Genetic analysis reveals functions of atypical polyubiquitin chains

  1. Fernando Meza Gutierrez
  2. Deniz Simsek
  3. Arda Mizrak
  4. Adam Deutschbauer
  5. Hannes Braberg
  6. Jeffrey Johnson
  7. Jiewei Xu
  8. Michael Shales
  9. Michelle Nguyen
  10. Raquel Tamse-Kuehn
  11. Curt Palm
  12. Lars M Steinmetz
  13. Nevan J Krogan
  14. David P Toczyski  Is a corresponding author
  1. University of California, San Francisco, United States
  2. Amgen Research, United States
  3. Lawrence Berkeley National Laboratory, United States
  4. Stanford University, United States
  5. University of California San Francisco, United States

Abstract

Although polyubiquitin chains linked through all lysines of ubiquitin exist, specific functions are well-established only for lysine-48 and lysine-63 linkages in Saccharomyces cerevisiae. To uncover pathways regulated by distinct linkages, genetic interactions between a gene deletion library and a panel of lysine-to-arginine ubiquitin mutants were systematically identified. The K11R mutant had strong genetic interactions with threonine biosynthetic genes. Consistently, we found that K11R mutants import threonine poorly. The K11R mutant also exhibited a strong genetic interaction with a subunit of the anaphase-promoting complex (APC), suggesting a role in cell cycle regulation. K11-linkages are important for vertebrate APC function, but this was not previously described in yeast. We show that the yeast APC also modifies substrates with K11-linkages in vitro, and that those chains contribute to normal APC-substrate turnover in vivo. This study reveals comprehensive genetic interactomes of polyubiquitin chains and characterizes the role of K11-chains in two biological pathways.

Data availability

All datasets generated are included as Supplementary Files 4 (SGA dataset) and 5 (quantitative proteomics).

Article and author information

Author details

  1. Fernando Meza Gutierrez

    Department of Biochemistry and Biophysics, University of California, San Francisco, San Francisco, United States
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-5601-7202
  2. Deniz Simsek

    Amgen Research, South San Francisco, United States
    Competing interests
    Deniz Simsek, is affiliated with Amgen Research. The author has no other competing interests to declare..
  3. Arda Mizrak

    Department of Biochemistry and Biophysics, University of California, San Francisco, San Francisco, United States
    Competing interests
    No competing interests declared.
  4. Adam Deutschbauer

    Lawrence Berkeley National Laboratory, Berkeley, United States
    Competing interests
    No competing interests declared.
  5. Hannes Braberg

    Department of Cellular and Molecular Pharmacology, University of California, San Francisco, San Francisco, United States
    Competing interests
    No competing interests declared.
  6. Jeffrey Johnson

    Department of Cellular and Molecular Pharmacology, University of California, San Francisco, San Francisco, United States
    Competing interests
    No competing interests declared.
  7. Jiewei Xu

    Department of Cellular and Molecular Pharmacology, University of California, San Francisco, San Francisco, United States
    Competing interests
    No competing interests declared.
  8. Michael Shales

    Department of Cellular and Molecular Pharmacology, University of California, San Francisco, San Francisco, United States
    Competing interests
    No competing interests declared.
  9. Michelle Nguyen

    Stanford Genome Technology Center, Stanford University, Stanford, United States
    Competing interests
    No competing interests declared.
  10. Raquel Tamse-Kuehn

    Stanford Genome Technology Center, Stanford University, Stanford, United States
    Competing interests
    No competing interests declared.
  11. Curt Palm

    Stanford Genome Technology Center, Stanford University, Stanford, United States
    Competing interests
    No competing interests declared.
  12. Lars M Steinmetz

    Genetics, Stanford University, Stanford, United States
    Competing interests
    No competing interests declared.
  13. Nevan J Krogan

    Department of Cellular and Molecular Pharmacology, University of California San Francisco, San Francisco, United States
    Competing interests
    No competing interests declared.
  14. David P Toczyski

