Microbial ethanol production is an important alternative energy resource to replace fossil fuels, but at high level, this product is highly toxic, which hampers its efficient production. Towards increasing ethanol-tolerance of Saccharomyces cerevisiae, the so far best industrial ethanol-producer, we evaluated an in vivo evolutionary engineering strategy based on batch selection under both constant (5%, v v-1) and gradually increasing (5-11.4%, v v-1) ethanol concentrations. Selection under increasing ethanol levels yielded evolved clones that could tolerate up to 12% (v v-1) ethanol and had cross-resistance to other stresses. Quite surprisingly, diploidization of the yeast population took place already at 7% (v v-1) ethanol level during evolutionary engineering, and this event was abolished by the loss of MKT1, a gene previously identified as being implicated in ethanol tolerance (Swinnen et al., Genome Res., 22, 975-984, 2012). Transcriptomic analysis confirmed diploidization of the evolved clones with strong down-regulation in mating process, and in several haploid-specific genes. We selected two clones exhibiting the highest viability on 12% ethanol, and found productivity and titer of ethanol significantly higher than those of the reference strain under aerated fed-batch cultivation conditions. This higher fermentation performance could be related with a higher abundance of glycolytic and ribosomal proteins and with a relatively lower respiratory capacity of the evolved strain, as revealed by a comparative transcriptomic and proteomic analysis between the evolved and the reference strains. Altogether, these results emphasize the efficiency of the in vivo evolutionary engineering strategy for improving ethanol tolerance, and the link between ethanol tolerance and diploidization.
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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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