Modelling lipid metabolism in plants: a slippery problem?

Working with Randy: The Diacylglycerol Acyltransferase Story

Vegetable oils are one of the main agricultural commodities. Demand has been increasing steadily over the last five decades and, with finite land available, it is vital that we increase productivity. My laboratory has focused on the regulation of plant lipid metabolism and, as part of this work, we identified diacylglycerol acyltransferase (DGAT) as important at regulating carbon flux during oil accumulation. This led to collaborations with Randy Weselake's research group when we quantified the importance of DGAT in oilseed rape by using flux control analysis. Later, with David Taylor, we showed that over-expression of DGAT boosted oil accumulation in field-grown crops by around 8%. These studies led to a multitude of experiments with different oil crops, such as oil palm and soybean, as well as many rewarding collaborations with Randy.

Mathematical modeling of plant metabolic pathways

The understanding of the control of metabolic flux in plants requires integrated mathematical formulations of gene and protein expression, enzyme kinetics, and developmental biology. Plants have a large number of metabolically active compartments, and non-steady-state conditions are frequently encountered. Consequently steady-state metabolic flux balance and isotopic flux balance modeling approaches have limited utility in probing plant metabolic systems. Transient isotopic flux analysis and kinetic modeling are powerful proven techniques for the quantification of metabolic fluxes in compartmentalized, dynamic metabolic systems. These tools are now widely used to address metabolic flux responses to environmental and genetic perturbations in plant metabolism. Continued developments in isotopic and kinetic modeling, quantifying metabolite exchange between compartments, and transcriptional and posttranscriptional regulatory mechanisms governing enzyme level and activity will enable simulation of large sections of plant metabolism under non-steady-state conditions. Metabolic control analysis will continue to make substantial contributions to the understanding of quantitative distribution of control of flux. From the synergy between mathematical models and experiments, creative methods for controlling the distribution of flux by genetic or environmental means will be discovered and rationally implemented.