Reducing atmospheric CO2 by optimizing the consumption from synthetic organismsView all posters
University of Catania, Italy
The atmospheric CO2 concentration has changed during the last 100 years more than in the past 25 million years. A natural antagonistic mechanism to the increasing CO2 concentration is the Calvin cycle of green plants in photosynthetic activity. Engineering this activity could be a way to contrast the increasing of CO2 concentration. We investigate two important metabolic networks: the Rhodobacter spheroides bacterium, and the Chlamydomonas reinhardtii alga. The first models all the most interesting features of photosynthesis, as well as the metabolic capabilities of this kind of organisms. During its photosynthetic growth, R. Sphaeroides uses CO2 as the sole carbon source. The autotrophic metabolism of R. Sphaeroides makes it a potential organism for sequestering atmospheric and industrial CO2. Conversely, the second allows the investigation of photosynthesis in algae. Increasing the ability of these organisms to consume CO2 can be very interesting. Therefore, we adopt a multi-objective optimization approach to maximize CO2 uptake rate and biomass formation in the genome-scale metabolic networks of R. Sphaeroides and C. Reinhardtii. We act both on a genetic level (finding optimal genetic manipulations) and on an input fluxes level (finding the optimal nutrients) in order to improve the CO2 consumption and biomass formation. For the genetic manipulations research, we consider the photoautotrophic conditions for both organisms, i.e. in a poor environment where the only carbon source is CO2. The results are Pareto optimal solutions. Pareto optimality analysis reveals extremely useful to compare different organisms and different strategies. We find that by using genetic strategies, we can obtain high level of CO2 consumption. For instance, R. Spheroides is able to absorb an amount of CO2 until 57.452 mmolh-1gDW-1 (+28.51%) with a biomass rate equal to 0.986 h-1, while C. Reinhardtii obtains a maximum of 6.733 (+6.73%) with a biomass formation equal to 0.138.