Evolution of an intricate J-protein network driving protein disaggregation in eukaryotes

  1. Nadinath B Nillegoda  Is a corresponding author
  2. Antonia Stank
  3. Duccio Malinverni
  4. Niels Alberts
  5. Anna Szlachcic
  6. Alessandro Barducci
  7. Paolo De Los Rios
  8. Rebecca C Wade  Is a corresponding author
  9. Bernd Bukau  Is a corresponding author
  1. University of Heidelberg, Germany
  2. Heidelberg Institute for Theoretical Studies, Germany
  3. École Polytechnique Fédérale de Lausanne, Switzerland
  4. Inserm, U1054, France
  5. University of Heidelberg, United Kingdom

Abstract

Hsp70 participates in a broad spectrum of protein folding processes extending from nascent chain folding to protein disaggregation. This versatility in function is achieved through a diverse family of J-protein cochaperones that select substrates for Hsp70. Substrate selection is further tuned by transient complexation between different classes of J-proteins, which expands the range of protein aggregates targeted by metazoan Hsp70 for disaggregation. We assessed the prevalence and evolutionary conservation of J-protein complexation and cooperation in disaggregation. We find the emergence of a eukaryote-specific signature for interclass complexation of canonical J-proteins. Consistently, complexes exist in yeast and human cells, but not in bacteria, and correlate with cooperative action in disaggregation in vitro. Signature alterations exclude some J-proteins from networking, which ensures correct J-protein pairing, functional network integrity and J-protein specialization. This fundamental change in J-protein biology during the prokaryote-to-eukaryote transition allows for increased fine-tuning and broadening of Hsp70 function in eukaryotes.

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Author details

  1. Nadinath B Nillegoda

    Center for Molecular Biology, University of Heidelberg, Heidelberg, Germany
    For correspondence
    n.nillegoda@zmbh.uni-heidelberg.de
    Competing interests
    The authors declare that no competing interests exist.
  2. Antonia Stank

    Heidelberg Institute for Theoretical Studies, Heidelberg, Germany
    Competing interests
    The authors declare that no competing interests exist.
  3. Duccio Malinverni

    Laboratory of Statistical Biophysics, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
    Competing interests
    The authors declare that no competing interests exist.
  4. Niels Alberts

    Center for Molecular Biology, University of Heidelberg, Heidelberg, Germany
    Competing interests
    The authors declare that no competing interests exist.
  5. Anna Szlachcic

    Center for Molecular Biology, University of Heidelberg, Heidelberg, Germany
    Competing interests
    The authors declare that no competing interests exist.
  6. Alessandro Barducci

    Inserm, U1054, Montpellier, France
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-1911-8039
  7. Paolo De Los Rios

    Laboratory of Statistical Biophysics, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
    Competing interests
    The authors declare that no competing interests exist.
  8. Rebecca C Wade

    Center for Molecular Biology, University of Heidelberg, Heidelberg, Germany
    For correspondence
    rebecca.wade@h-its.org
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-5951-8670
  9. Bernd Bukau

    Center for Molecular Biology, University of Heidelberg, Heidelberg, United Kingdom
    For correspondence
    bukau@zmbh.uni-heidelberg.de
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-0521-7199

Funding

Deutsche Forschungsgemeinschaft (SFB1036 BU617/19-3)

  • Bernd Bukau

Alexander von Humboldt-Stiftung (NA)

  • Nadinath B Nillegoda

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

Reviewing Editor

  1. Jeffery W Kelly, The Scripps Research Institute, United States

Publication history

  1. Received: December 22, 2016
  2. Accepted: May 12, 2017
  3. Accepted Manuscript published: May 15, 2017 (version 1)
  4. Accepted Manuscript updated: May 23, 2017 (version 2)
  5. Version of Record published: August 3, 2017 (version 3)
  6. Version of Record updated: August 8, 2017 (version 4)

Copyright

© 2017, Nillegoda 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.

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  1. Nadinath B Nillegoda
  2. Antonia Stank
  3. Duccio Malinverni
  4. Niels Alberts
  5. Anna Szlachcic
  6. Alessandro Barducci
  7. Paolo De Los Rios
  8. Rebecca C Wade
  9. Bernd Bukau
(2017)
Evolution of an intricate J-protein network driving protein disaggregation in eukaryotes
eLife 6:e24560.
https://doi.org/10.7554/eLife.24560

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    Background:

    Few studies have assessed the role of individual plasma cholesterol levels in the association between egg consumption and the risk of cardiovascular diseases. This research aims to simultaneously explore the associations of self-reported egg consumption with plasma metabolic markers and these markers with the risk of cardiovascular disease (CVD).

    Methods:

    Totally 4778 participants (3401 CVD cases subdivided into subtypes and 1377 controls) aged 30–79 were selected based on the China Kadoorie Biobank. Targeted nuclear magnetic resonance was used to quantify 225 metabolites in baseline plasma samples. Linear regression was conducted to assess associations between self-reported egg consumption and metabolic markers, which were further compared with associations between metabolic markers and CVD risk.

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    Egg consumption was associated with 24 out of 225 markers, including positive associations for apolipoprotein A1, acetate, mean HDL diameter, and lipid profiles of very large and large HDL, and inverse associations for total cholesterol and cholesterol esters in small VLDL. Among these 24 markers, 14 were associated with CVD risk. In general, the associations of egg consumption with metabolic markers and of these markers with CVD risk showed opposite patterns.

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    In the Chinese population, egg consumption is associated with several metabolic markers, which may partially explain the protective effect of moderate egg consumption on CVD.

    Funding:

    This work was supported by the National Natural Science Foundation of China (81973125, 81941018, 91846303, 91843302). The CKB baseline survey and the first re-survey were supported by a grant from the Kadoorie Charitable Foundation in Hong Kong. The long-term follow-up is supported by grants (2016YFC0900500, 2016YFC0900501, 2016YFC0900504, 2016YFC1303904) from the National Key R&D Program of China, National Natural Science Foundation of China (81390540, 81390541, 81390544), and Chinese Ministry of Science and Technology (2011BAI09B01). The funders had no role in the study design, data collection, data analysis and interpretation, writing of the report, or the decision to submit the article for publication.