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Intraclonal Protein Expression Heterogeneity in Recombinant CHO Cells

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Journal PLoS One
Date 2009 Dec 29
PMID 20037651
Citations 53
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Abstract

Therapeutic glycoproteins have played a major role in the commercial success of biotechnology in the post-genomic era. But isolating recombinant mammalian cell lines for large-scale production remains costly and time-consuming, due to substantial variation and unpredictable stability of expression amongst transfected cells, requiring extensive clone screening to identify suitable high producers. Streamlining this process is of considerable interest to industry yet the underlying phenomena are still not well understood. Here we examine an antibody-expressing Chinese hamster ovary (CHO) clone at single-cell resolution using flow cytometry and vectors, which couple light and heavy chain transcription to fluorescent markers. Expression variation has traditionally been attributed to genetic heterogeneity arising from random genomic integration of vector DNA. It follows that single cell cloning should yield a homogeneous cell population. We show, in fact, that expression in a clone can be surprisingly heterogeneous (standard deviation 50 to 70% of the mean), approaching the level of variation in mixed transfectant pools, and each antibody chain varies in tandem. Phenotypic variation is fully developed within just 18 days of cloning, yet is not entirely explained by measurement noise, cell size, or the cell cycle. By monitoring the dynamic response of subpopulations and subclones, we show that cells also undergo slow stochastic fluctuations in expression (half-life 2 to 11 generations). Non-genetic diversity may therefore play a greater role in clonal variation than previously thought. This also has unexpected implications for expression stability. Stochastic gene expression noise and selection bias lead to perturbations from steady state at the time of cloning. The resulting transient response as clones reestablish their expression distribution is not ordinarily accounted for but can contribute to declines in median expression over timescales of up to 50 days. Noise minimization may therefore be a novel strategy to reduce apparent expression instability and simplify cell line selection.

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