Een verkenning van de diversiteit van Saccharomyces cerevisiae-stammen als celfabrieken voor limoneenproductie

Genetically engineered microbes are increasingly utilized to produce a broad range of high-value compounds. However, most studies start with only a very narrow group of genetically tractable type strains that have not been selected for maximum titers or industrial robustness. In this study, we used high-throughput screening and parallel metabolic engineering to identify and optimize Saccharomyces cerevisiae chassis strains for limonene production, a monoterpene with applications in flavors, fragrances, and biofuels. We screened 921 genetically and phenotypically distinct S. cerevisiae strains for limonene tolerance and lipid content to identify optimal chassis strains for precision fermentation of limonene. In parallel, we also evaluated 16 different plant limonene synthases. Our results revealed that two of the selected strains showed approximately a 2-fold increase in titers compared to CEN.PK2-1C, the type strain that is often used as a chassis for limonene production, with the same genetic modifications in the mevalonate pathway. Intriguingly, the most effective engineering strategy proved strain-specific. Metabolic profiling revealed that this difference is likely explained by differences in native mevalonate production. Ultimately, by using strain-specific engineering strategies, we achieved 1412 mg/L in a new strain, which is 83% higher than the optimal titer (770 mg/L) achieved in CEN.PK2-1C. Our findings demonstrate the potential of leveraging genetic diversity in S. cerevisiae for monoterpene bioproduction and highlight the necessity for tailoring metabolic engineering strategies to specific strains.

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Publication Details

Journal
Lirias (KU Leuven)
Published
2026-01-09
Primary Topic
Plant biochemistry and biosynthesis
Type
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article

Een verkenning van de diversiteit van Saccharomyces cerevisiae-stammen als celfabrieken voor limoneenproductie

Y. C. Zhu
Lirias (KU Leuven)
Plant biochemistry and biosynthesis
article

Een verkenning van de diversiteit van Saccharomyces cerevisiae-stammen als celfabrieken voor limoneenproductie

Y. C. Zhu
article en

Abstract

Genetically engineered microbes are increasingly utilized to produce a broad range of high-value compounds. However, most studies start with only a very narrow group of genetically tractable type strains that have not been selected for maximum titers or industrial robustness. In this study, we used high-throughput screening and parallel metabolic engineering to identify and optimize Saccharomyces cerevisiae chassis strains for limonene production, a monoterpene with applications in flavors, fragrances, and biofuels. We screened 921 genetically and phenotypically distinct S. cerevisiae strains for limonene tolerance and lipid content to identify optimal chassis strains for precision fermentation of limonene. In parallel, we also evaluated 16 different plant limonene synthases. Our results revealed that two of the selected strains showed approximately a 2-fold increase in titers compared to CEN.PK2-1C, the type strain that is often used as a chassis for limonene production, with the same genetic modifications in the mevalonate pathway. Intriguingly, the most effective engineering strategy proved strain-specific. Metabolic profiling revealed that this difference is likely explained by differences in native mevalonate production. Ultimately, by using strain-specific engineering strategies, we achieved 1412 mg/L in a new strain, which is 83% higher than the optimal titer (770 mg/L) achieved in CEN.PK2-1C. Our findings demonstrate the potential of leveraging genetic diversity in S. cerevisiae for monoterpene bioproduction and highlight the necessity for tailoring metabolic engineering strategies to specific strains.

Lirias (KU Leuven)
Openalex Percentile: Top 99%
Plant biochemistry and biosynthesis
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Een verkenning van de diversiteit van Saccharomyces cerevisiae-stammen als celfabrieken voor limoneenproductie — Y. C. Zhu · Lirias (KU Leuven) (2026) | TGRS Research Map | TGRS