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利用傅里叶变换红外光谱和化学计量学快速监测哺乳动物细胞培养中的重组抗体生产。

Rapid monitoring of recombinant antibody production by mammalian cell cultures using fourier transform infrared spectroscopy and chemometrics.

机构信息

The University of Manchester, UK.

出版信息

Biotechnol Bioeng. 2010 Jun 15;106(3):432-42. doi: 10.1002/bit.22707.

Abstract

Fourier transform infrared (FT-IR) spectroscopy combined with multivariate statistical analyses was investigated as a physicochemical tool for monitoring secreted recombinant antibody production in cultures of Chinese hamster ovary (CHO) and murine myeloma non-secreting 0 (NS0) cell lines. Medium samples were taken during culture of CHO and NS0 cells lines, which included both antibody-producing and non-producing cell lines, and analyzed by FT-IR spectroscopy. Principal components analysis (PCA) alone, and combined with discriminant function analysis (PC-DFA), were applied to normalized FT-IR spectroscopy datasets and showed a linear trend with respect to recombinant protein production. Loadings plots of the most significant spectral components showed a decrease in the C-O stretch from polysaccharides and an increase in the amide I band during culture, respectively, indicating a decrease in sugar concentration and an increase in protein concentration in the medium. Partial least squares regression (PLSR) analysis was used to predict antibody titers, and these regression models were able to predict antibody titers accurately with low error when compared to ELISA data. PLSR was also able to predict glucose and lactate amounts in the medium samples accurately. This work demonstrates that FT-IR spectroscopy has great potential as a tool for monitoring cell cultures for recombinant protein production and offers a starting point for the application of spectroscopic techniques for the on-line measurement of antibody production in industrial scale bioreactors.

摘要

傅里叶变换红外(FT-IR)光谱结合多元统计分析被研究作为一种物理化学工具,用于监测中国仓鼠卵巢(CHO)和鼠骨髓瘤非分泌 0(NS0)细胞系培养物中分泌的重组抗体的生产。在 CHO 和 NS0 细胞系的培养过程中采集了培养基样本,其中包括产生抗体和不产生抗体的细胞系,并通过 FT-IR 光谱进行分析。主成分分析(PCA)单独使用,以及与判别函数分析(PC-DFA)结合使用,应用于归一化 FT-IR 光谱数据集,显示出与重组蛋白生产呈线性趋势。最显著的光谱分量的载荷图显示,在培养过程中多糖的 C-O 伸展减少,酰胺 I 带增加,分别表明培养基中糖浓度降低和蛋白质浓度增加。偏最小二乘回归(PLSR)分析用于预测抗体效价,与 ELISA 数据相比,这些回归模型能够准确地预测抗体效价,误差较低。PLSR 还能够准确地预测培养基样品中的葡萄糖和乳酸量。这项工作表明,FT-IR 光谱作为一种监测重组蛋白生产的细胞培养物的工具具有很大的潜力,并为在工业规模生物反应器中在线测量抗体生产的光谱技术的应用提供了一个起点。

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