Identification and control of novel growth inhibitors in fed-batch cultures of Chinese hamster ovary cells

Metabolic engineering of CHO cells towards cysteine prototrophy and systems analysis of the ensuing phenotype

Chinese hamster ovary (CHO) cells require cysteine for growth and productivity in fed-batch cultures. In intensified processes, supplementation of cysteine at high concentrations is a challenge due to its limited solubility and instability in solution. Methionine can be converted to cysteine (CYS) but key enzymes, cystathionine beta-synthase (Cbs) and cystathionine gamma-lyase (Cth), are not active in CHO cells resulting in accumulation of an intermediate, homocysteine (HCY), in cell culture milieu. In this study, Cbs and Cth were overexpressed in CHO cells to confer cysteine prototrophy, i.e., the ability to grow in a cysteine free environment. These pools (CbCt) needed homocysteine and beta-mercaptoethanol (βME) to grow in CYS-free medium. To increase intracellular homocysteine levels, Gnmt was overexpressed in CbCt pools. The resultant cell pools (GnCbCt), post adaptation in CYS-free medium with decreasing residual HCY and βME levels, were able to proliferate in the HCY-free, βME-free and CYS-free environment. Interestingly, CbCt pools were also able to be adapted to grow in HCY-free and CYS-free conditions, albeit at significantly higher doubling times than GnCbCt cells, but couldn't completely adapt to βME-free conditions. Further, single cell clones derived from the GnCbCt cell pool had a wide range in expression levels of Cbs, Cth and Gnmt and, when cultivated in CYS-free fed-batch conditions, performed similarly to the wild type (WT) cell line cultivated in CYS supplemented fed-batch culture. Intracellular metabolomic analysis showed that HCY and glutathione (GSH) levels were lower in the CbCt pool in CYS-free conditions but were restored closer to WT levels in the GnCbCt cells cultivated in CYS-free conditions. Transcriptomic analysis showed that GnCbCt cells upregulated several genes encoding transporters as well as methionine catabolism and transsulfuration pathway enzymes that support these cells to biosynthesize cysteine effectively. Further, 'omics analysis suggested CbCt pool was under ferroptotic stress in CYS-free conditions, which, when inhibited, enhanced the growth and viability of these cells in CYS-free conditions.

Harnessing metabolic plasticity in CHO cells for enhanced perfusion cultivation

Chinese Hamster Ovary (CHO) cells have rapidly become a cornerstone in biopharmaceutical production. Recently, a reinvigoration of perfusion culture mode in CHO cell cultivation has been observed. However, most cell lines currently in use have been engineered and adapted for fed-batch culture methods, and may not perform optimally under perfusion conditions. To improve the cell's resilience and viability during perfusion culture, we cultured a triple knockout CHO cell line, deficient in three apoptosis related genes BAX, BAK, and BOK in a perfusion system. After 20 days of culture, the cells exhibited a halt in cell proliferation. Interestingly, following this phase of growth arrest, the cells entered a second growth phase. During this phase, the cell numbers nearly doubled, but cell specific productivity decreased. We performed a proteomics investigation, elucidating a distinct correlation between growth arrest and cell cycle arrest and showing an upregulation of the central carbon metabolism and oxidative phosphorylation. The upregulation was partially reverted during the second growth phase, likely caused by intragenerational adaptations to stresses encountered. A phase-dependent response to oxidative stress was noted, indicating glutathione has only a secondary role during cell cycle arrest. Our data provides evidence of metabolic regulation under high cell density culturing conditions and demonstrates that cell growth arrest can be overcome. The acquired insights have the potential to not only enhance our understanding of cellular metabolism but also contribute to the development of superior cell lines for perfusion cultivation.

Advancements in CHO metabolomics: techniques, current state and evolving methodologies

Background: Investigating the metabolic behaviour of different cellular phenotypes, i.e., good/bad grower and/or producer, in production culture is important to identify the key metabolite(s)/pathway(s) that regulate cell growth and/or recombinant protein production to improve the overall yield. Currently, LC-MS, GC-MS and NMR are the most used and advanced technologies for investigating the metabolome. Although contributed significantly in the domain, each technique has its own biasness towards specific metabolites or class of metabolites due to various reasons including variability in the concept of working, sample preparation, metabolite-extraction methods, metabolite identification tools, and databases. As a result, the application of appropriate analytical technique(s) is very critical. Purpose and scope: This review provides a state-of-the-art technological insights and overview of metabolic mechanisms involved in regulation of cell growth and/or recombinant protein production for improving yield from CHO cultures. Summary and conclusion: In this review, the advancements in CHO metabolomics over the last 10 years are traced based on a bibliometric analysis of previous publications and discussed. With the technical advancement in the domain of LC-MS, GC-MS and NMR, metabolites of glycolytic and nucleotide biosynthesis pathway (glucose, fructose, pyruvate and phenylalanine, threonine, tryptophan, arginine, valine, asparagine, and serine, etc.) were observed to be upregulated in exponential-phase thereby potentially associated with cell growth regulation, whereas metabolites/intermediates of TCA, oxidative phosphorylation (aspartate, glutamate, succinate, malate, fumarate and citrate), intracellular NAD+/NADH ratio, and glutathione metabolic pathways were observed to be upregulated in stationary-phase and hence potentially associated with increased cell-specific productivity in CHO bioprocess. Moreover, each of technique has its own bias towards metabolite identification, indicating their complementarity, along with a number of critical gaps in the CHO metabolomics pipeline and hence first time discussed here to identify their potential remedies. This knowledge may help in future study designs to improve the metabolomic coverage facilitating identification of the metabolites/pathways which might get missed otherwise and explore the full potential of metabolomics for improving the CHO bioprocess performances.

Development of a novel tyrosine-based selection system for generation of recombinant Chinese hamster ovary cells

Efficiently expanding Chinese hamster ovary (CHO) cells, which serve as the primary host cells for recombinant protein production, have gained increasing industrial significance. A significant hurdle in stable cell line development is the low efficiency of the target gene integrated into the host genome, implying the necessity for an effective screening and selection procedure to separate these stable cells. In this study, the genes of phenylalanine hydroxylase (PAH) and pterin 4 alpha carbinolamine dehydratase 1 (PCBD1), which are key enzymes in the tyrosine synthesis pathway, were utilized as selection markers and transduced into host cells together with the target genes. This research investigated the enrichment effect of this system and advanced further in understanding its benefits for cell line development and rCHO cell culture. A novel tyrosine-based selection system that only used PCBD1 as a selection marker was designed to promote the enrichment effect. Post 9 days of starvation, positive transductants in the cell pool approached 100%. Applied the novel tyrosine-based selection system, rCHO cells expressing E2 protein were generated and named CHO TS cells. It could continue to grow, and the yield of E2 achieved 95.95 mg/L in a tyrosine-free and chemically-defined (CD) medium. Herein, we introduced an alternative to antibiotic-based selections for the establishment of CHO cell lines and provided useful insights for the design and development of CD medium.

