SWATH-MS insights on sodium butyrate effect on mAbs production and redox homeostasis in CHO cells

Sodium butyrate (NaBu), well-known as a histone deacetylase inhibitor and for its capacity to impede cell growth, can enhance the production of a specific protein, such as an antibody, in recombinant Chinese hamster ovary (CHO) cell cultures. In this study, two CHO cell lines, namely K1 and DG44, along with their corresponding mAb-producing lines, K1-Pr and DG44-Pr, were cultivated with or without NaBu. A SWATH-based profiling method was employed to analyze the proteome. Cells cultured in the presence of NaBu exhibited a reduction in mitosis and gene expression, supported by their culture data demonstrating growth inhibition. The presence of NaBu corresponded to upregulation of intracellular trafficking and secretion pathways, aligned with an observed increase in mAb production, and was associated with an elevated glycosylation pathway and a slight alteration in the glycosylation profile of the mAbs. Increased fatty acid oxidation, redox interactions, and lipid biosynthesis were also observed and are likely attributable to the metabolism of NaBu. A comprehensive understanding of the systemic effects of NaBu will facilitate the discovery of strategies to enhance or prolong the productivity of CHO cells.

Characterization of the Ubiquitin-Modified Proteome of Recombinant Chinese Hamster Ovary Cells in Response to Endoplasmic Reticulum Stress

Chinese hamster ovary (CHO) cells remain the most widely used host cell line for biotherapeutics production. Despite their widespread use, understanding endoplasmic reticulum (ER) stress conditions in recombinant protein production remains limited, often creating bottlenecks preventing improved production titers and product quality. Ubiquitination not only targets substrates (e.g., misfolded proteins) for proteasome degradation but also has important regulatory control functions including cell cycle regulation, translation, apoptosis, autophagy, etc. and hence is likely to be central to understanding and controlling the productivity of recombinant biotherapeutics. This study aimed to uncover differentially expressed ubiquitinated proteins following artificial induction of ER-stress in recombinant CHO cells. CHO cells were treated with the stress inducer tunicamycin and the proteasome inhibitor MG132, followed by LC-MS/MS proteomic analysis. We identified >4000 ubiquitinated peptides from CHO-DP12 cells under ER stress conditions and proteasome inhibition. Moreover, data analysis showed altered abundance levels of >900 ubiquitinated proteins under the combination of ER stress and proteasome inhibition compared to untreated controls. Gene Ontology (GO) analysis of these ubiquitinated proteins resulted in a significant enrichment of key pathways involving the proteasome, protein processing in the ER, N-glycan biosynthesis, and ubiquitin-mediated proteolysis. ER stress response proteins such as GRP78, HSP90B1, ATF6, HERPUD1, and PDIA4 were found to be highly ubiquitinated and exhibited a significant increase in abundance following induction of ER-stress conditions. This study broadens our comprehension of the roles played by protein ubiquitination in CHO cell stress responses, potentially revealing targets for tailored cell line engineering aimed at enhancing stress tolerance and production efficiency.

Molecular biomarkers identification and applications in CHO bioprocessing

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

Multi-cell-line learning for the data-driven construction of mechanistic metabolic models

Mammalian cells are commonly used as hosts in cell culture for biologics production in the pharmaceutical industry. Structured mechanistic models of metabolism have been used to capture complex cellular mechanisms that contribute to varying metabolic shifts in different cell lines. However, little research has focused on the impact of temporal changes in enzyme abundance and activity on the modeling of cell metabolism. In this work, we present a framework for constructing mechanistic models of metabolism that integrate growth-signaling control of enzyme activity and transcript dynamics. The proposed approach is applied to build models for three Chinese hamster ovary (CHO) cell lines using fed-batch culture data and time-series transcript profiles. Leveraging information from the transcriptome data, we develop a parameter estimation approach based on multi-cell-line (MCL) learning, which combines data sets from different cell lines and trains the individual cell-line models jointly to improve model accuracy. The computational results demonstrate the important role of growth signaling and transcript variability in metabolic models as well as the virtue of the MCL approach for constructing cell-line models with a limited amount of data. The resulting models exhibit a high level of accuracy in predicting distinct metabolic behaviors in the different cell lines; these models can potentially be used to accelerate the process and cell-line development for the biomanufacturing of new protein therapeutics.

Driving towards digital biomanufacturing by CHO genome-scale models

Genome-scale metabolic models (GEMs) of Chinese hamster ovary (CHO) cells are valuable for gaining mechanistic understanding of mammalian cell metabolism and cultures. We provide a comprehensive overview of past and present developments of CHO-GEMs and in silico methods within the flux balance analysis (FBA) framework, focusing on their practical utility in rational cell line development and bioprocess improvements. There are many opportunities for further augmenting the model coverage and establishing integrative models that account for different cellular processes and data for future applications. With supportive collaborative efforts by the research community, we envisage that CHO-GEMs will be crucial for the increasingly digitized and dynamically controlled bioprocessing pipelines, especially because they can be successfully deployed in conjunction with artificial intelligence (AI) and systems engineering algorithms.

