CHO工程细胞无血清流加培养代谢动力学及转录谱特征研究
|
摘要
中国仓鼠细胞(Chinese hamster ovary cell)及其无血清流加培养是目前包括工程抗体和重组蛋白在内的生物技术药物生产的最为重要的表达系统和工艺技术。CHO工程细胞无血清流加培养工艺技术的提升,在很大程度上有赖于对无血清流加培养条件下CHO工程细胞代谢动力学的深入了解。据此,本研究的主要目的在于应用MATLAB软件,采用全局收敛的Levenberg-Marquardt法,对CHO工程细胞无血清流加培养的细胞生长、底物消耗及流加速率的模型参数进行非线性规划,获得全局性收敛的最优参数估计值,建立CHO工程细胞无血清流加培养的生长及代谢动力学模型,为CHO工程细胞无血清流加培养的优化控制提供可参考的理论依据。同时,结合基因组学研究对细胞培养工程渗透和推动的技术发展趋势,本研究拟通过运用基因芯片技术考察CHO工程细胞在无血清流加培养模式下的转录谱特征,借于了解CHO工程细胞不同生长及代谢状态的内在原因,为探寻促使细胞处于更为有效的生长和代谢状态的可能途径提供依据。
建立能够在一定程度上体现流加培养工艺特色和技术指标的CHO工程细胞无血清流加培养技术是开展课题研究的基础和前提。课题研究选用表达重组人尿激酶原的CHO工程细胞为研究对象,在细胞悬浮体系中引入Pluronic F-68和硫酸葡聚糖,有效地消除了CHO工程细胞从静止贴附培养转入悬浮培养所引发的流体剪切力损伤和细胞聚结成团现象。与初转入悬浮培养的CHO工程细胞相比,悬浮培养适应的CHO工程细胞的平均比生长速率由0.27 d-1提高到0.48 d-1,最大细胞密度由2.5×106 cells/ml提高到6.3×106 cells/ml,悬浮适应前后CHO工程细胞的代谢特征基本相同。
应用Plackett-Burman方法及响应面方法,设计了一种适合CHO工程细胞悬浮培养的无血清培养基。CHO工程细胞在无血清培养基中批次培养的最大细胞密度为4.2×106 cells/ml,较CHO工程细胞在含血清培养基中批次培养的最大细胞密度约提高1.7倍;相应地CHO工程细胞表达的目标蛋白的最大生产浓度较其在含血清培养基中约提高1.6倍。与国外商品化的CHO细胞无血清培养基相比,所设计的CHO工程细胞无血清培养基不逊于国外同类培养基的培养效果。在此基础上通过对流加起始时间、初始接种密度、流加培养基中的不同营养成分及底物控制策略对CHO工程细胞流加培养效果的考察,初步建立了CHO工程细胞无血清流加培养的工艺技术。在12 d流加培养过程中CHO工程细胞的最大生长密度达到7.8×106 cells/ml、目标蛋白最大累积活性为8875 IU/ml,分别比批次培养提高85.7%和50.9%。
基于完整的流加培养过程可大致分为批次培养及流加培养两个阶段,为了更翔实的反映细胞在两个阶段的生长及代谢特征,分别研究了细胞无血清批次培养及流加培养的生长及代谢动力学。在细胞无血清批次培养的动力学研究中,依据细胞生长、底物消耗及产物形成的相关经验模型,并根据实际检测的实验数据,应用MATLAB软件,采用全局收敛的Levenberg-Marquardt法,对CHO工程细胞无血清批次培养对数生长期的细胞生长、葡萄糖消耗及乳酸生成的模型参数进行非线性规划,获得全局性收敛的最优参数估计值,建立了无血清批次培养细胞对数生长期的生长及代谢动力学模型。所建模型与实测数据吻合度较好,基本反映了CHO工程细胞无血清批次培养对数生长期的细胞生长、葡萄糖消耗及乳酸产出的内在规律。在此基础上,依据流加培养相关的细胞生长、底物消耗及流加速率的经验模型及实际检测数据,应用MATLAB软件,采用全局收敛的Levenberg-Marquardt法,对CHO工程细胞无血清流加培养的细胞生长、底物消耗及流加频率的模型参数进行非线性规划,获得全局性收敛的最优参数估计值,建立了CHO工程细胞无血清流加培养的生长及代谢动力学模型和依此为指导近似指数的间歇式流加策略,并在2 L搅拌罐式生物反应器中验证了代谢动力学模型用于指导CHO工程细胞无血清流加培养的优化控制的可行性。
运用基因芯片技术比较了CHO工程细胞在批次培养及流加培养不同培养阶段基因表达水平的差异,同时采用Genmapp软件,结合已知的细胞代谢途径或信号通路图,着重分析了两种培养模式下有关细胞糖代谢、凋亡及细胞周期的基因差异。结果表明基因芯片大致涉及的19191个目标基因中,下调表达的基因数量多于上调表达基因数目,且两种培养模式下的基因差异表达有着明显的不同,尤其是在培养的衰退期,流加培养下调表达的基因数量明显多于批次培养。根据有关糖酵解及三羧酸循环关键调控基因的差异表达情况,提示在批次培养方式下,CHO细胞对葡萄糖的利用更多的是进行糖酵解途径;在流加培养阶段由于酵解途径关键调控基因表达的下调,有可能减少细胞了葡萄糖不完全氧化的比例,进而提高了细胞葡萄糖完全氧化的比例,解释了细胞在两种培养方式下代谢的差异性。CHO细胞在两种培养模式下涉及细胞凋亡的两条主要途径中的大多数促使细胞凋亡的关键基因,在培养的整个过程中的表达均没有明显差异,仅有少数基因表达发生了变化,印证了流式细胞仪检测细胞凋亡的比例结果。依据有关调控细胞周期的关键基因的表达,表明CHO细胞主要是通过下调表达CDKs、cyclin及CKI家族中的Cdk6、Cdk2、Cdc2a、Ccne1、Ccne2基因及上调表达Smad4基因,来达到调控细胞增殖及维持自身活力的目的,较好的解释了细胞在两种培养模式下细胞周期分布的差异性。
综合上述结果表明,基于MATLAB软件及采用全局收敛的Levenberg-Marquardt法的CHO工程细胞无血清流加培养代谢动力学模型,能较为真实的反映实际培养过程中细胞生长及流加速率的变化,并为实现CHO工程细胞无血清流加培养的优化控制提供预见性指导。此外,针对CHO工程细胞无血清流加培养的基因转录谱特征的研究,不仅有助于阐明CHO工程细胞批次培养及流加培养的细胞生长及代谢差异的内在原因,也为探寻促使细胞保持更为有效的生长和代谢状态的可能途径提供线索。
CHO cells (Chinese hamster ovary cell) is presently the most important expression systems for engineering antibodies and recombinant protein and serum-free fed-batch culture is also the most important process for biopharmaceuticals production. Deeply Understanding CHO cells metabolic dynamics would be favor of improving serum-free fed-batch CHO cells culture technology. Accordingly, the main purpose of this study is to establish the dynamic model of cell growth and metabolism and build the approximate index intermittent fed-batch strategy in order to provide the reference theory for achieving optimal control of serum-free fed-batch culture. The global convergence optimal parameters of cell growth, substrate consumption and feed frequency were estimated by non-linear programming through using the global convergence Levenberg-Marquardt method based on MATLAB software. At the same time, according to the infiltration and promotion impact of genomics research on cell culture technology development, the gene transcription characteristics of the cells cultured in serum-free fed-batch mode was investigated by using gene chip technology in order to understand the underlying reasons about the growth and metabolic characteristics of the cells cultured in serum-free fed-batch mode and provide clues for exploring the possible way to promote cells in more effective growth and metabolism state.
