Genome-scale mathematical model of cannabis glandular trichome metabolism and identification of a missing link in terpenoid biosynthesis

Introduction Cannabis ( Cannabis sativa L.) glandular trichomes (GTs) are specialized structures on female inflorescences that serve as the primary sites for the biosynthesis and storage of metabolites responsible for potency and aroma, including cannabinoids, terpenoids, flavonoids, stilbenoids, phenolic amides, and volatile compounds. Despite substantial advances in cannabis biochemistry, uncertainties remain regarding key metabolic processes, including the biosynthetic origin of hexanoyl-CoA, the precursor supplying the cannabinoid side chain, and the formation of certain terpenoids such as 1,8-cineole. To address these knowledge gaps, we developed a genome-scale metabolic framework for cannabis GT metabolism. Methods An extensive literature review was used to reconstruct a cannabis GT metabolic network comprising approximately 772 metabolic and transport reactions. Comprehensive metabolite datasets encompassing cannabinoids, terpenoids, flavonoids, stilbenoids, phenolic amides, and non-terpenoid volatiles were integrated to parameterize the biomass objective function of the genome-scale metabolic model, CanSatGT_2025. Flux balance analysis was employed to evaluate competing hypotheses for hexanoyl-CoA biosynthesis, including: (i) early termination of fatty acid elongation, (ii) production through the oxylipin pathway following lipid degradation, and (iii) incomplete fatty acid β-oxidation. In addition, the hypothesis that ribulose bisphosphate carboxylase/oxygenase (RubisCO) is nonfunctional in non-photosynthetic GTs was assessed. To investigate the biosynthesis of 1,8-cineole, sequence and structural homology analyses were performed to identify candidate terpene synthases, followed by heterologous expression and biochemical characterization of selected enzymes. Results The reconstructed network enabled the development of the genome-scale model CanSatGT_2025 and its application to metabolic flux analysis across multiple cannabis cultivars. Flux balance analysis identified the most parsimonious solution as a combination of acyl-lipid thioesterase activity and a nonfunctional RubisCO. This configuration minimized total metabolic flux, ATP demand, and carbon dioxide loss while supporting GT metabolism. The analyses also revealed a gap in current knowledge of cannabis monoterpene biosynthesis. Although 1,8-cineole was detected in several cultivars, the enzyme responsible for its formation had not previously been identified. Subsequent sequence, structural, and biochemical studies led to the identification and validation of a terpene synthase that produces 1,8-cineole as its primary product. Discussion Our findings support acyl-lipid thioesterase-mediated hexanoyl-CoA production and the absence of functional RubisCO activity as the most metabolically efficient explanation for cannabinoid precursor biosynthesis in cannabis GTs. Furthermore, the discovery of a 1,8-cineole synthase resolves a previously unidentified step in cannabis monoterpene metabolism. Together, these results establish CanSatGT_2025 as a systems-level framework for investigating metabolic fluxes, elucidating biosynthetic pathways, and guiding future metabolic engineering and functional genomics efforts in cannabis glandular trichomes.