(58g) Using Dynamic Metabolic Modeling to Predict the Transcriptional Regulation of Cuticle Biosynthesis.

Plant cuticles protect the aerial parts of plants by providing a hydrophobic barrier that prevents excess stomatal water loss and limits pathogen invasion and the penetration of chemicals. The cuticle consists of the cutin polymer, intracuticular waxes embedded in the cutin, and epicuticular waxes that cover the outmost surface of the plant. Despite multiple efforts, it is still unclear how the individual components of a cuticle integrate to act cohesively and form such a robust barrier. This study hypothesizes that cuticle composition is controlled and coordinated by a network of transcription factors (TFs). This is tested by ectopically expressing maize cuticle TFs (ZmTFs) in the root epidermal cells of Arabidopsis thaliana, which does not normally produce a cuticle (Schroeder and Saha, 2020). Experimentally activating cuticle modules in a synthetic root chassis allows the identification of transcriptional regulators of specific cuticle modules and gives insight into the downstream metabolic effect of ZmTF activation on cuticle composition. The data collected includes root biomass, metabolite concentrations, and the temporal expression measurement of ZmTFs and cuticle checkpoint genes which is used to develop a dynamic metabolic modeling framework that is able to predict cuticle composition outcomes from different ZmTF pairs. The dynamic modeling framework uses a comprehensive genome-scale model of the Arabidopsis root as a blueprint, which contains genes, proteins, and reactions of the cuticle. Next, we perform dynamic Flux Balance Analysis (dFBA) on the initial root model to simulate the temporal metabolic changes that result from different ZmTF pairs. The resulting predictions of which will be tested experimentally by focusing on the ZmTF pairs that are predicted to be complementary. Each pair will be analyzed in the role of activating cutin monomer and cutin transport modules, the elongation module, and either the decarbonylative or the reductive modules. This in turn will identify the ZmTF combinations that uniquely generate diverse cuticle compositions and will also be used to further refine the dynamic metabolic model. Overall, these outcomes of the study will aid in building the synthetic platform that aims to better understand the biomolecular control of cuticle assembly, thus providing further insight into how plant cuticles could be altered to provide even better protection to the plant.

References:

National Science Foundation, (2022), Collaborative Research: PlantSynBio: Deciphering the roles of genetic and biochemical redundancy and pathway regulation via refactoring the protective plant cuticle. Available at: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2212799&HistoricalAward... (Accessed: 03 April 2023).

Schroeder, W.L. and Saha, R., (2020), Introducing an optimization-and explicit Runge-Kutta-based approach to perform dynamic flux balance analysis. Scientific reports, 10(1), p.9241.