Abstract
Understanding plant response to environmental factors such as temperature, drought, diseases, and carbon-to-nitrogen (C:N) ratio is essential for crop resilience, quality, and adaptation to climate change. Here, we present iCitrus2616, a high-resolution organ-specific genome-scale metabolic model for Citrus clementina, comprising 2,616 genes, 8,653 metabolites, and 10,654 reactions. The model integrates organ-specific metabolomics data, i.e., leaf, stem, and root, and predicts plant responses to different conditions with high accuracy. Lower C:N ratios showed higher growth rates compared to higher C:N ratios, suggesting an inverse relationship between growth and C:N ratios. Simulations show that polymers such as starch and hemicellulose increased 4-fold under mixotrophic compared to phototrophic conditions, contributing to enhanced rigidity of cell walls, thus improving mechanical and drought stress. Furthermore, iCitrus2616 revealed higher production of specialized metabolites such as flavonoids in the presence of specific nutrients. Additionally, transcriptomics data from symptomatic and asymptomatic leaf and root tissues across four seasons (winter, spring, fall, and summer) during Huanglongbing infection (citrus greening) were integrated into the model. This integration revealed tissue-specific metabolic adaptations, including shifts in energy allocation, secondary metabolite production, and stress-response pathways under biotic stress. These findings underscore the utility of iCitrus2616 in elucidating the metabolic underpinnings of biotic and abiotic stress resilience and could aid in improving crop productivity and quality, thereby meeting escalating market demands.