Proteomic analysis of host cell protein fouling during bioreactor harvesting

Chinese hamster ovary (CHO) cells are among the most common cell lines used for therapeutic protein production. Membrane fouling during bioreactor harvesting is a major limitation for the downstream purification of therapeutic proteins. Host cell proteins (HCP) are the most challenging impurities during downstream purification processes. The present work focuses on identification of HCP foulants during CHO bioreactor harvesting using reverse asymmetrical commercial membrane BioOptimal™ MF-SL. In order to investigate foulants and fouling behavior during cell clarification, for the first time a novel backwash process was developed to effectively elute almost all the HCP and DNA from the fouled membrane filter. The isoelectric points (pIs) and molecular weights (MWs) of major HCP in the bioreactor harvest and fouled on the membrane were successfully characterized using two-dimensional gel electrophoresis (2D SDS-PAGE). In addition, a total of 8 HCP were identified using matrix-assisted laser desorption/ionization-mass spectroscopy (MALDI-MS). The majority of these HCP are enzymes or associated with exosomes, both of which can form submicron-sized particles which could lead to the plugging of the filters.

Demonstration of a robust high cell density transient CHO platform yielding mAb titers of up to 2 g/L without medium exchange

Biopharmaceuticals like therapeutic monoclonal antibodies (mAbs) and other derived proteins are popular for treating various diseases. Transient gene expression (TGE) is typically used as a fast yet efficient method to generate moderate amounts of material. It has been used to support early stage research and discovery processes. Introduction of a robust high yielding and predictive TGE platform in Chinese hamster ovary (CHO) is crucial. It maintains the consistency in cell lines and processes throughout the early drug discovery and downstream manufacturing processes. This helps researchers to identify the issues at an early stage for timely resolution. In this study, we have demonstrated a simple high-titer platform for TGE in CHO based on a dilution process of seeding cells. We achieved titers ranging from 0.8 to 1.9 g/L for eight model mAbs at three scales (1, 30, 100 mL) in 10 days using our new platform. The ability to seed by dilution significantly streamlined the process and dramatically enhanced platform throughput. We observed a modest reduction in titer ranging from 11% to 28% when cells were seeded using dilution compared to when cells were seeded using medium exchange. Further studies revealed that carry over of spent medium into transfection negatively affected the DNA uptake and transcription processes, while the translation and secretion was minimally impacted. In summary, our transient CHO platform using cells prepared by dilution at high densities can achieve high titers of up to 1.9 g/L, which can be further improved by targeting the bottlenecks of transfection and transcription.

Animal Cell Lines as Expression Platforms in Viral Vaccine Production: A Post Covid-19 Perspective

Vaccines are considered the most effective tools for preventing diseases. In this sense, with the Covid-19 pandemic, the effects of which continue all over the world, humanity has once again remembered the importance of the vaccine. Also, with the various epidemic outbreaks that occurred previously, the development processes of effective vaccines against these viral pathogens have accelerated. By these efforts, many different new vaccine platforms have been approved for commercial use and have been introduced to the commercial landscape. In addition, innovations have been made in the production processes carried out with conventionally produced vaccine types to create a rapid response to prevent potential epidemics or pandemics. In this situation, various cell lines are being positioned at the center of the production processes of these new generation viral vaccines as expression platforms. Therefore, since the main goal is to produce a fast, safe, and effective vaccine to prevent the disease, in addition to existing expression systems, different cell lines that have not been used in vaccine production until now have been included in commercial production for the first time. In this review, first current viral vaccine types in clinical use today are described. Then, the reason for using cell lines, which are the expression platforms used in the production of these viral vaccines, and the general production processes of cell culture-based viral vaccines are mentioned. Also, selection parameters for animal cell lines as expression platforms in vaccine production are explained by considering bioprocess efficiency and current regulations. Finally, all different cell lines used in cell culture-based viral vaccine production and their properties are summarized, with an emphasis on the current and future status of cell cultures in industrial viral vaccine production.

Effects of autophagy-inhibiting chemicals on sialylation of Fc-fusion glycoprotein in recombinant CHO cells

The occurrence of autophagy in recombinant Chinese hamster ovary (rCHO) cell culture has attracted attention due to its effects on therapeutic protein production. Given the significance of glycosylation in therapeutic proteins, this study examined the effects of autophagy-inhibiting chemicals on sialylation of Fc-fusion glycoproteins in rCHO cells. Three chemical autophagy inhibitors known to inhibit different stages were separately treated with two rCHO cell lines that produce the same Fc-fusion glycoprotein derived from DUKX-B11 and DG44. All autophagy inhibitors significantly decreased the sialylation of Fc-fusion glycoprotein in both cell lines. The decrease in sialylation of Fc-fusion glycoprotein is unlikely to be attributed to the release of intracellular enzymes, given the high cell viability and low activity of extracellular sialidases. Interestingly, the five intracellular nucleotide sugars remained abundant in cells treated with autophagy inhibitors. In the mRNA expression profiles of 27 N-glycosylation-related genes using the NanoString nCounter system, no significant differences in gene expression were noted. With the positive effect of supplementing nucleotide sugar precursors on sialylation, attempts were made to enhance the levels of intracellular nucleotide sugars by supplying these precursors. The addition of nucleotide sugar precursors to cultures treated with inhibitors successfully enhanced the sialylation of Fc-fusion glycoproteins compared to the control culture. This was particularly evident under mild stress conditions and not under relatively severe stress conditions, which were characterized by a high decrease in sialylation. These results suggest that inhibiting autophagy in rCHO cell culture decreases sialylation of Fc-fusion glycoprotein by constraining the availability of intracellular nucleotide sugars. KEY POINTS: •  The autophagy inhibition in rCHO cell culture leads to a significant reduction in the sialylation of Fc-fusion glycoprotein. •  The pool of five intracellular nucleotide sugars remained highly abundant in cells treated with autophagy inhibitors. •  Supplementation of nucleotide sugar precursors effectively restores decreased sialylation, particularly under mild stress conditions but not in relatively severe stress conditions.

