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:

Structurally derived universal mechanism for the catalytic cycle of the tail-anchored targeting factor Get3

Nature Structural & Molecular Biology volume 29, pages 820–830 (2022)Cite this article

Subjects

Abstract

Tail-anchored (TA) membrane proteins, accounting for roughly 2% of proteomes, are primarily targeted posttranslationally to the endoplasmic reticulum membrane by the guided entry of TA proteins (GET) pathway. For this complicated process, it remains unknown how the central targeting factor Get3 uses nucleotide to facilitate large conformational changes to recognize then bind clients while also preventing exposure of hydrophobic surfaces. Here, we identify the GET pathway in Giardia intestinalis and present the structure of the Get3–client complex in the critical postnucleotide-hydrolysis state, demonstrating that Get3 reorganizes the client-binding domain (CBD) to accommodate and shield the client transmembrane helix. Four additional structures of GiGet3, spanning the nucleotide-free (apo) open to closed transition and the ATP-bound state, reveal the details of nucleotide stabilization and occluded CBD. This work resolves key conundrums and allows for a complete model of the dramatic conformational landscape of Get3.

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

Access options

Buy this article

  • Purchase on SpringerLink
  • Instant access to full article PDF
Buy now

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

Fig. 1: Identification of the GET pathway in G. intestinalis.
Fig. 2: Structures of GiGet3 in the ‘open’ and ‘closed’ states.
Fig. 3: Cryo-EM structure of the posthydrolysis GiGet3–TA complex.
Fig. 4: Conformational changes induced by the nucleotide state and TA protein binding.
Fig. 5: Universal model of the Get3 conformations that drive targeting.

Similar content being viewed by others

Data availability

Atomic coordinates and structure factors for the apo GiGet3 crystal structure and ATP-bound GiGet3 have been deposited in the PDB under accession codes 7SPZ and 7SPY, respectively. The atomic coordinates and cryo-EM maps for the ADP-bound GiGet3–TA complex have been deposited to the PDB under the accession code 7SQ0 and Electron Microscopy Data Bank (EMDB) under the accession codes EMD-25374 (overall Get3–TA complex) and EMD-25373 (NBD of the Get3–TA complex). The apo GiGet3 cryo-EM map was deposited to the EMDB under the accession code EMD-25375. Source data are provided with this paper.

References

  1. Guna, A. & Hegde, R. S. Transmembrane domain recognition during membrane protein biogenesis and quality control. Current Biol. 28, R498–R511 (2018).

    Article  CAS  Google Scholar 

  2. Kutay, U., Hartmann, E. & Rapoport, T. A. A class of membrane proteins with a C-terminal anchor. Trends Cell Biol. 3, 72–75 (1993).

    Article  CAS  PubMed  Google Scholar 

  3. Denic, V. A portrait of the GET pathway as a surprisingly complicated young man. Trends Biochem. Sci. 37, 411–417 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Wattenberg, B. W. & Lithgow, T. Targeting of C-terminal tail-anchored proteins: understanding how cytoplasmic activities are anchored to intracellular membranes. Traffic 2, 66–71 (2001).

    Article  CAS  PubMed  Google Scholar 

  5. Chartron, J. W., Clemons, W. M. Jr. & Suloway, C. J. The complex process of GETting tail-anchored membrane proteins to the ER. Curr. Opin. Struct. Biol. 22, 217–224 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Borgese, N., Colombo, S. & Pedrazzini, E. The tale of tail-anchored proteins. J. Cell Biol. 161, 1013–1019 (2003).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Rabu, C., Schmid, V., Schwappach, B. & High, S. Biogenesis of tail-anchored proteins: the beginning for the end? J. Cell Sci. 122, 3605–3612 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Cavalier-Smith, T. & Chao, E. E.-Y. Phylogeny and classification of phylum Cercozoa (protozoa). Protist 154, 341–358 (2003).

    Article  PubMed  Google Scholar 

  9. Wang, F., Brown, E. C., Mak, G., Zhuang, J. & Denic, V. A chaperone cascade sorts proteins for posttranslational membrane insertion into the endoplasmic reticulum. Mol. Cell 40, 159–171 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Simpson, P. J., Schwappach, B., Dohlman, H. G. & Isaacson, R. L. Structures of Get3, Get4, and Get5 provide new models for TA membrane protein targeting. Structure 18, 897–902 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Rome, M. E., Rao, M., Clemons, W. M. & Shan, S. O. Precise timing of ATPase activation drives targeting of tail-anchored proteins. Proc. Natl Acad. Sci. USA 110, 7666–7671 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Chartron, J. W., Gonzalez, G. M. & Clemons, W. M. A structural model of the Sgt2 protein and its interactions with chaperones and the Get4/Get5 complex. J. Biol. Chem. 286, 34325–34334 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Chio, U. S., Chung, S., Weiss, S. & Shan, S. O. A protean clamp guides membrane targeting of tail-anchored proteins. Proc. Natl Acad. Sci. USA 114, E8585–E8594 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Chartron, J. W., Suloway, C. J. M., Zaslaver, M. & Clemons, W. M. Structural characterization of the Get4/Get5 complex and its interaction with Get3. Proc. Natl Acad. Sci. USA 107, 12127–12132 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Shan, S. O. Guiding tail-anchored membrane proteins to the endoplasmic reticulum in a chaperone cascade. J. Biol. Chem. 294, 16577–16586 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. McDowell, M. A. et al. Structural basis of tail-anchored membrane protein biogenesis by the GET insertase complex. Molecular Cell 80, 72–86.e7 (2020).