Developing an ultra-intensified fed-batch cell culture process with greatly improved performance and productivity

Intensified fed-batch (IFB), a popular cell culture intensification strategy, has been widely used for productivity improvement through high density inoculation followed by fed-batch cultivation. However, such an intensification strategy may counterproductively induce rapidly progressing cell apoptosis and difficult-to-sustain productivity. To improve culture performance, we developed a novel cell culture process intermittent-perfusion fed-batch (IPFB) which incorporates one single or multiple cycles of intermittent perfusion during an IFB process for better sustained cellular and metabolic behaviors and notably improved productivity. Unlike continuous perfusion or other semi-continuous processes such as hybrid perfusion fed-batch with only early-stage perfusion, IPFB applies limited times of intermittent perfusion in the mid-to-late stage of production and still inherits bolus feedings on nonperfusion days as in a fed-batch culture. Compared to IFB, an average titer increase of ~45% was obtained in eight recombinant CHO cell lines studied. Beyond IPFB, ultra-intensified IPFB (UI-IPFB) was designed with a markedly elevated seeding density of 20-80 × 106 cell/mL, achieved through the conventional alternating tangential flow filtration (ATF) perfusion expansion followed with a cell culture concentration step using the same ATF system. With UI-IPFB, up to ~6 folds of traditional fed-batch and ~3 folds of IFB productivity were achieved. Furthermore, the application grounded in these two novel processes showed broad-based feasibility in multiple cell lines and products of interest, and was proven to be effective in cost of goods reduction and readily scalable to a larger scale in existing facilities.

A high-fidelity, dual site-specific integration system in CHO cells by a Bxb1 recombinase

Site-specific integration (SSI) via recombinase mediated cassette exchange (RMCE) has shown advantages over random integration methods for expression of biotherapeutics. As an extension of our previous work developing SSI host cells, we developed a dual-site SSI system having two independent integration sites at different genomic loci, each containing a unique landing pad (LP). This system was leveraged to generate and compare two RMCE hosts, one (dFRT) compatible with the Flp recombinase, the other (dBxb1) compatible with the Bxb1 recombinase. Our comparison demonstrated that the dBxb1 host was able to generate stable transfectant pools in a shorter time frame, and cells within the dBxb1 transfectant pools were more phenotypically and genotypically stable. We further improved process performance of the dBxb1 host, resulting in desired fed batch performance attributes. Clones derived from this improved host (referred as 41L-11) maintained stable expression profiles over extended generations. While the data represents a significant improvement in the efficiency of our cell line development process, the dual LP architecture also affords a high degree of flexibility for development of complex protein modalities.

Amino acid degradation pathway inhibitory by-products trigger apoptosis in CHO cells

Chinese hamster ovary (CHO) cells are widely used to produce complex biopharmaceuticals. Improving their productivity is necessary to fulfill the growing demand for such products. One way to enhance productivity is by cultivating cells at high densities, but inhibitory by-products, such as metabolite derivatives from amino acid degradation, can hinder achieving high cell densities. This research examines the impact of these inhibitory by-products on high-density cultures. We cultured X1 and X2 CHO cell lines in a small-scale semi-perfusion system and introduced a mix of inhibitory by-products on day 10. The X1 and X2 cell lines were chosen for their varied responses to the by-products; X2 was susceptible, while X1 survived. Proteomics revealed that the X2 cell line presented changes in the proteins linked to apoptosis regulation, cell building block synthesis, cell growth, DNA repair, and energy metabolism. We later used the AB cell line, an apoptosis-resistant cell line, to validate the results. AB behaved similar to X1 under stress. We confirmed the activation of apoptosis in X2 using a caspase assay. This research provides insights into the mechanisms of cell death triggered by inhibitory by-products and can guide the optimization of CHO cell culture for biopharmaceutical manufacturing.

Precision fermentation with mass spectrometry-based spent media analysis

Optimization and monitoring of bioprocesses requires the measurement of several process parameters and quality attributes. Mass spectrometry (MS)-based techniques such as those coupled to gas chromatography (GCMS) and liquid Chromatography (LCMS) enable the simultaneous measurement of hundreds of metabolites with high sensitivity. When applied to spent media, such metabolome analysis can help determine the sequence of substrate uptake and metabolite secretion, consequently facilitating better design of initial media and feeding strategy. Furthermore, the analysis of metabolite diversity and abundance from spent media will aid the determination of metabolic phases of the culture and the identification of metabolites as surrogate markers for product titer and quality. This review covers the recent advances in metabolomics analysis applied to the development and monitoring of bioprocesses. In this regard, we recommend a stepwise workflow and guidelines that a bioprocesses engineer can adopt to develop and optimize a fermentation process using spent media analysis. Finally, we show examples of how the use of MS can revolutionize the design and monitoring of bioprocesses.

Addressing amino acid-derived inhibitory metabolites and enhancing CHO cell culture performance through DOE-guided media modifications

Previously, we identified six inhibitory metabolites (IMs) accumulating in Chinese hamster ovary (CHO) cultures using AMBIC 1.0 community reference medium that negatively impacted culture performance. The goal of the current study was to modify the medium to control IM accumulation through design of experiments (DOE). Initial over-supplementation of precursor amino acids (AAs) by 100% to 200% in the culture medium revealed positive correlations between initial AA concentrations and IM levels. A screening design identified 5 AA targets, Lys, Ile, Trp, Leu, Arg, as key contributors to IMs. Response surface design analysis was used to reduce initial AA levels between 13% and 33%, and these were then evaluated in batch and fed-batch cultures. Lowering AAs in basal and feed medium and reducing feed rate from 10% to 5% reduced inhibitory metabolites HICA and NAP by up to 50%, MSA by 30%, and CMP by 15%. These reductions were accompanied by a 13% to 40% improvement in peak viable cell densities and 7% to 50% enhancement in IgG production in batch and fed-batch processes, respectively. This study demonstrates the value of tuning specific AA levels in reference basal and feed media using statistical design methodologies to lower problematic IMs.

"Organized stress" for robust scale-up of intensified production process with fed-batch seed bioreactor

Process intensification has been widely used for many years in the mammalian biomanufacturing industry to increase productivity, agility and flexibility while reducing production costs. The most commonly used intensified processes are operated using a perfusion or fed-batch seed bioreactor enabling a higher than usual seeding density in the fed-batch production bioreactor. Hence, as part of the growth phase is shifted to the seed bioreactor, there is a lower split ratio, which increases the criticality of the seed bioreactor and could impact production performance. Therefore, such intensified processes should be designed and characterized for robust process scale-up. This research work is focused on intensified processes with high seeding density inoculated from seed bioreactor in fed-batch mode. The impact of the feeding strategy and specific power input (P/V) in the seed bioreactor and on the production step with two different cell lines (CL1 and CL2) producing two different monoclonal antibodies was investigated. Cell culture performance in the production bioreactor has been improved due to more stressful conditions for the cells in the seed bioreactor and the impact of the production bioreactor P/V on the production performance was limited. This is the first reported study highlighting a positive impact of cellular stress in seed bioreactors on intensified production bioreactor with the introduction of the "organized stress" concept.

