Seth Gargi, Philp Robin J, Lau Ally, Jiun Kok Yee, Yap Miranda, Hu Wei-Shou
Department of Chemical Engineering and Materials Science, University of Minnesota, Minneapolis, MN 55455-0132, USA.
Biotechnol Bioeng. 2007 Jul 1;97(4):933-51. doi: 10.1002/bit.21234.
Many important therapeutic proteins are produced in recombinant mammalian cells. Upon the introduction of the product gene, the isolated clones typically exhibit a wide range of productivity and high producers are subsequently selected for use in production. Using DNA microarray, two-dimensional gel electrophoresis (2DE), and iTRAQ as global surveying tools, we examined the transcriptome and proteome profiles of 11 lines of NS0 cells producing the same antibody molecule. Genes that are significantly differentially expressed between high and low producer groups statistically fall into a number of functional classes. Their distribution among the functional classes differs somewhat between transcriptomic and proteomic results. Overall, a high degree of consistency between transcriptome and proteome analysis are seen, although some genes exhibiting inconsistent trends between transcript and protein levels were observed as expected. In a novel approach, functional gene networks were retrieved using computational pathway analysis tools and their association with productivity was tested by physiological comprehension of the possible pathways involved in high recombinant protein production. Network analysis indicates that protein synthesis pathways were altered in high producers at both transcriptome and proteome levels, whereas the effect on cell growth/death pathways was more prominent only at the transcript level. The results suggest a common mechanism entailing the alteration of protein synthesis and cell growth control networks leading to high productivity. However, alternate routes with different sets of genes may be invoked to give rise to the same mechanistic outcomes. Such systematic approaches, combining transcriptomic and proteomic tools to examine high and low producers of recombinant mammalian cells will greatly enhance our capability to rationally design high producer cells. This work is a first step towards shedding a new light on the global physiological landscape of hyper productivity of recombinant cells.
许多重要的治疗性蛋白质是在重组哺乳动物细胞中产生的。导入产物基因后,分离出的克隆通常表现出广泛的生产力范围,随后选择高产量的克隆用于生产。我们使用DNA微阵列、二维凝胶电泳(2DE)和iTRAQ作为全局检测工具,检测了11株产生相同抗体分子的NS0细胞的转录组和蛋白质组图谱。高产和低产组之间显著差异表达的基因在统计学上可分为多个功能类别。它们在功能类别中的分布在转录组和蛋白质组结果之间略有不同。总体而言,转录组和蛋白质组分析之间呈现出高度的一致性,尽管正如预期的那样,观察到一些基因在转录水平和蛋白质水平之间呈现出不一致的趋势。采用一种新方法,利用计算途径分析工具检索功能基因网络,并通过对高重组蛋白生产中可能涉及的途径进行生理学理解来测试它们与生产力的关联。网络分析表明,高产细胞在转录组和蛋白质组水平上蛋白质合成途径均发生了改变,而对细胞生长/死亡途径的影响仅在转录水平上更为突出。结果表明存在一种共同机制,即蛋白质合成和细胞生长控制网络的改变导致了高生产力。然而,可能会调用具有不同基因集的替代途径来产生相同的机制结果。这种结合转录组学和蛋白质组学工具来检测重组哺乳动物细胞高产和低产情况的系统方法,将大大提高我们合理设计高产细胞的能力。这项工作是朝着揭示重组细胞高生产力的全球生理格局迈出的第一步。