Cargando…

Genome-scale model-driven strain design for dicarboxylic acid production in Yarrowia lipolytica

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 shou...

Descripción completa

Detalles Bibliográficos
Autores principales: Mishra, Pranjul, Lee, Na-Rae, Lakshmanan, Meiyappan, Kim, Minsuk, Kim, Byung-Gee, Lee, Dong-Yup
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5861505/
https://www.ncbi.nlm.nih.gov/pubmed/29560822
http://dx.doi.org/10.1186/s12918-018-0542-5
_version_ 1783308108742787072
author Mishra, Pranjul
Lee, Na-Rae
Lakshmanan, Meiyappan
Kim, Minsuk
Kim, Byung-Gee
Lee, Dong-Yup
author_facet Mishra, Pranjul
Lee, Na-Rae
Lakshmanan, Meiyappan
Kim, Minsuk
Kim, Byung-Gee
Lee, Dong-Yup
author_sort Mishra, Pranjul
collection PubMed
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. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12918-018-0542-5) contains supplementary material, which is available to authorized users.
format Online
Article
Text
id pubmed-5861505
institution National Center for Biotechnology Information
language English
publishDate 2018
publisher BioMed Central
record_format MEDLINE/PubMed
spelling pubmed-58615052018-03-26 Genome-scale model-driven strain design for dicarboxylic acid production in Yarrowia lipolytica Mishra, Pranjul Lee, Na-Rae Lakshmanan, Meiyappan Kim, Minsuk Kim, Byung-Gee Lee, Dong-Yup BMC Syst Biol Research 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. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12918-018-0542-5) contains supplementary material, which is available to authorized users. BioMed Central 2018-03-19 /pmc/articles/PMC5861505/ /pubmed/29560822 http://dx.doi.org/10.1186/s12918-018-0542-5 Text en © The Author(s). 2018 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research
Mishra, Pranjul
Lee, Na-Rae
Lakshmanan, Meiyappan
Kim, Minsuk
Kim, Byung-Gee
Lee, Dong-Yup
Genome-scale model-driven strain design for dicarboxylic acid production in Yarrowia lipolytica
title Genome-scale model-driven strain design for dicarboxylic acid production in Yarrowia lipolytica
title_full Genome-scale model-driven strain design for dicarboxylic acid production in Yarrowia lipolytica
title_fullStr Genome-scale model-driven strain design for dicarboxylic acid production in Yarrowia lipolytica
title_full_unstemmed Genome-scale model-driven strain design for dicarboxylic acid production in Yarrowia lipolytica
title_short Genome-scale model-driven strain design for dicarboxylic acid production in Yarrowia lipolytica
title_sort genome-scale model-driven strain design for dicarboxylic acid production in yarrowia lipolytica
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5861505/
https://www.ncbi.nlm.nih.gov/pubmed/29560822
http://dx.doi.org/10.1186/s12918-018-0542-5
work_keys_str_mv AT mishrapranjul genomescalemodeldrivenstraindesignfordicarboxylicacidproductioninyarrowialipolytica
AT leenarae genomescalemodeldrivenstraindesignfordicarboxylicacidproductioninyarrowialipolytica
AT lakshmananmeiyappan genomescalemodeldrivenstraindesignfordicarboxylicacidproductioninyarrowialipolytica
AT kimminsuk genomescalemodeldrivenstraindesignfordicarboxylicacidproductioninyarrowialipolytica
AT kimbyunggee genomescalemodeldrivenstraindesignfordicarboxylicacidproductioninyarrowialipolytica
AT leedongyup genomescalemodeldrivenstraindesignfordicarboxylicacidproductioninyarrowialipolytica