CHO Cell Culture Research Articles

1 H NMR-based process understanding and biochemical marker identification methodology for monitoring CHO cell culture process during commercial-scale manufacturing.

Controlling the process of CHO cell fed-batch culture is critical for biologics quality control. However, the biological complexity of cells has hampered the reliable process understanding for industrial manufacturing. In this study, a workflow was developed for the consistency monitoring and biochemical marker identification of the commercial-scale CHO cell culture process through 1 H NMR assisted with multivariate data analysis (MVDA). Firstly, a total of 63 metabolites were identified in this study object in 1 H NMR spectra of the CHO cell-free supernatants. Secondly, multivariate statistical process control (MSPC) charts were used to evaluate process consistency. According to MSPC charts, the batch-to-batch quality consistency was high, indicating the CHO cell culture process at the commercial scale was well-controlled and stable. Then, the biochemical marker identification was provided through orthogonal partial least square discriminant analysis (OPLS-DA) based S-line plots during the cell logarithmic expansion, stable growth, and decline phases. Identified biochemical markers of the three cell growth phases were as follows: L-glutamine, pyroglutamic acid, 4-hydroxyproline, choline, glucose, lactate, alanine, and proline were of the logarithmic growth phase; isoleucine, leucine, valine, acetate, and alanine were of the stable growth phase; acetate, glycine, glycerin, and gluconic acid were of the cell decline phase. Additional potential metabolic pathways that might influence the cell culture phase transitions were demonstrated. The workflow proposed in this study demonstrates that the combination of MVDA tools and 1 H NMR technology is highly appealing to the research of the biomanufacturing process, and applies well to provide guidance in future work on consistency evaluation and biochemical marker monitoring of the production of other biologics.

Understanding the effect of temperature downshift on CHO cell growth, antibody titer and product quality by intracellular metabolite profiling and in vivo monitoring of redox state.

The strategy of temperature downshift has been widely used in the biopharmaceutical industry to improve antibody production and cell-specific production rate (qp ) with Chinese hamster ovary cells (CHO). However, the mechanism of temperature-induced metabolic rearrangement, especially important intracellular metabolic events, remains poorly understood. In this work, in order to explore the mechanisms of temperature-induced cell metabolism, we systematically assessed the differences in cell growth, antibody expression, and antibody quality between high-producing (HP) and low-producing (LP) CHO cell lines under both constant temperature (37°C) and temperature downshift (37°C→33°C) settings during fed-batch culture. Although the results showed that low-temperature culture during the late phase of exponential cell growth significantly reduced the maximum viable cell density (p < 0.05) and induced cell cycle arrest in the G0/G1 phase, this temperature downshift led to a higher cellular viability and increased antibody titer by 48% and 28% in HP and LP CHO cell cultures, respectively (p < 0.001), and favored antibody quality reflected in reduced charge heterogeneity and molecular size heterogeneity. Combined extra- and intra-cellular metabolomics analyses revealed that temperature downshift significantly downregulated intracellular glycolytic and lipid metabolic pathways while upregulated tricarboxylic acid (TCA)cycle, and particularly featured upregulated glutathione metabolic pathways. Interestingly, all these metabolic pathways were closely associated with the maintenance of intracellular redox state and oxidative stress-alleviating strategies. To experimentally address this, we developed two high-performance fluorescent biosensors, denoted SoNar and iNap1, for real-time monitoring of intracellular nicotinamide adenine dinucleotide/nicotinamide adenine dinucleotide + hydrogen (NAD+ /NADH) ratio and nicotinamide adenine dinucleotide phosphate (NADPH) amount, respectively. Consistent with such metabolic rearrangements, the results showed that temperature downshift decreased the intracellular NAD+ /NADH ratio, which might be ascribed to the re-consumption of lactate, and increased the intracellular NADPH amount (p < 0.01) to scavenge intracellular reactive oxygen species (ROS) induced by the increased metabolic requirements for high-level expression of antibody. Collectively, this study provides a metabolic map of cellular metabolic rearrangement induced by temperature downshift and demonstrates the feasibility of real-time fluorescent biosensors for biological processes, thus potentially providing a new strategy for dynamic optimization of antibody production processes.

Depth filter material process interaction in the harvest of mammalian cells.

