ArticleBMC systems biology2015
Optimization of lipid production with a genome-scale model of Yarrowia lipolytica.
Article in BMC systems biology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 45 papers.
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Who cites it
45 citing papers in PubMed, 138 citations in OpenAlex.
- Enzyme-constrained genome-scale model of Yarrowia lipolytica predicts growth-phase specific metabolic engineering targets.Applied microbiology and biotechnology · 2026Article
- Acetyl- and malonyl-CoA availability drive EPA selectivity in polyketide synthase-engineered Yarrowia lipolytica.Microbial cell factories · 2026Article
- Waste Sunflower Oil as a Feedstock for Efficient Single-Cell Oil and Biomass Production byFoods (Basel, Switzerland) · 2026Article
- Multi-omics reveals glucose repression of citric acid catabolism in Pichia kudriavzevii.Applied microbiology and biotechnology · 2025Article
- Recent advances in genetic engineering and chemical production in yeast species.FEMS yeast research · 2025Review
- Review
- Genome-scale model development and genomic sequencing of the oleaginous cladeFrontiers in bioengineering and biotechnology · 2024Article
- Compound K Production: Achievements and Perspectives.Life (Basel, Switzerland) · 2023Review
- Genetic inactivation of the Carnitine/Acetyl-Carnitine mitochondrial carrier of Yarrowia lipolytica leads to enhanced odd-chain fatty acid production.Microbial cell factories · 2023Article
- Construction and application of the genome-scale metabolic model ofFrontiers in bioengineering and biotechnology · 2023Article
- Papiliotrema laurentii: general features and biotechnological applications.Applied microbiology and biotechnology · 2022Review
- Enhancing very long chain fatty acids production in Yarrowia lipolytica.Microbial cell factories · 2022Article
- Linear programming based gene expression model (LPM-GEM) predicts the carbon source for Bacillus subtilis.BMC bioinformatics · 2022Article
- Genome-scale modeling of yeast metabolism: retrospectives and perspectives.FEMS yeast research · 2022Review
- Metabolomics-driven strain improvement: A mini review.Frontiers in molecular biosciences · 2022Review
- Dissecting carbon metabolism ofComputational and structural biotechnology journal · 2022Article
- The history, state of the art and future prospects for oleaginous yeast research.Microbial cell factories · 2021Review
- Engineering of Saccharomyces cerevisiae for the accumulation of high amounts of triacylglycerol.Microbial cell factories · 2021Article
- Review
- Evaluating accessibility, usability and interoperability of genome-scale metabolic models for diverse yeasts species.FEMS yeast research · 2021Article
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Authors and funding
4 authors at 2 institutions in 2 countries.
Funding
Abstract
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.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.