A theoretical estimate for nucleotide sugar demand towards Chinese Hamster Ovary cellular glycosylation

Challenges of Spatially Resolved Metabolism in Cancer Research

Stable isotope-resolved metabolomics comprises a critical set of technologies that can be applied to a wide variety of systems, from isolated cells to whole organisms, to define metabolic pathway usage and responses to perturbations such as drugs or mutations, as well as providing the basis for flux analysis. As the diversity of stable isotope-enriched compounds is very high, and with newer approaches to multiplexing, the coverage of metabolism is now very extensive. However, as the complexity of the model increases, including more kinds of interacting cell types and interorgan communication, the analytical complexity also increases. Further, as studies move further into spatially resolved biology, new technical problems have to be overcome owing to the small number of analytes present in the confines of a single cell or cell compartment. Here, we review the overall goals and solutions made possible by stable isotope tracing and their applications to models of increasing complexity. Finally, we discuss progress and outstanding difficulties in high-resolution spatially resolved tracer-based metabolic studies.

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

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

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.

Enzyme cascades for the synthesis of nucleotide sugars: Updates to recent production strategies

Nucleotide sugars play an elementary role in nature as building blocks of glycans, polysaccharides, and glycoconjugates used in the pharmaceutical, cosmetics, and food industries. As substrates of Leloir-glycosyltransferases, nucleotide sugars are essential for chemoenzymatic in vitro syntheses. However, high costs and the limited availability of nucleotide sugars prevent applications of biocatalytic cascades on a large industrial scale. Therefore, the focus is increasingly on nucleotide sugar synthesis strategies to make significant application processes feasible. The chemical synthesis of nucleotide sugars and their derivatives is well established, but the yields of these processes are usually low. Enzyme catalysis offers a suitable alternative here, and in the last 30 years, many synthesis routes for nucleotide sugars have been discovered and used for production. However, many of the published procedures shy away from assessing the practicability of their processes. With this review, we give an insight into the development of the (chemo)enzymatic nucleotide sugar synthesis pathways of the last years and present an assessment of critical process parameters such as total turnover number (TTN), space-time yield (STY), and enzyme loading.

Enhanced metabolism and negative regulation of ER stress support higher erythropoietin production in HEK293 cells

Recombinant protein production can cause severe stress on cellular metabolism, resulting in limited titer and product quality. To investigate cellular and metabolic characteristics associated with these limitations, we compare HEK293 clones producing either erythropoietin (EPO) (secretory) or GFP (non-secretory) protein at different rates. Transcriptomic and functional analyses indicate significantly higher metabolism and oxidative phosphorylation in EPO producers compared with parental and GFP cells. In addition, ribosomal genes exhibit specific expression patterns depending on the recombinant protein and the production rate. In a clone displaying a dramatically increased EPO secretion, we detect higher gene expression related to negative regulation of endoplasmic reticulum (ER) stress, including upregulation of ATF6B, which aids EPO production in a subset of clones by overexpression or small interfering RNA (siRNA) knockdown. Our results offer potential target pathways and genes for further development of the secretory power in mammalian cell factories.

Strategies for Glycoengineering Therapeutic Proteins

Almost all therapeutic proteins are glycosylated, with the carbohydrate component playing a long-established, substantial role in the safety and pharmacokinetic properties of this dominant category of drugs. In the past few years and moving forward, glycosylation is increasingly being implicated in the pharmacodynamics and therapeutic efficacy of therapeutic proteins. This article provides illustrative examples of drugs that have already been improved through glycoengineering including cytokines exemplified by erythropoietin (EPO), enzymes (ectonucleotide pyrophosphatase 1, ENPP1), and IgG antibodies (e.g., afucosylated Gazyva^®, Poteligeo^®, Fasenra™, and Uplizna^®). In the future, the deliberate modification of therapeutic protein glycosylation will become more prevalent as glycoengineering strategies, including sophisticated computer-aided tools for “building in” glycans sites, acceptance of a broad range of production systems with various glycosylation capabilities, and supplementation methods for introducing non-natural metabolites into glycosylation pathways further develop and become more accessible.