Upstream advances have led to increased mAb titers above 5g/L in 14-day fed-batch cultures. This is accompanied by higher cell densities and process-related impurities such as DNA and Host Cell Protein (HCP), which have caused challenges for downstream operations. Depth filtration remains a popular choice for harvesting CHO cell culture, and there is interest in utilizing these to remove process-related impurities at the harvest stage. Operation of the harvest stage has also been shown to affect the performance of the Protein A chromatography step. In addition, manufacturers are looking to move away from natural materials such as cellulose and Diatomaceous Earth (DE) for better filter consistency and security of supply. Therefore, there is an increased need for further understanding and knowledge of depth filtration. This study investigates the effect of depth filter material and loading on the Protein A resin lifetime with an industrially relevant high cell density feed material (40 million cells/ml). It focuses on the retention of process-related impurities such as DNA and HCP through breakthrough studies and a novel confocal microscopy method for imaging foulant in-situ. An increase in loading of the primary-synthetic filter by a third, led to earlier DNA breakthrough in the secondary filter, with DNA concentration at a throughput of 50 L/m2 being more than double. Confocal imaging of the depth filters showed that the foulant was pushed forward into the filter structure with higher loading. The additional two layers in the primary-synthetic filter led to better pressure profiles in both primary and secondary filters but did not help to retain HCP or DNA. Reduced filtrate clarity, as measured by OD600, was 1.6 fold lower in the final filtrate where a synthetic filter train was used. This was also associated with precipitation in the Protein A column feed. Confocal imaging of resin after 100 cycles showed that DNA build-up around the outside of the bead was associated with synthetic filter trains, leading to potential mass transfer problems.

Improvement of Recombinant Proteins Production by Inducing Mitochondrial Biogenesis in CHO Cell Culture

Improvement of Recombinant Proteins Production by Inducing Mitochondrial Biogenesis in CHO Cell Culture

Automated assembly of hybrid dynamic models for CHO cell culture processes

The emergent realisation of Industry 4.0 principles across biomanufacturing, through recent endeavours, will markedly enhance the development and manufacture of modern therapeutics. Through implementation of digital process models, a greater understanding of the intricate relationship between product quality attributes and manufacturing process performance may be established. While contributing towards accelerated process development, representative process models enable advanced optimisation of process parameters, thus having a tangible impact on the assurance of product quality and manufacturing robustness. Hybrid approaches, which couple mechanistic interpretability with statistical data-fitting, are posed to broaden the value and utility of digital models. To augment the advancement in modelling techniques and high-throughput technology, there is a growing requirement for automated approaches towards data processing and model assembly. In this study, a novel strategy is proposed, which leverages saturation and sigmoidal relationships, along with an underlying material balance framework, for the automated assembly of hybrid dynamic models of cell growth. The proposed hybrid model is compared against an equivalent mechanistic model based on Monod expressions. While both models achieve a reasonable fit against experimental data, the hybrid model demonstrates superior predictive performance. Development of automated hybrid models, as demonstrated in this study, may greatly accelerate process digitalisation across biopharmaceutical manufacture.

Enhanced recombinant protein production in CHO cell continuous cultures under growth-inhibiting conditions is associated with an arrested cell cycle in G1/G0 phase.

Low temperature and sodium butyrate (NaBu) are two of the most used productivity-enhancing strategies in CHO cell cultures during biopharmaceutical manufacturing. While these two approaches alter the balance in the reciprocal relationship between cell growth and productivity, we do not fully understand their mechanisms of action beyond a gross cell growth inhibition. Here, we used continuous culture to evaluate the differential effect of low temperature and NaBu supplementation on CHO cell performance and gene expression profile. We found that an increase in cell-productivity under growth-inhibiting conditions was associated with the arrest of cells in the G1/G0 phase. A transcriptome analysis revealed that the molecular mechanisms by which low temperature and NaBu arrested cell cycle in G1/G0 differed from each other through the deregulation of different cell cycle checkpoints and regulators. The individual transcriptome changes in pattern observed in response to low temperature and NaBu were retained when these two strategies were combined, leading to an additive effect in arresting the cell cycle in G1/G0 phase. The findings presented here offer novel molecular insights about the cell cycle regulation during the CHO cell bioprocessing and its implications for increased recombinant protein production. This data provides a background for engineering productivity-enhanced CHO cell lines for continuous manufacturing.

Recovery and characterization of secretory immunoglobulin A from CHO cell culture supernatant

Recovery and characterization of secretory immunoglobulin A from CHO cell culture supernatant

First Steps of Digitalization and Optimization of a CHO Cell Culture Process for Recombinant mAb Production

First Steps of Digitalization and Optimization of a CHO Cell Culture Process for Recombinant mAb Production

Model-based intensification of CHO cell cultures: One-step strategy from fed-batch to perfusion.