    Article  CAS  PubMed  Google Scholar 

  17. Mariappan, M. et al. The mechanism of membrane-associated steps in tail-anchored protein insertion. Nature 477, 61–66 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Mateja, A. et al. The structural basis of tail-anchored membrane protein recognition by Get3. Nature 461, 361–366 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Suloway, C. J. M., Chartron, J. W., Zaslaver, M. & Clemons, W. M. Model for eukaryotic tail-anchored protein binding based on the structure of Get3. Proc. Natl Acad. Sci. USA 106, 14849–14854 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Stefer, S. et al. Structural basis for tail-anchored membrane protein biogenesis by the Get3-receptor complex. Science 333, 758–762 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Bozkurt, G. et al. Structural insights into tail-anchored protein binding and membrane insertion by Get3. Proc. Natl Acad. Sci. USA 106, 21131–21136 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Gristick, H. B. et al. Crystal structure of ATP-bound Get3–Get4–Get5 complex reveals regulation of Get3 by Get4. Nat. Struct. Mol. Biol. 21, 437–442 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Mateja, A. et al. Structure of the Get3 targeting factor in complex with its membrane protein cargo. Science 347, 1152–1155 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Koonin, E. V. A superfamily of ATPases with diverse functions containing either classical or deviant ATP-binding motif. J. Mol. Biol. 229, 1165–1174 (1993).

    Article  CAS  PubMed  Google Scholar 

  25. Yamagata, A. et al. Structural insight into the membrane insertion of tail-anchored proteins by Get3. Genes Cells 15, 29–41 (2010).

    Article  CAS  PubMed  Google Scholar 

  26. Xing, S. et al. Loss of GET pathway orthologs in Arabidopsis thaliana causes root hair growth defects and affects SNARE abundance. Proc. Natl Acad. Sci. USA 114, E1544–E1553 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  27. Kumar, T., Maitra, S., Rahman, A. & Bhattacharjee, S. A conserved Guided Entry of Tail-anchored pathway is involved in the trafficking of a subset of membrane proteins in Plasmodium falciparum. PLoS Pathog. 17, 1–39 (2021).

    Google Scholar 

  28. Bodensohn, U. S. et al. The intracellular distribution of the components of the GET system in vascular plants. Biochim. Biophys. Acta: Mol. Cell Res. 1866, 1650–1662 (2019).

    Article  CAS  Google Scholar 

  29. Anderson, S. A., Satyanarayan, M. B., Wessendorf, R. L., Lu, Y. & Fernandez, D. E. A homolog of guided entry of tail-anchored proteins functions in membrane-specific protein targeting in chloroplasts of Arabidopsis. Plant Cell 33, 2812–2833 (2021).

    Article  PubMed  PubMed Central  Google Scholar 

  30. Adam, R. D. Giardia duodenalis: biology and pathogenesis. Clin. Microbiol. Rev. https://doi.org/10.1128/CMR.00024-19 (2021).

  31. Rome, M. E., Chio, U. S., Rao, M., Gristick, H. & ou Shan, S. Differential gradients of interaction affinities drive efficient targeting and recycling in the get pathway. Proc. Natl Acad. Sci. USA 111, E4929–E4935 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Jumper, J. et al. Highly accurate protein structure prediction with AlphaFold. Nature 596, 583–589 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Asseck, L. Y. et al. Endoplasmic reticulum membrane receptors of the GET pathway are conserved throughout eukaryotes. Proc. Natl Acad. Sci. USA https://doi.org/10.1073/pnas.2017636118 (2021).

  34. Yamamoto, Y. & Sakisaka, T. Molecular machinery for insertion of tail-anchored membrane proteins into the endoplasmic reticulum membrane in mammalian cells. Mol. Cell 48, 387–397 (2012).

    Article  CAS  PubMed  Google Scholar 

  35. Lin, K.-F., Fry, M. Y., Saladi, S. M. & Clemons, W. M. Molecular basis of tail-anchored integral membrane protein recognition by the cochaperone Sgt2. J. Biol. Chem. https://doi.org/10.1016/j.jbc.2021.100441 (2021).

  36. Cho, H. & Shan, S. O. Substrate relay in an Hsp70-cochaperone cascade safeguards tail-anchored membrane protein targeting. EMBO J. https://doi.org/10.15252/embj.201899264 (2018).

  37. Fry, M. Y., Saladi, S. M., Cunha, A. & Clemons, W. M. Jr Sequence-based features that are determinant for tail-anchored membrane protein sorting in eukaryotes. Traffic 22, 306–318 (2021).

