Professor Lee Sweetlove

Research Interests

Rational engineering of plant metabolic networks.

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 leaf metabolic network needs to be modified to accommodate more efficient photosynthetic modes such as C4 photosynthesis and CAM. We are also starting the process of integrating these metabolic models into whole-plant modelling frameworks.

Experimental: The experimental strand aims to implement the predicted metabolic engineering strategies from the computational strand. We are using biolistic co-transformation to systematically explore combinatorial transgenic interventions in leaf metabolism. We are currently using tobacco as a model species, but are also looking to develop the liverwort, Marchantia polymorpha, as a rapid testbed for synthetic biology approaches to improving the efficiency of the core metabolic network of plants. Finally, we are also collaborating with Mark Howarth, Department of Biochemistry, University of Oxford, to explore the potential of ‘molecular superglues’ as a mechanism for greater control over introduced metabolic pathways.

I am currently seeking DPhil students to work on:

  • Computational modelling of crop metabolic networks for enhanced productivity
  • Multi-gene metabolic engineering of plant metabolism
  • Marchantia polymorpha as a testbed for metabolic engineering
  • Engineering of synthetic enzyme assemblies using molecular superglues
  • Alternative CAM Modes Provide Environment-Specific Water-Saving Benefits in a Leaf Metabolic Model.

  • Flux balance analysis of metabolism during growth by osmotic cell expansion and its application to tomato fruits.

  • Multiple Metabolic Innovations and Losses Are Associated with Major Transitions in Land Plant Evolution.

  • Multiple metabolic innovations and losses are associated with major transitions in land plant evolution

  • Multiple metabolic innovations and losses are associated with major transitions in land plant evolution

  • Leaf Energy Balance Requires Mitochondrial Respiration and Export of Chloroplast NADPH in the Light.

  • Computational analysis of the productivity potential of CAM.

  • Protein-protein interactions and metabolite channelling in the plant tricarboxylic acid cycle.

  • More
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