Wednesday, May 2, 2012: 8:30 AM
Rhythms Ballroom, 2nd fl (Sheraton New Orleans)
The need for alternative renewable sources of energy has driven research investments and efforts toward developing clean and efficient processes. Among bio-based strategies, the use of oxygenic photosynthesis in cyanobacteria receives great interest, since biofuels can be made directly from CO2, water, and sunlight. Cyanobacteria possess a complex electron transport chain (ETC), in which partitioning between reductant and energy production affects cellular growth and biofuel production. We evaluated the complexity of cyanobacterial ETC and its impact on growth and product formation by developing a genome-scale model for the diazotrophic cyanobacterium, Cyanothece sp. ATCC 51142. The resulting metabolic reconstruction, iCce806, consists of 806 genes associated with 667 metabolic reactions and includes a detailed representation of the ETC. The model was able to predict growth rates that were close to those observed in batch cultures using different light intensities. Cells were grown in a custom-built photobioreactor, which allows quantification of light consumption rates, and the biomass composition, mRNA and protein expression were measured under two light- and ammonia-limited chemostat conditions. We then constrained the model based the experimental measurements and evaluated which pathways are predicted to be used under these conditions. We also examined how the presence and absence of ETC components (e.g., cytochrome oxidases) affects the production of various products. The resulting model can be used with a growing number of computational approaches to design metabolic engineering strategies for improving biofuel production in Cyanothece.