Parallel labeling experiments with [1,2-(13)C]glucose and [U-(13)C]glutamine provide new insights into CHO cell metabolism

Metabolic and transcriptomic reprogramming during contact inhibition-induced quiescence is mediated by YAP-dependent and YAP-independent mechanisms

Metabolic rewiring during the proliferation-to-quiescence transition is poorly understood. Here, using a model of contact inhibition-induced quiescence, we conducted 13C-metabolic flux analysis in proliferating (P) and quiescent (Q) mouse embryonic fibroblasts (MEFs) to investigate this process. Q cells exhibit reduced glycolysis but increased TCA cycle flux and mitochondrial respiration. Reduced glycolytic flux in Q cells correlates with reduced glycolytic enzyme expression mediated by yes-associated protein (YAP) inhibition. The increased TCA cycle activity and respiration in Q cells is mediated by induced mitochondrial pyruvate carrier (MPC) expression, rendering them vulnerable to MPC inhibition. The malate-to-pyruvate flux, which generates NADPH, is markedly reduced by modulating malic enzyme 1 (ME1) dimerization in Q cells. Conversely, the malate dehydrogenase 1 (MDH1)-mediated oxaloacetate-to-malate flux is reversed and elevated in Q cells, driven by high mitochondrial-derived malate levels, reduced cytosolic oxaloacetate, elevated MDH1 levels, and a high cytoplasmic NAD+/NADH ratio. Transcriptomic analysis revealed large number of genes are induced in Q cells, many of which are associated with the extracellular matrix (ECM), while YAP-dependent and cell cycle-related genes are repressed. The results suggest that high TCA cycle flux and respiration in Q cells are required to generate ATP and amino acids to maintain de-novo ECM protein synthesis and secretion.

Dialysis rolled scaffold bioreactor allows extended production of monoclonal antibody with reduced media use

Rapidly expanding biopharmaceutical market demands more cost-effective platforms to produce protein therapeutics. To this end, novel approaches, such as perfusion culture or concentrated fed-batch, have been explored for higher yields and lower manufacturing costs. Although these new approaches produced promising results, but their wide-spread use in the industry is still limited. In this study, a dialysis rolled scaffold bioreactor was presented for long-term production of monoclonal antibodies with reduced media consumption. Media dialysis can selectively remove cellular bio-wastes without losing cells or produced recombinant proteins. The dialysis process was streamlined to significantly improve its efficiency. Then, extended culture of recombinant CHO cells for 41 days was successfully demonstrated with consistent production rate and minimal media consumption. The unique configuration of the developed bioreactor allows efficient dialysis for media management, as well as rapid media exchange to harvest produced recombinant proteins before they degrade. Taken together, it was envisioned that the developed bioreactor will enable cost-effective and long-term large-scale culture of various cells for biopharmaceutical production.

Metabolic regulatory network kinetic modeling with multiple isotopic tracers for iPSCs

The rapidly expanding market for regenerative medicines and cell therapies highlights the need to advance the understanding of cellular metabolisms and improve the prediction of cultivation production process for human induced pluripotent stem cells (iPSCs). In this paper, a metabolic kinetic model was developed to characterize the underlying mechanisms of iPSC culture process, which can predict cell response to environmental perturbation and support process control. This model focuses on the central carbon metabolic network, including glycolysis, pentose phosphate pathway, tricarboxylic acid cycle, and amino acid metabolism, which plays a crucial role to support iPSC proliferation. Heterogeneous measures of extracellular metabolites and multiple isotopic tracers collected under multiple conditions were used to learn metabolic regulatory mechanisms. Systematic cross-validation confirmed the model's performance in terms of providing reliable predictions on cellular metabolism and culture process dynamics under various culture conditions. Thus, the developed mechanistic kinetic model can support process control strategies to strategically select optimal cell culture conditions at different times, ensure cell product functionality, and facilitate large-scale manufacturing of regenerative medicines and cell therapies.

Cell-culture process optimization via model-based predictions of metabolism and protein glycosylation

In order to meet the rising demand for biologics and become competitive on the developing biosimilar market, there is a need for process intensification of biomanufacturing processes. Process development of biologics has historically relied on extensive experimentation to develop and optimize biopharmaceutical manufacturing. Experimentation to optimize media formulations, feeding schedules, bioreactor operations and bioreactor scale up is expensive, labor intensive and time consuming. Mathematical modeling frameworks have the potential to enable process intensification while reducing the experimental burden. This review focuses on mathematical modeling of cellular metabolism and N-linked glycosylation as applied to upstream manufacturing of biologics. We review developments in the field of modeling cellular metabolism of mammalian cells using kinetic and stoichiometric modeling frameworks along with their applications to simulate, optimize and improve mechanistic understanding of the process. Interest in modeling N-linked glycosylation has led to the creation of various types of parametric and non-parametric models. Most published studies on mammalian cell metabolism have performed experiments in shake flasks where the pH and dissolved oxygen cannot be controlled. Efforts to understand and model the effect of bioreactor-specific parameters such as pH, dissolved oxygen, temperature, and bioreactor heterogeneity are critically reviewed. Most modeling efforts have focused on the Chinese Hamster Ovary (CHO) cells, which are most commonly used to produce monoclonal antibodies (mAbs). However, these modeling approaches can be generalized and applied to any mammalian cell-based manufacturing platform. Current and potential future applications of these models for Vero cell-based vaccine manufacturing, CAR-T cell therapies, and viral vector manufacturing are also discussed. We offer specific recommendations for improving the applicability of these models to industrially relevant processes.

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

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

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.

A contribution of metabolic engineering to addressing medical problems: Metabolic flux analysis

Metabolic engineering has served as a systematic discipline for industrial biotechnology as it has offered systematic tools and methods for strain development and bioprocess optimization. Because these metabolic engineering tools and methods are concerned with the biological network of a cell with emphasis on metabolic network, they have also been applied to a range of medical problems where better understanding of metabolism has also been perceived to be important. Metabolic flux analysis (MFA) is a unique systematic approach initially developed in the metabolic engineering community, and has proved its usefulness and potential when addressing a range of medical problems. In this regard, this review discusses the contribution of MFA to addressing medical problems. For this, we i) provide overview of the milestones of MFA, ii) define two main branches of MFA, namely constraint-based reconstruction and analysis (COBRA) and isotope-based MFA (iMFA), and iii) present successful examples of their medical applications, including characterizing the metabolism of diseased cells and pathogens, and identifying effective drug targets. Finally, synergistic interactions between metabolic engineering and biomedical sciences are discussed with respect to MFA.