A versatile design platform for glycoengineering therapeutic antibodies

Manipulation of glycosylation patterns, i.e., glycoengineering, is incorporated in the therapeutic antibody development workflow to ensure clinical safety, and this approach has also been used to modulate the biological activities, functions, or pharmacological properties of antibody drugs. Whereas most existing glycoengineering strategies focus on the canonical glycans found in the constant domain of immunoglobulin G (IgG) antibodies, we report a new strategy to leverage the untapped potential of atypical glycosylation patterns in the variable domains, which naturally occur in 15% to 25% of IgG antibodies. Glycosylation sites were added to the antigen-binding regions of two functionally divergent, interleukin-2-binding monoclonal antibodies. We used computational tools to rationally install various N-glycosylation consensus sequences into the antibody variable domains, creating "glycovariants" of these molecules. Strikingly, almost all the glycovariants were successfully glycosylated at their newly installed N-glycan sites, without reduction of the antibody's native function. Importantly, certain glycovariants exhibited modified activities compared to the parent antibody, showing the potential of our glycoengineering strategy to modulate biological function of antibodies involved in multi-component receptor systems. Finally, when coupled with a high-flux sialic acid precursor, a glycovariant with two installed glycosylation sites demonstrated superior in vivo half-life. Collectively, these findings validate a versatile glycoengineering strategy that introduces atypical glycosylation into therapeutic antibodies in order to improve their efficacy and, in certain instances, modulate their activity early in the drug development process.

Using MVDA with stoichiometric balances to optimize amino acid concentrations in chemically defined CHO cell culture medium for improved culture performance

Chemically defined (CD) media are routinely used in the production of biologics in Chinese hamster ovary (CHO) cell culture and provide enhanced raw material control. Nutrient optimized CD media is an important path to increase cell growth and monoclonal antibody (mAb) productivity in recombinant CHO cell lines. However, nutrient optimization efforts for CD media typically rely on multifactorial and experimental design of experiment approaches or complex mathematical models of cellular metabolism or gene expression systems. Moreover, the majority of these efforts are aimed at amino acids since they constitute essential nutrients in CD media as they directly contribute to biomass and protein production. In this study, we demonstrate the utilization of multivariate data analytics (MVDA) coupled with amino acid stoichiometric balances (SBs) to increased cell growth and mAb productivity in efforts to support CD media development efforts. SBs measure the difference between theoretical demand of amino acids and the empirically measured fluxes to identify various catabolic or anabolic states of the cell. When coupled with MVDA, the statistical models were not only able to highlight key amino acids toward cell growth or productivity, but also provided direction on metabolic favorability of the amino acid. Experimental validation of our approach resulted in a 55% increase in total cell growth and about an 80% increase in total mAb productivity. Increased specific consumption of stoichiometrically balanced amino acids and decreased specific consumption of glucose was also observed in optimized CD media suggesting favorable consumption of desired nutrients and a potential for energy redistribution toward increased cellular growth and mAb productivity.

Big-Data Glycomics: Tools to Connect Glycan Biosynthesis to Extracellular Communication

Characteristically, cells must sense and respond to environmental cues. Despite the importance of cell-cell communication, our understanding remains limited and often lacks glycans. Glycans decorate proteins and cell membranes at the cell-environment interface, and modulate intercellular communication, from development to pathogenesis. Providing further challenges, glycan biosynthesis and cellular behavior are co-regulating systems. Here, we discuss how glycosylation contributes to extracellular responses and signaling. We further organize approaches for disentangling the roles of glycans in multicellular interactions using newly available datasets and tools, including glycan biosynthesis models, omics datasets, and systems-level analyses. Thus, emerging tools in big data analytics and systems biology are facilitating novel insights on glycans and their relationship with multicellular behavior.

A consensus-based and readable extension of Linear Code for Reaction Rules (LiCoRR)

Systems glycobiology aims to provide models and analysis tools that account for the biosynthesis, regulation, and interactions with glycoconjugates. To facilitate these methods, there is a need for a clear glycan representation accessible to both computers and humans. Linear Code, a linearized and readily parsable glycan structure representation, is such a language. For this reason, Linear Code was adapted to represent reaction rules, but the syntax has drifted from its original description to accommodate new and originally unforeseen challenges. Here, we delineate the consensuses and inconsistencies that have arisen through this adaptation. We recommend options for a consensus-based extension of Linear Code that can be used for reaction rule specification going forward. Through this extension and specification of Linear Code to reaction rules, we aim to minimize inconsistent symbology thereby making glycan database queries easier. With a clear guide for generating reaction rule descriptions, glycan synthesis models will be more interoperable and reproducible thereby moving glycoinformatics closer to compliance with FAIR standards. Here, we present Linear Code for Reaction Rules (LiCoRR), version 1.0, an unambiguous representation for describing glycosylation reactions in both literature and code.

