Dataset Information

Dissecting carbon metabolism of Yarrowia lipolytica type strain W29 using genome-scale metabolic modelling.

ABSTRACT: Yarrowia lipolytica is a widely-used chassis cell in biotechnological applications. It has recently gained extensive research interest owing to its extraordinary ability of producing industrially valuable biochemicals from a variety of carbon sources. Genome-scale metabolic models (GSMMs) enable analyses of cellular metabolism for engineering various industrial hosts. In the present study, we developed a high-quality GSMM iYli21 for Y. lipolytica type strain W29 by extensive manual curation with Biolog experimental data. The model showed a high accuracy of 85.7% in predicting nutrient utilization. Transcriptomics data were integrated to delineate cellular metabolism of utilizing six individual metabolites as sole carbon sources. Comparisons showed that 302 reactions were commonly used, including those from TCA cycle, oxidative phosphorylation, and purine metabolism for energy and material supply. Whereas glycolytic reactions were employed only when glucose and glycerol used as sole carbon sources, gluconeogenesis and fatty acid oxidation reactions were specifically employed when fatty acid, alkane and glycerolipid were the sole carbon sources. Further test of 46 substrates for generating 5 products showed that hexanoate outcompeted other compounds in terms of maximum theoretical yield owing to the lowest carbon loss for energy supply. This newly generated model iYli21 will be a valuable tool in dissecting metabolic mechanism and guiding metabolic engineering of this important industrial cell factory.

SUBMITTER: Guo Y

PROVIDER: S-EPMC9136261 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature

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Dissecting carbon metabolism of Yarrowia lipolytica type strain W29 using genome-scale metabolic modelling.

Guo Yufeng Y Su Liqiu L Liu Qi Q Zhu Yan Y Dai Zongjie Z Wang Qinhong Q

Computational and structural biotechnology journal 20220516

Yarrowia lipolytica is a widely-used chassis cell in biotechnological applications. It has recently gained extensive research interest owing to its extraordinary ability of producing industrially valuable biochemicals from a variety of carbon sources. Genome-scale metabolic models (GSMMs) enable analyses of cellular metabolism for engineering various industrial hosts. In the present study, we developed a high-quality GSMM iYli21 for Y. lipolytica type strain W29 by extensive ...[more]

PMID: 35664225

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Project description:BACKGROUND:Recently, there have been several attempts to produce long-chain dicarboxylic acids (DCAs) in various microbial hosts. Of these, Yarrowia lipolytica has great potential due to its oleaginous characteristics and unique ability to utilize hydrophobic substrates. However, Y. lipolytica should be further engineered to make it more competitive: the current approaches are mostly intuitive and cumbersome, thus limiting its industrial application. RESULTS:In this study, we proposed model-guided metabolic engineering strategies for enhanced production of DCAs in Y. lipolytica. At the outset, we reconstructed genome-scale metabolic model (GSMM) of Y. lipolytica (iYLI647) by substantially expanding the previous models. Subsequently, the model was validated using three sets of published culture experiment data. It was finally exploited to identify genetic engineering targets for overexpression, knockout, and cofactor modification by applying several in silico strain design methods, which potentially give rise to high yield production of the industrially relevant long-chain DCAs, e.g., dodecanedioic acid (DDDA). The resultant targets include (1) malate dehydrogenase and malic enzyme genes and (2) glutamate dehydrogenase gene, in silico overexpression of which generated additional NADPH required for fatty acid synthesis, leading to the increased DDDA fluxes by 48% and 22% higher, respectively, compared to wild-type. We further investigated the effect of supplying branched-chain amino acids on the acetyl-CoA turn-over rate which is key metabolite for fatty acid synthesis, suggesting their significance for production of DDDA in Y. lipolytica. CONCLUSION:In silico model-based strain design strategies allowed us to identify several metabolic engineering targets for overproducing DCAs in lipid accumulating yeast, Y. lipolytica. Thus, the current study can provide a methodological framework that is applicable to other oleaginous yeasts for value-added biochemical production.

Project description:Background: Erythritol is a zero-calorie sweetener that is widely used in the food, pharmaceutical, and medical industries. Crude glycerol is the main by-product of biodiesel, and the effective utilization of crude glycerol will help to improve biodiesel viability. Previous studies on the production of erythritol from Y. lipolytica using crude glycerol as a carbon source have focused on optimizing the fermentation process of the mutant Y. lipolytica Wratislavia K1, while metabolic engineering has not been successfully applied. Results: To this end, we engineered the yeast Y. lipolytica to increase the productivity of this strain. Wild strains tolerant to high concentrations of crude glycerol were screened and identified. A series of rational metabolic approaches were employed to improve erythritol production. Among them, the engineered strain Y-04, obtained by tandem overexpression of GUT1 and GUT2, significantly increased glycerol assimilation by 33.3%, which was consistent with the results of RT-qPCR analysis. The effects of tandem overexpression of GUT1, GUT2, TKL1, and TAL1 on erythritol synthesis were also evaluated. The best results were obtained using a mutant that overexpressed GUT1, GUT2, and TKL1 and knocked out EYD1. The final Y-11 strain produced 150 g/l erythritol in a 5-L bioreactor with a yield and productivity of 0.62 g/g and 1.25 g/l/h, respectively. To the best of our knowledge, this is the highest erythritol yield and productivity from crude glycerol ever reported in Y. lipolytica. Conclusion: This work demonstrated that overexpression of GUT1, GUT2, and TKL1 and knockdown of EYD1 could be used to improve crude glycerol utilization and erythritol synthesis in Y. lipolytica. The process parameters such as erythritol yield and productivity were significantly elevated, which is valuable for industrial applications. Crude glycerol, as a carbon source, could efficiently restrict the synthesis of by-products while enhancing the generation of erythritol, compared to glucose. This indicates considerable potential for synthesizing value-added products from crude glycerol by Y. lipolytica.

Dataset Information

Dissecting carbon metabolism of Yarrowia lipolytica type strain W29 using genome-scale metabolic modelling.

Publications

Dissecting carbon metabolism of <i>Yarrowia lipolytica</i> type strain W29 using genome-scale metabolic modelling.

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