Impact of CHO Metabolism on Cell Growth and Protein Production: An Overview of Toxic and Inhibiting Metabolites and Nutrients

Comprehensive Vitamer Profiling of Folate Mono- and Polyglutamates in Baker's Yeast (Saccharomyces cerevisiae) as a Function of Different Sample Preparation Procedures

Folates are a group of B9 vitamins playing an important role in many metabolic processes such as methylation reactions, nucleotide synthesis or oxidation and reduction processes. However, humans are not able to synthesize folates de novo and thus rely on external sources thereof. Baker's yeast (Saccharomyces cerevisiae) has been shown to produce high amounts of this vitamin but extensive identification of its folate metabolism is still lacking. Therefore, we optimized and compared different sample preparation and purification procedures applying solid phase extraction (SPE). Strong anion exchange (SAX), C18 and hydrophilic-lipophilic-balanced (HLB) materials were tested for their applicability in future metabolomics studies. SAX turned out to be the preferred material for the quantitative purification of folates. Qualification of several folate vitamers was achieved by ultra-high pressure liquid chromatography quadrupole time of flight mass spectrometry (UHPLC-Q-ToF-MS) measurements and quantification was performed by liquid chromatography tandem mass spectrometry (LC-MS/MS) applying stable isotope dilution assays (SIDAs). The oxidation product s-pyrazino-triazine (MeFox) was included into the SIDA method for total folate determination and validation. Applying the best protocol (SAX) in regard to folate recovery, we analyzed 32 different vitamers in different polyglutamate states up to nonaglutamates, of which we could further identify 26 vitamers based on tandem-MS (MS2) spectra. Total folate quantification revealed differences in formyl folate contents depending on the cartridge chemistry used for purification. These are supposedly a result of interconversion reactions occurring during sample preparation due to variation in pH adjustments for the different purification protocols. The occurrence of interconversion and oxidation reactions should be taken into consideration in sample preparation procedures for metabolomics analyses with a focus on folates.

Progressively De-Differentiated Pancreatic Cancer Cells Shift from Glycolysis to Oxidative Metabolism and Gain a Quiescent Stem State

Pancreatic ductal adenocarcinoma (PDAC) is typically characterized by high chemoresistance and metastatic spread, features mainly attributable to cancer stem cells (CSCs). It is of central interest the characterization of CSCs and, in particular, the study of their metabolic features in order to selectively identify their peculiarities for an efficient therapeutic approach. In this study, CSCs have been obtained by culturing different PDAC cell lines with a specific growth medium. Cells were characterized for the typical stem/mesenchymal properties at short-, medium-, and long-term culture. Metabolomics, proteomics, analysis of oxygen consumption rate in live cells, and the effect of the inhibition of lactate transporter on cell proliferation have been performed to delineate the metabolism of CSCs. We show that gradually de-differentiated pancreatic cancer cells progressively increase the expression of both stem and epithelial-to-mesenchymal transition markers, shift their metabolism from a glycolytic to an oxidative one, and lastly gain a quiescent state. These quiescent stem cells are characterized by high chemo-resistance, clonogenic ability, and metastatic potential. Re-differentiation reverts these features, re-activating their proliferative capacity and glycolytic metabolism, which generally correlates with high aggressiveness. These observations add an important piece of knowledge to the comprehension of the biology of CSCs, whose metabolic plasticity could be exploited for the generation of promising and selective therapeutic approaches for PDAC patients.

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.

Integration of Time-Series Transcriptomic Data with Genome-Scale CHO Metabolic Models for mAb Engineering

Chinese hamster ovary (CHO) cells are the most commonly used cell lines in biopharmaceutical manufacturing. Genome-scale metabolic models have become a valuable tool to study cellular metabolism. Despite the presence of reference global genome-scale CHO model, context-specific metabolic models may still be required for specific cell lines (for example, CHO-K1, CHO-S, and CHO-DG44), and for specific process conditions. Many integration algorithms have been available to reconstruct specific genome-scale models. These methods are mainly based on integrating omics data (i.e., transcriptomics, proteomics, and metabolomics) into reference genome-scale models. In the present study, we aimed to investigate the impact of time points of transcriptomics integration on the genome-scale CHO model by assessing the prediction of growth rates with each reconstructed model. We also evaluated the feasibility of applying extracted models to different cell lines (generated from the same parental cell line). Our findings illustrate that gene expression at various stages of culture slightly impacts the reconstructed models. However, the prediction capability is robust enough on cell growth prediction not only across different growth phases but also in expansion to other cell lines.

