Background: Metabolic engineering enables the sustainable and cost-efficient production of complex chemicals. Efficient production of terpenes in Saccharomyces cerevisiae can be achieved by recruiting an intermediate of the mevalonate pathway. The present study aimed to evaluate the engineering strategies of S. cerevisiae for the production of taxadiene, a precursor of taxol, an antineoplastic drug.
Result: SCIGS22a, a previously engineered strain with modifications in the mevalonate pathway (MVA), was used as a background strain. This strain was engineered to enable a high flux towards farnesyl diphosphate (FPP) and the availability of NADPH. The strain MVA was generated from SCIGS22a by overexpressing all mevalonate pathway genes. Combining the background strains with 16 different episomal plasmids, which included the combination of 4 genes: tHMGR (3-hydroxy-3-methylglutaryl-CoA reductase), ERG20 (farnesyl pyrophosphate synthase), GGPPS (geranyl diphosphate synthase) and TS (taxadiene synthase) resulted in the highest taxadiene production in S. cerevisiae of 528 mg/L.
Conclusion: Our study highlights the critical role of pathway balance in metabolic engineering, mainly when dealing with toxic molecules like taxadiene. We achieved significant improvements in taxadiene production by employing a combinatorial approach and focusing on balancing the downstream and upstream pathways. These findings emphasize the importance of minor gene expression modification levels to achieve a well-balanced pathway, ultimately leading to enhanced taxadiene accumulation.
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Evidence ID | Analyze ID | Gene/Complex | Systematic Name/Complex Accession | Qualifier | Gene Ontology Term ID | Gene Ontology Term | Aspect | Annotation Extension | Evidence | Method | Source | Assigned On | Reference |
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Evidence ID | Analyze ID | Gene | Gene Systematic Name | Phenotype | Experiment Type | Experiment Type Category | Mutant Information | Strain Background | Chemical | Details | Reference |
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Evidence ID | Analyze ID | Gene | Gene Systematic Name | Disease Ontology Term | Disease Ontology Term ID | Qualifier | Evidence | Method | Source | Assigned On | Reference |
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Evidence ID | Analyze ID | Regulator | Regulator Systematic Name | Target | Target Systematic Name | Direction | Regulation of | Happens During | Regulator Type | Direction | Regulation Of | Happens During | Method | Evidence | Strain Background | Reference |
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Site | Modification | Modifier | Source | Reference |
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Evidence ID | Analyze ID | Interactor | Interactor Systematic Name | Interactor | Interactor Systematic Name | Allele | Assay | Annotation | Action | Phenotype | SGA score | P-value | Source | Reference | Note |
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Evidence ID | Analyze ID | Interactor | Interactor Systematic Name | Interactor | Interactor Systematic Name | Assay | Annotation | Action | Modification | Source | Reference | Note |
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Complement ID | Locus ID | Gene | Species | Gene ID | Strain background | Direction | Details | Source | Reference |
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Evidence ID | Analyze ID | Dataset | Description | Keywords | Number of Conditions | Reference |
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Evidence ID | Analyze ID | File | Description |
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