Programmable saponin biosynthesis from gene networks to predictive biomanufacturing

Saponins are a structurally diverse plant glycosides with important ecological functions and broad pharmaceutical and industrial value. Recent advances have shifted saponin research from descriptive pathway elucidation toward predictive and programmable biomanufacturing. High-quality genome assemblies, integrated multi-omics profiling, and metabolic gene cluster analyses have clarified the enzymatic logic and regulatory architecture underlying saponin biosynthesis and structural diversification, enabling quantitative modeling of pathway flux and identification of key regulatory bottlenecks. Building on these foundations, synthetic biology tools, including CRISPR-based transcriptional modulation, synthetic promoters, and transcription factor rewiring, allow precise and programmable control of biosynthetic networks. In parallel, structure-guided enzyme engineering and AI-assisted protein design accelerate the optimization of cytochrome P450s and glycosyltransferases, improving catalytic efficiency and pathway robustness. These strategies are implemented across multiple production platforms, including engineered microbes, plant suspension cells, hairy roots, and adventitious root systems, enabling iterative optimization through Design-Build-Tes-Learn-cycles. Together, this review synthesizes recent conceptual and technological advances, positioning saponins as a model system that bridges gene networks, regulatory logic, and industrial biomanufacturing, and highlighting a generalizable framework for predictive design and scalable production of complex plant natural products.