13C-Metabolic flux analysis of 3T3-L1 adipocytes illuminates its core metabolism under hypoxia

Hypoxia has been identified as a major factor in the pathogenesis of adipose tissue inflammation, which is a hallmark of obesity and obesity-linked type 2 diabetes mellitus. In this study, we have investigated the impact of hypoxia (1% oxygen) on the physiology and metabolism of 3T3-L1 adipocytes, a widely used cell culture model of adipose. Specifically, we applied parallel labeling experiments, isotopomer spectral analysis, and ¹³C-metabolic flux analysis to quantify the impact of hypoxia on adipogenesis, de novo lipogenesis and metabolic flux reprogramming in adipocytes. We found that 3T3-L1 cells can successfully differentiate into lipid-accumulating adipocytes under hypoxia, although the production of lipids was reduced by about 40%. Quantitative flux analysis demonstrated that short-term (1 day) and long-term (7 days) exposure to hypoxia resulted in similar reprogramming of cellular metabolism. Overall, we found that hypoxia: 1) reduced redox and energy generation by more than 2-fold and altered the patterns of metabolic pathway contributions to production and consumption of energy and redox cofactors; 2) redirected glucose metabolism from pentose phosphate pathway and citric acid cycle to lactate production; 3) rewired glutamine metabolism, from net glutamine production to net glutamine catabolism; 4) suppressed branched chain amino acid consumption; and 5) reduced biosynthesis of odd-chain fatty acids and mono-unsaturated fatty acids, while synthesis of saturated even-chain fatty acids was not affected. Together, these results highlight the profound impact of extracellular microenvironment on adipocyte metabolic activity and function.

1,2-13C2-Glucose Tracing Approach to Assess Metabolic Alterations of Human Monocytes under Neuroinflammatory Conditions

Neuroinflammation is one of the common features in most neurological diseases including multiple sclerosis (MScl) and neurodegenerative diseases such as Alzheimer's disease (AD). It is associated with local brain inflammation, microglial activation, and infiltration of peripheral immune cells into cerebrospinal fluid (CSF) and the central nervous system (CNS). It has been shown that the diversity of phenotypic changes in monocytes in CSF relates to neuroinflammation. It remains to be investigated whether these phenotypic changes are associated with functional or metabolic alteration, which may give a hint to their function or changes in cell states, e.g., cell activation. In this article, we investigate whether major metabolic pathways of blood monocytes alter after exposure to CSF of healthy individuals or patients with AD or MScl. Our findings show a significant alteration of the metabolism of monocytes treated with CSF from patients and healthy donors, including higher production of citric acid and glutamine, suggesting a more active glycolysis and tricarboxylic acid (TCA) cycle and reduced production of glycine and serine. These alterations suggest metabolic reprogramming of monocytes, possibly related to the change of compartment (from blood to CSF) and/or disease-related. Moreover, the levels of serine differ between AD and MScl, suggesting different phenotypic alterations between diseases.

Glutamine addiction promotes glucose oxidation in triple-negative breast cancer

Glutamine is a conditionally essential nutrient for many cancer cells, but it remains unclear how consuming glutamine in excess of growth requirements confers greater fitness to glutamine-addicted cancers. By contrasting two breast cancer subtypes with distinct glutamine dependencies, we show that glutamine-indispensable triple-negative breast cancer (TNBC) cells rely on a non-canonical glutamine-to-glutamate overflow, with glutamine carbon routed once through the TCA cycle. Importantly, this single-pass glutaminolysis increases TCA cycle fluxes and replenishes TCA cycle intermediates in TNBC cells, a process that achieves net oxidation of glucose but not glutamine. The coupling of glucose and glutamine catabolism appears hard-wired via a distinct TNBC gene expression profile biased to strip and then sequester glutamine nitrogen, but hampers the ability of TNBC cells to oxidise glucose when glutamine is limiting. Our results provide a new understanding of how metabolically rigid TNBC cells are sensitive to glutamine deprivation and a way to select vulnerable TNBC subtypes that may be responsive to metabolic-targeted therapies.

Metabolic Profiling of CHO Cells during the Production of Biotherapeutics

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

Attenuation of glutamine synthetase selection marker improves product titer and reduces glutamine overflow in Chinese hamster ovary cells

The glutamine synthetase (GS) expression system is commonly used to ensure stable transgene integration and amplification in CHO host lines. Transfected cell populations are typically grown in the presence of the GS inhibitor, methionine sulfoximine (MSX), to further select for increased transgene copy number. However, high levels of GS activity produce excess glutamine. We hypothesized that attenuating the GS promoter while keeping the strong IgG promoter on the GS-IgG expression vector would result in a more efficient cellular metabolic phenotype. Herein, we characterized CHO cell lines expressing GS from either an attenuated promoter or an SV40 promoter and selected with/without MSX. CHO cells with the attenuated GS promoter had higher IgG specific productivity and lower glutamine production compared to cells with SV40-driven GS expression. Selection with MSX increased both specific productivity and glutamine production, regardless of GS promoter strength. ¹³ C metabolic flux analysis (MFA) was performed to further assess metabolic differences between these cell lines. Interestingly, central carbon metabolism was unaltered by the attenuated GS promoter while the fate of glutamate and glutamine varied depending on promoter strength and selection conditions. This study highlights the ability to optimize the GS expression system to improve IgG production and reduce wasteful glutamine overflow, without significantly altering central metabolism. Additionally, a detailed supplementary analysis of two "lactate runaway" reactors provides insight into the poorly understood phenomenon of excess lactate production by some CHO cell cultures. This article is protected by copyright. All rights reserved.

Isotopically nonstationary 13C metabolic flux analysis in resting and activated human platelets

Platelet metabolism is linked to platelet hyper- and hypoactivity in numerous human diseases. Developing a detailed understanding of the link between metabolic shifts and platelet activation state is integral to improving human health. Here, we show the first application of isotopically nonstationary ¹³C metabolic flux analysis to quantitatively measure carbon fluxes in both resting and thrombin activated platelets. Metabolic flux analysis results show that resting platelets primarily metabolize glucose to lactate via glycolysis, while acetate is oxidized to fuel the tricarboxylic acid cycle. Upon activation with thrombin, a potent platelet agonist, platelets increase their uptake of glucose 3-fold. This results in an absolute increase in flux throughout central metabolism, but when compared to resting platelets they redistribute carbon dramatically. Activated platelets decrease relative flux to the oxidative pentose phosphate pathway and TCA cycle from glucose and increase relative flux to lactate. These results provide the first report of reaction-level carbon fluxes in platelets and allow us to distinguish metabolic fluxes with much higher resolution than previous studies.

