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.

  • Letter
  • Published:

Selective autophagy degrades nuclear pore complexes

Nature Cell Biology volume 22, pages 159–166 (2020)Cite this article

Subjects

Abstract

Nuclear pore complexes (NPCs) are very large proteinaceous assemblies that consist of more than 500 individual proteins1,2. NPCs are essential for nucleocytoplasmic transport of different cellular components, and disruption of the integrity of NPCs has been linked to aging, cancer and neurodegenerative diseases3,4,5,6,7. However, the mechanism by which membrane-embedded NPCs are turned over is currently unknown. Here we show that, after nitrogen starvation or genetic interference with the architecture of NPCs, nucleoporins are rapidly degraded in the budding yeast Saccharomyces cerevisiae. We demonstrate that NPC turnover involves vacuolar proteases and the core autophagy machinery. Autophagic degradation is mediated by the cytoplasmically exposed Nup159, which serves as intrinsic cargo receptor and directly binds to the autophagy marker protein Atg8. Autophagic degradation of NPCs is therefore inducible, enabling the removal of individual NPCs from the nuclear envelope.

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

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

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

Fig. 1: Nups are degraded after nitrogen starvation by both autophagy and the proteasome.
Fig. 2: Nuclear-envelope-embedded NPCs are degraded by autophagy.
Fig. 3: Nup159 is an autophagy receptor for NPC degradation.
Fig. 4: Selective autophagy is important for the clearance of aberrant NPCs.

Similar content being viewed by others

Data availability

Yeast strains and plasmids are available on request. The mass spectrometry proteomics raw data have been deposited to the ProteomeXchange Consortium through the PRIDE partner repository with the dataset identifier PXD011571. All other data supporting the findings of this study are available from the corresponding authors on reasonable request.

References

  1. Beck, M. & Hurt, E. The nuclear pore complex: understanding its function through structural insight. Nat. Rev. Mol. Cell Biol. 18, 73–89 (2017).

    CAS  PubMed  Google Scholar 

  2. Schwartz, T. U. The structure inventory of the nuclear pore complex. J. Mol. Biol. 428, 1986–2000 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  3. D’Angelo, M. A., Raices, M., Panowski, S. H. & Hetzer, M. W. Age-dependent deterioration of nuclear pore complexes causes a loss of nuclear integrity in postmitotic cells. Cell 136, 284–295 (2009).

    PubMed  PubMed Central  Google Scholar 

  4. Sakuma, S. & D’Angelo, M. A. The roles of the nuclear pore complex in cellular dysfunction, aging and disease. Semin. Cell Dev. Biol. 68, 72–84 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  5. Simon, D. N. & Rout, M. P. Cancer and the nuclear pore complex. Adv. Exp. Med. Biol. 773, 285–307 (2014).

    CAS  PubMed  Google Scholar 

  6. Lord, C. L., Ospovat, O. & Wente, S. R. Nup100 regulates Saccharomyces cerevisiae replicative life span by mediating the nuclear export of specific tRNAs. RNA 23, 365–377 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  7. Toyama, B. H. et al. Identification of long-lived proteins reveals exceptional stability of essential cellular structures. Cell 154, 971–982 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  8. Dilworth, D. J. et al. Nup2p dynamically associates with the distal regions of the yeast nuclear pore complex. J. Cell Biol. 153, 1465–1478 (2001).

    CAS  PubMed  PubMed Central  Google Scholar 

  9. Savas, J. N., Toyama, B. H., Xu, T., Yates, J. R. 3rd & Hetzer, M. W. Extremely long-lived nuclear pore proteins in the rat brain. Science 335, 942 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  10. Mathieson, T. et al. Systematic analysis of protein turnover in primary cells. Nat. Commun. 9, 689 (2018).

    PubMed  PubMed Central  Google Scholar 

  11. Mizushima, N., Yoshimori, T. & Ohsumi, Y. The role of Atg proteins in autophagosome formation. Annu. Rev. Cell Dev. Biol. 27, 107–132 (2011).

    CAS  PubMed  Google Scholar 

  12. Wen, X. & Klionsky, D. J. An overview of macroautophagy in yeast. J. Mol. Biol. 428, 1681–1699 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  13. Cheong, H. & Klionsky, D. J. Biochemical methods to monitor autophagy-related processes in yeast. Methods Enzymol. 451, 1–26 (2008).

