Dataset Information

Utilizing genome-scale models to optimize nutrient supply for sustained algal growth and lipid productivity.

ABSTRACT: Nutrient availability is critical for growth of algae and other microbes used for generating valuable biochemical products. Determining the optimal levels of nutrient supplies to cultures can eliminate feeding of excess nutrients, lowering production costs and reducing nutrient pollution into the environment. With the advent of omics and bioinformatics methods, it is now possible to construct genome-scale models that accurately describe the metabolism of microorganisms. In this study, a genome-scale model of the green alga Chlorella vulgaris (iCZ946) was applied to predict feeding of multiple nutrients, including nitrate and glucose, under both autotrophic and heterotrophic conditions. The objective function was changed from optimizing growth to instead minimizing nitrate and glucose uptake rates, enabling predictions of feed rates for these nutrients. The metabolic model control (MMC) algorithm was validated for autotrophic growth, saving 18% nitrate while sustaining algal growth. Additionally, we obtained similar growth profiles by simultaneously controlling glucose and nitrate supplies under heterotrophic conditions for both high and low levels of glucose and nitrate. Finally, the nitrate supply was controlled in order to retain protein and chlorophyll synthesis, albeit at a lower rate, under nitrogen-limiting conditions. This model-driven cultivation strategy doubled the total volumetric yield of biomass, increased fatty acid methyl ester (FAME) yield by 61%, and enhanced lutein yield nearly 3 fold compared to nitrogen starvation. This study introduces a control methodology that integrates omics data and genome-scale models in order to optimize nutrient supplies based on the metabolic state of algal cells in different nutrient environments. This approach could transform bioprocessing control into a systems biology-based paradigm suitable for a wide range of species in order to limit nutrient inputs, reduce processing costs, and optimize biomanufacturing for the next generation of desirable biotechnology products.

SUBMITTER: Li CT

PROVIDER: S-EPMC6760154 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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Utilizing genome-scale models to optimize nutrient supply for sustained algal growth and lipid productivity.

Li Chien-Ting CT Yelsky Jacob J Chen Yiqun Y Zuñiga Cristal C Eng Richard R Jiang Liqun L Shapiro Alison A Huang Kai-Wen KW Zengler Karsten K Betenbaugh Michael J MJ

NPJ systems biology and applications 20190924

Nutrient availability is critical for growth of algae and other microbes used for generating valuable biochemical products. Determining the optimal levels of nutrient supplies to cultures can eliminate feeding of excess nutrients, lowering production costs and reducing nutrient pollution into the environment. With the advent of omics and bioinformatics methods, it is now possible to construct genome-scale models that accurately describe the metabolism of microorganisms. In this study, a genome-s ...[more]

PMID: 31583115

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Project description:Diversity and productivity of primary producers are known to be influenced simultaneously by resource availability and resource ratio, but the relative importance of these two factors differed among studies and so far only entire phytoplankton communities were investigated which might ignore specific nutrient requirements and stoichiometric plasticity of different functional groups. We measured nutrient availability (DIN, total N [TN], total P [TP]), nutrient imbalance (TN:TP, DIN:TP, N:Pseston), species richness, and abundance of the whole phytoplankton community, as well as those specific for cyanobacteria, diatoms, and dinoflagellates in Cau Hai lagoon in Vietnam. We determined the correlation among these variables, using structural equation modeling. The models applied to the whole phytoplankton community indicated that the nutrient availability (particularly TP and DIN) drove variation in phytoplankton abundance and richness, and that abundance also depended on species richness. The models applied to different functional groups differed considerably from the entire community and among each other, and only a part of the models was significant. The relationship between nutrient availability (mainly TP) and abundance was driven by cyanobacteria, and the relationship between nutrient imbalance (only with N:Pseston) and species richness was driven by diatoms. Remarkably, the positive relationship between species richness and abundance, as consistently observed for the whole phytoplankton community, was only observed for one of the three functional groups (diatoms), indicating that resource complementarity occurs particularly among species of different functional groups. Our results emphasized that nutrient availability (TP and to a lesser extent DIN) as well as nutrient imbalance (albeit only with N:Pseston as proxy) were driving factors for the phytoplankton community in the Cau Hai lagoon and hence alterations in both of these factors leading to a shift in phytoplankton species composition and productivity.

Dataset Information

Utilizing genome-scale models to optimize nutrient supply for sustained algal growth and lipid productivity.

Publications

Utilizing genome-scale models to optimize nutrient supply for sustained algal growth and lipid productivity.

Similar Datasets

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