Modelling Cocoa-Phytophthora megakarya metabolic interaction to weaken Plant-Pathogen compatible relationship

Cocoa (Theobroma cacao L.) is an important cash crop in West and Central Africa; however, it is constantly under threat from various pests and diseases, including Phytophthora megakarya, a soil-borne oomycete that causes black pod disease. Phytophthora megakarya poses a major threat to farmers' livelihood and economic growth of producing countries, and although various control measures have been implemented, sustained success has been limited. Emergence of resistant cultivars would be a significant step towards effective control of the disease, and a strategy for achieving this goal is by understanding the metabolic interaction between the plant and the pathogen. To date, the metabolic interactions between the host and the pathogen during infection have hardly been studied and their interlinked metabolism remains poorly understood. However, gaining a quantitative understanding of nutrient exchanges in the host-pathogen system will be the prerequisite for suggesting intervention strategies for improved pathogen resistance. In this study, we developed a fully compartmentalized Genome-Scale Metabolic Model (GEM) for P. megakarya. Then, we simulated the metabolic fluxes at the host-pathogen interface by integrating genomic data and known physiological requirements such as sterol auxotrophy and specific amino acid dependencies, Our preliminary results provide insight into the metabolic processes driving the host-pathogen interaction and reveal key potential targets for disrupting this interaction. This system biology approach aims to guide metabolic engineering and precision breeding and ultimately leads to support sustainable agricultural development strategies for cocoa resilience.