Establishment of a serum-free fed-batch CHO cells culture paltform which can reflect a certain extent about the characteristics and technical indexes of fed-batch culture process was the basis and premise for this research. The recombinant CHO cells expressing recombinant human pro-urokinase (Pro-UK) as the object of study. And both the cells cluster and injury in suspension culture due to the shear stress were effectively eliminated by adding Pluronic F-68 and dextran sulfate. Compared with the original cells, the average growth rate of the cells adapted to suspension culture in logarithmic phase increases from 0.27-1 to 0.48-1, and the highest viable cell density, increased from 2.5×106 cells/ml to 6.3×106 cells/ml. It was shown that the cells adapted to suspension culture showed similar metabolism characteristics to the original cells.
An appropriate serum-free medium for CHO cell suspension culture was formulated by application of Plackett-Burman and response surface method. The maximum cells density reached 4.2×106 cells/ml in serum-free suspension batch culture mode and was about 1.7 fold of that in 1% serum-containing suspension batch culture, correspondingly the maximum activity of interest increased about 1.6 fold.
A serum-free fed-batch CHO cells culture platform was established through investigating the impact of the start time of feeding, the initial cell inoculation density, the different culture components and substrate limits strategy on fed-batch culture. The results showed that the maximum cells density reached 7.8×106 cells/ml and the largest protein activity reached 8875 IU/ml in fed-batch culture during 12 d culture process, which were about 85.7% and 50.9% increase as compared with those of the batch culture, respectively.
In consideration of the fact that a whole fed-batch culture process is actually compose of both a batch culture stage and a feeding culture stage, The growth and metabolic characteristics of the cells in both serum-free batch culture stage and serum-free fed-batch culture stage was investigated individually. According to the established mathematical model of cell growth, substrate consumption and product formation, the optimal mathematical model parameters of logarithmic cell growth phase was estimated by non-linear programming using the global convergence of the Levenberg-Marquardt method and the MATLAB software based on the actual experimental data. The dynamic models of cell growth and metabolism in serum-free batch culture, which could match the experimental results and reflected essentially inherent orderliness about cell growth, glucose consumption and lactic acid production of the cells in logarithmic growth phase stage were established Further, according to the established mathematical model of cell growth, substrate consumption and feed frequency, the optimal mathematical model parameters of the cells in feeding culture stage were estimated by non-linear programming using the global convergence of the estimated Levenberg-Marquardt method and the MATLAB software again, based on the actual experimental data. Thus, the dynamic models of growth and metabolism of the cells in fed-batch serum-free culture and the approximate index for intermittent feeding strategy were established, which were approved to be feasibility in guiding serum-free fed-batch culture control in a 2 L bioreactor.
The differences of gene expression levels of the cells in different culture phase in both batch and fed-batch modes were revealed by using gene chip technology. And based on the known metabolic pathway or the cell signaling pathway, the expression level differences of genes related to glucose metabolism, apoptosis and cell cycle of the cells cultured in batch and fed-batch modes were analysed by using Genmapp software. Results from this study showed that among approximate 19,191 the target gene in gene chip, the number of down-regulated genes was higher than that of up-regulated genes of the cells in both batch and fed-batch culture. Further, the number of down-regulated genes of the cells in fed-batch culture was much higher than that of the cells in the recession phase of batch culture. The results suggested that more glucose was utilized through glycolysis pathway by the cells in batch culture according to the key regulatory genes expression of glycolysis and TCA cycle in batch culture and fed-batch culture process. And, due to down-regulated of the key genes regulated glycolysis in the fed-batch culture stage, its would potentially bring about reducing the ratio of glucose incomplete oxidation and increasing the ratio of glucose of complete oxidation of glycolytic. There was no significant difference in the gene expression, which were related to the key apoptosis pathways of the cells cultured in batch and fed-batch mode, only a few gene expression changed, which illuminated the results of cell apoptosis proportion by using flow cytometry. According to the key regulation gene expression of cell cycle in both culture mode, the results indicated that the cell proliferation and cells viability were mainly regulated through down-regulating Cdk6, Cdk2, Cdc2a, Ccne1, Ccne2 genes of CDKs, cyclin and CKI family and up-regulating Smad4 genes, which also explained clearly the differences of cell cycle distribution in culture mode. Overall, in two culture modes, the cells achieved controlling cell metabolism, proliferation and the cycle and responded to changed culture conditions through down-regulating gene expression with reference to cell metabolic pathway or signaling pathway.
The above results show that metabolism dynamics model of serum-free fed-batch cells culture based on the MATLAB software and the global convergence Levenberg-Marquardt method reflected the actual cell growth and culture volume change of fed-batch cell culture process and provided a theoretical reference basis for realizing optimal control in serum-free fed-batch CHO cells culture. At the same time, the study about gene transcription characteristics of the CHO cells cultured in serum-free fed-batch culture will not only help to clarify the underlying causes of cell growth and metabolism differences between the CHO cells cultured in batch mode and fed-batch mode as well as to provide clues for exploring possible ways to promote cells in a more effective growth and metabolism state.
建立能够在一定程度上体现流加培养工艺特色和技术指标的CHO工程细胞无血清流加培养技术是开展课题研究的基础和前提。课题研究选用表达重组人尿激酶原的CHO工程细胞为研究对象,在细胞悬浮体系中引入Pluronic F-68和硫酸葡聚糖,有效地消除了CHO工程细胞从静止贴附培养转入悬浮培养所引发的流体剪切力损伤和细胞聚结成团现象。与初转入悬浮培养的CHO工程细胞相比,悬浮培养适应的CHO工程细胞的平均比生长速率由0.27 d-1提高到0.48 d-1,最大细胞密度由2.5×106 cells/ml提高到6.3×106 cells/ml,悬浮适应前后CHO工程细胞的代谢特征基本相同。