Optimization of medium with perfusion microbioreactors for high density CHO cell cultures at very low renewal rate aided by design of experiments

A novel approach of design of experiment (DoE) is developed for the optimization of key substrates of the culture medium, amino acids, and sugars, by utilizing perfusion microbioreactors with 2 mL working volume, operated in high cell density continuous mode, to explore the design space. A mixture DoE based on a simplex-centroid is proposed to test multiple medium blends in parallel perfusion runs, where the amino acids concentrations are selected based on the culture behavior in presence of different amino acid mixtures, and using targeted specific consumption rates. An optimized medium is identified with models predicting the culture parameters and product quality attributes (G0 and G1 level N-glycans) as a function of the medium composition. It is then validated in runs performed in perfusion microbioreactor in comparison with stirred-tank bioreactors equipped with alternating tangential flow filtration (ATF) or with tangential flow filtration (TFF) for cell separation, showing overall a similar process performance and N-glycosylation profile of the produced antibody. These results demonstrate that the present development strategy generates a perfusion medium with optimized performance for stable Chinese hamster ovary (CHO) cell cultures operated with very high cell densities of 60 × 106 and 120 × 106  cells/mL and a low cell-specific perfusion rate of 17 pL/cell/day, which is among the lowest reported and is in line with the framework recently published by the industry.

A novel hybrid bioprocess strategy addressing key challenges of advanced biomanufacturing

Monoclonal antibodies (mAb) are commonly manufactured by either discontinuous operations like fed-batch (FB) or continuous processes such as steady-state perfusion. Both process types comprise opposing advantages and disadvantages in areas such as plant utilization, feasible cell densities, media consumption and process monitoring effort. In this study, we show feasibility of a promising novel hybrid process strategy that combines beneficial attributes of both process formats. In detail, our strategy comprises a short duration FB, followed by a fast media exchange and cell density readjustment, marking the start of the next FB cycle. Utilizing a small-scale screening tool, we were able to identify beneficial process parameters, including FB interval duration and reinoculation cell density, that allow for multiple cycles of the outlined process in a reproducible manner. In addition, we could demonstrate scalability of the process to a 5L benchtop system, using a fluidized-bed centrifuge as scalable media exchange system. The novel process showed increased productivity (+217%) as well as longer cultivation duration, in comparison to a standard FB with a significantly lower media consumption per produced product (-50%) and a decreased need for process monitoring, in comparison to a perfusion cultivation. Further, the process revealed constant glycosylation pattern in comparison to the perfusion cultivation and has strong potential for further scale-up, due to the use of fully scalable cultivation and media exchange platforms. In summary, we have developed a novel hybrid process strategy that tackles the key challenges of current biomanufacturing of either low productivity or high media consumption, representing a new and innovative approach for future process intensification efforts.

Employing active learning in the optimization of culture medium for mammalian cells

Medium optimization is a crucial step during cell culture for biopharmaceutics and regenerative medicine; however, this step remains challenging, as both media and cells are highly complex systems. Here, we addressed this issue by employing active learning. Specifically, we introduced machine learning to cell culture experiments to optimize culture medium. The cell line HeLa-S3 and the gradient-boosting decision tree algorithm were used to find optimized media as pilot studies. To acquire the training data, cell culture was performed in a large variety of medium combinations. The cellular NAD(P)H abundance, represented as A450, was used to indicate the goodness of culture media. In active learning, regular and time-saving modes were developed using culture data at 168 h and 96 h, respectively. Both modes successfully fine-tuned 29 components to generate a medium for improved cell culture. Intriguingly, the two modes provided different predictions for the concentrations of vitamins and amino acids, and a significant decrease was commonly predicted for fetal bovine serum (FBS) compared to the commercial medium. In addition, active learning-assisted medium optimization significantly increased the cellular concentration of NAD(P)H, an active chemical with a constant abundance in living cells. Our study demonstrated the efficiency and practicality of active learning for medium optimization and provided valuable information for employing machine learning technology in cell biology experiments.

CRISPR Technologies in Chinese Hamster Ovary Cell Line Engineering

The Chinese hamster ovary (CHO) cell line is a well-established platform for the production of biopharmaceuticals due to its ability to express complex therapeutic proteins with human-like glycopatterns in high amounts. The advent of CRISPR technology has opened up new avenues for the engineering of CHO cell lines for improved protein production and enhanced product quality. This review summarizes recent advances in the application of CRISPR technology for CHO cell line engineering with a particular focus on glycosylation modulation, productivity enhancement, tackling adventitious agents, elimination of problematic host cell proteins, development of antibiotic-free selection systems, site-specific transgene integration, and CRISPR-mediated gene activation and repression. The review highlights the potential of CRISPR technology in CHO cell line genome editing and epigenetic engineering for the more efficient and cost-effective development of biopharmaceuticals while ensuring the safety and quality of the final product.

Investigation and development of transient production process for porcine circovirus Type-2 (PCV2) capsid protein in HEK293F cells

Porcine circovirus type-2 capsid protein contains a major immunodominant epitope used as a subunit vaccine. Transient expression in mammalian cells is an efficient process for producing recombinant proteins. However, there is still a lack of research on the efficient production of virus capsid proteins in mammalian cells. Here we present a comprehensive study to investigate and optimize the production process of a model "difficult-to-express" virus capsid protein, PCV2 capsid protein in HEK293F transient expression system. The study evaluated the transient expression of PCV2 capsid protein in the mammalian cell line HEK293F and investigated the subcellular distribution by confocal microscopy. In addition, the RNA sequencing (RNA-seq) was used to detect the differential expression of genes after cells transfected with pEGFP-N1-Capsid or empty vectors. The analysis revealed that the PCV2 capsid gene affected a panel of differential genes of HEK293F cells involved in protein folding, stress response, and translation process, such as SHP90β, GRP78, HSP47, and eIF4A. An integrated strategy of protein engineering combined with VPA addition was applied to promote the expression of PCV2 capsid protein in HEK293F. Moreover, this study significantly increased the production of the engineered PCV2 capsid protein in HEK293F cells, reaching a yield of 8.7 mg/L. Conclusively, this study may provide deep insight for other "difficult-to-express" virus capsid proteins in the mammalian cell system.

An Investigation into the Metabolic Differences between Conventional and High Seeding Density Fed-Batch Cell Cultures by Applying a Segmented Modeling Approach

The conventional fed-batch process characterized by a low titer currently challenges pharmaceutical development. Process optimization by applying a perfusion process in the pre-stage and subsequent production phase at a high seeding density (HSD) can meet this challenge. In this study, we employed a simplified approach based on measured experiments, namely segmented modeling, to systematically analyze an HSD fed-batch process compared to a standard process. A comparison indicated that the metabolic phases of HSD processes are not only shifted in time, but metabolite trends show an altered metabolism. In an extended study, we integrated the intracellular fluxes determined by a metabolic flux analysis into the segmented modeling approach. Compared to using only extracellular rates, similar phases are identified, and this highlights the reliability of phase identification modeling using extracellular rates only. Furthermore, the segmented linear regression approach is used to create a model that describes cellular behavior and that can be used to predict potential improvements in the feeding strategy and in harvest viability. Here, overfeeding was eliminated and a significantly higher titer was achieved. This work provides insights into the overall metabolic changes in the HSD process and paves the way towards the optimization of the feeding regime.