    CAS  PubMed  Google Scholar 

  14. Shintani, T. & Klionsky, D. J. Cargo proteins facilitate the formation of transport vesicles in the cytoplasm to vacuole targeting pathway. J. Biol. Chem. 279, 29889–29894 (2004).

    CAS  PubMed  Google Scholar 

  15. Webster, B. M., Colombi, P., Jager, J. & Lusk, C. P. Surveillance of nuclear pore complex assembly by ESCRT-III/Vps4. Cell 159, 388–401 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  16. Epple, U. D., Suriapranata, I., Eskelinen, E. L. & Thumm, M. Aut5/Cvt17p, a putative lipase essential for disintegration of autophagic bodies inside the vacuole. J. Bacteriol. 183, 5942–5955 (2001).

    CAS  PubMed  PubMed Central  Google Scholar 

  17. Roberts, P. et al. Piecemeal microautophagy of nucleus in Saccharomyces cerevisiae. Mol. Biol. Cell 14, 129–141 (2003).

    CAS  PubMed  PubMed Central  Google Scholar 

  18. Zaffagnini, G. & Martens, S. Mechanisms of selective autophagy. J. Mol. Biol. 428, 1714–1724 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  19. Farre, J. C. & Subramani, S. Mechanistic insights into selective autophagy pathways: lessons from yeast. Nat. Rev. Mol. Cell Biol. 17, 537–552 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  20. Stolz, A., Ernst, A. & Dikic, I. Cargo recognition and trafficking in selective autophagy. Nat. Cell Biol. 16, 495–501 (2014).

    CAS  PubMed  Google Scholar 

  21. Mochida, K. et al. Receptor-mediated selective autophagy degrades the endoplasmic reticulum and the nucleus. Nature 522, 359–362 (2015).

    CAS  PubMed  Google Scholar 

  22. Khaminets, A. et al. Regulation of endoplasmic reticulum turnover by selective autophagy. Nature 522, 354–358 (2015).

    CAS  PubMed  Google Scholar 

  23. Lu, K., Psakhye, I. & Jentsch, S. Autophagic clearance of polyQ proteins mediated by ubiquitin-Atg8 adaptors of the conserved CUET protein family. Cell 158, 549–563 (2014).

    CAS  PubMed  Google Scholar 

  24. Scott, S. V., Guan, J., Hutchins, M. U., Kim, J. & Klionsky, D. J. Cvt19 is a receptor for the cytoplasm-to-vacuole targeting pathway. Mol. Cell 7, 1131–1141 (2001).

    CAS  PubMed  PubMed Central  Google Scholar 

  25. Noda, N. N., Ohsumi, Y. & Inagaki, F. Atg8-family interacting motif crucial for selective autophagy. FEBS Lett. 584, 1379–1385 (2010).

    CAS  PubMed  Google Scholar 

  26. Kerppola, T. K. Bimolecular fluorescence complementation (BiFC) analysis as a probe of protein interactions in living cells. Annu. Rev. Biophys. 37, 465–487 (2008).

    CAS  PubMed  PubMed Central  Google Scholar 

  27. Aitchison, J. D., Blobel, G. & Rout, M. P. Nup120p: a yeast nucleoporin required for NPC distribution and mRNA transport. J. Cell Biol. 131, 1659–1675 (1995).

    CAS  PubMed  Google Scholar 

  28. Doye, V., Wepf, R. & Hurt, E. C. A novel nuclear pore protein Nup133p with distinct roles in poly(A)+ RNA transport and nuclear pore distribution. EMBO J. 13, 6062–6075 (1994).

    CAS  PubMed  PubMed Central  Google Scholar 

  29. Heath, C. V. et al. Nuclear pore complex clustering and nuclear accumulation of poly(A)+ RNA associated with mutation of the Saccharomyces cerevisiae RAT2/NUP120 gene. J. Cell Biol. 131, 1677–1697 (1995).

    CAS  PubMed  Google Scholar 

  30. Wente, S. R. & Blobel, G. A temperature-sensitive NUP116 null mutant forms a nuclear envelope seal over the yeast nuclear pore complex thereby blocking nucleocytoplasmic traffic. J. Cell Biol. 123, 275–284 (1993).