Coordinated reprogramming of metabolism and cell function in adipocytes from proliferation to differentiation

Adipose tissue plays a major role in regulating lipid and energy homeostasis by storing excess nutrients, releasing energetic substrates through lipolysis, and regulating metabolism of other tissues and organs through endocrine and paracrine signaling. Adipocytes within fat tissues store excess nutrients through increased cell number (hyperplasia), increased cell size (hypertrophy), or both. The differentiation of pre-adipocytes into mature lipid-accumulating adipocytes requires a complex interaction of metabolic pathways that is still incompletely understood. Here, we applied parallel labeling experiments and ¹³C-metabolic flux analysis to quantify precise metabolic fluxes in proliferating and differentiated 3T3-L1 cells, a widely used model to study adipogenesis. We found that morphological and biomass composition changes in adipocytes were accompanied by significant shifts in metabolic fluxes, encompassing all major metabolic pathways. In contrast to proliferating cells, differentiated adipocytes 1) increased glucose uptake and redirected glucose utilization from lactate production to lipogenesis and energy generation; 2) increased pathway fluxes through glycolysis, oxidative pentose phosphate pathway and citric acid cycle; 3) reduced lactate secretion, resulting in increased ATP generation via oxidative phosphorylation; 4) rewired glutamine metabolism, from glutaminolysis to de novo glutamine synthesis; 5) increased cytosolic NADPH production, driven mostly by increased cytosolic malic enzyme flux; 6) increased production of monounsaturated C16:1; and 7) activated a mitochondrial pyruvate cycle through simultaneous activity of pyruvate carboxylase, malate dehydrogenase and malic enzyme. Taken together, these results quantitatively highlight the complex interplay between pathway fluxes and cell function in adipocytes, and suggest a functional role for metabolic reprogramming in adipose differentiation and lipogenesis.

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.

Differential substrate use in EGF- and oncogenic KRAS-stimulated human mammary epithelial cells

Many metabolic phenotypes in cancer cells are also characteristic of proliferating nontransformed mammalian cells, and attempts to distinguish between phenotypes resulting from oncogenic perturbation from those associated with increased proliferation are limited. Here, we examined the extent to which metabolic changes corresponding to oncogenic KRAS expression differed from those corresponding to epidermal growth factor (EGF)-driven proliferation in human mammary epithelial cells (HMECs). Removal of EGF from culture medium reduced growth rates and glucose/glutamine consumption in control HMECs despite limited changes in respiration and fatty acid synthesis, while the relative contribution of branched-chain amino acids to the TCA cycle and lipogenesis increased in the near-quiescent conditions. Most metabolic phenotypes measured in HMECs expressing mutant KRAS were similar to those observed in EGF-stimulated control HMECs that were growing at comparable rates. However, glucose and glutamine consumption as well as lactate and glutamate production were lower in KRAS-expressing cells cultured in media without added EGF, and these changes correlated with reduced sensitivity to GLUT1 inhibitor and phenformin treatment. Our results demonstrate the strong dependence of metabolic behavior on growth rate and provide a model to distinguish the metabolic influences of oncogenic mutations and nononcogenic growth.

Compartment-specific metabolome labeling enables the identification of subcellular fluxes that may serve as promising metabolic engineering targets in CHO cells

¹³C labeling data are used to calculate quantitative intracellular flux patterns reflecting in vivo conditions. Given that approaches for compartment-specific metabolomics exist, the benefits they offer compared to conventional non-compartmented ¹³C flux studies remain to be determined. Using compartment-specific labeling information of IgG1-producing Chinese hamster ovary cells, this study investigated differences of flux patterns exploiting and ignoring metabolic labeling data of cytosol and mitochondria. Although cellular analysis provided good estimates for the majority of intracellular fluxes, half of the mitochondrial transporters, and NADH and ATP balances, severe differences were found for some reactions. Accurate flux estimations of almost all iso-enzymes heavily depended on the sub-cellular labeling information. Furthermore, key discrepancies were found for the mitochondrial carriers v_AGC1 (Aspartate/Glutamate antiporter), v_DIC (Malate/H⁺ symporter), and v_OGC (α-ketoglutarate/malate antiporter). Special emphasis is given to the flux of cytosolic malic enzyme (v_ME): it could not be estimated without the compartment-specific malate labeling information. Interesting enough, cytosolic malic enzyme is an important metabolic engineering target for improving cell-specific IgG1 productivity. Hence, compartment-specific ¹³C labeling analysis serves as prerequisite for related metabolic engineering studies.

Rapid intensification of an established CHO cell fed-batch process

Currently, the mammalian biomanufacturing industry explores process intensification (PI) to meet upcoming demands of biotherapeutics while keeping production flexible but, more importantly, as economic as possible. However, intensified processes often require more development time compared with conventional fed‐batches (FBs) preventing their implementation. Hence, rapid and efficient, yet straightforward strategies for PI are needed. In this study we demonstrate such a strategy for the intensification of an N‐stage FB by implementing N‐1 perfusion cell culture and high inoculum cell densities resulting in a robust intensified FB (iFB). Furthermore, we show successful combination of such an iFB with the addition of productivity enhancers, which has not been reported so far. The conventional CHO cell FB process was step‐wise improved and intensified rapidly in multi‐parallel small‐scale bioreactors using N‐1 perfusion. The iFBs were performed in 15 and 250 ml bioreactors and allowed to evaluate the impact on key process indicators (KPI): the space–time yield (STY) was successfully doubled from 0.28 to 0.55 g/L d, while product quality was maintained. This gain was generated by initially increasing the inoculation density, thus shrinking process time, and second supplementation with butyric acid (BA), which reduced cell growth and enhanced cell‐specific productivity from ~25 to 37 pg/(cell d). Potential impacts of PI on cell metabolism were evaluated using flux balance analysis. Initial metabolic differences between the standard and intensified process were observed but disappeared quickly. This shows that PI can be achieved rapidly for new as well as existing processes without introducing sustained changes in cellular and metabolic behavior.