Near-infrared spectroscopy based monitoring of all 20 amino acids in mammalian cell culture broth

The biopharmaceutical industry extensively employs Chinese hamster ovary (CHO) cell culture for monoclonal antibody production. Amino acids represent an essential source of nutrients in all CHO cell culture media, and their concentration is known to significantly impact cell viability, titre, and monoclonal antibody critical quality attributes. In this study, a robust Fourier transform near-infrared spectroscopy (FT-NIR) based quantification method has been developed for of all 20 amino acids (0-24 mM), as well as concentrations of glucose (0-6.7 mg mL^-1), lactate (0-2.7 mg mL^-1), and trastuzumab (0-2.5 mg mL^-1) in the CHO cell culture. Near infra-red absorbance spectrum in the range of 4000-11,000 cm^-1 were acquired, and spectra pre-processing through smoothening and derivatives were employed to enhance key characteristic signals. High-performance liquid chromatography with pre-column derivatization was used as the orthogonal analytical tool for quantification. Principal component analysis and partial least squares regression were employed for region selection and calibration model development, respectively. The results demonstrate that a good calibration statistic with the acceptable coefficient of determinations for both calibration (R_c² = 0.94-0.99) and prediction (R_p² = 0.83-0.98) could be achieved, along with high RPD values (>3) for all components except alanine (2.4). The external validation study also exhibited a satisfactory outcome (R_EV² = 0.89-0.99, RMSE = 0.04-1.04), validating the model's ability to predict the concentrations of the respective species. The calibration models were successfully applied for at-line monitoring of two perfusion runs on a 10 L scale. To our knowledge, this is the first application where NIR spectroscopy-based measurement of all 20 amino acids in mammalian cell culture samples has been demonstrated. The proposed tool can play a critical role as biopharma manufacturers implement continuous processing as well as for facilitating process analytical technology-based control of mammalian cell culture processes.

Metabolic Profiling of CHO Cells during the Production of Biotherapeutics

As indicated by an ever-increasing number of FDA approvals, biotherapeutics constitute powerful tools for the treatment of various diseases, with monoclonal antibodies (mAbs) accounting for more than 50% of newly approved drugs between 2014 and 2018 (Walsh, 2018). The pharmaceutical industry has made great progress in developing reliable and efficient bioproduction processes to meet the demand for recombinant mAbs. Mammalian cell lines are preferred for the production of functional, complex recombinant proteins including mAbs, with Chinese hamster ovary (CHO) cells being used in most instances. Despite significant advances in cell growth control for biologics manufacturing, cellular responses to environmental changes need to be understood in order to further improve productivity. Metabolomics offers a promising approach for developing suitable strategies to unlock the full potential of cellular production. This review summarizes key findings on catabolism and anabolism for each phase of cell growth (exponential growth, the stationary phase and decline) with a focus on the principal metabolic pathways (glycolysis, the pentose phosphate pathway and the tricarboxylic acid cycle) and the families of biomolecules that impact these circuities (nucleotides, amino acids, lipids and energy-rich metabolites).

LC-HRMS based Targeted Metabolomics for High-throughput and Quantitative Analysis of 21 Growth Inhibition Related Metabolites in CHO Cell Fed-Batch Cultures

Chinese hamster ovary (CHO) cells have been widely used in the biopharmaceutical industry for production of therapeutic proteins. CHO cells in fed-batch cultures produce various amino acid-derived intermediate metabolites. These small molecule metabolic byproducts have proven to be critical to cell growth, culture performance, and more interestingly antibody drug productivity. Herein, we developed a liquid chromatography - high resolution mass spectrometry (LC-HRMS) based targeted metabolomics approach for comprehensive quantification of total 21 growth inhibition related metabolites generated from 14 different amino acids in CHO cell fed-batch cultures. High throughput derivatization procedures, matrix-matched calibration curves, stable isotope-labeled internal standards, and accurate mass Full MS scan were utilized in order to achieve our goal for wide scope of metabolite screening as well as validity and reliability of metabolite quantification. We further present a novel analytical strategy for extending the assay's dynamic range by utilizing naturally occurring isotope M+1 ion as a quantification analogue in the circumstances where the principal M ion is beyond its calibration range. The integrated method was qualified for selectivity, sensitivity, linearity, accuracy, precision, isotope analysis and other analytical aspects to demonstrate assay robustness. We then applied this metabolomics approach to characterize metabolites of interest in a CHO cell based monoclonal antibody (mAb) production process with fed-batch bioreactor culture mode. Absolute quantification combined with multivariate statistical analysis illustrated that our target analytes derived from amino acids, especially from branched-chain amino acids, closely correlated with cell viability and significantly differentiated cellular stages in production process.

Modern Sensor Tools and Techniques for Monitoring, Controlling, and Improving Cell Culture Processes

The growing biopharmaceutical industry has reached a level of maturity that allows for the monitoring of numerous key variables for both process characterization and outcome predictions. Sensors were historically used in order to maintain an optimal environment within the reactor to optimize process performance. However, technological innovation has pushed towards on-line in situ continuous monitoring of quality attributes that could previously only be estimated off-line. These new sensing technologies when coupled with software models have shown promise for unique fingerprinting, smart process control, outcome improvement, and prediction. All this can be done without requiring invasive sampling or intervention on the system. In this paper, the state-of-the-art sensing technologies and their applications in the context of cell culture monitoring are reviewed with emphasis on the coming push towards industry 4.0 and smart manufacturing within the biopharmaceutical sector. Additionally, perspectives as to how this can be leveraged to improve both understanding and outcomes of cell culture processes are discussed.

Bax and Bak knockout apoptosis-resistant CHO cell lines significantly improve culture viability and titer in intensified fed-batch culture process

In the field of therapeutic protein production, process intensification strategies entailing higher starting cell seeding densities, can potentially increase culture productivity, lower cost of goods and improve facility utilization. However, increased cell densities often trigger apoptotic cell death at the end of the cell culture process and thus reduce total viable cell count. Apoptosis-resistant Chinese hamster ovary (CHO) cell lines may offer the possibility to diminish this undesired outcome of the intensified production process. In this study, we have generated and tested Bax/Bak double-knock-out (DKO) apoptosis resistant hosts to produce standard and bispecific antibodies, as well as complex molecules in intensified production processes both as pools and single cell clones, and at different scales. In all cases, therapeutic proteins expressed from clones or pools generated from the Bax/Bak DKO hosts showed not only better viability but also enabled extended productivity in the later stages of the 14-day intensified production process. The product qualities of the produced molecules were comparable between Bax/Bak DKO and wild type (WT) cells. Overall, we showed that Bax/Bak DKO apoptosis-resistant host cell lines significantly improve viability and volumetric productivity of the intensified production cultures without altering product qualities. This article is protected by copyright. All rights reserved.

Mathematical model of the multi-amino acid multi-transporter system predicts uptake flux in CHO cells

Supply and uptake of amino acids is of great importance to mammalian cell culture processes. Mammalian cells such as Chinese hamster ovary (CHO) cells express several amino acid (AA) transporters including uniporters and exchangers. Each transporter transports multiple AAs, making prediction of the effect of changed medium composition or transporter levels on individual AA transport rate challenging. A general kinetic model for such combinatorial amino acid transport, and a simplified analytical expression for the uptake rate as a function of amino acid concentrations and transporter levels is presented. From this general model, a CHO cell-specific AA transport model, to our knowledge the first such network model for any cell type, is constructed. The model is validated by its prediction of reported uptake flux and dependencies from experiments that were not used in model construction or parameter estimation. The model defines theoretical conditions for synergistic/repressive effect on the uptake rates of other AAs upon external addition of one AA. The ability of the CHO-specific model to predict amino acid interdependencies experimentally observed in other mammalian cell types suggests its robustness. This model will help formulate testable hypotheses of the effect of process changes on AA initial uptake, and serve as the AA transport component of kinetic models for cellular metabolism.