    CAS  PubMed  Google Scholar 

  31. Luo, M., Zhao, X., Song, Y., Cheng, H. & Zhou, R. Nuclear autophagy: an evolutionarily conserved mechanism of nuclear degradation in the cytoplasm. Autophagy 12, 1973–1983 (2016).

    PubMed  PubMed Central  Google Scholar 

  32. Mijaljica, D. & Devenish, R. J. Nucleophagy at a glance. J. Cell Sci. 126, 4325–4330 (2013).

    CAS  PubMed  Google Scholar 

  33. Otsuka, S. et al. Nuclear pore assembly proceeds by an inside-out extrusion of the nuclear envelope. eLife 5, e19071 (2016).

    PubMed  PubMed Central  Google Scholar 

  34. Cantwell, H. & Nurse, P. Unravelling nuclear size control. Curr. Genet. 65, 1281–1285 (2019).

    CAS  PubMed  PubMed Central  Google Scholar 

  35. McCloskey, A., Ibarra, A. & Hetzer, M. W. Tpr regulates the total number of nuclear pore complexes per cell nucleus. Genes Dev. 32, 1321–1331 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  36. Thaller, D. J. & Patrick Lusk, C. Fantastic nuclear envelope herniations and where to find them. Biochem. Soc. Trans. 46, 877–889 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  37. Mostofa, M. G. et al. CLIP and cohibin separate rDNA from nucleolar proteins destined for degradation by nucleophagy. J. Cell Biol. 217, 2675–2690 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  38. Toyama, B. H. et al. Visualization of long-lived proteins reveals age mosaicism within nuclei of postmitotic cells. J. Cell Biol. 218, 433–444 (2019).

    CAS  PubMed  PubMed Central  Google Scholar 

  39. Amberg, D. C., Burke, D. & Strathern, J. N. Methods in Yeast Genetics: A Cold Spring Harbor Laboratory Course Manual 2005 edn. (Cold Spring Harbor Laboratory Press, 2005).

  40. Sherman, F. Getting started with yeast. Methods Enzymol. 194, 3–21 (1991).

    CAS  PubMed  Google Scholar 

  41. Janke, C. et al. A versatile toolbox for PCR-based tagging of yeast genes: new fluorescent proteins, more markers and promoter substitution cassettes. Yeast 21, 947–962 (2004).

    CAS  PubMed  Google Scholar 

  42. Knop, M. et al. Epitope tagging of yeast genes using a PCR-based strategy: more tags and improved practical routines. Yeast 15, 963–972 (1999).

    CAS  PubMed  Google Scholar 

  43. Nakatogawa, H., Ishii, J., Asai, E. & Ohsumi, Y. Atg4 recycles inappropriately lipidated Atg8 to promote autophagosome biogenesis. Autophagy 8, 177–186 (2012).

    CAS  PubMed  Google Scholar 

  44. Rappsilber, J., Ishihama, Y. & Mann, M. Stop and go extraction tips for matrix-assisted laser desorption/ionization, nanoelectrospray, and LC/MS sample pretreatment in proteomics. Anal. Chem. 75, 663–670 (2003).

    CAS  PubMed  Google Scholar 

  45. Cox, J. & Mann, M. MaxQuant enables high peptide identification rates, individualized p.p.b.-range mass accuracies and proteome-wide protein quantification. Nat. Biotechnol. 26, 1367–1372 (2008).

    CAS  PubMed  Google Scholar 

  46. Cox, J. et al. Accurate proteome-wide label-free quantification by delayed normalization and maximal peptide ratio extraction, termed MaxLFQ. Mol. Cell. Proteomics. 13, 2513–2526 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  47. Tyanova, S. et al. The Perseus computational platform for comprehensive analysis of (prote)omics data. Nat. Methods 13, 731–740 (2016).

    CAS  PubMed  Google Scholar 

  48. Kukulski, W. et al. Correlated fluorescence and 3D electron microscopy with high sensitivity and spatial precision. J. Cell Biol. 192, 111–119 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  49. Thaller, D. J. et al. An ESCRT-LEM protein surveillance system is poised to directly monitor the nuclear envelope and nuclear transport system. eLife 8, e45284 (2019).

