Gayen Kalyan, Venkatesh K V
Department of Chemical Engineering, Indian Institute of Technology Bombay, Powai, Mumbai 400076, India.
J Ind Microbiol Biotechnol. 2007 May;34(5):363-72. doi: 10.1007/s10295-007-0205-9. Epub 2007 Jan 26.
Corynebacterium glutamicum is commonly used for lysine production. In the last decade, several metabolic engineering approaches have been successfully applied to C. glutamicum. However, only few studies have been focused on the kinetics of growth and lysine production. Here, we present a phenomenological model that captures the growth and lysine production during different phases of fermentation at various initial dextrose concentrations. The model invokes control coefficients to capture the dynamics of lysine and trehalose synthesis. The analysis indicated that maximum lysine productivity can be obtained using 72 g/L of initial dextrose concentration in the media, while growth was optimum at 27 g/L of dextrose concentration. The predictive capability was demonstrated through a two-stage fermentation strategy to enhance the productivity of lysine by 1.5 times of the maximum obtained in the batch fermentation. Two-stage fermentation indicated that the kinetic model could be further extended to predict the optimal feeding strategy for fed-batch fermentation.
谷氨酸棒杆菌常用于赖氨酸生产。在过去十年中,几种代谢工程方法已成功应用于谷氨酸棒杆菌。然而,只有少数研究关注生长动力学和赖氨酸生产。在此,我们提出一个现象学模型,该模型能够捕捉在不同初始葡萄糖浓度下发酵不同阶段的生长和赖氨酸生产情况。该模型引入控制系数来描述赖氨酸和海藻糖合成的动态变化。分析表明,培养基中初始葡萄糖浓度为72 g/L时可获得最大赖氨酸生产率,而葡萄糖浓度为27 g/L时生长最佳。通过两阶段发酵策略证明了该模型的预测能力,该策略可使赖氨酸生产率提高至分批发酵中获得的最大值的1.5倍。两阶段发酵表明,动力学模型可进一步扩展以预测补料分批发酵的最佳补料策略。