Systematic analysis of ribophagy in human cells reveals bystander flux during selective autophagy

  • Nature Cell Biologyvolume 20pages135143 (2018)
  • doi:10.1038/s41556-017-0007-x
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Ribosomes are abundant cellular machines1,2 that are regulated by assembly, supernumerary subunit turnover and nascent chain quality control mechanisms1,2,3,4,5. Moreover, nitrogen starvation in yeast has been reported to promote selective ribosome delivery to the vacuole in an autophagy conjugation system dependent manner, a process called ‘ribophagy’6,7. However, whether ribophagy in mammals is selective or regulated is unclear. Using Ribo–Keima flux reporters, we find that starvation or mTOR inhibition promotes VPS34-dependent ribophagic flux, which, unlike yeast, is largely independent of ATG8 conjugation and occurs concomitantly with other cytosolic protein autophagic flux reporters8,9. Ribophagic flux was not induced upon inhibition of translational elongation or nascent chain uncoupling, but was induced in a comparatively selective manner under proteotoxic stress induced by arsenite10 or chromosome mis-segregation11, dependent upon VPS34 and ATG8 conjugation. Unexpectedly, agents typically used to induce selective autophagy also promoted increased ribosome and cytosolic protein reporter flux, suggesting significant bulk or ‘bystander’ autophagy during what is often considered selective autophagy12,13. These results emphasize the importance of monitoring non-specific cargo flux when assessing selective autophagy pathways.

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  1. 1.

    Warner, J. R. The economics of ribosome biosynthesis in yeast. Trends Biochem. Sci. 24, 437–440 (1999).

  2. 2.

    Zhang, T., Shen, S., Qu, J. & Ghaemmaghami, S. Global analysis of cellular protein flux quantifies the selectivity of basal autophagy. Cell Rep. 14, 2426–2439 (2016).

  3. 3.

    Shao, S. & Hegde, R. S. Target selection during protein quality control. Trends Biochem. Sci. 41, 124–137 (2016).

  4. 4.

    Sung, M. K., Reitsma, J. M., Sweredoski, M. J., Hess, S. & Deshaies, R. J. Ribosomal proteins produced in excess are degraded by the ubiquitin–proteasome system. Mol. Biol. Cell 27, 2642–2652 (2016).

  5. 5.

    Sung, M. K. et al. A conserved quality-control pathway that mediates degradation of unassembled ribosomal proteins. eL ife 5, e19105 (2016).

  6. 6.

    Kraft, C., Deplazes, A., Sohrmann, M. & Peter, M. Mature ribosomes are selectively degraded upon starvation by an autophagy pathway requiring the Ubp3p/Bre5p ubiquitin protease. Nat. Cell Biol. 10, 602–610 (2008).

  7. 7.

    Ossareh-Nazari, B. et al. Cdc48 and Ufd3, new partners of the ubiquitin protease Ubp3, are required for ribophagy. EMBO Rep. 11, 548–554 (2010).

  8. 8.

    Nishida, Y. et al. Discovery of Atg5/Atg7-independent alternative macroautophagy. Nature 461, 654–658 (2009).

  9. 9.

    Tsuboyama, K. et al. The ATG conjugation systems are important for degradation of the inner autophagosomal membrane. Science 354, 1036–1041 (2016).

  10. 10.

    Anderson, P. & Kedersha, N. RNA granules. J. Cell Biol. 172, 803–808 (2006).

  11. 11.

    Santaguida, S., Vasile, E., White, E. & Amon, A. Aneuploidy-induced cellular stresses limit autophagic degradation. Gene. Dev. 29, 2010–2021 (2015).

  12. 12.

    Galluzzi, L. et al. Molecular definitions of autophagy and related processes. EMBO J. 36, 1811–1836 (2017).

  13. 13.

    Anding, A. L. & Baehrecke, E. H. Cleaning house: selective autophagy of organelles. Dev. Cell 41, 10–22 (2017).

  14. 14.

    Kishi-Itakura, C., Koyama-Honda, I., Itakura, E. & Mizushima, N. Ultrastructural analysis of autophagosome organization using mammalian autophagy-deficient cells. J. Cell Sci. 127, 4089–4102 (2014).

  15. 15.

    Katayama, H., Kogure, T., Mizushima, N., Yoshimori, T. & Miyawaki, A. A sensitive and quantitative technique for detecting autophagic events based on lysosomal delivery. Chem. Biol. 18, 1042–1052 (2011).

  16. 16.

    Mizushima, N., Yoshimori, T. & Levine, B. Methods in mammalian autophagy research. Cell 140, 313–326 (2010).

