Lee Sweetlove

Research Area

Rational engineering of plant metabolic networks.

Research Description

The growth of plants is underpinned by, and in many cases limited by, the capacity of their metabolic systems. In green tissues, the process of photosynthesis transduces light energy into chemical energy to power the assimilation of carbon and nitrogen from the environment, the biosynthesis and maintenance of cellular components and export of sugars and amino acids to support the growth of the rest of plant. There is renewed interest in these metabolic processes due to concerns about the productivity of the global agricultural system in relation to an ever-increasing demand for food.

The research in my lab aims to develop a better understanding of the behaviour of the metabolic systems of plants in order to devise metabolic engineering strategies that will improve the productivity and quality of crop plants. We use both computational and experimental approaches to achieve this.

Computational: we construct and analyse flux-balance models of large-scale (up to genome-scale) plant metabolic networks. We have spent the last few years refining the approach such that we are confident that these minimally-constrained models provide a realistic simulation of plant metabolism in leaves and non-photosynthetic tissues. The goal now is to exploit these models to design more efficient metabolic systems. We are particularly interested in using this approach to predict how the rice metabolic network needs to be modified to accommodate more efficient photosynthetic modes such as C4 photosynthesis and CAM.

Experimental: we are seeking to better understand and exploit two phenomena for metabolic engineering. The first is metabolite signalling which the plant uses to monitor its internal metabolic status. Many such signalling pathways are used as feedback loops which, if were removed, would release the brakes on anabolic metabolism and growth. We are characterising two metabolite signalling pathways: amino acid signalling (for N assimilation) and mitochondrial redox stress signalling (for stress metabolism) and are creating synthetic metabolite-responsive gene switches and sensors. The second phenomenon is metabolite channelling – the direct passage of metabolites between sequential enzymes in metabolic pathways. We have discovered that key pathways in plants can be dynamically assembled into systems in which metabolite channelling occurs and we are trying to understand the nature of these assemblies. This knowledge would be massively important for synthetic biology because it would allow the assembly of highly efficient metabolic modules that have minimal impact with the metabolism of the host organism.

All of these research programmes are funnelled into applied metabolic engineering. Currently I lead a multinational consortium project attempting to make wholesale genetic changes of both source and sink metabolism in tomato with the goal of dramatically increasing fruit yield.

I am currently seeking DPhil students to work on:

computational modelling of crop metabolic networks for enhanced productivity
dissection of metabolite signalling pathways
the metabolic cost of abiotic stress