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首页> 外文期刊>Molecular Biotechnology >Transcriptome and proteome profiling to understanding the biology of high productivity CHO cells
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Transcriptome and proteome profiling to understanding the biology of high productivity CHO cells

机译：转录组和蛋白质组图谱分析，以了解高产CHO细胞的生物学特性

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摘要

A combined transcriptome and proteome analysis was carried out to identify key genes and proteins differentially expressed in Chinese hamster ovary (CHO) cells producing high and low levels of dhfr-GFP fusion protein. Comparison of transcript levels was performed using a proprietary 15 K CHO cDNA microarray chip, whereas proteomic analysis was perfomed using iTRAQ quantitative protein profiling technique. Microarray analysis revealed 77 differentially expressed genes, with 53 genes upregulated and 24 genes downregulated. Proteomic analysis gave 75 and 80 proteins for the midexponential and stationary phase, respectively. Although there was a general lack of correlation between mRNA levels and quantitated protein abundance, results from both datasets concurred on groups of proteins/genes based on functional categorization. A number of genes (20%) and proteins (45 and 23%) were involved in processes related to protein biosynthesis. We also identified three genes/proteins involved in chromatin modification. Enzymes responsible for opening up chromatin, Hmgn3 and Hmgb1, were upregulated whereas enzymes that condense chromatin, histone H1.2, were downregulated. Genes and proteins that promote cell growth (Igfbp4, Ptma, S100a6, and Lgals3) were downregulated, whereas those that deter cell growth (Ccng2, Gsg2, and S100a11) were upregulated. Other main groups of genes and proteins include carbohydrate metabolism, signal transduction, and transport. Our findings show that an integrated genomic and proteomics approach can be effectively utilized to monitor transcriptional and posttranscriptional events of mammalian cells in culture.
机译：进行了转录组和蛋白质组学的结合分析，以鉴定在中国仓鼠卵巢（CHO）细胞中高表达和低表达dhfr-GFP融合蛋白的差异表达的关键基因和蛋白。使用专有的15 K CHO cDNA微阵列芯片对转录水平进行比较，而蛋白质组学分析则使用iTRAQ定量蛋白质谱分析技术进行。基因芯片分析显示77个差异表达的基因，其中53个基因上调，而24个基因下调。蛋白质组学分析分别为中指数期和固定期提供了75和80种蛋白质。尽管在mRNA水平和定量蛋白质丰度之间通常缺乏相关性，但两个数据集的结果均基于功能分类基于蛋白质/基因组。许多基因（20％）和蛋白质（45％和23％）参与了与蛋白质生物合成相关的过程。我们还确定了涉及染色质修饰的三个基因/蛋白质。负责打开染色质的酶Hmgn3和Hmgb1被上调，而浓缩染色质的酶组蛋白H1.2被下调。促进细胞生长的基因和蛋白质（Igfbp4，Ptma，S100a6和Lgals3）被下调，而阻止细胞生长的基因和蛋白质（Ccng2，Gsg2和S100a11）被上调。基因和蛋白质的其他主要类别包括碳水化合物的代谢，信号转导和转运。我们的发现表明，整合的基因组和蛋白质组学方法可以有效地用于监测培养物中哺乳动物细胞的转录和转录后事件。

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  • 来源
    《Molecular Biotechnology》 |2006年第2期|125-140|共16页
  • 作者

    Peter Morin Nissom; Arleen Sanny; Yee Jiun Kok; Yeo Thong Hiang; Song Hui Chuah; Tan Kher Shing; Yih Yean Lee; Tin Kam Wong; Wei-shou Hu; Miranda Yap Gek Sim; Robin Philp;

  • 作者单位

    Bioprocessing Technology Institute 20 Biopolis Way #06-01 Centros Singapore 138668;

    Bioprocessing Technology Institute 20 Biopolis Way #06-01 Centros Singapore 138668;

    Bioprocessing Technology Institute 20 Biopolis Way #06-01 Centros Singapore 138668;

    Bioprocessing Technology Institute 20 Biopolis Way #06-01 Centros Singapore 138668;

    Bioprocessing Technology Institute 20 Biopolis Way #06-01 Centros Singapore 138668;

    Bioprocessing Technology Institute 20 Biopolis Way #06-01 Centros Singapore 138668;

    Bioprocessing Technology Institute 20 Biopolis Way #06-01 Centros Singapore 138668;

    Bioprocessing Technology Institute 20 Biopolis Way #06-01 Centros Singapore 138668;

    Department of Chemical Engineering and Materials Science University of Minnesota 421 Washington Avenue SE 55455-0132 Minneapolis MN;

    Bioprocessing Technology Institute 20 Biopolis Way #06-01 Centros Singapore 138668;

    Bioprocessing Technology Institute 20 Biopolis Way #06-01 Centros Singapore 138668;

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  • 正文语种 eng
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  • 关键词

    Microarray; proteomics; Chinese hamster ovary; biotherapeutic; transcriptome; proteome;

    机译：芯片;蛋白质组学;仓鼠卵巢;生物治疗;转录组;蛋白质组;

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