Skip to main content

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

  • Article
  • Published:

Structure, lipid scrambling activity and role in autophagosome formation of ATG9A

Abstract

De novo formation of the double-membrane compartment autophagosome is seeded by small vesicles carrying membrane protein autophagy-related 9 (ATG9), the function of which remains unknown. Here we find that ATG9A scrambles phospholipids of membranes in vitro. Cryo-EM structures of human ATG9A reveal a trimer with a solvated central pore, which is connected laterally to the cytosol through the cavity within each protomer. Similarities to ABC exporters suggest that ATG9A could be a transporter that uses the central pore to function. Moreover, molecular dynamics simulation suggests that the central pore opens laterally to accommodate lipid headgroups, thereby enabling lipids to flip. Mutations in the pore reduce scrambling activity and yield markedly smaller autophagosomes, indicating that lipid scrambling by ATG9A is essential for membrane expansion. We propose ATG9A acts as a membrane-embedded funnel to facilitate lipid flipping and to redistribute lipids added to the outer leaflet of ATG9 vesicles, thereby enabling growth into autophagosomes.

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

Access options

Buy this article

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

Fig. 1: The structure of ATG9A.
Fig. 2: Dissection of the ATG9A architecture.
Fig. 3: Conformational stability of ATG9A.
Fig. 4: Functional studies of ATG9A.
Fig. 5: Models.

Similar content being viewed by others

Data availability

Cryo-EM density maps and atomic coordinates for human ATG9A have been deposited in the Electron Microscopy Data Bank and wwPDB, respectively, under accession codes EMD-22375 and PDB 7JLO (amphipol); EMD-22376 and PDB 7JLP (nanodisc); and EMD-22377 and PDB 7JLQ (LMNG). Source data are provided with this paper.

References

  1. Levine, B. & Kroemer, G. Biological functions of autophagy genes: a disease perspective. Cell 176, 11–42 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  2. Jiang, P. & Mizushima, N. Autophagy and human diseases. Cell Res. 24, 69–79 (2014).

    Article  CAS  PubMed  Google Scholar 

  3. Lamb, C. A., Yoshimori, T. & Tooze, S. A. The autophagosome: origins unknown, biogenesis complex. Nat. Rev. Mol. Cell Biol. 14, 759–774 (2013).

    Article  CAS  PubMed  Google Scholar 

  4. Yamamoto, H. et al. Atg9 vesicles are an important membrane source during early steps of autophagosome formation. J. Cell Biol. 198, 219–233 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. De Tito, S., Hervas, J. H., van Vliet, A. R. & Tooze, S. A. The Golgi as an assembly line to the autophagosome. Trends Biochem. Sci. 45, 484–496 (2020).

    Article  CAS  PubMed  Google Scholar 

  6. Orsi, A. et al. Dynamic and transient interactions of Atg9 with autophagosomes, but not membrane integration, are required for autophagy. Mol. Biol. Cell 23, 1860–1873 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Ohashi, Y. & Munro, S. Membrane delivery to the yeast autophagosome from the Golgi-endosomal system. Mol. Biol. Cell 21, 3998–4008 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Mari, M. et al. An Atg9-containing compartment that functions in the early steps of autophagosome biogenesis. J. Cell Biol. 190, 1005–1022 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Zhuang, X. et al. ATG9 regulates autophagosome progression from the endoplasmic reticulum in Arabidopsis. Proc. Natl Acad. Sci. USA 114, E426–E435 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Karanasios, E. et al. Autophagy initiation by ULK complex assembly on ER tubulovesicular regions marked by ATG9 vesicles. Nat. Commun. 7, 12420 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Itakura, E., Kishi-Itakura, C., Koyama-Honda, I. & Mizushima, N. Structures containing Atg9A and the ULK1 complex independently target depolarized mitochondria at initial stages of Parkin-mediated mitophagy. J. Cell Sci. 125, 1488–1499 (2012).

    Article  CAS  PubMed  Google Scholar 

  12. Koyama-Honda, I., Itakura, E., Fujiwara, T. K. & Mizushima, N. Temporal analysis of recruitment of mammalian ATG proteins to the autophagosome formation site. Autophagy 9, 1491–1499 (2013).