A Metabolomics Approach to Increasing Chinese Hamster Ovary (CHO) Cell Productivity

Much progress has been made in improving the viable cell density of bioreactor cultures in monoclonal antibody production from Chinese hamster ovary (CHO) cells; however, specific productivity (qP) has not been increased to the same degree. In this work, we analyzed a library of 24 antibody-expressing CHO cell clones to identify metabolites that positively associate with qP and could be used for clone selection or medium supplementation. An initial library of 12 clones, each producing one of two antibodies, was analyzed using untargeted LC-MS experiments. Metabolic model-based annotation followed by correlation analysis detected 73 metabolites that significantly correlated with growth, qP, or both. Of these, metabolites in the alanine, aspartate, and glutamate metabolism pathway, and the TCA cycle showed the strongest association with qP. To evaluate whether these metabolites could be used as indicators to identify clones with potential for high productivity, we performed targeted LC-MS experiments on a second library of 12 clones expressing a third antibody. These experiments found that aspartate and cystine were positively correlated with qP, confirming the results from untargeted analysis. To investigate whether qP correlated metabolites reflected endogenous metabolic activity beneficial for productivity, several of these metabolites were tested as medium additives during cell culture. Medium supplementation with citrate improved qP by up to 490% and more than doubled the titer. Together, these studies demonstrate the potential for using metabolomics to discover novel metabolite additives that yield higher volumetric productivity in biologics production processes.

A genome-scale nutrient minimization forecast algorithm for controlling essential amino acid levels in CHO cell cultures

Mammalian cell culture processes rely heavily on empirical knowledge in which process control remains a challenge due to the limited characterization/understanding of cell metabolism and inability to predict the cell behaviors. This study facilitates control of Chinese hamster ovary (CHO) processes through a forecast-based feeding approach that predicts multiple essential amino acids levels in the culture from easily acquired viable cell density data. Multiple cell growth behavior forecast extrapolation approaches are considered with logistic curve fitting found to be the most effective. Next, the nutrient-minimized CHO genome-scale model is combined with the growth forecast model to generate essential amino acid forecast profiles of multiple CHO batch cultures. Comparison of the forecast with the measurements suggests that this algorithm can accurately predict the concentration of most essential amino acids from cell density measurement with error mitigated by incorporating off-line amino acids concentration measurements. Finally, the forecast algorithm is applied to CHO fed-batch cultures to support amino acid feeding control to control the concentration of essential amino acids below 1-2 mM for lysine, leucine, and valine as a model over a 9-day fed batch culture while maintaining comparable growth behavior to an empirical-based culture. In turn, glycine production was elevated, alanine reduced and lactate production slightly lower in control cultures due to metabolic shifts in branched-chain amino acid degradation. With the advantage of requiring minimal measurement inputs while providing valuable and in-advance information of the system based on growth measurements, this genome model-based amino acid forecast algorithm represent a powerful and cost-effective tool to facilitate enhanced control over CHO and other mammalian cell-based bioprocesses.

Metabolic trends of Chinese hamster ovary cells in biopharmaceutical production under batch and fed-batch conditions

Extensive knowledge of Chinese hamster ovary (CHO) cell metabolism is required to improve process productivity and culture performance in biopharmaceutical manufacturing. However, CHO cells show a dynamic metabolism during culturing in batch and fed-batch bioreactors. CHO cell metabolism is generally described as taking place in three stages: exponential growth phase, stationary phase, and death phase. This review aims to summarize the trends of central metabolism for CHO cells during each stage. Additional insights into how culture conditions are related to phase transitions and force metabolic rewiring are provided. Understanding of CHO cell metabolism lends itself to improving culture qualities by, for example, identifying sources of toxic byproducts and pathways for cellular engineering. In summary, this review describes the changes in CHO cell central metabolism over the course of the culture.

Production of butyrate and branched-chain amino acid catabolic byproducts by CHO cells in fed-batch culture enhances their specific productivity

Chinese hamster ovary (CHO) cells in fed-batch cultures produce several metabolic byproducts derived from amino acid catabolism, some of which accumulate to growth inhibitory levels. Controlling the accumulation of these byproducts has been shown to significantly enhance cell proliferation. Interestingly, some of these byproducts have physiological roles that go beyond inhibition of cell proliferation. In this study, we show that, in CHO cell fed-batch cultures, branched-chain amino acid (BCAA) catabolism contributes to the formation of butyrate, a novel byproduct that is also a well-established specific productivity enhancer. We further show that other byproducts of BCAA catabolism, namely isovalerate and isobutyrate, which accumulate in CHO cell fed-batch cultures, also enhance specific productivity. Lastly, we show that the rate of production of these BCAA catabolic byproducts is negatively correlated with glucose uptake and lactate production rates. Thus, limiting glucose supply to suppress glucose uptake and lactate production, as in the case of fed-batch cultures employing high-end pH-controlled delivery of glucose (HiPDOG) technology, significantly enhances BCAA catabolic byproduct accumulation, resulting in higher specific productivities.

Identification of novel inhibitory metabolites and impact verification on growth and protein synthesis in mammalian cells

Mammalian cells consume large amount of nutrients during growth and production. However, endogenous metabolic inefficiencies often prevent cells to fully utilize nutrients to support growth and protein production. Instead, significant fraction of fed nutrients is diverted into extracellular accumulation of waste by-products and metabolites, further inhibiting proliferation and protein synthesis. In this study, an LC-MS/MS based metabolomics pipeline was used to screen Chinese hamster ovary (CHO) extracellular metabolites. Six out of eight identified inhibitory metabolites, caused by the inefficient cell metabolism, were not previously studied in CHO cells: aconitic acid, 2-hydroxyisocaproic acid, methylsuccinic acid, cytidine monophosphate, trigonelline, and n-acetyl putrescine. When supplemented back into a fed-batch culture, significant reduction in cellular growth was observed in the presence of each metabolite and all the identified metabolites were shown to impact the glycosylation of a model secreted antibody, with seven of these also reducing CHO cellular productivity (titer) and all eight inhibiting the formation of mono-galactosylated biantennary (G1F) and biantennary galactosylated (G2F) N-glycans. These inhibitory metabolites further impact the metabolism of cells, leading to a significant reduction in CHO cellular growth and specific productivity in fed-batch culture (maximum reductions of 27.2% and 40.6% respectively). In-depth pathway analysis revealed that these metabolites are produced when cells utilize major energy sources such as glucose and select amino acids (tryptophan, arginine, isoleucine, and leucine) for growth, maintenance, and protein production. Furthermore, these novel inhibitory metabolites were observed to accumulate in multiple CHO cell lines (CHO–K1 and CHO-GS) as well as HEK293 cell line. This study provides a robust and holistic methodology to incorporate global metabolomic analysis into cell culture studies for elucidation and structural verification of novel metabolites that participate in key metabolic pathways to growth, production, and post-translational modification in biopharmaceutical production.

