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Feb 1, 2011 (Vol. 31, No. 3)

Tips on How to Make Good Cells Better

Cell-Line Optimization Takes Many Forms, and Each Approach Has Its Adherents

  • Nurture Becomes Nature

    Sometimes lost in the nature-vs.-nurture debate on factors affecting productivity is the affect of process conditions on gene expression. For example, adapting attachment-dependent cells to suspension conditions can dramatically influence gene expression.

    Using genome-wide expression profiles for CHO cells, Yung-Shyeng Tsao, Ph.D., senior principal scientist at Merck, identified more than 500 genes, and several major pathways that are “profoundly affected by suspension adaptation.”

    As expected, pathways for cell-cell adhesion were downregulated, as were mechanisms for cell cycle, nucleotide synthesis, transcription, translation, and others. Upregulated pathways included those governing extracellular matrix, basement membrane, hypoxia signaling, and amino acid transporters. Genes controlling lipid transport and synthesis were upregulated by as much as a factor of 500.

    Dr. Tsao’s principal approach to analyzing genomes is a CHO DNA microarray. Now in its third generation, the microarray was originally developed through the CHO Consortium, an academic-industrial group dedicated to improving CHO production cells. The microarray analyzes hamster ovary cells and other tissues as well. “CHO cells have been passaged for many generations, in many different locations, which has been selective for the expression or downregulation of certain genes,” Dr. Tsao explains. “So if you only examine CHO cells you cannot cover the entire genome.”

    Merck is also profiling cell metabolism, partly in collaboration with Metabolon. This detailed analysis is too expensive and time-consuming to conduct for every project, but it does provide key insights into the ultimate status of cells. For select projects Dr. Tsao compares the genome, proteome, and metabolome. The overlaps as one moves downstream from genes to small molecules can confirm, for example, which genes ultimately affect cell performance.

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