Synthetic biology and metabolic engineering experiments frequently require the fine-tuning of gene expression to balance and optimize protein levels of regulators or metabolic enzymes. A key concept of synthetic biology is the development of modular parts that can be used in different contexts. Here, we have applied a computational multifactor design approach to generate de novo synthetic core promoters and 5' untranslated regions (UTRs) for yeast cells. In contrast to upstream cis-regulatory modules (CRMs), core promoters are typically not subject to specific regulation, making them ideal engineering targets for gene expression fine-tuning. 112 synthetic core promoter sequences were designed on the basis of the sequence/function relationship of natural core promoters, nucleosome occupancy and the presence of short motifs. The synthetic core promoters were fused to the Pichia pastoris AOX1 CRM, and the resulting activity spanned more than a 200-fold range (0.3% to 70.6% of the wild type AOX1 level). The top-ten synthetic core promoters with highest activity were fused to six additional CRMs (three in P. pastoris and three in Saccharomyces cerevisiae). Inducible CRM constructs showed significantly higher activity than constitutive CRMs, reaching up to 176% of natural core promoters. Comparing the activity of the same synthetic core promoters fused to different CRMs revealed high correlations only for CRMs within the same organism. These data suggest that modularity is maintained to some extent but only within the same organism. Due to the conserved role of eukaryotic core promoters, this rational design concept may be transferred to other organisms as a generic engineering tool.
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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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