应用Plackett-Burman方法及响应面方法,设计了一种适合CHO工程细胞悬浮培养的无血清培养基。CHO工程细胞在无血清培养基中批次培养的最大细胞密度为4.2×106 cells/ml,较CHO工程细胞在含血清培养基中批次培养的最大细胞密度约提高1.7倍;相应地CHO工程细胞表达的目标蛋白的最大生产浓度较其在含血清培养基中约提高1.6倍。与国外商品化的CHO细胞无血清培养基相比,所设计的CHO工程细胞无血清培养基不逊于国外同类培养基的培养效果。在此基础上通过对流加起始时间、初始接种密度、流加培养基中的不同营养成分及底物控制策略对CHO工程细胞流加培养效果的考察,初步建立了CHO工程细胞无血清流加培养的工艺技术。在12 d流加培养过程中CHO工程细胞的最大生长密度达到7.8×106 cells/ml、目标蛋白最大累积活性为8875 IU/ml,分别比批次培养提高85.7%和50.9%。
基于完整的流加培养过程可大致分为批次培养及流加培养两个阶段,为了更翔实的反映细胞在两个阶段的生长及代谢特征,分别研究了细胞无血清批次培养及流加培养的生长及代谢动力学。在细胞无血清批次培养的动力学研究中,依据细胞生长、底物消耗及产物形成的相关经验模型,并根据实际检测的实验数据,应用MATLAB软件,采用全局收敛的Levenberg-Marquardt法,对CHO工程细胞无血清批次培养对数生长期的细胞生长、葡萄糖消耗及乳酸生成的模型参数进行非线性规划,获得全局性收敛的最优参数估计值,建立了无血清批次培养细胞对数生长期的生长及代谢动力学模型。所建模型与实测数据吻合度较好,基本反映了CHO工程细胞无血清批次培养对数生长期的细胞生长、葡萄糖消耗及乳酸产出的内在规律。在此基础上,依据流加培养相关的细胞生长、底物消耗及流加速率的经验模型及实际检测数据,应用MATLAB软件,采用全局收敛的Levenberg-Marquardt法,对CHO工程细胞无血清流加培养的细胞生长、底物消耗及流加频率的模型参数进行非线性规划,获得全局性收敛的最优参数估计值,建立了CHO工程细胞无血清流加培养的生长及代谢动力学模型和依此为指导近似指数的间歇式流加策略,并在2 L搅拌罐式生物反应器中验证了代谢动力学模型用于指导CHO工程细胞无血清流加培养的优化控制的可行性。
运用基因芯片技术比较了CHO工程细胞在批次培养及流加培养不同培养阶段基因表达水平的差异,同时采用Genmapp软件,结合已知的细胞代谢途径或信号通路图,着重分析了两种培养模式下有关细胞糖代谢、凋亡及细胞周期的基因差异。结果表明基因芯片大致涉及的19191个目标基因中,下调表达的基因数量多于上调表达基因数目,且两种培养模式下的基因差异表达有着明显的不同,尤其是在培养的衰退期,流加培养下调表达的基因数量明显多于批次培养。根据有关糖酵解及三羧酸循环关键调控基因的差异表达情况,提示在批次培养方式下,CHO细胞对葡萄糖的利用更多的是进行糖酵解途径;在流加培养阶段由于酵解途径关键调控基因表达的下调,有可能减少细胞了葡萄糖不完全氧化的比例,进而提高了细胞葡萄糖完全氧化的比例,解释了细胞在两种培养方式下代谢的差异性。CHO细胞在两种培养模式下涉及细胞凋亡的两条主要途径中的大多数促使细胞凋亡的关键基因,在培养的整个过程中的表达均没有明显差异,仅有少数基因表达发生了变化,印证了流式细胞仪检测细胞凋亡的比例结果。依据有关调控细胞周期的关键基因的表达,表明CHO细胞主要是通过下调表达CDKs、cyclin及CKI家族中的Cdk6、Cdk2、Cdc2a、Ccne1、Ccne2基因及上调表达Smad4基因,来达到调控细胞增殖及维持自身活力的目的,较好的解释了细胞在两种培养模式下细胞周期分布的差异性。
综合上述结果表明,基于MATLAB软件及采用全局收敛的Levenberg-Marquardt法的CHO工程细胞无血清流加培养代谢动力学模型,能较为真实的反映实际培养过程中细胞生长及流加速率的变化,并为实现CHO工程细胞无血清流加培养的优化控制提供预见性指导。此外,针对CHO工程细胞无血清流加培养的基因转录谱特征的研究,不仅有助于阐明CHO工程细胞批次培养及流加培养的细胞生长及代谢差异的内在原因,也为探寻促使细胞保持更为有效的生长和代谢状态的可能途径提供线索。
CHO cells (Chinese hamster ovary cell) is presently the most important expression systems for engineering antibodies and recombinant protein and serum-free fed-batch culture is also the most important process for biopharmaceuticals production. Deeply Understanding CHO cells metabolic dynamics would be favor of improving serum-free fed-batch CHO cells culture technology. Accordingly, the main purpose of this study is to establish the dynamic model of cell growth and metabolism and build the approximate index intermittent fed-batch strategy in order to provide the reference theory for achieving optimal control of serum-free fed-batch culture. The global convergence optimal parameters of cell growth, substrate consumption and feed frequency were estimated by non-linear programming through using the global convergence Levenberg-Marquardt method based on MATLAB software. At the same time, according to the infiltration and promotion impact of genomics research on cell culture technology development, the gene transcription characteristics of the cells cultured in serum-free fed-batch mode was investigated by using gene chip technology in order to understand the underlying reasons about the growth and metabolic characteristics of the cells cultured in serum-free fed-batch mode and provide clues for exploring the possible way to promote cells in more effective growth and metabolism state.
Establishment of a serum-free fed-batch CHO cells culture paltform which can reflect a certain extent about the characteristics and technical indexes of fed-batch culture process was the basis and premise for this research. The recombinant CHO cells expressing recombinant human pro-urokinase (Pro-UK) as the object of study. And both the cells cluster and injury in suspension culture due to the shear stress were effectively eliminated by adding Pluronic F-68 and dextran sulfate. Compared with the original cells, the average growth rate of the cells adapted to suspension culture in logarithmic phase increases from 0.27-1 to 0.48-1, and the highest viable cell density, increased from 2.5×106 cells/ml to 6.3×106 cells/ml. It was shown that the cells adapted to suspension culture showed similar metabolism characteristics to the original cells.
An appropriate serum-free medium for CHO cell suspension culture was formulated by application of Plackett-Burman and response surface method. The maximum cells density reached 4.2×106 cells/ml in serum-free suspension batch culture mode and was about 1.7 fold of that in 1% serum-containing suspension batch culture, correspondingly the maximum activity of interest increased about 1.6 fold.
A serum-free fed-batch CHO cells culture platform was established through investigating the impact of the start time of feeding, the initial cell inoculation density, the different culture components and substrate limits strategy on fed-batch culture. The results showed that the maximum cells density reached 7.8×106 cells/ml and the largest protein activity reached 8875 IU/ml in fed-batch culture during 12 d culture process, which were about 85.7% and 50.9% increase as compared with those of the batch culture, respectively.
In consideration of the fact that a whole fed-batch culture process is actually compose of both a batch culture stage and a feeding culture stage, The growth and metabolic characteristics of the cells in both serum-free batch culture stage and serum-free fed-batch culture stage was investigated individually. According to the established mathematical model of cell growth, substrate consumption and product formation, the optimal mathematical model parameters of logarithmic cell growth phase was estimated by non-linear programming using the global convergence of the Levenberg-Marquardt method and the MATLAB software based on the actual experimental data. The dynamic models of cell growth and metabolism in serum-free batch culture, which could match the experimental results and reflected essentially inherent orderliness about cell growth, glucose consumption and lactic acid production of the cells in logarithmic growth phase stage were established Further, according to the established mathematical model of cell growth, substrate consumption and feed frequency, the optimal mathematical model parameters of the cells in feeding culture stage were estimated by non-linear programming using the global convergence of the estimated Levenberg-Marquardt method and the MATLAB software again, based on the actual experimental data. Thus, the dynamic models of growth and metabolism of the cells in fed-batch serum-free culture and the approximate index for intermittent feeding strategy were established, which were approved to be feasibility in guiding serum-free fed-batch culture control in a 2 L bioreactor.
