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Genome-scale model-driven strain design for dicarboxylic acid production in Yarrowia lipolytica
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Mishra, Pranjul | - |
dc.contributor.author | Lee, Na-Rae | - |
dc.contributor.author | Lakshmanan, Meiyappan | - |
dc.contributor.author | Kim, Minsuk | - |
dc.contributor.author | Kim, Byung-Gee | - |
dc.contributor.author | Lee, Dong-Yup | - |
dc.date.accessioned | 2018-05-14T07:56:59Z | - |
dc.date.available | 2018-05-14T16:58:09Z | - |
dc.date.issued | 2018-03-19 | - |
dc.identifier.citation | BMC Systems Biology, 12(Suppl 2):12 | ko_KR |
dc.identifier.issn | 1752-0509 | - |
dc.identifier.uri | https://hdl.handle.net/10371/139758 | - |
dc.description.abstract | 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. | ko_KR |
dc.description.sponsorship | This work was supported by the Academic Research Fund (R-279-000-476-112) of the National University of Singapore, Biomedical Research Council of A*STAR (Agency for Science, Technology and Research), Singapore, the Global R&D project program (N011500017), Ministry of Trade, Industry and
Energy (MOTIE), Republic of Korea and the Next-Generation BioGreen 21 Program of the Rural Development Administration, Republic of Korea (Systems and Synthetic Agrobiotech Center; grant no. PJ01334605). Publication cost was covered by NUS SynCTI program. | ko_KR |
dc.language.iso | en | ko_KR |
dc.publisher | BioMed Central | ko_KR |
dc.subject | Yarrowia lipolytica | ko_KR |
dc.subject | Dicarboxylic acid | ko_KR |
dc.subject | Genome-scale metabolic models | ko_KR |
dc.subject | Strain design | ko_KR |
dc.subject | Metabolic engineering | ko_KR |
dc.title | Genome-scale model-driven strain design for dicarboxylic acid production in Yarrowia lipolytica | ko_KR |
dc.type | Article | ko_KR |
dc.contributor.AlternativeAuthor | 이나래 | - |
dc.contributor.AlternativeAuthor | 김민석 | - |
dc.contributor.AlternativeAuthor | 김병기 | - |
dc.contributor.AlternativeAuthor | 이동엽 | - |
dc.identifier.doi | 10.1186/s12918-018-0542-5 | - |
dc.language.rfc3066 | en | - |
dc.rights.holder | The Author(s). | - |
dc.date.updated | 2018-03-25T05:31:10Z | - |
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