way ANOVA. Differences in individual genes or between two groups were assessed using two-tailed t-tests (95% confidence interval). All experiments were performed independently at least twice. For uncropped gel source data, see Supplementary Fig. 1. For all individual P values, see Source Data.

Source data

Extended Data Figure 4 Reliance on ubl-5 and on increased mitochondrial stress response of GMC101 worms.

a, Fraction of worms that reached D1 adulthood fed with ubl-5 RNAi (n = 5 biologically independent samples). b, c, Mobility of worms (b) and percentage of paralysed and dead D8 adult worms (c) upon ubl-5 RNAi (b; CL2122, ev, n = 39; ubl-5, n = 43; GMC101, ev, n = 40; ubl-5, n = 41 worms; c; n = 5 biologically independent samples). d, e, Transcript analysis of UPRER, HSR and daf-16 target genes in GMC101 (d) and CL2122 (e) worms upon atfs-1 RNAi (n = 3 biologically independent samples). f, Validation of the atfs-1-overexpressing strains AUW9, AUW10 and AUW11 (n = 3 biologically independent samples). See Methods. g, Worm mobility in atfs-1-overexpressing CL2122- and GMC101-derived lines (CL2122, n = 40; GMC101, n = 57; AUW9, n = 40; AUW10, n = 38; AUW11, n = 42 worms). h, Percentage of paralysed and dead D6 adult worms (n = 5 biologically independent samples). *P < 0.05 (from left to right, P = 0.019, 0.046, 0.041). i, j, Mobility (i) and percentage of paralysed and dead D8 adult worms (j) of GMC101, clk-1 mutant (CB4876) and AUW12 strains (i; GMC101, n = 35; CB4876, n = 42; AUW12, n = 38 worms; j; n = 5 biologically independent samples). k, l, Mobility (k) and percentage of paralysed and dead D8 adult worms (l) of GMC101, nuo-6 mutant (MQ1333) and AUW13 strains (k; GMC101, n = 46; MQ1333, n = 50; AUW13, n = 47 worms; l; n = 5 biologically independent samples). For further information on all strains, see Methods. ev, scrambled RNAi; A.U., arbitrary units. Data are mean ± s.e.m. *P < 0.05; **P ≤ 0.01; ***P ≤ 0.001; ****P ≤ 0.0001; n.s., not significant. Overall differences between conditions were assessed by two-way ANOVA. Differences in individual genes or between two groups were assessed using two-tailed t-tests (95% confidence interval). All experiments were performed independently at least twice. For uncropped gel source data, see Supplementary Fig. 1. For all individual P values, see Source Data.

Source data

Extended Data Figure 5 Effects of the inhibition of mitochondrial translation and mitophagy in worms, and of compound treatments in mammalian cells.

a, Representative images of GMC101 worms upon mrps-5 RNAi feeding or DOX treatment (15 μg ml−1) from eggs to D1 (n = 2 independent experiments). b, MSR transcript analysis of DOX-treated CL2122 worms (n = 4 biologically independent samples). c, d, Transcript analysis of UPRER, HSR and daf-16 target genes in GMC101 worms fed with mrps-5 RNAi (c) or treated with DOX (15 μg ml−1) (d) (c, d, n = 3 biologically independent samples). e, Amyloid aggregation in worms upon mrps-5 RNAi or DOX treatment (n = 3 biologically independent samples). f, Respiration on D3 and D6 in GMC101 worms fed with mrps-5 RNAi (n = 9; mrps-5 D6, n = 8 biologically independent samples). g, Additional confocal images of the SH-SY5Y(APPSwe) cells stained with the anti-β-amyloid 1–42 antibody, after DOX and ISRIB treatment. Scale bar, 10 μm. h, Immunoblot of OXPHOS proteins in SH-SY5Y(APPSwe) cells showing the effects of NR (1 mM) and DOX (10 μg ml−1) (n = 2 biologically independent samples). i, j, Transcript levels of MSR and OXPHOS genes (i) and ATF4 target genes (j) in APPSwe-expressing cell line after 24 h of DOX (10 μg ml−1; n = 4 biologically independent samples). k, Mobility of GMC101 worms upon dct-1 RNAi (ev, n = 54; dct-1, n = 44 worms). l, Mobility of GMC101 worms fed with dct-1, mrsp-5 or both RNAis (ev, n = 54; dct-1, n = 44; mrps-5, n = 35; mrps-5;dct-1, n = 45 worms). m, Mobility of GMC101 worms treated with DOX and/or fed dct-1 RNAi (ev, n = 54; dct-1, n = 44; DOX, n = 52; DOX and dct-1, n = 54 worms). n, o, Mobility of CL2122 worms fed with dct-1 RNAi (n) from D1 to D4 (ev, n = 44; dct-1, n = 40 worms) or (o) at D8 (n = 38 worms, *P < 0.05 (P = 0.018)). ev, scrambled RNAi; DOX, doxycycline; NR, nicotinamide riboside; ISRIB, integrated stress response inhibitor; A.U. Data are mean ± s.e.m. *P < 0.05; **P ≤ 0.01; ***P ≤ 0.001; ****P ≤ 0.0001; n.s., not significant. Overall differences between conditions were assessed by two-way ANOVA. Differences in individual genes or between two groups were assessed using two-tailed t-tests (95% confidence interval). All experiments were performed independently at least twice. For uncropped gel source data, see Supplementary Fig. 1. For all individual P values, see Source Data.

