Abstract
BackgroundThe green microalga Dunaliella salina accumulates a high proportion of β-carotene during abiotic stress conditions. To better understand the intracellular flux distribution leading to carotenoid accumulation, this work aimed at reconstructing a carbon core metabolic network for D. salina CCAP 19/18 based on the recently published nuclear genome and its validation with experimental observations and literature data.ResultsThe reconstruction resulted in a network model with 221 reactions and 212 metabolites within three compartments: cytosol, chloroplast and mitochondrion. The network was implemented in the MATLAB toolbox CellNetAnalyzer and checked for feasibility. Furthermore, a flux balance analysis was carried out for different light and nutrient uptake rates. The comparison of the experimental knowledge with the model prediction revealed that the results of the stoichiometric network analysis are plausible and in good agreement with the observed behavior. Accordingly, our model provides an excellent tool for investigating the carbon core metabolism of D. salina.ConclusionsThe reconstructed metabolic network of D. salina presented in this work is able to predict the biological behavior under light and nutrient stress and will lead to an improved process understanding for the optimized production of high-value products in microalgae.
Highlights
Microalgae received increased attention over recent years due to their ability to produce high-value compounds such as polyunsaturated fatty acids and carotenoids [1, 2, 3]
The size of the metabolic network for D. salina is in the range of some previously published reduced networks for green microalgae
As algae of the genus Dunaliella and Chlamydomonas are closely related, because they both belong to the order of Volvocales [44], a comparison of annotated enzymes for the calvin cycle, the carbon-core metabolism and the isoprenoid biosynthesis of D. salina and C. reinhardtii showed a high degree of similarity [41]
Summary
Microalgae received increased attention over recent years due to their ability to produce high-value compounds such as polyunsaturated fatty acids and carotenoids [1, 2, 3]. The construction of dynamic-kinetic growth models using ordinary differential equations (ODEs) is a well-established formalism in bioprocess engineering These models allow for prediction of biomass growth, nutrient uptake and metabolite production and enable the identification of bottlenecks in the process setup for lab-scale as well as large-scale outdoor cultivation systems [9, 10, 11]. These simplified growth models are robust and computationally inexpensive, they might be only valid for a certain range of environmental conditions and have limited predictive capabilities for extrapolation outside the experimental region [12]. To better understand the intracellular flux distribution leading to carotenoid accumulation, this work aimed at reconstructing a carbon core metabolic network for D. salina CCAP 19/18 based on the recently published nuclear genome and its validation with experimental observations and literature data
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
