IDEAS home Printed from https://ideas.repec.org/a/nat/natcom/v14y2023i1d10.1038_s41467-023-41906-2.html
   My bibliography  Save this article

Ecological network analysis reveals cancer-dependent chaperone-client interaction structure and robustness

Author

Listed:
  • Geut Galai

    (Ben-Gurion University of the Negev)

  • Xie He

    (Dartmouth College)

  • Barak Rotblat

    (Ben-Gurion University of the Negev
    The National Institute for Biotechnology in the Negev)

  • Shai Pilosof

    (Ben-Gurion University of the Negev)

Abstract

Cancer cells alter the expression levels of metabolic enzymes to fuel proliferation. The mitochondrion is a central hub of metabolic reprogramming, where chaperones service hundreds of clients, forming chaperone-client interaction networks. How network structure affects its robustness to chaperone targeting is key to developing cancer-specific drug therapy. However, few studies have assessed how structure and robustness vary across different cancer tissues. Here, using ecological network analysis, we reveal a non-random, hierarchical pattern whereby the cancer type modulates the chaperones’ ability to realize their potential client interactions. Despite the low similarity between the chaperone-client interaction networks, we highly accurately predict links in one cancer type based on another. Moreover, we identify groups of chaperones that interact with similar clients. Simulations of network robustness show that this group structure affects cancer-specific response to chaperone removal. Our results open the door for new hypotheses regarding the ecology and evolution of chaperone-client interaction networks and can inform cancer-specific drug development strategies.

Suggested Citation

  • Geut Galai & Xie He & Barak Rotblat & Shai Pilosof, 2023. "Ecological network analysis reveals cancer-dependent chaperone-client interaction structure and robustness," Nature Communications, Nature, vol. 14(1), pages 1-11, December.
  • Handle: RePEc:nat:natcom:v:14:y:2023:i:1:d:10.1038_s41467-023-41906-2
    DOI: 10.1038/s41467-023-41906-2
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/s41467-023-41906-2
    File Function: Abstract
    Download Restriction: no

