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Reconstruction of the microalga Nannochloropsis salina genome-scale metabolic model with applications to lipid production

BACKGROUND: Nannochloropsis salina (= Eustigmatophyceae) is a marine microalga which has become a biotechnological target because of its high capacity to produce polyunsaturated fatty acids and triacylglycerols. It has been used as a source of biofuel, pigments and food supplements, like Omega 3. On...

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Detalles Bibliográficos
Autores principales: Loira, Nicolás, Mendoza, Sebastian, Paz Cortés, María, Rojas, Natalia, Travisany, Dante, Genova, Alex Di, Gajardo, Natalia, Ehrenfeld, Nicole, Maass, Alejandro
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5496344/
https://www.ncbi.nlm.nih.gov/pubmed/28676050
http://dx.doi.org/10.1186/s12918-017-0441-1
Descripción
Sumario:BACKGROUND: Nannochloropsis salina (= Eustigmatophyceae) is a marine microalga which has become a biotechnological target because of its high capacity to produce polyunsaturated fatty acids and triacylglycerols. It has been used as a source of biofuel, pigments and food supplements, like Omega 3. Only some Nannochloropsis species have been sequenced, but none of them benefit from a genome-scale metabolic model (GSMM), able to predict its metabolic capabilities. RESULTS: We present iNS934, the first GSMM for N. salina, including 2345 reactions, 934 genes and an exhaustive description of lipid and nitrogen metabolism. iNS934 has a 90% of accuracy when making simple growth/no-growth predictions and has a 15% error rate in predicting growth rates in different experimental conditions. Moreover, iNS934 allowed us to propose 82 different knockout strategies for strain optimization of triacylglycerols. CONCLUSIONS: iNS934 provides a powerful tool for metabolic improvement, allowing predictions and simulations of N. salina metabolism under different media and genetic conditions. It also provides a systemic view of N. salina metabolism, potentially guiding research and providing context to -omics data. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12918-017-0441-1) contains supplementary material, which is available to authorized users.