Cell Line Profiling to Improve Monoclonal Antibody Production
Cell Line Profiling to Improve Monoclonal Antibody Production
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DOI：
10.1002/bit.25141
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发表时间：
2014-04-01
影响因子：
3.8
通讯作者：
Deshpande, Rohini
中科院分区：
文献类型：
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作者：
Kang, Sohye;Ren, Da;Deshpande, Rohini
哺乳动物细胞培养性能受到内在（遗传）和外在（培养基和过程）因素的影响。在本研究中，通过将各种产生单克隆抗体的中国仓鼠卵巢 (CHO) 细胞系暴露于相同的培养条件下，对它们的内在能力进行了比较。利用基于微阵列的转录组学和 LC-MS/MS 鸟枪蛋白质组学技术来获得不同细胞系的表达景观。与生产力、生长速率和细胞大小相关的特定转录物和蛋白质已被鉴定。蛋白质组学分析结果显示重组DHFR的胞内蛋白表达水平与生产力之间存在很强的相关性。相反，重组单克隆抗体的轻链和重链均未显示出与生产率的相关性。其他与生产力呈正相关的排名靠前的蛋白质包括衔接蛋白复合物亚基 AP3D1 和 AP2B2、DNA 修复蛋白 DDB1 和 ER 易位复合物成分 SRPR。分子伴侣T复合蛋白1的亚基和线粒体一碳代谢调节因子MTHFD2与生产力呈负相关。转录组学分析已确定钙信号传导调节因子 Tmem20 和 Rcan1 分别是与生产力呈正相关和负相关的排名最高的基因。对于研究的第二部分，生成主成分分析 (PCA) 以查看表达数据的底层全局结构。在两个不同的细胞系簇之间观察到明显的分裂和表达极性，与生产力或任何其他检查性状的联系无关。从转录组学或蛋白质组学数据生成的 PCA 的主要成分显示出与细胞大小和倍增时间的强相关性，而没有一个主要成分显示出与生产率的相关性。我们的研究结果表明，在全局转录或蛋白质表达空间的背景下，生产力只是一个次要特征。生物技术。生物工程。 2014；111：748-760。 (c) 2013 年 Wiley 期刊公司。
Mammalian cell culture performance is influenced by both intrinsic (genetic) and extrinsic (media and process) factors. In this study, intrinsic capacity of various monoclonal antibody-producing Chinese Hamster Ovary (CHO) cell lines was compared by exposing them to the same culture condition. Microarray-based transcriptomics and LC-MS/MS shotgun proteomics technologies were utilized to obtain expression landscape of different cell lines. Specific transcripts and proteins correlating with productivity, growth rate and cell size have been identified. The proteomics analysis results showed a strong correlation between the intracellular protein expression levels of the recombinant DHFR and productivity. In contrast, neither the light chain nor the heavy chain of the recombinant monoclonal antibody showed correlation to productivity. Other top ranked proteins which demonstrated positive correlation to productivity included the adaptor protein complex subunits AP3D1and AP2B2, DNA repair protein DDB1 and the ER translocation complex component, SRPR. The subunits of molecular chaperone T-complex protein 1 and the regulator of mitochondrial one-carbon metabolism MTHFD2 showed negative correlation to productivity. The transcriptomics analysis has identified the regulators of calcium signaling, Tmem20 and Rcan1, as the top ranked genes displaying positive and negative correlation to productivity, respectively. For the second part of the study, the principal component analysis (PCA) was generated to view the underlying global structure of the expression data. A clear division and expression polarity was observed between the two distinct clusters of cell lines, independent of link to productivity or any other traits examined. The primary component of the PCA generated from either transcriptomics or proteomics data displayed a strong correlation to cell size and doubling time, while none of the main principal components showed correlation to productivity. Our findings suggest that productivity is rather a minor feature in the context of global transcriptional or protein expression space. Biotechnol. Bioeng. 2014;111: 748-760. (c) 2013 Wiley Periodicals, Inc.