    Article  CAS  PubMed  Google Scholar 

  38. Aurrecoechea, C. et al. GiardiaDB and trichDB: integrated genomic resources for the eukaryotic protist pathogens Giardia lamblia and Trichomonas vaginalis. Nucleic Acids Res. 37, D526–D530 (2008).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  39. Schuldiner, M. et al. The GET complex mediates insertion of tail-anchored proteins into the ER membrane. Cell 134, 634–645 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. Zhao, G. & London, E. An amino acid ‘transmembrane tendency’ scale that approaches the theoretical limit to accuracy for prediction of transmembrane helices: relationship to biological hydrophobicity. Protein Sci. 15, 1987–2001 (2006).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Keszei, A., Yip, M., Hsieh, T.-C. & Shao, S. Structural insights into metazoan pretargeting get complexes. Nat. Struct. Mol. Biol. 28, 1029–1037 (2021).

    Article  CAS  PubMed  Google Scholar 

  42. Chio, U. S., Chung, S., Weiss, S. & Shan, S. A chaperone lid ensures efficient and privileged client transfer during tail-anchored protein targeting. Cell Reports 26, 37–44.e7 (2019).

    Article  CAS  PubMed  Google Scholar 

  43. Salonen, L. M., Ellermann, M. & Diederich, F. Aromatic rings in chemical and biological recognition: energetics and structures. Angew. Chem. Int. Ed. 50, 4808–4842 (2011).

    Article  CAS  Google Scholar 

  44. Shao, S., Rodrigo-Brenni, M. C., Kivlen, M. H. & Hegde, R. S. Mechanistic basis for a molecular triage reaction. Science 355, 298–302 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Morgens, D. W. et al. Retro-2 protects cells from ricin toxicity by inhibiting ASNA1-mediated ER targeting and insertion of tail-anchored proteins. eLife 8, e48434 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Thompson, J. D., Gibson, T. J., Plewniak, F., Jeanmougin, F. & Higgins, D. G. The CLUSTAL X Windows interface: flexible strategies for multiple sequence alignment aided by quality analysis tools. Nucleic Acids Res. 25, 4876–4882 (1997).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Hehl, A. B. & Marti, M. Secretory protein trafficking in Giardia intestinalis. Mol. Microbiol. 53, 19–28 (2004).

    Article  CAS  PubMed  Google Scholar 

  48. Martincová, E. et al. Probing the biology of Giardia intestinalis mitosomes using in vivo enzymatic tagging. Mol. Cell. Biol. 35, 2864–2874 (2015).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  49. Saladi, S. M., Maggiolo, A. O., Radford, K. & Clemons, W. M. Structural biologists, let’s mind our colors. Preprint at bioRxiv https://doi.org/10.1101/2020.09.22.308593 (2020).

  50. Pei, J., Kim, B.-H. & Grishin, N. V. PROMALS3D: a tool for multiple protein sequence and structure alignments. Nucleic Acids Res. 36, 2295–2300 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  51. Waterhouse, A. M., Procter, J. B., Martin, D. M. A., Clamp, M. & Barton, G. J. Jalview version 2–a multiple sequence alignment editor and analysis workbench. Bioinformatics 25, 1189–1191 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  52. Finn, R. D., Clements, J. & Eddy, S. R. HMMER web server: interactive sequence similarity searching. Nucleic Acids Res. 39, W29–W37 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  53. Consortium, T. U. UniProt: the universal protein knowledgebase in 2021. Nucleic Acids Res. 49, D480–D489 (2020).

    Article  CAS  Google Scholar 

  54. Richter, D. J., Berney, C., Strassert, J. F. H., Burki, F. & de Vargas, C. EukProt: a database of genome-scale predicted proteins across the diversity of eukaryotic life. Preprint at bioRxiv https://doi.org/10.1101/2020.06.30.180687 (2020).

  55. Katoh, K., Rozewicki, J. & Yamada, K. D. MAFFT online service: multiple sequence alignment, interactive sequence choice and visualization. Briefings Bioinform. 20, 1160–1166 (2017).

    Article  CAS  Google Scholar 

  56. 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 

  57. Mistry, J. et al. Pfam: the protein families database in 2021. Nucleic Acids Res. 49, D412–D419 (2020).

    Article  PubMed Central  CAS  Google Scholar 

  58. Steinegger, M. & Söding, J. MMseqs2 enables sensitive protein sequence searching for the analysis of massive data sets. Nat. Biotechnol. 35, 1026–1028 (2017).