There is a growing interest in continuous processing of the biopharmaceutical industry. However, the technology transfer from traditional batch-based processes is considered a challenge as protocol and tools still remain to be established for their usage at the manufacturing scale. Here, we present a model-based approach to design optimized perfusion cultures of Chinese Hamster Ovary cells using only the knowledge captured during small-scale fed-batch experiments. The novelty of the proposed model lies in the simplicity of its structure. Thanks to the introduction of a new catch-all variable representing a bulk of by-products secreted by the cells during their cultivation, the model was able to successfully predict cellular behavior under different operating modes without changes in its formalism. To our knowledge, this is the first experimentally validated model capable, with a single set of parameters, to capture culture dynamic under different operating modes and at different scales.

Advancing Raman model calibration for perfusion bioprocesses using spiked harvest libraries.

Raman spectroscopy has gained popularity to monitor multiple process indicators simultaneously in biopharmaceutical processes. However, robust and specific model calibration remains a challenge due to insufficient analyte variability to train the models and high cross-correlation of various media components and artifacts throughout the process. A systematic Raman calibration workflow for perfusion processes enabling highly specific and fast model calibration was developed. Harvest libraries consisting of frozen harvest samples from multiple CHO cell culture bioreactors collected at different process times were established. Model calibration was subsequently performed in an offline setup using a flow cell by spiking process harvest with glucose, raffinose, galactose, mannose, and fructose. In a screening phase, Raman spectroscopy was proven capable not only to distinguish sugars with similar chemical structures in perfusion harvest but also to quantify them independently in process-relevant concentrations. In a second phase, a robust and highly specific calibration model for simultaneous glucose (root mean square error prediction [RMSEP]=0.32gL-1 ) and raffinose (RMSEP=0.17gL-1 ) real-time monitoring was generated and verified in a third phase during a perfusion process. The proposed novel offline calibration workflow allowed proper Raman peak decoupling, reduced calibration time from months down to days, and can be applied to other analytes of interest including lactate, ammonia, amino acids, or product titer.

One kind of challenging tetrapeptide biomimetic chromatographic resin for antibody separation

Short peptide biomimetic chromatography technology as a developing protein separation technology has huge potential for antibody purification. In this study, four tetrapeptide ligands (Ac-FYKH, Ac-YEHF, Ac-YFLH and Ac-FYHI) with high potential binding ability to antibody were selected for the optimal ligand to antibody purification. The results showed that Ac-YEHF-4FF resin had higher binding capacity and selectivity for hIgG among the four resins. And at pH 7.0 and 0.3 ml/min, the highest Q10%-hIgG of Ac-YEHF-4FF resin was 26.2 mg/ml resin while its Q10%-BSA was just 2.2 mg/ml resin. Further, Ac-YEHF-4FF resin was used to purify protein mixtures. By binding at pH 7.0 and being eluted at pH 5.0 and pH 4.0, Ac-YEHF-4FF resin was well used to separate hIgG from BSA containing feedstock, HSA containing feedstock and human serum with the purity and yield both more than 95 %. And the screened resin could also separate mAb from CHO cell culture supernatant with purity 94.3 % and yield 97.5 %. The adsorption and separation results of Ac-YEHF-4FF resin indicated that the goal of getting the efficacy of critical residues from protein A to biomimetic its structure and function could be achieved, which had great significance to the establishment and improvement of tetrapeptide biomimetic chromatography, and also provided a new method for the field of antibody separation and purification.

Generic Chemometric Models for Metabolite Concentration Prediction Based on Raman Spectra.

Chemometric models for on-line process monitoring have become well established in pharmaceutical bioprocesses. The main drawback is the required calibration effort and the inflexibility regarding system or process changes. So, a recalibration is necessary whenever the process or the setup changes even slightly. With a large and diverse Raman dataset, however, it was possible to generate generic partial least squares regression models to reliably predict the concentrations of important metabolic compounds, such as glucose-, lactate-, and glutamine-indifferent CHO cell cultivations. The data for calibration were collected from various cell cultures from different sites in different companies using different Raman spectrophotometers. In testing, the developed “generic” models were capable of predicting the concentrations of said compounds from a dilution series in FMX-8 mod medium, as well as from an independent CHO cell culture. These spectra were taken with a completely different setup and with different Raman spectrometers, demonstrating the model flexibility. The prediction errors for the tests were mostly in an acceptable range (<10% relative error). This demonstrates that, under the right circumstances and by choosing the calibration data carefully, it is possible to create generic and reliable chemometric models that are transferrable from one process to another without recalibration.