The differences of gene expression levels of the cells in different culture phase in both batch and fed-batch modes were revealed by using gene chip technology. And based on the known metabolic pathway or the cell signaling pathway, the expression level differences of genes related to glucose metabolism, apoptosis and cell cycle of the cells cultured in batch and fed-batch modes were analysed by using Genmapp software. Results from this study showed that among approximate 19,191 the target gene in gene chip, the number of down-regulated genes was higher than that of up-regulated genes of the cells in both batch and fed-batch culture. Further, the number of down-regulated genes of the cells in fed-batch culture was much higher than that of the cells in the recession phase of batch culture. The results suggested that more glucose was utilized through glycolysis pathway by the cells in batch culture according to the key regulatory genes expression of glycolysis and TCA cycle in batch culture and fed-batch culture process. And, due to down-regulated of the key genes regulated glycolysis in the fed-batch culture stage, its would potentially bring about reducing the ratio of glucose incomplete oxidation and increasing the ratio of glucose of complete oxidation of glycolytic. There was no significant difference in the gene expression, which were related to the key apoptosis pathways of the cells cultured in batch and fed-batch mode, only a few gene expression changed, which illuminated the results of cell apoptosis proportion by using flow cytometry. According to the key regulation gene expression of cell cycle in both culture mode, the results indicated that the cell proliferation and cells viability were mainly regulated through down-regulating Cdk6, Cdk2, Cdc2a, Ccne1, Ccne2 genes of CDKs, cyclin and CKI family and up-regulating Smad4 genes, which also explained clearly the differences of cell cycle distribution in culture mode. Overall, in two culture modes, the cells achieved controlling cell metabolism, proliferation and the cycle and responded to changed culture conditions through down-regulating gene expression with reference to cell metabolic pathway or signaling pathway.
The above results show that metabolism dynamics model of serum-free fed-batch cells culture based on the MATLAB software and the global convergence Levenberg-Marquardt method reflected the actual cell growth and culture volume change of fed-batch cell culture process and provided a theoretical reference basis for realizing optimal control in serum-free fed-batch CHO cells culture. At the same time, the study about gene transcription characteristics of the CHO cells cultured in serum-free fed-batch culture will not only help to clarify the underlying causes of cell growth and metabolism differences between the CHO cells cultured in batch mode and fed-batch mode as well as to provide clues for exploring possible ways to promote cells in a more effective growth and metabolism state.
引文
1. Wer RG,Noe W,Kopp K,et al. Appropriate mammalian expression systems for biopharmaceuticals. Drug Res1998, 48: 870-880.
2.胡显文,陈惠鹏,汤仲明,马清钧.生物制药的现状和未来(一):历史与与现实市场.中国生物工程杂志, 2004, 24: 95-101
3. McKenna K A, Granados R R. Method for adpating anchorage-dependent cell lines to suspension conditions. US Patent, 1994, 5348877.
4. Dee K, Wood H A, Shuler M L. Inducing single cell suspension of BTI-TNSBI-4 insect cells:Ⅱthe effect of sulatfed polyanions on baculoviurs inefetion. Biotechnol Bioeng, 1997, 54: 206-220.
5. Zanghi J A, Renner W, Bailey J E, et al. The growth factor inhibitor surmain reduces apoptosis and aggregation in protein-free CHO cell batch cultures. Biotechnol Prog, 2000, 16: 319-325.
6. Taticek R A, McKennac K A, Granadose R R, et al. Rapid initiation of suspension cultures of Trichoplusia in insect cells (TN5B-1-4) using heparin. Biotechnol Technique, 1997, 11: 237-240.
7. Wlaschin K, Seth G, Hu W. Toward genomic cell culture engineering. Cytotechnology, 2006, 50: 121-140
8. Griffin T J, Seth G, Xie H, et al. Advancing mammalian cell culture engineering using genome-scale technologies. Trends in Biotechnol, 2007, 25: 400-408
9. Horiuchi J I, Kishimoto M. Application of fuzzy control to industrial bioprocesses in Japan. Fuzzy Sets and Sys tems, 2002, 128: 117-124
10. De Alwis D M, Dutton R L, Scharer J, et al. Statistical methods in media optimization for batch and fed-batch animal cell culture. Bioprocess Biosyst Eng, 2007, 30: 107-113
11. Aboytes K A, Fong D K, et al. Development and optimization of cell culture media: genomic and proteomic approaches. Bioprocess International, 2005, 3: 38-45.
12. Whitford W G. Fed-batch mammalian cell culture in bioproduction. BioProcessInternational, 2006, 4: 30-40
13. Bibila T A, Ranucci C S, Glazomitsky K, et al. Monoclonal antibody process development using medium concentrates. Biotechnol Prog, 1994, 10: 87-96
14. Xie L Z, Wang D I C. Fed-batch cultivation of animal cells using different medium design concepts and feeding strategies. Biotechnol Bioeng, 1994, 43: 1175-1189
15. Xie L Z, Wang D I C. High cell density and high monoclonal antibody production through medium design and rational control in bioreactor. Biotechnol Bioeng, 1996, 51: 725-729
16. Zhou W C, Rehm J, Europa A, et al. Alteration of mammalian cell metabolism by dynamic nutrient feeding. Cytotechnology, 1997, 24: 99-108
17. Zhou W C, Chen C C, Buckland B, et al. Fed-batch culture of recombinant NS0 myeloma cells with high monoclonal antibody production. Biotechnol Bioeng, 1997, 55:783-792
18. Zeng, A P, Bi J. Cell Culture Kinetics and Modeling.In:S.S.Ozturk and WS Hu Cell culture technology for pharmaceutical and cellular therapies. Taylor&Francis Group, Atlanta, 2003, pp:299-347.
19. Chetan T G, Klaus J, Konstantin B K, et al. Logistic equations effectively model mammalian cell batch and fed-batch kinetics by logically constraining the fit. Biotechnol Prog, 2005, 21, 1109-1118
20. Provost A, Bastin G. Dynamic metabolic modeling under the balanced growth condition.J Proc Cont, 2004, 14:717-728.
21. Xie L Z, Wang D I C. Material balance studies on animal cell metabolism using a stoichiometrically based reaction network.Biotechnol Bioeng, 1996a, 52:579-590.
22. Novak B, Tyson J J. A model for restriction point control of the mammalian cell cycle.J theor Biol, 2004, 230:563-579.
23. Sauer P W, Burky J E, Wesson M C. A high-yielding, generic fed-batch cell culture process for production of recombinant antibodies. Biotechnol Bioeng, 2000, 67: 585-97.
24. Senger R S, Karim M N. Optimization of fed-batch parameters and harvestime ofCHO cell cultures for a glycosylated product with multiple mechanisms of inactivation. Biotechnol and Bioeng, 2007, 98: 378-390.
25. Ozturk S S, Thrift J C, Blackie J D, et al. Real-time monitoring and control of glucose and lactate concentrations in a mammalian cell perfusion reactor. Biotechnol Bioeng, 1997, 53: 372-378.
26. Glaken M W, Fleischaker R J, Sinskey A J. Reduction of waste product excretion via nutrient control: possible strategies for maximizing product and cell yields on serum in cultures of mammalian cells. Biotechnol Bioeng, 1986, 28: 1376-1389.
27. Gambhir A, Korke R, Lee J, et al. Analysis of cellular metabolism of hybridoma cells at distint physiological states. J Biosci Bioeng, 2003, 95: 317-327.
28. Li L, Mi L, Feng Q, et al. Increasing the culture efficiency of hybridoma cells by the use of integrated metabolic control of glucose and glutamine at low levels. Biotechnol Appl Biochem, 2005, 42: 73-80.
29. Fox S R, Patel U A, Yap M G, et al. Maximizing interferon-gamma production by Chinese hamster ovary cells through temperature shift optimization: experimental and modeling. Biotechnol Bioeng, 2004, 85: 177-184.
30. Underhill M F, Smales C M. The cold-shock response in mammalian cells: investigating the HeLa cell cold-shock proteome. Cytotechnology, 2007,53: 47-53
31. Lee Y Y, Wong K T K, Nissom P M, et al. Transcriptional profiling of batch and fed-batch protein-free 293-HEK cultures. Metabolic Engineering 2007, 9:52-67.
