Metabolite profiling of CHO cells with different growth characteristics

Mammalian cell cultures are the predominant system for the production of recombinant proteins requiring post-translational modifications. As protein yields are a function of growth performance (among others), and performance varies greatly between culture medium (e.g., different growth rates and peak cell densities), an understanding of the biological mechanisms underpinning this variability would facilitate rational medium and process optimization, increasing product yields, and reducing costs. We employed a metabolomics approach to analyze differences in metabolite concentrations of CHO cells cultivated in three different media exhibiting different growth rates and maximum viable cell densities. Analysis of intra- and extracellular metabolite concentrations over the course of the cultures using a combination of HPLC and GC-MS, readily detected medium specific and time dependent changes. Using multivariate data analysis, we identified a range of metabolites correlating with growth rate, illustrating how metabolomics can be used to relate gross phenotypic changes to the fine details of cellular metabolism.     

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.     

Dynamic multiscale metabolic network modeling of Chinese hamster ovary cell metabolism integrating N‐linked glycosylation in industrial biopharmaceutical manufacturing

Experimental and modeling work, described in this article, is focused on the metabolic pathway of Chinese hamster ovary (CHO) cells, which are the preferred expression system for monoclonal antibody protein production. CHO cells are one of the primary hosts for monoclonal antibodies production, which have extensive applications in multiple fields like biochemistry, biology and medicine. Here, an approach to explain cellular metabolism with in silico modeling of a microkinetic reaction network is presented and validated with unique experimental results. Experimental data of 25 different fed‐batch bioprocesses included the variation of multiple process parameters, such as pH, agitation speed, oxygen and CO₂ content, and dissolved oxygen. A total of 151 metabolites were involved in our proposed metabolic network, which consisted of 132 chemical reactions that describe the reaction pathways, and include 25 reactions describing N‐glycosylation and additional reactions for the accumulation of the produced glycoforms. Additional eight reactions are considered for accumulation of the N‐glycosylation products in the extracellular environment and one reaction to correlate cell degradation. The following pathways were considered: glycolysis, pentose phosphate pathway, nucleotide synthesis, tricarboxylic acid cycle, lipid synthesis, protein synthesis, biomass production, anaplerotic reactions, and membrane transport. With the applied modeling procedure, different operational scenarios and fed‐batch techniques can be tested.     

Metabolite profiling of CHO cells: Molecular reflections of bioprocessing effectiveness

Whilst development of medium and feeds has provided major advances in recombinant protein production in CHO cells, the fundamental understanding is limited. We have applied metabolite profiling with established robust (GC‐MS) analytics to define the molecular loci by which two yield‐enhancing feeds improve recombinant antibody yields from a model GS‐CHO cell line. With data across core metabolic pathways, that report on metabolism within several cellular compartments, these data identify key metabolites and events associated with increased cell survival and specific productivity of cells. Of particular importance, increased process efficiency was linked to the functional activity of the mitochondria, with the amount and time course of use/production of intermediates of the citric acid cycle, for uses such as lipid biosynthesis, precursor generation and energy production, providing direct indicators of cellular status with respect to productivity. The data provide clear association between specific cellular metabolic indicators and cell process efficiency, extending from prior indications of the relevance of lactate metabolic balance to other redox sinks (glycerol, sorbitol and threitol). The information, and its interpretation, identifies targets for engineering cell culture efficiency, either from genetic or environmental perspectives, and greater understanding of the significance of specific medium components towards overall CHO cell bioprocessing.     

