Network solutions for crop productivity

The metabolic network that transforms the nutrients acquired by growing plants into harvestable outputs (e.g. seeds, tubers) is large and complex. As a result, intuitive predictions about interventions that might improve crop productivity are often unsuccessful, particularly when the aim is to redirect the fluxes in central metabolism. Despite this, ambitious programmes are underway to transfer complex traits between species, with the aim of increasing photosynthetic efficiency (the C4 rice project), water use efficiency (the CAM BioDesign consortium) and nitrogen use efficiency (engineering nitrogen fixation into cereals). A striking feature of these exciting projects is their empirical basis, and the belief that novel phenotypes will emerge that will provide the platform for successive rounds of intervention to reach the desired objective. Another feature of these projects is their very limited use of modelling techniques, even though the usefulness of such methods has been amply demonstrated in the re-engineering of micro-organisms. We believe that this is a mistake and that modelling could provide a new dimension for the rational improvement of crops. Accordingly, we are developing a systematic metabolic modelling approach to identify groups of candidate metabolic genes that could be targeted to improve crop productivity and nutrient use efficiency.

There are several ways to model metabolic networks, and constraints-based analysis, typically flux balance analysis (FBA), of genome-scale networks has emerged as a powerful method for probing the provision and utilisation of carbon skeletons, reducing power and energy in the complex compartmented networks of plant cells. Our recent work has extended the capabilities of FBA, demonstrating its effectiveness in predicting realistic flux distributions and generating new insights into cell maintenance (1), the relationship of CAM to conventional C3 photosynthesis (2), and the utilisation and disposal of energy in illuminated leaves (3). We are now using these methods in a project that has the objective of increasing fruit yield in tomato through multi-point manipulation of targets in source and sink tissues.

Two other areas are of immediate interest and would form the basis for a D.Phil. project. One is the trade-off between water use efficiency and carbon conversion efficiency in leaf metabolism, and the other is an analysis of the network-wide impact of introducing a C4 photosynthetic cycle into a C3 leaf. These investigations will take advantage of the novel diel (day-night) FBA framework that we have developed for constraints-based modelling of leaf metabolism and they will address questions that are of immediate agronomic relevance. In particular water use efficiency is an important target for plant breeders, and the conversion of C3 rice to C4 is being actively pursued by many researchers as a potential solution to the problem that world agriculture faces in meeting the anticipated demand for food by 2050.

STUDENT PROFILE

This project requires a strong background in biochemistry, including metabolism, an interest in metabolic analysis, and an aptitude for computational methods.