32. Yee J C, Gatti M L, Philp R J, et al. Genomic and proteomic exploration of CHO and hybridoma cells under sodium butyrate treatment. Biotechnol Bioeng, 2008, 99: 1187-1204.
1. Link T Backstrom M, Graham R, et al. Bioprocess development for the production of a recombinant MUCl fusion protein expressed by CHO-K1 cells in protein-free medium. J Biotechnol, 2004, 110:51-62.
2.韩素文,俞炜源,李秀珍等.培养细胞分泌的血纤维蛋白溶解酶原激活物的研究.军事科学院院刊, 1987, 11:101-108.
3. Gigout A, Buschmann M D, Jolicoeur M. The fate of Pluronic F-68 in chondrocytes and CHO cells. Biotechnol Bioeng, 2008, 100:975-987.
4. Hokett S D, Cuenin M F, O’Neal R B, et al. Pluronic polyol effects on human gingival fibroblast attachment and growth. J Periodontol, 2000, 71:803–809.
5. Renner W A, Jordan M, Eppenberger H M, et al. Cell-cell adhesion and aggregation: Influence on the growth behavior of CHO cells. Biotechnol Bioeng, 1993, 41:188-193.
6. Sinacore N, Charlebios T, Harrison S, et al. CHO DUKX cell lineages preadapted to growth in serum-free suspension culture enable rapid development of cell culture processes for the manufacture of recombinant proteins. Biotechnol Bioeng, 1996, 52: 518-528.
7. Dee K U, Shuler M L, Wood H A. Inducing single-cell suspension of BTI-TN5B1- 4 Insect cells:I. The use of sulfatedpolyanions to prevent cell aggregation and enhance recombinant protein production. Biotechnol Bioeng, 1997, 54: 191-205.
8. Curz H J, Dias E M, Moerira J L, et al. Cell-dislodging method under serum-free conditions. Appl microbiol Biotechnol, 1997, 47:482-488.
9. Tsao Y S, Condon R, Schaefer E, et al. Development and improvement of a serum-free suspension process for the production of recombinant adenoviral vectors using HEK293 cells. Cytotechnology, 2001, 37:189-198.
10. Dee K, Wood H A, Shuler M L. Inducing single cell suspension of BTI-TNSBI-4 insect cells:Ⅱthe effect of sulatfed polyanions on baculoviurs inefetion. Biotechnol Bioeng, 1997, 54:206-220.
11. Zanghi J A, Renner W, Bailey J E, et al. The growth factor inhibitor surmain reduces apoptosis and aggregation in protein-free CHO cell batch cultures. Biotechnol Prog, 2000, 16:319-325.
12. McKenna K A, Granados R R. Method for adpating anchorage-dependent cell lines to suspension conditions. US Patent, 1994, 5348877.
13. Taticek R A, McKennac K A, Granadose R R, et al. Rapid initiation of suspension cultures of trichoplusia in insect cells-(TN5B-1-4) using heparin. Biotechnol Technique, 1997, 11:237-240.
1. Plackett R L, Burman J P. The design of optimum multifactorial experiment. Bimemetrika, 1946, 33: 305-325.
2. Douglas C Montgomery.实验设计与分析.北京:中国统计出版社,1998,589-640.
3. Ganne V, Mignot G.. Application of statistical design of experiments to the optimization of factor VIII expression by CHO cells. Cytotechnology, 1991, 6: 233–240.
4. Lee G M, Kim E J, Kim N S, et al.Development of a serum-free medium for the production of erythropoietin by suspension culture of recombinant Chinese hamster ovary cells using a statistical design. Journal of Biotechnology, 1999, 69: 85–93.
5. Castro P M L, Hayter P M, Ison A P, Bull, AT. Application of a statistical design to the optimization of culture medium for recombinant interferon-gamma production by Chinese hamster ovary cells. Appl Microbiol Biotechnol, 1992, 38: 84-90.
6. Freshney R I, Culture of Animal Cells: A manual of basic technique, 3rd edition. Wiley J. Liss, New York, 1994, 85-98.
7. Weuster-Botz D. Experimental design for fermentation media development: statistical design or global random search. J Biosci.Bioeng, 2000, 90:473-483.
8. Myers W R. Response surface methodology. Encycloedia of biopharmaceutical statistics. New York: Marcel Dekker, 2003:858-869.
9. Horiuchi J I, Kishimoto M. Application of fuzzy control to industrial bioprocesses in Japan. Fuzzy Sets and Sys tems, 2002, 128:117-124.
10. DeAlwis D M, Dutton R L, Scharer J, et al. Statistical methods in media optimization for batch and fed-batch animal cell culture. Bioprocess Biosyst Eng, 2007, 30:107-113.
11. Allison D W, Aboytes K A, Fong D K, et al. Development and optimization of cell culture media: genomic and proteomic approaches. Bioprocess International, 2005, 3: 38-45.
12. Weuster-Botz D. Experimental design for fermentation media development: statistical design or global random search. J. Biosci.Bioeng, 2000, 90:473-483.
13. Myers W R. Response surface methodology. Encycloedia of biopharmaceutical statistics. New York: Marcel Dekker, 2003, 858-869
14. Sanfeliu A, Chung J D, Stephanopoulos G. Effects of insulin stimulation on the proliferation and death of Chinese hamster ovary cells. Biotechnol Bioeng, 2000, 70:421-427
15. Wong V T, Nissom P M, Sim S L, et al. Zinc as an insulin replacement in hybridoma cultures. Biotechnol Bioeng, 2006, 93:553-563.
16.刘文献,贾茜,谭西霞.产HbsAg CHO细胞无血清培养研究.中国生物工程杂志, 2002, 22:93-96.
17. Kurano N, Leist C, Messi F, et al. Growth behavior of Chinese haster ovary cells in a compact loop bioreactor: 1. Effects of physical and chemical enviroments. Journal of Biotechnology, 1990, 15:101-112.
18. Ozturk S S, Palsson B O. Physio logical changes during the adaption of hybridoma cells. Biochemical and Biotechnology, 1991, 37:35-46.
19. Europa A F, Gambhir A F C, Hu W S. Multiple steady states with distinct cellular metabolism in continuous culture of mammalian cells. Biotechnol Bioeng, 2000, 67:25-34.
20. Korke R, de Leon G M, Lau A, et al. Large scale gene expression profiling of metabolic shift of mammalian cells in culture. J Biotechnol, 2004, 107:1-17.
1. Bailey J E, Ollis D F. Biochemical engineering fundamentals[M]. 2ndEdition, New York, Mc-Grawl-Hill BookCompany.1986.
2. Luedeking R, Piret E L A. kinetic study of the lactic acid fermentation:batch process at controlled pH. J Biochem Microbiol Technol Eng, 1960, 2:393-412.
3. Monod J. The growth of bacterial cultures. Annu Rev Microbiol 1949, 3:364-371.
4. Wlaschin K F, Hu W S. Fed-batch Culture and Dynamic Nutrient Feeding. Adv Biochem Eng/Biotechnol, 2006, 101, 43-74.
5. Hideo K, Yong S P, Shinji L , et al. Grow th characteristics in fed-batch culture of hybridoma cells with contro l of glucose and glutamine concentrations. Bio technol Bioeng, 1994, 44: 95-103.
6. Kuwae S, Ohda T, Tamashima H, et al. Development of a fed-batch culture process for enhanced production of recombinant human antit hrombin by Chinese hamster ovary cells. J Biosci Bioeng, 2005, 100:502-510.
