Genome-Scale Metabolic Model for the Green Alga Chlorella vulgaris UTEX 395 Accurately Predicts Phenotypes under Autotrophic, Heterotrophic, and Mixotrophic Growth Conditions

Genome-Scale Metabolic Model for the Green Alga Chlorella vulgaris UTEX 395 Accurately Predicts... The green microalga Chlorella vulgaris has been widely recognized as a promising candidate for biofuel production due to its ability to store high lipid content and its natural metabolic versatility. Compartmentalized genome-scale metabolic models constructed from genome sequences enable quantitative insight into the transport and metabolism of compounds within a target organism. These metabolic models have long been utilized to generate optimized design strategies for an improved production process. Here, we describe the reconstruction, validation, and application of a genome-scale metabolic model for C. vulgaris UTEX 395, i CZ843. The reconstruction represents the most comprehensive model for any eukaryotic photosynthetic organism to date, based on the genome size and number of genes in the reconstruction. The highly curated model accurately predicts phenotypes under photoautotrophic, heterotrophic, and mixotrophic conditions. The model was validated against experimental data and lays the foundation for model-driven strain design and medium alteration to improve yield. Calculated flux distributions under different trophic conditions show that a number of key pathways are affected by nitrogen starvation conditions, including central carbon metabolism and amino acid, nucleotide, and pigment biosynthetic pathways. Furthermore, model prediction of growth rates under various medium compositions and subsequent experimental validation showed an increased growth rate with the addition of tryptophan and methionine. Glossary KEGG Kyoto Encyclopedia of Genes and Genomes GPR gene/protein/reaction BOF biomass objective function TAG triacylglycerol PG phosphatidylglycerol PI phosphatidylinositol PE phosphatidylethanolamine MGDG monogalactosyldiacylglycerol MCC Matthews correlation coefficient PPP pentose phosphate pathway BBM Bold’s basal medium http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Plant Physiology American Society of Plant Biologist

Genome-Scale Metabolic Model for the Green Alga Chlorella vulgaris UTEX 395 Accurately Predicts Phenotypes under Autotrophic, Heterotrophic, and Mixotrophic Growth Conditions

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Publisher
American Society of Plant Biologist
Copyright
Copyright © 2016 by the American Society of Plant Biologists
ISSN
1532-2548
eISSN
0032-0889
DOI
10.1104/pp.16.00593
pmid
27372244
Publisher site
See Article on Publisher Site

Abstract

The green microalga Chlorella vulgaris has been widely recognized as a promising candidate for biofuel production due to its ability to store high lipid content and its natural metabolic versatility. Compartmentalized genome-scale metabolic models constructed from genome sequences enable quantitative insight into the transport and metabolism of compounds within a target organism. These metabolic models have long been utilized to generate optimized design strategies for an improved production process. Here, we describe the reconstruction, validation, and application of a genome-scale metabolic model for C. vulgaris UTEX 395, i CZ843. The reconstruction represents the most comprehensive model for any eukaryotic photosynthetic organism to date, based on the genome size and number of genes in the reconstruction. The highly curated model accurately predicts phenotypes under photoautotrophic, heterotrophic, and mixotrophic conditions. The model was validated against experimental data and lays the foundation for model-driven strain design and medium alteration to improve yield. Calculated flux distributions under different trophic conditions show that a number of key pathways are affected by nitrogen starvation conditions, including central carbon metabolism and amino acid, nucleotide, and pigment biosynthetic pathways. Furthermore, model prediction of growth rates under various medium compositions and subsequent experimental validation showed an increased growth rate with the addition of tryptophan and methionine. Glossary KEGG Kyoto Encyclopedia of Genes and Genomes GPR gene/protein/reaction BOF biomass objective function TAG triacylglycerol PG phosphatidylglycerol PI phosphatidylinositol PE phosphatidylethanolamine MGDG monogalactosyldiacylglycerol MCC Matthews correlation coefficient PPP pentose phosphate pathway BBM Bold’s basal medium

Journal

Plant PhysiologyAmerican Society of Plant Biologist

Published: Sep 1, 2016

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