Loss of SNORA73 reprograms cellular metabolism and protects against steatohepatitis

Dyslipidemia and resulting lipotoxicity are pathologic signatures of metabolic syndrome and type 2 diabetes. Excess lipid causes cell dysfunction and induces cell death through pleiotropic mechanisms that link to oxidative stress. However, pathways that regulate the response to metabolic stress are not well understood. Herein, we show that disruption of the box H/ACA SNORA73 small nucleolar RNAs encoded within the small nucleolar RNA hosting gene 3 (Snhg3) causes resistance to lipid-induced cell death and general oxidative stress in cultured cells. This protection from metabolic stress is associated with broad reprogramming of oxidative metabolism that is dependent on the mammalian target of rapamycin signaling axis. Furthermore, we show that knockdown of SNORA73 in vivo protects against hepatic steatosis and lipid-induced oxidative stress and inflammation. Our findings demonstrate a role for SNORA73 in the regulation of metabolism and lipotoxicity.

mfapy: An open-source Python package for 13C-based metabolic flux analysis

¹³C-based metabolic flux analysis (¹³C-MFA) is an essential tool for estimating intracellular metabolic flux levels in metabolic engineering and biology. In ¹³C-MFA, a metabolic flux distribution that explains the observed isotope labeling data was computationally estimated using a non-linear optimization method. Herein, we report the development of mfapy, an open-source Python package developed for more flexibility and extensibility for ¹³C-MFA. mfapy compels users to write a customized Python code by describing each step in the data analysis procedures of the isotope labeling experiments. The flexibility and extensibility provided by mfapy can support trial-and-error performance in the routine estimation of metabolic flux distributions, experimental design by computer simulations of ¹³C-MFA experiments, and development of new data analysis techniques for stable isotope labeling experiments. mfapy is available to the public from the Github repository (https://github.com/fumiomatsuda/mfapy).

•

An open-source Python package, mfapy, is developed for ¹³C-MFA.

•

mfapy enables users to write Python codes for data analysis procedures of ¹³C-MFA.

•

mfapy has a flexibility and extensibility to support various data analysis procedures.

•

Computer simulations of ¹³C-MFA experiments is supported for experimental design.

Exometabolome profiling reveals activation of the carnitine buffering pathway in fed-batch cultures of CHO cells co-fed with glucose and lactic acid

Adjustments to CHO cell physiology were recently observed during implementation of a Raman spectroscopy-based glucose and lactate control strategy. To further understand how these cells, under monoclonal antibody (mAb) production conditions, utilized the extra lactic acid fed, we performed a comprehensive semi-quantitative and time-dependent analysis of the exometabolome. This study focused on the CHO cell's metabolic shift from the fifth day of culture. We compared relative levels of extracellular metabolites in the absence or presence of a 2 g/L lactic acid setpoint while glucose was kept at 4 g/L. Our hypothesis is that extra lactic acid would supply more pyruvate, favoring oxidative phosphorylation. We subsequentially uncovered several carnitine derivatives as biomarkers of the simultaneous activation of TCA anaplerotic pathways as well as a carbon-buffering pathway. CHO cells exhibited a balance between intermediates from (i) amino acid catabolism, (ii) fatty acid β-oxidation, and (iii) pyruvate from glycolysis and lactic acid; and the secretion of their intermediate carnitine derivatives. In addition, 3-hydroxy-methyl-glutaric acid (HMG) and mevalonate syntheses were found as biomarkers of alternative acyl group removal. Together, under a limited capacity to assimilate the surplus of acyl-CoA groups as well as an ability to maintain the acyl-CoA: free CoA ratio for proper and continuous functioning of the TCA cycle, CHO cells activate the carnitine-buffering system, HMG, and mevalonate pathways.

Redox as a bioprocess parameter: analytical redox quantification in biological therapeutic production

Engineered Chinese hamster ovary (CHO) cells are the most widely utilized cell line for protein-based therapeutics production at industrial scales. Process development strategies which improve production capacity and quality are often implemented without an understanding of underlying intracellular changes. Intracellular redox conditions drive reactions in pathways critical to biologics production, including bioenergetic and biosynthetic pathways, necessitating methods to quantify redox-related changes. Advances in methods for analytical redox quantification presented here, including bioreactor probes, redox-targeted proteomics, genetically encoded redox-sensitive fluorescent proteins, and biochemical assays, are creating new opportunities to characterize the effects of redox in biologics production. Implementing these methods will lead to enhanced media formulations, improved bioprocess strategies, and new cell line engineering targets and ultimately develop redox into an optimizable bioprocess parameter to improve the yield and quality of these lifesaving medicines.

13 C NMR of glutamate for monitoring the pentose phosphate pathway in myocardium

After administration of 13 C-labeled glucose, the activity of the pentose phosphate pathway (PPP) is often assessed by the distribution of 13 C in lactate. However, in some tissues, such as the well-oxygenated heart, the concentration of lactate may be too low for convenient analysis by NMR. Here, we examined 13 C-labeled glutamate as an alternative biomarker of the PPP in the heart. Isolated rat hearts were perfused with media containing [2,3-13 C2 ]glucose and the tissue extracts were analyzed. Metabolism of [2,3-13 C2 ]glucose yields [1,2-13 C2 ]pyruvate via glycolysis and [2,3-13 C2 ]pyruvate via the PPP. Pyruvate is in exchange with lactate or is further metabolized to glutamate through pyruvate dehydrogenase and the TCA cycle. A doublet from [4,5-13 C2 ]glutamate, indicating flux through the PPP, was readily detected in 13 C NMR of heart extracts even when the corresponding doublet from [2,3-13 C2 ]lactate was minimal. Benfotiamine, known to induce the PPP, caused an increase in production of [4,5-13 C2 ]glutamate. In rats receiving [2,3-13 C2 ]glucose, brain extracts showed well-resolved signals from both [2,3-13 C2 ]lactate and [4,5-13 C2 ]glutamate in 13 C NMR spectra. Assessment of the PPP in the brain based on glutamate had a strong linear correlation with lactate-based assessment. In summary, 13 C NMR analysis of glutamate enabled detection of the low PPP activity in isolated hearts. This analyte is an alternative to lactate for monitoring the PPP with the use of [2,3-13 C2 ]glucose.

The metabolic origins of non-photorespiratory CO2 release during photosynthesis: a metabolic flux analysis

Respiration in the light (RL) releases CO2 in photosynthesizing leaves and is a phenomenon that occurs independently from photorespiration. Since RL lowers net carbon fixation, understanding RL could help improve plant carbon-use efficiency and models of crop photosynthesis. Although RL was identified more than 75 years ago, its biochemical mechanisms remain unclear. To identify reactions contributing to RL, we mapped metabolic fluxes in photosynthesizing source leaves of the oilseed crop and model plant camelina (Camelina sativa). We performed a flux analysis using isotopic labeling patterns of central metabolites during 13CO2 labeling time course, gas exchange, and carbohydrate production rate experiments. To quantify the contributions of multiple potential CO2 sources with statistical and biological confidence, we increased the number of metabolites measured and reduced biological and technical heterogeneity by using single mature source leaves and quickly quenching metabolism by directly injecting liquid N2; we then compared the goodness-of-fit between these data and data from models with alternative metabolic network structures and constraints. Our analysis predicted that RL releases 5.2 μmol CO2 g-1 FW h-1 of CO2, which is relatively consistent with a value of 9.3 μmol CO2 g-1 FW h-1 measured by CO2 gas exchange. The results indicated that ≤10% of RL results from TCA cycle reactions, which are widely considered to dominate RL. Further analysis of the results indicated that oxidation of glucose-6-phosphate to pentose phosphate via 6-phosphogluconate (the G6P/OPP shunt) can account for >93% of CO2 released by RL.

