Background: There have been many successful strategies to implement xylose metabolism in Saccharomyces cerevisiae, but no effort has so far enabled xylose utilization at rates comparable to that of glucose (the preferred sugar of this yeast). Many studies have pointed towards the engineered yeast not sensing that xylose is a fermentable carbon source despite growing and fermenting on it, which is paradoxical. We have previously used fluorescent biosensor strains to in vivo monitor the sugar signalome in yeast engineered with xylose reductase and xylitol dehydrogenase (XR/XDH) and have established that S. cerevisiae senses high concentrations of xylose with the same signal as low concentration of glucose, which may explain the poor utilization.
Results: In the present study, we evaluated the effects of three deletions (ira2∆, isu1∆ and hog1∆) that have recently been shown to display epistatic effects on a xylose isomerase (XI) strain. Through aerobic and anaerobic characterization, we showed that the proposed effects in XI strains were for the most part also applicable in the XR/XDH background. The ira2∆isu1∆ double deletion led to strains with the highest specific xylose consumption- and ethanol production rates but also the lowest biomass titre. The signalling response revealed that ira2∆isu1∆ changed the low glucose-signal in the background strain to a simultaneous signalling of high and low glucose, suggesting that engineering of the signalome can improve xylose utilization.
Conclusions: The study was able to correlate the previously proposed beneficial effects of ira2∆, isu1∆ and hog1∆ on S. cerevisiae xylose uptake, with a change in the sugar signalome. This is in line with our previous hypothesis that the key to resolve the xylose paradox lies in the sugar sensing and signalling networks. These results indicate that the future engineering targets for improved xylose utilization should probably be sought not in the metabolic networks, but in the signalling ones.
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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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