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A genome-scale metabolic model of the lipid-accumulating yeast Yarrowia lipolytica.

ABSTRACT: BACKGROUND: Yarrowia lipolytica is an oleaginous yeast which has emerged as an important microorganism for several biotechnological processes, such as the production of organic acids, lipases and proteases. It is also considered a good candidate for single-cell oil production. Although some of its metabolic pathways are well studied, its metabolic engineering is hindered by the lack of a genome-scale model that integrates the current knowledge about its metabolism. RESULTS: Combining in silico tools and expert manual curation, we have produced an accurate genome-scale metabolic model for Y. lipolytica. Using a scaffold derived from a functional metabolic model of the well-studied but phylogenetically distant yeast S. cerevisiae, we mapped conserved reactions, rewrote gene associations, added species-specific reactions and inserted specialized copies of scaffold reactions to account for species-specific expansion of protein families. We used physiological measures obtained under lab conditions to validate our predictions. CONCLUSIONS: Y. lipolytica iNL895 represents the first well-annotated metabolic model of an oleaginous yeast, providing a base for future metabolic improvement, and a starting point for the metabolic reconstruction of other species in the Yarrowia clade and other oleaginous yeasts.

SUBMITTER: Loira N

PROVIDER: S-EPMC3443063 | biostudies-literature | 2012

REPOSITORIES: biostudies-literature

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A genome-scale metabolic model of the lipid-accumulating yeast Yarrowia lipolytica.

Loira Nicolas N Dulermo Thierry T Nicaud Jean-Marc JM Sherman David James DJ

BMC systems biology 20120504

<h4>Background</h4>Yarrowia lipolytica is an oleaginous yeast which has emerged as an important microorganism for several biotechnological processes, such as the production of organic acids, lipases and proteases. It is also considered a good candidate for single-cell oil production. Although some of its metabolic pathways are well studied, its metabolic engineering is hindered by the lack of a genome-scale model that integrates the current knowledge about its metabolism.<h4>Results</h4>Combinin ...[more]

PMID: 22558935

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Project description:BACKGROUND:Yarrowia 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. RESULTS:Using 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. CONCLUSIONS:Genome 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.

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:BackgroundRecent trends in bioprocessing have underlined the significance of lignocellulosic biomass conversions for biofuel production. These conversions demand at least 90% energy upgradation of cellulosic sugars to generate renewable drop-in biofuel precursors (Heff/C ~ 2). Chemical methods fail to achieve this without substantial loss of carbon; whereas, oleaginous biological systems propose a greener upgradation route by producing oil from sugars with 30% theoretical yields. However, these oleaginous systems cannot compete with the commercial volumes of vegetable oils in terms of overall oil yields and productivities. One of the significant challenges in the commercial exploitation of these microbial oils lies in the inefficient recovery of the produced oil. This issue has been addressed using highly selective oil capturing agents (OCA), which allow a concomitant microbial oil production and in situ oil recovery process.ResultsAdsorbent-based oil capturing agents were employed for simultaneous in situ oil recovery in the fermentative production broths. Yarrowia lipolytica, a model oleaginous yeast, was milked incessantly for oil production over 380 h in a media comprising of glucose as a sole carbon and nutrient source. This was achieved by continuous online capture of extracellular oil from the aqueous media and also the cell surface, by fluidizing the fermentation broth over an adsorbent bed of oil capturing agents (OCA). A consistent oil yield of 0.33 g per g of glucose consumed, corresponding to theoretical oil yield over glucose, was achieved using this approach. While the incorporation of the OCA increased the oil content up to 89% with complete substrate consumptions, it also caused an overall process integration.ConclusionThe nondisruptive oil capture mediated by an OCA helped in accomplishing a trade-off between microbial oil production and its recovery. This strategy helped in realizing theoretically efficient sugar-to-oil bioconversions in a continuous production process. The process, therefore, endorses a sustainable production of molecular drop-in equivalents through oleaginous yeasts, representing as an absolute microbial oil factory.