    Article  CAS  PubMed  Google Scholar 

  13. Kakuta, S. et al. Small GTPase Rab1B is associated with ATG9A vesicles and regulates autophagosome formation. FASEB J. 31, 3757–3773 (2017).

    Article  CAS  PubMed  Google Scholar 

  14. Imai, K. et al. Atg9A trafficking through the recycling endosomes is required for autophagosome formation. J. Cell Sci. 129, 3781–3791 (2016).

    Article  CAS  PubMed  Google Scholar 

  15. Suzuki, K., Akioka, M., Kondo-Kakuta, C., Yamamoto, H. & Ohsumi, Y. Fine mapping of autophagy-related proteins during autophagosome formation in Saccharomyces cerevisiae. J. Cell Sci. 126, 2534–2544 (2013).

    Article  CAS  PubMed  Google Scholar 

  16. Graef, M., Friedman, J. R., Graham, C., Babu, M. & Nunnari, J. ER exit sites are physical and functional core autophagosome biogenesis components. Mol. Biol. Cell 24, 2918–2931 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Gomez-Sanchez, R. et al. Atg9 establishes Atg2-dependent contact sites between the endoplasmic reticulum and phagophores. J. Cell Biol. 217, 2743–2763 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Mizushima, N. et al. Dissection of autophagosome formation using Apg5-deficient mouse embryonic stem cells. J. Cell Biol. 152, 657–668 (2001).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Nishimura, T. et al. Autophagosome formation is initiated at phosphatidylinositol synthase-enriched ER subdomains. EMBO J. 36, 1719–1735 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Maeda, S., Otomo, C. & Otomo, T. The autophagic membrane tether ATG2A transfers lipids between membranes. Elife 8, e45777 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  21. Valverde, D. P. et al. ATG2 transports lipids to promote autophagosome biogenesis. J. Cell Biol. 218, 1787–1798 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Osawa, T. et al. Atg2 mediates direct lipid transfer between membranes for autophagosome formation. Nat. Struct. Mol. Biol. 26, 281–288 (2019).

    Article  CAS  PubMed  Google Scholar 

  23. Young, A. R. et al. Starvation and ULK1-dependent cycling of mammalian Atg9 between the TGN and endosomes. J. Cell Sci. 119, 3888–3900 (2006).

    Article  CAS  PubMed  Google Scholar 

  24. He, C. et al. Recruitment of Atg9 to the preautophagosomal structure by Atg11 is essential for selective autophagy in budding yeast. J. Cell Biol. 175, 925–935 (2006).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Lai, L. T. F. et al. Subnanometer resolution cryo-EM structure of Arabidopsis thaliana ATG9. Autophagy 16, 575–583 (2020).

    Article  CAS  PubMed  Google Scholar 

  26. He, C., Baba, M., Cao, Y. & Klionsky, D. J. Self-interaction is critical for Atg9 transport and function at the phagophore assembly site during autophagy. Mol. Biol. Cell 19, 5506–5516 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Aryal, P., Sansom, M. S. & Tucker, S. J. Hydrophobic gating in ion channels. J. Mol. Biol. 427, 121–130 (2015).

    Article  CAS  PubMed  Google Scholar 

  28. Entova, S., Billod, J. M., Swiecicki, J. M., Martin-Santamaria, S. & Imperiali, B. Insights into the key determinants of membrane protein topology enable the identification of new monotopic folds. Elife 7, e40889 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  29. Schaeffer, R. D. et al. ECOD: identification of distant homology among multidomain and transmembrane domain proteins. BMC Mol. Cell Biol. 20, 18 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  30. Ho, H. et al. Structural basis for dual-mode inhibition of the ABC transporter MsbA. Nature 557, 196–201 (2018).

    Article  CAS  PubMed  Google Scholar 

  31. Choudhury, H. G. et al. Structure of an antibacterial peptide ATP-binding cassette transporter in a novel outward occluded state. Proc. Natl Acad. Sci. USA 111, 9145–9150 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Wang, Z., Hu, W. & Zheng, H. Pathogenic siderophore ABC importer YbtPQ adopts a surprising fold of exporter. Sci. Adv. 6, eaay7997 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Johnson, Z. L. & Chen, J. Structural basis of substrate recognition by the multidrug resistance protein MRP1. Cell 168, 1075–1085.e9 (2017).