7. Marange L, Goochee C F. Metabolism of PER.C6 cells cultured under fed-batch conditions at low glucose and glutamine levels. Biotechnol Bioeng, 2006, 94: 139-150.
8. Gambhir A, Korke R, Lee J, et al. Analysis of cellular metabolism of hybridoma cells at distinct physiological states. J Biosci Bioeng, 2003, 95: 317-327.
9. Chen P, Harcum S W. Effects of amino acid additions on ammonium stressed CHO cells. J Biotechnol, 2005, 117: 277-286.
10. Spens E, Ha¨ggstro¨m L. Defined protein and animal component-Free NS0 fed-batch culture. Biotechnol Bioeng, 2007, 98: 1183-1194.
11. Burky J E, Wesson M C, Young A, et al. Protein-free fed-batch culture of Non-GS NS0 cell lines for production of recombinant antibodies. Biotechnol Bioeng. 2007, 96: 281–293.
12. Bloemkolk J W and Gray M R. Effect of temperature on hybridoma cell cycle and MAb production. Biotechnol Bioeng, 1992, 40:427-431.
13. Christopher C W, Kohlbacher M S, Amos H. Transport of sugars in check-embryo fibroblasts. Evidence for a low-affinity system and a high-affinity system for glucose transport. Biochem J, 1976, 158(2): 439-450.
14. Zhou WC, Rehm J, Hu WS. High viable cell concentration fed-batch cultures of Hybridoma through on-line nutrient feeding. Biotechnol Bioeng, 1995, 46: 579-587.
15. Glaken M W, Fleischaker R J, Sinskey A J. Reduction of waste product excretion via nutrient control: possible strategies for maximizing product and cell yields on serum in cultures of mammalian cells. Biotechnol Bioeng, 1986, 28: 1376-1389.
1. Wong D C F, Wong K T K, Lee Y Y, et al. Transcriptional profiling of apoptotic pathways in batch and fed-batch CHO cell cultures. Biotechnol Bioeng, 2005, 94:373-382.
2. Lee Y Y, Wong K T K, Nissom P M, et al.Transcriptional profiling of batch and fed-batch protein-free 293-HEK cultures. Metabolic Engineering, 2007, 9:52-67.
3. Yee J C, Gatti M L, Philp R J, et al. Genomic and proteomic exploration of CHO and hybridoma cells under sodium butyrate treatment. Biotechnol Bioeng, 2008, 99:1187-1204.
4. Neuzil J, Wang X F, Dong L F, et al. Molecular mechanism of intocan induced apoptosis in cancer cells epitomizes the multiple roles of reactive oxygen species and Bcl-2 family proteins. FEBS Lett, 2006, 580:5125-5129.
5. Wohlpart D, Kirwan D, Gainer J. Effects of cell density and glucose and glutamine levels on the resp iration rates of hybridoma. Biotechnol Bioeng, 1990, 36: 630-635.
6. Miller W M, Blanch H W, Wilke C R. Transient responses of hybridoma cells to nutient additions in continious culture: I. Glucose pulse and step change. Biotechnol Bioeng, 1988, 33: 477-486.
7. Singh R P , Al2Rubeai M, Gregory C D , et al . Cell death in bioreactors: a role for apoptosis. Biotechnol Bioeng, 1994, 44:720-726.
8. Cotter T G, Al-Rubeai M. Cell death (apoptosis) in cell culture system. Trends in Biotechnology, 1995, 13:150-155.
9. Laken H A, Leonard M W. Understanding and modulating apoptosis in industrial cell culture. Curr opin biotechnol, 200, 12:175-179.
10. Oltval Z N, Milliman C L, Korsmeyer S J. Bcl-2 heterodin erizes in vivo with a conserved homologbax that accelerates programmed cell death. Cell, 1993,74:609-618.
11. Kyriakis J M, Avruch J. Mammalian mitogen-activated protein kinase in preconditioning a detrimental factor or protective Kinase. CircRes, 2000, 86:92-100.
12. Tamura A, Yui K. Age-dependent reduction of bcl-2 expression in peripheral T cells of lpr and gld mutantmice. J Immunol, 1995, 155: 499-506.
13. Pu C, Fang M, Li Y, et al. Mitochondrial protein the promotes cytochrome C- dependend caspase activation by eliminating IAP inhibition. Cell, 2002,102: 331-336
14. Ailitieri D C. Validating surviving as a cancer therapeutit target. Nat Rev Cancer, 2003, 3:461-468.
15. Attisano L, Wrana J L. Signal transduction by the TGF-beta superfamily. Science, 2002, 296:1646-1647
2.胡显文,陈惠鹏,汤仲明,马清钧.生物制药的现状和未来(一):历史与与现实市场.中国生物工程杂志, 2004, 24: 95-101
3. McKenna K A, Granados R R. Method for adpating anchorage-dependent cell lines to suspension conditions. US Patent, 1994, 5348877.
4. Dee K, Wood H A, Shuler M L. Inducing single cell suspension of BTI-TNSBI-4 insect cells:Ⅱthe effect of sulatfed polyanions on baculoviurs inefetion. Biotechnol Bioeng, 1997, 54: 206-220.
5. Zanghi J A, Renner W, Bailey J E, et al. The growth factor inhibitor surmain reduces apoptosis and aggregation in protein-free CHO cell batch cultures. Biotechnol Prog, 2000, 16: 319-325.
6. Taticek R A, McKennac K A, Granadose R R, et al. Rapid initiation of suspension cultures of Trichoplusia in insect cells (TN5B-1-4) using heparin. Biotechnol Technique, 1997, 11: 237-240.
7. Wlaschin K, Seth G, Hu W. Toward genomic cell culture engineering. Cytotechnology, 2006, 50: 121-140
8. Griffin T J, Seth G, Xie H, et al. Advancing mammalian cell culture engineering using genome-scale technologies. Trends in Biotechnol, 2007, 25: 400-408
9. Horiuchi J I, Kishimoto M. Application of fuzzy control to industrial bioprocesses in Japan. Fuzzy Sets and Sys tems, 2002, 128: 117-124
10. De Alwis D M, Dutton R L, Scharer J, et al. Statistical methods in media optimization for batch and fed-batch animal cell culture. Bioprocess Biosyst Eng, 2007, 30: 107-113
11. Aboytes K A, Fong D K, et al. Development and optimization of cell culture media: genomic and proteomic approaches. Bioprocess International, 2005, 3: 38-45.
12. Whitford W G. Fed-batch mammalian cell culture in bioproduction. BioProcessInternational, 2006, 4: 30-40
13. Bibila T A, Ranucci C S, Glazomitsky K, et al. Monoclonal antibody process development using medium concentrates. Biotechnol Prog, 1994, 10: 87-96
14. Xie L Z, Wang D I C. Fed-batch cultivation of animal cells using different medium design concepts and feeding strategies. Biotechnol Bioeng, 1994, 43: 1175-1189
15. Xie L Z, Wang D I C. High cell density and high monoclonal antibody production through medium design and rational control in bioreactor. Biotechnol Bioeng, 1996, 51: 725-729
16. Zhou W C, Rehm J, Europa A, et al. Alteration of mammalian cell metabolism by dynamic nutrient feeding. Cytotechnology, 1997, 24: 99-108
17. Zhou W C, Chen C C, Buckland B, et al. Fed-batch culture of recombinant NS0 myeloma cells with high monoclonal antibody production. Biotechnol Bioeng, 1997, 55:783-792
18. Zeng, A P, Bi J. Cell Culture Kinetics and Modeling.In:S.S.Ozturk and WS Hu Cell culture technology for pharmaceutical and cellular therapies. Taylor&Francis Group, Atlanta, 2003, pp:299-347.
