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A reference map of the human binary protein interactome

Author

Listed:
  • Katja Luck

    (Dana-Farber Cancer Institute
    Harvard Medical School
    Dana-Farber Cancer Institute)

  • Dae-Kyum Kim

    (Dana-Farber Cancer Institute
    University of Toronto
    University of Toronto
    Sinai Health System)

  • Luke Lambourne

    (Dana-Farber Cancer Institute
    Harvard Medical School
    Dana-Farber Cancer Institute)

  • Kerstin Spirohn

    (Dana-Farber Cancer Institute
    Harvard Medical School
    Dana-Farber Cancer Institute)

  • Bridget E. Begg

    (Dana-Farber Cancer Institute
    Harvard Medical School
    Dana-Farber Cancer Institute)

  • Wenting Bian

    (Dana-Farber Cancer Institute
    Harvard Medical School
    Dana-Farber Cancer Institute)

  • Ruth Brignall

    (Dana-Farber Cancer Institute
    Harvard Medical School
    Dana-Farber Cancer Institute)

  • Tiziana Cafarelli

    (Dana-Farber Cancer Institute
    Harvard Medical School
    Dana-Farber Cancer Institute)

  • Francisco J. Campos-Laborie

    (Consejo Superior de Investigaciones Científicas (CSIC) and University of Salamanca (USAL)
    Institute for Biomedical Research of Salamanca (IBSAL))

  • Benoit Charloteaux

    (Dana-Farber Cancer Institute
    Harvard Medical School
    Dana-Farber Cancer Institute)

  • Dongsic Choi

    (The Research Institute of the McGill University Health Centre (RI-MUHC))

  • Atina G. Coté

    (Dana-Farber Cancer Institute
    University of Toronto
    University of Toronto
    Sinai Health System)

  • Meaghan Daley

    (Dana-Farber Cancer Institute
    Harvard Medical School
    Dana-Farber Cancer Institute)

  • Steven Deimling

    (University of Toronto)

  • Alice Desbuleux

    (Dana-Farber Cancer Institute
    Harvard Medical School
    Dana-Farber Cancer Institute
    Groupe Interdisciplinaire de Génomique Appliquée (GIGA) and Laboratory of Viral Interactomes, University of Liège)

  • Amélie Dricot

    (Dana-Farber Cancer Institute
    Harvard Medical School
    Dana-Farber Cancer Institute)

  • Marinella Gebbia

    (Dana-Farber Cancer Institute
    University of Toronto
    University of Toronto
    Sinai Health System)

  • Madeleine F. Hardy

    (Dana-Farber Cancer Institute
    Harvard Medical School
    Dana-Farber Cancer Institute)

  • Nishka Kishore

    (Dana-Farber Cancer Institute
    University of Toronto
    University of Toronto
    Sinai Health System)

  • Jennifer J. Knapp

    (Dana-Farber Cancer Institute
    University of Toronto
    University of Toronto
    Sinai Health System)

  • István A. Kovács

    (Dana-Farber Cancer Institute
    Northeastern University
    Institute for Solid State Physics and Optics)

  • Irma Lemmens

    (Vlaams Instituut voor Biotechnologie (VIB)
    Ghent University)

  • Miles W. Mee

    (University of Toronto
    University of Toronto
    University of Toronto)

  • Joseph C. Mellor

    (Dana-Farber Cancer Institute
    University of Toronto
    University of Toronto
    Sinai Health System)

  • Carl Pollis

    (Dana-Farber Cancer Institute
    Harvard Medical School
    Dana-Farber Cancer Institute)

  • Carles Pons

    (Institute for Research in Biomedicine (IRB Barcelona), The Barcelona Institute for Science and Technology)

  • Aaron D. Richardson

    (Dana-Farber Cancer Institute
    Harvard Medical School
    Dana-Farber Cancer Institute)

  • Sadie Schlabach

    (Dana-Farber Cancer Institute
    Harvard Medical School
    Dana-Farber Cancer Institute)

  • Bridget Teeking

    (Dana-Farber Cancer Institute
    Harvard Medical School
    Dana-Farber Cancer Institute)

