No abstract

High-throughput siRNA screens were only recently applied to cell factories to identify novel engineering targets which are able to boost cells towards desired phenotypes. While siRNA libraries exist for model organisms such as mice, no CHO-specific library is publicly available, hindering the application of this technique to CHO cells. The optimization of these cells is of special interest, as they are the main host for the production of therapeutic proteins. Here, we performed a cross-species approach by applying a mouse whole-genome siRNA library to CHO cells, optimized the protocol for suspension cultured cells, as this is the industrial practice for CHO cells, and developed an in silico method to identify functioning siRNAs, which also revealed the limitations of using cross-species libraries. With this method, we were able to identify several genes that, upon knockdown, enhanced the total productivity in the primary screen. A second screen validated two of these genes, Rad21 and Chd4 , whose knockdown was tested in additional CHO cell lines, confirming the induced high productivity phenotype, but also demonstrating the cell line/clone specificity of engineering effects.

Chinese hamster ovary (CHO) cells are the most extensively used mammalian production system for biologics intended for use in humans. A critical step in the establishment of production cell lines is single cell cloning, with the objective of achieving high productivity and product quality. Despite general use, knowledge of the effects of this process is limited. Importantly, single cell cloned cells display a wide array of observed phenotypes, which so far was attributed to the instability and variability of the CHO genome. In this study we present data indicating that the emergence of diverse phenotypes during single cell cloning is associated with changes in DNA methylation patterns and transcriptomes that occur during the subcloning process. The DNA methylation pattern of each analyzed subclone, randomly picked from all outgrowing clones of the experiment, had unique changes preferentially found in regulatory regions of the genome such as enhancers, and de‐enriched in actively transcribed sequences (not including the respective promoters), indicating that these changes resulted in adaptations of the relative gene expression pattern. The transcriptome of each subclone also had a significant number of individual changes. These results indicate that epigenetic regulation is a hidden, but important player in cell line development with a major role in the establishment of high performing clones with improved characteristics for bioprocessing.

Chinese hamster ovary (CHO) cells produce a large share of today's biopharmaceuticals. Still, the generation of satisfactory producer cell lines is a tedious undertaking. Recently, it was found that CHO cells, when exposed to new environmental conditions, modify their epigenome, suggesting that cells adapt their gene expression pattern to handle new challenges. The major aim of the present study was to employ artificially induced, random changes in the DNA-methylation pattern of CHO cells to diversify cell populations and consequently increase the finding of cell lines with improved cellular characteristics. To achieve this, DNA methyltransferases and/or the ten-eleven translocation enzymes were downregulated by RNA interference over a time span of ∼16 days. Methylation analysis of the resulting cell pools revealed that the knockdown of DNA methyltransferases was highly effective in randomly demethylating the genome. The same approach, when applied to stable CHO producer cells resulted in (a) an increased productivity diversity in the cell population, and (b) a higher number of outliers within the population, which resulted in higher specific productivity and titer in the sorted cells. These findings suggest that epigenetics play a previously underestimated, but actually important role in defining the overall cellular behavior of production clones.

Predictably regulating protein expression levels to improve recombinant protein production has become an important tool, but is still rarely applied to engineer mammalian cells. We therefore sought to set-up an easy-to-implement toolbox to facilitate fast and reliable regulation of protein expression in mammalian cells by introducing defined RNA hairpins, termed ‘regulation elements (RgE)’, in the 5′-untranslated region (UTR) to impact translation efficiency. RgEs varying in thermodynamic stability, GC-content and position were added to the 5′-UTR of a fluorescent reporter gene. Predictable translation dosage over two orders of magnitude in mammalian cell lines of hamster and human origin was confirmed by flow cytometry. Tuning heavy chain expression of an IgG with the RgEs to various levels eventually resulted in up to 3.5-fold increased titers and fewer IgG aggregates and fragments in CHO cells. Co-expression of a therapeutic Arylsulfatase-A with RgE-tuned levels of the required helper factor SUMF1 demonstrated that the maximum specific sulfatase activity was already attained at lower SUMF1 expression levels, while specific production rates steadily decreased with increasing helper expression. In summary, we show that defined 5′-UTR RNA-structures represent a valid tool to systematically tune protein expression levels in mammalian cells and eventually help to optimize recombinant protein expression.

No abstract

Chinese hamster ovary (CHO) cells are the leading platform for the production of biopharmaceuticals with human-like glycosylation. The standard practice for cell line generation relies on trial and error approaches such as adaptive evolution and high-throughput screening, which typically take several months. Metabolic modeling could aid in designing better producer cell lines and thus shorten development times. The genome-scale metabolic model (GSMM) of CHO can accurately predict growth rates. However, in order to predict rational engineering strategies it also needs to accurately predict intracellular fluxes. In this work we evaluated the agreement between the fluxes predicted by parsimonious flux balance analysis (pFBA) using the CHO GSMM and a wide range of 13C metabolic flux data from literature. While glycolytic fluxes were predicted relatively well, the fluxes of tricarboxylic acid (TCA) cycle were vastly underestimated due to too low energy demand. Inclusion of computationally estimated maintenance energy significantly improved the overall accuracy of intracellular flux predictions. Maintenance energy was therefore determined experimentally by running continuous cultures at different growth rates and evaluating their respective energy consumption. The experimentally and computationally determined maintenance energy were in good agreement. Additionally, we compared alternative objective functions (minimization of uptake rates of seven nonessential metabolites) to the biomass objective. While the predictions of the uptake rates were quite inaccurate for most objectives, the predictions of the intracellular fluxes were comparable to the biomass objective function.

Manipulation of multiple genes to engineer Chinese Hamster Ovary (CHO) cells for better performance in production processes of biopharmaceuticals has recently become more and more popular. Yet, identification of useful genes and the unequivocally assessment of their effect alone and in combination(s) on the cellular phenotype is difficult due to high variation between subclones. Here, we present development and proof-of-concept of a novel engineering strategy using multiplexable activation of artificially repressed genes (MAARGE). This strategy will allow faster screening of overexpression of multiple genes in all possible combinations. MAARGE, in its here presented installment, comprises four different genes of interest that can all be stably integrated into the genome from one plasmid in a single transfection. Three of the genes are initially repressed by a repressor element (RE) that is integrated between promoter and translation start site. We show that an elongated 5'-UTR with an additional transcription termination (poly(A)) signal most efficiently represses protein expression. Distinct guide RNA (gRNA) targets flanking the REs for each gene then allow to specifically delete the RE by CRISPR/Cas9 and thus to activate the expression of the corresponding gene(s). We show that both individual and multiplexed activation of the genes of interest in a stably transfected CHO cell line is possible. Also, upon transfection of this stable cell line with all three gRNAs together, it was possible to isolate cells that express all potential gene combinations in a single experiment.