    Article  CAS  PubMed  Google Scholar 

  34. Malvezzi, M. et al. Ca2+-dependent phospholipid scrambling by a reconstituted TMEM16 ion channel. Nat. Commun. 4, 2367 (2013).

    Article  PubMed  Google Scholar 

  35. Menon, I. et al. Opsin is a phospholipid flippase. Curr. Biol. 21, 149–153 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Chang, Q. L., Gummadi, S. N. & Menon, A. K. Chemical modification identifies two populations of glycerophospholipid flippase in rat liver ER. Biochemistry 43, 10710–10718 (2004).

    Article  CAS  PubMed  Google Scholar 

  37. Kaizuka, T. et al. An autophagic flux probe that releases an internal control. Mol. Cell 64, 835–849 (2016).

    Article  CAS  PubMed  Google Scholar 

  38. Sun, D., Wu, R., Zheng, J., Li, P. & Yu, L. Polyubiquitin chain-induced p62 phase separation drives autophagic cargo segregation. Cell Res. 28, 405–415 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Brunner, J. D., Lim, N. K., Schenck, S., Duerst, A. & Dutzler, R. X-ray structure of a calcium-activated TMEM16 lipid scramblase. Nature 516, 207–212 (2014).

    Article  CAS  PubMed  Google Scholar 

  40. Lee, B. C. et al. Gating mechanism of the extracellular entry to the lipid pathway in a TMEM16 scramblase. Nat. Commun. 9, 3251 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Guardia, C. M. et al. Structure of human ATG9A, the only transmembrane protein of the core autophagy machinery. Cell Reports 31, 107837 (2020).

    Article  CAS  PubMed  Google Scholar 

  42. Feng, S. et al. Cryo-EM studies of TMEM16F calcium-activated ion channel suggest features important for lipid scrambling. Cell Rep. 28, 1385 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. Falzone, M. E. et al. Structural basis of Ca2+-dependent activation and lipid transport by a TMEM16 scramblase. Elife 8, e43229 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  44. Herzik, M. A. Jr., Wu, M. & Lander, G. C. Achieving better-than-3-Å resolution by single-particle cryo-EM at 200 keV. Nat. Methods 14, 1075–1078 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Suloway, C. et al. Automated molecular microscopy: the new Leginon system. J. Struct. Biol. 151, 41–60 (2005).

    Article  CAS  PubMed  Google Scholar 

  46. Zheng, S. Q. et al. MotionCor2: anisotropic correction of beam-induced motion for improved cryo-electron microscopy. Nat. Methods 14, 331–332 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Lander, G. C. et al. Appion: an integrated, database-driven pipeline to facilitate EM image processing. J. Struct. Biol. 166, 95–102 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Rohou, A. & Grigorieff, N. CTFFIND4: fast and accurate defocus estimation from electron micrographs. J. Struct. Biol. 192, 216–221 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  49. Zhang, K. Gctf: real-time CTF determination and correction. J. Struct. Biol. 193, 1–12 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Zivanov, J. et al. New tools for automated high-resolution cryo-EM structure determination in RELION-3. Elife 7, e42166 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  51. Punjani, A., Rubinstein, J. L., Fleet, D. J. & Brubaker, M. A. cryoSPARC: algorithms for rapid unsupervised cryo-EM structure determination. Nat. Methods 14, 290–296 (2017).

    Article  CAS  PubMed  Google Scholar 

  52. Scheres, S. H. & Chen, S. Prevention of overfitting in cryo-EM structure determination. Nat. Methods 9, 853–854 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  53. Tan, Y. Z. et al. Addressing preferred specimen orientation in single-particle cryo-EM through tilting. Nat. Methods 14, 793–796 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  54. Emsley, P., Lohkamp, B., Scott, W. G. & Cowtan, K. Features and development of Coot. Acta Crystallogr. D Biol. Crystallogr. 66, 486–501 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  55. Liebschner, D. et al. Macromolecular structure determination using X-rays, neutrons and electrons: recent developments in Phenix. Acta Crystallogr. D Struct. Biol. 75, 861–877 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  56. Chen, V. B. et al. MolProbity: all-atom structure validation for macromolecular crystallography. Acta Crystallogr. D Biol. Crystallogr. 66, 12–21 (2010).

