Dataset Information

Biochemical modulation of growth, lipid quality and productivity in mixotrophic cultures of Chlorella sorokiniana.

ABSTRACT: The genus Chlorella is a widely employed microalga for biodiesel, as it can be grown using photo/mixo/heterotrophic mode of cultivation. The present investigation was undertaken with the hypothesis that addition of different substrates (amino acids, carbon sources, vitamins) along with reducing agents may aid in diverting Acetyl CoA to malonyl CoA or fatty acid biosynthesis, under mixotrophic conditions in Chlorella sorokiniana. Preliminary investigations undertaken with two reducing agents individually (sodium thiosulphate and methyl viologen) along with selected substrates revealed the promise of sodium thiosulphate (1%) in enhancing lipid accumulation significantly. Further, the role of inclusion of twelve substrates and sodium thiosulphate revealed that supplementation with tryptophan (0.1%) recorded 57.28% enhancement in lipid productivity on 4(th) day. Highest values of lipid productivity of 33% were recorded on 8(th) day in 0.1% glucose supplemented medium containing sodium thiosulphate. Fatty Acid Methyl Ester (FAME) profiles generated revealed significant reduction in the content of Poly unsaturated fatty acids (PUFA) and enhanced Mono unsaturated fatty acids (MUFA) (especially oleic acid) in the treatments involving tryptophan, Vitamin B12, sodium pyruvate and glucose. This study reveals the promise of using sodium thiosulphate along with selected substrate for enriching the quality and quantity of lipids, which can be valuable for exploiting algae as a source of biodiesel.

SUBMITTER: Ngangkham M

PROVIDER: S-EPMC3725904 | biostudies-other | 2012

REPOSITORIES: biostudies-other

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Biochemical modulation of growth, lipid quality and productivity in mixotrophic cultures of Chlorella sorokiniana.

Ngangkham Momocha M Ratha Sachitra Kumar SK Prasanna Radha R Saxena Anil Kumar AK Dhar Dolly Wattal DW Sarika Chandragiri C Prasad Rachapudi Badari Narayana RB

SpringerPlus 20121006

The genus Chlorella is a widely employed microalga for biodiesel, as it can be grown using photo/mixo/heterotrophic mode of cultivation. The present investigation was undertaken with the hypothesis that addition of different substrates (amino acids, carbon sources, vitamins) along with reducing agents may aid in diverting Acetyl CoA to malonyl CoA or fatty acid biosynthesis, under mixotrophic conditions in Chlorella sorokiniana. Preliminary investigations undertaken with two reducing agents indi ...[more]

PMID: 23961362

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Project description: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.

Dataset Information

Biochemical modulation of growth, lipid quality and productivity in mixotrophic cultures of Chlorella sorokiniana.

Publications

Biochemical modulation of growth, lipid quality and productivity in mixotrophic cultures of Chlorella sorokiniana.

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