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Evidence for dynamically organized modularity in the yeast protein–protein interaction network
- Jing-Dong J. Han1,
- Nicolas Bertin1,
- Tong Hao1,
- Debra S. Goldberg2,
- Gabriel F. Berriz2,
- Lan V. Zhang2,
- Denis Dupuy1,
- Albertha J. M. Walhout1 nAff3,
- Michael E. Cusick1,
- Frederick P. Roth2 &
- …
- Marc Vidal1
Naturevolume 430, pages88–93 (2004)Cite this article
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AnErratum to this article was published on 15 July 2004
Abstract
In apparently scale-free protein–protein interaction networks, or ‘interactome’ networks1,2, most proteins interact with few partners, whereas a small but significant proportion of proteins, the ‘hubs’, interact with many partners. Both biological and non-biological scale-free networks are particularly resistant to random node removal but are extremely sensitive to the targeted removal of hubs1. A link between the potential scale-free topology of interactome networks and genetic robustness3,4 seems to exist, because knockouts of yeast genes5,6 encoding hubs are approximately threefold more likely to confer lethality than those of non-hubs1. Here we investigate how hubs might contribute to robustness and other cellular properties for protein–protein interactions dynamically regulated both in time and in space. We uncovered two types of hub: ‘party’ hubs, which interact with most of their partners simultaneously, and ‘date’ hubs, which bind their different partners at different times or locations. Bothin silico studies of network connectivity and genetic interactions describedin vivo support a model of organized modularity in which date hubs organize the proteome, connecting biological processes—or modules7 —to each other, whereas party hubs function inside modules.
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References
Jeong, H., Mason, S. P., Barabasi, A. L. & Oltvai, Z. N. Lethality and centrality in protein networks.Nature411, 41–42 (2001)
Li, S. et al. A map of the interactome network of the metazoanC. elegans.Science303, 540–543 (2004)
Wagner, A. Robustness against mutations in genetic networks of yeast.Nature Genet.24, 355–361 (2000)
Gu, Z. et al. Role of duplicate genes in genetic robustness against null mutations.Nature421, 63–66 (2003)
Winzeler, E. A. et al. Functional characterization of theS. cerevisiae genome by gene deletion and parallel analysis.Science285, 901–906 (1999)
Giaever, G. et al. Functional profiling of theSaccharomyces cerevisiae genome.Nature418, 387–391 (2002)
Hartwell, L. H., Hopfield, J. J., Leibler, S. & Murray, A. W. From molecular to modular cell biology.Nature402, C47–C52 (1999)
Papin, J. A., Price, N. D., Wiback, S. J., Fell, D. A. & Palsson, B. O. Metabolic pathways in the post-genome era.Trends Biochem. Sci.28, 250–258 (2003)
Kemmeren, P. et al. Protein interaction verification and functional annotation by integrated analysis of genome-scale data.Mol. Cell9, 1133–1143 (2002)
von Mering, C. et al. Comparative assessment of large-scale data sets of protein–protein interactions.Nature417, 399–403 (2002)
Ge, H., Liu, Z., Church, G. M. & Vidal, M. Correlation between transcriptome and interactome mapping data fromSaccharomyces cerevisiae.Nature Genet.29, 482–486 (2001)
Huh, W. K. et al. Global analysis of protein localization in budding yeast.Nature425, 686–691 (2003)
Albert, R., Jeong, H. & Barabasi, A. L. Error and attack tolerance of complex networks.Nature406, 378–382 (2000)
Mewes, H. W. et al. MIPS: a database for genomes and protein sequences.Nucleic Acids Res.30, 31–34 (2002)
Ideker, T. & Lauffenburger, D. Building with a scaffold: emerging strategies for high- to low-level cellular modeling.Trends Biotechnol.21, 255–262 (2003)
Giot, L. et al. A protein interaction map ofDrosophila melanogaster.Science302, 1727–1736 (2003)
Le Pont, F. et al. A new scale for measuring dynamic patterns of sexual partnership and concurrency: application to three French Caribbean regions.Sex. Transm. Dis.30, 6–9 (2003)
Uetz, P. et al. A comprehensive analysis of protein–protein interactions inSaccharomyces cerevisiae.Nature403, 623–627 (2000)
Ito, T. et al. A comprehensive two-hybrid analysis to explore the yeast protein interactome.Proc. Natl Acad. Sci. USA98, 4569–4574 (2001)
Fromont-Racine, M., Rain, J. C. & Legrain, P. Toward a functional analysis of the yeast genome through exhaustive two-hybrid screens.Nature Genet.16, 277–282 (1997)
