Improving CHO cell line performance through cell and bioprocess
engineering
A continuing goal in mammalian biomanufacturing processes is to
evaluate, modify, and ultimately enhance the performance of CHO cells in
culture. Indeed, one of the major challenges in CHO cell culture is long
term cell line stability. Torres et al . took a deeper look into
this issue, examining changes in cell culture performance, gene
expression, and metabolism over time for two cell lines. Especially
interesting was the upregulation of genes involved in cell proliferation
and survival concomitantly with changes in metabolites’ uptake and
production rates. Acknowledging the impact that culture time has on the
cell, researchers are now exploring ways to improve cell line stability,
aiming to design more predictable, consistent, and productive expression
system. One of such approaches is targeted integration; however,
identifying a CHO cell genomic loci capable of supporting high-level
protein expression is still a bottleneck. To address this need, Leeet al ., implemented the “Thousands of Reporters Integrated in
Parallel” (TRIP) high-throughput screening method, identifying several
hotspot candidates in the CHO genome exhibiting high transgene mRNA
expression. In another study, Marx et al. presented a fast and
robust method -the nanopore Cas9-targeted sequencing (nCats) pipeline -
to characterize cell clones and isolate the most promising ones. This
method was able to identify integration sites, the composition of the
integrated sequence, and the DNA methylation status in CHO cells in a
single sequencing run. Building up on CRISPR/Cas9 technology for
mammalian cells, Lee et al . developed an all-in one reporter
system to quantify gene disruption and site-specific integration (SSI)
in CHO cells. Using this system, it was possible to identify specific
molecules (inhibitors of DNA repair pathways) that enhance SSI
efficiency and thus accelerate cell engineering. Another approach to
further improve mammalian cell factories is to ameliorate cell’s
capacity to handle proteotoxic stress, which can result in cellular
apoptosis. In Segatori et al. , the challenges and opportunities
in synthetic biology for improving these programmable cell factories is
detailed. An important contribution to the field of cell line and
metabolic engineering is provided by Kontoravdi et al. with a
review on the current state of CHO genome-scale metabolic models (GEM),
their inability to model intracellular metabolism and capture
extracellular phenotypes. In addition, Kontoravdi et al .
presented an improved GEM, iCHO2441, as well as two cell line specific
GEMs for CHO-S and CHO-K1 that may serve as foundations for better
design and assess next-generation flux analysis techniques. Jimenez del
Val et al . propose a more compact network model, CHOmpact, that
can provide improved interpretations from simulations, including
identification of shifts in key metabolic behaviours. This model could
also serve as a platform for dynamic models used for process control and
optimization. The advancement in process analytical techniques (PAT) and
artificial intelligence (AI) has enabled the generation of enormous
culture datasets from biomanufacturing processes. AI-based data-driven
models permit the correlation of biological and process conditions and
cell culture states. This approach was exploited by Lee et al.that describe data-driven prediction models for forecasting multi-step
ahead profiles of mAbs produced in CHO towards bioprocess digital twins.
A complementary approach to cell line engineering is the development of
improved biomanufacturing processes. To address that need, Ben Yahiaet al. worked on intensified processes by optimizing the feeding
strategy and specific power input (P/V) in a high-cell-density (HCD)
seed bioreactor operated in fed-batch mode towards improved monoclonal
antibodies (mAb) expression in the production bioreactor. Interestingly
they report a positive impact of cellular “organized stress” in the
seed bioreactor on the production performance. Chotteau et al .
implemented a Design of Experiment (DoE) approach to design an optimal
CHO culture medium capable of supporting the operation of
microbioreactors in perfusion at HCD and low specific perfusion rates
while maintaining constant specific product quality attributes such as
N-glycosylation profile of the produced antibody. Using a similar
statistical design methodology, Ladiwala et al . fine-tuned
specific amino acids levels in reference basal and feed media in order
to limit production of inhibitory metabolites, ultimately enhancing peak
viable cell densities and product titers. Alternatively, Naik et
al. looked at adding glycolysis inhibitors to limit the production of
lactate as metabolic by-product in CHO cell cultures. They found that
specific glucose analogs could lower peak lactate concentrations while
also providing an increase in the final titers, although there was some
changes in glycosylation patterns indicating an effect on product
quality.