    File URL: https://libkey.io/10.1038/s41467-023-41906-2?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Chun-Shik Shin & Shuxia Meng & Spiros D. Garbis & Annie Moradian & Robert W. Taylor & Michael J. Sweredoski & Brett Lomenick & David C. Chan, 2021. "LONP1 and mtHSP70 cooperate to promote mitochondrial protein folding," Nature Communications, Nature, vol. 12(1), pages 1-10, December.
    2. Giovanni Strona & Domenico Nappo & Francesco Boccacci & Simone Fattorini & Jesus San-Miguel-Ayanz, 2014. "A fast and unbiased procedure to randomize ecological binary matrices with fixed row and column totals," Nature Communications, Nature, vol. 5(1), pages 1-9, September.
    3. Chuliang Song & Serguei Saavedra, 2020. "Telling ecological networks apart by their structure: An environment-dependent approach," PLOS Computational Biology, Public Library of Science, vol. 16(4), pages 1-15, April.
    4. Shai Pilosof & Miguel A. Fortuna & Jean-François Cosson & Maxime Galan & Chaisiri Kittipong & Alexis Ribas & Eran Segal & Boris R. Krasnov & Serge Morand & Jordi Bascompte, 2014. "Host–parasite network structure is associated with community-level immunogenetic diversity," Nature Communications, Nature, vol. 5(1), pages 1-9, December.
    5. Edward B Baskerville & Andy P Dobson & Trevor Bedford & Stefano Allesina & T Michael Anderson & Mercedes Pascual, 2011. "Spatial Guilds in the Serengeti Food Web Revealed by a Bayesian Group Model," PLOS Computational Biology, Public Library of Science, vol. 7(12), pages 1-11, December.
    6. Phillip P. A. Staniczenko & Jason C. Kopp & Stefano Allesina, 2013. "The ghost of nestedness in ecological networks," Nature Communications, Nature, vol. 4(1), pages 1-6, June.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Matthew J Michalska-Smith & Stefano Allesina, 2019. "Telling ecological networks apart by their structure: A computational challenge," PLOS Computational Biology, Public Library of Science, vol. 15(6), pages 1-13, June.
    2. Michel Alexandre & Felipe Jordão Xavier & Thiago Christiano Silva & Francisco A. Rodrigues, 2022. "Nestedness in the Brazilian Financial System," Working Papers Series 566, Central Bank of Brazil, Research Department.
    3. Fabio Saracco & Riccardo Di Clemente & Andrea Gabrielli & Tiziano Squartini, 2015. "Detecting early signs of the 2007-2008 crisis in the world trade," Papers 1508.03533, arXiv.org, revised Jul 2016.
    4. Magdalena Meyer & Dominik W. Melville & Heather J. Baldwin & Kerstin Wilhelm & Evans Ewald Nkrumah & Ebenezer K. Badu & Samuel Kingsley Oppong & Nina Schwensow & Adam Stow & Peter Vallo & Victor M. Co, 2024. "Bat species assemblage predicts coronavirus prevalence," Nature Communications, Nature, vol. 15(1), pages 1-11, December.
    5. Rivest, Louis-Paul & Ebouele, Sergio Ewane, 2020. "Sampling a two dimensional matrix," Computational Statistics & Data Analysis, Elsevier, vol. 149(C).
    6. Mika J. Straka & Guido Caldarelli & Tiziano Squartini & Fabio Saracco, 2017. "From Ecology to Finance (and Back?): Recent Advancements in the Analysis of Bipartite Networks," Papers 1710.10143, arXiv.org.
    7. Jeroen van Lidth de Jeude & Riccardo Di Clemente & Guido Caldarelli & Fabio Saracco & Tiziano Squartini, 2019. "Reconstructing Mesoscale Network Structures," Complexity, Hindawi, vol. 2019, pages 1-13, January.
    8. Marco Bardoscia & Paolo Barucca & Stefano Battiston & Fabio Caccioli & Giulio Cimini & Diego Garlaschelli & Fabio Saracco & Tiziano Squartini & Guido Caldarelli, 2021. "The Physics of Financial Networks," Papers 2103.05623, arXiv.org.
    9. Pascale Baden & Maria Jose Perez & Hariam Raji & Federico Bertoli & Stefanie Kalb & María Illescas & Fokion Spanos & Claudio Giuliano & Alessandra Maria Calogero & Marvin Oldrati & Hannah Hebestreit &, 2023. "Glucocerebrosidase is imported into mitochondria and preserves complex I integrity and energy metabolism," Nature Communications, Nature, vol. 14(1), pages 1-21, December.
    10. Marjan Cugmas & Aleš Žiberna & Anuška Ferligoj, 2021. "The Relative Fit measure for evaluating a blockmodel," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 30(5), pages 1315-1335, December.
    11. Luiz G. A. Alves & Giuseppe Mangioni & Isabella Cingolani & Francisco A. Rodrigues & Pietro Panzarasa & Yamir Moreno, 2018. "The nested structural organization of the worldwide trade multi-layer network," Papers 1803.02872, arXiv.org, revised Sep 2019.
    12. Jonas Benjamin Michaelis & Melinda Elaine Brunstein & Süleyman Bozkurt & Ludovico Alves & Martin Wegner & Manuel Kaulich & Christian Pohl & Christian Münch, 2022. "Protein import motor complex reacts to mitochondrial misfolding by reducing protein import and activating mitophagy," Nature Communications, Nature, vol. 13(1), pages 1-12, December.
    13. Vincent Miele & Catherine Matias & Stéphane Robin & Stéphane Dray, 2019. "Nine quick tips for analyzing network data," PLOS Computational Biology, Public Library of Science, vol. 15(12), pages 1-10, December.
    14. Tad Dallas & Andrew W Park & John M Drake, 2017. "Predicting cryptic links in host-parasite networks," PLOS Computational Biology, Public Library of Science, vol. 13(5), pages 1-15, May.
    15. Stock, Michiel & Piot, Niels & Vanbesien, Sarah & Meys, Joris & Smagghe, Guy & De Baets, Bernard, 2021. "Pairwise learning for predicting pollination interactions based on traits and phylogeny," Ecological Modelling, Elsevier, vol. 451(C).
    16. Isaac Trindade-Santos & Faye Moyes & Anne E. Magurran, 2022. "Global patterns in functional rarity of marine fish," Nature Communications, Nature, vol. 13(1), pages 1-9, December.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:nat:natcom:v:14:y:2023:i:1:d:10.1038_s41467-023-41906-2. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.nature.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.