Fromont-Racine, M. et al. Genome-wide protein interaction screens reveal functional networks involving Sm-like proteins.Yeast17, 95–110 (2000)
Ho, Y. et al. Systematic identification of protein complexes inSaccharomyces cerevisiae by mass spectrometry.Nature415, 180–183 (2002)
Gavin, A. C. et al. Functional organization of the yeast proteome by systematic analysis of protein complexes.Nature415, 141–147 (2002)
Bader, G. D., Betel, D. & Hogue, C. W. BIND: the Biomolecular Interaction Network Database.Nucleic Acids Res.31, 248–250 (2003)
Marcotte, E. M., Pellegrini, M., Thompson, M. J., Yeates, T. O. & Eisenberg, D. A combined algorithm for genome-wide prediction of protein function.Nature402, 83–86 (1999)
Dandekar, T., Snel, B., Huynen, M. & Bork, P. Conservation of gene order: a fingerprint of proteins that physically interact.Trends Biochem. Sci.23, 324–328 (1998)
Watts, D. J. & Strogatz, S. H. Collective dynamics of ‘small-world’ networks.Nature393, 440–442 (1998)
Snel, B., Bork, P. & Huynen, M. A. The identification of functional modules from the genomic association of genes.Proc. Natl Acad. Sci. USA99, 5890–5895 (2002)
Acknowledgements
We thank DFCI Research Computing, especially L. Cai and M. Temple, for technical support and computation resources; members of the Vidal laboratory and J. Dekker for suggestions; T. Clingingsmith for administrative assistance; and H. Ge, C. Armstrong, D. Hill, M. Boxem and P.-O. Vidalain for reading the manuscript. F.P.R., G.F.B., L.V.Z. and D.S.G. were supported in part by an institutional grant from the HHMI Biomedical Research Support Program for Medical Schools. L.V.Z. and D.S.G. were supported by a Fu Fellowship and an NSF Postdoctoral Fellowship in Interdisciplinary Informatics, respectively. This work was supported by grants from the NHGRI, NIGMS and NCI awarded to M.V.
Author information
Albertha J. M. Walhout
Present address: Program in Gene Function and Expression, University of Massachusetts Medical School, Worcester, Massachusetts, 01605, USA
Authors and Affiliations
Center for Cancer Systems Biology and Department of Cancer Biology, Dana-Farber Cancer Institute, and Department of Genetics, Harvard Medical School, Boston, Massachusetts, 02115, USA
Jing-Dong J. Han, Nicolas Bertin, Tong Hao, Denis Dupuy, Albertha J. M. Walhout, Michael E. Cusick & Marc Vidal
Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, Massachusetts, 02115, USA
Debra S. Goldberg, Gabriel F. Berriz, Lan V. Zhang & Frederick P. Roth
- Jing-Dong J. Han
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- Nicolas Bertin
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- Tong Hao
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- Debra S. Goldberg
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- Gabriel F. Berriz
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- Lan V. Zhang
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- Denis Dupuy
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- Albertha J. M. Walhout
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- Michael E. Cusick
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- Frederick P. Roth
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- Marc Vidal
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Corresponding author
Correspondence toMarc Vidal.
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Supplementary information
Supplementary Information
Includes supplementary notes, supplementary methods, supplementary figure legends and references. (DOC 82 kb)
Supplementary Figures
Supplementary figure 1: High-confidence filtered yeast interactome (FYI) dataset; supplementary figure 2: Quality assessment of yeast interaction datasets; supplementary figure 3: Scale-free organization of the FYI network; supplementary figure 4: Titration of AvgPCC distribution according to degree distribution; supplementary figure 5: Impact of date or party hubs removals on the network topology. (PDF 1100 kb)
Supplementary Table 1
The identities of date and party hubs analysed in this study are listed together with their overall and condition-specific AvgPCCs and the number of interactions they mediate. (PDF 181 kb)
Supplementary Table 2
All interactions in FYI dataset. (PDF 323 kb)
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Han, JD., Bertin, N., Hao, T.et al. Evidence for dynamically organized modularity in the yeast protein–protein interaction network.Nature430, 88–93 (2004). https://doi.org/10.1038/nature02555
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