Synthetic symmetry breaking and programmable multicellular structure formation

During development, cells undergo symmetry breaking into differentiated subpopulations that self-organize into complex structures.1,2,3,4,5 However, few tools exist to recapitulate these behaviors in a controllable and coupled manner.6,7,8,9 Here, we engineer a stochastic recombinase genetic switch tunable by small molecules to induce programmable symmetry breaking, commitment to downstream cell fates, and morphological self-organization. Inducers determine commitment probabilities, generating tunable subpopulations as a function of inducer dosage. We use this switch to control the cell-cell adhesion properties of cells committed to each fate.10,11 We generate a wide variety of 3D morphologies from a monoclonal population and develop a computational model showing high concordance with experimental results, yielding new quantitative insights into the relationship between cell-cell adhesion strengths and downstream morphologies. We expect that programmable symmetry breaking, generating precise and tunable subpopulation ratios and coupled to structure formation, will serve as an integral component of the toolbox for complex tissue and organoid engineering.

From observational to actionable: rethinking omics in biologics production

As the era of omics continues to expand with increasing ubiquity and success in both academia and industry, omics-based experiments are becoming commonplace in industrial biotechnology, including efforts to develop novel solutions in bioprocess optimization and cell line development. Omic technologies provide particularly valuable 'observational' insights for discovery science, especially in academic research and industrial R&D; however, biomanufacturing requires a different paradigm to unlock 'actionable' insights from omics. Here, we argue the value of omic experiments in biotechnology can be maximized with deliberate selection of omic approaches and forethought about analysis techniques. We describe important considerations when designing and implementing omic-based experiments and discuss how systems biology analysis strategies can enhance efforts to obtain actionable insights in mammalian-based biologics production.

Enhanced cell growth, production, and mAb quality produced in Chinese hamster ovary-K1 cells by supplementing polyamine in the media

Polyamines such as putrescine (PUT), spermidine (SPD), and spermine (SPM) are amine group-containing biomolecules that regulate multiple intracellular functions such as proliferation, differentiation, and stress response in mammalian cells. Although these biomolecules can be generated intracellularly, lack of polyamine-synthesizing activity has occasionally been reported in a few mammalian cell lines such as Chinese hamster ovary (CHO)-K1; thus, polyamine supplementation in serum-free media is required to support cell growth and production. In the present study, the effects of biogenic polyamines PUT, SPD, and SPM in media on cell growth, production, metabolism, and antibody quality were explored in cultures of antibody-producing CHO-K1 cells. Polyamine withdrawal from media significantly suppressed cell growth and production. On the other hand, enhanced culture performance was achieved in polyamine-containing media conditions in a dose-dependent manner regardless of polyamine type. In addition, in polyamine-deprived medium, distinguishing metabolic features, such as enriched glycolysis and suppressed amino acid consumption, were observed and accompanied by higher heterogeneity of antibody quality compared with the optimal concentration of polyamines. Furthermore, an excessive concentration of polyamines negatively affected culture performance as well as antibody quality. Hence, the results suggest that polyamine-related metabolism needs to be further investigated and polyamines in cell growth media should be optimized as a controllable parameter in CHO cell culture bioprocessing. KEY POINTS: • Polyamine supplementation enhanced cell growth and production in a dose-dependent manner • Polyamine type and concentration in the media affected mAb quality • Optimizing polyamines in the media is suggested in CHO cell bioprocessing.

A reflection on the improvement of Chinese Hamster ovary cell-based bioprocesses through advances in proteomic techniques

Chinese hamster ovary (CHO) cells are the preferred mammalian host for the large-scale production of recombinant proteins in the biopharmaceutical industry. Research endeavors have been directed to the optimization of CHO-based bioprocesses to increase protein quantity and quality, often in an empirical manner. To provide a rationale for those achievements, a myriad of CHO proteomic studies has arisen in recent decades. This review gives an overview of significant advances in LC-MS-based proteomics and sheds light on CHO proteomic studies, with a particular focus on CHO cells with superior bioprocessing phenotypes (growth, viability, titer, productivity and cQA), that have exploited novel proteomic or sub-omic techniques. These proteomic findings expand the current knowledge and understanding about the underlying protein clusters, protein regulatory networks and biological pathways governing such phenotypic changes. The proteomic studies, highlighted herein, will help in the targeted modulation of these cell factories to the desired needs.

