A signal capture and proofreading mechanism for the KDEL-receptor explains selectivity and dynamic range in ER retrieval

Abstract

ER proteins of widely differing abundance are retrieved from the Golgi by the KDEL-receptor. Abundant ER proteins tend to have KDEL rather than HDEL signals, whereas ADEL and DDEL are not used in most organisms. Here, we explore the mechanism of selective retrieval signal capture by the KDEL-receptor and how HDEL binds with ten-fold higher affinity than KDEL. Our results show the carboxyl-terminus of the retrieval signal moves along a ladder of arginine residues as it enters the binding pocket of the receptor. Gatekeeper residues D50 and E117 at the entrance of this pocket exclude ADEL and DDEL sequences. D50N/E117Q mutation of human KDEL-receptors changes the selectivity to ADEL and DDEL. However, further analysis of HDEL, KDEL and RDEL-bound receptor structures shows that affinity differences are explained by interactions between the variable -4 H/K/R position of the signal and W120, rather than D50 or E117. Together, these findings explain KDEL-receptor selectivity, and how signal variants increase dynamic range to support efficient ER retrieval of low and high abundance proteins.

Data availability

Atomic coordinates for the models have been deposited in the Protein Data Bank (PDB) under accession codes 6Y7V and 6ZXR.Data generated or analysed during this study are included in the manuscript and supporting files. Source data files have been provided for Figures 1, 1Sup1, 1Sup2, 2, 3, 3Sup1, 4, 4Sup1, 6, 6Sup1, 6Sup2, 7, and 7Sup1.

The following previously published data sets were used

Article and author information

Author details

  1. Andreas Gerondopoulos

    Department of Biochemistry, University of Oxford, Oxford, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
  2. Philipp Bräuer

    Department of Biochemistry, University of Oxford, Oxford, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-4127-2638
  3. Tomoaki Sobajima

    Department of Biochemistry, University of Oxford, Oxford, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-0753-5361
  4. Zhiyi Wu

    Department of Biochemistry, University of Oxford, Oxford, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-7615-7851
  5. Joanne L Parker

    Department of Biochemistry, University of Oxford, Oxford, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
  6. Philip Biggin

    Biochemistry, University of Oxford, Oxford, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-5100-8836
  7. Francis A Barr Ph.D.

    Department of Biochemistry, University of Oxford, Oxford, United Kingdom
    For correspondence
    francis.barr@bioch.ox.ac.uk
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-7518-253X
  8. Simon Newstead

    Department of Biochemistry, University of Oxford, Oxford, United Kingdom
    For correspondence
    simon.newstead@bioch.ox.ac.uk
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-7432-2270

Funding

Wellcome Trust (219531/Z/19/Z,203741/Z/16/A and 109133/Z/15/A)

  • Zhiyi Wu

Engineering and Physical Sciences Research Council (EP/R029407/1)

  • Andreas Gerondopoulos
  • Philipp Bräuer
  • Tomoaki Sobajima

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Copyright

© 2021, Gerondopoulos et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

Metrics

  • 4,649
    views
  • 559
    downloads
  • 19
    citations

Views, downloads and citations are aggregated across all versions of this paper published by eLife.

Download links

A two-part list of links to download the article, or parts of the article, in various formats.

Downloads (link to download the article as PDF)

Open citations (links to open the citations from this article in various online reference manager services)

Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)

  1. Andreas Gerondopoulos
  2. Philipp Bräuer
  3. Tomoaki Sobajima
  4. Zhiyi Wu
  5. Joanne L Parker
  6. Philip Biggin
  7. Francis A Barr Ph.D.
  8. Simon Newstead
(2021)
A signal capture and proofreading mechanism for the KDEL-receptor explains selectivity and dynamic range in ER retrieval
eLife 10:e68380.
https://doi.org/10.7554/eLife.68380

Share this article

https://doi.org/10.7554/eLife.68380

Further reading

    1. Cell Biology
    2. Genetics and Genomics
    Keva Li, Nicholas Tolman ... UK Biobank Eye and Vision Consortium
    Research Article

    A glaucoma polygenic risk score (PRS) can effectively identify disease risk, but some individuals with high PRS do not develop glaucoma. Factors contributing to this resilience remain unclear. Using 4,658 glaucoma cases and 113,040 controls in a cross-sectional study of the UK Biobank, we investigated whether plasma metabolites enhanced glaucoma prediction and if a metabolomic signature of resilience in high-genetic-risk individuals existed. Logistic regression models incorporating 168 NMR-based metabolites into PRS-based glaucoma assessments were developed, with multiple comparison corrections applied. While metabolites weakly predicted glaucoma (Area Under the Curve = 0.579), they offered marginal prediction improvement in PRS-only-based models (p=0.004). We identified a metabolomic signature associated with resilience in the top glaucoma PRS decile, with elevated glycolysis-related metabolites—lactate (p=8.8E-12), pyruvate (p=1.9E-10), and citrate (p=0.02)—linked to reduced glaucoma prevalence. These metabolites combined significantly modified the PRS-glaucoma relationship (Pinteraction = 0.011). Higher total resilience metabolite levels within the highest PRS quartile corresponded to lower glaucoma prevalence (Odds Ratiohighest vs. lowest total resilience metabolite quartile=0.71, 95% Confidence Interval = 0.64–0.80). As pyruvate is a foundational metabolite linking glycolysis to tricarboxylic acid cycle metabolism and ATP generation, we pursued experimental validation for this putative resilience biomarker in a human-relevant Mus musculus glaucoma model. Dietary pyruvate mitigated elevated intraocular pressure (p=0.002) and optic nerve damage (p<0.0003) in Lmx1bV265D mice. These findings highlight the protective role of pyruvate-related metabolism against glaucoma and suggest potential avenues for therapeutic intervention.

    1. Cell Biology
    Affiong Ika Oqua, Kin Chao ... Alejandra Tomas
    Research Article

    G protein-coupled receptors (GPCRs) are integral membrane proteins which closely interact with their plasma membrane lipid microenvironment. Cholesterol is a lipid enriched at the plasma membrane with pivotal roles in the control of membrane fluidity and maintenance of membrane microarchitecture, directly impacting on GPCR stability, dynamics, and function. Cholesterol extraction from pancreatic beta cells has previously been shown to disrupt the internalisation, clustering, and cAMP responses of the glucagon-like peptide-1 receptor (GLP-1R), a class B1 GPCR with key roles in the control of blood glucose levels via the potentiation of insulin secretion in beta cells and weight reduction via the modulation of brain appetite control centres. Here, we unveil the detrimental effect of a high cholesterol diet on GLP-1R-dependent glucoregulation in vivo, and the improvement in GLP-1R function that a reduction in cholesterol synthesis using simvastatin exerts in pancreatic islets. We next identify and map sites of cholesterol high occupancy and residence time on active vs inactive GLP-1Rs using coarse-grained molecular dynamics (cgMD) simulations, followed by a screen of key residues selected from these sites and detailed analyses of the effects of mutating one of these, Val229, to alanine on GLP-1R-cholesterol interactions, plasma membrane behaviours, clustering, trafficking and signalling in INS-1 832/3 rat pancreatic beta cells and primary mouse islets, unveiling an improved insulin secretion profile for the V229A mutant receptor. This study (1) highlights the role of cholesterol in regulating GLP-1R responses in vivo; (2) provides a detailed map of GLP-1R - cholesterol binding sites in model membranes; (3) validates their functional relevance in beta cells; and (4) highlights their potential as locations for the rational design of novel allosteric modulators with the capacity to fine-tune GLP-1R responses.