2. Academic Validation
  3. A reference map of the human binary protein interactome

A reference map of the human binary protein interactome

  • Nature. 2020 Apr;580(7803):402-408. doi: 10.1038/s41586-020-2188-x.
Katja Luck # 1 2 3,  Dae-Kyum Kim # 1 4 5 6,  Luke Lambourne # 1 2 3,  Kerstin Spirohn # 1 2 3,  Bridget E Begg 1 2 3,  Wenting Bian 1 2 3,  Ruth Brignall 1 2 3,  Tiziana Cafarelli 1 2 3,  Francisco J Campos-Laborie 7 8,  Benoit Charloteaux 1 2 3,  Dongsic Choi 9,  Atina G Coté 1 4 5 6,  Meaghan Daley 1 2 3,  Steven Deimling 10,  Alice Desbuleux 1 2 3 11,  Amélie Dricot 1 2 3,  Marinella Gebbia 1 4 5 6,  Madeleine F Hardy 1 2 3,  Nishka Kishore 1 4 5 6,  Jennifer J Knapp 1 4 5 6,  István A Kovács 1 12 13,  Irma Lemmens 14 15,  Miles W Mee 4 5 16,  Joseph C Mellor 1 4 5 6 17,  Carl Pollis 1 2 3,  Carles Pons 18,  Aaron D Richardson 1 2 3,  Sadie Schlabach 1 2 3,  Bridget Teeking 1 2 3,  Anupama Yadav 1 2 3,  Mariana Babor 1 4 5 6,  Dawit Balcha 1 2 3,  Omer Basha 19 20,  Christian Bowman-Colin 2 3,  Suet-Feung Chin 21,  Soon Gang Choi 1 2 3,  Claudia Colabella 22 23,  Georges Coppin 1 2 3 11,  Cassandra D'Amata 10,  David De Ridder 1 2 3,  Steffi De Rouck 14 15,  Miquel Duran-Frigola 18,  Hanane Ennajdaoui 1 4 5 6,  Florian Goebels 4 5 16,  Liana Goehring 2 3,  Anjali Gopal 1 4 5 6,  Ghazal Haddad 1 4 5 6,  Elodie Hatchi 2 3,  Mohamed Helmy 4 5 16,  Yves Jacob 24 25,  Yoseph Kassa 1 2 3,  Serena Landini 2 3,  Roujia Li 1 4 5 6,  Natascha van Lieshout 1 4 5 6,  Andrew MacWilliams 1 2 3,  Dylan Markey 1 2 3,  Joseph N Paulson 26 27 28,  Sudharshan Rangarajan 1 2 3,  John Rasla 1 2 3,  Ashyad Rayhan 1 4 5 6,  Thomas Rolland 1 2 3,  Adriana San-Miguel 1 2 3,  Yun Shen 1 2 3,  Dayag Sheykhkarimli 1 4 5 6,  Gloria M Sheynkman 1 2 3,  Eyal Simonovsky 19 20,  Murat Taşan 1 4 5 6 16,  Alexander Tejeda 1 2 3,  Vincent Tropepe 10,  Jean-Claude Twizere 11,  Yang Wang 1 2 3,  Robert J Weatheritt 4,  Jochen Weile 1 4 5 6 16,  Yu Xia 1 29,  Xinping Yang 1 2 3,  Esti Yeger-Lotem 19 20,  Quan Zhong 1 2 3 30,  Patrick Aloy 18 31,  Gary D Bader 4 5 16,  Javier De Las Rivas 7 8,  Suzanne Gaudet 1 2 3,  Tong Hao 1 2 3,  Janusz Rak 9,  Jan Tavernier 14 15,  David E Hill 32 33 34,  Marc Vidal 35 36,  Frederick P Roth 37 38 39 40 41 42,  Michael A Calderwood 43 44 45
Affiliations