    PubMed  PubMed Central  Google Scholar 

  50. Mastronarde, D. N. Automated electron microscope tomography using robust prediction of specimen movements. J. Struct. Biol. 152, 36–51 (2005).

    PubMed  Google Scholar 

  51. Kremer, J. R., Mastronarde, D. N. & McIntosh, J. R. Computer visualization of three-dimensional image data using IMOD. J. Struct. Biol. 116, 71–76 (1996).

    CAS  PubMed  Google Scholar 

  52. Paul-Gilloteaux, P. et al. eC-CLEM: flexible multidimensional registration software for correlative microscopies. Nat. Methods 14, 102–103 (2017).

    CAS  PubMed  Google Scholar 

  53. de Chaumont, F. et al. Icy: an open bioimage informatics platform for extended reproducible research. Nat. Methods 9, 690–696 (2012).

    PubMed  Google Scholar 

Download references

Acknowledgements

We thank J. Sun (intern in the EMCF at EMBL) for tomogram manual segmentation and N. Romanov for MS analysis; staff at the MPIB Imaging Facility, in particular G. Cardone and M. Spitaler, for help with image analysis; W. Baumeister, J. Buchner, F. U. Hartl, M. Hayer-Hartl, B. Schulman and B. Engel, and members of the Jentsch, Beck and Pfander laboratories for discussions and comments on the manuscript; and N. Nagaraj and S. Uebel of the Biochemistry Core Facility of the Max Planck Institute of Biochemistry for MS analysis. The B.P. laboratory acknowledges funding by the Max Planck Society and Deutsche Forschungsgemeinschaft. M.B. acknowledges funding by the EMBL. Research in the S.J. laboratory was supported by Max Planck Society, Deutsche Forschungsgemeinschaft, Center for Integrated Protein Science Munich, Louis-Jeantet Foundation and a European Research Council (ERC) Advanced Grant. F.W. was supported by an EMBO Long-Term Fellowship ALTF 764-2014. M.A. was funded by an EMBO Long-Term Fellowship ALTF-1389–2016.

Author information

Author notes

  1. These authors contributed equally: Chia-Wei Lee, Florian Wilfling.

  2. Deceased: Stefan Jentsch.

Authors and Affiliations

  1. Molecular Cell Biology, Max Planck Institute of Biochemistry, Martinsried, Germany

    Chia-Wei Lee, Florian Wilfling & Stefan Jentsch

  2. Electron Microscopy Core Facility (EMCF), European Molecular Biology Laboratory, Heidelberg, Germany

    Paolo Ronchi

  3. Structural and Computational Biology Unit, Cell Biology and Biophysics Unit, European Molecular Biology Laboratory, Heidelberg, Germany

    Matteo Allegretti, Shyamal Mosalaganti & Martin Beck

  4. Molecular Sociology, Max Planck Institute of Biophysics, Frankfurt am Main, Germany

    Martin Beck

  5. DNA Replication and Genome Integrity, Max Planck Institute of Biochemistry, Martinsried, Germany

    Boris Pfander

Authors
  1. Chia-Wei Lee
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Florian Wilfling
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Paolo Ronchi
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Matteo Allegretti
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Shyamal Mosalaganti
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Stefan Jentsch
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Martin Beck
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Boris Pfander
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

C.-W.L., F.W., S.J., M.B. and B.P. conceived the study. C.-W.L., F.W., S.J., M.B. and B.P. designed experiments. P.R. performed the CLEM experiments. M.A. helped with the experimental design for CLEM. S.M. performed the microscopy and GFP-cleavage assay in the mammalian system that was not included in the current manuscript. C.-W.L. and F.W. performed all of the other experiments. C.-W.L., F.W., M.A., S.J., M.B. and B.P. analysed the data. C.-W.L., F.W., M.B. and B.P. wrote the manuscript.

Corresponding authors

Correspondence to Martin Beck or Boris Pfander.

