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Assessment of Cultivation Factors that Affect Biomass and Geraniol Production in Transgenic Tobacco Cell Suspension Cultures

机译:影响转基因烟草细胞悬浮培养中生物量和香叶醇产量的栽培因子的评估

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摘要

A large-scale statistical experimental design was used to determine essential cultivation parameters that affect biomass accumulation and geraniol production in transgenic tobacco (Nicotiana tabacum cv. Samsun NN) cell suspension cultures. The carbohydrate source played a major role in determining the geraniol yield and factors such as filling volume, inoculum size and light were less important. Sucrose, filling volume and inoculum size had a positive effect on geraniol yield by boosting growth of plant cell cultures whereas illumination of the cultures stimulated the geraniol biosynthesis. We also found that the carbohydrates sucrose and mannitol showed polarizing effects on biomass and geraniol accumulation. Factors such as shaking frequency, the presence of conditioned medium and solubilizers had minor influence on both plant cell growth and geraniol content. When cells were cultivated under the screened conditions for all the investigated factors, the cultures produced ∼5.2 mg/l geraniol after 12 days of cultivation in shaking flasks which is comparable to the yield obtained in microbial expression systems. Our data suggest that industrial experimental designs based on orthogonal arrays are suitable for the selection of initial cultivation parameters prior to the essential medium optimization steps. Such designs are particularly beneficial in the early optimization steps when many factors must be screened, increasing the statistical power of the experiments without increasing the demand on time and resources.
机译:大规模统计实验设计用于确定影响转基因烟草(Nicotiana tabacum cv。Samsun NN)细胞悬浮培养物中生物量积累和香叶醇产量的基本培养参数。碳水化合物来源在确定香叶醇产量中起主要作用,而诸如填充量,接种量和光照等因素则不那么重要。蔗糖,灌装量和接种量通过促进植物细胞培养物的生长而对香叶醇的产量产生积极影响,而培养物的光照刺激了香叶醇的生物合成。我们还发现,碳水化合物蔗糖和甘露醇对生物量和香叶醇的蓄积具有极化作用。诸如振荡频率,条件培养基和增溶剂的存在等因素对植物细胞生长和香叶醇含量均具有较小的影响。当在筛选条件下针对所有研究的因素培养细胞时,在摇瓶中培养12天后,培养物产生约5.2 mg / l香叶醇,这与微生物表达系统获得的产率相当。我们的数据表明,基于正交阵列的工业实验设计适合在基本培养基优化步骤之前选择初始培养参数。当必须筛选许多因素时,这样的设计在早期优化步骤中特别有益,从而可以在不增加时间和资源需求的情况下提高实验的统计能力。

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