Biological function is the complex consequence of the action of a large number of molecules that interact in many different ways. Elucidating the contribution of each molecule to a particular function would seem hopeless, had evolution not shaped the interaction of molecules in such a way that they form functional units, or building blocks, of the organisms function. These building blocks can be called modules, whose interactions, interconnections, and fault-tolerance can be investigated from a higher-level point of view, allowing for a synthetic view of biological systems. This FIBR program takes an integrated interdisciplinary computational and experimental approach to determine the extent of modularity in the gene-interaction network, the properties of modules, their contribution to robustness and fault-tolerance, their origin and evolution, and how existing and emerging criteria of module definition and function affect our ability to predict biological function.
Our research teams develop and evaluate different algorithms for module detection as applied to known gene interaction networks available in the literature, as well as to networks that have been evolved in-silico under different controlled conditions. This effort will yield a set of proposed modules for a given gene interaction network. On the experimental side, they generate a high-level causal interaction map of gene function by transforming a set of several hundred known temperature-sensitive mutants of bakers yeast (S. cerevisiae) in order to obtain sets of compensatory gene pairs, that is, pairs of genes whose single-knockout or overexpression is harmful, while the pair is neutral. These pairs form a subset of all interacting genes that reflect alternative functional interactions, and are therefore likely to be involved in modules. The team will test how the clustered causal map overlays to the putative modules derived from the computational effort, which will either validate or amend our current concepts of modularity. A similar effort will be conducted using compensatory pairs in Pichia pastoris, a close relative of S. cervisiae that has an alternative metabolic pathway, in order to study evolutionary changes in the modules contributing to metabolic function.
This interdisciplinary project brings together a team of collaborators with very distinct but complementary expertise in molecular biology, computational science, and physics at the Keck Graduate Institute, the University of Rochester Medical School, and the San Diego Supercomputing Center (SDSC). Part of the project involves the development of a web-based Systems Biology Component centered on the concepts of modularity in biological function, illustrated in parallel with examples of modularity in electronic circuit design.
An important component of this program is the dissemination to local schools, through training and outreach programs, of the fundamental concepts behind the workings of complex living cells, how evolution shapes these functions, and how training in mathematics, physics, computing and biology together are needed for understanding life.