Oxidative stress-alleviating strategies to improve recombinant protein production in CHO cells

Large scale biopharmaceutical production of biologics relies on the overexpression of foreign proteins by cells cultivated in stirred tank bioreactors. It is well recognized and documented fact that protein overexpression may impact host cell metabolism and that factors associated with large scale culture, such as the hydrodynamic forces and inhomogeneities within the bioreactors, may promote cellular stress. The metabolic adaptations required to support the high‐level expression of recombinant proteins include increased energy production and improved secretory capacity, which, in turn, can lead to a rise of reactive oxygen species (ROS) generated through the respiration metabolism and the interaction with media components. Oxidative stress is defined as the imbalance between the production of free radicals and the antioxidant response within the cells. Accumulation of intracellular ROS can interfere with the cellular activities and exert cytotoxic effects via the alternation of cellular components. In this context, strategies aiming to alleviate oxidative stress generated during the culture have been developed to improve cell growth, productivity, and reduce product microheterogeneity. In this review, we present a summary of the different approaches used to decrease the oxidative stress in Chinese hamster ovary cells and highlight media development and cell engineering as the main pathways through which ROS levels may be kept under control.

Computer-Aided Strategies for Determining the Amino Acid Composition of Medium for Chinese Hamster Ovary Cell-Based Biomanufacturing Platforms

Chinese hamster ovary (CHO) cells are used for the production of the majority of biopharmaceutical drugs, and thus have remained the standard industry host for the past three decades. The amino acid composition of the medium plays a key role in commercial scale biologics manufacturing, as amino acids constitute the building blocks of both endogenous and heterologous proteins, are involved in metabolic and non-metabolic pathways, and can act as main sources of nitrogen and carbon under certain conditions. As biomanufactured proteins become increasingly complex, the adoption of model-based approaches become ever more popular in complementing the challenging task of medium development. The extensively studied amino acid metabolism is exceptionally suitable for such model-driven analyses, and although still limited in practice, the development of these strategies is gaining attention, particularly in this domain. This paper provides a review of recent efforts. We first provide an overview of the widely adopted practice, and move on to describe the model-driven approaches employed for the improvement and optimization of the external amino acid supply in light of cellular amino acid demand. We conclude by proposing the likely prevalent direction the field is heading towards, providing a critical evaluation of the current state and the future challenges and considerations.

Oxygen Uptake Rate Soft-Sensing via Dynamic k L a Computation: Cell Volume and Metabolic Transition Prediction in Mammalian Bioprocesses

In aerobic cell cultivation processes, dissolved oxygen is a key process parameter, and an optimal oxygen supply has to be ensured for proper process performance. To achieve optimal growth and/or product formation, the rate of oxygen transfer has to be in right balance with the consumption by cells. In this study, a 15 L mammalian cell culture bioreactor was characterized with respect to k_La under varying process conditions. The resulting dynamic k_La description combined with functions for the calculation of oxygen concentrations under prevailing process conditions led to an easy-to-apply model, that allows real-time calculation of the oxygen uptake rate (OUR) throughout the bioprocess without off-gas analyzers. Subsequently, the established OUR soft-sensor was applied in a series of 13 CHO fed-batch cultivations. The OUR was found to be directly associated with the amount of viable biomass in the system, and deploying of cell volumes instead of cell counts led to higher correlations. A two-segment linear model predicted the viable biomass in the system sufficiently. The segmented model was necessary due to a metabolic transition in which the specific consumption of oxygen changed. The aspartate to glutamate ratio was identified as an indicator of this metabolic shift. The detection of such transitions is enabled by a combination of the presented dynamic OUR method with another state-of-the-art viable biomass soft-sensor. In conclusion, this hyphenated technique is a robust and powerful tool for advanced bioprocess monitoring and control based exclusively on bioreactor characteristics.