19. Chetan T G, Klaus J, Konstantin B K, et al. Logistic equations effectively model mammalian cell batch and fed-batch kinetics by logically constraining the fit. Biotechnol Prog, 2005, 21, 1109-1118
20. Provost A, Bastin G. Dynamic metabolic modeling under the balanced growth condition.J Proc Cont, 2004, 14:717-728.
21. Xie L Z, Wang D I C. Material balance studies on animal cell metabolism using a stoichiometrically based reaction network.Biotechnol Bioeng, 1996a, 52:579-590.
22. Novak B, Tyson J J. A model for restriction point control of the mammalian cell cycle.J theor Biol, 2004, 230:563-579.
23. Sauer P W, Burky J E, Wesson M C. A high-yielding, generic fed-batch cell culture process for production of recombinant antibodies. Biotechnol Bioeng, 2000, 67: 585-97.
24. Senger R S, Karim M N. Optimization of fed-batch parameters and harvestime ofCHO cell cultures for a glycosylated product with multiple mechanisms of inactivation. Biotechnol and Bioeng, 2007, 98: 378-390.
25. Ozturk S S, Thrift J C, Blackie J D, et al. Real-time monitoring and control of glucose and lactate concentrations in a mammalian cell perfusion reactor. Biotechnol Bioeng, 1997, 53: 372-378.
26. Glaken M W, Fleischaker R J, Sinskey A J. Reduction of waste product excretion via nutrient control: possible strategies for maximizing product and cell yields on serum in cultures of mammalian cells. Biotechnol Bioeng, 1986, 28: 1376-1389.
27. Gambhir A, Korke R, Lee J, et al. Analysis of cellular metabolism of hybridoma cells at distint physiological states. J Biosci Bioeng, 2003, 95: 317-327.
28. Li L, Mi L, Feng Q, et al. Increasing the culture efficiency of hybridoma cells by the use of integrated metabolic control of glucose and glutamine at low levels. Biotechnol Appl Biochem, 2005, 42: 73-80.
29. Fox S R, Patel U A, Yap M G, et al. Maximizing interferon-gamma production by Chinese hamster ovary cells through temperature shift optimization: experimental and modeling. Biotechnol Bioeng, 2004, 85: 177-184.
30. Underhill M F, Smales C M. The cold-shock response in mammalian cells: investigating the HeLa cell cold-shock proteome. Cytotechnology, 2007,53: 47-53
31. Lee Y Y, Wong K T K, Nissom P M, et al. Transcriptional profiling of batch and fed-batch protein-free 293-HEK cultures. Metabolic Engineering 2007, 9:52-67.
32. Yee J C, Gatti M L, Philp R J, et al. Genomic and proteomic exploration of CHO and hybridoma cells under sodium butyrate treatment. Biotechnol Bioeng, 2008, 99: 1187-1204.
1. Link T Backstrom M, Graham R, et al. Bioprocess development for the production of a recombinant MUCl fusion protein expressed by CHO-K1 cells in protein-free medium. J Biotechnol, 2004, 110:51-62.
2.韩素文,俞炜源,李秀珍等.培养细胞分泌的血纤维蛋白溶解酶原激活物的研究.军事科学院院刊, 1987, 11:101-108.
3. Gigout A, Buschmann M D, Jolicoeur M. The fate of Pluronic F-68 in chondrocytes and CHO cells. Biotechnol Bioeng, 2008, 100:975-987.
4. Hokett S D, Cuenin M F, O’Neal R B, et al. Pluronic polyol effects on human gingival fibroblast attachment and growth. J Periodontol, 2000, 71:803–809.
5. Renner W A, Jordan M, Eppenberger H M, et al. Cell-cell adhesion and aggregation: Influence on the growth behavior of CHO cells. Biotechnol Bioeng, 1993, 41:188-193.
6. Sinacore N, Charlebios T, Harrison S, et al. CHO DUKX cell lineages preadapted to growth in serum-free suspension culture enable rapid development of cell culture processes for the manufacture of recombinant proteins. Biotechnol Bioeng, 1996, 52: 518-528.
7. Dee K U, Shuler M L, Wood H A. Inducing single-cell suspension of BTI-TN5B1- 4 Insect cells:I. The use of sulfatedpolyanions to prevent cell aggregation and enhance recombinant protein production. Biotechnol Bioeng, 1997, 54: 191-205.
8. Curz H J, Dias E M, Moerira J L, et al. Cell-dislodging method under serum-free conditions. Appl microbiol Biotechnol, 1997, 47:482-488.
9. Tsao Y S, Condon R, Schaefer E, et al. Development and improvement of a serum-free suspension process for the production of recombinant adenoviral vectors using HEK293 cells. Cytotechnology, 2001, 37:189-198.
10. Dee K, Wood H A, Shuler M L. Inducing single cell suspension of BTI-TNSBI-4 insect cells:Ⅱthe effect of sulatfed polyanions on baculoviurs inefetion. Biotechnol Bioeng, 1997, 54:206-220.
11. Zanghi J A, Renner W, Bailey J E, et al. The growth factor inhibitor surmain reduces apoptosis and aggregation in protein-free CHO cell batch cultures. Biotechnol Prog, 2000, 16:319-325.
12. McKenna K A, Granados R R. Method for adpating anchorage-dependent cell lines to suspension conditions. US Patent, 1994, 5348877.
13. Taticek R A, McKennac K A, Granadose R R, et al. Rapid initiation of suspension cultures of trichoplusia in insect cells-(TN5B-1-4) using heparin. Biotechnol Technique, 1997, 11:237-240.
1. Plackett R L, Burman J P. The design of optimum multifactorial experiment. Bimemetrika, 1946, 33: 305-325.
2. Douglas C Montgomery.实验设计与分析.北京:中国统计出版社,1998,589-640.
3. Ganne V, Mignot G.. Application of statistical design of experiments to the optimization of factor VIII expression by CHO cells. Cytotechnology, 1991, 6: 233–240.
4. Lee G M, Kim E J, Kim N S, et al.Development of a serum-free medium for the production of erythropoietin by suspension culture of recombinant Chinese hamster ovary cells using a statistical design. Journal of Biotechnology, 1999, 69: 85–93.
5. Castro P M L, Hayter P M, Ison A P, Bull, AT. Application of a statistical design to the optimization of culture medium for recombinant interferon-gamma production by Chinese hamster ovary cells. Appl Microbiol Biotechnol, 1992, 38: 84-90.
6. Freshney R I, Culture of Animal Cells: A manual of basic technique, 3rd edition. Wiley J. Liss, New York, 1994, 85-98.
7. Weuster-Botz D. Experimental design for fermentation media development: statistical design or global random search. J Biosci.Bioeng, 2000, 90:473-483.
8. Myers W R. Response surface methodology. Encycloedia of biopharmaceutical statistics. New York: Marcel Dekker, 2003:858-869.
9. Horiuchi J I, Kishimoto M. Application of fuzzy control to industrial bioprocesses in Japan. Fuzzy Sets and Sys tems, 2002, 128:117-124.
10. DeAlwis D M, Dutton R L, Scharer J, et al. Statistical methods in media optimization for batch and fed-batch animal cell culture. Bioprocess Biosyst Eng, 2007, 30:107-113.
11. Allison D W, Aboytes K A, Fong D K, et al. Development and optimization of cell culture media: genomic and proteomic approaches. Bioprocess International, 2005, 3: 38-45.
