Metabolic engineering to enhance photosynthesis based on empirical data and in silico modelling

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World demand for food is growing and it has been estimated that a 50% increase in yield will be needed to meet the increasing demand due to growing population. The changing climate and the competing demand for plants as biofuels further exacerbates this situation. Photosynthesis is the process by which plants use the energy from the sun to convert carbon dioxide from the atmosphere into carbohydrates and other chemical compounds, which are used for growth. Over the last decade numerous experiments of plants grown in elevated CO2 have shown unambiguously that increased rates of photosynthetic carbon assimilation can lead to increased biomass. Furthermore transgenic experiments conducted during the 1990's in which activities of individual enzymes were up- or down- regulated provided information showing that manipulation of the Calvin cycle could influence plant composition and increase plant productivity. These studies clearly identified photosynthetic carbon assimilation as an untapped opportunity to increase yield. In this project we will produce transgenic Arabidopsis plants with altered photosynthetic characteristics based on a combination of empirical data, metabolic and network modeling. A detailed physiological and molecular analysis of the resulting lines will carried out to obtain detailed measurements of photosynthetic parameters and growth in greenhouse grown plants. The transgenic plants generated in this programme with altered photosynthetic carbon metabolism will be used to explore the relationships between CO2 assimilation, carbon storage and plant growth. These analyses will provide data for further interrogation and improvement of these models. This research will also provide a proof of concept and will form the basis to enable informed manipulation of crop plants.