β-Carotene is a high-value compound with multiple commercial applications as a pigment and due to its antioxidant properties. For its industrial production, precision fermentation using engineered microorganisms has been proposed as an attractive alternative given consumer concerns and technical limitations of traditional production methods such as chemical synthesis and extraction from plants. However, the factors limiting microbial production are complex and remain poorly understood, hindering bioprocess scale-up. To tackle this limitation, we built and evaluated kinetic model ensembles of the native mevalonate and the heterologous β-carotene production pathways in recombinant Saccharomyces cerevisiae strains to identify bottlenecks limiting the production flux. For this task, flux and transcriptomic data from chemostat cultivations were generated and combined with literature information for simulating model structures capturing different degrees of kinetic detail and complexity within the ABC-GRASP framework. Our results showed that detailed kinetic models including both allosteric regulation and complex mechanistic descriptions (e.g., enzyme promiscuity) are necessary to explain the metabolic phenotype of recombinant strains in different conditions. Calculation of flux and concentration response coefficients of the detailed models revealed that the promiscuous CrtYB enzyme exerts the highest control over β-carotene production at different growth rates in the best producer. Simulation of various enzyme and metabolite perturbations confirmed the above result and discarded other seemingly intuitive targets for intervention, e.g., upregulation of ERG10. Overall, this work deepens our understanding about the factors limiting β-carotene production in yeast, providing mechanistic models for in silico metabolic prospection and rational design of genetic interventions.
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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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