Project description:The oleaginous yeast Yarrowia lipolytica has attracted much attention due to its ability to utilize a wide range of substrates to accumulate high lipid content and its flexibility for genetic manipulation. In this study, intracellular lipid metabolism in Y. lipolytica was tailored to produce fatty acid, a renewable oleochemical and precursor for production of advanced biofuels. Two main strategies, including blocking activation and peroxisomal uptake of fatty acids and elimination of biosynthesis of lipids, were employed to reduce fatty acid consumption by the native pathways in Y. lipolytica. Both genetic modifications improved fatty acid production. However, disruption of the genes responsible for assembly of nonpolar lipid molecules including triacylglycerols (TAGs) and steryl esters resulted in the deleterious effects on the cell growth. The gene tesA encoding thioesterase from Escherichia coli was expressed in the strain with disrupted faa genes encoding fatty acyl-CoA synthetases and pxa1 encoding peroxisomal acyl-CoA transporter, and the titer of fatty acids resulted in 2.3 g/L in shake flask culture, representing 11-fold improvement compared with the parent strain. Expressing the native genes encoding acetyl-CoA carboxylase (ACC) and hexokinase also increased fatty acid production, although the improvement was not as significant as that with tesA expression. Saturated fatty acids including palmitic acid (C16:0) and stearic acid (C18:0) increased remarkably in the fatty acid composition of the recombinant bearing tesA compared with the parent strain. The recombinant expressing tesA gene resulted in high lipid content, indicating the great fatty acid producing potential of Y. lipolytica. The results highlight the achievement of fatty acid overproduction without adverse effect on growth of the strain. Results of this study provided insight into the relationship between fatty acid and lipid metabolism in Y. lipolytica, confirming the avenue to reprogram lipid metabolism of this host for overproduction of renewable fatty acids.

Project description:Yarrowia lipolytica is known to be capable of metabolizing glucose and accumulating lipids intracellularly; however, it lacks the cellulolytic enzymes needed to break down cellulosic biomass directly. To develop Y. lipolytica as a consolidated bioprocessing (CBP) microorganism, we previously expressed the heterologous CBH I, CBH II, and EG II cellulase enzymes both individually and collectively in this microorganism. We concluded that the coexpression of these cellulases resulted in a metabolic drain on the host cells leading to reduced cell growth and lipid accumulation. The current study aims to build a new cellulase coexpressing platform to overcome these hinderances by (1) knocking out the sucrose non-fermenting 1 (Snf1) gene that represses the energetically expensive lipid and protein biosynthesis processes, and (2) knocking in the cellulase cassette fused with the recyclable selection marker URA3 gene in the background of a lipid-accumulating Y. lipolytica strain overexpressing ATP citrate lyase (ACL) and diacylglycerol acyltransferase 1 (DGA1) genes. We have achieved a homologous recombination insertion rate of 58% for integrating the cellulases-URA3 construct at the disrupted Snf1 site in the genome of host cells. Importantly, we observed that the disruption of the Snf1 gene promoted cell growth and lipid accumulation and lowered the cellular saturated fatty acid level and the saturated to unsaturated fatty acid ratio significantly in the transformant YL163t that coexpresses cellulases. The result suggests a lower endoplasmic reticulum stress in YL163t, in comparison with its parent strain Po1g ACL-DGA1. Furthermore, transformant YL163t increased in vitro cellulolytic activity by 30%, whereas the "total in vivo newly formed FAME (fatty acid methyl esters)" increased by 16% in comparison with a random integrative cellulase-expressing Y. lipolytica mutant in the same YNB-Avicel medium. The Snf1 disruption platform demonstrated in this study provides a potent tool for the further development of Y. lipolytica as a robust host for the expression of cellulases and other commercially important proteins.

Dataset Information

A genome-scale metabolic model of the lipid-accumulating yeast Yarrowia lipolytica.

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A genome-scale metabolic model of the lipid-accumulating yeast Yarrowia lipolytica.

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