Efficiently rewiring microbial metabolism for molecule production lies at the core of industrial metabolic engineering. Combinatorial libraries are useful for directing metabolism towards molecule production; however, their construction is labor-intensive, and their use in iterative strain engineering campaigns is often restricted by site-specific genomic integration. Here we present an automation-friendly framework for generating reusable and modular integration-based combinatorial libraries that can be used repeatedly to build high-performing strains. We apply this approach to engineer the production of betacyanins, a commonly used red food colorant extracted from beetroots, in Saccharomyces cerevisiae. Iterative implementation of combinatorial libraries targeting the betacyanin biosynthesis pathway (design space: ∼25,000), precursors (design space: ∼43,000), and cofactors (design space: ∼26,000) consistently improved pigment production by 1.2-5.7-fold per cycle over seven rounds of engineering. Sequencing of high-performing library isolates from each round revealed unique insights into betacyanin and yeast metabolism, e.g. we found strong evidence implicating the S. cerevisiae cytochrome b5 in heterologous red beet pigment production. Altogether, this study demonstrates a framework for combinatorial library engineering well-suited for accelerating the development of high-performing cell factories for industrial fermentation processes.
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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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