Systematic Adaptation of Bacillus licheniformis to 2-Phenylethanol Stress

The compound 2-phenylethanol (2-PE) is a bulk flavor and fragrance with a rose-like aroma that can be produced by microbial cell factories, but its cellular toxicity inhibits cellular growth and limits strain performance. Specifically, the microbe Bacillus licheniformis has shown a strong tolerance to 2-PE. Understanding these tolerance mechanisms is crucial for achieving the hyperproduction of 2-PE. In this report, the mechanisms of B. licheniformis DW2 resistance to 2-PE were studied by multi-omics technology coupled with physiological and molecular biological approaches. 2-PE induced reactive oxygen species formation and affected nucleic acid, ribosome, and cell wall synthesis. To manage 2-PE stress, the antioxidant and global stress response systems were activated; the repair system of proteins and homeostasis of the ion and osmotic were initiated. Furthermore, the tricarboxylic acid cycle and NADPH synthesis pathways were upregulated; correspondingly, scanning electron microscopy revealed that cell morphology was changed. These results provide deeper insights into the adaptive mechanisms of B. licheniformis to 2-PE and highlight the potential targets for genetic manipulation to enhance 2-PE resistance. IMPORTANCE The ability to tolerate organic solvents is essential for bacteria producing these chemicals with high titer, yield, and productivity. As exemplified by 2-PE, bioproduction of 2-PE represents a promising alternative to chemical synthesis and plant extraction approaches, but its toxicity hinders successful large-scale microbial production. Here, a multi-omics approach is employed to systematically study the mechanisms of B. licheniformis DW2 resistance to 2-PE. As a 2-PE-tolerant strain, B. licheniformis displays multifactorial mechanisms of 2-PE tolerance, including activating global stress response and repair systems, increasing NADPH supply, changing cell morphology and membrane composition, and remodeling metabolic pathways. The current work yields novel insights into the mechanisms of B. licheniformis resistance to 2-PE. This knowledge can also be used as a clue for improving bacterial performances to achieve industrial-scale production of 2-PE and potentially applied to the production of other relevant organic solvents, such as tyrosol and hydroxytyrosol.

Artificial intelligence in the analysis of glycosylation data

Glycans are complex, yet ubiquitous across biological systems. They are involved in diverse essential organismal functions. Aberrant glycosylation may lead to disease development, such as cancer, autoimmune diseases, and inflammatory diseases. Glycans, both normal and aberrant, are synthesized using extensive glycosylation machinery, and understanding this machinery can provide invaluable insights for diagnosis, prognosis, and treatment of various diseases. Increasing amounts of glycomics data are being generated thanks to advances in glycoanalytics technologies, but to maximize the value of such data, innovations are needed for analyzing and interpreting large-scale glycomics data. Artificial intelligence (AI) provides a powerful analysis toolbox in many scientific fields, and here we review state-of-the-art AI approaches on glycosylation analysis. We further discuss how models can be analyzed to gain mechanistic insights into glycosylation machinery and how the machinery shapes glycans under different scenarios. Finally, we propose how to leverage the gained knowledge for developing predictive AI-based models of glycosylation. Thus, guiding future research of AI-based glycosylation model development will provide valuable insights into glycosylation and glycan machinery.

Hybrid cell line development system utilizing site-specific integration and methotrexate-mediated gene amplification in Chinese hamster ovary cells

Site-specific integration has emerged as a promising strategy for streamlined and predictable Chinese hamster ovary (CHO) cell line development (CLD). However, the low specific productivity of the targeted integrants limits their practical application. In this study, we developed a hybrid CLD platform combining site-specific integration of a transgene and dihydrofolate reductase/methotrexate (DHFR/MTX)-mediated gene amplification to generate high-producing recombinant CHO cell lines. We used the CRISPR/Cas9-based recombinase-mediated cassette exchange landing pad platform to integrate the DHFR expression cassette and transgene landing pad into a CHO genomic hot spot, C12orf35 locus, of DHFR-knockout CHO-K1 host cell lines. When subjected to various MTX concentrations up to 1 μM, EGFP-expressing targeted integrants showed a 3.6-fold increase in EGFP expression in the presence of 200 nM MTX, accompanied by an increase in the DHFR and EGFP copy number. A single-step 200 nM MTX amplification increased the specific monoclonal antibody (mAb) productivity (q_mAb) of recombinant mAb-producing targeted integrants by 2.8-folds, reaching a q_mAb of 9.1–11.0 pg/cell/day. Fluorescence in situ hybridization analysis showed colocalization of DHFR and mAb sequences at the intended chromosomal locations without clear amplified arrays of signals. Most MTX-amplified targeted integrants sustained recombinant mAb production during long-term culture in the absence of MTX, supporting stable gene expression in the amplified cell lines. Our study provides a new CLD platform that increases the productivity of targeted integrants by amplifying the transgene copies.