    Article  CAS  PubMed  Google Scholar 

  59. Capella-Gutiérrez, S., Silla-Martínez, J. M. & Gabaldón, T. trimAl: a tool for automated alignment trimming in large-scale phylogenetic analyses. Bioinformatics 25, 1972–1973 (2009).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  60. Nguyen, L.-T., Schmidt, H. A., von Haeseler, A. & Minh, B. Q. IQ-TREE: a fast and effective stochastic algorithm for estimating maximum-likelihood phylogenies. Mol. Biol. Evol. 32, 268–274 (2014).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  61. Kalyaanamoorthy, S., Minh, B. Q., Wong, T. K. F., von Haeseler, A. & Jermiin, L. S. ModelFinder: fast model selection for accurate phylogenetic estimates. Nat. Methods 14, 587–589 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  62. Hoang, D. T., Chernomor, O., von Haeseler, A., Minh, B. Q. & Vinh, L. S. UFBoot2: improving the ultrafast bootstrap approximation. Mol. Biol. Evol. 35, 518–522 (2017).

    Article  PubMed Central  CAS  Google Scholar 

  63. Letunic, I. & Bork, P. Interactive Tree Of Life (iTOL) v5: an online tool for phylogenetic tree display and annotation. Nucleic Acids Res. 49, W293–W296 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  64. Keister, D. B. Axenic culture of Giardia lamblia in TYI-S-33 medium supplemented with bile. Trans. Royal Soc. Tropical Med. Hyg. 77, 487–488 (1983).

    Article  CAS  Google Scholar 

  65. Doležal, P. et al. Giardia mitosomes and Trichomonad hydrogenosomes share a common mode of protein targeting. Proc. Natl Acad. Sci. USA 102, 10924–10929 (2005).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  66. Voleman, L. et al. Giardia intestinalis mitosomes undergo synchronized fission but not fusion and are constitutively associated with the endoplasmic reticulum. BMC Biol. 15, 27–27 (2017).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  67. Schindelin, J. et al. Fiji: an open-source platform for biological-image analysis. Nat. Methods 9, 676–682 (2012).

    Article  CAS  PubMed  Google Scholar 

  68. Najdrová, V., Stairs, C. W., Vinopalová, M., Voleman, L. & Doležal, P. The evolution of the puf superfamily of proteins across the tree of eukaryotes. BMC Biol. 18, 77 (2020).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  69. 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).

    Article  CAS  PubMed  Google Scholar 

  70. Cox, J. et al. Andromeda: a peptide search engine integrated into the MaxQuant environment. J. Proteome Res. 10, 1794–1805 (2011).

    Article  CAS  PubMed  Google Scholar 

  71. Tyanova, S., Temu, T. & Cox, J. The MaxQuant computational platform for mass spectrometry-based shotgun proteomics. Nat. Protoc. 11, 2301–2319 (2016).

    Article  CAS  PubMed  Google Scholar 

  72. Goedhart, J. & Luijsterburg, M. S. VolcaNoseR is a web app for creating, exploring, labeling and sharing volcano plots. Sci. Rep. 10, 20560 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  73. Chun, E. et al. Fusion partner toolchest for the stabilization and crystallization of G protein-coupled receptors. Cell Struct. Funct. 20, 967–976 (2012).

    CAS  Google Scholar 

  74. Minor, W., Cymborowski, M., Otwinowski, Z. & Chruszcz, M. HKL-3000: the integration of data reduction and structure solution – from diffraction images to an initial model in minutes. Acta Crystallogr. Sect. D. 62, 859–866 (2006).

    Article  CAS  Google Scholar 

  75. Afonine, P. V. et al. Towards automated crystallographic structure refinement with phenix.refine. Acta Crystallogr. Sect. D. 68, 352–367 (2012).

    Article  CAS  Google Scholar 

  76. Headd, J. J. et al. Use of knowledge-based restraints in phenix.refine to improve macromolecular refinement at low resolution. Acta Crystallogr. Sect. D. 68, 381–390 (2012).

    Article  CAS  Google Scholar 

  77. Afonine, P. V., Grosse-Kunstleve, R. W., Urzhumtsev, A. & Adams, P. D. Automatic multiple-zone rigid-body refinement with a large convergence radius. J. Appl. Crystallogr. 42, 607–615 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  78. Bunkóczi, G. & Read, R. J. Improvement of molecular-replacement models with Sculptor. Acta Crystallogr. Sect. D. 67, 303–312 (2011).

    Article  CAS  Google Scholar 

  79. Murshudov, G. N. et al. REFMAC5 for the refinement of macromolecular crystal structures. Acta Crystallogr. Sect. D. 67, 355–367 (2011).

    Article  CAS  Google Scholar 

  80. Williams, C. J. et al. MolProbity: more and better reference data for improved all-atom structure validation. Protein Sci. 27, 293–315 (2018).

    Article  CAS  PubMed  Google Scholar 

  81. Winn, M. D. et al. Overview of the CCP4 suite and current developments. Acta Crystallogr. Sect. D. 67, 235–242 (2011).

    Article  CAS  Google Scholar 

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

    Article  PubMed  Google Scholar 

  83. 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 

  84. 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 

  85. Asarnow, D., Palovcak, E. & Cheng, Y. asarnow/pyem: UCSF pyem v0.5. Zenodo https://doi.org/10.5281/zenodo.3576630 (2019).