Metabolic analysis of antibody producing CHO cells in fed‐batch production

Chinese hamster ovary (CHO) cells are commonly used for industrial production of recombinant proteins in fed batch or alternative production systems. Cells progress through multiple metabolic stages during fed‐batch antibody (mAb) production, including an exponential growth phase accompanied by lactate production, a low growth, or stationary phase when specific mAb production increases, and a decline when cell viability declines. Although media composition and cell lineage have been shown to impact growth and productivity, little is known about the metabolic changes at a molecular level. Better understanding of cellular metabolism will aid in identifying targets for genetic and metabolic engineering to optimize bioprocess and cell engineering. We studied a high expressing recombinant CHO cell line, designated high performer (HP), in fed‐batch productions using stable isotope tracers and biochemical methods to determine changes in central metabolism that accompany growth and mAb production. We also compared and contrasted results from HP to a high lactate producing cell line that exhibits poor growth and productivity, designated low performer (LP), to determine intrinsic metabolic profiles linked to their respective phenotypes. Our results reveal alternative metabolic and regulatory pathways for lactate and TCA metabolite production to those reported in the literature. The distribution of key media components into glycolysis, TCA cycle, lactate production, and biosynthetic pathways was shown to shift dramatically between exponential growth and stationary (production) phases. We determined that glutamine is both utilized more efficiently than glucose for anaplerotic replenishment and contributes more significantly to lactate production during the exponential phase. Cells shifted to glucose utilization in the TCA cycle as growth rate decreased. The magnitude of this metabolic switch is important for attaining high viable cell mass and antibody titers. We also found that phosphoenolpyruvate carboxykinase (PEPCK1) and pyruvate kinase (PK) are subject to differential regulation during exponential and stationary phases. The concomitant shifts in enzyme expression and metabolite utilization profiles shed light on the regulatory links between cell metabolism, media metabolites, and cell growth. Biotechnol. Bioeng. 2013; 110: 1735–1747. © 2013 Wiley Periodicals, Inc.     

Dynamic model of CHO cell metabolism

Fed-batch cultures are extensively used for the production of therapeutic proteins. However, process optimization is hampered by lack of quantitative models of mammalian cellular metabolism in these cultures. This paper presents a new kinetic model of CHO cell metabolism and a novel framework for simulating the dynamics of metabolic and biosynthetic pathways of these cells grown in fed-batch culture. The model defines a subset of the intracellular reactions with kinetic rate expressions based on extracellular metabolite concentrations and temperature- and redox-dependent regulatory variables. The simulation uses the rate expressions to calculate pseudo-steady state flux distributions and extracellular metabolite concentrations at discrete time points. Experimental data collected in this study for several different CHO cell fed-batch cultures are used to derive the rate expressions, fit the parameters, and validate the model. The simulations accurately predicted the effects of process variables, including temperature shift, seed density, specific productivity, and nutrient concentrations.     

Elucidation of metabolism in hybridoma cells grown in fed‐batch culture by genome‐scale modeling

Genome‐scale modeling of mouse hybridoma cells producing monoclonal antibodies (mAb) was performed to elucidate their physiological and metabolic states during fed‐batch cell culture. Initially, feed media nutrients were monitored to identify key components among carbon sources and amino acids with significant impact on the desired outcome, for example, cell growth and antibody production. The monitored profiles indicated rapid assimilation of glucose and glutamine during the exponential growth phase. Significant increase in mAb concentration was also observed when glutamine concentration was controlled at 0.5 mM as a feeding strategy. Based on the reconstructed genome‐scale metabolic network of mouse hybridoma cells and fed‐batch profiles, flux analysis was then implemented to investigate the cellular behavior and changes in internal fluxes during the cell culture. The simulated profile of the cell growth was consistent with experimentally measured specific growth rate. The in silico simulation results indicated (i) predominant utilization of glycolytic pathway for ATP production, (ii) importance of pyruvate node in metabolic shifting, and (iii) characteristic pattern in lactate to glucose ratio during the exponential phase. In future, experimental and in silico analyses can serve as a promising approach to identifying optimal feeding strategies and potential cell engineering targets as well as facilitate media optimization for the enhanced production of mAb or recombinant proteins in mammalian cells. Biotechnol. Bioeng. 2009;102: 1494–1504. © 2008 Wiley Periodicals, Inc.     

Towards a metabolic and isotopic steady state in CHO batch cultures for reliable isotope-based metabolic profiling

Attaining metabolic and isotopic balanced growth is one critical condition for physiological studies using isotope-labeled tracers, but is very difficult to obtain in batch culture due to the extensive metabolite exchange with the surrounding medium and related physiological changes. In the present study, we investigated metabolic and isotopic behavior of CHO cells in differently designed media. We observed that the assumption of balanced cell growth cannot be justified in batch culture of CHO cells directly using conventional, commercially available media. By systematically redesigning media composition and characterizing metabolic steady state based on mass balances and measurement of labeling dynamics, we achieved balanced cell growth for the main cellular substrates in CHO cells. This was done in a step-by-step analysis of growth and primary metabolism of CHO cells with the use of [U-¹³C]glucose feeding and adjusting concentrations of amino acids in the growth medium. The optimized media obtained at the end of the study provide balanced growth and isotopic steady state or at least asymptotic steady state. As a result, we established a platform to conduct isotope-based physiological studies of mammalian systems more reliably and therefore well suited for later use in metabolic profiling of mammalian systems such as ¹³C-labeled metabolic flux analysis.     

