Abstract
Currently available protein-protein interaction (PPI) network or 'interactome' maps, obtained with the yeast two-hybrid (Y2H) assay or by co-affinity purification followed by mass spectrometry (co-AP/MS), only cover a fraction of the complete PPI networks. These partial networks display scale-free topologies–most proteins participate in only a few interactions whereas a few proteins have many interaction partners. Here we analyze whether the scale-free topologies of the partial networks obtained from Y2H assays can be used to accurately infer the topology of complete interactomes. We generated four theoretical interaction networks of different topologies (random, exponential, power law, truncated normal). Partial sampling of these networks resulted in sub-networks with topological characteristics that were virtually indistinguishable from those of currently available Y2H-derived partial interactome maps. We conclude that given the current limited coverage levels, the observed scale-free topology of existing interactome maps cannot be confidently extrapolated to complete interactomes.
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References
Barabási, A.L. & Oltvai, Z.N. Network biology: understanding the cell's functional organization. Nat. Rev. Genet. 5, 101–113 (2004).
Strogatz, S.H. Exploring complex networks. Nature 410, 268–276 (2001).
Barabási, A.L., Albert, R. & Jeong, H. Scale-free characteristics of random networks: the topology of the world-wide web. Physica A (Amsterdam) 281, 69–77 (2000).
Yook, S.H., Jeong, H. & Barabasi, A.L. Modeling the Internet's large-scale topology. Proc. Natl. Acad. Sci. USA 99, 13382–13386 (2002).
Uetz, P. et al. A comprehensive analysis of protein-protein interactions in Saccharomyces cerevisiae. Nature 403, 623–627 (2000).
Ito, T. et al. A comprehensive two-hybrid analysis to explore the yeast protein interactome. Proc. Natl. Acad. Sci. USA 98, 4569–4574 (2001).
Reboul, J. et al. C. elegans ORFeome version 1.1: experimental verification of the genome annotation and resource for proteome-scale protein expression. Nat. Genet. 34, 35–41 (2003).
Giot, L. et al. A protein interaction map of Drosophila melanogaster. Science 302, 1727–1736 (2003).
Li, S. et al. A map of the interactome network of the metazoan C. elegans. Science 303, 540–543 (2004).
Han, J.D. et al. Evidence for dynamically organized modularity in the yeast protein-protein interaction network. Nature 430, 88–93 (2004).
Gavin, A.C. et al. Functional organization of the yeast proteome by systematic analysis of protein complexes. Nature 415, 141–147 (2002).
Ho, Y. et al. Systematic identification of protein complexes in Saccharomyces cerevisiae by mass spectrometry. Nature 415, 180–183 (2002).
Walhout, A.J., Boulton, S.J. & Vidal, M. Yeast two-hybrid systems and protein interaction mapping projects for yeast and worm. Yeast 17, 88–94 (2000).
Edwards, A.M. et al. Bridging structural biology and genomics: assessing protein interaction data with known complexes. Trends Genet. 18, 529–536 (2002).
Bader, G.D. & Hogue, C.W. Analyzing yeast protein-protein interaction data obtained from different sources. Nat. Biotechnol. 20, 991–997 (2002).
von Mering, C. et al. Comparative assessment of large-scale data sets of protein-protein interactions. Nature 417, 399–403 (2002).
Grigoriev, A. On the number of protein-protein interactions in the yeast proteome. Nucleic Acids Res. 31, 4157–4161 (2003).
Ito, T. et al. Roles for the two-hybrid system in exploration of the yeast protein interactome. Mol. Cell. Proteomics 1, 561–566 (2002).
Formstecher, E. et al. Protein interaction mapping: A Drosophila case study. Genome Res. 15, 376–384 (2005).
Stumpf, M.P., Wiuf, C. & May, R.M. Subnets of scale-free networks are not scale-free: Sampling properties of networks. Proc. Natl. Acad. Sci. USA (2005).
Przulj, N., Corneil, D.G. & Jurisica, I. Modeling interactome: scale-free or geometric? Bioinformatics 20, 3508–3515 (2004).
Jeong, H., Mason, S.P., Barabasi, A.L. & Oltvai, Z.N. Lethality and centrality in protein networks. Nature 411, 41–42 (2001).
Thomas, A., Cannings, R., Monk, N.A. & Cannings, C. On the structure of protein-protein interaction networks. Biochem. Soc. Trans. 31, 1491–1496 (2003).
Yook, S.H., Oltvai, Z.N. & Barabasi, A.L. Functional and topological characterization of protein interaction networks. Proteomics 4, 928–942 (2004).
Erdös, P. & Rényi, A. On the evolution of random graphs. Publ. Math. Inst. Hung. Acad. Sci. 5, 17–60 (1960).
Barabási, A.L. & Albert, R. Emergence of scaling in random networks. Science 286, 509–512 (1999).