Advanced strategies in glycosylation prediction and control during biopharmaceutical development: Avenues toward Industry 4.0

Glycosylation has been shown to define the safety and efficacy of biopharmaceuticals, thus classified as a critical quality attribute. However, controlling glycan heterogeneity has always been a major challenge owing to the multi-variate factors that govern the glycosylation process. Conventional approaches for controlling glycosylation such as gene editing and metabolic control have succeeded in obtaining desired glycan profiles in accordance with the Quality by Design paradigm. Nonetheless, the development of smart algorithms and omics-enabled complete cell characterization have made it possible to predict glycan profiles beforehand, and manipulate process variables accordingly. This review thus discusses the various approaches available for control and prediction of glycosylation in biopharmaceuticals. Further, the futuristic goal of integrating such technologies is discussed in order to attain an automated and digitized continuous bioprocess for control of glycosylation. Given, control of a process as complex as glycosylation requires intense monitoring intervention, we examine the current technologies that enable automation. Finally, we discuss the challenges and the technological gap that currently limits incorporation of an automated process in routine bio-manufacturing, with a glimpse into the economic bearing. This article is protected by copyright. All rights reserved.

Development of a stable antibody production system utilizing an Hspa5 promoter in CHO cells

Chinese hamster ovary (CHO) cells are widely used for manufacturing antibody drugs. We attempted to clone a novel high-expression promoter for producing monoclonal antibodies (mAbs) based on transcriptome analysis to enhance the transcriptional abundance of mAb genes. The efficacy of conventional promoters such as CMV and hEF1α decrease in the latter phase of fed-batch cell culture. To overcome this, we screened genes whose expression was maintained or increased throughout the culture period. Since CHO cells have diverse genetic expression depending on the selected clone and culture medium, transcriptome analysis was performed on multiple clones and culture media anticipated to be used in mAb manufacturing. We thus acquired the Hspa5 promoter as a novel high-expression promoter, which uniquely enables mAb productivity per cell to improve late in the culture period. Productivity also improved for various IgG subclasses under Hspa5 promoter control, indicating this promoter’s potential universal value for mAb production. Finally, it was suggested that mAb production with this promoter is correlated with the transcription levels of endoplasmic reticulum stress-related genes. Therefore, mAb production utilizing the Hspa5 promoter might be a new method for maintaining protein homeostasis and achieving stable expression of introduced mAb genes during fed-batch culture.

Chromosomal instability drives convergent and divergent evolution toward advantageous inherited traits in mammalian CHO bioproduction lineages

Genetic instability of Chinese hamster ovary (CHO) cells is implicated in production inconsistency through poorly defined mechanisms. Using a multi-omics approach, we analyzed the variations of CHO lineages derived from CHO-K1 cells. We identify an equilibrium between random genetic variation of the CHO genome and heritable traits driven by culture conditions, selection criteria, and genetic linkage. These inherited changes are associated with the selection pressures related to serum removal, suspension culture transition, protein expression, and secretion. We observed that a haploid reduction of a Chromosome 2 region after serum-free, suspension adaptation, was consistently inherited, suggesting common adaptation mechanisms. Genetic variations also included ∼200 insertions/deletions, ∼1000 single-nucleotide polymorphisms, and ∼300-2000 copy number variations, which were exacerbated after gene editing. In addition, heterochromatic chromosomes were preferentially lost as cells continuously evolved. Together, these observations demonstrate a highly plastic signature for adapted CHO cells and paves the way towards future host cell engineering.

CDMOs Play a Critical Role in the Biopharmaceutical Ecosystem

Biopharmaceutical industries have advanced significantly after the millennium. Novel biopharmaceuticals have been developed one after another, and blockbuster drugs have been produced. Accompanying the increase in the demand for biopharmaceuticals, a business model called “contract development manufacturing organization (CDMO)” has emerged. A CDMO is entrusted with the development and manufacturing of production processes from pharmaceutical companies. In this review, we identify the success factors of the biopharmaceutical CDMO by analyzing the foundry business for the semiconductor industry. Furthermore, we also review monoclonal antibody production platforms and new technologies that are critical aspects of differentiation strategies in the biopharmaceutical CDMO.

Insights into the Impact of Rosmarinic Acid on CHO Cell Culture Improvement through Transcriptomics Analysis

The use of antioxidants in Chinese hamster ovary (CHO) cell cultures to improve monoclonal antibody production has been a topic of great interest. Nevertheless, the antioxidants do not have consistent benefits of production improvement, which might be cell line specific and/or process specific. In this work, we investigated how treatment with the antioxidant rosmarinic acid (RA) improved cell growth and titer in CHO cell cultures using transcriptomics. In particular, transcriptomics analysis indicated that RA treatment modified gene expression and strongly affected the MAPK and PI3K/Akt signaling pathways, which regulate cell survival and cell death. Moreover, it was observed that these signaling pathways, which had been identified to be up-regulated on day 2 and day 6 by RA, were also up-regulated over time (from initial growth phase day 2 to slow growth or protein production phase day 6) in both conditions. In summary, this transcriptomics analysis provides insights into the role of the antioxidant RA in industrial cell culture processes. The current study also represents an example in the industry of how omics can be applied to gain an in-depth understanding of CHO cell biology and to identify critical pathways that can contribute to cell culture process improvement and cell line engineering.

