title: Evolutionary cores of domain co-occurrence networks.
abstract: BACKGROUND
  The modeling of complex systems, as disparate as the World Wide Web and the cellular metabolism, as networks has recently uncovered a set of generic organizing principles: Most of these systems are scale-free while at the same time modular, resulting in a hierarchical architecture. The structure of the protein domain network, where individual domains correspond to nodes and their co-occurrences in a protein are interpreted as links, also falls into this category, suggesting that domains involved in the maintenance of increasingly developed, multicellular organisms accumulate links. Here, we take the next step by studying link based properties of the protein domain co-occurrence networks of the eukaryotes S. cerevisiae, C. elegans, D. melanogaster, M. musculus and H. sapiens.
  
  
  RESULTS
  We construct the protein domain co-occurrence networks from the PFAM database and analyze them by applying a k-core decomposition method that isolates the globally central (highly connected domains in the central cores) from the locally central (highly connected domains in the peripheral cores) protein domains through an iterative peeling process. Furthermore, we compare the subnetworks thus obtained to the physical domain interaction network of S. cerevisiae. We find that the innermost cores of the domain co-occurrence networks gradually grow with increasing degree of evolutionary development in going from single cellular to multicellular eukaryotes. The comparison of the cores across all the organisms under consideration uncovers patterns of domain combinations that are predominately involved in protein functions such as cell-cell contacts and signal transduction. Analyzing a weighted interaction network of PFAM domains of yeast, we find that domains having only a few partners frequently interact with these, while the converse is true for domains with a multitude of partners. Combining domain co-occurrence and interaction information, we observe that the co-occurrence of domains in the innermost cores (globally central domains) strongly coincides with physical interaction. The comparison of the multicellular eukaryotic domain co-occurrence networks with the single celled of S. cerevisiae (the overlap network) uncovers small, connected network patterns.
  
  
  CONCLUSIONS
  We hypothesize that these patterns, consisting of the domains and links preserved through evolution, may constitute nucleation kernels for the evolutionary increase in proteome complexity. Combining co-occurrence and physical interaction data we argue that the driving force behind domain fusions is a collective effect caused by the number of interactions and not the individual interaction frequency.
authors.affiliation: Northwestern Institute of Complexity, Northwestern University, Evanston, IL, USA. s-wuchty@northwestern.edu
authors.forename: Stefan
authors.initials: S
authors.lastname: Wuchty
authors.forename: Eivind
authors.initials: E
authors.lastname: Almaas
mesh_terms: D000818:Animals; D016000:Cluster Analysis; D019295:Computational Biology; D030562:Databases, Protein; D019143:Evolution, Molecular; D023281:Genomics; D006801:Humans; D008957:Models, Genetic; D015233:Models, Statistical; D011485:Protein Binding; D025941:Protein Interaction Mapping; D017434:Protein Structure, Tertiary; D011506:Proteins / Q000737:chemistry; D040901:Proteomics / Q000379:methods; D012441:Saccharomyces cerevisiae / Q000378:metabolism; D020539:Sequence Analysis, Protein; D015398:Signal Transduction; D013045:Species Specificity
chemical_list: D011506:Proteins