Biology Department Seminar

Improving the yield and efficiency of plants is an urgent goal of research, but it is difficult to understand the functioning and regulation of these complex traits by studying individual genes and phenotypes. Mathematical models are particularly useful in addressing multifactorial characteristics because they embody the interactions of multiple system components and can predict the quantitative effect of changing these components. Here, I describe my work on integrating experimental data with models of nutrient fluxes in plant systems operating at three different biological scales. First, we analyzed carbon-for-nitrogen exchange in the legume-rhizobia mutualism using a trade-based approach. We found that classical symmetric interactions cannot explain the observed nutrient exchange rates and ratios. Rather, the plant has more influence on these nutrient exchange parameters than the rhizobia and this rises as soil nitrogen becomes more scarce. This finding highlights the importance of environmental conditions for the functioning and evolution of mutualisms. Second, we used isotopic labeling based Metabolic Flux Analysis to determine the routes and rates of fluxes through central metabolism in developing seed embryos of Camelina sativa—a promising oil seed crop. Our goal was to understand why they have low carbon use efficiency. By identifying decarboxylation reactions with abnormally high fluxes, we have identified strategies for bioengineering these plants to increase their yield. Lastly, I describe our recent progress towards elucidating the network structure of triacylglycerol synthesis in Camelina embryos. By integrating isotopic labeling time-course data with first-order reaction kinetics, we can predict the number and arrangement of active precursor pools in this metabolic pathway. Together, these endeavors demonstrate how models can be integrated with a broad range of data to address questions at ecological, organismal, and different metabolic scales.