Dual proteome-scale networks reveal cell-specific remodeling of the human interactome
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SUMMARY: Thousands of interactions assemble proteins into modules that impart spatial and functional organization to the cellular proteome. Through affinity-purification mass spectrometry, we have created two proteome-scale, cell-line-specific interaction networks. The first, BioPlex 3.0, results from affinity purification of 10,128 human proteins – half the proteome – in 293T cells and includes 118,162 interactions among 14,586 proteins; the second results from 5,522 immunoprecipitations in HCT116 cells. These networks model the interactome at unprecedented scale, encoding protein function, localization, and complex membership. Their comparison validates thousands of interactions and reveals extensive customization of each network. While shared interactions reside in core complexes and involve essential proteins, cell-specific interactions bridge conserved complexes, likely ‘rewiring’ each cell’s interactome. Interactions are gained and lost in tandem among proteins of shared function as the proteome remodels to produce each cell’s phenotype. Viewable interactively online through BioPlexExplorer, these networks define principles of proteome organization and enable unknown protein characterization.
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Experimental approaches to discover protein-protein interactions at scale are laborious, yield many false positive and false negative interactions, and have not generated a comprehensive structural interactome.
“While these methods have uncovered many PPIs, they are laborious, yield many false positive and false negative interactions, and thus far have not generated a comprehensive structural interactome.”
From Predictomes, a classifier-curated database of AlphaFold-modeled protein-protein interactions (2025) · cites this paper as [5]
The Introduction says extensive AP-MS sample preparation limits scalability and that a complete human interactome map remains elusive. The Results discuss missed real interactions and the risk of spurious ones, but say stringent filtering keeps the reported false-discovery rate low. The paper therefore does not support the unqualified claim that these approaches yield many false-positive interactions; it also discusses an incomplete interactome map rather than specifically a comprehensive structural interactome. (LLM, conf=0.86)
Experimental — accuracy not yet measuredThe introduction of data from Bioplex, STRING and Reactome has allowed display of rich PPI data and allows users to examine how multiple targets may interact.
“The introduction of data from Bioplex (39), STRING and Reactome (40) has allowed us to display rich PPI data, and allows users to examine how multiple targets may interact”
From TCRD and pharos 2021: mining the human proteome for disease biology (2021) · cites this paper as [39]
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Cell-fate determination by ubiquitin-dependent regulation of translation
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Complex‐centric proteome profiling by SEC‐SWATH‐MS
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Functional organization of the Sm core in the crystal structure of human U1 snRNP
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Self-citationThe complete structure of the human TFIIH core complex
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Cryo-EM Structure of the Human Ribonuclease P Holoenzyme
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Polyglutamylation: a fine‐regulator of protein function?
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Spatiotemporal variation of mammalian protein complex stoichiometries
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CryoEM structures of human CMG–ATPγS–DNA and CMG–AND-1 complexes
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A multi-scale map of cell structure fusing protein images and interactions
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ABRO1 suppresses tumourigenesis and regulates the DNA damage response by stabilizing p53
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High‐resolution mapping of cancer cell networks using co‐functional interactions
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A proximity-dependent biotinylation map of a human cell: an interactive web resourcePreprint
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Disentangling Genetic and Environmental Effects on the Proteotypes of Individuals
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Glucose deprivation induces primary cilium formation through mTORC1 inactivation
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A Compendium of Co-regulated Protein Complexes in Breast Cancer Reveals Collateral Loss Events
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Context-specific interactions in literature-curated protein interaction databases
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A Proximity Biotinylation Map of a Human Cell
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A reference map of the human protein interactomePreprint
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C11ORF74 interacts with the IFT-A complex and participates in ciliary BBSome localization
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Flagged first, then by citations
Research works printed but not linked: 1
- Qin Y, Winsnes CF, Huttlin EL, Zheng F, Ouyang W, Park J, Pitea A, Kreisberg JF, Gygi SP, Harper JW, (2020). Mapping cell structure across scales by fusing protein images and interactions. Biorxiv 2020.06.21.163709.
Cited by
Sorted by citations
OpenCell: Endogenous tagging for the cartography of human cellular organization
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The IntAct database: efficient access to fine-grained molecular interaction data
del Toro, N., Shrivastava, A., Ragueneau, E., Meldal, B., Combe, C., Barrera, E., Perfetto, L., How, K., Ratan, P., Shirodkar, G., et al. (2022) · Nucleic Acids Research · doi:10.1093/nar/gkab1006 · Cited by 405 · see citing works
TCRD and pharos 2021: mining the human proteome for disease biology
Sheils, T. K., Mathias, S. L., Kelleher, K. J., Siramshetty, V. B., Nguyen, D.-T., Bologa, C. G., Jensen, L. J., Vidović, D., Koleti, A., Schürer, S. C., et al. (2021) · Nucleic Acids Research · doi:10.1093/nar/gkaa993 · Cited by 160 · see citing works
The social and structural architecture of the yeast protein interactome
Michaelis, A. C., Brunner, A.-D., Zwiebel, M., Meier, F., Strauss, M. T., Bludau, I., & Mann, M. (2023) · Nature · doi:10.1038/s41586-023-06739-5 · Cited by 119 · see citing works
“Yeast proteins are highly connected, with an average of 16 and a median of 6 interactions per protein, significantly more than the human BioPlex interactome 24 (average interactions: 8) (Fig.”