Data-driven and model-guided systematic framework for media development in CHO cell culture

Proposed herein is a systematic media design framework that combines multivariate statistical approaches with in silico analysis of a genome-scale metabolic model of Chinese hamster ovary cell. The framework comprises sequential modules including cell culture and metabolite data collection, multivariate data analysis, in silico modeling and flux prediction, and knowledge-based identification of target media components. Two monoclonal antibody-producing cell lines under two different media conditions were used to demonstrate the applicability of the framework. First, the cell culture and metabolite profiles from all conditions were generated, and then statistically and mechanistically analyzed to explore combinatorial effects of cell line and media on intracellular metabolism. As a result, we found a metabolic bottleneck via a redox imbalance in the TCA cycle in the poorest growth condition, plausibly due to inefficient coenzyme q10-q10h2 recycling. Subsequent in silico simulation allowed us to suggest q10 supplementation to debottleneck the imbalance for the enhanced cellular energy state and TCA cycle activity. Finally, experimental validation was successfully conducted by adding q10 in the media, resulting in increased cell growth. Taken together, the proposed framework rationally identified target nutrients for cell line-specific media design and reformulation, which could greatly improve cell culture performance.

ANALISIS FAKTOR YANG MEMPENGARUHI PERTUMBUHAN KULTUR SEL CHO (Chinase Hamster Ovarium) PADA PEMBUATAN OBAT TRASTUZUMAB DI PT. BIO FARMA

This study examines what factors can affect the growth of CHO cell cultures which are often used in biological and medical research and commercially in the production of therapeutic proteins. The purpose of this study was to determine whether CHO cells were able to grow and reproduce with the process flow and manufacturing method of drug preparations in accordance with the requirements of the applicable legislation. The workings of this research are divided into two stages, namely the microbiological stage and the biotechnology stage. The microbiological stage begins with making a working culture, then purification is carried out for culture rejuvenation, harvesting, cell culture breakdown, and purification of target cells. At the biotechnology stage, protein measurements were carried out, Optical Density 600 observations, polyacrylamide gel SDS electrophoresis, and gel electrophoresis staining.

High-density adherent culture of CHO cells using rolled scaffold bioreactor.

Rapid expansion of biopharmaceutical market calls for more efficient and reliable platforms to culture mammalian cells on a large scale. Stirred-tank bioreactors have been widely used for large-scale cell culture. However, it requires months of trials and errors to optimize culture conditions for each cell line. In this article, we extend our earlier studies on rolled scaffold (RS) bioreactors for high-density adherent cell culture and report two new implementations of RSs with greatly enhanced mass-manufacturability, termed as Mesh-RS and Fiber-RS. CHO-K1 cells were successfully expanded in Mesh-RS and Fiber-RS bioreactors with an average growth rate of 1.09 ± 0.04 1/day and 0.95 ± 0.07 1/day, which were higher than those reported in similar studies. Fiber-RS bioreactor exhibited a very high cell density of 72.8 × 106 cells/ml. Besides, a dialyzer was integrated into the RS bioreactor to remove cellular waste and to replenish nutrients without disturbing the cells. By collecting the dialyzed media separately, the dialysis efficiency was significantly improved. In conclusion, the developed RS bioreactor has a strong potential to provide a highly reliable and easily scalable platform for large-scale cell culture in the biopharmaceutical industry.

Oxygen Transfer Rate (OTR) Prediction Model for CHO Cell Culture in Shake Flasks

Oxygen Transfer Rate (OTR) Prediction Model for CHO Cell Culture in Shake Flasks

Real-time amino acid and glucose monitoring system for the automatic control of nutrient feeding in CHO cell culture using Raman spectroscopy.

An innovative, Raman spectroscopy-based monitoring and control system is introduced in this paper for designing dynamic feeding strategies that allow the maintenance of key cellular nutrients at an ideal level in Chinese hamster ovary cell culture. The Partial Least Squares calibration models built for glucose, lactate and 16 (out of 20) individual amino acids had very good predictive power with low root mean square errors values and high square correlation coefficients. The developed models used for real-time measurement of nutrient and by-product concentrations allowed us to gain better insight into the metabolic behavior and nutritional consumption of cells. To establish a more beneficial nutritional environment for the cells, two types of dynamic feeding strategies were used to control the delivery of two-part multi-component feed media according to the prediction of Raman models (glucose or arginine). As a result, instead of high fluctuations, the nutrients (glucose together with amino acids) were maintained at the desired level providing a more balanced environment for the cells. Moreover, the use of amino acid-based feeding control enabled to prevent the excessive nutrient replenishment and was economically beneficial by significantly reducing the amount of supplied feed medium compared to the glucose-based dynamic fed culture.

