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Application of medium optimization tools for improving recombinant human interferon gamma production from Kluyveromyces lactis.
Preparative Biochemistry & Biotechnology 2018 March 17
The present study is focused upon improving biomass of Kluyveromyces lactis cells expressing recombinant human interferon gamma (hIFN-γ), with the aim of augmenting hIFN-γ concentration using statistical and artificial intelligence approach. Optimization of medium components viz., lactose, yeast extract, and trace elements were performed with Box-Behnken design (BBD) and artificial neural network linked genetic algorithm (ANN-GA) for maximizing biomass of recombinant K. lactis (objective function). The studies resulted over 1.5-fold improvement in the biomass concentration in a medium composed of 80 g/L lactose, 10.353 g/L yeast extract, and 15 mL/L trace elements as compared with initial biomass value. In the same study hIFN-γ concentration reached 881 µg/L which was 2.28-fold higher as compared with initial hIFN-γ concentration obtained in unoptimized medium. Further the batch fermentation study displayed mixed growth associated kinetics with the maximum hIFN-γ production rate of 1.1 mg/L. BBD and ANN-GA, both optimization techniques predicted a higher lactose concentration was clearly beneficial for augmenting K. lactis biomass which in turn increased hIFN-γ concentration.
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