Advances of Glycometabolism Engineering in Chinese Hamster Ovary Cells

As the most widely used mammalian cell line, Chinese hamster ovary (CHO) cells can express various recombinant proteins with a post translational modification pattern similar to that of the proteins from human cells. During industrial production, cells need large amounts of ATP to support growth and protein expression, and since glycometabolism is the main source of ATP for cells, protein production partly depends on the efficiency of glycometabolism. And efficient glycometabolism allows less glucose uptake by cells, reducing production costs, and providing a better mammalian production platform for recombinant protein expression. In the present study, a series of progresses on the comprehensive optimization in CHO cells by glycometabolism strategy were reviewed, including carbohydrate intake, pyruvate metabolism and mitochondrial metabolism. We analyzed the effects of gene regulation in the upstream and downstream of the glucose metabolism pathway on cell’s growth and protein expression. And we also pointed out the latest metabolic studies that are potentially applicable on CHO cells. In the end, we elaborated the application of metabolic models in the study of CHO cell metabolism.

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.

Selection of high-producing clones by a relative titer predictive model using image analysis

Background

The commercial success of monoclonal antibodies (Mabs) has made biological therapeutics attractive to pharmaceutical companies. The priority of biopharmaceutical companies is to acquire and develop cell lines that enable them to manufacture biologics quickly, consistently, and economically. Clone selection is a critical process for cell line development. However, the traditional clone selection process requires the evaluation of large numbers of clones using cell growth rate, cell densities and titer, product quality, and so on.

Methods

To improve efficiency of the clone selection strategies, we developed a relative titer (RT) prediction model by the quantitative information extracted from microscope images during the cell line development process. The performance of this RT prediction model was further evaluated with 50 clones from 5 different cell lines.

Results

The RT prediction model was able to predict high producers from a given data set when the same host cells were used. Although inaccurate prediction occurred when different host cell was used, this RT prediction model may serve as an excellent proof of concept study that quantitative information from cell line development images provides valuable information to facilitate the cell line development process.

Conclusions

Here, we present the first predictive model that can be used to estimate the relative productivity of Chinese hamster ovaries (CHO) clones during the cell line development. Additional experiments are currently in process to further improve the RT predictive model. Nevertheless, our current study will serve as a foundation for more prediction models for cell line development that can facilitate the selection of clones.

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.

Multi-omics profiling of a CHO cell culture system unravels the effect of culture pH on cell growth, antibody titer, and product quality

A robust monoclonal antibody (mAb) bioprocess requires physiological parameters such as temperature, pH, or dissolved oxygen to be well-controlled as even small variations in them could potentially impact the final product quality. For instance, pH substantially affects N-glycosylation, protein aggregation, and charge variant profiles, as well as mAb productivity. However, relatively less is known about how pH jointly influences product quality and titer. In this study, we investigated the effect of pH on culture performance, product titer, and quality profiles by applying longitudinal multi-omics profiling, including transcriptomics, proteomics, metabolomics, and glycomics, at three different culture pH set points. The subsequent systematic analysis of multi-omics data showed that pH set points differentially regulated various intracellular pathways including intracellular vesicular trafficking, cell cycle, and apoptosis, thereby resulting in differences in specific productivity, product titer, and quality profiles. In addition, a time-dependent variation in mAb N-glycosylation profiles, independent of pH, was identified to be mainly due to the accumulation of mAb proteins in the endoplasmic reticulum disrupting cellular homeostasis over culture time. Overall, this multi-omics-based study provides an in-depth understanding of the intracellular processes in mAb-producing CHO cell line under varied pH conditions, and could serve as a baseline for enabling the quality optimization and control of mAb production.

Considerations of the Impacts of Cell-Specific Growth and Production Rate on Clone Selection—A Simulation Study

For the manufacturing of complex biopharmaceuticals using bioreactors with cultivated mammalian cells, high product concentration is an important objective. The phenotype of the cells in a reactor plays an important role. Are clonal cell populations showing high cell-specific growth rates more favorable than cell lines with higher cell-specific productivities or vice versa? Five clonal Chinese hamster ovary cell populations were analyzed based on the data of a 3-month-stability study. We adapted a mechanistic cell culture model to the experimental data of one such clonally derived cell population. Uncertainties and prior knowledge concerning model parameters were considered using Bayesian parameter estimations. This model was used then to define an inoculum train protocol. Based on this, we subsequently simulated the impacts of differences in growth rates (±10%) and production rates (±10% and ±50%) on the overall cultivation time, including making the inoculum train cultures; the final production phase, the volumetric titer in that bioreactor and the ratio of both, defined as overall process productivity. We showed thus unequivocally that growth rates have a higher impact (up to three times) on overall process productivity and for product output per year, whereas cells with higher productivity can potentially generate higher product concentrations in the production vessel.

Towards rational glyco-engineering in CHO: from data to predictive models

Metabolic modelling strives to develop modelling approaches that are robust and highly predictive. To achieve this, various modelling designs, including hybrid models, and parameter estimation methods that define the type and number of parameters used in the model, are adapted. Accurate input data play an important role so that the selection of experimental methods that provide input data of the required precision with low measurement errors is crucial. For the biopharmaceutically relevant protein glycosylation, the most prominent available models are kinetic models which are able to capture the dynamic nature of protein N-glycosylation. In this review we focus on how to choose the most suitable model for a specific research question, as well as on parameters and considerations to take into account before planning relevant experiments.