    Article  CAS  PubMed  Google Scholar 

  57. Lomize, M. A., Pogozheva, I. D., Joo, H., Mosberg, H. I. & Lomize, A. L. OPM database and PPM web server: resources for positioning of proteins in membranes. Nucleic Acids Res. 40, D370–D376 (2012).

    Article  CAS  PubMed  Google Scholar 

  58. Baker, N. A., Sept, D., Joseph, S., Holst, M. J. & McCammon, J. A. Electrostatics of nanosystems: application to microtubules and the ribosome. Proc. Natl Acad. Sci. USA 98, 10037–10041 (2001).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  59. Klesse, G., Rao, S., Sansom, M. S. P. & Tucker, S. J. CHAP: a versatile tool for the structural and functional annotation of ion channel pores. J. Mol. Biol. 431, 3353–3365 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  60. Ashkenazy, H. et al. ConSurf 2016: an improved methodology to estimate and visualize evolutionary conservation in macromolecules. Nucleic Acids Res. 44, W344–W350 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  61. Goddard, T. D. et al. UCSF ChimeraX: meeting modern challenges in visualization and analysis. Protein Sci. 27, 14–25 (2018).

    Article  CAS  PubMed  Google Scholar 

  62. Holm, L. DALI and the persistence of protein shape. Protein Sci. 29, 128–140 (2020).

    Article  CAS  PubMed  Google Scholar 

  63. Li, Z., Jaroszewski, L., Iyer, M., Sedova, M. & Godzik, A. FATCAT 2.0: towards a better understanding of the structural diversity of proteins. Nucleic Acids Res. 48, W60–W64 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  64. Zimmermann, L. et al. A completely reimplemented MPI bioinformatics toolkit with a new HHpred server at its core. J. Mol. Biol. 430, 2237–2243 (2018).

    Article  CAS  PubMed  Google Scholar 

  65. Dolinsky, T. J., Nielsen, J. E., McCammon, J. A. & Baker, N. A. PDB2PQR: an automated pipeline for the setup of Poisson–Boltzmann electrostatics calculations. Nucleic Acids Res. 32, W665–W667 (2004).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  66. Lee, J. et al. CHARMM-GUI membrane builder for complex biological membrane simulations with glycolipids and lipoglycans. J. Chem. Theory Comput. 15, 775–786 (2019).

    Article  CAS  PubMed  Google Scholar 

  67. Lee, J. et al. CHARMM-GUI input generator for NAMD, GROMACS, AMBER, OpenMM, and CHARMM/OpenMM simulations using the CHARMM36 additive force field. J. Chem. Theory Comput. 12, 405–413 (2016).

    Article  CAS  PubMed  Google Scholar 

  68. Phillips, J. C. et al. Scalable molecular dynamics with NAMD. J. Comput. Chem. 26, 1781–1802 (2005).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  69. Huang, J. et al. CHARMM36m: an improved force field for folded and intrinsically disordered proteins. Nat. Methods 14, 71–73 (2017).

    Article  CAS  PubMed  Google Scholar 

  70. Klauda, J. B. et al. Update of the CHARMM all-atom additive force field for lipids: validation on six lipid types. J. Phys. Chem. B 114, 7830–7843 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  71. Jorgensen, W. L., Chandrasekhar, J., Madura, J. D., Impey, R. W. & Klein, M. L. Comparison of simple potential functions for simulating liquid water. J. Chem. Phys. 79, 926–935 (1983).

    Article  CAS  Google Scholar 

  72. Adelman, S. A. & Doll, J. D. Generalized Langevin equation approach for atom/solid-surface scattering: collinear atom/harmonic chain model. J. Chem. Phys. 61, 4242–4245 (1974).

    Article  CAS  Google Scholar 

  73. Darden, T., York, D. & Pedersen, L. Particle mesh Ewald: an N.Log(N) method for Ewald sums in large systems. J. Chem. Phys. 98, 10089–10092 (1993).

