2016
DOI: 10.1104/pp.16.00593
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Genome-Scale Metabolic Model for the Green Alga Chlorella vulgaris UTEX 395 Accurately Predicts Phenotypes under Autotrophic, Heterotrophic, and Mixotrophic Growth Conditions

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 … Show more

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Cited by 84 publications
(85 citation statements)
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“…PCC 6803 GSMFBA6777596016143 [45] Tetraselmis sp.GSMFBA22491725186242 [47] d Tisochrysis lutea CMEM15716222 [50]

Metabolic models are classified into two different groups: Genome - scale metabolic models (GSM) and core models (CM). The analyses were classified in: flux balance analysis (FBA), dynamic FBA (dFBA), elementary modes (EM), metabolic flux analysis (MFA), MFA using 13 C tracer ( 13 C MFA), and their combinations a Modified the metabolic model of C. reinhardtii from Cogne et al [27] b Modified the metabolic model of C. reinhardtii from Chang et al [26] c Used the genome-scale model of C. vulgaris from Zuñiga et al [32] d Used the genome-scale model of C. reinhardtii from Dal’Molin et al [25] with constraints for Tetraselmis sp.

Fig. 1Key developments in constraint-based metabolic modeling of oleaginous microalgae.
…”
Section: Introductionmentioning
confidence: 99%
“…PCC 6803 GSMFBA6777596016143 [45] Tetraselmis sp.GSMFBA22491725186242 [47] d Tisochrysis lutea CMEM15716222 [50]

Metabolic models are classified into two different groups: Genome - scale metabolic models (GSM) and core models (CM). The analyses were classified in: flux balance analysis (FBA), dynamic FBA (dFBA), elementary modes (EM), metabolic flux analysis (MFA), MFA using 13 C tracer ( 13 C MFA), and their combinations a Modified the metabolic model of C. reinhardtii from Cogne et al [27] b Modified the metabolic model of C. reinhardtii from Chang et al [26] c Used the genome-scale model of C. vulgaris from Zuñiga et al [32] d Used the genome-scale model of C. reinhardtii from Dal’Molin et al [25] with constraints for Tetraselmis sp.

Fig. 1Key developments in constraint-based metabolic modeling of oleaginous microalgae.
…”
Section: Introductionmentioning
confidence: 99%
“…C. variabilis , i AJ526, was reconstructed with 526 genes, 1445 reactions and 1236 metabolites based on C. variabilis NC64A strain under three light sources [77]. The model for C. vulgaris UTEX 395, i CZ843, is the most comprehensive reconstruction (843 genes, 2294 reactions, and 1770 metabolites) [78] of the Chlorella models. Importantly, this reconstruction makes use of the Biolog phenotype microarray platform [70,79] to validate some reactions and pathways.…”
Section: Approaches For Developing Algal Cell Factoriesmentioning
confidence: 99%
“…Several species of Chlorella have been proposed or have already been used commercially over the past 40 years as a food and feed supplement because of their fast growth and their high resistance to biotic and abiotic stresses (Lum et al ., ). Chlorella vulgaris is one of the most cultivated species at the industrial scale because of the high biomass yield and the possibility to grow either in autotrophic or mixotrophic conditions, in the latter case with the addition of reduced carbon source to further improve the biomass yield (Lv et al ., ; Zuniga et al ., ).…”
Section: Introductionmentioning
confidence: 97%
“…Among the many candidates of algal strains for biotechnological applications, a genus of considerable interest is Chlorella (Blanc et al ., ; Juneja et al ., ; Zuniga et al ., ; Sarayloo et al ., ; Arriola et al ., ). Several species of Chlorella have been proposed or have already been used commercially over the past 40 years as a food and feed supplement because of their fast growth and their high resistance to biotic and abiotic stresses (Lum et al ., ).…”
Section: Introductionmentioning
confidence: 99%