Affiliations

  • 1 Center for Cancer Systems Biology (CCSB), Dana-Farber Cancer Institute, Boston, MA, USA.
  • 2 Department of Genetics, Blavatnik Institute, Harvard Medical School, Boston, MA, USA.
  • 3 Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA, USA.
  • 4 The Donnelly Centre, University of Toronto, Toronto, Ontario, Canada.
  • 5 Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada.
  • 6 Lunenfeld-Tanenbaum Research Institute (LTRI), Sinai Health System, Toronto, Ontario, Canada.
  • 7 Cancer Research Center (CiC-IBMCC, CSIC/USAL), Consejo Superior de Investigaciones Científicas (CSIC) and University of Salamanca (USAL), Salamanca, Spain.
  • 8 Institute for Biomedical Research of Salamanca (IBSAL), Salamanca, Spain.
  • 9 The Research Institute of the McGill University Health Centre (RI-MUHC), Montreal, Quebec, Canada.
  • 10 Department of Cell and Systems Biology, University of Toronto, Toronto, Ontario, Canada.
  • 11 Molecular Biology of Diseases, Groupe Interdisciplinaire de Génomique Appliquée (GIGA) and Laboratory of Viral Interactomes, University of Liège, Liège, Belgium.
  • 12 Network Science Institute, Northeastern University, Boston, MA, USA.
  • 13 Wigner Research Centre for Physics, Institute for Solid State Physics and Optics, Budapest, Hungary.
  • 14 Center for Medical Biotechnology, Vlaams Instituut voor Biotechnologie (VIB), Ghent, Belgium.
  • 15 Cytokine Receptor Laboratory (CRL), Department of Biomolecular Medicine, Faculty of Medicine and Health Sciences, Ghent University, Ghent, Belgium.
  • 16 Department of Computer Science, University of Toronto, Toronto, Ontario, Canada.
  • 17 seqWell, Beverly, MA, USA.
  • 18 Institute for Research in Biomedicine (IRB Barcelona), The Barcelona Institute for Science and Technology, Barcelona, Catalonia, Spain.
  • 19 Department of Clinical Biochemistry and Pharmacology, Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer-Sheva, Israel.
  • 20 National Institute for Biotechnology in the Negev (NIBN), Ben-Gurion University of the Negev, Beer-Sheva, Israel.
  • 21 Cancer Research UK (CRUK) Cambridge Institute, University of Cambridge, Cambridge, UK.
  • 22 Department of Pharmaceutical Sciences, University of Perugia, Perugia, Italy.
  • 23 Istituto Zooprofilattico Sperimentale dell'Umbria e delle Marche "Togo Rosati" (IZSUM), Perugia, Italy.
  • 24 Département de Virologie, Unité de Génétique Moléculaire des Virus à ARN (GMVR), Institut Pasteur, UMR3569, Centre National de la Recherche Scientifique (CNRS), Paris, France.
  • 25 Université Paris Diderot, Paris, France.
  • 26 Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Boston, MA, USA.
  • 27 Department of Biostatistics, Harvard School of Public Health, Boston, MA, USA.
  • 28 Department of Biostatistics, Product Development, Genentech Inc., South San Francisco, CA, USA.
  • 29 Department of Bioengineering, McGill University, Montreal, Quebec, Canada.
  • 30 Department of Biological Sciences, Wright State University, Dayton, OH, USA.
  • 31 Institució Catalana de Recerca i Estudis Avançats (ICREA), Barcelona, Catalonia, Spain.
  • 32 Center for Cancer Systems Biology (CCSB), Dana-Farber Cancer Institute, Boston, MA, USA. david_hill@dfci.harvard.edu.
  • 33 Department of Genetics, Blavatnik Institute, Harvard Medical School, Boston, MA, USA. david_hill@dfci.harvard.edu.
  • 34 Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA, USA. david_hill@dfci.harvard.edu.
  • 35 Center for Cancer Systems Biology (CCSB), Dana-Farber Cancer Institute, Boston, MA, USA. marc_vidal@dfci.harvard.edu.
  • 36 Department of Genetics, Blavatnik Institute, Harvard Medical School, Boston, MA, USA. marc_vidal@dfci.harvard.edu.
  • 37 Center for Cancer Systems Biology (CCSB), Dana-Farber Cancer Institute, Boston, MA, USA. fritz.roth@utoronto.ca.
  • 38 The Donnelly Centre, University of Toronto, Toronto, Ontario, Canada. fritz.roth@utoronto.ca.
  • 39 Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada. fritz.roth@utoronto.ca.
  • 40 Lunenfeld-Tanenbaum Research Institute (LTRI), Sinai Health System, Toronto, Ontario, Canada. fritz.roth@utoronto.ca.
  • 41 Department of Computer Science, University of Toronto, Toronto, Ontario, Canada. fritz.roth@utoronto.ca.
  • 42 Canadian Institute for Advanced Research (CIFAR), Toronto, Ontario, Canada. fritz.roth@utoronto.ca.
  • 43 Center for Cancer Systems Biology (CCSB), Dana-Farber Cancer Institute, Boston, MA, USA. michael_calderwood@dfci.harvard.edu.
  • 44 Department of Genetics, Blavatnik Institute, Harvard Medical School, Boston, MA, USA. michael_calderwood@dfci.harvard.edu.
  • 45 Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA, USA. michael_calderwood@dfci.harvard.edu.
  • # Contributed equally.
PMID: 32296183 DOI: 10.1038/s41586-020-2188-x
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.

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