Metabolic engineering of deinococcus radiodurans based on computational analysis and functional genomics

The objective of our work is to develop novel computational tools to analyze the Deinococcus radiodurans DNA repair pathways and the influence of the metabolic flux distribution on DNA repair. These tools will be applied to provide insights for metabolic engineering of strains capable of growing under nutrient poor conditions similar to those found in mixed contaminant sites of interest to the DOE. Over the entire grant period we accomplished all our specific aims and were also able to pursue new directions of research. Below, I will list the major accomplishments over the previous 3 years. (1) Performed Monte Carlo Simulations of RecA Mediated Pairing of Homologous DNA Molecules. (2) Developed a statistical approach to study the gene expression data from D. radiodurans. We have been studying the data from John Batista's. (3) Developed an expression profiling technology to generate very accurate and precise expression data. We followed up on results from John Batista's group using this approach. (4) Developed and put online a database for metabolic reconstructions. (5) We have developed and applied new Monte Carlo algorithms that are optimized for studying biological systems. (6) We developed a flux balance model for the D. radiodurans metabolic networ