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Structural organization of the retriever–CCC endosomal recycling complex

Nature Structural & Molecular Biology (2023)Cite this article

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Abstract

The recycling of membrane proteins from endosomes to the cell surface is vital for cell signaling and survival. Retriever, a trimeric complex of vacuolar protein-sorting-associated protein (VPS)35L, VPS26C and VPS29, together with the CCC complex comprising coiled-coil domain-containing (CCDC)22, CCDC93 and copper metabolism domain-containing (COMMD) proteins, plays a crucial role in this process. The precise mechanisms underlying retriever assembly and its interaction with CCC have remained elusive. Here, we present a high-resolution structure of retriever in humans determined using cryogenic electron microscopy. The structure reveals a unique assembly mechanism, distinguishing it from its remotely related paralog retromer. By combining AlphaFold predictions and biochemical, cellular and proteomic analyses, we further elucidate the structural organization of the entire retriever–CCC complex across evolution and uncover how cancer-associated mutations in humans disrupt complex formation and impair membrane protein homeostasis. These findings provide a fundamental framework for understanding the biological and pathological implications associated with retriever–CCC-mediated endosomal recycling.

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Fig. 1: Cryo-EM structure of retriever reveals a unique assembly mechanism.
Fig. 2: VPS35L bridges VPS26C and VPS29 through conserved surfaces.
Fig. 3: Disruption of retriever assembly affects membrane protein homeostasis.
Fig. 4: Structural model of CCDC22–CCDC93 binding to retriever.
Fig. 5: Structural model of CCDC22–CCDC93 binding to DENND10.
Fig. 6: Structural model of CCDC22–CCDC93 binding to COMMD.
Fig. 7: Overall model of the retriever–CCC complex.

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Data availability

Cryo-EM maps and models have been deposited in the EMDB (accession numbers EMD-40884, EMD-40885 and EMD-40886) and the PDB (accession numbers PDB 8SYM, PDB 8SYN and PDB 8SYO). AlphaFold-Multimer-derived models are available in ModelArchive (https://modelarchive.org) under the accession codes ma-cfy9y (human retriever), ma-h9nwf (human retriever–CCDC22–CCDC93), ma-o592z (human CCDC22–CCDC93–DENND10), ma-itenz (human COMMD1–COMMD10 ring–CCDC22–CCDC93), ma-icsco (Danio rerio COMMD1–COMMD10 ring–CCDC22–CCDC93), ma-45mmt (Dictyostelium discoideum COMMD1–COMMD10 ring–CCDC22–CCDC93) and ma-2g80v (human retriever–CCC complex). MS data have been deposited at the MassIVE repository (accession numbers MSV000092100, MSV000092102, MSV000092103, MSV000092104). To our knowledge, all information required to reanalyze the data reported here is publicly available. Any additional data that we inadvertently missed will be shared upon reasonable request. This paper does not report original code. Source data are provided with this paper.

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Acknowledgements

We thank the ResearchIT at Iowa State University for hardware resources, installation of AlphaFold and ongoing computational and diagnostic support. We also thank A. Lemoff and the Proteomics Core as well as A. Mobley and the Flow Cytometry Core at UT Southwestern. Electron microscopy data were collected in collaboration with the Structural Biology Laboratory with help from Y. Li, using the Cryo-Electron Microscopy Facility at the UT Southwestern Medical Center (partially supported by grant RP220582 from the Cancer Prevention and Research Institute of Texas for cryo-EM studies) and the Iowa State University Cryo-EM Facility (supported by the Roy J. Carver Structural Initiative). Research was supported by funding from the National Institutes of Health (R35 GM128786 to B.C., and R01 DK107733 to E.B. and D.D.B.), the National Science Foundation CAREER award (CDF 2047640 to B.C.) and Roy J. Carver Charitable Trust seed funds (to B.C.).

