Department of Chemical Engineering and Materials Science, University of Minnesota, 421 Washington Avenue SE, Minneapolis, MN, 55455-0132, USA.
Cytotechnology. 2006 Mar;50(1-3):121-40. doi: 10.1007/s10616-006-9004-9. Epub 2006 Jul 25.
Genomic and proteomic based global gene expression profiling has altered the landscape of biological research in the past few years. Its potential impact on cell culture bioprocessing has only begun to emanate, partly due to the lack of genomic sequence information for the most widely used industrial cells, Chinese hamster ovary (CHO) cells. Transcriptome and proteome profiling work for species lacking extensive genomic resources must rely on information for other related species or on data obtained from expressed sequence tag (EST) sequencing projects, for which burgeoning efforts have only recently begun. This article discusses the aspects of EST sequencing in those industrially important, genomic resources-poor cell lines, articulates some of the unique features in employing microarray in the study of cultured cells, and highlights the infrastructural needs in establishing a platform for genomics based cell culture research. Recent experience has revealed that generally, most changes in culture conditions only elicit a moderate level of alteration in gene expression. Nevertheless, by broadening the conventional scope of microarray analysis to consider estimated levels of transcript abundance, much physiological insight can be gained. Examples of the application of microarray in cell culture are discussed, and the utility of pattern identification and process diagnosis are highlighted. As genomic resources continue to expand, the power of genomic tools in cell culture processing research will be amply evident. The key to harnessing the immense benefit of these genomic resources resides in the development of physiological understanding from their application.
基于基因组和蛋白质组的全基因表达谱分析在过去几年中改变了生物研究的格局。它对细胞培养生物工艺的潜在影响才刚刚开始显现,部分原因是缺乏最广泛使用的工业细胞(中国仓鼠卵巢细胞,CHO 细胞)的基因组序列信息。对于缺乏广泛基因组资源的物种,转录组和蛋白质组谱分析工作必须依赖于其他相关物种的信息,或者依赖于从表达序列标签(EST)测序项目中获得的数据,而最近才刚刚开始进行这些项目的蓬勃发展。本文讨论了在那些工业上重要但基因组资源匮乏的细胞系中进行 EST 测序的各个方面,阐述了在培养细胞研究中使用微阵列的一些独特特点,并强调了建立基于基因组的细胞培养研究平台的基础设施需求。最近的经验表明,通常情况下,培养条件的大多数变化只会引起基因表达的适度改变。然而,通过将微阵列分析的传统范围扩大到考虑转录本丰度的估计水平,可以获得更多的生理学见解。讨论了微阵列在细胞培养中的应用实例,并强调了模式识别和过程诊断的效用。随着基因组资源的不断扩展,基因组工具在细胞培养处理研究中的强大功能将得到充分体现。利用这些基因组资源的巨大优势的关键在于从它们的应用中发展出生理学的理解。