BackgroundScalable genetic screening for regulatory circuits using compressed Perturb-seq
Yao, D., Binan, L., Bezney, J., Simonton, B., Freedman, J., Frangieh, C. J., Dey, K., Geiger-Schuller, K., Eraslan, B., Gusev, A., et al. (2024) · Nature Biotechnology · doi:10.1038/s41587-023-01964-9 · Cited by 101 · see citing works
Systematic discovery of protein interaction interfaces using AlphaFold and experimental validation
Lee, C. Y., Hubrich, D., Varga, J. K., Schäfer, C., Welzel, M., Schumbera, E., Djokic, M., Strom, J. M., Schönfeld, J., Geist, J. L., et al. (2024) · Molecular Systems Biology · doi:10.1038/s44320-023-00005-6 · Cited by 105 · see citing works
“Mass spectrometry-based approaches involving affinity purification or co-fractionation have identified around 150,000 co-complex associations between human proteins (Drew et al , 2017; Huttlin et al , 2021).”
BackgroundSystematic discovery of protein interaction interfaces using AlphaFold and experimental validation
Lee, C. Y., Hubrich, D., Varga, J. K., Schäfer, C., Welzel, M., Schumbera, E., Đokić, M., Strom, J. M., Schönfeld, J., Geist, J. L., et al. (2023) · doi:10.1101/2023.08.07.552219 · Cited by 105 · see citing works
Network analysis reveals rare disease signatures across multiple levels of biological organization
Buphamalai, P., Kokotovic, T., Nagy, V., & Menche, J. (2021) · Nature Communications · doi:10.1038/s41467-021-26674-1 · Cited by 95 · see citing works
Predictomes, a classifier-curated database of AlphaFold-modeled protein-protein interactions
Schmid, E. W., & Walter, J. C. (2025) · Molecular Cell · doi:10.1016/j.molcel.2025.01.034 · Cited by 120 · see citing works
“Experimental approaches toward this goal include yeast two hybrid assays 2,4 , co-immunoprecipitation 5 , column chromatography based complex fractionation 6 , and cross-linking coupled with mass spectrometry 7 .”
A multi-scale map of cell structure fusing protein images and interactions
Qin, Y., Huttlin, E. L., Winsnes, C. F., Gosztyla, M. L., Wacheul, L., Kelly, M. R., Blue, S. M., Zheng, F., Chen, M., Schaffer, L. V., et al. (2021) · Nature · doi:10.1038/s41586-021-04115-9 · Cited by 82 · see citing works
Self-citationDecoding the Foodome: Molecular Networks Connecting Diet and Health
Menichetti, G., Barabási, A.-L., & Loscalzo, J. (2024) · Annual Review of Nutrition · doi:10.1146/annurev-nutr-062322-030557 · Cited by 32 · see citing works
On the robustness of graph-based clustering to random network alterations
Stacey, R. G., Skinnider, M. A., & Foster, L. J. (2021) · Molecular & Cellular Proteomics · doi:10.1074/mcp.ra120.002275 · Cited by 11 · see citing works
- Authors
- Huttlin, E. L., Bruckner, R. J., Navarrete-Perea, J., Cannon, J. R., Baltier, K., Gebreab, F., Gygi, M. P., Thornock, A., Zarraga, G., Tam, S., Szpyt, J., Panov, A., Parzen, H., Fu, S., Golbazi, A., Maenpaa, E., Stricker, K., Thakurta, S. G., Rad, R., Pan, J., Nusinow, D. P., Paulo, J. A., Schweppe, D. K., Vaites, L. P., Harper, J. W., & Gygi, S. P.
- Affiliations
- Harvard University (US)
- Broad Institute (US)
- Corresponding author
- Huttlin, Edward L.
- Harper, J. Wade
- Gygi, Steven P.
- ORCID
- Venue
- Cell
- Publisher
- openRxiv
- Published
- 2020-01-19
- Volume
- 184
- Issue
- 11
- Pages
- 3022-3040.e28
- ISSN
- 0092-8674 (ISSN-L)
- PMC
- PMC8165030
- OpenAlex
- W3157357317
- Cited by
- 960
- References
- 115
- Citations by year
- 2026: 135 · 2025: 195 · 2024: 213 · 2023: 187 · 2022: 139 · 2021: 68 · 2020: 20 · 2018: 1 · 2013: 1
- FWCI
- 48.56
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Cell (publishedVersion)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- Biogen
- National Institutes of Health (HG006673)
- National Human Genome Research Institute (U41HG006673, U24HG006673)
- National Institute of General Medical Sciences (T32GM080189)
- 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
- human interactome, protein-protein interaction, HEK293T cells, HCT116 cells, protein complexes, cell line comparison
- MeSH terms
- Humans, Mass Spectrometry, Computational Biology, Proteome, Protein Interaction Mapping, Proteomics, HCT116 Cells, HEK293 Cells, Protein Interaction Maps
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