Figuring out genetic functional systems in Prokaryotes through computational genomics and metagenomics

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The proposed research program is concerned to two problems: (1) Since prokaryotic genomes within a species show high variability in gene content, and since such gene differences can make the difference between a harmless bacterial strain and a pathogenic one, we aim at understanding how different gene sets incorporate into the functional network of their host genome. To this end, we will examine high-quality computationally predicted associations by comparing against knowledge databases and literature, and by finding patterns revealing points of insertion into functional networks. We will concentrate on the role of transcription factors in the integration of genomic islands to their hosts. (2) Since we have developed powerful computational tools for predicting functional interactions in prokaryotic genomes, and there is an increasing abundance of semi-finished genomes, and metagenomic sequences, we aim at expanding these tools towards predicting such interactions with the same quality in any sequences, as when using complete genomes. These predictions will associate unknown genes to well understood functions and provide hints for their later characterization in the laboratory. The proposed work will benefit Canada and the world by providing instruments for finding different versions of gene modules attaining similar functions, from pathogenicity to functions of interest to industry such as cellulose degradation. Such information might help finding new ways for combating disease, or point to novel genes for biotechnological applications.