Towards dynamic metabolic flux analysis in CHO cell cultures

Chinese hamster ovary (CHO) cells are the most widely used mammalian cell line for biopharmaceutical production, with a total global market approaching $100 billion per year. In the pharmaceutical industry CHO cells are grown in fed-batch culture, where cellular metabolism is characterized by high glucose and glutamine uptake rates combined with high rates of ammonium and lactate secretion. The metabolism of CHO cells changes dramatically during a fed-batch culture as the cells adapt to a changing environment and transition from exponential growth phase to stationary phase. Thus far, it has been challenging to study metabolic flux dynamics in CHO cell cultures using conventional metabolic flux analysis techniques that were developed for systems at metabolic steady state. In this paper we review progress on flux analysis in CHO cells and techniques for dynamic metabolic flux analysis. Application of these new tools may allow identification of intracellular metabolic bottlenecks at specific stages in CHO cell cultures and eventually lead to novel strategies for improving CHO cell metabolism and optimizing biopharmaceutical process performance.     

Flux-sum analysis: a metabolite-centric approach for understanding the metabolic network

Background  

Constraint-based flux analysis of metabolic network model quantifies the reaction flux distribution to characterize the state of cellular metabolism. However, metabolites are key players in the metabolic network and the current reaction-centric approach may not account for the effect of metabolite perturbation on the cellular physiology due to the inherent limitation in model formulation. Thus, it would be practical to incorporate the metabolite states into the model for the analysis of the network.     

Characterizing Escherichia coli DH5alpha growth and metabolism in a complex medium using genome-scale flux analysis

Genome-scale flux analysis of Escherichia coli DH5alpha growth in a complex medium was performed to investigate the relationship between the uptake of various nutrients and their metabolic outcomes. During the exponential growth phase, we observed a sequential consumption order of serine, aspartate and glutamate in the complex medium as well as the complete consumption of key carbohydrate nutrients, glucose and trehalose. Based on the consumption and production rates of the measured metabolites, constraints-based flux analysis of a genome-scale E. coli model was then conducted to elucidate their utilization in the metabolism. The in silico analysis revealed that the cell exploited biosynthetic precursors taken up directly from the complex medium, through growth-related anabolic pathways. This suggests that the cell could be functioning in an energetically more efficient manner by reducing the energy needed to produce amino acids. The in silico simulation also allowed us to explain the observed rapid consumption of serine: excessively consumed external serine from the complex medium was mainly converted into pyruvate and glycine, which in turn, led to the acetate accumulation. The present work demonstrates the application of an in silico modeling approach to characterizing microbial metabolism under complex medium condition. This work further illustrates the use of in silico genome-scale analysis for developing better strategies related to improving microbial growth and enhancing the productivity of desirable metabolites.     

LC‐MS‐based metabolic characterization of high monoclonal antibody‐producing Chinese hamster ovary cells

The selection of suitable mammalian cell lines with high specific productivities is a crucial aspect of large‐scale recombinant protein production. This study utilizes a metabolomics approach to elucidate the key characteristics of Chinese hamster ovary (CHO) cells with high monoclonal antibody productivities (q_mAb). Liquid chromatography‐mass spectrometry (LC‐MS)‐based intracellular metabolite profiles of eight single cell clones with high and low q_mAb were obtained at the mid‐exponential phase during shake flask batch cultures. Orthogonal projection to latent structures discriminant analysis (OPLS‐DA) subsequently revealed key differences between the high and low q_mAb clones, as indicated by the variable importance for projection (VIP) scores. The mass peaks were further examined for their potential association with q_mAb across all clones using Pearson's correlation analysis. Lastly, the identities of metabolites with high VIP and correlation scores were confirmed by comparison with standards through LC‐MS‐MS. A total of seven metabolites were identified—NADH, FAD, reduced and oxidized glutathione, and three activated sugar precursors. These metabolites are involved in key cellular pathways of citric acid cycle, oxidative phosphorylation, glutathione metabolism, and protein glycosylation. To our knowledge, this is the first study to identify metabolites that are associated closely with q_mAb. The results suggest that the high producers had elevated levels of specific metabolites to better regulate their redox status. This is likely to facilitate the generation of energy and activated sugar precursors to meet the demands of producing more glycosylated recombinant monoclonal antibodies. Biotechnol. Bioeng. 2012; 109: 3103–3111. © 2012 Wiley Periodicals, Inc.     