Ethics declarations

Competing interests

The authors declare no competing 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 NPC scaffold proteins are degraded by both autophagy and the proteasome.

a, Schematic representation of NPC architecture in a cross-section view of the NPC. The central core of the NPC consists of one inner-ring complex (magenta) flanked on both sides by the outer NPC scaffold (orange, consistent of Y complex and the heteromeric Nic96), together forming the NPC scaffold. Peripheral nucleoporins constitute cytoplasmic filaments (dark brown) and the nuclear basket (navy blue). The permeability barrier is established by FG-nucleoporins (green). Three pore membrane proteins (Poms; light brown) anchor the NPC scaffold at the outer nuclear membrane (ONM) and inner nuclear membrane (INM) joint. b, Degradation of scaffold nucleoporins (Nup192–eGFP and Nup133–eGFP) was measured over 24 h after cycloheximide block (CHX; 80 μg ml–1) of translation by anti-eGFP immunoblotting. Dpm1 serves as control. Quantifications from n=3 biologically independent experiments are shown as mean ± s.d.. c, Nup192–eGFP-tagged cells were subjected to nitrogen starvation (SD-N), glucose starvation (YP medium lacking glucose), or rapamycin treatment (12 nM) for indicated time (n=2 biologically independent experiments). The Nup192–eGFP western blot illustrates that nitrogen starvation or rapamycin treatment, but not glucose starvation-induces a drop in Nup192–eGFP levels. Dpm1 serves as control. d, Degradation of Nup192–eGFP after nitrogen starvation as in Fig. 1c, but in different ubiquitin-proteasome receptor mutants (rpn10∆, rpn13∆, rad23∆, dsk2∆, rad23∆ dsk2∆) (n=2 biologically independent experiments). e, Starvation-induced Nup192–eGFP degradation was measured as in Fig. 1d, but in atg7∆, atg8∆, atg1∆, atg6∆, atg3∆ and atg4∆ cells deficient in the core autophagy machinery (n=2 biologically independent experiments). Autophagy-deficient cells do not show appearance of the free eGFP band and lead to stabilization of Nup192–eGFP. f, g Starvation-induced Nup192–eGFP degradation (f) was measured in wildtype and mutants cells, deficient in ESCRT (vps4∆) or proteasome (cim3-1) as in Fig. 1c. (g) Atg8-degradation and vacuolar cleavage of eGFP-Atg8 was measured by immunoblotting in wildtype, vps4∆, and cim3-1 mutant cells before and 2, 4, 8 h after induction of autophagy by nitrogen starvation. Quantifications from n=3 biologically independent experiments are shown as mean ± s.d., **p ≤ 0.005, ***p ≤ 0.001, ****p ≤ 0.0001, two-tailed Student’s t-tests. Data available in Statistical Source Data Extended Data Figure 1 and Unprocessed Blots Extended Data Figure 1.

Source data

Extended Data Fig. 2 The core autophagy machinery is important for NPC degradation in contrast to other previously characterized selective autophagy pathways.

