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Optimization And Control Of Culture Condition For Isoflavone Production Of Maackia Amurensis Through Plant Cell Engineering

Posted on:2006-10-15Degree:MasterType:Thesis
Country:ChinaCandidate:K LuoFull Text:PDF
GTID:2121360152990362Subject:Agricultural Products Processing and Storage
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Maackia amurensis, a precious wild medicinal plant in China, is known for its functional element isoflavones, which have marked pharmacological effects, such as hepatoprotection, antitumor, antioxidation and osteoporosis inhibition. However, it is becoming exhausted. In order to provide a foundation for sustainable utilization of the medicinal metabolite resource of M amurensis through plant cell engineering on a large scale, this thesis aimed at optimizing and controlling culture condition for isoflavone production of Maackia amurensis suspension cell cultures. Furthermore, the obtained culture conditions were valuated by culturing cells in 10 L air-lift bioreactor.On the basis of singer-factor, optimal medium for isoflavone production in Maackia amurensis suspension cells has been developed through the artificial neural networks (ANNs) and the real coding based accelerating genetic algorithm (RAGA). According to the prediction of the model, the optimum combination of four factors for genistein production was obtained as follows: 149.68 mg/L of (NH)2SO4, 2936.10 mg/L of KNO3, 0.01 mg/L of 2,4-D and 0.19 mg/L of 6-BA, respectively. The yield of genistein under this combination amounted to 14.13 mg/L, but the result of orthogonal experiments only arrived 5.76 mg/L, and its relative error between experimental value and predictive value was 7.38%. The results suggested that this model was feasible for optimizing medium components in Maackia amurensis cell culture.According to in vitro and in vivo metabolism of sucrose in culture medium, a structured kinetic model, which described the cell growth, sucrose uptake, structure components production, intermediate matter changes, cell respiration loss and secondary metabolite production, has been formulated and applied to batch suspension culture of Maackia amurensis cells. By methods of Runge-Kutta and no-linear Powell to gain and optimize parameters, the best combination was obtained. The results showed a high fit between the experimental data and the model and can been used to predict growth and isoflavone production of Maackia amurensis cultured cells.Effect of temperature on cell growth and genestein production in cell suspension cultures of Maackia amurensis was investigated. The results revealed that 25 ℃ was suitable for genistein accumulation and 28 ℃ for cell growth. According to kinetic changes of cell growth and genistein production at different temperatures, the culture temperature shift from 28 ℃ for the first nine days to 25 ℃ for another 3 days was applied. It was found that genistein production was 1.14 and 2.50- fold higher than that obtained at 25℃ and 28℃, respectively. Experiment in 10 L air-lift bioreactor showed that genesitein production of cultured cells could reach 26.66 mg/L by the temperature shift operation.
Keywords/Search Tags:Maackia amurensis, suspension culture, isoflavone, artificial neural networks, accelerating genetic algorithm, structure model, temperature shift, air-lift bioreactor
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