    Article  CAS  Google Scholar 

  74. Humphrey, W., Dalke, A. & Schulten, K. VMD: visual molecular dynamics. J. Mol. Graph 14, 33–38 (1996).

    Article  CAS  PubMed  Google Scholar 

  75. Falzone, M. E. & Accardi, A. Reconstitution of proteoliposomes for phospholipid scrambling and nonselective channel assays. Methods Mol. Biol. 2127, 207–225 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  76. Brunner, J. D. & Schenck, S. Preparation of proteoliposomes with purified TMEM16 protein for accurate measures of lipid scramblase activity. Methods Mol. Biol. 1949, 181–199 (2019).

    Article  CAS  PubMed  Google Scholar 

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

    Article  CAS  PubMed  Google Scholar 

  78. Saitoh, T. et al. Atg9a controls dsDNA-driven dynamic translocation of STING and the innate immune response. Proc. Natl Acad. Sci. USA 106, 20842–20846 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

We thank K. Ohashi, S. Chowdhury and G. C. Lander for their contributions to preliminary studies of this project; S. Chowdhury and G. C. Lander for also providing cryo-EM training; M. Shirakawa, K. Igarashi, Y. Ishida, C. Saito, and I. Koyama-Honda for technical assistance with cellular studies; B. Anderson for technical assistance with cryo-EM operation; J-C. Ducom and the Scripps HPC Facility for computational support for cryo-EM data processing and MD simulations; and I. J. Macrae for critical reading of the manuscript. The MultiBac expression system, cDNA of BRIL, and pMSP2N2 (Addgene plasmid no. 29520), pMXs-puro, Atg9a KO MEFs, pCG-gag-pol and pCG-VSV-G retrovirus plasmids were gifts from I. Berger, R. Stevens, S. Sligar, T. Kitamura, T. Saitoh and T. Yasui, respectively. This work was supported by grants from the National Institute of Health (GM092740 to T.O., GM069832 to S.F. and GM127390 to N.V.G.), the Welch Foundation (I-1505 to N.V.G.), a Grant-in-Aid for Exploratory Research for Advanced Technology (ERATO) (JPMJER1702 to N.M.) from the Japan Science and Technology Agency (JST). Computational analyses of EM data were performed using shared instrumentation at The Scripps Research Institute funded by NIH S10OD021634.

Author information

Authors and Affiliations

Authors

Contributions

S.M. purified proteins, collected and processed cryo-EM data and performed lipid scrambling assays; H.Y. performed autophagy assays, fluorescence and 3D CLEM imaging, and analyses. L.N.K. performed bioinformatics analyses under supervision of N.V.G. C.M.G performed MD simulations under supervision of S.F. S.T. collected and analyzed 3D CLEM data. C.O. generated plasmids and expressed proteins. N.M. supervised cellular studies. T.O. conceived the project, assisted structural and biochemical analyses and wrote the initial draft of the manuscript. All authors discussed the results and edited or commented on the manuscript.

Corresponding author

Correspondence to Takanori Otomo.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Peer review information Anke Sparmann and Inês Chen were the primary editors on this article and managed its editorial process and peer review in collaboration with the rest of the editorial team.

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

Extended data

Extended Data Fig. 1 Conformational variability of ATG9A.

a, Superposition of ATG9A structures in amphipols (gray) and nanodiscs (colored). b, Conservation mapping of ATG9A. c, The structure of ATG9A in LMNG micelles. d,e, Superpositions of ATG9A structures in nanodiscs (colored) and LMNG (gray and violet): overall superposition (d) and focused on a protomer (e). f,g, Top views of the nanodisc (f) and LMNG (g) structures visualizing the dilation of the central pore. h, CHAP analysis of the LMNG structure.

Extended Data Fig. 2 Similarities between the N- and C-terminal halves of ATG9A.

a,b, The bundles of α-helices flanking the TMH1–2 (a) and TMH3–4 (b) hairpins. c, Superposition of the bundles. d, Structural overlay of the N- and C-terminal halves generated by superposing TMH1–2 and TMH3–4. e, FATCAT flexible structural alignment of the N- and C-terminal halves. f, Sequence alignment between the N- and C-terminal halves of ATG9A.