  86. 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 

  87. Pintilie, G., Chen, D. H., Haase-Pettingell, C. A., King, J. A. & Chiu, W. Resolution and probabilistic models of components in cryo-EM maps of mature p22 bacteriophage. Biophys. J. 110, 827–839 (2016).

    Article  CAS  PubMed  Google Scholar 

  88. Pettersen, E. F. et al. USCF Chimera – a visualization system of exploratory research and analysis. J. Comput. Chem. 25, 1605–1612 (2004).

    Article  CAS  PubMed  Google Scholar 

  89. Topf, M. et al. Protein structure fitting and refinement guided by cryo-EM density. Structure 16, 295–307 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  90. Pettersen, E. F. et al. UCSF ChimeraX: structure visualization for researchers educators, and developers. Protein Sci. 30, 70–82 (2021).

    Article  CAS  PubMed  Google Scholar 

  91. Olp, M. D., Kalous, K. S. & Smith, B. C. ICEKAT: an interactive online tool for calculating initial rates from continuous enzyme kinetic traces. BMC Bioinf. 21, 186 (2020).

    Article  CAS  Google Scholar 

  92. Cleveland, W. S. Robust locally weighted regression and smoothing scatterplots. J. Am. Stat. Assoc. 74, 829–836 (1979).

    Article  Google Scholar 

  93. Mock, J.-Y., Xu, Y., Ye, Y. & Clemons, W. M. Structural basis for regulation of the nucleo-cytoplasmic distribution of Bag6 by TRC35. Proc. Natl Acad. Sci. USA 114, 11679–11684 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  94. Chartron, J. W., VanderVelde, D. G. & Clemons, W. M. Structures of the Sgt2/SGTA dimerization domain with the Get5/UBL4A UBL domain reveal an interaction that forms a conserved dynamic interface. Cell Reports 2, 1620–1632 (2012).

    Article  CAS  PubMed  Google Scholar 

Download references

Acknowledgements

We thank A. Malyutin, S. Chen, H. Scott, G. Lander and J. Kaiser for technical assistance. We thank S.-O.u Shan, R. Voorhees, D. Rees and A. Barlow for discussion and comments. We thank Luboš, Voleman and V. Dohnálek for their help with microscopy and phylogenetic analysis, respectively, V. Mechem for help with protein purification and crystallization, A. Barlow for help with the ATPase assay and Y. Liu for help with the in vitro TA protein capture assay. Crystallography data were collected at the SSRL beamline 12-2. We are grateful to the Gordon and Betty Moore Foundation for support of the Molecular Observatory at the California Institute of Technology. SSRL operations are supported by the US Department of Energy and US National Institutes of Health (NIH). (Cryo)Electron microscopy on the GiGet3–TA protein complex was done in the Beckman Institute Resource Center for Transmission Electron Microscopy at Caltech. A portion of this research was supported by NIH grant no. U24GM129547 and performed at the Pacific Northwest Center for Cryo-EM at Oregon Health & Science University and accessed through EMSL (grid.436923.9), a Department of Energy Office of Science User Facility sponsored by the Office of Biological and Environmental Research. Some computing resources were provided by the Extreme Science and Engineering Discovery Environment (XSEDE) resources, which is supported by the National Science Foundation grant no. Acl-1052574(108). Work in the United States was supported by the NIH grant nos. R01GM097572, R01GM125063 and DP1GM105385 to W.M.C. Work in the Czech Republic was supported by the Czech Science Foundation grant no. 20-25417S, a grant from Charles University Grant Agency (project no. 1396217) and the project ‘Centre for research of pathogenicity and virulence of parasites’ (grant no. CZ.02.1.01/0.0/0.0/16 019/0000759) funded by the European Regional Development Fund. S.M.S. was supported by National Science Foundation Graduate Research fellowship under grant no. 11444469. S.M.S. and M.Y.F. were supported by a NIH/National Research Service Award Training grant no. T32GM07616.

Author information

Authors and Affiliations

  1. Division of Chemistry and Chemical Engineering, California Institute of Technology, Pasadena, CA, USA

    Michelle Y. Fry, Ailiena O. Maggiolo, Shyam M. Saladi & William M. Clemons Jr

  2. Department of Parasitology, Faculty of Science, BIOCEV, Charles University, Prague, Czech Republic

    Vladimíra Najdrová & Pavel Doležal

Authors
  1. Michelle Y. Fry
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Vladimíra Najdrová
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Ailiena O. Maggiolo
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Shyam M. Saladi
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Pavel Doležal
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. William M. Clemons Jr
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

W.M.C., P.D. and M.Y.F. conceived the study. V.N. identified the Get3 homolog in Giardia and performed the verification using biochemical and cell biology methods. V.N. and S.M.S. identified other GET pathway components in Giardia and performed the phyologenetic analyses throughout eukaryotes. M.Y.F. performed the biochemistry to demonstrate GiSgt2 capture of TA proteins and identification of substrates in G. intestinalis. M.Y.F. prepared samples for structural studies, crystallized apo and ATP-bound GiGet3, and performed the all cryo-EM analyses and processing. M.Y.F., A.O.M. and W.M.C. refined the crystallography data and built the atomic model into the electron density. M.Y.F., A.O.M. and W.M.C. built the model into the GiGet3–TA complex cryo-EM map and M.Y.F. and W.M.C conducted the model building for the apo GiGet3 cryo-EM map. M.Y.F. and W.M.C. wrote the manuscript with input from all authors. All authors edited and approved the manuscript.

