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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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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
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author Loira, Nicolás
Mendoza, Sebastian
Paz Cortés, María
Rojas, Natalia
Travisany, Dante
Genova, Alex Di
Gajardo, Natalia
Ehrenfeld, Nicole
Maass, Alejandro
author_facet Loira, Nicolás
Mendoza, Sebastian
Paz Cortés, María
Rojas, Natalia
Travisany, Dante
Genova, Alex Di
Gajardo, Natalia
Ehrenfeld, Nicole
Maass, Alejandro
author_sort Loira, Nicolás
collection PubMed
description 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.
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spelling pubmed-54963442017-07-05 Reconstruction of the microalga Nannochloropsis salina genome-scale metabolic model with applications to lipid production Loira, Nicolás Mendoza, Sebastian Paz Cortés, María Rojas, Natalia Travisany, Dante Genova, Alex Di Gajardo, Natalia Ehrenfeld, Nicole Maass, Alejandro BMC Syst Biol Research Article 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. BioMed Central 2017-07-04 /pmc/articles/PMC5496344/ /pubmed/28676050 http://dx.doi.org/10.1186/s12918-017-0441-1 Text en © The Author(s) 2017 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 Article
Loira, Nicolás
Mendoza, Sebastian
Paz Cortés, María
Rojas, Natalia
Travisany, Dante
Genova, Alex Di
Gajardo, Natalia
Ehrenfeld, Nicole
Maass, Alejandro
Reconstruction of the microalga Nannochloropsis salina genome-scale metabolic model with applications to lipid production
title Reconstruction of the microalga Nannochloropsis salina genome-scale metabolic model with applications to lipid production
title_full Reconstruction of the microalga Nannochloropsis salina genome-scale metabolic model with applications to lipid production
title_fullStr Reconstruction of the microalga Nannochloropsis salina genome-scale metabolic model with applications to lipid production
title_full_unstemmed Reconstruction of the microalga Nannochloropsis salina genome-scale metabolic model with applications to lipid production
title_short Reconstruction of the microalga Nannochloropsis salina genome-scale metabolic model with applications to lipid production
title_sort reconstruction of the microalga nannochloropsis salina genome-scale metabolic model with applications to lipid production
topic Research Article
url 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
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