Deducing topology of protein-protein interaction networks from experimentally measured sub-networks

BackgroundProtein-protein interaction networks are commonly sampled using yeast two hybrid approaches. However, whether topological information reaped from these experimentally-measured sub-networks can be extrapolated to complete protein-protein interaction networks is unclear.ResultsBy analyzing various experimental protein-protein interaction datasets, we found that they are not random samples of the parent networks. Based on the experimental bait-prey behaviors, our computer simulations show that these non-random sampling features may affect the topological information. We tested the hypothesis that a core sub-network exists within the experimentally sampled network that better maintains the topological characteristics of the parent protein-protein interaction network. We developed a method to filter the experimentally sampled network to result in a core sub-network that more accurately reflects the topology of the parent network. These findings have fundamental implications for large-scale protein interaction studies and for our understanding of the behavior of cellular networks.ConclusionThe topological information from experimental measured networks network as is may not be the correct source for topological information about the parent protein-protein interaction network. We define a core sub-network that more accurately reflects the topology of the parent network.

[1]  J. Doyle,et al.  Some protein interaction data do not exhibit power law statistics , 2005, FEBS letters.

[2]  Albert,et al.  Emergence of scaling in random networks , 1999, Science.

[3]  A Vázquez,et al.  The topological relationship between the large-scale attributes and local interaction patterns of complex networks , 2004, Proceedings of the National Academy of Sciences of the United States of America.

[4]  Frederick H Willeboordse Dynamical advantages of scale-free networks. , 2006, Physical review letters.

[5]  Zhilin Qu,et al.  Hysteresis and cell cycle transitions: how crucial is it? , 2005, Biophysical journal.

[6]  Prahlad T. Ram,et al.  Formation of Regulatory Patterns During Signal Propagation in a Mammalian Cellular Network , 2005, Science.

[7]  S. Shen-Orr,et al.  Networks Network Motifs : Simple Building Blocks of Complex , 2002 .

[8]  A. Barabasi,et al.  Network biology: understanding the cell's functional organization , 2004, Nature Reviews Genetics.

[9]  S. Havlin,et al.  Self-similarity of complex networks , 2005, Nature.

[10]  Albert-László Barabási,et al.  Error and attack tolerance of complex networks , 2000, Nature.

[11]  Carsten Wiuf,et al.  Sampling properties of random graphs: the degree distribution. , 2005, Physical review. E, Statistical, nonlinear, and soft matter physics.

[12]  A. Fraser,et al.  A first-draft human protein-interaction map , 2004, Genome Biology.

[13]  S. Shen-Orr,et al.  Network motifs: simple building blocks of complex networks. , 2002, Science.

[14]  Hawoong Jeong,et al.  Statistical properties of sampled networks. , 2005, Physical review. E, Statistical, nonlinear, and soft matter physics.

[15]  M. Vidal,et al.  Effect of sampling on topology predictions of protein-protein interaction networks , 2005, Nature Biotechnology.

[16]  R. Ozawa,et al.  A comprehensive two-hybrid analysis to explore the yeast protein interactome , 2001, Proceedings of the National Academy of Sciences of the United States of America.

[17]  R. Tsien,et al.  Specificity and Stability in Topology of Protein Networks , 2022 .

[18]  J. Rothberg,et al.  Gaining confidence in high-throughput protein interaction networks , 2004, Nature Biotechnology.

[19]  S. L. Wong,et al.  A Map of the Interactome Network of the Metazoan C. elegans , 2004, Science.

[20]  Edward A. Bender,et al.  The Asymptotic Number of Labeled Graphs with Given Degree Sequences , 1978, J. Comb. Theory A.

[21]  Hong Qian,et al.  Free-energy distribution of binary protein-protein binding suggests cross-species interactome differences. , 2006, Proceedings of the National Academy of Sciences of the United States of America.

[22]  Carsten Wiuf,et al.  Subnets of scale-free networks are not scale-free: sampling properties of networks. , 2005, Proceedings of the National Academy of Sciences of the United States of America.

[23]  R. Albert,et al.  The large-scale organization of metabolic networks , 2000, Nature.

[24]  Adam J. Smith,et al.  The Database of Interacting Proteins: 2004 update , 2004, Nucleic Acids Res..

[25]  B. Snel,et al.  Comparative assessment of large-scale data sets of protein–protein interactions , 2002, Nature.

[26]  James R. Knight,et al.  A Protein Interaction Map of Drosophila melanogaster , 2003, Science.

[27]  S. Shen-Orr,et al.  Superfamilies of Evolved and Designed Networks , 2004, Science.

[28]  H. Lehrach,et al.  A Human Protein-Protein Interaction Network: A Resource for Annotating the Proteome , 2005, Cell.

[29]  Lan V. Zhang,et al.  Evidence for dynamically organized modularity in the yeast protein–protein interaction network , 2004, Nature.

[30]  R. Russell,et al.  Potential artefacts in protein‐interaction networks , 2002, FEBS letters.

[31]  Eric J. Deeds,et al.  A simple physical model for scaling in protein-protein interaction networks. , 2005, Proceedings of the National Academy of Sciences of the United States of America.

[32]  Soon-Hyung Yook,et al.  Statistical properties of sampled networks by random walks. , 2007, Physical review. E, Statistical, nonlinear, and soft matter physics.

[33]  A. Barabasi,et al.  Lethality and centrality in protein networks , 2001, Nature.

[34]  Z. N. Oltvai,et al.  Topological units of environmental signal processing in the transcriptional regulatory network of Escherichia coli , 2005, Proceedings of the National Academy of Sciences of the United States of America.

[35]  James R. Knight,et al.  A comprehensive analysis of protein–protein interactions in Saccharomyces cerevisiae , 2000, Nature.

[36]  Raya Khanin,et al.  How Scale-Free Are Biological Networks , 2006, J. Comput. Biol..

[37]  Sergei Maslov,et al.  Protein interaction networks beyond artifacts , 2002, FEBS letters.

[38]  K. Sneppen,et al.  Specificity and Stability in Topology of Protein Networks , 2002, Science.

[39]  Ioannis Xenarios,et al.  DIP: The Database of Interacting Proteins: 2001 update , 2001, Nucleic Acids Res..

[40]  J. Collins,et al.  Inferring Genetic Networks and Identifying Compound Mode of Action via Expression Profiling , 2003, Science.

[41]  K. N. Chandrika,et al.  Analysis of the human protein interactome and comparison with yeast, worm and fly interaction datasets , 2006, Nature Genetics.

[42]  Nicholas J. Guido,et al.  A bottom-up approach to gene regulation , 2006, Nature.

[43]  Igor Jurisica,et al.  Modeling interactome: scale-free or geometric? , 2004, Bioinform..

[44]  S. Low,et al.  The "robust yet fragile" nature of the Internet. , 2005, Proceedings of the National Academy of Sciences of the United States of America.

[45]  B. Berger,et al.  Herpesviral Protein Networks and Their Interaction with the Human Proteome , 2006, Science.