A comprehensive pipeline for biosynthetic pathway identification and functional elucidation of plant terpenoids. (IMAGE)
Caption
(a) Pharmaceutical components accumulated in specific organs of medicinal plants (indicated with red circles). (b) Biosynthetic pathways of terpenoids start with the DMAPP/IPP from MVA and MEP pathways; the core cyclic skeletons are produced from prenyl diphosphates with varying five-carbon-atom (C5) units through cyclization by TPSs followed by oxidation catalyzed by cytochrome P450 monooxygenases (CYP450s), and further tailoring reactions drive the complexity of terpenoids to produce the targeted compounds. (c) Schematic diagram outlining a generalized strategy for elucidating the biosynthetic pathways of targeted terpenes in medicinal plants. (i) Classic analyses typically use metabolomics, genomics, and transcriptomics (even single-cell level omics are considered). The microbiome can aid in the discovery of novel genomic resources for identifying variations in terpenoids. (ii) The identification of biosynthesis-related gene clusters (BGCs) is currently a key method used for the validation of genes encoding enzymes involved in specialized terpenoid pathways. Genome and metabolome mining use nonmachine learning methods such as correlation and regression (for example, linking metabolomic and transcriptomics data) and deep learning, among other methods. (iii) Nicotiana benthamiana and yeast are useful platforms for the reconstitution of terpene pathways. Synthetic biology approaches are transforming field production to the generation of gene circuits for the stable expression of complex specialized terpenes in cell factories for pharmaceutical, biocontrol and ecological purposes. The blue arrows indicate well-established pathways of terpene biosynthesis; the red arrows indicate cutting-edge research focusing on the steps of terpene biosynthesis. Api: apiose; Glc: glucose; Rha: rhamnose; Xyl: xylose; AI: artificial intelligence; IDI: isopentenyl diphosphate isomerase; APT: aromatic prenyltransferase; UGT: UDP-dependent glycosyltransferase; AT: acyltransferase; PT: prenyltransferase; t-SNE: t-distributed stochastic neighbor embedding. The figure was created using Adobe Illustrator and BioRender.com.
Credit
Xiaochen Wang, Guodong Wang
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