Molecular Lego in the Green Factory: Engineering Plant Metabolism with Golden Gate Assembly

Fuente: PubMed "medicinal and aromatic plants"
Methods Mol Biol. 2026;3054:105-121. doi: 10.1007/978-1-0716-5384-5_8.ABSTRACTPlant specialized metabolites encompass a diverse array of bioactive compounds with significant pharmaceutical, nutraceutical, and industrial relevance, and they play vital roles in plant defense, signaling, and ecological interactions. However, their complex biosynthetic pathways and low natural yields present a major bottleneck for commercial exploitation. Synthetic biology provides new tools for the rational design and engineering of metabolic pathways to enhance specialized metabolite biosynthesis in plants as well as in microbes such as E. coli and yeast. Here, we report a synthetic biology framework utilizing Golden Gate assembly (GGA) for the modular construction and optimization of plant metabolic pathways. Golden Gate enables scarless, directional assembly of multigene constructs with high efficiency, ideal for refactoring biosynthetic gene clusters and for the systematic design of complex metabolic networks. Golden Gate assembly can efficiently join up to 10-20 fragments simultaneously in a single reaction, a significant improvement over traditional molecular biology cloning methods. We developed and validated a standardized module of promoters, untranslated regions (UTRs), coding sequences, and regulatory elements compatible with plant transformation systems. Using this platform, we successfully reconstructed the biosynthetic pathway for plant specialized metabolites by transient expression in Nicotiana benthamiana, demonstrating significant improvements in construct stability. Our results highlight the potential of Golden Gate as a cornerstone technology for plant metabolic engineering, offering a scalable and versatile strategy to enhance the production of valuable specialized metabolites and set the stage for custom metabolic rewiring aimed at sustainable production of high-value compounds.PMID:42390748 | DOI:10.1007/978-1-0716-5384-5_8