Reference: Zhang X, et al. (2026) Omics analyses decoding mechanisms underlying the self-flocculating phenotype of yeast cells and stress tolerance for robust production. Metab Eng

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Abstract


A unique self-flocculating yeast strain SPSC01 was developed through protoplast fusion for fuel ethanol production with high product titers. In this study, we conducted comparative multi-omics analyses on SPSC01 to elucidate mechanisms underlying its self-flocculating phenotype and associated stress tolerance, the most desirable merit for robust production in industry. Leveraging two cutting-edge third-generation sequencing technologies, we achieved a gapless high-quality and chromosome-level assembly for the genome of SPSC01 and its parental strains as well. Through comprehensive genome analyses, we identified 25 unique genes that are absent in the parental strains, along with 13 novel genes with unknown functions. The self-flocculation of yeast cells is driven by the copy number of genetic variations and significantly upregulated transcription of FLO genes. Mutations in both cis- and trans-regulatory elements contribute to the constitutive expression of FLO1 and its derivative genes, a prerequisite for developing the self-flocculating phenotype. Notably, we discovered a novel small protein G12 that harbors a zinc finger domain, and its overexpression substantially enhanced ethanol production of engineered yeast strains. Furthermore, alterations in metabolic pathways with ergosterol, glutathione, amino acid, and glycerophospholipid are implicated for developing tolerance to ethanol and major inhibitors acetic acid and furfural that are released during the pretreatment of lignocellulosic biomass. The progress provides strategies for engineering yeast cell factories with robustness through rational designs to produce biofuels and bio-based chemicals with high product titers and productivities, in particular for the biorefinery of lignocellulosic biomass for sustainable socioeconomic development.

Reference Type
Journal Article
Authors
Zhang X, Dai Y, Zhao XQ, Liu CG, Wang Z, Bai FW
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