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Next-generation large-scale binary protein interaction network for Drosophila melanogaster

Author

Listed:
  • Hong-Wen Tang

    (Harvard Medical School
    Duke-NUS Medical School
    Humphrey Oei Institute of Cancer Research, National Cancer Centre Singapore)

  • Kerstin Spirohn

    (Harvard Medical School
    Dana-Farber Cancer Institute)

  • Yanhui Hu

    (Harvard Medical School)

  • Tong Hao

    (Harvard Medical School
    Dana-Farber Cancer Institute)

  • István A. Kovács

    (Dana-Farber Cancer Institute
    Northwestern University
    Northwestern University)

  • Yue Gao

    (Harvard Medical School)

  • Richard Binari

    (Harvard Medical School
    Howard Hughes Medical Institute)

  • Donghui Yang-Zhou

    (Harvard Medical School)

  • Kenneth H. Wan

    (Lawrence Berkeley National Laboratory)

  • Joel S. Bader

    (Whiting School of Engineering, Johns Hopkins University
    Institute of Basic Biological Sciences, Johns Hopkins School of Medicine)

  • Dawit Balcha

    (Harvard Medical School
    Dana-Farber Cancer Institute)

  • Wenting Bian

    (Harvard Medical School
    Dana-Farber Cancer Institute)

  • Benjamin W. Booth

    (Lawrence Berkeley National Laboratory)

  • Atina G. Coté

    (Dana-Farber Cancer Institute
    University of Toronto
    Sinai Health, 600 University Ave)

  • Steffi Rouck

    (Cytokine Receptor Lab, VIB Center for Medical Biotechnology)

  • Alice Desbuleux

    (Harvard Medical School
    Dana-Farber Cancer Institute)

  • Kah Yong Goh

    (Duke-NUS Medical School)

  • Dae-Kyum Kim

    (Roswell Park Comprehensive Cancer Center)

  • Jennifer J. Knapp

    (University of Toronto
    Sinai Health, 600 University Ave)

  • Wen Xing Lee

    (Duke-NUS Medical School)

  • Irma Lemmens

    (Cytokine Receptor Lab, VIB Center for Medical Biotechnology)

  • Cathleen Li

    (Harvard Medical School)

  • Mian Li

    (Harvard Medical School)

  • Roujia Li

    (Dana-Farber Cancer Institute
    University of Toronto
    Sinai Health, 600 University Ave)

  • Hyobin Julianne Lim

    (Roswell Park Comprehensive Cancer Center)

  • Yifang Liu

    (Harvard Medical School)

  • Katja Luck

    (Harvard Medical School
    Dana-Farber Cancer Institute)

  • Dylan Markey

    (Harvard Medical School
    Dana-Farber Cancer Institute)

  • Carl Pollis

    (Harvard Medical School
    Dana-Farber Cancer Institute)

  • Sudharshan Rangarajan

    (Harvard Medical School
    Dana-Farber Cancer Institute)

  • Jonathan Rodiger

    (Harvard Medical School)

  • Sadie Schlabach

    (Harvard Medical School
    Dana-Farber Cancer Institute)

  • Yun Shen

    (Harvard Medical School
    Dana-Farber Cancer Institute)

  • Dayag Sheykhkarimli

    (Dana-Farber Cancer Institute
    University of Toronto
    Sinai Health, 600 University Ave)

  • Bridget TeeKing

    (Harvard Medical School
    Dana-Farber Cancer Institute)

  • Frederick P. Roth

    (Dana-Farber Cancer Institute
    University of Toronto
    Sinai Health, 600 University Ave
    University of Toronto)

  • Jan Tavernier

    (Cytokine Receptor Lab, VIB Center for Medical Biotechnology)

  • Michael A. Calderwood

    (Harvard Medical School
    Dana-Farber Cancer Institute)

  • David E. Hill

    (Harvard Medical School
    Dana-Farber Cancer Institute)

  • Susan E. Celniker

    (Lawrence Berkeley National Laboratory)

  • Marc Vidal

    (Harvard Medical School
    Dana-Farber Cancer Institute)

  • Norbert Perrimon

    (Harvard Medical School
    Howard Hughes Medical Institute)

  • Stephanie E. Mohr

    (Harvard Medical School)

Abstract

Generating reference maps of interactome networks illuminates genetic studies by providing a protein-centric approach to finding new components of existing pathways, complexes, and processes. We apply state-of-the-art methods to identify binary protein-protein interactions (PPIs) for Drosophila melanogaster. Four all-by-all yeast two-hybrid (Y2H) screens of > 10,000 Drosophila proteins result in the ‘FlyBi’ dataset of 8723 PPIs among 2939 proteins. Testing subsets of data from FlyBi and previous PPI studies using an orthogonal assay allows for normalization of data quality; subsequent integration of FlyBi and previous data results in an expanded binary Drosophila reference interaction network, DroRI, comprising 17,232 interactions among 6511 proteins. We use FlyBi data to generate an autophagy network, then validate in vivo using autophagy-related assays. The deformed wings (dwg) gene encodes a protein that is both a regulator and a target of autophagy. Altogether, these resources provide a foundation for building new hypotheses regarding protein networks and function.

Suggested Citation

  • 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.
  • Handle: RePEc:nat:natcom:v:14:y:2023:i:1:d:10.1038_s41467-023-37876-0
    DOI: 10.1038/s41467-023-37876-0
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    References listed on IDEAS

    as
    1. Soon Gang Choi & Julien Olivet & Patricia Cassonnet & Pierre-Olivier Vidalain & Katja Luck & Luke Lambourne & Kerstin Spirohn & Irma Lemmens & Mélanie Dos Santos & Caroline Demeret & Louis Jones & Sud, 2019. "Maximizing binary interactome mapping with a minimal number of assays," Nature Communications, Nature, vol. 10(1), pages 1-13, December.
    2. Orit Rozenblatt-Rosen & Rahul C. Deo & Megha Padi & Guillaume Adelmant & Michael A. Calderwood & Thomas Rolland & Miranda Grace & Amélie Dricot & Manor Askenazi & Maria Tavares & Samuel J. Pevzner & F, 2012. "Interpreting cancer genomes using systematic host network perturbations by tumour virus proteins," Nature, Nature, vol. 487(7408), pages 491-495, July.
    3. István A. Kovács & Katja Luck & Kerstin Spirohn & Yang Wang & Carl Pollis & Sadie Schlabach & Wenting Bian & Dae-Kyum Kim & Nishka Kishore & Tong Hao & Michael A. Calderwood & Marc Vidal & Albert-Lász, 2019. "Network-based prediction of protein interactions," Nature Communications, Nature, vol. 10(1), pages 1-8, December.
    4. Christian Behrends & Mathew E. Sowa & Steven P. Gygi & J. Wade Harper, 2010. "Network organization of the human autophagy system," Nature, Nature, vol. 466(7302), pages 68-76, July.
    5. James B. Brown & Nathan Boley & Robert Eisman & Gemma E. May & Marcus H. Stoiber & Michael O. Duff & Ben W. Booth & Jiayu Wen & Soo Park & Ana Maria Suzuki & Kenneth H. Wan & Charles Yu & Dayu Zhang &, 2014. "Diversity and dynamics of the Drosophila transcriptome," Nature, Nature, vol. 512(7515), pages 393-399, August.
    6. 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.
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