Double NPY motifs at the N-terminus of the yeast t-SNARE Sso2 synergistically bind Sec3 to promote membrane fusion

  1. Maximilian Peer
  2. Hua Yuan
  3. Yubo Zhang
  4. Katharina Korbula
  5. Peter Novick  Is a corresponding author
  6. Gang Dong  Is a corresponding author
  1. Medical University of Vienna, Austria
  2. University of California, San Diego, United States
  3. Medical Unviersity of Vienna, Austria

Abstract

Exocytosis is an active vesicle trafficking process by which eukaryotes secrete materials to the extracellular environment and insert membrane proteins into the plasma membrane. The final step of exocytosis in yeast involves the assembly of two t-SNAREs, Sso1/2 and Sec9, with the v-SNARE, Snc1/2, on secretory vesicles. The rate-limiting step in this process is the formation of a binary complex of the two t-SNAREs. Despite a previous report of acceleration of binary complex assembly by Sec3, it remains unknown how Sso2 is efficiently recruited to the vesicle-docking site marked by Sec3. Here we report a crystal structure of the pleckstrin homology (PH) domain of Sec3 in complex with a nearly full-length version of Sso2 lacking only its C-terminal transmembrane helix. The structure shows a previously uncharacterized binding site for Sec3 at the N-terminus of Sso2, consisting of two highly conserved triple residue motifs (NPY: Asn-Pro-Tyr). We further reveal that the two NPY motifs bind Sec3 synergistically, which together with the previously reported binding interface constitute dual-site interactions between Sso2 and Sec3 to drive the fusion of secretory vesicles at target sites on the plasma membrane.

Data availability

Diffraction data have been deposited in PDB under the accession code 7Q83.

Article and author information

Author details

  1. Maximilian Peer

    Vienna Biocenter, Medical University of Vienna, Vienna, Austria
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-5032-8029
  2. Hua Yuan

    Department of Cellular and Molecular Medicine, University of California, San Diego, La Jolla, United States
    Competing interests
    The authors declare that no competing interests exist.
  3. Yubo Zhang

    Vienna Biocenter, Medical University of Vienna, Vienna, Austria
    Competing interests
    The authors declare that no competing interests exist.
  4. Katharina Korbula

    Vienna Biocenter, Medical University of Vienna, Vienna, Austria
    Competing interests
    The authors declare that no competing interests exist.
  5. Peter Novick

    Department of Cellular and Molecular Medicine, University of California, San Diego, La Jolla, United States
    For correspondence
    pnovick@ucsd.edu
    Competing interests
    The authors declare that no competing interests exist.
  6. Gang Dong

    Medical Unviersity of Vienna, Vienna, Austria
    For correspondence
    gang.dong@meduniwien.ac.at
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-9745-8103

Funding

Austrian Science Fund (P28231-B28)

  • Gang Dong

Austrian Science Fund (I4960-B)

  • Gang Dong

National Institutes of Health (GM35370)

  • Peter Novick

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

Copyright

© 2022, Peer 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

  • 792
    views
  • 260
    downloads
  • 7
    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. Maximilian Peer
  2. Hua Yuan
  3. Yubo Zhang
  4. Katharina Korbula
  5. Peter Novick
  6. Gang Dong
(2022)
Double NPY motifs at the N-terminus of the yeast t-SNARE Sso2 synergistically bind Sec3 to promote membrane fusion
eLife 11:e82041.
https://doi.org/10.7554/eLife.82041

Share this article

https://doi.org/10.7554/eLife.82041

Further reading

    1. Structural Biology and Molecular Biophysics
    Bradley P Clarke, Alexia E Angelos ... Yi Ren
    Research Article

    In eukaryotes, RNAs transcribed by RNA Pol II are modified at the 5′ end with a 7-methylguanosine (m7G) cap, which is recognized by the nuclear cap binding complex (CBC). The CBC plays multiple important roles in mRNA metabolism, including transcription, splicing, polyadenylation, and export. It promotes mRNA export through direct interaction with a key mRNA export factor, ALYREF, which in turn links the TRanscription and EXport (TREX) complex to the 5′ end of mRNA. However, the molecular mechanism for CBC-mediated recruitment of the mRNA export machinery is not well understood. Here, we present the first structure of the CBC in complex with an mRNA export factor, ALYREF. The cryo-EM structure of CBC-ALYREF reveals that the RRM domain of ALYREF makes direct contact with both the NCBP1 and NCBP2 subunits of the CBC. Comparing CBC-ALYREF with other cellular complexes containing CBC and/or ALYREF components provides insights into the coordinated events during mRNA transcription, splicing, and export.

    1. Structural Biology and Molecular Biophysics
    Julia Belyaeva, Matthias Elgeti
    Review Article

    Under physiological conditions, proteins continuously undergo structural fluctuations on different timescales. Some conformations are only sparsely populated, but still play a key role in protein function. Thus, meaningful structure–function frameworks must include structural ensembles rather than only the most populated protein conformations. To detail protein plasticity, modern structural biology combines complementary experimental and computational approaches. In this review, we survey available computational approaches that integrate sparse experimental data from electron paramagnetic resonance spectroscopy with molecular modeling techniques to derive all-atom structural models of rare protein conformations. We also propose strategies to increase the reliability and improve efficiency using deep learning approaches, thus advancing the field of integrative structural biology.