Author information

Author notes

  1. These authors contributed equally: Daniel J. Boesch, Amika Singla, Yan Han.

Authors and Affiliations

  1. Roy J. Carver Department of Biochemistry, Biophysics and Molecular Biology, Iowa State University, Ames, IA, USA

    Daniel J. Boesch, Daniel A. Kramer & Baoyu Chen

  2. Department of Internal Medicine, University of Texas Southwestern Medical Center, Dallas, TX, USA

    Amika Singla, Qi Liu, Kohei Suzuki & Xin Long

  3. Department of Biophysics, University of Texas Southwestern Medical Center, Dallas, TX, USA

    Yan Han & Zhe Chen

  4. Cryo-EM Facility, Office of Biotechnology, Iowa State University, Ames, IA, USA

    Puneet Juneja

  5. Information Technology Services, Iowa State University, Ames, IA, USA

    Xuefeng Zhao

  6. Division of Oncology Research, College of Medicine, Mayo Clinic, Rochester, MN, USA

    Michael J. Medlyn & Daniel D. Billadeau

  7. Department of Molecular Biology, University of Texas Southwestern Medical Center, Dallas, TX, USA

    Ezra Burstein

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Contributions

E.B., B.C. and D.D.B. conceived the project. E.B. oversaw cell biological and proteomic experiments performed by A.S. with help from Q.L., K.S. and X.L. B.C. oversaw protein purification, biochemical experiments and AlphaFold predictions performed by D.J.B. with help from D.A.K. and X.Z. Z.C. and Y.H. oversaw cryo-EM grid preparation, data collection, single-particle reconstruction and atomic model building. P.J. supervised initial cryo-EM grid preparation and data collection performed by D.J.B. at Iowa State. M.J.M. and D.D.B. helped with cellular experiments and data interpretation. B.C., Z.C., D.J.B. and Y.H. analyzed structures. E.B., B.C. and Z.C. drafted the manuscript and prepared figures with assistance from all other authors.

Corresponding authors

Correspondence to Zhe Chen, Baoyu Chen or Ezra Burstein.

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The authors declare no competing interests.

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Nature Structural & Molecular Biology thanks Oleksiy Kovtun and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Primary Handling Editor: Katarzyna Ciazynska, in collaboration with the Nature Structural & Molecular Biology team. Peer reviewer reports are available.

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Extended data

Extended Data Fig. 1 Purification and cryo-EM structural determination of Retriever.

(a) Representative gel filtration chromatography of the purified Retriever complex. Purification was repeated at least 5 times. (b) Representative cryo-EM micrograph from a total of 2,892 micrographs used for data processing. (c) Representative 2D class averages. (d) Euler angle distribution plots for Retriever (upper) and the locally refined VPS29 with the NT ‘belt’ peptide and the CT region of VPS35L (lower). (e) Local resolution map of Retriever (upper) and the locally refined VPS29 with the NT ‘belt’ peptide and the CT region of VPS35L (lower). (f) Fourier Shell Correlation (FSC) plot for Retriever (upper) and the locally refined VPS29 with the NT ‘belt’ peptide and the CT region of VPS35L (lower). (g) Schematic showing cryo-EM data processing steps for obtaining 3D reconstruction of Retriever. The three maps deposited to PDB/EMDB are labeled.

Source data

Extended Data Fig. 2 Structural comparison between Retriever and Retromer.

(a) Surface representation of electrostatic potentials of Retriever vs. Retromer (PDB: 7U6F). (b) Superimposition of individual subunits from Retriever (colored) vs. Retromer (gray). (c) Intermolecular interface between VPS35L and VPS29 vs. VPS35 and VPS29, shown as surface representations of electrostatic potentials. (d) Same as in (C), with VPS35L and VPS26C vs. VPS35 and VPS26A. (e) Detailed comparison of VPS29 binding surface on VPS35L in Retriever vs. VPS35 in Retromer. For clarity, the backbones of VPS29 are shown as loops. VPS35L and VPS35 are shown as cartoons and semi-transparent surface representations of electrostatic potentials.

Extended Data Fig. 3 Cellular and proteomic analysis of VPS35L mutants.

