The increasing consumption of fossil fuels is contributing to global resource depletion and environmental pollution. Branched-chain higher alcohols, such as isopentanol and isobutanol, have attracted significant attention as next-generation biofuels. Biofuel production through microbial fermentation offers a green, sustainable, and renewable alternative to chemical synthesis. While enhanced production of isopentanol has been achieved in a variety of chassis, the fermentation yield has not yet reached levels suitable for industrial-scale production. In this study, we employed a continuous perturbation tool to construct a genome-scale perturbation library, combined with an isopentanol biosensor to screen for high-yielding mutants. We identified five high-yielding mutants, each exhibiting an increased glucose conversion rate and isopentanol titer. The F2 strain, in particular, achieved an isopentanol titer of 1.57 ± 0.014 g/L and a yield of 14.04 ± 0.251 mg/g glucose (10% glucose), surpassing the highest values reported to date in engineered Saccharomyces cerevisiae. Systematic transcriptome analysis of the isopentanol synthesis, glycolysis, glycerol metabolism, and ethanol synthesis pathways revealed that MPC, OAC1, BAT2, GUT2, PDC6, and ALD4 are linked to efficient isopentanol production. Further analysis of differentially expressed genes (DEGs) identified 17 and 12 co-expressed DEGs (co-DEGs) in all mutants and the two second-round mutants, respectively. In addition, we validated the knockout or overexpression of key co-DEGs. Our results confirmed the critical roles of HOM3 and DIP5 in isopentanol production, along with genes associated with the aerobic respiratory chain (SDH3, CYT1, COX7, ROX1, and ATG41) and cofactor balance (BNA2 and NDE1). Additionally, functional analysis of the co-DEGs revealed that MAL33 is associated with the synthesis of branched-chain higher alcohols, expanding the intracellular metabolic network and offering new possibilities for green, cost-effective biofuel production.

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Journal Article

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Xiao Q, Shi J, Wang L, Zhao G, Zhang Y

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