Advances in metabolic modeling of oleaginous microalgae

Abstract

Production of biofuels and bioenergy precursors by phototrophic microorganisms, such as microalgae and cyanobacteria, is a promising alternative to conventional fuels obtained from non-renewable resources. Several species of microalgae have been investigated as potential candidates for the production of biofuels, for the most part due to their exceptional metabolic capability to accumulate large quantities of lipids. Constraint-based modeling, a systems biology approach that accurately predicts the metabolic phenotype of phototrophs, has been deployed to identify suitable culture conditions as well as to explore genetic enhancement strategies for bioproduction. Core metabolic models were employed to gain insight into the central carbon metabolism in photosynthetic microorganisms. More recently, comprehensive genome-scale models, including organelle-specific information at high resolution, have been developed to gain new insight into the metabolism of phototrophic cell factories. Here, we review the current state of the art of constraint-based modeling and computational method development and discuss how advanced models led to increased prediction accuracy and thus improved lipid production in microalgae.

MetaNetX/MNXref - unified namespace for metabolites and biochemical reactions in the context of metabolic models

“…Beyond popular applications, such as metabolic flux prediction with flux balance analysis and prediction of the gene essentiality, GSMNs have been used in numerous applications (38) , e.g. chemicals and materials production (39)(40)(41)(42) , drug targeting (43,44) , human metabolism, disease understanding (45,46) and, multi-organism interaction modeling (47,48) . MNXref is now used within tools for testing GSMNs such as MEMOTE (49) , and has been proposed as a reference for minimal standard content for metabolic network reconstruction (50) .…”

Cultivation of Oily Microalgae for the Production of Third-Generation Biofuels

“…On the basis of the metabolic pathway, one can select the growth condition of the microalgae as autotrophs, heterotrophs, or mixotrophs. Biomass yield under mixotrophic conditions is higher than that of heterotrophy [5,12,20]. Microalgae are adapted to transform their internal structure (biochemical and physiological acclimation) according to the available situations.…”

Dynamic resource allocation drives growth under nitrogen starvation in eukaryotes

“…On the other hand, nitrogen depletion has been proven to selectively decrease the synthesis of proteins and nucleic acids, triggering a metabolic response that upregulates the synthesis of carbon-rich compounds 13 . Previous studies on the metabolic response mechanism to nitrogen depletion have identified key signal metabolites 13 and global biomass composition trends 14,15 . However, an in-depth analysis at the genome scale has not yet been employed to understand how metabolic pathway use changes to survive in nutrient-deplete conditions.…”

“…However, an in-depth analysis at the genome scale has not yet been employed to understand how metabolic pathway use changes to survive in nutrient-deplete conditions. M-model simulations allow to identify main metabolic reactions driving growth phenotypes under diverse genetic and environmental conditions 15,16 . Using a reduced number of known uptake rates, or constraints 17 , M-model simulations predict growth and flux distributions (phenotypes) under diverse genetic and environmental conditions, identifying the main drivers of metabolism 14 .…”