  • Anupama Yadav

    (Dana-Farber Cancer Institute
    Harvard Medical School
    Dana-Farber Cancer Institute)

  • Mariana Babor

    (Dana-Farber Cancer Institute
    University of Toronto
    University of Toronto
    Sinai Health System)

  • Dawit Balcha

    (Dana-Farber Cancer Institute
    Harvard Medical School
    Dana-Farber Cancer Institute)

  • Omer Basha

    (Ben-Gurion University of the Negev
    Ben-Gurion University of the Negev)

  • Christian Bowman-Colin

    (Harvard Medical School
    Dana-Farber Cancer Institute)

  • Suet-Feung Chin

    (University of Cambridge)

  • Soon Gang Choi

    (Dana-Farber Cancer Institute
    Harvard Medical School
    Dana-Farber Cancer Institute)

  • Claudia Colabella

    (University of Perugia
    Istituto Zooprofilattico Sperimentale dell’Umbria e delle Marche “Togo Rosati” (IZSUM))

  • Georges Coppin

    (Dana-Farber Cancer Institute
    Harvard Medical School
    Dana-Farber Cancer Institute
    Groupe Interdisciplinaire de Génomique Appliquée (GIGA) and Laboratory of Viral Interactomes, University of Liège)

  • Cassandra D’Amata

    (University of Toronto)

  • David Ridder

    (Dana-Farber Cancer Institute
    Harvard Medical School
    Dana-Farber Cancer Institute)

  • Steffi Rouck

    (Vlaams Instituut voor Biotechnologie (VIB)
    Ghent University)

  • Miquel Duran-Frigola

    (Institute for Research in Biomedicine (IRB Barcelona), The Barcelona Institute for Science and Technology)

  • Hanane Ennajdaoui

    (Dana-Farber Cancer Institute
    University of Toronto
    University of Toronto
    Sinai Health System)

  • Florian Goebels

    (University of Toronto
    University of Toronto
    University of Toronto)

  • Liana Goehring

    (Harvard Medical School
    Dana-Farber Cancer Institute)

  • Anjali Gopal

    (Dana-Farber Cancer Institute
    University of Toronto
    University of Toronto
    Sinai Health System)

  • Ghazal Haddad

    (Dana-Farber Cancer Institute
    University of Toronto
    University of Toronto
    Sinai Health System)

  • Elodie Hatchi

    (Harvard Medical School
    Dana-Farber Cancer Institute)

  • Mohamed Helmy

    (University of Toronto
    University of Toronto
    University of Toronto)

  • Yves Jacob

    (Département de Virologie, Unité de Génétique Moléculaire des Virus à ARN (GMVR), Institut Pasteur, UMR3569, Centre National de la Recherche Scientifique (CNRS)
    Université Paris Diderot)

  • Yoseph Kassa

    (Dana-Farber Cancer Institute
    Harvard Medical School
    Dana-Farber Cancer Institute)

  • Serena Landini

    (Harvard Medical School
    Dana-Farber Cancer Institute)

  • Roujia Li

    (Dana-Farber Cancer Institute
    University of Toronto
    University of Toronto
    Sinai Health System)

  • Natascha Lieshout

    (Dana-Farber Cancer Institute
    University of Toronto
    University of Toronto
    Sinai Health System)

  • Andrew MacWilliams

    (Dana-Farber Cancer Institute
    Harvard Medical School
    Dana-Farber Cancer Institute)

  • Dylan Markey

    (Dana-Farber Cancer Institute
    Harvard Medical School
    Dana-Farber Cancer Institute)

  • Joseph N. Paulson

    (Dana-Farber Cancer Institute
    Harvard School of Public Health
    Genentech Inc.)