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Mammalian metabolic inefficiencies lead to accumulation of waste by-products.

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Untargeted and targeted metabolomics for identification of novel metabolites.

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Identified six CHO metabolic inhibitors negatively impact growth and titer production.

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Inhibitors were shown to accumulate across different mammalian cell lines.

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A holistic methodology incorporating metabolomics analysis into cell culture studies.

Untargeted proteomics reveals upregulation of stress response pathways during CHO-based monoclonal antibody manufacturing process leading to disulfide bond reduction

Monoclonal antibody (mAb) interchain disulfide bond reduction can cause a loss of function and negatively impact the therapeutic’s efficacy and safety. Disulfide bond reduction has been observed at various stages during the manufacturing process, including processing of the harvested material. The factors and mechanisms driving this phenomenon are not fully understood. In this study, we examined the host cell proteome as a potential factor affecting the susceptibility of a mAb to disulfide bond reduction in the harvested cell culture fluid (HCCF). We used untargeted liquid-chromatography-mass spectrometry-based proteomics experiments in conjunction with a semi-automated protein identification workflow to systematically compare Chinese hamster ovary (CHO) cell protein abundances between bioreactor conditions that result in reduction-susceptible and reduction-free HCCF. Although the growth profiles and antibody titers of these two bioreactor conditions were indistinguishable, we observed broad differences in host cell protein (HCP) expression. We found significant differences in the abundance of glycolytic enzymes, key protein reductases, and antioxidant defense enzymes. Multivariate analysis of the proteomics data determined that upregulation of stress-inducible endoplasmic reticulum (ER) and other chaperone proteins is a discriminatory characteristic of reduction-susceptible HCP profiles. Overall, these results suggest that stress response pathways activated during bioreactor culture increase the reduction-susceptibility of HCCF. Consequently, these pathways could be valuable targets for optimizing culture conditions to improve protein quality.

Knowing more from less: miniaturization of ligand-binding assays and electrophoresis as new paradigms for at-line monitoring and control of mammalian cell bioprocesses

Monitoring technologies for Process Analytical Technology (PAT) in mammalian cell cultures are often focusing on the same hand full parameters although a deeper knowledge and control of a larger panel of culture components would highly benefit process optimization, control and robustness. This short review highlights key advances in microfluidic affinity assays and microchip capillary electrophoresis (MCE). Aiming at the miniaturization and integration of PAT, these can detect at-line a variety of metabolites, proteins and Critical Quality Attributes (CQA's) in a bioprocess. Furthermore, discrete analytical components, which can potentially support the translation of increasingly mature microfluidic technologies towards this novel application, are also presented as a comprehensive toolbox ranging from sample preparation to signal acquisition.

From omics to Cellular mechanisms in mammalian cell factory development

Mammalian cells have been used widely as biopharmaceutical cell factories due to their ability to make complex biotherapeutic proteins with human-compatible modifications. However, their application for some products has been hampered by low protein yields. Numerous studies have aimed to characterize cellular bottlenecks in the hope of boosting protein productivity, but the complexity of the underlying pathways and the diversity of the modifications have complicated cell engineering when relying solely on traditional methodologies. Incorporating omics-based and systems approaches into cell engineering can provide valuable insights into desirable phenotypes of cell factories. Here, we discuss cell engineering strategies for enhancing protein productivity in mammalian cell factories, particularly CHO and HEK293, and the opportunities and limitations of the genome-wide screening and multi-omics approaches for guiding cell engineering. Systems biology strategies will also be discussed to show how they refine our understanding of the cellular mechanisms which will aid in effective engineering strategies.

Predictive macroscopic modeling of cell growth, metabolism and monoclonal antibody production: Case study of a CHO fed-batch production

We describe a systematic approach to establish predictive models of CHO cell growth, cell metabolism and monoclonal antibody (mAb) formation during biopharmaceutical production. The prediction is based on a combination of an empirical metabolic model connecting extracellular metabolic fluxes with cellular growth and product formation with mixed Monod-inhibition type kinetics that we generalized to every possible external metabolite. We describe the maximum specific growth rate as a function of the integral viable cell density (IVCD). Moreover, we also take into account the accumulation of metabolites in intracellular pools that can influence cell growth. This is possible even without identification and quantification of these metabolites as illustrated with fed-batch cultures of Chinese Hamster Ovary (CHO) cells producing a mAb. The impact of cysteine and tryptophan on cell growth and cell productivity was assessed, and the resulting macroscopic model was successfully used to predict the impact of new, untested feeding strategies on cell growth and mAb production. This model combining piecewise linear relationships between metabolic rates, growth rate and production rate together with Monod-inhibition type models for cell growth did well in predicting cell culture performance in fed-batch cultures even outside the range of experimental data used for establishing the model. It could therefore also successfully be applied for in silico prediction of optimal operating conditions.

Systematic evaluation of parameters for genome-scale metabolic models of cultured mammalian cells

Genome-scale metabolic models describe cellular metabolism with mechanistic detail. Given their high complexity, such models need to be parameterized correctly to yield accurate predictions and avoid overfitting. Effective parameterization has been well-studied for microbial models, but it remains unclear for higher eukaryotes, including mammalian cells. To address this, we enumerated model parameters that describe key features of cultured mammalian cells - including cellular composition, bioprocess performance metrics, mammalian-specific pathways, and biological assumptions behind model formulation approaches. We tested these parameters by building thousands of metabolic models and evaluating their ability to predict the growth rates of a panel of phenotypically diverse Chinese Hamster Ovary cell clones. We found the following considerations to be most critical for accurate parameterization: (1) cells limit metabolic activity to maintain homeostasis, (2) cell morphology and viability change dynamically during a growth curve, and (3) cellular biomass has a particular macromolecular composition. Depending on parameterization, models predicted different metabolic phenotypes, including contrasting mechanisms of nutrient utilization and energy generation, leading to varying accuracies of growth rate predictions. Notably, accurate parameter values broadly agreed with experimental measurements. These insights will guide future investigations of mammalian metabolism.

Application of metabolic modeling for targeted optimization of high seeding density processes

Process intensification by application of perfusion mode in pre‐stage bioreactors and subsequent inoculation of cell cultures at high seeding densities (HSD) has the potential to meet the increasing requirements of future manufacturing demands. However, process development is currently restrained by a limited understanding of the cell's requirements under these process conditions. The goal of this study was to use extended metabolite analysis and metabolic modeling for targeted optimization of HSD cultivations. The metabolite analysis of HSD N‐stage cultures revealed accumulation of inhibiting metabolites early in the process and flux balance analysis led to the assumption that reactive oxygen species (ROS) were contributing to the fast decrease in cell viability. Based on the metabolic analysis an optimized feeding strategy with lactate and cysteine supplementation was applied, resulting in an increase in antibody titer of up to 47%. Flux balance analysis was further used to elucidate the surprisingly strong synergistic effect of lactate and cysteine, indicating that increased lactate uptake led to reduced ROS formation under these conditions whilst additional cysteine actively reduced ROS via the glutathione pathway. The presented results finally demonstrate the benefit of modeling approaches for process intensification as well as the potential of HSD cultivations for biopharmaceutical manufacturing.