Extended Data Fig. 3 Structural alignments of ATG9A with ABCexps.

a,b, Structures of YbtQ (a, PDB 6P6J) and MRP1 (b, PDB 5UJA) bound to their substrates. TMH1–3 are colored violet. c, A cutaway view of the central pore of ATG9A. d,e, Superpositions of ATG9A with YbtQ (d) and MRP1 (e). ATG9A’s TMH3–4 can be superimposed with TMH1–2 from the identified ABCexp structures using as a guide for the helix register the conserved Asp (D398 in ATG9 with D53 in MsbA, D56 in YbtQ, D355 in MRP1). In all cases, ABCexps’ substrates locate to the central pore of ATG9A.

Extended Data Fig. 4 MD simulation of the nanodisc structure.

a, The inter-residue distances measured are indicated on the nanodisc structure. b–d, Analyses of the simulation. The top panels are structure snapshots at t = 894 ns. The middle panels show time-dependent changes of the three pore openings between three selected pairs of residues at the A-C (b), B-A (c), and C-B (d) chain interfaces. The bottom panels show the trajectory of individual lipids that penetrated through the interface during the simulation. Each trace shows the Z position of the phosphate head of a lipid of interest, normalized by the average z coordinate of the luminal (0) and cytosolic (1) leaflets. The simulation shows lipid movements induced by the dynamic behavior of the protein. The luminal sides of the A-C and B-A interfaces (blue and orange lines in b and c) opened early (t = ~100–200 ns), followed by insertions of the headgroups of the lipids #59 and #42 from the luminal leaflet through the A-C and B-A interfaces, respectively (b, c, cyan lines, t = ~300–450 ns). As these headgroups moved toward the cytosolic side, the lipids #5 and #61 in the luminal leaflet inserted their headgroups into the pore through the A-C and B-A interfaces, respectively (b, c). Subsequently, the cytosolic side of the A-C and B-A interfaces opened (b, c, green lines), and at the A-C interface, the lipid #258 in the cytosolic leaflet entered the pore. Conversely, the C-B interface remained closed longer with respect to the A-C and B-A interfaces, but it eventually started to open after t = ~700 ns, allowing lipid #2 in the luminal leaflet to insert its headgroup into the luminal side of the pore (d). All the lipids mentioned here became laterally orientated following the placement of their headgroups into the pore. Source data for plots are available online.

Source data

Extended Data Fig. 5 Dithionite permeation assays.

a,b, Top panels show the schemes of the experiments with no protein (a) and ATG9A (b). 26 µM NBD-phosphoethanolamine (PEA), which was synthesized by conjugating NBD-chloride and PEA and purified by agarose gel electrophoresis, was included in the (proteo)liposome reconstitution mixtures. After reconstitutions, NBD-PEA was removed by dialysis. Fluorescence was recorded as described for the dithionite lipid scramblase assays. 30 mM dithionite was added to the reaction mixtures at t = 100 s. The initial drops of fluorescence indicate that the residual amounts of NBD-PEA at the outside of the (proteo)liposomes were quenched. Between the two experiments, the addition of dithionite quenched the same amount of fluorescence and left the same amount of fluorescence, indicating that the same amount of NBD-PEA was included in the (proteo)liposomes. Fluorescence remained almost unchanged after reaching plateaus quickly. At 600 s, 0.1 % TritonX-100 was added to the reaction mixtures to dissolve the membranes for full quenching. The same amount of fluorescence was lost between the two experiments, confirming that the same amounts of NBD-PEA were included in liposomes and proteoliposomes. Thus, the ATG9A proteoliposomes were impermeable to dithionite. The experiments were repeated three times. All results are shown in different colors. Source data are available online.