  • Sudharshan Rangarajan

    (Dana-Farber Cancer Institute
    Harvard Medical School
    Dana-Farber Cancer Institute)

  • John Rasla

    (Dana-Farber Cancer Institute
    Harvard Medical School
    Dana-Farber Cancer Institute)

  • Ashyad Rayhan

    (Dana-Farber Cancer Institute
    University of Toronto
    University of Toronto
    Sinai Health System)

  • Thomas Rolland

    (Dana-Farber Cancer Institute
    Harvard Medical School
    Dana-Farber Cancer Institute)

  • Adriana San-Miguel

    (Dana-Farber Cancer Institute
    Harvard Medical School
    Dana-Farber Cancer Institute)

  • Yun Shen

    (Dana-Farber Cancer Institute
    Harvard Medical School
    Dana-Farber Cancer Institute)

  • Dayag Sheykhkarimli

    (Dana-Farber Cancer Institute
    University of Toronto
    University of Toronto
    Sinai Health System)

  • Gloria M. Sheynkman

    (Dana-Farber Cancer Institute
    Harvard Medical School
    Dana-Farber Cancer Institute)

  • Eyal Simonovsky

    (Ben-Gurion University of the Negev
    Ben-Gurion University of the Negev)

  • Murat Taşan

    (Dana-Farber Cancer Institute
    University of Toronto
    University of Toronto
    Sinai Health System)

  • Alexander Tejeda

    (Dana-Farber Cancer Institute
    Harvard Medical School
    Dana-Farber Cancer Institute)

  • Vincent Tropepe

    (University of Toronto)

  • Jean-Claude Twizere

    (Groupe Interdisciplinaire de Génomique Appliquée (GIGA) and Laboratory of Viral Interactomes, University of Liège)

  • Yang Wang

    (Dana-Farber Cancer Institute
    Harvard Medical School
    Dana-Farber Cancer Institute)

  • Robert J. Weatheritt

    (University of Toronto)

  • Jochen Weile

    (Dana-Farber Cancer Institute
    University of Toronto
    University of Toronto
    Sinai Health System)

  • Yu Xia

    (Dana-Farber Cancer Institute
    McGill University)

  • Xinping Yang

    (Dana-Farber Cancer Institute
    Harvard Medical School
    Dana-Farber Cancer Institute)

  • Esti Yeger-Lotem

    (Ben-Gurion University of the Negev
    Ben-Gurion University of the Negev)

  • Quan Zhong

    (Dana-Farber Cancer Institute
    Harvard Medical School
    Dana-Farber Cancer Institute
    Wright State University)

  • Patrick Aloy

    (Institute for Research in Biomedicine (IRB Barcelona), The Barcelona Institute for Science and Technology
    Institució Catalana de Recerca i Estudis Avançats (ICREA))

  • Gary D. Bader

    (University of Toronto
    University of Toronto
    University of Toronto)

  • Javier Las Rivas

    (Consejo Superior de Investigaciones Científicas (CSIC) and University of Salamanca (USAL)
    Institute for Biomedical Research of Salamanca (IBSAL))

  • Suzanne Gaudet

    (Dana-Farber Cancer Institute
    Harvard Medical School
    Dana-Farber Cancer Institute)

  • Tong Hao

    (Dana-Farber Cancer Institute
    Harvard Medical School
    Dana-Farber Cancer Institute)

  • Janusz Rak

    (The Research Institute of the McGill University Health Centre (RI-MUHC))

  • Jan Tavernier

    (Vlaams Instituut voor Biotechnologie (VIB)
    Ghent University)

  • David E. Hill

    (Dana-Farber Cancer Institute
    Harvard Medical School
    Dana-Farber Cancer Institute)

  • Marc Vidal

    (Dana-Farber Cancer Institute
    Harvard Medical School)

  • Frederick P. Roth

    (Dana-Farber Cancer Institute
    University of Toronto
    University of Toronto
    Sinai Health System)

  • Michael A. Calderwood

    (Dana-Farber Cancer Institute
    Harvard Medical School
    Dana-Farber Cancer Institute)

Abstract

Global insights into cellular organization and genome function require comprehensive understanding of the interactome networks that mediate genotype–phenotype relationships1,2. Here we present a human ‘all-by-all’ reference interactome map of human binary protein interactions, or ‘HuRI’. With approximately 53,000 protein–protein interactions, HuRI has approximately four times as many such interactions as there are high-quality curated interactions from small-scale studies. The integration of HuRI with genome3, transcriptome4 and proteome5 data enables cellular function to be studied within most physiological or pathological cellular contexts. We demonstrate the utility of HuRI in identifying the specific subcellular roles of protein–protein interactions. Inferred tissue-specific networks reveal general principles for the formation of cellular context-specific functions and elucidate potential molecular mechanisms that might underlie tissue-specific phenotypes of Mendelian diseases. HuRI is a systematic proteome-wide reference that links genomic variation to phenotypic outcomes.