Corresponding author

Correspondence to William M. Clemons Jr.

Ethics declarations

Competing interests

The authors declare no competing interests.

Peer review

Peer review information

Nature Structural & Molecular Biology thanks the anonymous reviewers for their contribution to the peer review of this work. Peer reviewer reports are available. Primary Handling Editor: Florian Ullrich, in collaboration with the Nature Structural & Molecular Biology team.

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 Alignment of Get3.

The full alignment of Get3 homologs partially shown in Fig. 1A. Conserved Get3 features are marked by bars below the alignment: P-loop (green), Switch I (magenta), Switch II (blue), A-loop (orange), the TRC40 insert (black), and the CXXC motif (black). Secondary structure for the Get3/TA•ATP complex (cyan) and Get3D53N •ATP (orange) are depicted above the alignment – cylinders for α-helices, arrows for β-sheets, and dashed lines for residues that were disordered. The region that contains H4/5 highlighted in purple. Conserved residues that were demonstrated to play a role in Get4 binding have asterisks below the alignment. Residues are colored using the ClustalX color scheme46.

Extended Data Fig. 2 Validation of G. intestinalis GET components.

A) ATPase assays with GiGet3 (blue) & GiGet3D53N (orange). Absorbance was measured at a wavelength of 360nm at varying ATP concentrations. Experiment was done in triplicate. The lines represent the data fit using a LOESS (LOcally Estimated Scatterplot Smoothing) regression92. B) A schematic of experimental set-up which was conducted twice. ScSsa1 transfers ScBos1 with an engineered BPA crosslinking site to GiSgt2. Crosslinking is initiated by UV exposure. C) A western blot visualizing the crosslinked GiSgt2/ScBos1 complexes before and after transfer and with and without UV light treatment. C) GiGet3 and putative GiTA proteins were recombinantly expressed in E. coli then purified 2-3 times (depending on putative client) utilizing an affinity column to the Strep-tag on the TA proteins. Get3 could only be visualized if the TA protein expressed and bound to the TA protein. For western analysis, eluted samples were run on a gel and transferred to a membrane. The membrane was split in half, marked by dotted line, with the top blotted with an anti-GiGet3 antibody and the bottom by an anti-SUMO antibody. Putative TA proteins tested (GL50803_005161, GL50803_003896, GL50803_0015983, GL50803_003869, GL50803_0010803, GL50803_009849 and GL50803_0024512) are arranged by increasing TMD hydrophobicity (labeled in parentheses) using the TM tendency scale. GiGet3 was clearly identified in the eluates of GL50803_0024512 and GL50803_009849.

Source data

Extended Data Fig. 3 Alignment of Get4 homologs.

A) (Left) AlphaFold2 structural prediction of the identified GiGet4 colored based on confidence from blue (most confident) to orange (least confident). Experimentally determined structure of the yeast Get4 (center)14 and human Get4 (PDBID: 6AU8) (right)93 are colored from N- to C-terminus using the viridis color scheme (purple to yellow). B) Alignment of Get4 homologs including: G. intestinalis, H. sapiens, S. cerevisiae, A. queenslandica, S. pombe, N. crassa, A. fumigatus, and P. falciparum. Conserved residues that were demonstrated to play a role in Get3 binding are highlighted with asterisks above. Residues are colored as in Extended Data Fig. 122.

Extended Data Fig. 4 Identification of a Get2 homolog in G. intestinalis.

A) An alignment of the identified Get2 from G. intestinalis with CAML from H. sapiens and Get2 from S. cerevisiae. The three predicted TMDs are shown with red cylinders above the alignment and the conserved N-terminal helices that tether to Get3 are shown as blue cylinders. The two conserved residues involved in Get3 binding are marked by asterisks below the alignment. Residues are colored using the ClustalX color scheme. Representative images from three experiments for (B) detection of GiGet2 using Stimulated Emission Depletion (STED) microscopy images of G. intestinalis trophozites. Get2 with a C-terminal V5 tag was detected by an anti-V5 antibody (yellow) and the ER membrane was labeled by an anti-PDI2 antibody (magenta). Images are merged in the third panel. (C) The ER localization of GiGet2 differs from the cellular localization of GiGet3. GiGet3 with a N-terminal HA-tag was labeled by an anti-HA antibody (yellow) and GiGet2 is labeled by the same method in (A) (magenta). Images are merged in the third panel. Scale bars represent 5µm.

Extended Data Fig. 5 Structures and alignment of Sgt2.