Source data

Extended Data Fig. 6 BSA back extraction lipid scrambling assays.

a, Schematic for the BSA back extraction-based lipid scrambling assay. NBD-lipids are preferentially extracted by fatty acid-free BSA. Upon extraction, the fluorescence of BSA-bound NBD-lipids is reduced by ~ 50%. b, The results with reconstituted liposomes and ATG9A-containing proteoliposomes. 1.5 mg/ml BSA was added to each reaction at t = 100 s. BSA extracts NBD-lipids only from the outer leaflet of the membranes. Thus, in the absence of scrambling, ~50% of NBD-lipids on the outer leaflet lose their fluorescence by ~50%, reducing the total fluorescence by ~25%. In the presence of ATG9A, an additional ~15% of fluorescence was lost upon BSA addition, which indicates that NBD-lipids that were originally in the inner leaflet were exposed to BSA upon flipping. Source data are available online.

Source data

Extended Data Fig. 7 GFP-LC3-RFP autophagic flux assays with ATG9A mutants.

a, Locations of the mutations on the ATG9A nanodisc structure. Hydrophilic and hydrophobic amino acids were replaced with hydrophobic and hydrophilic ones, respectively. b,c, Flow cytometry autophagy flux assays. GFP/RFP fluorescence ratios of Torin 1-treated ATG9A KO HeLa cells stably expressing GFP-LC3-mRFP and ATG9A-FLAG mutants are plotted. Data shown in (b) and (c) are the results of the first and second rounds of mutant screenings, respectively. Data of cell populations (n = 4800 for b and n = 2500 for c) are presented as box plots. The box limit, the horizontal line, and the whisker show the first and third quartiles, the median, and the minimum and maximum values, respectively. No outliers are shown. The assay was repeated for the mutants shown in Fig. 4, and they were reproducible. The data shown in blue and green are of mutations in the lateral cavity and central pore, respectively. d,e, Western blotting of ATG9A KO HeLa cells stably expressing ATG9A-FLAG mutants. Source data for the box plots are available online.

Source data

Extended Data Fig. 8 Autophagosome formation in ATG9A mutant-expressing cells.

a,b, ATG9A KO HeLa cells (a) and Atg9a KO MEFs (b) stably expressing GFP-LC3-mRFP and ATG9A-FLAG mutants were observed by fluorescence microscopy. GFP fluorescence was monitored. In (a) additional mutants M26 (T412W) and M32 (M8 + M26) are shown. ATG9A KO HeLa ells and WT ATG9A-FLAG-expressing cells are the same image as shown in Fig. 4. Images were acquired after 3 h starvation. M26 yielded typical GFP-LC3 puncta while M32 generated smaller autophagosomes. The results are similar to those of M28 (T419W) and M33 (M8 + M28), which were selected for followed-up 3D CLEM and biochemical studies, as shown in Fig. 4. (b) MEFs were starved for 1 h, and GFP fluorescence was monitored. In Atg9a KO MEFs, GFP-LC3 forms larger puncta than typical autophagosomes. Expression of WT ATG9A-FLAG, as well as M26 and M28, generated ring-shaped autophagosomes, while M8-expressing, M32-expressing and M33-expressing cells yielded markedly smaller GFP-puncta. These observations are consistent with the results with HeLa cells, leading to the conclusion that the observed effects of the mutations in ATG9A are cell type-independent.

Supplementary information

Supplementary Information

Supplementary Note 1, Supplementary Figures 1–11 and Supplementary Tables 1 and 2.

Reporting Summary

Supplementary Data 1

HHpred hits with various ATG9 sequences and sequence alignments.

Supplementary Video 1

Movie of the MD simulation in a top cutaway view and three side views.

Supplementary Video 2

3D reconstruction of a cup-shaped phagophore observed in M33-expressing cells. A cup-shaped phagophore, a closed autophagosome and the ER are colored green, light green and red, respectively.

Source data

Source Data Fig. 4

Statistical source data

Source Data Extended Data Fig. 4

Statistical source data

Source Data Extended Data Fig. 5

Statistical source data

Source Data Extended Data Fig. 6

Statistical source data

Source Data Extended Data Fig. 7

Statistical source data

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Maeda, S., Yamamoto, H., Kinch, L.N. et al. Structure, lipid scrambling activity and role in autophagosome formation of ATG9A. Nat Struct Mol Biol 27, 1194–1201 (2020). https://doi.org/10.1038/s41594-020-00520-2

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41594-020-00520-2

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