A metabolic CRISPR-Cas9 screen in Chinese hamster ovary cells identifies glutamine-sensitive genes

Media and feed optimization have fueled many-fold improvements in mammalian biopharmaceutical production, but genome editing offers an emerging avenue for further enhancing cell metabolism and bioproduction. However, the complexity of metabolism, involving thousands of genes, makes it unclear which engineering strategies will result in desired traits. Here we present a comprehensive pooled CRISPR screen for CHO cell metabolism, including ~16,000 gRNAs against ~2500 metabolic enzymes and regulators. Using this screen, we identified a glutamine response network in CHO cells. Glutamine is particularly important since it is often over-fed to drive increased TCA cycle flux, but toxic ammonia may accumulate. With the screen we found one orphan glutamine-responsive gene with no clear connection to our network. Knockout of this novel and poorly characterized lipase, Abhd11, substantially increased growth in glutamine-free media by altering the regulation of the TCA cycle. Thus, the screen provides an invaluable targeted platform to comprehensively study genes involved in any metabolic trait, and elucidate novel regulators of metabolism.

Oxidative Pentose Phosphate Pathway Enzyme 6-Phosphogluconate Dehydrogenase Plays a Key Role in Breast Cancer Metabolism

The pentose phosphate pathway (PPP) plays an essential role in the metabolism of breast cancer cells for the management of oxidative stress and the synthesis of nucleotides. 6-phosphogluconate dehydrogenase (6PGD) is one of the key enzymes of the oxidative branch of PPP and is involved in nucleotide biosynthesis and redox maintenance status. Here, we aimed to analyze the functional importance of 6PGD in a breast cancer cell model. Inhibition of 6PGD in MCF7 reduced cell proliferation and showed a significant decrease in glucose consumption and an increase in glutamine consumption, resulting in an important alteration in the metabolism of these cells. No difference in reactive oxygen species (ROS) production levels was observed after 6PGD inhibition, indicating that 6PGD, in contrast to glucose 6-phosphate dehydrogenase, is not involved in redox balance. We found that 6PGD inhibition also altered the stem cell characteristics and mammosphere formation capabilities of MCF7 cells, opening new avenues to prevent cancer recurrance after surgery or chemotherapy. Moreover, inhibition of 6PGD via chemical inhibitor S3 resulted in an induction of senescence, which, together with the cell cycle arrest and apoptosis induction, might be orchestrated by p53 activation. Therefore, we postulate 6PGD as a novel therapeutic target to treat breast cancer.

Metabolic substrate utilization in stress-induced immune cells

Immune cell activation leads to the acquisition of new functions, such as proliferation, chemotaxis, and cytokine production. These functional changes require continuous metabolic adaption in order to sustain ATP homeostasis for sufficient host defense. The bioenergetic demands are usually met by the interconnected metabolic pathways glycolysis, TCA cycle, and oxidative phosphorylation. Apart from glucose, other sources, such as fatty acids and glutamine, are able to fuel the TCA cycle.Rising evidence has shown that cellular metabolism has a direct effect on the regulation of immune cell functions. Thus, quiescent immune cells maintain a basal metabolic state, which shifts to an accelerated metabolic level upon immune cell activation in order to promote key effector functions.This review article summarizes distinct metabolic signatures of key immune cell subsets from quiescence to activation and demonstrates a methodical concept of how to assess cellular metabolic pathways. It further discusses why metabolic functions are of rising interest for translational research and how they can be affected by the underlying pathophysiological condition and/or therapeutic interventions.

A guide to metabolic flux analysis in metabolic engineering: Methods, tools and applications

The field of metabolic engineering is primarily concerned with improving the biological production of value-added chemicals, fuels and pharmaceuticals through the design, construction and optimization of metabolic pathways, redirection of intracellular fluxes, and refinement of cellular properties relevant for industrial bioprocess implementation. Metabolic network models and metabolic fluxes are central concepts in metabolic engineering, as was emphasized in the first paper published in this journal, "Metabolic fluxes and metabolic engineering" (Metabolic Engineering, 1: 1-11, 1999). In the past two decades, a wide range of computational, analytical and experimental approaches have been developed to interrogate the capabilities of biological systems through analysis of metabolic network models using techniques such as flux balance analysis (FBA), and quantify metabolic fluxes using constrained-based modeling approaches such as metabolic flux analysis (MFA) and more advanced experimental techniques based on the use of stable-isotope tracers, i.e. ¹³C-metabolic flux analysis (¹³C-MFA). In this review, we describe the basic principles of metabolic flux analysis, discuss current best practices in flux quantification, highlight potential pitfalls and alternative approaches in the application of these tools, and give a broad overview of pragmatic applications of flux analysis in metabolic engineering practice.

Induced pluripotent stem cells can utilize lactate as a metabolic substrate to support proliferation

Human-induced pluripotent stem cells (iPSCs) hold the promise to improve cell-based therapies. Yet, to meet rising demands and become clinically impactful, sufficient high-quality iPSCs in quantity must be generated, a task that exceeds current capabilities. In this study, K3 iPSCs cultures were examined using parallel-labeling metabolic flux analysis (¹³ C-MFA) to quantify intracellular fluxes at relevant bioprocessing stages: glucose concentrations representative of initial media concentrations and high lactate concentrations representative of fed-batch culture conditions, prior to and after bolus glucose feeds. The glucose and lactate concentrations are also representative of concentrations that might be encountered at different locations within 3D cell aggregates. Furthermore, a novel method was developed to allow the isotopic tracer [U-¹³ C₃ ] lactate to be used in the ¹³ C-MFA model. The results indicated that high extracellular lactate concentrations decreased glucose consumption and lactate production, while glucose concentrations alone did not affect rates of aerobic glycolysis. Moreover, for the high lactate cultures, lactate was used as a metabolic substrate to support oxidative mitochondrial metabolism. These results demonstrate that iPSCs have metabolic flexibility and possess the capacity to metabolize lactate to support exponential growth, and that high lactate concentrations alone do not adversely impact iPSC proliferation.

