Mathematical Modeling-Guided Evaluation of Biochemical, Developmental, Environmental, and Genotypic Determinants of Essential Oil Composition and Yield in Peppermint Leaves

Abstract

ABSTRACT: We have previously reported the use of a combination of computational simulations and targeted experiments to build a first generation mathematical model of peppermint (Mentha × piperita) essential oil biosynthesis. Here, we report on the expansion of this approach to identify the key factors controlling monoterpenoid essential oil biosynthesis under adverse environmental conditions. We also investigated determinants of essential oil biosynthesis in transgenic peppermint lines with modulated essential oil profiles. A computational perturbation analysis, which was implemented to identify the variables that exert prominent control over the outputs of the model, indicated that the essential oil composition should be highly dependent on certain biosynthetic enzyme concentrations [(+)-pulegone reductase and (+)-menthofuran synthase], whereas oil yield should be particularly sensitive to the density and/or distribution of leaf glandular trichomes, the specialized anatomical structures responsible for the synthesis and storage of essential oils. A microscopic evaluation of leaf surfaces demonstrated that the final mature size of glandular trichomes was the same across all experiments. However, as predicted by the perturbation analysis, differences in the size distribution and the total number of glandular trichomes strongly correlated with differences in monoterpenoid essential oil yield. Building on various experimental data sets, appropriate mathematical functions were selected to approximate the dynamics of glandular trichome distribution/density and enzyme concentrations in our kinetic model. Based on a χ 2 statistical analysis, simulated and measured essential oil profiles were in very good agreement, indicating that modeling is a valuable tool for guiding metabolic engineering efforts aimed at improving essential oil quality and quantity.