Presentation Information
[P04-557]Construction of a Genome Scale Metabolic Modelof the Oleaginous Diatom Fistulifera solaris
○Tomoki Mizoguchi1, Tsuyoshi Tanaka1 (1. Tokyo University of Agriculture and Technology (Japan))
Keywords:
Microalgae,Oleaginous diatom,Genome-scale metabolic model,Flux balance analysis
Purpose
The oleaginous diatom Fistulifera solaris is a promising host for converting CO2 into valuable bioproducts because of its high lipid productivities. However, rational strain improvement is still hindered by limited understanding of intracellular metabolite network across subcellular compartments. To enable more efficient and predictive strain optimization, genome scale metabolic models (GEMs), which represent comprehensive intracellular reaction networks based on genome annotations, provide a quantitative framework for metabolic engineering. Although GEMs have been constructed for centric diatoms so far, it remains unclear whether these models are applicable to pennate diatoms, including F. solaris, which are evolutionarily distant lineage from centric diatoms. Therefore, this study aimed to construct a GEM of F. solaris based on a centric diatom GEM to establish a metabolic engineering platform for enhancing strain optimization.
Method
F.solaris was cultivated in f/2 medium at 25°C under continuous illumination (140 umol photons m-2 s-1) with 2% CO2 for 48 h. After cultivation, the biomass composition, including protein, carbohydrate, neutral lipid, and total lipid contents, was quantified to construct a biomass reaction. Time course changes in biomass and nitrate concentrations were measured to calculate the specific growth rate and nitrate uptake rate during cultivation. Metabolic enzyme candidate was identified by homology searches against a centric diatom Thalassiosira pseudonana GEM, and by protein domain analysis using InterProScan. Subcellular localization was predicted using ASAFind, HECTAR, and Mitoprot. Based on these results, metabolic reactions we are reconstructed using the RAVEN Toolbox.Results&Consideration
Using T. pseudonana GEM as a template, 1399 enzymes in F. solaris were identified by homology. Predicted subcellular localizations were then incorporated into the draft GEM. The resulting model comprises 6916 genes and 2630 reactions. A biomass objective function for constraint metabolic flux was defined based on experimentally determined biomass composition. To validate the draft GEMs, the experimentally determined nitrate uptake rate was applied as a constraint to calculate the specific growth rate of F. solaris. Incorporating subcellular localization predictions into the GEM did not affect model performance and the final predicted growth rate was 6.74 × 10-2 h-1, yielding a relative error of 40.1% relative to the experimentally observed growth rate (1.12 × 10-1 h-1), comparable to those reported for other microalgal GEMs.
Conclusion
A genome scale metabolic model of F. solaris capable of simulating growth was successfully constructed.
The oleaginous diatom Fistulifera solaris is a promising host for converting CO2 into valuable bioproducts because of its high lipid productivities. However, rational strain improvement is still hindered by limited understanding of intracellular metabolite network across subcellular compartments. To enable more efficient and predictive strain optimization, genome scale metabolic models (GEMs), which represent comprehensive intracellular reaction networks based on genome annotations, provide a quantitative framework for metabolic engineering. Although GEMs have been constructed for centric diatoms so far, it remains unclear whether these models are applicable to pennate diatoms, including F. solaris, which are evolutionarily distant lineage from centric diatoms. Therefore, this study aimed to construct a GEM of F. solaris based on a centric diatom GEM to establish a metabolic engineering platform for enhancing strain optimization.
Method
F.solaris was cultivated in f/2 medium at 25°C under continuous illumination (140 umol photons m-2 s-1) with 2% CO2 for 48 h. After cultivation, the biomass composition, including protein, carbohydrate, neutral lipid, and total lipid contents, was quantified to construct a biomass reaction. Time course changes in biomass and nitrate concentrations were measured to calculate the specific growth rate and nitrate uptake rate during cultivation. Metabolic enzyme candidate was identified by homology searches against a centric diatom Thalassiosira pseudonana GEM, and by protein domain analysis using InterProScan. Subcellular localization was predicted using ASAFind, HECTAR, and Mitoprot. Based on these results, metabolic reactions we are reconstructed using the RAVEN Toolbox.Results&Consideration
Using T. pseudonana GEM as a template, 1399 enzymes in F. solaris were identified by homology. Predicted subcellular localizations were then incorporated into the draft GEM. The resulting model comprises 6916 genes and 2630 reactions. A biomass objective function for constraint metabolic flux was defined based on experimentally determined biomass composition. To validate the draft GEMs, the experimentally determined nitrate uptake rate was applied as a constraint to calculate the specific growth rate of F. solaris. Incorporating subcellular localization predictions into the GEM did not affect model performance and the final predicted growth rate was 6.74 × 10-2 h-1, yielding a relative error of 40.1% relative to the experimentally observed growth rate (1.12 × 10-1 h-1), comparable to those reported for other microalgal GEMs.
Conclusion
A genome scale metabolic model of F. solaris capable of simulating growth was successfully constructed.
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