  17. 17.

    Ni, H. M. et al. Dissecting the dynamic turnover of GFP-LC3 in the autolysosome. Autophagy 7, 188–204 (2011).

  18. 18.

    Gross, L. A., Baird, G. S., Hoffman, R. C., Baldridge, K. K. & Tsien, R. Y. The structure of the chromophore within DsRed, a red fluorescent protein from coral. Proc. Natl Acad. Sci. USA 97, 11990–11995 (2000).

  19. 19.

    Chan, E. Y., Kir, S. & Tooze, S. A. siRNA screening of the kinome identifies ULK1 as a multidomain modulator of autophagy. J. Biol. Chem. 282, 25464–25474 (2007).

  20. 20.

    Hurley, J. H. & Young, L. N. Mechanisms of autophagy initiation. Annu. Rev. Biochem. 86, 225–244 (2017).

  21. 21.

    Ktistakis, N. T. & Tooze, S. A. Digesting the expanding mechanisms of autophagy. Trends Cell Biol. 26, 624–635 (2016).

  22. 22.

    Anderson, D. J. et al. Targeting the AAA ATPase p97 as an approach to treat cancer through disruption of protein homeostasis. Cancer Cell 28, 653–665 (2015).

  23. 23.

    Liu, J. et al. Beclin1 controls the levels of p53 by regulating the deubiquitination activity of USP10 and USP13. Cell 147, 223–234 (2011).

  24. 24.

    Harper, J. W. & Bennett, E. J. Proteome complexity and the forces that drive proteome imbalance. Nature 537, 328–338 (2016).

  25. 25.

    Hewitt, L. et al. Sustained Mps1 activity is required in mitosis to recruit O-Mad2 to the Mad1-C-Mad2 core complex. J. Cell Biol. 190, 25–34 (2010).

  26. 26.

    Santaguida, S., Tighe, A., D’Alise, A. M., Taylor, S. S. & Musacchio, A. Dissecting the role of MPS1 in chromosome biorientation and the spindle checkpoint through the small molecule inhibitor reversine. J. Cell Biol. 190, 73–87 (2010).

  27. 27.

    Panas, M. D., Ivanov, P. & Anderson, P. Mechanistic insights into mammalian stress granule dynamics. J. Cell Biol. 215, 313–323 (2016).

  28. 28.

    Buchan, J. R., Kolaitis, R. M., Taylor, J. P. & Parker, R. Eukaryotic stress granules are cleared by autophagy and Cdc48/VCP function. Cell 153, 1461–1474 (2013).

  29. 29.

    Ichimura, Y. et al. Phosphorylation of p62 activates the Keap1-Nrf2 pathway during selective autophagy. Mol. Cell 51, 618–631 (2013).

  30. 30.

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

  31. 31.

    Higgins, R. et al. The unfolded protein response triggers site-specific regulatory ubiquitylation of 40S ribosomal proteins. Mol. Cell 59, 35–49 (2015).

  32. 32.

    Yoshii, S. R., Kishi, C., Ishihara, N. & Mizushima, N. Parkin mediates proteasome-dependent protein degradation and rupture of the outer mitochondrial membrane. J. Biol. Chem. 286, 19630–19640 (2011).

  33. 33.

    Ran, F. A. et al. Genome engineering using the CRISPR-Cas9 system. Nat. Protoc. 8, 2281–2308 (2013).

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This work was supported by the National Institutes of Health (grants R37NS083524 and RO1GM095567 to J.W.H.). The authors acknowledge the Nikon Imaging Center and the Imaging and Data Analysis Core (Harvard Medical School) for imaging assistance.

Author information


  1. Department of Cell Biology, Harvard Medical School, Boston, MA, USA

    • Heeseon An
    •  & J. Wade Harper


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J.W.H. and H.A. conceived the study. H.A. performed all experiments. H.A. and J.W.H. analysed the data and wrote the paper.

Competing Interests

The authors declare no competing financial interests.

Corresponding author

Correspondence to J. Wade Harper.

Supplementary information

  1. Supplementary Information

    Supplementary Figures 1–6, Legends

  2. Life Sciences Reporting Summary

  3. Supplementary Table 1

    Sequences of guide RNAs used for CRISPR tagging and knock-out, and primers for genotyping and next-generation sequencing.

  4. Supplementary Table 2

    Statistics Source Data. The source data for statistical analyses of Figs. 2b, 2f-h, 3b, 4b, 4d-e, 4g, 4l, 5e-f, and Supplemental Figs. 2j, 3a, 5c, and 5h.

  5. Supplementary Table 3

    Information of antibodies used in the study.