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Translatome analysis of CHO cells to identify key growth genes

机译:对CHO细胞进行Translatome分析以鉴定关键生长基因

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We report the first investigation of translational efficiency on a global scale, also known as translatome, of a Chinese hamster ovary (CHO) DG44 cell line producing monoclonal antibodies (mAb). The translatome data was generated via combined use of high resolution and streamlined polysome profiling technology and proprietary Nimblegen microarrays probing for more than 13 K annotated CHO-specific genes. The distribution of ribosome loading during the exponential growth phase revealed the translational activity corresponding to the maximal growth rate, thus allowing us to identify stably and highly translated genes encoding heterogeneous nuclear ribonucleoproteins (Hnrnpc and Hnrnpa2b1), protein regulator of cytokinesis 1 (Prc1), glucose-6-phosphate dehydrogenase (G6pdh), UTP6 small subunit processome (Utp6) and RuvB-like protein 1 (Ruvbl1) as potential key players for cellular growth. Moreover, correlation analysis between transcriptome and translatome data sets showed that transcript level and translation efficiency were uncoupled for 95% of investigated genes, suggesting the implication of translational control mechanisms such as the mTOR pathway. Thus, the current translatome analysis platform offers new insights into gene expression in CHO cell cultures by bridging the gap between transcriptome and proteome data, which will enable researchers of the bioprocessing field to prioritize in high-potential candidate genes and to devise optimal strategies for cell engineering toward improving culture performance
机译:我们报告了中国仓鼠卵巢(CHO)DG44细胞株产生单克隆抗体(mAb)的全球规模,也称为翻译组的翻译效率的首次调查。通过结合使用高分辨率和简化的多核糖体图谱分析技术以及专有的Nimblegen微阵列来生成跨转录组数据,该芯片可探测超过13 K注释的CHO特异性基因。指数生长期核糖体负荷的分布揭示了对应于最大生长速率的翻译活性,从而使我们能够鉴定出稳定且高度翻译的编码异质核糖核蛋白(Hnrnpc和Hnrnpa2b1),胞质分裂蛋白1(Prc1)的蛋白质的基因,葡萄糖6磷酸脱氢酶(G6pdh),UTP6小亚基加工组(Utp6)和RuvB样蛋白1(Ruvbl1)是细胞生长的潜在关键参与者。此外,转录组和翻译组数据集之间的相关性分析表明,对于95%的研究基因,转录水平和翻译效率是不相关的,这暗示了翻译控制机制(如mTOR途径)的含义。因此,当前的翻译组分析平台通过弥合转录组和蛋白质组数据之间的差距,为CHO细胞培养中的基因表达提供了新的见解,这将使生物加工领域的研究人员能够优先考虑高潜力的候选基因并为细胞设计最佳策略工程,以提高文化表现

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