Hibberd Lab

Dr Ivan Reyna-Llorens

My research involves using synthetic biology and evolution for improving agricultural traits, more specifically to improve photosynthesis. As the world population continues to expand, it is predicted that crop yields will have to increase by 50% over the next 35 years. Traditional breeding programs cannot keep pace with this current population growth rate. Plant biomass is produced by carbon dioxide (CO2) fixed by the enzyme Rubisco during photosynthesis.

This process known as C3 photosynthesis can be very inefficient as Rubisco also interacts with Oxygen (O2) in a wasteful process known as photorespiration. In order to increase yields, photorespiration should be reduced considerably. Fortunately, some plants have evolved such mechanism already. C4 photosynthesis results from a series of anatomical and biochemical modifications in the leaf that lead to photosynthesis being compartmentalized between mesophyll and bundle sheath cells. This division of labour generates a CO2 enriched environment where photorespiration is effectively abolished. C4 plants therefore produce more yield and use water and nitrogen more efficiently. The fact that C4 photosynthesis has evolved independently in more than 60 lineages allows us to think it is possible to engineer C4 photosynthesis in C3 plants. In order to engineer this trait, cell specific genetic circuits need to be developed. Unfortunately there is a limited number of genetic parts driving cell specificity in leaves. My main objective in OpenPlant is to generate a library of leaf specific motifs that can be used to drive the expression of both nuclear and plastid encoded genes in specific compartments and specific cells of leaves.

Together with colleagues in the Department of Plant Sciences, Department of Chemistry and the Depart­ment of Physics I am part of an OpenPlant fund project that aims to use microfluidics for high-throughput analysis of genetic parts. We hope to generate a whole toolbox of parts that are useful to rewire different traits.