Dataset Information

A set of Yarrowia lipolytica CRISPR/Cas9 vectors for exploiting wild-type strain diversity.

ABSTRACT:

Objectives

The construction and validation of a set of Yarrowia lipolytica CRISPR/Cas9 vectors containing six different markers that allows virtually any genetic background to be edited, including those of wild-type strains.

Results

Using the Golden Gate method, we assembled a set of six CRISPR/Cas9 vectors, each containing a different selection marker, to be used for editing the genome of the industrial yeast Y. lipolytica. This vector set is available via Addgene. Any guide RNA (gRNA) sequence can be easily and rapidly introduced in any of these vectors using Golden Gate assembly. We successfully edited six different genes in a variety of genetic backgrounds, including those of wild-type strains, with five of the six vectors. Use of these vectors strongly improved homologous recombination and cassette integration at a specific locus.

Conclusions

We have created a versatile and modular set of CRISPR/Cas9 vectors that will allow any Y. lipolytica strain to be rapidly edited; this tool will facilitate experimentation with any prototroph wild-type strains displaying interesting features.

SUBMITTER: Larroude M

PROVIDER: S-EPMC7101291 | biostudies-literature | 2020 May

REPOSITORIES: biostudies-literature

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Publications

A set of Yarrowia lipolytica CRISPR/Cas9 vectors for exploiting wild-type strain diversity.

Larroude Macarena M Trabelsi Heykel H Nicaud Jean-Marc JM Rossignol Tristan T

Biotechnology letters 20200123 5

<h4>Objectives</h4>The construction and validation of a set of Yarrowia lipolytica CRISPR/Cas9 vectors containing six different markers that allows virtually any genetic background to be edited, including those of wild-type strains.<h4>Results</h4>Using the Golden Gate method, we assembled a set of six CRISPR/Cas9 vectors, each containing a different selection marker, to be used for editing the genome of the industrial yeast Y. lipolytica. This vector set is available via Addgene. Any guide RNA ...[more]

PMID: 31974649

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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.

Dataset Information

A set of Yarrowia lipolytica CRISPR/Cas9 vectors for exploiting wild-type strain diversity.

Objectives

Results

Conclusions

Publications

A set of Yarrowia lipolytica CRISPR/Cas9 vectors for exploiting wild-type strain diversity.

Similar Datasets

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