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通过物种特异性微阵列分析适应无蛋白培养基悬浮培养后 CHO 细胞的转录组变化。

Transcriptomic changes in CHO cells after adaptation to suspension growth in protein-free medium analysed by a species-specific microarray.

机构信息

Department of Biotechnology, BOKU University, Vienna, Austria.

Austrian Centre of Industrial Biotechnology, Austria.

出版信息

J Biotechnol. 2017 Sep 10;257:13-21. doi: 10.1016/j.jbiotec.2017.03.012. Epub 2017 Mar 14.

Abstract

Chinese Hamster Ovary (CHO) cells are the preferred cell line for production of biopharmaceuticals. These cells are capable to grow without serum supplementation, but drastic changes in their phenotype occur during adaptation to protein-free growth, which typically include the change to a suspension phenotype with reduced growth rate. A possible approach to understand this transformation, with the intention to counteract the reduction in growth by targeted supplementation of protein-free media, is gene expression profiling. The increasing availability of genome-scale data for CHO now facilitates quests for a better understanding of metabolic pathways and gene networks. So far, systematic large-scale expression profiling in CHO cells by microarray was limited due to lack of publicly available array designs and limitations of alternative approaches. Based on the recent release of CHO and Chinese Hamster genome sequences, including an annotated RefSeq genome, we have constructed a publicly available microarray design for effective genome-scale expression profiling. The design employed microarray probes optimized for uniformity, sensitivity, and specificity, with probe properties computed using the latest thermodynamic models. We validated the platform in an analysis of gene expression changes in response to serum-free adaptation. The observed effects on the lipid metabolism as well as on nucleotide synthesis were used to successfully select media supplements that were able to increase growth rate.

摘要

中国仓鼠卵巢(CHO)细胞是生物制药生产的首选细胞系。这些细胞能够在没有血清补充的情况下生长,但在适应无蛋白生长的过程中,其表型会发生剧烈变化,通常包括生长速率降低的悬浮表型变化。为了理解这种转化,一种可能的方法是通过有针对性地补充无蛋白培养基来进行基因表达谱分析,以期抵消生长的减少。目前,随着 CHO 的基因组规模数据的可用性不断增加,有助于更好地理解代谢途径和基因网络。到目前为止,由于缺乏公开可用的芯片设计和替代方法的限制,CHO 细胞的系统大规模表达谱分析受到限制。基于最近发布的 CHO 和中国仓鼠基因组序列,包括注释的 RefSeq 基因组,我们构建了一个公开的微阵列设计,用于有效的全基因组表达谱分析。该设计采用了优化均匀性、灵敏度和特异性的微阵列探针,并使用最新的热力学模型计算了探针特性。我们通过分析无血清适应过程中基因表达的变化验证了该平台。观察到的对脂质代谢以及核苷酸合成的影响被成功地用于选择能够提高生长速率的培养基补充剂。

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