Segmented linear modeling of CHO fed‐batch culture and its application to large scale production

We describe a systematic approach to model CHO metabolism during biopharmaceutical production across a wide range of cell culture conditions. To this end, we applied the metabolic steady state concept. We analyzed and modeled the production rates of metabolites as a function of the specific growth rate. First, the total number of metabolic steady state phases and the location of the breakpoints were determined by recursive partitioning. For this, the smoothed derivative of the metabolic rates with respect to the growth rate were used followed by hierarchical clustering of the obtained partition. We then applied a piecewise regression to the metabolic rates with the previously determined number of phases. This allowed identifying the growth rates at which the cells underwent a metabolic shift. The resulting model with piecewise linear relationships between metabolic rates and the growth rate did well describe cellular metabolism in the fed‐batch cultures. Using the model structure and parameter values from a small‐scale cell culture (2 L) training dataset, it was possible to predict metabolic rates of new fed‐batch cultures just using the experimental specific growth rates. Such prediction was successful both at the laboratory scale with 2 L bioreactors but also at the production scale of 2000 L. This type of modeling provides a flexible framework to set a solid foundation for metabolic flux analysis and mechanistic type of modeling. Biotechnol. Bioeng. 2017;114: 785–797. © 2016 The Authors. Biotechnology and Bioengineering Published by Wiley Periodicals, Inc.     

Inhibiting the apoptosis pathway using MDM2 in mammalian cell cultures

The ability to regulate apoptosis in mammalian cell cultures represents one approach to developing more economical and efficient processes. Genetic modification of cells using anti-apoptotic genes is one method that may be used to improve cellular performance. This study investigates a method to inhibit upstream apoptosis pathways through the overexpression of MDM2, an E3 ubiquitin ligase for p53. Both 293 and CHO cells expressing MDM2 were examined under both batch and spent media conditions. For batch cultures, MDM2 overexpression increased viable cell densities and viabilities over control cells with the largest enhancements observed in CHO cells. When CHO cells were passaged without medium exchange, cells expressing MDM2 reached a viable cell density that was nearly double the control and survived for an extra day in culture. When exposed to spent media initially, both 293-MDM2 and CHO-MDM2 cells continued to grow for 2 days while the control cells stopped growing after the first day. DNA analysis using flow cytometry confirmed that while CHO controls were found to be undergoing DNA fragmentation, CHO-MDM2 cells exhibit DNA degradation at a much slower rate. When compared to Bcl-2-expressing cells, MDM2 expression showed greater protection against apoptosis in passaged culture, spent medium, and following transient p53 overexpression. However, expression of the RING sequence of MDM2 responsible for E3 ligase activity without the other components of the protein was found to be toxic to 293 cells in culture. These results suggest that the overexpression of heterologous MDM2 represents a promising method to delay apoptosis in mammalian cell cultures.     

CHOmpact: A reduced metabolic model of Chinese hamster ovary cells with enhanced interpretability

Metabolic modeling has emerged as a key tool for the characterization of biopharmaceutical cell culture processes. Metabolic models have also been instrumental in identifying genetic engineering targets and developing feeding strategies that optimize the growth and productivity of Chinese hamster ovary (CHO) cells. Despite their success, metabolic models of CHO cells still present considerable challenges. Genome-scale metabolic models (GeMs) of CHO cells are very large (>6000 reactions) and are difficult to constrain to yield physiologically consistent flux distributions. The large scale of GeMs also makes the interpretation of their outputs difficult. To address these challenges, we have developed CHOmpact, a reduced metabolic network that encompasses 101 metabolites linked through 144 reactions. Our compact reaction network allows us to deploy robust, nonlinear optimization and ensure that the computed flux distributions are physiologically consistent. Furthermore, our CHOmpact model delivers enhanced interpretability of simulation results and has allowed us to identify the mechanisms governing shifts in the anaplerotic consumption of asparagine and glutamate as well as an important mechanism of ammonia detoxification within mitochondria. CHOmpact, thus, addresses key challenges of large-scale metabolic models and will serve as a platform to develop dynamic metabolic models for the control and optimization of biopharmaceutical cell culture processes.     

