Bioconversion of lignocellulosic biomass to biofuels such as bioethanol and high value-added products has attracted great interest in recent decades due to the carbon neutral nature of biomass feedstock. However, there are still many key technical difficulties for the industrial application of biomass bioconversion processes. One of the challenges associated with the microorganism Saccharomyces cerevisiae that is usually used for bioethanol production refers to the inhibition of the yeast by various stress factors. These inhibitive effects seriously restrict the growth and fermentation performance of the strains, resulting in reduced bioethanol production efficiency. Therefore, improving the stress response ability of the strains is of great significance for industrial production of bioethanol. In this article, the response mechanisms of S. cerevisiae to various hydrolysate-derived stress factors including organic acids, furan aldehydes, and phenolic compounds have been reviewed. Organic acids mainly stimulate cells to induce intracellular acidification, furan aldehydes mainly break the intracellular redox balance, and phenolic compounds have a greater effect on membrane homeostasis. These damages lead to inadequate intracellular energy supply and dysregulation of transcription and translation processes, and then activate a series of stress responses. The regulation mechanisms of S. cerevisiae in response to these stress factors are discussed with regard to the cell wall/membrane, energy, amino acids, transcriptional and translational, and redox regulation. The reported key target genes and transcription factors that contribute to the improvement of the strain performance are summarized. Furthermore, the genetic engineering strategies of constructing multilevel defense and eliminating stress effects are discussed in order to provide technical strategies for robust strain construction. It is recommended that robust S. cerevisiae can be constructed with the intervention of metabolic regulation based on the specific stress responses. Rational design with multilevel gene control and intensification of key enzymes can provide good strategies for construction of robust strains.
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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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