Intraclonal Protein Expression Heterogeneity in Recombinant CHO Cells

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.

Development of a Microfluidic GHz Impedance Cytometer

“…An overlap between cells and beads can be observed, which shows that they have comparable size. The average cell diameter is calculated to be 12.5 μm, which is close to reported values for CHO cells of 12.9 μm [15]. A relatively large variation is to be expected, as no effort has been made to control the cell development stage during culturing.…”

Microarray profiling of preselected CHO host cell subclones identifies gene expression patterns associated with in‐creased production capacity

“…Several studies have investigated the underlying bottlenecks that limit cell specific productivities with, in part, contradictory results. This is not surprising in view of the phenotypic and genomic diversity observed in CHO cells [4][5][6]. Although the precise genes involved vary from case to case, certain cellular pathways and functions are frequently found to influence cellular productivity (Table 1).…”

“…The latter can be caused by both genomic changes and epigenetic regulation [17][18][19]. This genomic and phenotypic heterogeneity has advantages and disadvantages: On the one hand it allows the effective selection of cells with different physiological and process relevant properties during screening [6,[20][21][22][23][24][25], on the other hand it limits the stability of these properties [21,26,27] and requires large numbers of subclones to be tested over prolonged periods of time to identify the few stable clones suited for production. The endogenous heterogeneity present in CHO cells is further enhanced by the process of recombination and gene amplification during cell line development, where the gene of interest and selection markers are integrated at a random site into the host cell genome, which may cause knockout of genes as well as changes in their expression levels either by separation of genes from their genetic control elements or by co-amplification with the recombinant gene.…”

Single‐cell tracking with a reversing flow cytometer

“…Variability of properties has been indicated in the progression of certain diseases (1) and in explaining the productivity of chemicals or pharmaceuticals with engineered cultures (2,3). This variability has been generally related to genetic differences, to different positions in the cell cycle, to the exposure of a heterogeneous environment, or to stochastic variations due to the low number of molecules in individual cells.…”