A) AlphaFold2 structural prediction of the identified GiSgt2 colored based on confidence as in Extended Data Fig. 3A. Structural models of fungal Sgt2 domains: the N-terminal domain from S. cerevisiae (orange) (PDBID:2LXB)94, the TPR domain from A. fumigatus (yellow) (PDBID:3SZ7)12 and the C-domain from S. cerevisiae (green)35. B) An alignment of Sgt2 homologs: G. intestinalis, H. sapiens, S. cerevisiae, S. pombe, A. fumigatus, C. thermophium, and C. savignyi. The three domains are indicated by lines above the alignment, N-terminal dimerization (yellow), TPR-domain (orange), and substrate binding C-domain (green). Residues are colored using the ClustalX color scheme.

Extended Data Fig. 6 The crystal structure of apo GiGet3.

A) Size exclusion chromatograms of nickel eluate for Get3 and (B) SDS-PAGE gels of the peak highlighted in (A). GiGet3 was purified 10-20 separate times in order to produce enough material for crystal trays and cryo-EM analysis. B) The asymmetric unit of apo GiGet3 contains two distinct monomers of Get3 (gray), which are designated apo1 and apo2. Each monomer pairs with its respective symmetry equivalent in the neighboring asymmetric unit to form two distinct dimers. One dimer, apo1 (magenta), has the ’open’ conformation. The other dimer, apo2 (purple), has a conformation that is slightly more closed than the previously seen ‘open’ conformations. C) Alignment of the two monomers highlighting additional slight differences between. Apo1 is colored from N to C terminus using the viridis color map and apo2 in grey. The monomers are aligned to the P-loops and there are no notable differences in the NBD. The flexibility of the CBD is demonstrated here. Most distinct is a shift in the loop between H5 and H6 (residues 121-139) with most of this region disordered in apo2. Additionally, H5 is shorter at the N-terminus in apo2 compared to apo1 due to a close contact with a symmetry mate that presumably disrupts the helix (red arrows in F). A 2Fo-Fc map shown as blue mesh at 1.0 sigma showing the region that includes the Zn2+ ions on the symmetry axes for (D) apo1 (outlined in cyan) and (E) apo2 (outlined in orange); these positions correspond to the arrows in (B). F) A single layer of the crystal lattice for apo GiGet3 crystals. Grey monomers define the asymmetric unit and symmetry related dimers are colored for either apo1 (magenta) or apo2 (purple).

Source data

Extended Data Fig. 7 SPA data processing of apo GiGet3.

A) An aligned and dose weighted micrograph from the data collection (7,607 micrographs) with apo GiGet3 sample particles selected with green circles. Scale bar represents 50nm. B) 2D class averages of particles used for the reconstruction. C) Processing of data through cryoSPARCv3.2.0 and RELION 3.1.2. D) Two views of the angular distribution of particles. Particle concentration is displayed by color and length (blue to red). Density filtered to 7 sigma for various helices that are shown as sticks: E) H7 (cyan) & H9 (magenta) and F) H10 (magenta) & H11 (cyan).

Extended Data Fig. 8 The crystal structure of GiGet3D53N •ATP.

A) Size exclusion chromatograms of nickel eluate for Get3D53N and (B) a SDS-PAGE gel of the peak highlighted in (A). GiGet3D53N was purified 10-20 separate times in order to produce enough material for crystal trays. C) A cartoon model of the GiGet3D53N •ATP crystals. The asymmetric unit is shown in (yellow) with symmetry related molecules in grey. Regions of interest in the crystals are shown with arrows. Corresponding close-up views are shown in outlined panels boxed corresponding to the arrows in (C) each shown in sticks colored as before with 2Fo-Fc density contoured at 1.5 σ and colored blue in C-I. D) The bridging Zn2+ ion coordinated by four cysteines, two from each monomer (Cys287 & Cys290, magenta arrow). E) Similar representation as in B for the Zn2+ ion coordinated via a crystal contact by the surface residues His6, Asp10 and the same residues in a symmetry related molecule. In C & D the identity of the Zn2+ ions are confirmed by positive density (magenta mesh) in an anomalous double difference map obtained from data collected at two energies, 9.669keV and 9.659keV, which are just above and below the absorption K-edge of zinc. The anomalous double difference map is contoured at 6 sigma. F-H) Three views of the active site. F) The ATP molecule, surrounding loops, and coordinated waters within the active site. G) The residues and waters coordinating the Mg2+ ion. H) In the active site a Pro167 and Asn53 orient the catalytic water molecule above the γ-phosphate in the ATP molecule. I) A SO42- ion from the buffer bound to two arginines (Arg291 & Arg295).

Source data

Extended Data Fig. 9 SPA data processing of GiGet3-TA complexes.

A) Size exclusion chromatogram of nickel eluate of Get3-TA complexes and an SDS-page gel of the peak from one of the 10 separate purifications of the complex. A single fraction was used for structure determination B) An aligned micrograph from the data collection (2,732 micrographs) with sample particles selected with yellow circles. Scale bar represents 50nm. C) 2D class averages of particles used for the reconstruction. D) Processing of data through cryoSPARCv3.2.0 and RELION 3.1.2. E) Two views of the angular distribution of particles. Particle concentration is displayed by color and length (blue to red).