Identification of metabolic fluxes in hepatic cells from transient 13C-labeling experiments: Part II. Flux estimation

This contribution addresses the identification of metabolic fluxes and metabolite concentrations in mammalian cells from transient (13)C-labeling experiments. Whilst part I describes experimental set-up and acquisition of required metabolite and (13)C-labeling data, part II focuses on setting up network models and the estimation of intracellular fluxes. Metabolic fluxes were determined in glycolysis, pentose-phosphate pathway (PPP), and citric acid cycle (TCA) in a hepatoma cell line grown in aerobic batch cultures. In glycolytic and PPP metabolite pools isotopic stationarity was observed within 30 min, whereas in the TCA cycle the labeling redistribution did not reach isotopic steady state even within 180 min. In silico labeling dynamics were in accordance with in vivo (13)C-labeling data. Split ratio between glycolysis and PPP was 57%:43%; intracellular glucose concentration was estimated at 101.6 nmol per 10(6) cells. In contrast to isotopic stationary (13)C-flux analysis, transient (13)C-flux analysis can also be applied to industrially relevant mammalian cell fed-batch and batch cultures.     

Dynamics of growth and metabolism controlled by glutamine availability in Chinese hamster ovary cells

The physiology of animal cells is characterized by constantly changing environmental conditions and adapting cellular responses. Applied dynamic metabolic flux analysis captures metabolic dynamics and can be applied to industrially relevant cultivation conditions. We investigated the impact of glutamine availability or limitation on the physiology of CHO K1 cells in eight different batch and fed-batch cultivations. Varying glutamine availability resulted in global metabolic changes. We observed dose-dependent effects of glutamine in batch cultivation. Identifying metabolic links from the glutamine metabolism to specific metabolic pathways, we show that glutamine feeding results in its coupling to tricarboxylic acid cycle fluxes and in its decoupling from metabolic waste production. We provide a mechanistic explanation of the cellular responses upon mild or severe glutamine limitation and ammonia stress. The growth rate of CHO K1 decreased with increasing ammonia levels in the supernatant. On the other hand, growth, especially culture longevity, was stimulated at mild glutamine-limiting conditions. Flux rearrangements in the pyruvate and amino acid metabolism compensate glutamine limitation by consumption of alternative carbon sources and facilitating glutamine synthesis and mitigate ammonia stress as result of glutamine abundance.     

Real‐time monitoring of specific oxygen uptake rates of embryonic stem cells in a microfluidic cell culture device

Oxygen plays a key role in stem cell biology as a signaling molecule and as an indicator of cell energy metabolism. Quantification of cellular oxygen kinetics, i.e. the determination of specific oxygen uptake rates (sOURs), is routinely used to understand metabolic shifts. However current methods to determine sOUR in adherent cell cultures rely on cell sampling, which impacts on cellular phenotype. We present real‐time monitoring of cell growth from phase contrast microscopy images, and of respiration using optical sensors for dissolved oxygen. Time‐course data for bulk and peri‐cellular oxygen concentrations obtained for Chinese hamster ovary (CHO) and mouse embryonic stem cell (mESCs) cultures successfully demonstrated this non‐invasive and label‐free approach. Additionally, we confirmed non‐invasive detection of cellular responses to rapidly changing culture conditions by exposing the cells to mitochondrial inhibiting and uncoupling agents. For the CHO and mESCs, sOUR values between 8 and 60 amol cell^?1 s^?1, and 5 and 35 amol cell^?1 s^?1 were obtained, respectively. These values compare favorably with literature data. The capability to monitor oxygen tensions, cell growth, and sOUR, of adherent stem cell cultures, non‐invasively and in real time, will be of significant benefit for future studies in stem cell biology and stem cell‐based therapies.     

Sphingoid bases and phospholipase D activation

There is increased interest in physiological functions and mechanisms of action of sphingolipids metabolites, ceramide, sphingosine, and sphingosine-l-phosphate (SPP), members of a new class of lipid second messengers. This review summarizes current knowledge regarding the role of these sphingolipids metabolites in the actions of growth factors and focuses on the second messenger roles of sphingosine and its metabolite, SPP, in the regulation of cell growth. We also discuss possible interactions with intermediates of the well known glycerophospholipid cycle. Sphingosine and SPP generally provide positive mitogenic signals whereas ceramide has been reported to induce apoptosis and cell arrest in several mammalian cell lines. Stimulation of phospholipase D leading to an increase in phosphatidic acid, a positive regulator of cell growth, by sphingosine and SPP, and its inhibition by ceramide, might be related to their opposite effects on cell growth. This also indicates that sphingolipid turnover could regulate the diacylglycerol cycle. Cross-talk between sphingolipid turnover pathways and the diacylglycerol cycle increases complexity of signaling pathways leading to cellular proliferation and adds additional sites of regulation.