Hildebrandt/Töpfer: Understanding storage protein metabolism during germination and seedling development in the high protein crop Lupinus albus through data-integrative metabolic modelling
This project will be co-supervised by Tatjana Hildebrandt and Nadine Töpfer at the University of Cologne
During germination and early seedling development plants rely on their seed storage compounds to provide them with energy and precursors for the synthesis of macromolecular structures. Lupin seeds use predominantly proteins as their storage compounds (up to 35% of the seed dry weight) and do not contain starch and are thus a valuable crop for human nutrition and animal feed. However, plant metabolism is primarily geared to using carbohydrates as substrates for mitochondrial ATP production and as starting materials for the synthesis of cell walls. During carbohydrate starvation, storage proteins are used as alternative respiratory substrates and they can also be converted to glucose for cellulose synthesis. These processes potentially liberate large quantities of toxic ammonium. It is not clear how the seeding metabolically integrates amino acid and nitrogen fluxes from storage proteins. To tackle this question, in this project the candidate will construct a time-resolved, large-scale metabolic model to analyze storage protein metabolism during germination and post-germinative seedling growth in Lupinus albus. The model will be parameterized with existing proteomics, metabolite profiling, and physiological parameters and analyzed using flux-balance approaches. Furthermore, the candidate will generate additional modelling relevant data and test model-based hypotheses. This approach will elucidate how the different metabolic processes are coordinated to meet the demands of the growing seedling. The gained knowledge will increase our understanding of metabolic adaptations required for using proteins as major seed storage compounds and will identify targets for breeding future crops with a beneficial seed protein composition.
Key publication: Moreira TB, Shaw R, Luo X, Ganguly O, Kim HS, Coelho LGF, Cheung CYM, Rhys Williams TC. A Genome-Scale Metabolic Model of Soybean (Glycine max) Highlights Metabolic Fluxes in Seedlings. Plant Physiol. 2019 Aug;180(4):1912-1929. doi: https://doi.org/10.1104/pp.19.00122