N-Glycosylation of IgG and IgG-Like Recombinant Therapeutic Proteins: Why Is It Important and How Can We Control It?

Regulatory bodies worldwide consider N-glycosylation to be a critical quality attribute for immunoglobulin G (IgG) and IgG-like therapeutics. This consideration is due to the importance of posttranslational modifications in determining the efficacy, safety, and pharmacokinetic properties of biologics. Given its critical role in protein therapeutic production, we review N-glycosylation beginning with an overview of the myriad interactions of N-glycans with other biological factors. We examine the mechanism and drivers for N-glycosylation during biotherapeutic production and the several competing factors that impact glycan formation, including the abundance of precursor nucleotide sugars, transporters, glycosidases, glycosyltransferases, and process conditions. We explore the role of these factors with a focus on the analytical approaches used to characterize glycosylation and associated processes, followed by the current state of advanced glycosylation modeling techniques. This combination of disciplines allows for a deeper understanding of N-glycosylation and will lead to more rational glycan control.

A high-resolution measurement of nucleotide sugars by using ion-pair reverse chromatography and tandem columns

N-Linked glycosylation is a cellular process transferring sugars from glycosyl donors to proteins or lipids. Biopharmaceutical products widely produced by culturing mammalian cells such as Chinese hamster ovary (CHO) cells are typically glycosylated during biosynthesis. For some biologics, the N-linked glycan is a critical quality attribute of the drugs. Nucleotide sugars are the glycan donors and impact the intracellular glycosylation process. In current analytical methods, robust separation of nucleotide sugar isomers such as UDP glucose and UDP galactose remains a challenge because of their structural similarity. In this study, we developed a strategy to resolve the separation of major nucleotide sugars including challenging isomers based on the use of ion-pair reverse phase (IP-RP) chromatography. The strategy applies core-shell columns and connects multiple columns in tandem to increase separation power and ultimately enables high-resolution detection of nucleotide sugars from cell extracts. The key parameters in the IP-RP method, including temperature, mobile phase, and flow rates, have been systematically evaluated in this work and the theoretical mechanisms of the chromatographic behavior were proposed. Graphical abstract.

Genome-scale reconstructions of the mammalian secretory pathway predict metabolic costs and limitations of protein secretion

In mammalian cells, >25% of synthesized proteins are exported through the secretory pathway. The pathway complexity, however, obfuscates its impact on the secretion of different proteins. Unraveling its impact on diverse proteins is particularly important for biopharmaceutical production. Here we delineate the core secretory pathway functions and integrate them with genome-scale metabolic reconstructions of human, mouse, and Chinese hamster ovary cells. The resulting reconstructions enable the computation of energetic costs and machinery demands of each secreted protein. By integrating additional omics data, we find that highly secretory cells have adapted to reduce expression and secretion of other expensive host cell proteins. Furthermore, we predict metabolic costs and maximum productivities of biotherapeutic proteins and identify protein features that most significantly impact protein secretion. Finally, the model successfully predicts the increase in secretion of a monoclonal antibody after silencing a highly expressed selection marker. This work represents a knowledgebase of the mammalian secretory pathway that serves as a novel tool for systems biotechnology.

Model-based optimization of antibody galactosylation in CHO cell culture

Exerting control over the glycan moieties of antibody therapeutics is highly desirable from a product safety and batch-to-batch consistency perspective. Strategies to improve antibody productivity may compromise quality, while interventions for improving glycoform distribution can adversely affect cell growth and productivity. Process design therefore needs to consider the trade-off between preserving cellular health and productivity while enhancing antibody quality. In this work, we present a modeling platform that quantifies the impact of glycosylation precursor feeding - specifically that of galactose and uridine - on cellular growth, metabolism as well as antibody productivity and glycoform distribution. The platform has been parameterized using an initial training data set yielding an accuracy of ±5% with respect to glycoform distribution. It was then used to design an optimized feeding strategy that enhances the final concentration of galactosylated antibody in the supernatant by over 90% compared with the control without compromising the integral of viable cell density or final antibody titer. This work supports the implementation of Quality by Design towards higher-performing bioprocesses.