Compartmentalized Proteomic Profiling Outlines the Crucial Role of the Classical Secretory Pathway during Recombinant Protein Production in Chinese Hamster Ovary Cells

Different cellular processes that contribute to protein production in Chinese hamster ovary (CHO) cells have been previously investigated by proteomics. However, although the classical secretory pathway (CSP) has been well documented as a bottleneck during recombinant protein (RP) production, it has not been well represented in previous proteomic studies. Hence, the significance of this pathway for production of RP was assessed by identifying its own proteins that were associated to changes in RP production, through subcellular fractionation coupled to shot-gun proteomics. Two CHO cell lines producing a monoclonal antibody with different specific productivities were used as cellular models, from which 4952 protein groups were identified, which represent a coverage of 59% of the Chinese hamster proteome. Data are available via ProteomeXchange with identifier PXD021014. By using SAM and ROTS algorithms, 493 proteins were classified as differentially expressed, of which about 80% was proposed as novel targets and one-third were assigned to the CSP. Endoplasmic reticulum (ER) stress, unfolded protein response, calcium homeostasis, vesicle traffic, glycosylation, autophagy, proteasomal activity, protein synthesis and translocation into ER lumen, and secretion of extracellular matrix components were some of the affected processes that occurred in the secretory pathway. Processes from other cellular compartments, such as DNA replication, transcription, cytoskeleton organization, signaling, and metabolism, were also modified. This study gives new insights into the molecular traits of higher producer cells and provides novel targets for development of new sub-lines with improved phenotypes for RP production.

The emerging role of cellular post-translational modifications in modulating growth and productivity of recombinant Chinese hamster ovary cells

Chinese hamster ovary (CHO) cells are one of the most commonly used host cell lines used for the production human therapeutic proteins. Much research over the past two decades has focussed on improving the growth, titre and cell specific productivity of CHO cells and in turn lowering the costs associated with production of recombinant proteins. CHO cell engineering has become of particular interest in recent years following the publication of the CHO cell genome and the availability of data relating to the proteome, transcriptome and metabolome of CHO cells. However, data relating to the cellular post-translational modification (PTMs) which can affect the functionality of CHO cellular proteins has only begun to be presented in recent years. PTMs are important to many cellular processes and can further alter proteins by increasing the complexity of proteins and their interactions. In this review, we describe the research presented from CHO cells to date related on three of the most important PTMs; glycosylation, phosphorylation and ubiquitination.

Proteomic Profiling of IgG1 Producing CHO Cells Using LC/LC-SPS-MS3: The Effects of Bioprocessing Conditions on Productivity and Product Quality

The biopharmaceutical market is dominated by monoclonal antibodies, the majority of which are produced in Chinese hamster ovary (CHO) cell lines. Intense cell engineering, in combination with optimization of various process parameters results in increasing product titers. To enable further improvements in manufacturing processes, detailed information about how certain parameters affect cellular mechanisms in the production cells, and thereby also the expressed drug substance, is required. Therefore, in this study the effects of commonly applied changes in bioprocessing parameters on an anti-IL8 IgG1 producing CHO DP-12 cell line were investigated on the level of host cell proteome expression combined with product quality assessment of the expressed IgG1 monoclonal antibody. Applying shifts in temperature, pH and dissolved oxygen concentration, respectively, resulted in altered productivity and product quality. Furthermore, analysis of the cells using two-dimensional liquid chromatography-mass spectrometry employing tandem mass tag based isotopic quantitation and synchronous precursor selection-MS³ detection revealed substantial changes in the protein expression profiles of CHO cells. Pathway analysis indicated that applied bioprocessing conditions resulted in differential activation of oxidative phosphorylation. Additionally, activation of ERK5 and TNFR1 signaling suggested an affected cell cycle. Moreover, in-depth product characterization by means of charge variant analysis, peptide mapping, as well as structural and functional analysis, revealed posttranslational and structural changes in the expressed drug substance. Taken together, the present study allows the conclusion that, in anti-IL8 IgG1 producing CHO DP-12 cells, an improved energy metabolism achieved by lowering the cell culture pH is favorable when aiming towards high antibody production rates while maintaining product quality.

CHOmics: A web-based tool for multi-omics data analysis and interactive visualization in CHO cell lines

Chinese hamster ovary (CHO) cell lines are widely used in industry for biological drug production. During cell culture development, considerable effort is invested to understand the factors that greatly impact cell growth, specific productivity and product qualities of the biotherapeutics. While high-throughput omics approaches have been increasingly utilized to reveal cellular mechanisms associated with cell line phenotypes and guide process optimization, comprehensive omics data analysis and management have been a challenge. Here we developed CHOmics, a web-based tool for integrative analysis of CHO cell line omics data that provides an interactive visualization of omics analysis outputs and efficient data management. CHOmics has a built-in comprehensive pipeline for RNA sequencing data processing and multi-layer statistical modules to explore relevant genes or pathways. Moreover, advanced functionalities were provided to enable users to customize their analysis and visualize the output systematically and interactively. The tool was also designed with the flexibility to accommodate other types of omics data and thereby enabling multi-omics comparison and visualization at both gene and pathway levels. Collectively, CHOmics is an integrative platform for data analysis, visualization and management with expectations to promote the broader use of omics in CHO cell research.

