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  • Title: Transcriptome analysis reveals multiple targets of erythritol-related transcription factor EUF1 in unconventional yeast Yarrowia Lipolytica.
    Author: Rzechonek DA, Szczepańczyk M, Borodina I, Neuvéglise C, Mirończuk AM.
    Journal: Microb Cell Fact; 2024 Mar 12; 23(1):77. PubMed ID: 38475794.
    Abstract:
    BACKGROUND: Erythritol is a four-carbon polyol with an unclear role in metabolism of some unconventional yeasts. Its production has been linked to the osmotic stress response, but the mechanism of stress protection remains unclear. Additionally, erythritol can be used as a carbon source. In the yeast Yarrowia lipolytica, its assimilation is activated by the transcription factor Euf1. The study investigates whether this factor can link erythritol to other processes in the cell. RESULTS: The research was performed on two closely related strains of Y. lipolytica: MK1 and K1, where strain K1 has no functional Euf1. Cultures were carried out in erythritol-containing and erythritol-free media. Transcriptome analysis revealed the effect of Euf1 on the regulation of more than 150 genes. Some of these could be easily connected with different aspects of erythritol assimilation, such as: utilization pathway, a new potential isoform of transketolase, or polyol transporters. However, many of the upregulated genes have never been linked to metabolism of erythritol. The most prominent examples are the degradation pathway of branched-chain amino acids and the glyoxylate cycle. The high transcription of genes affected by Euf1 is still dependent on the erythritol concentration in the medium. Moreover, almost all up-regulated genes have an ATGCA motif in the promoter sequence. CONCLUSIONS: These findings may be particularly relevant given the increasing use of erythritol-induced promoters in genetic engineering of Y. lipolytica. Moreover, use of this yeast in biotechnological processes often takes place under osmotic stress conditions. Erythritol might be produce as a by-product, thus better understanding of its influence on cell metabolism could facilitate processes optimization.
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