Suggested Citation

  • Katja Luck & Dae-Kyum Kim & Luke Lambourne & Kerstin Spirohn & Bridget E. Begg & Wenting Bian & Ruth Brignall & Tiziana Cafarelli & Francisco J. Campos-Laborie & Benoit Charloteaux & Dongsic Choi & At, 2020. "A reference map of the human binary protein interactome," Nature, Nature, vol. 580(7803), pages 402-408, April.
  • Handle: RePEc:nat:nature:v:580:y:2020:i:7803:d:10.1038_s41586-020-2188-x
    DOI: 10.1038/s41586-020-2188-x
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    Cited by:

    1. Pisanu Buphamalai & Tomislav Kokotovic & Vanja Nagy & Jörg Menche, 2021. "Network analysis reveals rare disease signatures across multiple levels of biological organization," Nature Communications, Nature, vol. 12(1), pages 1-15, December.
    2. Xu-Wen Wang & Lorenzo Madeddu & Kerstin Spirohn & Leonardo Martini & Adriano Fazzone & Luca Becchetti & Thomas P. Wytock & István A. Kovács & Olivér M. Balogh & Bettina Benczik & Mátyás Pétervári & Be, 2023. "Assessment of community efforts to advance network-based prediction of protein–protein interactions," Nature Communications, Nature, vol. 14(1), pages 1-14, December.
    3. Bingjie Hao & István A. Kovács, 2023. "A positive statistical benchmark to assess network agreement," Nature Communications, Nature, vol. 14(1), pages 1-11, December.
    4. Gergo Gogl & Boglarka Zambo & Camille Kostmann & Alexandra Cousido-Siah & Bastien Morlet & Fabien Durbesson & Luc Negroni & Pascal Eberling & Pau Jané & Yves Nominé & Andras Zeke & Søren Østergaard & , 2022. "Quantitative fragmentomics allow affinity mapping of interactomes," Nature Communications, Nature, vol. 13(1), pages 1-18, December.
    5. Yesheng Fu & Lei Li & Xin Zhang & Zhikang Deng & Ying Wu & Wenzhe Chen & Yuchen Liu & Shan He & Jian Wang & Yuping Xie & Zhiwei Tu & Yadi Lyu & Yange Wei & Shujie Wang & Chun-Ping Cui & Cui Hua Liu & , 2024. "Systematic HOIP interactome profiling reveals critical roles of linear ubiquitination in tissue homeostasis," Nature Communications, Nature, vol. 15(1), pages 1-19, December.
    6. Michael A. Skinnider & Mopelola O. Akinlaja & Leonard J. Foster, 2023. "Mapping protein states and interactions across the tree of life with co-fractionation mass spectrometry," Nature Communications, Nature, vol. 14(1), pages 1-11, December.
    7. Shilin Sun & Hua Tian & Runze Wang & Zehua Zhang, 2023. "Biomedical Interaction Prediction with Adaptive Line Graph Contrastive Learning," Mathematics, MDPI, vol. 11(3), pages 1-14, February.
    8. Patrick Bryant & Gabriele Pozzati & Arne Elofsson, 2022. "Improved prediction of protein-protein interactions using AlphaFold2," Nature Communications, Nature, vol. 13(1), pages 1-11, December.
    9. Nilesh Kumar & M. Shahid Mukhtar, 2024. "Viral Targets in the Human Interactome with Comprehensive Centrality Analysis: SARS-CoV-2, a Case Study," Data, MDPI, vol. 9(8), pages 1-12, August.
    10. Hong-Wen Tang & Kerstin Spirohn & Yanhui Hu & Tong Hao & István A. Kovács & Yue Gao & Richard Binari & Donghui Yang-Zhou & Kenneth H. Wan & Joel S. Bader & Dawit Balcha & Wenting Bian & Benjamin W. Bo, 2023. "Next-generation large-scale binary protein interaction network for Drosophila melanogaster," Nature Communications, Nature, vol. 14(1), pages 1-16, December.
