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• W3138328568 abstract "Limonene is an important plant natural product widely used in food and cosmetics production as well as in the pharmaceutical and chemical industries. However, low efficiency of plant extraction and high energy consumption in chemical synthesis limit the sustainability of industrial limonene production. Recently, the advancement of metabolic engineering and synthetic biology has facilitated the engineering of microbes into microbial cell factories for producing limonene. However, the deleterious effects on cellular activity by the toxicity of limonene is the major obstacle in achieving high-titer production of limonene in engineered microbes. In this study, by using transcriptomics, we identified 82 genes from the nonconventional yeast Yarrowia lipolytica that were up-regulated when exposed to limonene. When overexpressed, 8 of the gene candidates improved tolerance of this yeast to exogenously added limonene. To determine whether overexpression of these genes could also improve limonene production, we individually coexpressed the tolerance-enhancing genes with a limonene synthase gene. Indeed, expression of 5 of the 8 candidate genes enhanced limonene production in Y. lipolytica. Particularly, overexpressing YALI0F19492p led to an 8-fold improvement in product titer. Furthermore, through short-term adaptive laboratory evolution strategy, in combination with morphological and cytoplasmic membrane integrity analysis, we shed light on the underlying mechanism of limonene cytotoxicity to Y. lipolytica. This study demonstrated an effective strategy for improving limonene tolerance of Y. lipolytica and limonene titer in the host strain through the combinatorial use of tolerance engineering and evolutionary engineering." @default.
• W3138328568 created "2021-03-29" @default.
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• W3138328568 date "2021-03-15" @default.
• W3138328568 modified "2023-10-14" @default.
• W3138328568 title "Simultaneous Improvement of Limonene Production and Tolerance in <i>Yarrowia lipolytica</i> through Tolerance Engineering and Evolutionary Engineering" @default.
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• W3138328568 doi "https://doi.org/10.1021/acssynbio.1c00052" @default.
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• W3138328568 hasPublicationYear "2021" @default.
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