Chlorella vulgaris Extract as a Serum Replacement That Enhances Mammalian Cell Growth and Protein Expression

The global cell culture market is experiencing significant growth due to the rapid advancement in antibody-based and cell-based therapies. Both rely on the capacity of different living factories, namely prokaryotic and eukaryotic cells, plants or animals for reliable and mass production. The ability to improve production yield is of important concern. Among many strategies pursued, optimizing the complex nutritional requirements for cell growth and protein production has been frequently performed via culture media component titration and serum replacement. The addition of specific ingredients into culture media to modulate host cells’ metabolism has also recently been explored. In this study, we examined the use of extracted bioactive components of the microalgae Chlorella vulgaris, termed chlorella growth factor (CGF), as a cell culture additive for serum replacement and protein expression induction. We first established a chemical fingerprint of CGF using ultraviolet-visible spectroscopy and liquid chromatography-mass spectrometry and evaluated its ability to enhance cell proliferation in mammalian host cells. CGF successfully promoted the growth of Chinese hamster ovary (CHO) and mesenchymal stem cells (MSC), in both 2D and 3D cell cultures under reduced serum conditions for up to 21 days. In addition, CGF preserved cell functions as evident by an increase in protein expression in CHO cells and the maintenance of stem cell phenotype in MSC. Taken together, our results suggest that CGF is a viable culture media additive and growth matrix component, with wide ranging applications in biotechnology and tissue engineering.

Systematically gap-filling the genome-scale metabolic model of CHO cells

OBJECTIVE

Chinese hamster ovary (CHO) cells are the leading cell factories for producing recombinant proteins in the biopharmaceutical industry. In this regard, constraint-based metabolic models are useful platforms to perform computational analysis of cell metabolism. These models need to be regularly updated in order to include the latest biochemical data of the cells, and to increase their predictive power. Here, we provide an update to iCHO1766, the metabolic model of CHO cells.

RESULTS

We expanded the existing model of Chinese hamster metabolism with the help of four gap-filling approaches, leading to the addition of 773 new reactions and 335 new genes. We incorporated these into an updated genome-scale metabolic network model of CHO cells, named iCHO2101. In this updated model, the number of reactions and pathways capable of carrying flux is substantially increased.

CONCLUSIONS

The present CHO model is an important step towards more complete metabolic models of CHO cells.

Enzyme capacity-based genome scale modelling of CHO cells

Chinese hamster ovary (CHO) cells are most prevalently used for producing recombinant therapeutics in biomanufacturing. Recently, more rational and systems approaches have been increasingly exploited to identify key metabolic bottlenecks and engineering targets for cell line engineering and process development based on the CHO genome-scale metabolic model which mechanistically characterizes cell culture behaviours. However, it is still challenging to quantify plausible intracellular fluxes and discern metabolic pathway usages considering various clonal traits and bioprocessing conditions. Thus, we newly incorporated enzyme kinetic information into the updated CHO genome-scale model (iCHO2291) and added enzyme capacity constraints within the flux balance analysis framework (ecFBA) to significantly reduce the flux variability in biologically meaningful manner, as such improving the accuracy of intracellular flux prediction. Interestingly, ecFBA could capture the overflow metabolism under the glucose excess condition where the usage of oxidative phosphorylation is limited by the enzyme capacity. In addition, its applicability was successfully demonstrated via a case study where the clone- and media-specific lactate metabolism was deciphered, suggesting that the lactate-pyruvate cycling could be beneficial for CHO cells to efficiently utilize the mitochondrial redox capacity. In summary, iCHO2296 with ecFBA can be used to confidently elucidate cell cultures and effectively identify key engineering targets, thus guiding bioprocess optimization and cell engineering efforts as a part of digital twin model for advanced biomanufacturing in future.

Recent Developments in Bioprocessing of Recombinant Proteins: Expression Hosts and Process Development

Infectious diseases, along with cancers, are among the main causes of death among humans worldwide. The production of therapeutic proteins for treating diseases at large scale for millions of individuals is one of the essential needs of mankind. Recent progress in the area of recombinant DNA technologies has paved the way to producing recombinant proteins that can be used as therapeutics, vaccines, and diagnostic reagents. Recombinant proteins for these applications are mainly produced using prokaryotic and eukaryotic expression host systems such as mammalian cells, bacteria, yeast, insect cells, and transgenic plants at laboratory scale as well as in large-scale settings. The development of efficient bioprocessing strategies is crucial for industrial production of recombinant proteins of therapeutic and prophylactic importance. Recently, advances have been made in the various areas of bioprocessing and are being utilized to develop effective processes for producing recombinant proteins. These include the use of high-throughput devices for effective bioprocess optimization and of disposable systems, continuous upstream processing, continuous chromatography, integrated continuous bioprocessing, Quality by Design, and process analytical technologies to achieve quality product with higher yield. This review summarizes recent developments in the bioprocessing of recombinant proteins, including in various expression systems, bioprocess development, and the upstream and downstream processing of recombinant proteins.