Network Biology
In collaboration with Drs. Emili and Greenblatt at the university of Toronto, we recently generated and analysed the first large scale protein interaction network from E. coli. Adopting a comparative approach, we revealed a highly conserved core of interacting proteins within this network and detected patterns of functional diversification and the formation of novel evolutionary modules. As well as providing insights into the evolution of microbial interaction networks, these findings will facilitate the design of cross- and broad spectrum anti-microbials. Building on this work we have recently received funding from CIHR, to complete the mapping of protein-protein interactions within E. coli. While the experimental work is being undertaken in the labs of Drs. Emili and Greenblatt, our lab is developing new methods to integrate different lines of evidence to predict functional interaction networks in E. coli as a prelude to applying these methods across different organisms. To host and display these results we have developed a dedicated web resource Bacteriome.org. Using results from both our labs functional predictions and those arising from experimental datasets, we are applying graph theoretic tools, network clustering algorithms and comparative genomics methods to define functional modules, extended interaction neighborhoods, and patterns of evolutionary variation. These studies will provide a deeper understanding of the molecular basis of evolutionary adaptation, including colonization of a human host, and identify novel drug targets.
Heirarchical analysis of predicted functional network in E. coli
The three images, generated from the Bacteriome web resource, show different levels of our predicted functional interaction network in E. coli. The first view details the entire functional network with nodes representing individual proteins (coloured by COG functional category). The middle graphic show functional modules predicted from this dataset. Each pie chart represents an individual module, with coloured sectors indicating the proportion of proteins in the module with particular functional categories). The graphic on the right shows the detailed interactions between individual proteins of a module selected from the previous graphic. The coloured sectors indicate the proportion of genomes associated with a variety of taxonomic groups which share significant sequence similarity with the protein in the network.
In addition to E. coli, we recently exploited the PartiGeneDB datasets to analyse the topology and conservation of a global network of yeast protein interactions, the largest study of high quality interaction data performed to date. We are continuing on from these initial evolutionary analyses of the yeast PPI network and are examining global and local properties of the network with evolutionary metrics. Such analyses are expected reveal evolutionary insights into major biological activities, for example clusters of nodes within the network, specific to the higher fungi may reflect specialized functional modules involved in e.g. the development of fruiting bodies.