Glycosylation Flux Analysis of Immunoglobulin G in Chinese Hamster Ovary Perfusion Cell Culture

The terminal sugar molecules of the N-linked glycan attached to the fragment crystalizable (Fc) region is a critical quality attribute of therapeutic monoclonal antibodies (mAbs) such as immunoglobulin G (IgG). There exists naturally-occurring heterogeneity in the N-linked glycan structure of mAbs, and such heterogeneity has a significant influence on the clinical safety and efficacy of mAb drugs. We previously proposed a constraint-based modeling method called glycosylation flux analysis (GFA) to characterize the rates (fluxes) of intracellular glycosylation reactions. One contribution of this work is a significant improvement in the computational efficiency of the GFA, which is beneficial for analyzing large datasets. Another contribution of our study is the analysis of IgG glycosylation in continuous perfusion Chinese Hamster Ovary (CHO) cell cultures. The GFA of the perfusion cell culture data indicated that the dynamical changes of IgG glycan heterogeneity are mostly attributed to alterations in the galactosylation flux activity. By using a random forest regression analysis of the IgG galactosylation flux activity, we were further able to link the dynamics of galactosylation with two process parameters: cell-specific productivity of IgG and extracellular ammonia concentration. The characteristics of IgG galactosylation dynamics agree well with what we previously reported for fed-batch cultivations of the same CHO cell strain.

Physiological responses of Chinese hamster ovary cells to a productivity-enhancing yeast extract

Hydrolysates play important roles in enhancing the productivity of recombinant proteins in mammalian cell cultures. Lacking of detailed understanding of the mechanisms, hydrolysate is commonly regarded as an unstable factor which should be used with cautions. A yeast extract (YE) was approved to improve the Fc-fusion protein productivity in a recombinant Chinese hamster ovary (CHO) cell line. To elucidate the responses of cells to hydrolysates, we further elaborate their physiological changes during the processes in the presence and absence of YE. Firstly, cell sizes and the cellular components including dry cell weight, cellular fatty acid, and total cellular protein were increased in the presence of YE. Then, by comparing the extracellular and intracellular concentrations of the main metabolites and their consumption rates, we excluded the possibility of nutrient depletion in the absence of YE and observed a distinct improvement on the net consumption rates of metabolites in the presence of YE. Furthermore, the increase on the contents of intracellular nucleotides illustrated an abundance of the nucleic acid precursors and energy charge for recombinant protein synthesis in the presence of YE. In conclusion, this study systematically elucidated YE enhanced cell mass and capacity, activated substrate and energy metabolism of cells in addition to a boost in product synthesis process. The findings provide valuable information for process optimization and cell engineering.

Influence of protein/glycan interaction on site-specific glycan heterogeneity

To study how the interaction between N-linked glycans and the surrounding amino acids influences oligosaccharide processing, we used protein disulfide isomerase (PDI), a glycoprotein bearing 5 N-glycosylation sites, as a model system and expressed it transiently in a Chinese hamster ovary (CHO)-S cell line. PDI was produced as both secreted Sec-PDI and endoplasmic reticulum-retained glycoprotein (ER)-PDI, to study glycan processing by ER and Golgi resident enzymes. Quantitative site-specific glycosylation profiles were obtained, and flux analysis enabled modeling site-specific glycan processing. By altering the primary sequence of PDI, we changed the glycan/protein interaction and thus the site-specific glycoprofile because of the improved enzymatic fluxes at enzymatic bottlenecks. Our results highlight the importance of direct interactions between N-glycans and surface-exposed amino acids of glycoproteins on processing in the ER and the Golgi and the possibility of changing a site-specific N-glycan profile by modulating such interactions and thus the associated enzymatic fluxes. Altering the primary protein sequence can therefore be used to glycoengineer recombinant proteins.-Losfeld, M.-E., Scibona, E., Lin, C.-W., Villiger, T. K., Gauss, R., Morbidelli, M., Aebi, M. Influence of protein/glycan interaction on site-specific glycan heterogeneity.

What can mathematical modelling say about CHO metabolism and protein glycosylation?

Chinese hamster ovary cells have been in the spotlight for process optimization in recent years, due to being the major, long established cell factory for the production of recombinant proteins. A deep, quantitative understanding of CHO metabolism and mechanisms involved in protein glycosylation has proven to be attainable through the development of high throughput technologies. Here we review the most notable accomplishments in the field of modelling CHO metabolism and protein glycosylation.