Regulation of Metabolic Homeostasis in Cell Culture Bioprocesses

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

Comprehensive Isotopic Targeted Mass Spectrometry: Reliable Metabolic Flux Analysis with Broad Coverage

Metabolic flux analysis (MFA) is highly relevant to understanding metabolic mechanisms of various biological processes. While the pace of methodology development in MFA has been rapid, a major challenge the field continues to witness is limited metabolite coverage, often restricted to a small to moderate number of well-known compounds. In addition, isotopic peaks from an enriched metabolite tend to have low abundances, which makes liquid chromatography tandem mass spectrometry (LC-MS/MS) highly useful in MFA due to its high sensitivity and specificity. Previously we have built large-scale LC-MS/MS approaches that can be routinely used for measurement of up to ∼1,900 metabolite/feature levels [Gu et al. Anal. Chem. 2015, 87, 12355-12362. Shi et al. Anal. Chem. 2019, 91, 13737-13745.]. In this study, we aim to expand our previous studies focused on metabolite level measurements to flux analysis and establish a novel comprehensive isotopic targeted mass spectrometry (CIT-MS) method for reliable MFA analysis with broad coverage. As a proof-of-principle, we have applied CIT-MS to compare the steady-state enrichment of metabolites between Myc(oncogene)-On and Myc-Off Tet21N human neuroblastoma cells cultured with U-13C6-glucose medium. CIT-MS is operationalized using multiple reaction monitoring (MRM) mode and is able to perform MFA of 310 identified metabolites (142 reliably detected, 46 kinetically profiled) selected from >35 metabolic pathways of strong biological significance. Further, we developed a novel concept of relative flux, which eliminates the requirement of absolute quantitation in traditional MFA and thus enables comparative MFA under the pseudosteady state. As a result, CIT-MS was shown to possess the advantages of broad coverage, easy implementation, fast throughput, and more importantly, high fidelity and accuracy in MFA. In principle, CIT-MS can be easily adapted to track the flux of other labeled tracers (such as 15N-tracers) in any metabolite detectable by LC-MS/MS and in various biological models (such as mice). Therefore, CIT-MS has great potential to bring new insights to both basic and clinical metabolism research.

Direct and quantitative analysis of altered metabolic flux distributions and cellular ATP production pathway in fumarate hydratase-diminished cells

Fumarate hydratase (FH) is an enzyme in the tricarboxylic acid (TCA) cycle, biallelic loss-of-function mutations of which are associated with hereditary leiomyomatosis and renal cell cancer. However, how FH defect modulates intracellular metabolic fluxes in human cells has remained unclear. This study aimed to reveal metabolic flux alterations induced by reduced FH activity. We applied ¹³C metabolic flux analysis (¹³C-MFA) to an established cell line with diminished FH activity (FH^dim) and parental HEK293 cells. FH^dim cells showed reduced pyruvate import flux into mitochondria and subsequent TCA cycle fluxes. Interestingly, the diminished FH activity decreased FH flux only by about 20%, suggesting a very low need for FH to maintain the oxidative TCA cycle. Cellular ATP production from the TCA cycle was dominantly suppressed compared with that from glycolysis in FH^dim cells. Consistently, FH^dim cells exhibited higher glucose dependence for ATP production and higher resistance to an ATP synthase inhibitor. In summary, using FH^dim cells we demonstrated that FH defect led to suppressed pyruvate import into mitochondria, followed by downregulated TCA cycle activity and altered ATP production pathway balance from the TCA cycle to glycolysis. We confirmed that ¹³C-MFA can provide direct and quantitative information on metabolic alterations induced by FH defect.

Computational data mining method for isotopomer analysis in the quantitative assessment of metabolic reprogramming

Measurement of metabolic flux levels using stable isotope labeling has been successfully used to investigate metabolic redirection and reprogramming in living cells or tissues. The metabolic flux ratio between two reactions can be estimated from the ¹³C-labeling patterns of a few metabolites combined with the knowledge of atom mapping in the complicated metabolic network. However, it remains unclear whether an observed change in the labeling pattern of the metabolites is sufficient evidence of a shift in flux ratio between two metabolic states. In this study, a data analysis method was developed for the quantitative assessment of metabolic reprogramming. The Metropolis-Hastings algorithm was used with an in silico metabolic model to generate a probability distribution of metabolic flux levels under a condition in which the ¹³C-labeling pattern was observed. Reanalysis of literature data demonstrated that the developed method enables analysis of metabolic redirection using whole ¹³C-labeling pattern data. Quantitative assessment by Cohen’s effect size (d) enables a more detailed read-out of metabolic reprogramming information. The developed method will enable future applications of the metabolic isotopomer analysis to various targets, including cultured cells, whole tissues, and organs.

Software Supporting a Workflow of Quantitative Dynamic Flux Maps Estimation in Central Metabolism from SIRM Experimental Data

Stable isotope-resolved metabolomics (SIRM), based on the analysis of biological samples from living cells incubated with artificial isotope enriched substrates, enables mapping the rates of biochemical reactions (metabolic fluxes). We developed software supporting a workflow of analysis of SIRM data obtained with mass spectrometry (MS). The evaluation of fluxes starting from raw MS recordings requires at least three steps of computer support: first, extraction of mass spectra of metabolites of interest, then correction of the spectra for natural isotope abundance, and finally, evaluation of fluxes by simulation of the corrected spectra using a corresponding mathematical model. A kinetic model based on ordinary differential equations (ODEs) for isotopomers of metabolites of the corresponding biochemical network supports the final part of the analysis, which provides a dynamic flux map.

BCAT1 and BCAT2 disruption in CHO cells has cell line-dependent effects

In recombinant protein expression using Chinese hamster ovary (CHO) cells, chemically defined media contain essential amino acids such as branched chain amino acids (BCAAs) leucine, isoleucine and valine. Availability of amino acids is critical as these are building blocks for protein synthesis. However, breakdown of amino acids can lead to build up of toxic intermediates and metabolites that decrease cell growth, productivity and product quality. BCAA catabolism also hampers the usage of BCAAs for protein synthesis. In this work we studied the effects of disrupting the genes responsible for the first step of BCAA catabolism: branched chain aminotransferase 1 (Bcat1) and branched chain aminotransferase 2 (Bcat2). We evaluated the effect of disrupting the genes individually and in combination, and examined the effects in producer and non-producer host cells. Our experiments show that Bcat1 disruption improves cell growth in producer cells, but not in non-producers. Conversely, Bcat2 has a minor negative effect on growth in producer cells, and none in non-producers. Combined Bcat1 and Bcat2 disruption improves growth in producer cells. By-product metabolism is cell line-, clone- and producer-dependent. Overall, our results show that the effects of targeting Bcat1 and/or Bcat2 are cell line-dependent, and seemingly linked to the burden of recombinant protein expression.