A genome-scale metabolic network model and machine learning predict amino acid concentrations in Chinese Hamster Ovary cell cultures

The control of nutrient availability is critical to large-scale manufacturing of biotherapeutics. However, the quantification of proteinogenic amino acids is time-consuming and thus is difficult to implement for real-time in situ bioprocess control. Genome-scale metabolic models describe the metabolic conversion from media nutrients to proliferation and recombinant protein production, and therefore are a promising platform for in silico monitoring and prediction of amino acid concentrations. This potential has not been realized due to unresolved challenges: (1) the models assume an optimal and highly efficient metabolism, and therefore tend to underestimate amino acid consumption, and (2) the models assume a steady state, and therefore have a short forecast range. We address these challenges by integrating machine learning with the metabolic models. Through this we demonstrate accurate and time-course dependent prediction of individual amino acid concentration in culture medium throughout the production process. Thus, these models can be deployed to control nutrient feeding to avoid premature nutrient depletion or provide early predictions of failed bioreactor runs.

Hydrocyclones as cell retention devices for an N-1 perfusion bioreactor linked to a continuous-flow stirred tank production bioreactor

A continuous Chinese hamster ovary (CHO) cell culture process comprised of a highly proliferative N-1 perfusion bioreactor utilizing a hydrocyclone as a cell retention device linked to a production continuous-flow stirred tank reactor (CSTR) is presented. The overflow stream from the hydrocyclone, which is only partially depleted of cells, provides a continuous source of high viability cells from the N-1 perfusion bioreactor to the 5-20 times larger CSTR. Under steady-state conditions, this linked-bioreactor system achieved a peak volumetric productivity of 0.96 g/L/day, twofold higher than the optimized fed-batch process. The linked bioreactor system using a hydrocyclone was also shown to be 1.8-3.1 times more productive than a dual, cascading CSTR system without cell retention.

Caspase-7 deficiency in Chinese hamster ovary cells reduces cell proliferation and viability

BACKGROUND

Chinese hamster ovary (CHO) cells are the most commonly used mammalian host cell in the commercial-scale production of biopharmaceutical proteins. Modification of genes involved in apoptosis may improve the productivity of CHO cells. Executive caspases, including caspases 3 and 7, play critical roles in apoptosis. The effects of the ablation of the caspase 7 gene on proliferation and viability of CHO cells remains unknown. In this study, we applied clustered regularly interspaced short palindromic repeat (CRISPR/Cas9) to target caspase 7 gene of CHO K1 cell via all in one and homology targeted integration strategies. Consequently, the effect of caspase 7 deficiency on cell proliferation, viability, and apoptosis was studied by MTT assay and flow cytometry.

RESULTS

Findings of gel electrophoresis, western blotting, and sequencing confirmed the caspase 7 gene silencing in CHO cells (CHO-KO). Proliferation assay revealed that caspase 7 deficiency in CHO cells resulted in the reduction of proliferation in various CHO-KO clones. Besides, the disruption of caspase 7 had negative effects on cell viability in exposure with NaBu which confirmed by MTT assay. Results of flow cytometry using Anexin V/PI demonstrated that Nabu treatment (11 mM) declined the percentage of live CHO-K1 and CHO-KO cells to 70.3% and 5.79%. These results verified that the CHO-K1 cells were more resistant to apoptosis than CHO-KO, however most of CHO-KO cells undergone early apoptosis (91.9%) which seems to be a fascinating finding.

CONCLUSION

These results reveal that caspase 7 may be involved in the cell cycle progression of CHO cells. Furthermore, it seems that targeting caspase 7 is not the ideal route as it had previously been imagined within the prevention of apoptosis but the relation between caspase 7 deficiency, cell cycle arrest, and the occurrence of early apoptosis will require more investigation.

Regulation of Metabolic Homeostasis in Cell Culture Bioprocesses

Mammalian cells are the main tool for the production of therapeutic proteins, viruses for gene therapy, and cells for cell therapy. In production processes cell metabolism is the main driver that causes changes in the growth environment and affects productivity and product quality. Of all nutrients, glucose has the most prominent impact on bioprocesses. We summarize recent findings on the regulation of glucose and energy metabolism in cultured cells. Local allosteric regulations and post-translational modifications of enzymes in metabolic networks interplay with global signaling and transcriptional regulation. These regulatory networks sustain homeostasis across the cytosolic and mitochondrial compartments. Understanding the regulation of glucose metabolism and metabolic state is crucial for enhancing process productivity and product quality.

Feedback control of two supplemental feeds during fed-batch culture on a platform process using inline Raman models for glucose and phenylalanine concentration

The use of Raman models for glucose and phenylalanine concentrations to provide the signal for a control algorithm to continuously adjust the feed rate of two separate supplemental feeds during the fed-batch culture of a CHOK1SV GS-KO® cell line in a platform process was evaluated. Automated feed rate adjustment of the glucose feed using a Raman model for glucose concentration, maintained the glucose concentration within the desired target (average deviation ± 0.49 g/L). Automated feed rate adjustment of the nutrient feed using a Raman model for phenylalanine concentration, maintained phenylalanine concentrations within the target (average deviation ± 29.97 mg/L). The novel use of a Raman model for phenylalanine concentration, combined with a Raman model for glucose concentration, to maintain target glucose and phenylalanine concentrations through feed-rate adjustments, reduced the average cumulative glucose and nutrient feed additions (19% and 27% respectively) compared to manually adjusted cultures. Additionally, the proposed automation strategy led to lower osmolality during culture, maintained the nutrient environment more consistently, and achieved higher harvest product concentration (≈ 20% higher) compared to typical fed-batch process control for the cell line and platform process evaluated. Furthermore, the proposed feeding strategy yielded similar glycosylation and charge variant profiles compared to manually adjusted fed-batch process control. The ability to continuously adjust the feed rate addition of two separate feeds in this manner helps enable a shift away from the current daily offline sampling needed to control fed-batch mammalian cell culture during clinical and commercial manufacturing on platform processes.

Low-concentration staurosporine improves recombinant antibody productivity in Chinese hamster ovary cells without inducing cell death

Chinese hamster ovary (CHO) cells are used as host cells for biopharmaceutical production, including monoclonal antibodies (mAbs). Arresting the cell cycle with chemical compounds is an effective approach to improve biopharmaceutical productivity. In a previous study, potential new cell cycle-arresting compounds were screened from marine-derived microorganism culture extracts, and it was suggested that staurosporine might improve mAb productivity in CHO cells via cell cycle arrest. The purpose of this study was to demonstrate the effectiveness of staurosporine as a cell-cycle arresting compound to improve mAb productivity. The optimal staurosporine concentration range was initially investigated using batch cultures. Thereafter, the effects on the culture profile and mAb productivity were evaluated using fed-batch cultures. Staurosporine at concentrations ≥10 nM induced cell death, but at concentrations ≤5 nM did not. In the range of 2-4 nM, cell growth was inhibited, whereas the specific production rate (Qp) and cell longevity were improved in a dose-dependent manner. The Qp and maximum mAb concentration with 4 nM staurosporine improved by 36.3 and 5.2%, respectively, compared to those with control conditions. Cell viability post-culture without staurosporine was 40.0 ± 0.3%, whereas with 4 nM staurosporine, it was 90.1 ± 1.0%. Flow cytometric analysis indicated cell-cycle arrest at the G1/G0 phase with 4 nM staurosporine addition. The present study highlighted the efficacy of staurosporine in improving mAb production by causing cell-cycle arrest. Further research into staurosporine analogs and how to use them will lead to development of more effective industrial production technologies of biopharmaceuticals.

