System biology database and pathway analysis
Development of high throughput methods of analysis in the post-genomic era allowed the system biology approach in studying of complex processes and disorders, like glaucoma and cataract formation. The clinical and genetic (epistatic) data for major diseases are comprehensive, abundant yet noisy and poorly utilized to date due to a lack of functional interpretation methods. The small scale genetic data and HT data are not directly comparable, as they represent discrete levels in a non-linear information flow between genotype and phenotype. The interpretation of complex disease datasets requires a systems approach, implying an understanding of connectivity between the genes and proteins affected in the disease. Different types of disease-relevant data can be integrated, cross-validated and interpreted using biological networks built out of binary protein interactions with genes and proteins as the nodes. The one-step binary interactions form multi-step modules and pathways, which graphically represent protein complexes and chains of consecutive functions and reactions in the cell. The complete set of species-specific interactions defines the potential of the core cellular machinery of the organism, where only a fraction is activated at any time and condition, which is generally captured by HT experiments. Recently, it was established that eukaryotic biological networks are non-random and are modular. The network topology correlates with biological properties of the nodes, in which well-connected hubs are largely represented by evolutionarily conserved, essential proteins, as shown in yeast. The links between highly connected and infrequently connected nodes define the condition-specific topology of a network with implications for the modules as drug targets.
Complex, multifactorial nature of the both disorders studied in our lab, slow progression and strong influence of age require comprehensive systems approach to study them. In addition to the vast array of modern molecular cell biology, functional genomics and bioinformatics methods, we utilize the to elucidate these mechanisms at the levels of gene regulation, protein interaction and activity of pathways and protein networks. Using the MetaCore™ Analytical suite (in collaboration with GeneGo Inc.) we extract additional layers of functional information from various “high throughput” (HT) data. Analysis of HT data obtained from the affected cells in the lens and the optic nerve tissues revealed changes in complex networks of interacting cellular pathways. Such “network” analysis allows us to utilize various types of HT data, including microarray and proteomic data, to complement for gaps and imperfections in these datasets, and reveal conserved network modules that are most relevant to pathophysiology.