(a) Huh-7 hepatocellular carcinoma cells carrying the indicated mutations in VPS35L (EV, empty vector). Immunoprecipitation of VPS35L followed by western blot for the indicated proteins is shown. (b) Immunoprecipitation of VPS35L followed by competitive elution of native complexes using HA peptide, and separation of the complexes in blue native gels. After transfer, the complexes were immunoblotted with the indicated antibodies. (c) Heatmap representation of protein-protein interaction results using proteomics. VPS35L was immunoprecipitated from the indicated Huh-7 stable cell lines (in triplicate samples) and the results are expressed as fold compared to Huh-7 control cells (darker blue depicts greater depletion compared to WT VPS35L). Statistical significance as determined by Student’s t-test is indicated in color scale (yellow indicating p<0.05, and grey indicating p>0.05). (d) Immunoprecipitation of VPS35L carrying indicated point mutations expressed in HEK293T cells and immunoblotting for the indicated proteins. Immunoblots are representative results of one iteration out of at least three independent experiments with the exception of VPS35L K940N and R766W mutants, which were tested only once.

Source data

Extended Data Fig. 4 VPS35L localization and PM proteome effects.

(a) Immunofluorescence staining for VPS35L (green channel, using HA antibody), FAM21 (red channel), and nuclei (DAPI, blue channel) in the indicated stable Huh-7 cell lines. Representative images of one out of two independent experiments are shown. (b) Immunofluorescence staining for VPS35L (green channel, using HA antibody), FAM21 (red channel), and nuclei (DAPI, blue channel) in the indicated HeLa knockout cell lines transfected with HA-VPS35L. Representative images of one experiment are shown. (c, d) Representative gating and acquisition parameters for Villin and CD14 staining by flow cytometry.

Extended Data Fig. 5 AlphaFold Multimer prediction of CCDC22-CCDC93 binding to Retriever.

(a & d) Overlay of all 25 AlphaFold Multimer models of Retriever alone (A) or CCDC22-CCDC93-Retriever (D) with the cryo-EM model of Retriever. AFM models of Retriever are grey. (b & e) Representative AFM models colored using pLDDT scores. High scores indicate high reliability in local structure prediction. (c & f) PAE score matrix of the AFM model shown in (B & E). Low scores (deep color) indicate high reliability in the relative position in the 3D space. Boundaries of protein sequences and important structure regions are indicated.

Extended Data Fig. 6 AlphaFold Multimer prediction of CCDC22-CCDC93 binding to DENND10.

(a) AlphaFold Multimer prediction of DENND10 binding to full-length (FL) CCDC22-CCDC93. (b) Representative AFM models colored using pLDDT scores. (c) PAE score matrix of the AFM model shown in (B). Boundaries of protein sequences and important structure regions are indicated. (d) Superimposition of the AFM model of DENND10 with the crystal structure of DENND1a (PDB: 6EKK). Rab35 binding surface of DENND1a and CCDC22-CCDC93 binding surface of DENN10 are colored to show the partial overlap of the two surfaces.

Extended Data Fig. 7 AlphaFold Multimer prediction of CCDC22-CCDC93 binding to COMMD.

(a–c) Overlays of AlphaFold Multimer models and schematic showing CCDC22-CCDC93 binding to COMMD decamer ring for proteins from Human (A), Zebrafish (B), and Amoeba (Dictyostelium) (C). (d–f) Representative AFM models colored using pLDDT scores. (g–i) PAE score matrices of the AFM models shown in (D-F). Boundaries of protein sequences and important structure regions are indicated.

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Unprocessed western blots.

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Unprocessed western blots.

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Numerical data.

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Numerical data.

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Unprocessed western blots and Coomassie blue gels.

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Unprocessed western blots and Coomassie blue gels.

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Chromatography data.

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Unprocessed western blots.

Source Data Extended Data Fig. 1

Unprocessed Coomassie blue gels.

Source Data Extended Data Fig. 1

Chromatography data.

Source Data Extended Data Fig. 3

Unprocessed western blots.

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Boesch, D.J., Singla, A., Han, Y. et al. Structural organization of the retriever–CCC endosomal recycling complex. Nat Struct Mol Biol (2023). https://doi.org/10.1038/s41594-023-01184-4

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