Senger Ryan S, Karim M Nazmul
Department of Chemical and Biological Engineering, Northwestern University, 2145 Sheridan Road, Evanston, Illinois 60208, USA.
Biotechnol Bioeng. 2007 Oct 1;98(2):378-90. doi: 10.1002/bit.21428.
Optimization of fed-batch feeding parameters was explored for a system with multiple mechanisms of product inactivation. In particular, two separate mechanisms of inactivation were identified for the recombinant tissue-type activator (r-tPA) protein. Dynamic inactivation models were written to describe particular r-tPA glycoform inactivation in the presence and absence of free-glucose. A glucose-independent inactivation mechanism was identified, and inactivation rate constants were found dependent upon the presence of glycosylation of r-tPA at N184. Inactivation rate constants of the glucose-dependent mechanism were not affected by glycosylation at N184. Fed-batch optimization was performed for r-tPA production by CHO cell culture in a stirred-tank reactor with glucose, glutamine and asparagine feed. Feeding profiles in which culture supernatant concentrations of free-glucose and amino acids (combined glutamine and asparagine) were used as control variables, were evaluated for a wide variety of set points. Simulation results for a controlled feeding strategy yielded an optimum at set points of 1.51 g L(-1) glucose and 1.18 g L(-1) of amino acids. Optimization was also performed in absence of metabolite control using fixed feed-flow rates initiate during the exponential growth phase. Fixed feed-flow results displayed a family of optimum solutions along a mass flow rate ratio of 3.15 of glucose to amino acids. Comparison of the two feeding strategies showed a slight advantage of rapid feeding at a fixed flow rate as opposed to metabolite control for a product with multiple mechanisms of inactivation.
针对具有多种产物失活机制的系统,研究了补料分批培养补料参数的优化。具体而言,确定了重组组织型纤溶酶原激活剂(r-tPA)蛋白的两种不同失活机制。编写了动态失活模型,以描述在存在和不存在游离葡萄糖的情况下特定r-tPA糖型的失活。确定了一种不依赖葡萄糖的失活机制,发现失活速率常数取决于r-tPA在N184处的糖基化情况。依赖葡萄糖的机制的失活速率常数不受N184处糖基化的影响。在搅拌罐反应器中,通过CHO细胞培养生产r-tPA,并使用葡萄糖、谷氨酰胺和天冬酰胺补料进行补料分批优化。将游离葡萄糖和氨基酸(谷氨酰胺和天冬酰胺的总和)的培养上清液浓度用作控制变量的补料曲线,针对各种设定点进行了评估。受控补料策略的模拟结果在葡萄糖设定点为1.51 g L(-1)和氨基酸设定点为1.18 g L(-1)时产生了最佳值。还在没有代谢物控制的情况下进行了优化,在指数生长期开始时使用固定的补料流速。固定补料流速结果显示了一系列最佳解决方案,葡萄糖与氨基酸的质量流速比为3.15。两种补料策略的比较表明,对于具有多种失活机制的产物,与代谢物控制相比,固定流速快速补料具有轻微优势。