Metabolic flux ratio analysis by parallel 13C labeling of isoprenoid biosynthesis in Rhodobacter sphaeroides

Metabolic engineering for increased isoprenoid production often benefits from the simultaneous expression of the two naturally available isoprenoid metabolic routes, namely the 2-methyl-D-erythritol 4-phosphate (MEP) pathway and the mevalonate (MVA) pathway. Quantification of the contribution of these pathways to the overall isoprenoid production can help to obtain a better understanding of the metabolism within a microbial cell factory. Such type of investigation can benefit from ¹³C metabolic flux ratio studies. Here, we designed a method based on parallel labeling experiments (PLEs), using [1-¹³C]- and [4-¹³C]glucose as tracers to quantify the metabolic flux ratios in the glycolytic and isoprenoid pathways. By just analyzing a reporter isoprenoid molecule and employing only four equations, we could describe the metabolism involved from substrate catabolism to product formation. These equations infer ¹³C atom incorporation into the universal isoprenoid building blocks, isopentenyl-pyrophosphate (IPP) and dimethylallyl-pyrophosphate (DMAPP). Therefore, this renders the method applicable to the study of any of isoprenoid of interest. As proof of principle, we applied it to study amorpha-4,11-diene biosynthesis in the bacterium Rhodobacter sphaeroides. We confirmed that in this species the Entner-Doudoroff pathway is the major pathway for glucose catabolism, while the Embden-Meyerhof-Parnas pathway contributes to a lesser extent. Additionally, we demonstrated that co-expression of the MEP and MVA pathways caused a mutual enhancement of their metabolic flux capacity. Surprisingly, we also observed that the isoprenoid flux ratio remains constant under exponential growth conditions, independently from the expression level of the MVA pathway. Apart from proposing and applying a tool for studying isoprenoid biosynthesis within a microbial cell factory, our work reveals important insights from the co-expression of MEP and MVA pathways, including the existence of a yet unclear interaction between them.

Metformin attenuates hepatoma cell proliferation by decreasing glycolytic flux through the HIF-1α/PFKFB3/PFK1 pathway

AIMS

Enhanced aerobic glycolysis is an essential hallmark of malignant cancer. Blocking the glycolytic pathway has been suggested as a therapeutic strategy to impair the proliferation of tumor cells. Metformin, a widely used anti-diabetes drug, exhibits anti-tumor properties. However, the underlying molecular mechanism of its action linking glucose metabolism with the suppression of proliferation has not been fully clarified.

MAIN METHODS

Stable isotope tracing technology and gas chromatography-mass spectrometry method were utilized to analyze the effect of metformin on glycolytic flux in HCC cells. Western blot and immunohistochemistry were utilized to analyze the expression of phosphofructokinase-1 (PFK1) and 6-phosphofructo-2-kinase/fructose-2,6-biphosphatase 3 (PFKFB3) in HCC cells or xenograft tumor tissues. Lactate measurement and glucose uptake assay were used to analyze the level of lactate and glucose in the presence of frucose-2,6-diphosphate (F2,6BP) in HCC cells treated with metformin.

KEY FINDINGS

We found that metformin significantly impaired hepatoma cell proliferation by inhibiting the glycolytic flux via PFK1 blockade. Interestingly, activation of PFK1 by F2,6BP reverses the inhibitory effect of metformin on hepatoma cell proliferation and glycolysis. Mechanistically, PFKFB3，a potent allosteric activator of PFK1, was markedly suppressed through inhibiting hypoxia-induced factor 1 (HIF-1α) accumulation mediated by metformin.

SIGNIFICANCE

Taken together these data indicate that HIF-1α/PFKFB3/PFK1 regulatory axis is a vital determinant of glucose metabolic reprogramming in hepatocellular carcinoma, which gives new insights into the action of metformin in combatting liver cancer.

An unconventional uptake rate objective function approach enhances applicability of genome-scale models for mammalian cells

Constraint-based modeling has been applied to analyze metabolism of numerous organisms via flux balance analysis and genome-scale metabolic models, including mammalian cells such as the Chinese hamster ovary (CHO) cells-the principal cell factory platform for therapeutic protein production. Unfortunately, the application of genome-scale model methodologies using the conventional biomass objective function is challenged by the presence of overly-restrictive constraints, including essential amino acid exchange fluxes that can lead to improper predictions of growth rates and intracellular flux distributions. In this study, these constraints are found to be reliably predicted by an "essential nutrient minimization" approach. After modifying these constraints with the predicted minimal uptake values, a series of unconventional objective functions are applied to minimize each individual non-essential nutrient uptake rate, revealing useful insights about metabolic exchange rates and flows across different cell lines and culture conditions. This unconventional uptake-rate objective functions (UOFs) approach is able to distinguish metabolic differences between three distinct CHO cell lines (CHO-K1, -DG44, and -S) not directly observed using the conventional biomass growth maximization solutions. Further, a comparison of model predictions with experimental data from literature correctly correlates with the specific CHO-DG44-derived cell line used experimentally, and the corresponding dual prices provide fruitful information concerning coupling relationships between nutrients. The UOFs approach is likely to be particularly suited for mammalian cells and other complex organisms which contain multiple distinct essential nutrient inputs, and may offer enhanced applicability for characterizing cell metabolism and physiology as well as media optimization and biomanufacturing control.

High extracellular lactate causes reductive carboxylation in breast tissue cell lines grown under normoxic conditions

In cancer tumors, lactate accumulation was initially attributed to high glucose consumption associated with the Warburg Effect. Now it is evident that lactate can also serve as an energy source in cancer cell metabolism. Additionally, lactate has been shown to promote metastasis, generate gene expression patterns in cancer cells consistent with "cancer stem cell" phenotypes, and result in treatment resistant tumors. Therefore, the goal of this work was to quantify the impact of lactate on metabolism in three breast cell lines (one normal and two breast cancer cell lines-MCF 10A, MCF7, and MDA-MB-231), in order to better understand the role lactate may have in different disease cell types. Parallel labeling metabolic flux analysis (13C-MFA) was used to quantify the intracellular fluxes under normal and high extracellular lactate culture conditions. Additionally, high extracellular lactate cultures were labelled in parallel with [U-13C] lactate, which provided qualitative information regarding the lactate uptake and metabolism. The 13C-MFA model, which incorporated the measured extracellular fluxes and the parallel labeling mass isotopomer distributions (MIDs) for five glycolysis, four tricarboxylic acid cycle (TCA), and three intracellular amino acid metabolites, predicted lower glycolysis fluxes in the high lactate cultures. All three cell lines experienced reductive carboxylation of glutamine to citrate in the TCA cycle as a result of high extracellular lactate. Reductive carboxylation previously has been observed under hypoxia and other mitochondrial stresses, whereas these cultures were grown aerobically. In addition, this is the first study to investigate the intracellular metabolic responses of different stages of breast cancer progression to high lactate exposure. These results provide insight into the role lactate accumulation has on metabolic reaction distributions in the different disease cell types while the cells are still proliferating in lactate concentrations that do not significantly decrease exponential growth rates.