Source data

Extended Data Fig. 10 Representative resolution and density of GiGet3-TA complex.

A) The local resolution of the unsharpened map presented in Extended Data Fig. 9. Representative density of (B) H11, (C) H7 & H9, (D) active site with ADP molecule and Mg2+ ion, and (E) β-sheet 1. F) Representative density (grey) of the reconstruction without any symmetry imposed of H11 as shown in (B). G) The unsharpened map of the reconstruction before imposing symmetry. Density corresponding to the TA protein and H4/5 are colored as they are in Fig. 3A,B.

Supplementary information

Supplementary Information

Supplementary Figs. 1–7 and References.

Reporting Summary

Peer Review File

Supplementary Video 1

Morph created in PyMOL v.2.5.0 (ref. 10) of the Get3 dimer from apo (most open to closed: apo1 (magenta), apo2 (purple), then ‘closed apo’ (blue, EM structure)), to ATP-bound (yellow) and then client-bound, posthydrolysis (teal) states. As apo Get3 transitions from the ‘open’ to ‘closed’ form, the NBD of Get3 expands in the closed apo conformation. Once ATP binds, the two monomers come together, constricting the NBD. During the transition from apo to ATP-bound, the CBD domain does not undergo major remodeling. Due to client binding and ATP hydrolysis, the NBD domain expands, the dimer rotates slightly open, causing considerable remodeling in the CBD. Mainly, H6 comes down toward the active site and this movement is coupled with a restructuring of H5 to become parallel to H7 and H9 and H4 becomes ordered. In the following frames, the Get3 dimer is rotated 70 Å to focus on the active site of one monomer (apo2). First, the conserved features of the active site are highlighted: P-loop (green), Switch I (magenta), Switch II (blue) and A-loop (orange). Using this color scheme, Get3 active site is morphed from apo2 to the ATP-bound state and then to the client-bound, posthydrolysis state.

Supplementary Video 2

A side by side morph of the states in Fig. 4b (helical orientation and numbering is consistent with Fig. 4b) as a cartoon (left) and a surface representation (right). In the surface representation cylindrical helices are traced for clarity and residues are colored based on their hydrophobicity from hydrophilic (blue) to hydrophobic (orange) using the transmembrane tendency scale3. The occlusion of the hydrophobic groove by H5 in both the apo and ATP-bound form is clearly illustrated in the surface view. Binding of ATP causes Switch II to rotate, allowing Lys22 to interact with the ATP molecule across the dimer interface. Switch I rotates down to position the catalytic aspartate near the ATP molecule. Dramatic remodeling of the CBD is observed after the TA protein binds and ATP is hydrolyzed. ATP hydrolysis results in the release of Switch II, which triggers a restructuring of the CBD causing H7 to twist. This results in a reorganization of the hydrophobic face of the H7 that subsequently forms part of the wall of the hydrophobic groove in the CBD. In conjunction with this movement, H10 shifts away from the active site, disrupting the Get3/4 binding interface. H6 moves down toward the active site, forming the bottom of the hydrophobic groove to facilitate client binding. H5, which initially shields the hydrophobic residues of H7 and H9, moves to become parallel to H7 and H9. The movement of H5 exposes these shielded residues in H7 and H9. H4 transitions from disordered to ordered, becoming parallel to H5, H7 and H9 and shifting slightly away causing an expansion of the CBD. Altogether, these movements demonstrate a breathing of the Get3 monomer after ATP hydrolysis and client binding. Formation of the hydrophobic groove is observed with the restructuring of the helices in the CBD.

Supplementary Table 1

A list of the Get3 homologs identified throughout eukaryotes, separated by supergroups as shown in Fig. 1b.

Supplementary Table 2

A list of the proteins identified in the elution of the GiGet3 pull-downs from G. intestinalis lysate as plotted in Fig. 1d. Proteins are sorted by their enrichment and those that are significantly enriched are highlighted in orange. Significance was determined using a two-sided t-test.

Supplementary Table 3

A list of putative TA proteins from the G. intestinalis genome with their predicted TMD sequence, sorted by hydrophobicity using the transmembrane tendency scale40.

Source data

Source Data Fig. 1

Unprocessed western blots.

Source Data Extended Data Fig. 2

Unprocessed western blots.

Source Data Extended Data Fig. 2

Statistical source data.

Source Data Extended Data Fig. 6

Unprocessed gels.

Source Data Extended Data Fig. 8

Unprocessed gels.

Source Data Extended Data Fig. 9

Unprocessed gels.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Fry, M.Y., Najdrová, V., Maggiolo, A.O. et al. Structurally derived universal mechanism for the catalytic cycle of the tail-anchored targeting factor Get3. Nat Struct Mol Biol 29, 820–830 (2022). https://doi.org/10.1038/s41594-022-00798-4

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41594-022-00798-4

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