12. Weuster-Botz D. Experimental design for fermentation media development: statistical design or global random search. J. Biosci.Bioeng, 2000, 90:473-483.
13. Myers W R. Response surface methodology. Encycloedia of biopharmaceutical statistics. New York: Marcel Dekker, 2003, 858-869
14. Sanfeliu A, Chung J D, Stephanopoulos G. Effects of insulin stimulation on the proliferation and death of Chinese hamster ovary cells. Biotechnol Bioeng, 2000, 70:421-427
15. Wong V T, Nissom P M, Sim S L, et al. Zinc as an insulin replacement in hybridoma cultures. Biotechnol Bioeng, 2006, 93:553-563.
16.刘文献,贾茜,谭西霞.产HbsAg CHO细胞无血清培养研究.中国生物工程杂志, 2002, 22:93-96.
17. Kurano N, Leist C, Messi F, et al. Growth behavior of Chinese haster ovary cells in a compact loop bioreactor: 1. Effects of physical and chemical enviroments. Journal of Biotechnology, 1990, 15:101-112.
18. Ozturk S S, Palsson B O. Physio logical changes during the adaption of hybridoma cells. Biochemical and Biotechnology, 1991, 37:35-46.
19. Europa A F, Gambhir A F C, Hu W S. Multiple steady states with distinct cellular metabolism in continuous culture of mammalian cells. Biotechnol Bioeng, 2000, 67:25-34.
20. Korke R, de Leon G M, Lau A, et al. Large scale gene expression profiling of metabolic shift of mammalian cells in culture. J Biotechnol, 2004, 107:1-17.
1. Bailey J E, Ollis D F. Biochemical engineering fundamentals[M]. 2ndEdition, New York, Mc-Grawl-Hill BookCompany.1986.
2. Luedeking R, Piret E L A. kinetic study of the lactic acid fermentation:batch process at controlled pH. J Biochem Microbiol Technol Eng, 1960, 2:393-412.
3. Monod J. The growth of bacterial cultures. Annu Rev Microbiol 1949, 3:364-371.
4. Wlaschin K F, Hu W S. Fed-batch Culture and Dynamic Nutrient Feeding. Adv Biochem Eng/Biotechnol, 2006, 101, 43-74.
5. Hideo K, Yong S P, Shinji L , et al. Grow th characteristics in fed-batch culture of hybridoma cells with contro l of glucose and glutamine concentrations. Bio technol Bioeng, 1994, 44: 95-103.
6. Kuwae S, Ohda T, Tamashima H, et al. Development of a fed-batch culture process for enhanced production of recombinant human antit hrombin by Chinese hamster ovary cells. J Biosci Bioeng, 2005, 100:502-510.
7. Marange L, Goochee C F. Metabolism of PER.C6 cells cultured under fed-batch conditions at low glucose and glutamine levels. Biotechnol Bioeng, 2006, 94: 139-150.
8. Gambhir A, Korke R, Lee J, et al. Analysis of cellular metabolism of hybridoma cells at distinct physiological states. J Biosci Bioeng, 2003, 95: 317-327.
9. Chen P, Harcum S W. Effects of amino acid additions on ammonium stressed CHO cells. J Biotechnol, 2005, 117: 277-286.
10. Spens E, Ha¨ggstro¨m L. Defined protein and animal component-Free NS0 fed-batch culture. Biotechnol Bioeng, 2007, 98: 1183-1194.
11. Burky J E, Wesson M C, Young A, et al. Protein-free fed-batch culture of Non-GS NS0 cell lines for production of recombinant antibodies. Biotechnol Bioeng. 2007, 96: 281–293.
12. Bloemkolk J W and Gray M R. Effect of temperature on hybridoma cell cycle and MAb production. Biotechnol Bioeng, 1992, 40:427-431.
13. Christopher C W, Kohlbacher M S, Amos H. Transport of sugars in check-embryo fibroblasts. Evidence for a low-affinity system and a high-affinity system for glucose transport. Biochem J, 1976, 158(2): 439-450.
14. Zhou WC, Rehm J, Hu WS. High viable cell concentration fed-batch cultures of Hybridoma through on-line nutrient feeding. Biotechnol Bioeng, 1995, 46: 579-587.
15. Glaken M W, Fleischaker R J, Sinskey A J. Reduction of waste product excretion via nutrient control: possible strategies for maximizing product and cell yields on serum in cultures of mammalian cells. Biotechnol Bioeng, 1986, 28: 1376-1389.
1. Wong D C F, Wong K T K, Lee Y Y, et al. Transcriptional profiling of apoptotic pathways in batch and fed-batch CHO cell cultures. Biotechnol Bioeng, 2005, 94:373-382.
2. Lee Y Y, Wong K T K, Nissom P M, et al.Transcriptional profiling of batch and fed-batch protein-free 293-HEK cultures. Metabolic Engineering, 2007, 9:52-67.
3. Yee J C, Gatti M L, Philp R J, et al. Genomic and proteomic exploration of CHO and hybridoma cells under sodium butyrate treatment. Biotechnol Bioeng, 2008, 99:1187-1204.
4. Neuzil J, Wang X F, Dong L F, et al. Molecular mechanism of intocan induced apoptosis in cancer cells epitomizes the multiple roles of reactive oxygen species and Bcl-2 family proteins. FEBS Lett, 2006, 580:5125-5129.
5. Wohlpart D, Kirwan D, Gainer J. Effects of cell density and glucose and glutamine levels on the resp iration rates of hybridoma. Biotechnol Bioeng, 1990, 36: 630-635.
6. Miller W M, Blanch H W, Wilke C R. Transient responses of hybridoma cells to nutient additions in continious culture: I. Glucose pulse and step change. Biotechnol Bioeng, 1988, 33: 477-486.
7. Singh R P , Al2Rubeai M, Gregory C D , et al . Cell death in bioreactors: a role for apoptosis. Biotechnol Bioeng, 1994, 44:720-726.
8. Cotter T G, Al-Rubeai M. Cell death (apoptosis) in cell culture system. Trends in Biotechnology, 1995, 13:150-155.
9. Laken H A, Leonard M W. Understanding and modulating apoptosis in industrial cell culture. Curr opin biotechnol, 200, 12:175-179.
10. Oltval Z N, Milliman C L, Korsmeyer S J. Bcl-2 heterodin erizes in vivo with a conserved homologbax that accelerates programmed cell death. Cell, 1993,74:609-618.
11. Kyriakis J M, Avruch J. Mammalian mitogen-activated protein kinase in preconditioning a detrimental factor or protective Kinase. CircRes, 2000, 86:92-100.
12. Tamura A, Yui K. Age-dependent reduction of bcl-2 expression in peripheral T cells of lpr and gld mutantmice. J Immunol, 1995, 155: 499-506.
13. Pu C, Fang M, Li Y, et al. Mitochondrial protein the promotes cytochrome C- dependend caspase activation by eliminating IAP inhibition. Cell, 2002,102: 331-336
14. Ailitieri D C. Validating surviving as a cancer therapeutit target. Nat Rev Cancer, 2003, 3:461-468.
15. Attisano L, Wrana J L. Signal transduction by the TGF-beta superfamily. Science, 2002, 296:1646-1647
© 2004-2018 中国地质图书馆版权所有 京ICP备05064691号 京公网安备11010802017129号 地址：北京市海淀区学院路29号 邮编：100083 电话：办公室：(+86 10)66554848；文献借阅、咨询服务、科技查新：66554700 |