Source data

Extended Data Figure 6 Effect of NAD+-boosting compounds and sirtuin depletion in worms, and NR treatment in mammalian cells.

a, Percentage of paralysed D8 adult GMC101 worms after NR or AZD treatment (n = 3 independent experiments). b, c, MSR transcript analysis of CL2122 worms treated with NR (b; 1 mM) or AZD (c; 0.3 μM) (b, c, n = 3 biologically independent samples). d, e, Mobility of CL2122 treated with NR (1 mM) or AZD (0.3 μM) from (d) D1 to D4 (vehicle, n = 44; NR, n = 48; AZD, n = 43 worms) or (e) at D8 (vehicle, n = 38; NR, n = 36; AZD, n = 33 worms, *P < 0.05 (P = 0.017); **P ≤ 0.01 (P = 0.004)). f, g, Percentage of paralysed D8 adult GMC101 treated with NR upon atfs-1 RNAi (f) or dct-1 RNAi (g) (n = 5 biologically independent samples). h, Representative images of worms fed with atfs-1, sir-2.1 or daf-16 RNAis (n = 2 independent experiments). i, Mobility of NR-treated GMC101 worms (1 mM) fed with sir-2.1 RNAi (ev, n = 52; sir-2.1, n = 37; NR, n = 40; sir-2.1 and NR, n = 51 worms). j, Mobility of NR-treated GMC101 worms (1 mM) fed with daf-16 RNAi (ev, n = 52; daf-16, n = 43; NR, n = 40; daf-16 and NR, n = 48 worms). k, Percentage of paralysed and dead D8 adult GMC101 worms treated with NR or fed with sir-2.1, daf-16 or atfs-1 RNAis (n = 5 biologically independent samples). l, m, Transcript analysis of UPRER, HSR and daf-16 target genes in GMC101 worms treated with NR (l; 1 mM, *P < 0.05 (hsp-16.41, P = 0.03; hsp-16.48/49, P = 0.008)), or AZD (m; 0.3 μM, *P < 0.05 (P = 0.033); **P ≤ 0.01 (P = 0.0004)) (n = 3 biologically independent samples). n, Additional confocal images of the intracellular amyloid deposits in the SH-SY5Y(APPSwe) cells after 24 h NR treatment. o, Transcript levels of MSR genes in APPSwe-expressing cells after NR (1 mM) (n = 4 biologically independent samples). NR, nicotinamide riboside; ISRIB, integrated stress response inhibitor; AZD, Olaparib; ev, scrambled RNAi; A.U., arbitrary units. Data are mean ± s.e.m. *P < 0.05; **P ≤ 0.01; ***P ≤ 0.001; ****P ≤ 0.0001; n.s., not significant. Overall differences between conditions were assessed by two-way ANOVA. Differences in individual genes or between two groups were assessed using two-tailed t-tests (95% confidence interval). All experiments were performed independently twice. For all individual P values, see Source Data.

Source data

Extended Data Figure 7 Proposed model.

Scheme illustrating the role of mitochondrial proteostasis in Aβ proteopathies based on our studies in the GMC101 model. (1) Accumulation of amyloid aggregates triggers mitochondrial dysfunction, which induces the MSR. (2) atfs-1 depletion results in loss of mitochondrial homeostasis, more pronounced amyloid aggregation and decreased healthspan. (3) Enhancing mitochondrial proteostasis with DOX, mrps-5 RNAi, and NAD+ boosters (NR and Olaparib) increases organismal fitness, delaying the development of Aβ proteotoxicity.

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This file contains Supplementary Tables 1-13, Supplementary Text and Supplementary Figure 1, the uncropped western blots (PDF 2292 kb)

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Sorrentino, V., Romani, M., Mouchiroud, L. et al. Enhancing mitochondrial proteostasis reduces amyloid-β proteotoxicity. Nature 552, 187–193 (2017). https://doi.org/10.1038/nature25143

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