## 4 Production of Plant Secondary Metabolites Using Microbial Chassis
### Engineering Enzymes and Cofactors  
Once the biosynthetic pathway of plant secondary metabolites is elucidated, the genes encoding pathway enzymes can theoretically be introduced into microorganisms to produce these secondary metabolites. However, enzymes from the native host may have no activity or poor activity in microorganisms. Through genome and transcriptome mining, homologous enzymes or isoenzymes with potential catalytic activity can be identified and screened. For example, [PERSON] et al. [162] identified the most active limonene synthase from nine candidate enzymes obtained from the genera _Citrus_, _Solanum habrochaites_, and _Agastache rugosa_. [PERSON] et al. [159] discovered an enzyme with higher activity from _C. roseus_ through the screening of nine geraniol synthase genes from diverse species. Additionally, there is a wealth of metagenomic resources in unculturable environmental microorganisms that can be explored for genes encoding enzymes with potential activities [208]. After obtaining candidate pathway enzyme genes, combinatorial optimization can be used to find the optimal combination. For example, [PERSON] et al. [209] combined genes from _Staphylococcus aureus_, _Myxococcus xanthus_, _Clostridium beijerinclii_, and _E. coli_ to construct an isoprenoid alcohol pathway using a retrobiosynthetic approach to provide a high accumulation of precursors for downstream terpene synthesis. By expressing four biosynthetic enzymes from three different plants, [PERSON] [187] achieved 18.6 mg/L of genistein from p-coumaric acid in _E. coli_. For synthesizing lycopene, [PERSON] et al. [181] initially screened the activities of nine GGPP synthase, five CrtB, and seven CrtI enzymes from various hosts, followed by further screening of over thirty combinations. This process led to a significant increase in lycopene production, from 4.5 mg/L to 118 mg/L. However, this  
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\begin{tabular}{c} _S. combinatorial optimization approach often involves a considerable amount of trial-and-error efforts. Fortunately, gene mining aided by bioinformatics [210] and the convenience of component assembly in synthetic biology [211] can reduce the initial screening and vector construction work. If the enzymes discovered in microorganisms exhibit issues such as insufficient substrate specificity, known as substrate promiscuity, low activity, and poor stability, they can be modified using enzyme engineering techniques such as random mutagenesis, directed evolution, and computer-aided semi-rational design, to alter active pockets, replace amino acids in loop regions, or make other modifications. In yeast, ERG20 catalyzes the condensation of IPP and DMAPP into both GPP and FPP. [PERSON] et al. [212; 213] introduced mutations into ERG20 using rational design, changing it into sole GPP synthase or GGPP synthase. Sometimes, the activity and (or) stability of enzymes can also be improved by fusing them with tag proteins or other enzymes. For instance, terpene synthase and lavandulyl diphosphate synthase fused with maltose-binding protein exhibited improved stability [169]. In their study, it was also found that the fused enzymes showed higher activity compared to individual expression, which was mainly due to the closely located enzymes which allowed for a more efficient substrate transfer. [PERSON] et al. [172] found that GGPPS and taxadiene synthase exhibit different subcellular localization in yeast and that fusion expression increases taxadiene production by 54%. When expressing plant-derived enzymes in microorganisms, especially P450 enzymes, it is common to encounter reduced or lost activity. Approximately 40% of plant-derived P450 enzymes are expressed poorly in yeast [214]. Additionally, P450 enzymes typically require characteristic redox partners, such as cytochrome P450 reductase (CPR), to transfer electrons. However, microorganisms may lack a sufficient amount of CPR or the available CPR may not effectively couple with exogenous P450 enzymes.