    Department of Biochemistry and Biophysics, University of California, San Francisco, San Francisco, United States
    For correspondence
    dpt4darwin@gmail.com
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-5924-0365

Funding

National Institutes of Health (R35 GM118104)

  • David P Toczyski

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

Copyright

© 2018, Meza Gutierrez 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

  • 2,072
    views
  • 275
    downloads
  • 12
    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. Fernando Meza Gutierrez
  2. Deniz Simsek
  3. Arda Mizrak
  4. Adam Deutschbauer
  5. Hannes Braberg
  6. Jeffrey Johnson
  7. Jiewei Xu
  8. Michael Shales
  9. Michelle Nguyen
  10. Raquel Tamse-Kuehn
  11. Curt Palm
  12. Lars M Steinmetz
  13. Nevan J Krogan
  14. David P Toczyski
(2018)
Genetic analysis reveals functions of atypical polyubiquitin chains
eLife 7:e42955.
https://doi.org/10.7554/eLife.42955

Share this article

https://doi.org/10.7554/eLife.42955

Further reading

    1. Biochemistry and Chemical Biology
    2. Microbiology and Infectious Disease
    Mai Nguyen, Elda Bauda ... Cecile Morlot
    Research Article

    Teichoic acids (TA) are linear phospho-saccharidic polymers and important constituents of the cell envelope of Gram-positive bacteria, either bound to the peptidoglycan as wall teichoic acids (WTA) or to the membrane as lipoteichoic acids (LTA). The composition of TA varies greatly but the presence of both WTA and LTA is highly conserved, hinting at an underlying fundamental function that is distinct from their specific roles in diverse organisms. We report the observation of a periplasmic space in Streptococcus pneumoniae by cryo-electron microscopy of vitreous sections. The thickness and appearance of this region change upon deletion of genes involved in the attachment of TA, supporting their role in the maintenance of a periplasmic space in Gram-positive bacteria as a possible universal function. Consequences of these mutations were further examined by super-resolved microscopy, following metabolic labeling and fluorophore coupling by click chemistry. This novel labeling method also enabled in-gel analysis of cell fractions. With this approach, we were able to titrate the actual amount of TA per cell and to determine the ratio of WTA to LTA. In addition, we followed the change of TA length during growth phases, and discovered that a mutant devoid of LTA accumulates the membrane-bound polymerized TA precursor.

    1. Biochemistry and Chemical Biology
    2. Computational and Systems Biology
    Shinichi Kawaguchi, Xin Xu ... Toshie Kai
    Research Article

    Protein–protein interactions are fundamental to understanding the molecular functions and regulation of proteins. Despite the availability of extensive databases, many interactions remain uncharacterized due to the labor-intensive nature of experimental validation. In this study, we utilized the AlphaFold2 program to predict interactions among proteins localized in the nuage, a germline-specific non-membrane organelle essential for piRNA biogenesis in Drosophila. We screened 20 nuage proteins for 1:1 interactions and predicted dimer structures. Among these, five represented novel interaction candidates. Three pairs, including Spn-E_Squ, were verified by co-immunoprecipitation. Disruption of the salt bridges at the Spn-E_Squ interface confirmed their functional importance, underscoring the predictive model’s accuracy. We extended our analysis to include interactions between three representative nuage components—Vas, Squ, and Tej—and approximately 430 oogenesis-related proteins. Co-immunoprecipitation verified interactions for three pairs: Mei-W68_Squ, CSN3_Squ, and Pka-C1_Tej. Furthermore, we screened the majority of Drosophila proteins (~12,000) for potential interaction with the Piwi protein, a central player in the piRNA pathway, identifying 164 pairs as potential binding partners. This in silico approach not only efficiently identifies potential interaction partners but also significantly bridges the gap by facilitating the integration of bioinformatics and experimental biology.