a, Quantitative analysis of Nup192–eGFP fluorescence signal and nuclear volume before and after nitrogen starvation. Wildtype or atg8∆ mutant cells expressing Nup192-eGFP were trapped in a microfluidic device and incubated for two hours with regular growth media before the buffer stream was changed and cells were incubated with medium lacking any nitrogen source (SD-N) for 24 hours. Every hour a z-stack for the Nup192-eGFP signal was recorded. The nuclear volume and the Nup192-eGFP intensity within this volume were followed in individual cells (n=100 individual cells for each condition) before and after 24 hours of SD-N treatment. ****p ≤ 0.0001, two-tailed Student’s t-tests. b, eGFP-Atg8 interacting proteins were measured by eGFP-Atg8 Co-IP as in Fig. 2c, with eGFP-Atg8 under control of the ADH promoter. For this analysis, cells with tagged Nup159-6HA (upper right panel), Pom152-6HA (bottom right panel) or Nup192-6HA (left panel) were subjected to immunoprecipitation with GFP-Trap matrix (n=2 biologically independent experiments). Immunoprecipitates were probed with antibodies directed against eGFP, HA (labeling Nup192-6HA and Nup159-6HA, respectively), Nup84, Nup98 (multiple FG-nucleoporins) and Nsp1. Pgk1 serves as control. c, Fluorescent images of cells with Nup192-eGFP-containing ATG8-dependent structures (marked by arrows) inside the vacuole after 24 h of nitrogen starvation (n=2 biologically independent experiments). ATG15 was deleted in order to block vacuolar digestion of autophagic bodies16. Deletion of ATG8, but not NVJ1 abolished accumulation of Nup192-containing structures inside the vacuole. Vph1-mars was used as marker of the vacuolar membrane. Scale bar, 5 μm. d, Degradation of Nup192-eGFP after induction of autophagy by nitrogen starvation (24 h) was measured by immunoblotting against eGFP in wildtype and nvj1∆ mutant cells as in Fig. 1c. Quantifications from n=3 biologically independent experiments are shown as mean ± s.d., NS: P ≥ 0.05, two-tailed Student’s t-tests. e, Degradation of Nup192-eGFP was measured by immunoblotting against eGFP in wildtype, atg39∆, atg40∆, and atg39∆ atg40∆ mutant cells before and after induction of autophagy by nitrogen starvation (24 h) (n=3 biologically independent experiments). f, Degradation of Nup192-eGFP was measured by immunoblotting against eGFP in wildtype, and cue5∆ mutant cells before and after induction of autophagy by nitrogen starvation (24 h). g, h, Degradation of Nup192-eGFP involves the Atg11 scaffold. (g) Degradation of Nup192-eGFP was measured by immunoblotting against eGFP in wildtype, atg11∆, and atg19∆ mutant cells before and after induction of autophagy by nitrogen starvation (24 h). Depicted are mean ± s.d. from n=3 biologically independent experiments, NS: P ≥ 0.05, ***p ≤ 0.001, two-tailed Student’s t-tests. (h) Degradation of Nup159-eGFP was measured by immunoblotting against eGFP in wildtype and atg11∆ mutant cells before and after induction of autophagy by nitrogen starvation (24 h). Depicted are mean ± s.d. from n=3 biologically independent experiments, ****p ≤ 0.0001, two-tailed Student’s t-tests. Data available in Statistical Source Data Extended Data Figure 2 and Unprocessed Blots Extended Data Figure 2.

Source data

Extended Data Fig. 3 Nup159 is an AIM-dependent Atg8 receptor.

a, Depiction of Nup159 protein domains including the AIMs and the corresponding AIM mutations. Co-immunoprecipitation of eGFP-Atg8 with wildtype Nup159-6HA or different nup159AIM mutants, followed by Western blot with the indicated antibodies (n=2 biologically independent experiments). Schematic overview of Nup159 domain architecture with the potential Atg8-interacting motifs (AIM) depicted. b, Atg8 turnover is normal in nup159AIM1 cells. Degradation of eGFP-Atg8 measured by immunoblotting against eGFP in wildtype cells or nup159AIM1 mutant cells. Quantifications from (n=3) experiments are shown as mean ± s.d.. c, Nup159 interacts with Atg11 in vivo. Co-immunoprecipitation of Nup159-6HA with eGFP-Atg11 expressed under the control of the ADH promoter in wildtype cells (n=2 biologically independent experiments). Immunoprecipitates were probed with anti-eGFP and anti-HA antibodies. Anti-Pgk1 serves as control. d, Mlp1 does not interact with Atg8 at the nuclear envelope. Fluorescent micrographs of the BiFC signal arising from pADH::VN-ATG8 with MLP1-VC are examined before and after 24 h of nitrogen starvation (n=2 biologically independent experiments). Inner-ring nucleoporin Nup170-mars marks fully assembled NPCs. Scale bar, 5 μm. e, The VN-Atg8 Y49A, L50A mutant does not interact with Nup159-VC at the nuclear envelope. Fluorescent micrographs of the BiFC signal arising from pADH::VN-ATG8 or pADH::VN-ATG8 Y49A, L50A mutant with NUP159-VC are examined at normal growth condition (n=2 biologically independent experiments). Inner-ring nucleoporin Nup170-mars marks fully assembled NPCs. Scale bar, 5 μm. f, NPC-containing nuclear vesicles visualized by CLEM. Additional examples of CLEM visualized vacuolar trapped autophagic bodies in atg15∆ cells loaded with NPC-containing nuclear vesicles (as in Fig. 3g). Scale bar, 500 nm and 200 nm for inset. Data available in Statistical Source Data Extended Data Figure 3 and Unprocessed Blots Extended Data Figure 3.