Application of a genome-scale model in tandem with enzyme assays for identification of metabolic signatures of high and low CHO cell producers

Biopharmaceutical industrial processes are based on high yielding stable recombinant Chinese Hamster Ovary (CHO) cells that express monoclonal antibodies. However, the process and feeding regimes need to be adapted for each new cell line, as they all have a slightly different metabolism and product performance. A main limitation for accelerating process development is that the metabolic pathways underlying this physiological variability are not yet fully understood. This study describes the evolution of intracellular fluxes during the process for 4 industrial cell lines, 2 high producers and 2 low producers (n = 3), all of them producing a different antibody. In order to understand from a metabolic point of view the phenotypic differences observed, and to find potential targets for improving specific productivity of low producers, the analysis was supported by a tailored genome-scale model and was validated with enzymatic assays performed at different days of the process. A total of 59 reactions were examined from different key pathways, namely glycolysis, pentose phosphate pathway, TCA cycle, lipid metabolism, and oxidative phosphorylation. The intracellular fluxes did not show a metabolic correlation between high producers, but the degree of similitude observed between cell lines could be confirmed with additional experimental observations. The whole analysis led to a better understanding of the metabolic requirements for all the cell lines, allowed to the identification of metabolic bottlenecks and suggested targets for further cell line engineering. This study is a successful application of a curated genome-scale model to multiple industrial cell lines, which makes the metabolic model suitable for process platform.

Multi-Omics Study on the Impact of Cysteine Feed Level on Cell Viability and mAb Production in a CHO Bioprocess

There is continual demand to maximize CHO cell culture productivity of a biotherapeutic while maintaining product quality. In this study, a comprehensive multi-omics analysis is performed to investigate the cellular response to the level of dosing of the amino acid cysteine (Cys) in the production of a monoclonal antibody (mAb). When Cys feed levels are insufficient, there is a significant decrease in protein titer. Multi-omics (metabolomics and proteomics, with support from RNAseq) is performed over the time course of the CHO bioprocess producing an IgG1 mAb in 5 L bioreactors. Pathway analysis reveals that insufficient levels of Cys in the feed lead to Cys depletion in the cell. This depletion negatively impacts antioxidant molecules, such as glutathione (GSH) and taurine, leading to oxidative stress with multiple deleterious cellular effects. In this paper, the resultant ER stress and subsequent apoptosis that affects cell viability and viable cell density has been considered. Key metabolic enzymes and metabolites are identified that can be potentially monitored as the process progresses and/or increased in the cell either by nutrient feeding or genetic engineering. This work reinforces the centrality of redox balance to cellular health and success of the bioprocess as well as the power of multi-omics to provide an in-depth understanding of the CHO cell biology during biopharmaceutical production.

Metabolic flux balance analysis during lactate and glucose concomitant consumption in HEK293 cell cultures

At early stages of the exponential growth phase in HEK293 cell cultures, the tricarboxylic acid cycle is unable to process all the amount of NADH generated in the glycolysis pathway, being lactate the main by-product. However, HEK293 cells are also able to metabolize lactate depending on the environmental conditions. It has been recently observed that one of the most important modes of lactate metabolization is the cometabolism of lactate and glucose, observed even during the exponential growth phase. Extracellular lactate concentration and pH appear to be the key factors triggering the metabolic shift from glucose consumption and lactate production to lactate and glucose concomitant consumption. The hypothesis proposed for triggering this metabolic shift to lactate and glucose concomitant consumption is that HEK293 cells metabolize extracellular lactate as a response to both extracellular protons and lactate accumulation, by means of cotransporting them (extracellular protons and lactate) into the cytosol. At this point, there exists a considerable controversy about how lactate reaches the mitochondrial matrix: the first hypothesis proposes that lactate is converted into pyruvate in the cytosol, and afterward, pyruvate enters into the mitochondria; the second alternative considers that lactate enters first into the mitochondria, and then, is converted into pyruvate. In this study, lactate transport and metabolization into mitochondria is shown to be feasible, as evidenced by means of respirometry tests with isolated active mitochondria, including the depletion of lactate concentration of the respirometry assay. Although the capability of lactate metabolization by isolated mitochondria is demonstrated, the possibility of lactate being converted into pyruvate in the cytosol cannot be excluded from the discussion. For this reason, the calculation of the metabolic fluxes for an HEK293 cell line was performed for the different metabolic phases observed in batch cultures under pH controlled and noncontrolled conditions, considering both hypotheses. The main objective of this study is to evaluate the redistribution of cellular metabolism and compare the differences or similarities between the phases before and after the metabolic shift of HEK293 cells (shift observed when pH is not controlled). That is from a glucose consumption/lactate production phase to a glucose-lactate coconsumption phase. Interestingly, switching to a glucose and lactate cometabolization results in a better-balanced cell metabolism, with decreased glucose and amino acids uptake rates, affecting minimally cell growth. This behavior could be applied to further develop new approaches in terms of cell engineering and to develop improved cell culture strategies in the field of animal cell technology.