The plant cuticle a lipid-derived extracellular barrier composed primarily of cutin and waxes is essential for mitigating abiotic stress, yet its biosynthetic regulation and metabolic integration remain poorly characterized. This gap limits rational strategies to engineer stress-resilient crops through synthetic cuticle enhancement. Here, we extend our genome-scale Arabidopsis root metabolic model, AraRoot, to incorporate the cuticle biosynthetic pathway, enabling in-silico analysis of ectopic cuticle production in tissues that naturally lack this barrier. Dynamic flux balance analysis coupled with shadow price evaluation revealed substantial reductions in proline and glutamine availability metabolites critical for abiotic stress response thereby exposing trade-offs between cuticle induction and nitrogen assimilation pathways. To experimentally probe this network reprogramming, we ectopically express maize-derived cuticle-associated transcription factors (ZmTFs) in Arabidopsis roots. Differential gene expression analysis between ZmTF-expressing and wild-type roots, followed by co-expression network construction via Pearson correlation, identify candidate regulatory nodes. These targets are interrogated using a mixed-integer linear programming (MILP) framework to infer plausible transcriptional circuits connecting ZmTFs to downstream biosynthetic control points. Through this integrative systems approach, we elucidate the regulatory logic and metabolic constraints governing cuticle assembly. Long-term, this work supports the development of synthetic regulatory modules and predictive metabolic models to fine-tune cuticle production under dynamic environmental conditions. Future efforts will incorporate drought and UV-induced expression datasets and expand multi-omics integration to enhance model granularity and accuracy. Ultimately, this research provides a quantitative framework for engineering plant bioproduct traits that improve environmental stress tolerance advancing the design of sustainable, climate-resilient crops through synthetic biology and metabolic engineering.