Source data

Extended Data Fig. 4 Nup159-dependent autophagy is important for clearing aberrant, clustered NPCs.

a, Nic96-eGFP degradation in wildtype and nup120∆ cells was induced by nitrogen starvation for indicated time. Measurement and quantification of free eGFP band was done as in Fig. 3d. The ratio of eGFP’/Dpm1 was normalized to 16 hours SD-N time point in wildtype. Dpm1 served as a control and was used for normalization (right). Depicted are mean ± s.d. from n=3 biologically independent experiments, *p ≤ 0.05, **p ≤ 0.005, ***p ≤ 0.001, two-tailed Student’s t-tests. b, Degradation of Nup188-eGFP in Nup116-deficient cells (nup116∆) is strongly impaired. Starvation-induced degradation of Nup188-eGFP in nup116∆ mutant background, was analysed as in Fig. 1a. Dpm1 served as a control and was used for normalization (right). Depicted are mean ± s.d. from n=3 biologically independent experiments normalized against the 24 hours SD-N time point in wildtype, *p ≤ 0.05, **p ≤ 0.005, ****p ≤ 0.0001, two-tailed Student’s t-tests. c, Degradation of Nup133-eGFP in Nup116-deficient cells (nup116∆) is strongly impaired. Starvation-induced degradation of Nup133-eGFP in nup116∆ mutant background, was analysed as in Fig. 1a. Dpm1 served as a control and was used for normalization (right). Depicted are mean ± s.d. from n=3 biologically independent experiments, *p ≤ 0.05, ***p ≤ 0.001, two-tailed Student’s t-tests. d, eGFP-Atg8 interacting proteins were measured by eGFP-Atg8 Co-IP as in Fig. 2c, for wildtype or nup116∆ mutant cells. For this analysis, cells with tagged Nup159-6HA, were subjected to immunoprecipitation of eGFP-Atg8 with GFP-Trap matrix (n=2 biologically independent experiments). Immunoprecipitates were probed with antibodies against eGFP tag, HA tag, Nup84, Nup98 (multiple FG-nucleoporins), Nsp1 and Pgk1 as control. e, Nup159 does not interact with NPC in nup116∆ cells at non-permissive temperature. Cells with tagged Nup159-6HA and Nup84-eGFP, were subjected to immunoprecipitation with GFP-Trap matrix and probed with antibodies against eGFP tag, HA tag, Nup98 (multiple FG-nucleoporins) and Pgk1 as control (n=2 biologically independent experiments). f, Degradation of Nic96-eGFP in the cluster background (nup120∆) is impaired in nup159AIM1 mutant cells. Starvation-induced degradation of Nic96-eGFP in nup120∆ nup159∆ mutant background complemented with wildtype NUP159 or the nup159AIM1 mutant, was analysed as in Fig. 3d. Dpm1 served as a control and was used for normalization (right). Depicted are mean ± s.d. from n=3 biologically independent experiments, *p ≤ 0.05, ***p ≤ 0.001, two-tailed Student’s t-tests. g, Hypothetical cartoon model of NPC turnover by selective autophagy. A fraction of fully assembled NPCs (I) clusters upon nitrogen starvation or even more dramatic upon genetic perturbation (nup120∆) (II). This leads to interaction of the intrinsic receptor Nup159 with Atg8 and packaging of nuclear vesicles into autophagosomes (III), which our data predicts as cellular intermediate. These autophagosomes will subsequently fuse with the vacuole for degradation (IV). Color-code of NPC is analogue to the NPC model (Extended Data Fig. 1a). Data available in Statistical Source Data Extended Data Figure 4 and Unprocessed Blots Extended Data Figure 4.

Source data

Supplementary information

Reporting Summary

Supplementary Video 1

CLEM tomogram of an NPC-containing nuclear vesicle in the vacuole in atg15∆ mutant cells. Description, segmentation and scale bar as in Fig. 3g.

Supplementary Tables 1 and 2

Supplementary Table 1: The strains used in this study. Supplementary Table 2: The plasmids used in this study.

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 and gels.

Source Data Fig. 4

Statistical source data.

Source Data Fig. 4

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. 4

Statistical source data.

Source Data Extended Data Fig. 4

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, CW., Wilfling, F., Ronchi, P. et al. Selective autophagy degrades nuclear pore complexes. Nat Cell Biol 22, 159–166 (2020). https://doi.org/10.1038/s41556-019-0459-2

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41556-019-0459-2

This article is cited by

Search

Advanced search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing