ArticleBMC systems biology2018
Genome-scale model-driven strain design for dicarboxylic acid production in Yarrowia lipolytica.
Article in BMC systems biology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.
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Who cites it
27 citing papers in PubMed, 88 citations in OpenAlex.
- Enzyme-constrained genome-scale model of Yarrowia lipolytica predicts growth-phase specific metabolic engineering targets.Applied microbiology and biotechnology · 2026Article
- Metabolic modeling of Halomonas campaniensis improves polyhydroxybutyrate production under nitrogen limitation.Applied microbiology and biotechnology · 2024Article
- Genome-scale model development and genomic sequencing of the oleaginous cladeFrontiers in bioengineering and biotechnology · 2024Article
- Metabolic modeling predicts unique drug targets inmSystems · 2023Article
- Unlocking the magic in mycelium: Using synthetic biology to optimize filamentous fungi for biomanufacturing and sustainability.Materials today. Bio · 2023Article
- Construction and application of the genome-scale metabolic model ofFrontiers in bioengineering and biotechnology · 2023Article
- A Computational Toolbox to Investigate the Metabolic Potential and Resource Allocation in Fission Yeast.mSystems · 2022Article
- Review
- Reconstruction of a catalogue of genome-scale metabolic models with enzymatic constraints using GECKO 2.0.Nature communications · 2022Article
- Dissecting carbon metabolism ofComputational and structural biotechnology journal · 2022Article
- Diversity begets diversity during community assembly until ecological limits impose a diversity ceiling.Molecular ecology · 2021Article
- Evaluating accessibility, usability and interoperability of genome-scale metabolic models for diverse yeasts species.FEMS yeast research · 2021Article
- Fine-tuning mitochondrial activity in Yarrowia lipolytica for citrate overproduction.Scientific reports · 2021Article
- MetaNetX/MNXref: unified namespace for metabolites and biochemical reactions in the context of metabolic models.Nucleic acids research · 2021Article
- Genome-scale metabolic modeling underscores the potential of Cutaneotrichosporon oleaginosus ATCC 20509 as a cell factory for biofuel production.Biotechnology for biofuels · 2021Article
- Boosting Biomass Quantity and Quality by Improved Mixotrophic Culture of the DiatomFrontiers in plant science · 2021Article
- Application of Random Mutagenesis and Synthetic FadR Promoter forFrontiers in bioengineering and biotechnology · 2021Article
- Synthetic biology, systems biology, and metabolic engineering of Yarrowia lipolytica toward a sustainable biorefinery platform.Journal of industrial microbiology & biotechnology · 2020Review
- Biosynthesis of terpene compounds using the non-model yeast Yarrowia lipolytica: grand challenges and a few perspectives.Current opinion in biotechnology · 2020Review
- Application of Stable Isotope Tracing to Elucidate Metabolic Dynamics During Yarrowia lipolytica α-Ionone Fermentation.iScience · 2020Article
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Authors and funding
6 authors at 4 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundRecently, 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.
resultsIn 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.
conclusionIn 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.
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