    11. Adrià Fernández-Torras & Miquel Duran-Frigola & Martino Bertoni & Martina Locatelli & Patrick Aloy, 2022. "Integrating and formatting biomedical data as pre-calculated knowledge graph embeddings in the Bioteque," Nature Communications, Nature, vol. 13(1), pages 1-18, December.
    12. Yuan Liu & Jingwen Yang & Tianlu Wang & Mei Luo & Yamei Chen & Chengxuan Chen & Ze’ev Ronai & Yubin Zhou & Eytan Ruppin & Leng Han, 2023. "Expanding PROTACtable genome universe of E3 ligases," Nature Communications, Nature, vol. 14(1), pages 1-17, December.
    13. Ghulam Muhiuddin & Sovan Samanta & Abdulrahman F. Aljohani & Abeer M. Alkhaibari, 2023. "A Study on Graph Centrality Measures of Different Diseases Due to DNA Sequencing," Mathematics, MDPI, vol. 11(14), pages 1-18, July.
    14. Diego Esposito & Jane Dudley-Fraser & Acely Garza-Garcia & Katrin Rittinger, 2022. "Divergent self-association properties of paralogous proteins TRIM2 and TRIM3 regulate their E3 ligase activity," Nature Communications, Nature, vol. 13(1), pages 1-14, December.
    15. Patrick Bryant & Gabriele Pozzati & Wensi Zhu & Aditi Shenoy & Petras Kundrotas & Arne Elofsson, 2022. "Predicting the structure of large protein complexes using AlphaFold and Monte Carlo tree search," Nature Communications, Nature, vol. 13(1), pages 1-14, December.
    16. Jens S. Andersen & Aaran Vijayakumaran & Christopher Godbehere & Esben Lorentzen & Vito Mennella & Kenneth Bødtker Schou, 2024. "Uncovering structural themes across cilia microtubule inner proteins with implications for human cilia function," Nature Communications, Nature, vol. 15(1), pages 1-17, December.
    17. Siyuan Sun & Zhenxiang Zheng & Jun Wang & Fengming Li & An He & Kunjia Lai & Shuang Zhang & Jia-Hong Lu & Ruijun Tian & Chris Soon Heng Tan, 2023. "Improved in situ characterization of protein complex dynamics at scale with thermal proximity co-aggregation," Nature Communications, Nature, vol. 14(1), pages 1-15, December.
    18. Maik Müller & Fabienne Gräbnitz & Niculò Barandun & Yang Shen & Fabian Wendt & Sebastian N. Steiner & Yannik Severin & Stefan U. Vetterli & Milon Mondal & James R. Prudent & Raphael Hofmann & Marc Oos, 2021. "Light-mediated discovery of surfaceome nanoscale organization and intercellular receptor interaction networks," Nature Communications, Nature, vol. 12(1), pages 1-17, December.
    19. Jing Lei & Reiko U. Yoshimoto & Takeshi Matsui & Masayuki Amagai & Mizuho A. Kido & Makoto Tominaga, 2023. "Involvement of skin TRPV3 in temperature detection regulated by TMEM79 in mice," Nature Communications, Nature, vol. 14(1), pages 1-13, December.
    20. Cheoljun Choi & Yujin L. Jeong & Koung-Min Park & Minji Kim & Sangseob Kim & Honghyun Jo & Sumin Lee & Heeseong Kim & Garam Choi & Yoon Ha Choi & Je Kyung Seong & Sik Namgoong & Yeonseok Chung & Young, 2024. "TM4SF19-mediated control of lysosomal activity in macrophages contributes to obesity-induced inflammation and metabolic dysfunction," Nature Communications, Nature, vol. 15(1), pages 1-21, December.
    21. Florin Ratajczak & Mitchell Joblin & Marcel Hildebrandt & Martin Ringsquandl & Pascal Falter-Braun & Matthias Heinig, 2023. "Speos: an ensemble graph representation learning framework to predict core gene candidates for complex diseases," Nature Communications, Nature, vol. 14(1), pages 1-18, December.

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