Investigation into the impact of tyrosine on the product formation and quality attributes of mAbs in rCHO cell cultures

Tyrosine (Tyr) is crucial to the maintenance of the monoclonal antibody (mAb) titers and quality attributes in fed-batch cultures of recombinant Chinese hamster ovary (rCHO) cells. However, the relation between tyrosine and these aspects is not yet fully defined. In order to further elucidate such a relation, two groups of fed-batch experiments with high tyrosine (H-T) or low tyrosine (L-T) additions producing an IgG1 monoclonal antibody against CD20 were implemented to investigate the intracellular and extracellular effects of tyrosine on the culture performance. It was found that the scarcity of tyrosine led to the distinctive reduction in both viable cell density and antibody specific production rate, hence the sharply reduced titer, possibly related to the impaired translation efficiency caused by the substrate limitation of tyrosine. In addition, alterations to the critical quality attributes were detected in the L-T group, compared to those in the H-T condition. Notable decrease in the contents of intact antibody was found under the L-T condition because of the elevated reductive level in the supernatant. Moreover, the aggregate content in the L-T condition was also reduced, probably resulting from the accumulation of extracellular cystine. In particular, the lysine variant content noticeably increased with tyrosine limitation owing to the downregulation of two carboxypeptidases, i.e., CpB and CpH. Overall, understanding the role of tyrosine in these aspects is fundamental to the increase of product titers and control of critical quality attributes in the monoclonal antibody production of rCHO cell fed-batch cultures. KEY POINTS: • Tyrosine is essential in the maintenance of product titers and the control of product qualities in high cell density cultivations in rCHO cell. • This study revealed the bottleneck of decreased q_mAbupon the deficiency of tyrosine. • The impact of tyrosine on the critical product qualities and the underlying mechanisms were also thoroughly assessed.

Bigdata analytics identifies metabolic inhibitors and promoters for productivity improvement and optimization of monoclonal antibody (mAb) production process

Recent advances in metabolite quantification and identification have enabled new research into the detection and control of titer inhibitors and promoters. This paper presents a bigdata analytics study to identify both inhibitors and promoters using multivariate data analysis of metabolomics data. By applying multi-way partial least squares (PLS) model to metabolite data from four fed-batch bioreactor conditions where feed formulation and selection agent concentrations varied, metabolites which exhibited the most significant impact on titer during cultivation were ranked from highest to lowest. The model outputs were then constrained to reduce the number of statistically relevant inhibitors or promoters to the top ten, which were used to conduct metabolic pathway analysis. Furthermore, a method is presented for identifying amino acids that prevent the accumulation of the inhibitors and/or enhance the formation of promoters during production. Finally, the metabolomics and pathway analysis results were integrated and validated with transcriptomics data to characterize metabolic changes occurring among different growth conditions. From these results, new feeding strategies were implemented which resulted in increased fed-batch production titer. Methodology from this work could be applied to future process optimization strategies for biotherapeutic production.

Key Challenges in Designing CHO Chassis Platforms

Following the success of and the high demand for recombinant protein-based therapeutics during the last 25 years, the pharmaceutical industry has invested significantly in the development of novel treatments based on biologics. Mammalian cells are the major production systems for these complex biopharmaceuticals, with Chinese hamster ovary (CHO) cell lines as the most important players. Over the years, various engineering strategies and modeling approaches have been used to improve microbial production platforms, such as bacteria and yeasts, as well as to create pre-optimized chassis host strains. However, the complexity of mammalian cells curtailed the optimization of these host cells by metabolic engineering. Most of the improvements of titer and productivity were achieved by media optimization and large-scale screening of producer clones. The advances made in recent years now open the door to again consider the potential application of systems biology approaches and metabolic engineering also to CHO. The availability of a reference genome sequence, genome-scale metabolic models and the growing number of various “omics” datasets can help overcome the complexity of CHO cells and support design strategies to boost their production performance. Modular design approaches applied to engineer industrially relevant cell lines have evolved to reduce the time and effort needed for the generation of new producer cells and to allow the achievement of desired product titers and quality. Nevertheless, important steps to enable the design of a chassis platform similar to those in use in the microbial world are still missing. In this review, we highlight the importance of mammalian cellular platforms for the production of biopharmaceuticals and compare them to microbial platforms, with an emphasis on describing novel approaches and discussing still open questions that need to be resolved to reach the objective of designing enhanced modular chassis CHO cell lines.

Using Metabolomics to Identify Cell Line-Independent Indicators of Growth Inhibition for Chinese Hamster Ovary Cell-based Bioprocesses

Chinese hamster ovary (CHO) cells are widely used for the production of biopharmaceuticals. Efforts to improve productivity through medium design and feeding strategy optimization have focused on preventing the depletion of essential nutrients and managing the accumulation of lactate and ammonia. In addition to ammonia and lactate, many other metabolites accumulate in CHO cell cultures, although their effects remain largely unknown. Elucidating these effects has the potential to further improve the productivity of CHO cell-based bioprocesses. This study used untargeted metabolomics to identify metabolites that accumulate in fed-batch cultures of monoclonal antibody (mAb) producing CHO cells. The metabolomics experiments profiled six cell lines that are derived from two different hosts, produce different mAbs, and exhibit different growth profiles. Comparing the cell lines’ metabolite profiles at different growth stages, we found a strong negative correlation between peak viable cell density (VCD) and a tryptophan metabolite, putatively identified as 5-hydroxyindoleacetaldehyde (5-HIAAld). Amino acid supplementation experiments showed strong growth inhibition of all cell lines by excess tryptophan, which correlated with the accumulation of 5-HIAAld in the culture medium. Prospectively, the approach presented in this study could be used to identify cell line- and host-independent metabolite markers for clone selection and bioprocess development.

Biological Filtering and Substrate Promiscuity Prediction for Annotating Untargeted Metabolomics

Mass spectrometry coupled with chromatography separation techniques provides a powerful platform for untargeted metabolomics. Determining the chemical identities of detected compounds however remains a major challenge. Here, we present a novel computational workflow, termed extended metabolic model filtering (EMMF), that aims to engineer a candidate set, a listing of putative chemical identities to be used during annotation, through an extended metabolic model (EMM). An EMM includes not only canonical substrates and products of enzymes already cataloged in a database through a reference metabolic model, but also metabolites that can form due to substrate promiscuity. EMMF aims to strike a balance between discovering previously uncharacterized metabolites and the computational burden of annotation. EMMF was applied to untargeted LC-MS data collected from cultures of Chinese hamster ovary (CHO) cells and murine cecal microbiota. EMM metabolites matched, on average, to 23.92% of measured masses, providing a > 7-fold increase in the candidate set size when compared to a reference metabolic model. Many metabolites suggested by EMMF are not catalogued in PubChem. For the CHO cell, we experimentally confirmed the presence of 4-hydroxyphenyllactate, a metabolite predicted by EMMF that has not been previously documented as part of the CHO cell metabolic model.