Network science deals with biological complexity by summarizing complex systems as components (nodes) and interactions (edges) between them. Despite or even perhaps because of such simplifications, informative discoveries can and have been made (Interactome networks and human disease, Cell 2011). In cellular systems nodes are metabolites and macromolecules such as proteins, RNA molecules and gene sequences, while the edges are physical, biochemical and functional interactions that can be identified with a plethora of technologies.
The first step is to provide maps of such functional interactions using systematic and standardized approaches and assays that are as unbiased as possible, undertaken by the Interactome Group. The challenge then faced by the Network Biology Group is to examine the resulting ‘‘interactome’’ networks, the networks of interactions between cellular components, and extract global or local graph theory properties. Such graph properties can be related back to improved understanding of biological processes.
The Network Biology Group has been exploring how perturbations of interactome networks may differ between complete loss of gene products (node removal) versus interaction-specific or edge-specific (edgetic) alterations (Edgetic perturbation models of human inherited disorders, Mol Syst Biol 2009; 'Edgetic' perturbation of a C. elegans BCL2 ortholog, Nat Methods 2009), and how protein-protein interactions are mediated through independently folding modular domains (A protein domain-based interactome network for C. elegans early embryogenesis, Cell 2008). A novel network modeling strategy was applied to successfully identify genes potentially associated with higher risk of breast cancer (Network modeling links breast cancer susceptibility and centrosome dysfunction, Nat Genet 2007).
Efforts are now underway to carry out edgetic profiling systematically for dozens of diseases, hundreds of proteins, and thousands of genetic variants. This undertaking is supported by a Center of Excellence in Genomic Science (CEGS) award on “Genomic Analysis of Network Perturbations in Human Disease” grant P50-HG004233.
Creation of networks of genetic disorders and all their known gene associations (The human disease network, PNAS 2007), or of drugs and all their known protein targets (Drug-target network, Nat Biotechnol 2007), enabled worthwhile insights into human disease and disease therapy. Protein-protein interaction mapping efforts focused on specific human diseases (ataxia [Lim et al, Cell 2006; Lim et al, Nature 2008], autism [Sakai et al, Sci Trans Med 2011], and breast cancer [Pujana et al, Nat Genet 2007]) have identified novel interactions among proteins encoded by known disease genes, and have also predicted new disease susceptibility genes. The common finding among these disease interactomes is the discovery of unexpected relationships between disease genes that initially appeared unrelated [e.g., Kahle et al, Hum Mol Genet 2011 for ataxia]. Building and analyzing more disease-centric networks is accordingly a critical step towards deeper understanding of underlying disease mechanisms. Such efforts are currently supported by NIH grant R01-GM109199 "Functional profiling of human disease targets".
As networks expand and rewire, new nodes, that is new genes and new proteins, get joined into the network. A longstanding question in evolution is where do new genes come from. We formalized for the yeast S. cerevisiae an evolutionary model by which functional genes evolve through transitory proto-genes generated by widespread translational activity in non-genic sequences (Proto-genes and de novo gene birth, Nature 2012). Proto-genes mirror for gene birth the established pseudo-gene route to gene death (Figure).
Edgetic perturbations might play a role in evolution. In the first proteome-wide binary protein-protein interaction map for the interactome network of the reference plant Arabidopsis thaliana we observed a dynamic rewiring of interactions following gene duplication events. The interactions mediated by the products of duplicated genes diverged in a time-dependent manner similar to how their protein sequences diverge. This finding argues that rewiring of protein-protein interactions of proteins encoded by duplicated genes contributes strongly to phenotypic evolution (Arabidopsis Interactome Mapping Consortium, Science 2011).
The Network Biology Group efforts are focused on deciphering properties and meaning of the recent concluded Space-II map of the human interactome (here). Another major effort is the interpretation of an unprecedented and robust inter-interactome network map constructed by confronting together two proteomes, yeast Saccharomyces cerevisiae and human, evolutionarily separated for a billion years.