Analysis of an artificially selected GS-NS0 variant with increased resistance to apoptosis

Molecular biomarkers identification and applications in CHO bioprocessing

Biomarkers are valuable tools in clinical research where they allow to predict susceptibility to diseases, or response to specific treatments. Likewise, biomarkers can be extremely useful in the biomanufacturing of therapeutic proteins. Indeed, constraints such as short timelines and the need to find hyper-productive cells could benefit from a data-driven approach during cell line and process development. Many companies still rely on large screening capacities to develop productive cell lines, but as they reach a limit of production, there is a need to go from empirical to rationale procedures. Similarly, during bioprocessing runs, substrate consumption and metabolism wastes are commonly monitored. None of them possess the ability to predict the culture behavior in the bioreactor. Big data driven approaches are being adapted to the study of industrial mammalian cell lines, enabled by the publication of Chinese hamster and CHO genome assemblies which allowed the use of next-generation sequencing with these cells, as well as continuous proteome and metabolome annotation. However, if these different -omics technologies contributed to the characterization of CHO cells, there is a significant effort remaining to apply this knowledge to biomanufacturing methods. The correlation of a complex phenotype such as high productivity or rapid growth to the presence or expression level of a specific biomarker could save time and effort in the screening of manufacturing cell lines or culture conditions. In this review we will first discuss the different biological molecules that can be identified and quantified in cells, their detection techniques, and associated challenges. We will then review how these markers are used during the different steps of cell line and bioprocess development, and the inherent limitations of this strategy.

The relationship between mTOR signalling pathway and recombinant antibody productivity in CHO cell lines

Background

High recombinant protein productivity in mammalian cell lines is often associated with phenotypic changes in protein content, energy metabolism, and cell growth, but the key determinants that regulate productivity are still not clearly understood. The mammalian target of rapamycin (mTOR) signalling pathway has emerged as a central regulator for many cellular processes including cell growth, apoptosis, metabolism, and protein synthesis. This role of this pathway changes in response to diverse environmental cues and allows the upstream proteins that respond directly to extracellular signals (such as nutrient availability, energy status, and physical stresses) to communicate with downstream effectors which, in turn, regulate various essential cellular processes.

Results

In this study, we have performed a transcriptomic analysis using a pathway-focused polymerase chain reaction (PCR) array to compare the expression of 84 target genes related to the mTOR signalling in two recombinant CHO cell lines with a 17.4-fold difference in specific monoclonal antibody productivity (q_p). Eight differentially expressed genes that exhibited more than a 1.5-fold change were identified. Pik3cd (encoding the Class 1A catalytic subunit of phosphatidylinositol 3-kinase [PI3K]) was the most differentially expressed gene having a 71.3-fold higher level of expression in the high producer cell line than in the low producer. The difference in the gene’s transcription levels was confirmed at the protein level by examining expression of p110δ.

Conclusion

Expression of p110δ correlated with specific productivity (q_p) across six different CHO cell lines, with a range of expression levels from 3 to 51 pg/cell/day, suggesting that p110δ may be a key factor in regulating productivity in recombinant cell lines.