Accelerating Biologics Manufacturing by Upstream Process Modelling

Intensified and accelerated development processes are being demanded by the market, as innovative biopharmaceuticals such as virus-like particles, exosomes, cell and gene therapy, as well as recombinant proteins and peptides will possess no available platform approach. Therefore, methods that are able to accelerate this development are preferred. Especially, physicochemical rigorous process models, based on all relevant effects of fluid dynamics, phase equilibrium, and mass transfer, can be predictive, if the model is verified and distinctly quantitatively validated. In this approach, a macroscopic kinetic model based on Monod kinetics for mammalian cell cultivation is developed and verified according to a general valid model validation workflow. The macroscopic model is verified and validated on the basis of four decision criteria (plausibility, sensitivity, accuracy and precision as well as equality). The process model workflow is subjected to a case study, comprising a Chinese hamster ovary fed-batch cultivation for the production of a monoclonal antibody. By performing the workflow, it was found that, based on design of experiments and Monte Carlo simulation, the maximum growth rate µmax exhibited the greatest influence on model variables such as viable cell concentration XV and product concentration. In addition, partial least squares regressions statistically evaluate the correlations between a higher µmax and a higher cell and product concentration, as well as a higher substrate consumption.

Differential gene expression of a feed-spiked super-producing CHO cell line

Feed supplements are concentrated cell culture media that contain a variety of nutrients, which can be added during a bioprocess. During fed-batch cultivation, feed media are typically added to a growing cell culture to maximize cell and product concentrations. In this study, only a single shot of feed medium was added on day 0 to a basal cell culture medium and compared to non-supplemented basal medium (feed-spiked at day 0 versus control experiments) by cultivation of a recombinant mAb expressing CHO cell line in batch mode under controlled conditions in a bioreactor. Since the feed-spike at day 0 was based on existing medium components without introducing additional supplements, a desirable process with decreased complexity was generated. Unlike cells in basal medium, feed-spiked cultures reached almost 2× higher peak cell concentrations (10 × 10⁶ c/mL vs. 18 × 10⁶ c/mL) and 3× higher antibody concentrations (0.8 g/L vs. 2.4 g/L). Batch process time and the integral over the viable cell count were similar for both process types. Constantly high cell-specific production rates in feed-spiked cultures (70 pg/cell/day) compared to continuously declining rates in basal medium (from 70 to 10 pg/cell/day) were responsible for an overall 70% higher cell-specific production rate and the higher product concentrations. To associate gene expression patterns to different process proceedings, transcriptome analysis was performed using microarrays. Several transcripts that are involved with glutamine de novo synthesis and citric acid cycle were significantly upregulated on several days in feed-spiked cultures. The top identified gene ontology (GO) terms related well to cell cycle and primary metabolism, cellular division as well as nucleobase formation or regulation, which indicated a more active proliferative state for feed-spiked cultures. KEGG biochemical pathway analysis and Gene set enrichment analysis (GSEA) further confirmed these findings from a complementary perspective. Moreover, several interesting gene targets, which have not yet been associated with recombinant protein expression, were identified that related to a higher proliferative state, growth, protein synthesis, cell-size control, metabolism, cell survival as well as genes that are associated with the control of the mammalian target of rapamycin (mTOR) in feed-spiked cultures. Analysis of critical product quality attributes (i.e. glycosylation, charge variants and size distribution) showed that feed-spiking did not change antibody quality.

Metabolic Flexibility as an Adaptation to Energy Resources and Requirements in Health and Disease

The ability to efficiently adapt metabolism by substrate sensing, trafficking, storage, and utilization, dependent on availability and requirement, is known as metabolic flexibility. In this review, we discuss the breadth and depth of metabolic flexibility and its impact on health and disease. Metabolic flexibility is essential to maintain energy homeostasis in times of either caloric excess or caloric restriction, and in times of either low or high energy demand, such as during exercise. The liver, adipose tissue, and muscle govern systemic metabolic flexibility and manage nutrient sensing, uptake, transport, storage, and expenditure by communication via endocrine cues. At a molecular level, metabolic flexibility relies on the configuration of metabolic pathways, which are regulated by key metabolic enzymes and transcription factors, many of which interact closely with the mitochondria. Disrupted metabolic flexibility, or metabolic inflexibility, however, is associated with many pathological conditions including metabolic syndrome, type 2 diabetes mellitus, and cancer. Multiple factors such as dietary composition and feeding frequency, exercise training, and use of pharmacological compounds, influence metabolic flexibility and will be discussed here. Last, we outline important advances in metabolic flexibility research and discuss medical horizons and translational aspects.

Mass Spectrometry-Based Method to Study Inhibitor-Induced Metabolic Redirection in the Central Metabolism of Cancer Cells

Cancer cells often respond to chemotherapeutic inhibitors by redirecting carbon flow in the central metabolism. To understand the metabolic redirections of inhibitor treatment on cancer cells, this study established a 13C-metabolic flux analysis (13C-MFA)-based method to evaluate metabolic redirection in MCF-7 breast cancer cells using mass spectrometry. A metabolic stationary state necessary for accurate 13C-MFA was confirmed during an 8-24 h window using low-dose treatments of various metabolic inhibitors. Further 13C-labeling experiments using [1-13C]glucose and [U-13C]glutamine, combined with gas chromatography-mass spectrometry (GC-MS) analysis of mass isotopomer distributions (MIDs), confirmed that an isotopic stationary state of intracellular metabolites was reached 24 h after treatment with paclitaxel (Taxol), an inhibitor of mitosis used for cancer treatment. Based on these metabolic and isotopic stationary states, metabolic flux distribution in the central metabolism of paclitaxel-treated MCF-7 cells was determined by 13C-MFA. Finally, estimations of the 95% confidence intervals showed that tricarboxylic acid cycle metabolic flux increased after paclitaxel treatment. Conversely, anaerobic glycolysis metabolic flux decreased, revealing metabolic redirections by paclitaxel inhibition. The gap between total regeneration and consumption of ATP in paclitaxel-treated cells was also found to be 1.2 times greater than controls, suggesting ATP demand was increased by paclitaxel treatment, likely due to increased microtubule polymerization. These data confirm that 13C-MFA can be used to investigate inhibitor-induced metabolic redirection in cancer cells. This will contribute to future pharmaceutical developments and understanding variable patient response to treatment.