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Cited by 1,437Bioinformatics and Genomic NetworksAdvanced Proteomics Techniques and ApplicationsBiotin and Related Studies

Architecture of the human interactome defines protein communities and disease networks

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Huttlin, Edward L., Bruckner, Raphael J., Paulo, Joao A., Cannon, Joe R., Ting, Lily, Baltier, Kurt, Colby, Greg, Gebreab, Fana +17 more·2017·Nature
DOI 10.1038/nature22366PMC PMC5531611
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Abstract

The physiology of a cell can be viewed as the product of thousands of proteins acting in concert to shape the cellular response. Coordination is achieved in part through networks of protein-protein interactions that assemble functionally related proteins into complexes, organelles, and signal transduction pathways. Understanding the architecture of the human proteome has the potential to inform cellular, structural, and evolutionary mechanisms and is critical to elucidating how genome variation contributes to disease. Here we present BioPlex 2.0 (Biophysical Interactions of ORFeome-derived complexes), which uses robust affinity purification-mass spectrometry methodology to elucidate protein interaction networks and co-complexes nucleated by more than 25% of protein-coding genes from the human genome, and constitutes, to our knowledge, the largest such network so far. With more than 56,000 candidate interactions, BioPlex 2.0 contains more than 29,000 previously unknown co-associations and provides functional insights into hundreds of poorly characterized proteins while enhancing network-based analyses of domain associations, subcellular localization, and co-complex formation. Unsupervised Markov clustering of interacting proteins identified more than 1,300 protein communities representing diverse cellular activities. Genes essential for cell fitness are enriched within 53 communities representing central cellular functions. Moreover, we identified 442 communities associated with more than 2,000 disease annotations, placing numerous candidate disease genes into a cellular framework. BioPlex 2.0 exceeds previous experimentally derived interaction networks in depth and breadth, and will be a valuable resource for exploring the biology of incompletely characterized proteins and for elucidating larger-scale patterns of proteome organization.

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  • BioPlex originated from affinity purification coupled to mass spectrometry, while STRING and InWeb aggregate data from multiple sources.

    “The BioPlex database was developed by the method of affinity purification and mass spectrometry, whereas the STRING and InWeb contain information from various sources.”

    From Deep Multilayer Brain Proteomics Identifies Molecular Networks in Alzheimer’s Disease Progression (2020) · cites this paper as Huttlin et al., 2017

    The Online Experimental Methods section, “Affinity-Purification Mass Spectrometry” (page unavailable), describes the AP-MS experiments used to build BioPlex. “Comparison with Interaction Databases” names STRING but does not say it aggregates multiple sources; no passage found addresses InWeb or its sources. (LLM, conf=0.88)

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Authors
Huttlin, E. L., Bruckner, R. J., Paulo, J. A., Cannon, J. R., Ting, L., Baltier, K., Colby, G., Gebreab, F., Gygi, M. P., Parzen, H., Szpyt, J., Tam, S., Zarraga, G., Pontano-Vaites, L., Swarup, S., White, A. E., Schweppe, D. K., Rad, R., Erickson, B. K., Obar, R. A., Guruharsha, K. G., Li, K., Artavanis-Tsakonas, S., Gygi, S. P., & Harper, J. W.
Affiliations
  • Harvard University (US)
  • Biogen (United States) (US)
Corresponding author
  • Huttlin, Edward L.
  • Gygi, Steven P.
  • Harper, J. Wade
ORCID
Venue
Nature
Publisher
Springer Science and Business Media LLC
Published
2017-05
Volume
545
Issue
7655
Pages
505-509
ISSN
  • 0028-0836 (ISSN-L)
  • 1476-4687
DOI
10.1038/nature22366
PMC
PMC5531611
OpenAlex
W2616561032
Cited by
1,437
References
11
Citations by year
2026: 75 · 2025: 109 · 2024: 145 · 2023: 123 · 2022: 162 · 2021: 217 · 2020: 237 · 2019: 174 · 2018: 147 · 2017: 44 · 2015: 1 · 2013: 1
FWCI
67.61
Type
journal article
Language
en
Open access
Licence
www.springer.com/tdm (tdm)
Locations
  • Nature (publishedVersion)
  • PubMed (publishedVersion)
  • Europe PMC (PubMed Central) (acceptedVersion)
  • PubMed Central (acceptedVersion)
  • Digital Access to Scholarship at Harvard (DASH) (Harvard University) (submittedVersion, cc-by)
  • RePEc: Research Papers in Economics (submittedVersion)
Funders
  • National Human Genome Research Institute (U41HG006673)
  • National Institute of Diabetes and Digestive and Kidney Diseases (K01DK098285)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
  • Physical Sciences › Chemistry › Spectroscopy › Advanced Proteomics Techniques and Applications
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Cell Biology › Biotin and Related Studies
Keywords
protein-protein interaction, disease networks, candidate disease genes, affinity purification mass spectrometry, Markov clustering, essential genes, subcellular localization
MeSH terms
Cell Physiological Phenomena, Disease, Humans, Markov Chains, Mass Spectrometry, Genome, Human, Open Reading Frames, Proteome, Protein Interaction Mapping, Databases, Protein, Intracellular Space, Molecular Sequence Annotation, Protein Interaction Maps

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