Valine feeding reduces ammonia production through rearrangement of metabolic fluxes in central carbon metabolism of CHO cells.

Ammonia is a toxic byproduct of CHO cell metabolism, which inhibits cell growth, reduces cell viability, alters glycosylation, and decreases recombinant protein productivity. In an attempt to minimize the ammonium accumulation in cell culture media, different amino acids were added individually to the culture medium before the production phase to alleviate the negative effects of ammonium on cell culture performance. Among all the amino acids examined in this study, valine showed the most positive impact on CHO cell culture performance. When the cultured CHO cells were fed with 5mM valine, EPO titer was increased by 25% compared to the control medium, and ammonium and lactate production were decreased by 23 and 26%, respectively, relative to the control culture. Moreover, the sialic acid content of the EPO protein in valine-fed culture was higher than in the control culture, most likely because of the lower ammonium concentration. Flux balance analysis (FBA) results demonstrated that the citric acid cycle was enriched by valine feeding. The measurement of TCA cycle activity supported this finding. The analysis revealed that there might be a link between promoting tricarboxylic acid (TCA) cycle metabolism in valine-fed culture and reduction in lactate and ammonia accumulation. Furthermore, in valine-fed culture, FBA outcomes showed that alanine was excreted into the medium as the primary mechanism for reducing ammonium concentration. It was predicted that the elevated TCA cycle metabolism was concurrent with an increment in recombinant protein production. Taken together, our data demonstrate that valine addition could be an effective strategy for mitigating the negative impacts of ammonium and enhancing glycoprotein production in both quality and quantity. KEY POINTS: • Valine feeding can mitigate the negative impacts of ammonia on CHO cell growth. • Valine addition assists the ammonia removal mechanism by enriching the TCA cycle. • Ammonia is removed from the media through alanine excretion in valine-fed culture.

Comparison of partial least square, artificial neural network, and support vector regressions for real-time monitoring of CHO cell culture processes using in situ near-infrared spectroscopy.

The biopharmaceutical industry must guarantee the efficiency and biosafety of biological medicines, which are quite sensitive to cell culture process variability. Real-time monitoring procedures based on vibrational spectroscopy such as near-infrared (NIR) spectroscopy, are then emerging to support innovative strategies for retro-control of key parameters as substrates and by-product concentration. Whereas monitoring models are mainly constructed using partial least squares regression (PLSR), spectroscopic models based on artificial neural networks (ANNR) and support vector regression (SVR) are emerging with promising results. Unfortunately, analysis of their performance in cell culture monitoring has been limited. This study was then focused to assess their performance and suitability for the cell culture process challenges. PLSR had inferior values of the determination coefficient (R2 ) for all the monitored parameters (i.e., 0.85, 0.93, and 0.98, respectively for the PLSR, SVR, and ANNR models for glucose). In general, PLSR had a limited performance while models based on ANNR and SVR have been shown superior due to better management of inter-batch heterogeneity and enhanced specificity. Overall, the use of SVR and ANNR for the generation of calibration models enhanced the potential of NIR spectroscopy as a monitoring tool.

Equal mixing time enables scale‐down and optimization of a CHO cell culture process using a shaken microbioreactor system

The advancement of microbioreactor technology in recent years has transformed early- and mid-stage process development. The monitoring and control capabilities of microbioreactors not only promote the quick accumulation of process knowledge but has also led to an increased scalability when compared to traditionally used systems such as shake flasks and microtitre plates. This study seeks to establish a framework for the micro-Matrix microbioreactor (Applikon-Biotechnology BV) as process development tool. Using the Dual Indicator System for Mixing Time, the system was initially characterized for mixing properties at varying operating conditions, which was found to yield mixing times between 0.9 and 41.8 s. A matched mixing time was proposed as scale-down criterion for an IgG4 producing GS-CHO fed-batch process between a 5 L stirred tank reactor (STR) and the micro-Matrix microbioreactor. Growth trends, maximum viable cell concentrations, final titre, and glycoprofiles were nearly identical at both scales. The scale-down model was then employed to optimize a bolus feeding regime using response surface methodology, which led to a 25.4% increase of the space-time yield and a 25% increase of the final titre. The optimized feeding strategy was validated at the small-scale and successfully scaled up to the 5 L STR. This work for the first time provides a framework of how the micro-Matrix microbioreactor can be implemented in a bioprocess development workflow and demonstrates scalability of growth and production kinetics as well as IgG4 glycosylation between the micro-Matrix and a benchtop-scale STR system.