Goffeau, A. et al. Life with 6000 genes. Science 274, 546, 563–547 (1996).
The C. elegans Sequencing Consortium. Genome sequence of the nematode C. elegans: a platform for investigating biology. Science 282, 2012–2018 (1998).
Adams, M.D. et al. The genome sequence of Drosophila melanogaster. Science 287, 2185–2195 (2000).
Schwikowski, B., Uetz, P. & Fields, S. A network of protein-protein interactions in yeast. Nat. Biotechnol. 18, 1257–1261 (2000).
Zhu, H. et al. Global analysis of protein activities using proteome chips. Science 293, 2101–2105 (2001).
Tong, A.H. et al. A combined experimental and computational strategy to define protein interaction networks for peptide recognition modules. Science 295, 321–324 (2002).
Walhout, A.J. & Vidal, M. A genetic strategy to eliminate self-activator baits prior to high-throughput yeast two-hybrid screens. Genome Res. 9, 1128–1134 (1999).
Legrain, P., Wojcik, J. & Gauthier, J.M. Protein-protein interaction maps: a lead towards cellular functions. Trends Genet. 17, 346–352 (2001).
Vidalain, P.O., Boxem, M., Ge, H., Li, S. & Vidal, M. Increasing specificity in high-throughput yeast two-hybrid experiments. Methods 32, 363–370 (2004).
Albert, R., Jeong, H. & Barabasi, A.L. Error and attack tolerance of complex networks. Nature 406, 378–382 (2000).
Wagner, A. Robustness against mutations in genetic networks of yeast. Nat. Genet. 24, 355–361 (2000).
Vogelstein, B., Lane, D. & Levine, A.J. Surfing the p53 network. Nature 408, 307–310 (2000).
Apic, G., Ignjatovic, T., Boyer, S. & Russell, R.B. Illuminating drug discovery with biological pathways. FEBS Lett. 579, 1872–1877 (2005).
Lappe, M. & Holm, L. Unraveling protein interaction networks with near-optimal efficiency. Nat. Biotechnol. 22, 98–103 (2004).
Eisenberg, E. & Levanon, E.Y. Preferential attachment in the protein network evolution. Phys. Rev. Lett. 91, 138701 (2003).
Qin, H., Lu, H.H., Wu, W.B. & Li, W.H. Evolution of the yeast protein interaction network. Proc. Natl. Acad. Sci. USA 100, 12820–12824 (2003).
Pereira-Leal, J.B., Audit, B., Peregrin-Alvarez, J.M. & Ouzounis, C.A. An exponential core in the heart of the yeast protein interaction network. Mol. Biol. Evol. 22, 421–425 (2004).
Hartwell, L.H., Hopfield, J.J., Leibler, S. & Murray, A.W. From molecular to modular cell biology. Nature 402, C47–C52 (1999).
Poyatos, J.F. & Hurst, L.D. How biologically relevant are interaction-based modules in protein networks? Genome Biol. 5, R93 (2004).
Bork, P. et al. Protein interaction networks from yeast to human. Curr. Opin. Struct. Biol. 14, 292–299 (2004).
Dunn, R., Dudbridge, F. & Sanderson, C.M. The use of edge-betweenness clustering to investigate biological function in protein interaction networks. BMC Bioinformatics 6, 39 (2005).
Shen-Orr, S.S., Milo, R., Mangan, S. & Alon, U. Network motifs in the transcriptional regulation network of Escherichia coli. Nat. Genet. 31, 64–68 (2002).
Rives, A.W. & Galitski, T. Modular organization of cellular networks. Proc. Natl. Acad. Sci. USA 100, 1128–1133 (2003).
Bader, G.D. & Hogue, C.W. An automated method for finding molecular complexes in large protein interaction networks. BMC Bioinformatics 4, 2 (2003).
Pereira-Leal, J.B., Enright, A.J. & Ouzounis, C.A. Detection of functional modules from protein interaction networks. Proteins 54, 49–57 (2004).
Acknowledgements
We thank Mike Boxem, Fritz Roth and Debra Goldberg for extremely useful discussions and careful reading of the manuscript. This work was supported by grants from NIGMS, NHGRI, and NCI to M.V.
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Supplementary information
Supplementary Fig. 1
Degree distribution of the complete theoretical networks. (PDF 851 kb)
Supplementary Fig. 2
Sampled networks derived from starting networks of various topologies. (PDF 4952 kb)
Supplementary Fig. 3
Degree distribution of sampled networks. (PDF 4683 kb)
Supplementary Table 1
Comparison between the PPI maps and sampled networks of similar size. (XLS 21 kb)
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Han, JD., Dupuy, D., Bertin, N. et al. Effect of sampling on topology predictions of protein-protein interaction networks. Nat Biotechnol 23, 839–844 (2005). https://doi.org/10.1038/nbt1116
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DOI: https://doi.org/10.1038/nbt1116
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