Dataset Information

Improving Lipid Production of Yarrowia lipolytica by the Aldehyde Dehydrogenase-Mediated Furfural Detoxification.

ABSTRACT: Yarrowia lipolytica, the non-conventional yeast capable of high lipogenesis, is a microbial chassis for producing lipid-based biofuels and chemicals from renewable resources such as lignocellulosic biomass. However, the low tolerance of Y. lipolytica against furfural, a major inhibitory furan aldehyde derived from the pretreatment processes of lignocellulosic biomass, has restricted the efficient conversion of lignocellulosic hydrolysates. In this study, the furfural tolerance of Y. lipolytica has been improved by supporting its endogenous detoxification mechanism. Specifically, the endogenous genes encoding the aldehyde dehydrogenase family proteins were overexpressed in Y. lipolytica to support the conversion of furfural to furoic acid. Among them, YALI0E15400p (FALDH2) has shown the highest conversion rate of furfural to furoic acid and resulted in two-fold increased cell growth and lipid production in the presence of 0.4 g/L of furfural. To our knowledge, this is the first report to identify the native furfural detoxification mechanism and increase furfural resistance through rational engineering in Y. lipolytica. Overall, these results will improve the potential of Y. lipolytica to produce lipids and other value-added chemicals from a carbon-neutral feedstock of lignocellulosic biomass.

SUBMITTER: Kim J

PROVIDER: S-EPMC9102794 | biostudies-literature | 2022 Apr

REPOSITORIES: biostudies-literature

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Improving Lipid Production of Yarrowia lipolytica by the Aldehyde Dehydrogenase-Mediated Furfural Detoxification.

Kim Jiwon J Son Hyeoncheol Francis HF Hwang Sungmin S Gong Gyeongtaek G Ko Ja Kyong JK Um Youngsoon Y Han Sung Ok SO Lee Sun-Mi SM

International journal of molecular sciences 20220426 9

Yarrowia lipolytica, the non-conventional yeast capable of high lipogenesis, is a microbial chassis for producing lipid-based biofuels and chemicals from renewable resources such as lignocellulosic biomass. However, the low tolerance of Y. lipolytica against furfural, a major inhibitory furan aldehyde derived from the pretreatment processes of lignocellulosic biomass, has restricted the efficient conversion of lignocellulosic hydrolysates. In this study, the furfural tolerance of < ...[more]

PMID: 35563152

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Project description:BackgroundThe utilization of industrial wastes as feedstock in microbial-based processes is a one of the high-potential approach for the development of sustainable, environmentally beneficial and valuable bioproduction, inter alia, lipids. Rye straw hydrolysate, a possible renewable carbon source for bioconversion, contains a large amount of xylose, inaccessible to the wild-type Yarrowia lipolytica strains. Although these oleaginous yeasts possesses all crucial genes for xylose utilization, it is necessary to induce their metabolic pathway for efficient growth on xylose and mixed sugars from agricultural wastes. Either way, biotechnological production of single cell oils (SCO) from lignocellulosic hydrolysate requires yeast genome modification or adaptation to a suboptimal environment.ResultsThe presented Y. lipolytica strain was developed using minimal genome modification-overexpression of endogenous xylitol dehydrogenase (XDH) and xylulose kinase (XK) genes was sufficient to allow yeast to grow on xylose as a sole carbon source. Diacylglycerol acyltransferase (DGA1) expression remained stable and provided lipid overproduction. Obtained an engineered Y. lipolytica strain produced 5.51 g/L biomass and 2.19 g/L lipids from nitrogen-supplemented rye straw hydrolysate, which represents an increase of 64% and an almost 10 times higher level, respectively, compared to the wild type (WT) strain. Glucose and xylose were depleted after 120 h of fermentation. No increase in byproducts such as xylitol was observed.ConclusionsXylose-rich rye straw hydrolysate was exploited efficiently for the benefit of production of lipids. This study indicates that it is possible to fine-tune a newly strain with as minimally genetic changes as possible by adjusting to an unfavorable environment, thus limiting multi-level genome modification. It is documented here the use of Y. lipolytica as a microbial cell factory for lipid synthesis from rye straw hydrolysate as a low-cost feedstock.

Project description:BackgroundYarrowia lipolytica is a non-conventional yeast that is extensively investigated for its ability to excrete citrate or to accumulate large amounts of storage lipids, which is of great significance for single cell oil production. Both traits are thus of interest for basic research as well as for biotechnological applications but they typically occur simultaneously thus lowering the respective yields. Therefore, engineering of strains with high lipid content relies on novel concepts such as computational simulation to better understand the two competing processes and to eliminate citrate excretion.ResultsUsing a genome-scale model (GSM) of baker's yeast as a scaffold, we reconstructed the metabolic network of Y. lipolytica and optimized it for use in flux balance analysis (FBA), with the aim to simulate growth and lipid production phases of this yeast. We validated our model and found the predictions of the growth behavior of Y. lipolytica in excellent agreement with experimental data. Based on these data, we successfully designed a fed-batch strategy to avoid citrate excretion during the lipid production phase. Further analysis of the network suggested that the oxygen demand of Y. lipolytica is reduced upon induction of lipid synthesis. According to this finding we hypothesized that a reduced aeration rate might induce lipid accumulation. This prediction was indeed confirmed experimentally. In a fermentation combining these two strategies lipid content of the biomass was increased by 80%, and lipid yield was improved more than four-fold, compared to standard conditions.ConclusionsGenome scale network reconstructions provide a powerful tool to predict the effects of genetic modifications and the metabolic response to environmental conditions. The high accuracy and the predictive value of a newly reconstructed GSM of Y. lipolytica to optimize growth conditions for lipid accumulation are demonstrated. Based on these findings, further strategies for engineering Y. lipolytica towards higher efficiency in single cell oil production are discussed.

Dataset Information

Improving Lipid Production of Yarrowia lipolytica by the Aldehyde Dehydrogenase-Mediated Furfural Detoxification.

Publications

Improving Lipid Production of <i>Yarrowia lipolytica</i> by the Aldehyde Dehydrogenase-Mediated Furfural Detoxification.

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